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Lean blowout detection for bluff-body stabilized flame
Fuel 266 (2020) 117008
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Full Length Article
Lean blowout detection for bluff-body stabilized flame a
a
Liuyong Chang , Zhang Cao , Bo Fu
a,b
c
, Yuzhen Lin , Lijun Xu
a,⁎
T
a
School of Instrumentation and Opto-Electronic Engineering, Beihang University, Beijing 100191, China BUAA-CCMU Advanced Innovation Center For Big Data-based Precision Medicine, Interdisciplinary Innovation Institute of Medicine and Engineering, Beihang University, Beijing 100191, China c School of Energy and Power Engineering, Beihang University, Beijing 100191, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Bluff-body stabilized flame Flame fluctuation Lean blowout detection Ion current signal CH* detector
The present work proposed an index to extend the previous lean blowout detection method to bluff-body stabilized flame at the condition of low Reynolds number. Dynamic characteristics near lean blowout of low Reynolds number bluff-body flame are not exactly same with that of high Reynolds number bluff-body flame. Thus lean blowout detection index requires modification for low Reynolds number bluff-body flame. The flame images show that, for a fixed fuel flow, increase of air flow to a certain value can cause flame liftoff-reattachment events, and further increase of air flow can lead to complete liftoff and even lean blowout. Temporal and spectral analyses of the ion current and CH* signals exhibit that both standard deviation and low frequency energy within 0.2–10 Hz of each signal first increase due to flame liftoff-reattachment and then decrease due to complete flame liftoff with the increase of air flow. This leads to that the lean blowout detection indexes including the normalized root mean square (NRMS), normalized cumulative duration (θ) and fraction of the fast Fourier transform (FFT) power at low-frequencies (FFT%[0 − f1 Hz]) first increase and then decrease with the increase of air flow. As a result, the flame at the liftoff state may be wrongly classified as stable state. To avoid this, the histogram distributions of two signals were investigated. The number of small value sample points of each signal increases with increase of air flow, indicating that the percentage of small value sample points can be used to detect lean blowout. The mean value of each signal at the liftoff-reattachment state is used as the threshold value to classify small value sample points. For either the ion current signal or CH* signal, percentage of sample points below the corresponding threshold value (P k< ) is used to detect lean blowout. The flame is considered as close to lean blowout when P k< reaches 50%. Experimental results show that P k< can be used for reliable detection of lean blowout for bluff-body stabilized flame at the condition of low Reynolds number.
1. Introduction Bluff-body flame holder has been widely used in practical applications, e.g., gas turbine combustor, scramjet combustor and industrial furnaces [1]. Bluff-body creates a recirculation zone for anchoring the flame. The hot burnt mixture is recirculated into this zone and continuously ignites incoming mixtures, acting as a heat source [2–4]. Besides, bluff-body flame holder is also widely used in Reynolds number combustors such as gas stove [5]. With the increasing attention to environmental protection, indoor air pollution has attracted great concern [6]. Lean combustion was widely adopted to reduce NOX emissions by reducing the flame temperature [7,8]. However, lean combustion is susceptible to lean blowout and bluff-body flame holder is used to ensure the combustion stable at fuel-lean condition. In recent years, low Reynolds number bluff-body flame has received extensive
⁎
concerns. Berger et al. experimentally studied the impact of wall temperature on flame stabilization for low Reynolds number bluff-body flame [9]. Kedia and Ghoniem numerically researched the blow-off and anchoring mechanism of a low Reynolds number bluff-body flame [10,11]. Lean blowout can cause serious problems for combustors and should be avoided. However, lean blowout limit is uncertain and varies with the change of operating parameters, such as fuel compositions, environment temperature and combustor age [12]. NOX production can be reduced and burner lifetime can be increased by operating in a narrower safety margin, which needs accurate detection of lean blowout. A lot of studies have been done in lean blowout detection. In 2002, Muruganandam et al. used the number of local extinction and reignition events in 33 s and the fraction of the total energy in low frequencies (10–200 Hz) to predict lean blowout [13]. In this work,
Corresponding author. E-mail address: [email protected] (L. Xu).
https://doi.org/10.1016/j.fuel.2020.117008 Received 25 September 2019; Received in revised form 13 December 2019; Accepted 2 January 2020 0016-2361/ © 2020 Elsevier Ltd. All rights reserved.
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they used one-quarter of the mean signal value as the threshold to identify the local extinction and reignition events [13]. In 2003, they proposed using double thresholds to identify the local extinction and reignition events [14]. The event starts as the signal drops below onequarter of the mean signal value, and ends when the signal goes above 0.3 times of the mean signal value [14]. In 2004, they extended their work to non-premixed, liquid-fueled combustors [15]. They used 50% of mean signal value as the lower threshold and two times of the standard deviation of the signal above the lower threshold as the upper threshold [15]. In 2005, they used the number of local extinction events per second [16] and the fraction of power in low-frequencies [17] to detect and further control lean blowout. In 2007, Yi and Gutmark studied proposed the normalized cumulative duration (θ) based on the method of Muruganandam et al. to predict the occurrence of lean blowout [18]. Li et al. investigated the swirl flame close to lean blowout using a tunable diode laser, and they found that the fraction of the fast Fourier transform (FFT) power at low-frequencies (FFT%[0 − f1 Hz]) increases exponentially as the flame approaches lean blowout [19]. In 2015, Mahesh and Mishra investigated the inverse jet flame close to lean blowout using a PMT. They used the ratio of standard deviation of the CH* intensity to the mean CH* signal defined as normalized root mean square (NRMS) to predict lean blowout [20]. In 2017, Li et al. proposed using the ratio of the working frequency components energy fraction over the low frequency components energy fraction to detect lean blowout for a pulse combustor [21]. These works focus on high Reynolds number flame and lean blowout detection index steeply increases as lean blowout is approached as shown in Fig. 1(a) [12–19]. A threshold is chosen and the flame is considered to be close to lean blowout when the index goes above the threshold value. In this study, it was found that existing indexes first increase and then decrease as approaching to lean blowout for low Reynolds number bluff-body flame as shown in Fig. 1(b). This is different with the previous studies and the decrease may lead to that the flame near lean blowout was classified as stable flame. Thus an index without sudden decrease is needed for low Reynolds number bluff-body flame, and this is one motivation of the present work. Besides, previous studies usually used acoustic or optic technologies [13–20]. Acoustic and optic detections are global measurement, with low spatial resolution and sensitivity to background noise and luminosity [12]. In addition, optical measurements require complicated optical systems and optical windows [22], and hence is expensive and difficult to use in practice. A technique with simple structure, low cost and applicability in practice is needed to detect lean blowout. Our previous work has proved that ion sensor is easy to install in any interest positions, and is appropriate for the detection of lean blowout for
Fig. 2. Schematic of experimental setup.
pulse combustor [21]. An additional motivation is to test the suitability of ion sensor in detecting lean blowout for bluff-body stabilized flame. 2. Experiment setup and measurement system 2.1. Experiment setup The experimental setup is shown in Fig. 2 which consists of a fuel tank, an air tank, two mass flow controllers (MFC, Sevenstar-CS200A) and a bluff-body burner. The fuel is composed of 80% butane and 20% propane. The burner consists of a conical bluff body, a prop rod and a circular tube. The conical bluff-body (40° half-angle) with diameter D1 = 8 mm is concentrically fitted within the tube and mounted on the rod with diameter of 1 mm. The inner diameter D2 of the tube is 10 mm. Therefore the blockage ratioβ [23] is 0.64, which is defined as:
β=
D12 D22
(1)
2.2. Measurement system The measurement system was built up to capture the flame signals and was shown in Fig. 3. The ion probe and photoelectric detector were used to detect the local oscillation and global oscillation, respectively. The ion probe detected the signal at the flame root, which is crucial for the stability of the bluff-body flame. However, it failed to detect the flame signal when the flame was lifted. This is one reason why the photoelectric detector was used to detect global oscillation rather than
Fig. 1. Schematic variation of existing index with air flow for (a) high Reynolds number flame in previous studies and (b) low Reynolds number bluff-body flame in this study. 2
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ion probe, which benefits by the small size of tungsten electrodes. Therefore, the ion probe has limited effects on the flame stability. During experiments, the operating state was controlled by adjusting the air flow (Qair) and fuel flow (Qfuel). Table 1 lists the operating conditions of the cases. For each experiment, Qfuel remained unchanged, while Qair increased from stable state until the flame was blowout. For the first experiment, Qfuel was set at 70 mL/min and Qair varied in the range of 2.0–3.4 L/min. The flame was blowout when the air flow exceeded 3.4 L/min. For all the experiments, the maximum Reynolds number based on the fluid properties at burner outlet and the bluffbody diameter is 567, which is close to the Reynolds number in the study of Kedia and Ghoniem [11]. Fig. 3. Schematic diagram of the measuring system.
3. Fundamentals
oscillation of the flame root. Besides, the photoelectric detector was used to offer validation for the ion probe and illustrate the difference between the local oscillation and global oscillation. The high speed camera was used to capture the flame events towards blowout. The photoelectric detector adopts the photodiode of Hamamatsu S12698 with a bandpass filter of wavelength 430 ± 7.5 nm. The flame signals were acquired using a data acquisition (DAQ) board at a sampling rate of 50000 Hz for 5 s. The visible flame appearance was captured using a camera (Canon EOS 800D) at 50 frames per second (fps). The high speed events occurring in bluff-body flame towards blowout were captured using a high speed camera (FASTCAM SA-X2) at 500 fps. The ion probe detects the burning rate of the flame by measuring the concentrations of charged ions, e.g., OH−, CHO+ and H3O+ [24,25]. Fig. 4 shows the structure of ion probe, which consists of two tungsten electrodes and a ceramic tube. The diameter of the tungsten electrode is designed as 0.2 mm to decrease its interference on the flow, and electrode stands out for 1.5 mm. The length of tungsten electrodes outside the ceramic tube is 10 mm, so as to avoid the effect of the ceramic tube on the flow. If the resistance of the fluid between two electrodes was Rx, the output voltage can be expressed as,
Vout =
3.1. Lean blowout of bluff-body stabilized flame at low Reynolds number Flame extinction can occur by reducing the equivalence ratio beyond a minimum threshold limit, which is defined as lean blowout. The bluff-body stabilized flame turns from stable to unstable as Qair increases from 2.0 L/min to 3.8 L/min at Qfuel = 80 mL/min. Timeaverage images of stable and unstable bluff-body flames are shown in Fig. 7. In this part, the flame images were captured without ion probe to eliminate the disturbance on the flow. As the air flow increases from 2.0 L/min to 3.8 L/min, the flame presents three state. The first state is stable state of flame as shown in Fig. 7(a and b), and the stable flame consists of a base flame anchored near the burner rim and a main flame seated above the base flame. As the air flow increases from 2.0 L/min to 2.9 L/min, the base flame becomes brighter and the total length of flame decreases. The second state is the liftoff-reattachment state of flame. As the air flow is further increased to 3.3 L/min, the length of the base flame increases, and liftoff-reattachment events are observed as shown in Fig. 8. The liftoff-reattachment events are different with the local extinction and reignition events occurring in high Reynolds number bluff-body flame which can be seen in the results of Shanbhogue et al. [26]. The third state is the complete liftoff state of flame. When the air flow reaches 3.6 L/min, the flame lifts off completely from the burner rim, as shown in Fig. 7(d). At this state, flame cannot reattach to the burner rim. Different with recessed inverse jet flame [27], the bluff-body flame does not blow out abruptly when the flame completely lifts off. The liftoff height increases as the air flow is increased to 3.8 L/min, which can be observed from Fig. 7(e).
−GVin 4(1 +
Rx ) R
(2)
where G is the gain of the amplifier, Vin is the supply voltage and R is the resistance of the bridge arm. Considering that ion probe is a local measurement method, it is important to optimize the measurement position. Ion probe was installed at different positions. The length of tungsten electrodes outside the ceramic tube is 0.5 mm in this part, to ensure that the probe measures local information. Fig. 5(a) shows the coordinate of measurement point. Coordinate center locates at the center of the bluffbody. Fig. 5(b) shows the variation of mean output voltage with measurement position. Results show that mean output voltage is low in recirculation zone. Mean output voltage reaches the maximum at r = 4 mm for h = 1–3 mm. When the height of measurement point exceeds 3 mm, the mean output voltage has no obvious peak. Considering that ion signals are strong at h = 1 mm and r = 4 mm, the electrodes of ion probe are mounted at this position in this study. To explore the effects of ion probe on the stability of the flame, the comparison of blowout air flow with and without ion probe was performed as shown in Fig. 6. It can be found that the blowout air flow with ion prove is a little higher than that without ion probe. However, the difference is very small compared with the blowout air flow without
3.2. Existing indexes for lean blowout detection To detect lean blowout, it is usual to analyze the fluctuation level of flame and then obtain lean blowout indicator [18,20]. The fluctuation level of flame can be quantificationally reflected by the standard deviation σ (I ) in time-domain and the low frequencies energy El in frequency-domain of the flame signal, N
El =
∫0
−
∑i =1 (Ii − I )2/N
σ (I ) = f2
Pf df
(3) (4)
where Ii is the i-th signal point, N is the number of signal points, Pf is the spectral power at frequency f, f2 is the upper boundary of the low frequency range. Previous studies have proposed a series methods to detect lean blowout [12,18–20]. (a) Normalized root mean square Normalized root mean square (NRMS) has been proved as a useful index for lean blowout detection of turbulent inverse jet flame [20], and is defined as the ratio of the standard deviation of signal to the
Fig. 4. Structure of the ion probe. 3
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Fig. 5. Measurement coordinate system and variation of mean output voltage of ion current sensor with the radial position.
Fig. 8. Liftoff-reattachment events of the bluff-body stabilized flame at Qair = 80 mL/min and Qfuel = 3.3 L/min.
Fig. 6. Comparison of blowout air flow with and without ion probe. Table 1 Operating conditions for case studies. Serial number
Qfuel (mL/min)
Qair (L/min)
1 2 3
70 80 90
2.0–3.4 2.0–3.8 2.0–4.2
mean signal,
NRMS =
Fig. 9. Variation of NRMS, θ and FFT%[0.2–10 Hz] calculated by CH* signal with air flow at Qfuel = 80 mL/min (The arrows indicate that NRMS and θ correspond to the left Y-axis, while FFT%[0.2–10 Hz] corresponds to the right Y-axis).
σ (I ) −
I
(5)
−
where I is the mean value of signal.
N(I < n ·I−)
(b) Normalized cumulative duration
θ=
Yi et al. [18] used normalized cumulative duration (θ) of local extinction and reignition events based on the studies of Muruganandam et al. [16] to detect lean blowout of a swirl flame,
where I is the mean of signal, N(I < n ·I−) denotes the number of signal
(6)
N −
−
points below n ·I , n is an factor.
Fig. 7. Time-averaged flame images when the fuel flow is 80 mL/min and the air flow of is (a) 2.0 L/min, (b) 2.9 L/min, (c) 3.3 L/min, (d) 3.6 L/min and (e) 3.8 L/ min, respectively. 4
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Fig. 10. Time series of the ion signal (a, c, e) and the CH* intensity signal (b, d, f) when the fuel flow is 80 mL/min and the air flow is 2.0 L/min, 3.3 L/min and 3.6 L/ min, respectively.
upper boundary of the low frequency range. These indexes have not been used in detecting lean blowout of bluffbody stabilized flame at low Reynolds number. In this work, it is found that NRMS, θ and FFT%[0.2 − 10Hz] calculated by CH* signal increase sharply beyond a critical air flow, and decrease suddenly beyond another critical air flow, as shown in Fig. 9. This is different with the results of previous studies [12,18,20], in which these indexes increase beyond a critical air flow and do not decrease. The difference is caused by the different dynamics near blowout of the flame at low Reynolds
(c) Fraction of the FFT power at low-frequencies The fraction of the FFT power at low-frequencies (FFT%[0 − f1 Hz]) has been successfully used by Li et al. to detect the lean blowout of a swirl flame [12],
FFT%[0 − f1 Hz] =
T rms2 [0, f1 ] T rms2 [0,1000]
(7)
where T rms2 [0, f1] is the variance of low-frequency signals and f1 is the 5
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Fig. 11. Comparison of flame signals and flame images when the fuel flow is 80 mL/min and the air flow is 3.3 L/min.
small value signal points, the liftoff-reattachment state is treated as a critical state. The mean value of ion current signal or CH* signal at this state was used as the threshold value, −
Thk = I1k
(8)
I1k
is the ion signal when k denotes ion and CH* signal when k where denotes CH* at liftoff-attachment state. The percent of signal points below the critical value is expressed as:
P k< =
N(I k < T k ) h
(9)
N Thk ,
N is the total where N(I k < T k ) is the number of signal points below h number of signal points. Physically, this parameter reveals the frequency of liftoff occurring in bluff-body stabilized flame as it approaches blowout. It is noted that this parameter is different with θ as it does not use average value as threshold but uses a certain value Thk . The selection of Thk is significant for this method, and the selection in the present work is based on the analyses of the dynamic characteristic of the flame as approaching to lean blowout.
Fig. 12. Variation of the standard deviation of the normalized ion probe signal and the CH* intensity signal with air flow.
number and high Reynolds number. The low values of NRMS, θ and FFT%[0.2 − 10Hz] when air flow is less than 3 L/min correspond to the stable flame. The increases of NRMS, θ and FFT%[0.2 − 10Hz] in the air flow range of 3.3–3.5 L/min correspond to the flame at liftoff-reattachment state. The decreases of NRMS, θ and FFT%[0.2 − 10Hz] in the air flow range of 3.6–3.8 L/min correspond to the flame at complete liftoff state. The decrease of these indexes may result in that the flame at complete liftoff state was classified as stable state. Thus it is highly desired to modify the index for lean blowout detection of bluff-body flame at low Reynolds number.
5. Results 5.1. Temporal characteristics near blowout Normalized ion and CH* signals for the stable and unstable flames are shown in Fig. 10. It can be seen that for Qair = 2.0 L/min, the fluctuation of normalized CH* signal is stronger than that of ion signal. The difference of fluctuation level between the two signals is due to the natural flicker of the flame. This reveals that the CH* signal is affected by flame flicker, and the ion current signal is insensitive to flame flicker. The fluctuation level of both signals at Qair = 3.3 L/min are higher as compared to the stable flame. To investigate the physical mechanism of increased fluctuation level, the ion and CH* signals are compared with the flame images as shown in Fig. 11. A sudden drop can be found from either ion signal or CH* signal. The flame is attached at 0.15 s, lifted at 0.235 s and reattached at 0.3 s. The decrease of the signal corresponds to the liftoff of flame. Therefore, the sudden drop and spontaneous increase of flame signal are caused by the liftoff and reattachment of flame, respectively. As the air flow is further increased
4. Proposed index for lean blowout detection To avoid that the flame at complete liftoff state was classified as stable as detecting lean blowout of low Reynolds number bluff-body flame, the index is modified in the present work. Histogram of either the ion current signal or the CH* signal indicates that as approaching to lean blowout, the percentage of small value signal points increases. Therefore, the percentage of small value signal points represents the instability of flame. To quantificationally describe the percentage of 6
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Fig. 13. Spectral analysis of the ion signal (a, c, e) and CH* intensity signal (b, d, f) when the fuel flow is 80 mL/min and the air flow is 2.0 L/min, 3.3 L/min and 3.6 L/min, respectively.
events occur, further increase in air flow results in that the flame completely lifts off and does not reattach to the burner rim. The fluctuation level of the flame at complete liftoff state is lower than that at liftoff-reattachment state. Therefore, the standard deviation first increases and then decreases as approaching to lean blowout.
to 3.6 L/min, the fluctuation levels of both signals do not increase but decrease. Fig. 7(d) shows that the flame is completely lifted at this condition. This indicates that the fluctuation of flame at complete state is lower than that at liftoff-reattachment state. The standard deviation of ion and CH* signals with air flow is plotted in Fig. 12. It can be found that the standard deviation first increases and then decreases with the increase of air flow. This is quite different with previous studies about high speed combustion [18,20]. For high speed flame, the standard deviation increases monotonously with the increase of air flow due to intense local extinction and reignition. For low speed bluff-body flame, when liftoff-reattachment
5.2. Spectral characteristics near blowout Power spectral density (PSD) of normalized ion and CH* signals at Qfuel = 80 mL/min and Qair = 2.0–3.6 L/min are shown in Fig. 13. The spectrums have been normalized according to the maximum of PSD 7
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the percentage of small value signal points represents the extent of flame instability. A critical value is hence needed to classify the small value signal points. For a fixed fuel flow, increase in air flow can cause liftoff-reattachment events, and further increase in the air flow can lead to complete liftoff and even blowout. The liftoff-reattachment events can be seen as an indicator for lean blowout. The mean value of each signal at the liftoff-reattachment state is defined as the critical value (Thk ). Fig. 16 shows time series and corresponding mean value of ion and CH* signals at Qfuel = 80 mL/min and Qair = 3.3 L/min, when the liftoffreattachment events occur. Liftoff of the flame can be identified by the signal points below the critical value, while the points above the critical value indicate reattachment. Therefore, the percentage of signal points below the critical value (P k< , defined in Eq. (9)) can be used to evaluate the extent of flame instability. Fig. 17 shows variation of P k< calculated from the ion and CH* signals with air flow. It can be seen that P k< calculated from both ion and CH* signals increases sharply beyond a critical air flow for a particular fuel flow. In this study, threshold P k< value is chosen as 0.5, which means that the number of signals below Thk equals to that above Thk . The threshold lies between the maxim1um and minimum values, providing enough time for control system to prevent blowout. It can be concluded that the method is suitable to detect lean blowout of bluffbody stabilized flame at low Reynolds number. To investigate the effects of time duration (Δt) of signal on P k< , P k< was calculated with different Δt and was shown in Fig. 18. In Fig. 18, Δt = 0.1 s means calculating P k< using the signals in the time range of 0–0.1 s. It can be found for all conditions of time duration, P
Fig. 14. Variation of the integral power within 0.2–10 Hz with air flow.
values at the condition of Qair = 3.3 L/min. For Qair = 2.0 L/min, two peaks are found at 0.8 Hz and 2.3 Hz in the spectrum of ion signal, and three peaks are found at less than 2 Hz in the spectrum of CH* signal. The flame in this case is stable and the spectrum peaks are caused by natural flicker. For Qair = 3.3 L/min, two dominant frequencies are observed in the ion signal spectrum: 2.2 and 4.8 Hz. These two peaks are caused by liftoff-reattachment events. In the CH* signal spectrum, the dominant frequencies are 2, 3.4 and 5 Hz. For Qair = 3.6 L/min, a series of peaks can be found from the enlarged view of ion signal. Three peaks are found at 1 Hz, 3.6 Hz and 4 Hz in the spectrum of CH* signal. The peak frequencies of two signals are different at all cases. One possible explanation for the difference is that the photoelectric detector is a global measurement method. The fluctuation of heat release in all positions of the flame can affect the CH* signal. However, the ion sensor is a point measurement device, resulting in that it is only sensitive to the fluctuation in the local point. Although the peak frequencies are different for two signals, the variation trend of low frequency energy (0.2–10 Hz) with air flow is similar. As the air flow increases to 3.3 L/min from 2.0 L/min, the low frequency energy increases for both signals. As the air flow further increases to 3.6 L/min, the low frequency energy does not further increase but decease. Fig. 14 shows the variation of integral power within 0.2–10 Hz with air flow. The integral power for ion and CH* signals first increases and then decreases with increase of air flow. This is quite different with previous studies about turbulent combustion [12,17,19]. The decrease of low frequency energy in this study is due to that the fluctuation level of the flame at complete liftoff state is lower than that at liftoff-reattachment state.
5.4. Comparison with the three existing indexes Fig. 19 shows the variation of θ, NRMS, FFT%[0.2–10 Hz] and P k< with air flow at Qfuel = 80 mL/min. It is shown that θ and NRMS calculated by both ion and CH* signals increase sharply beyond a critical air flow, and this is just the criterion of detecting blowout. Different with the results of Yi et al. [18] and Mahesh et al. [20], θ and NRMS decrease sharply beyond another critical air flow. It should be noted that the factor n is chosen as 0.8 here, and similar variation trend can be found when taking other values. The decrease will result in that the flame near blowout is classified as stable state. Therefore, θ and NRMS are improper to detect lean blowout of bluff-body stabilized flame at low Reynolds number. FFT%[0.2–10 Hz] calculated by ion signal decrease steeply beyond a critical air flow, which is caucused by liftoff. For FFT%[0.2–10 Hz] calculated by CH* signal, the dynamic range is narrow, and the decrease is also found. Therefore, FFT%[0.2–10 Hz] is also improper to detect lean blowout of bluff-body stabilized flame at low Reynolds number. In general, θ, NRMS and FFT%[0.2–10 Hz] first increase and then decrease as approaching to lean blowout. The sudden decrease may lead to that the flame near blowout is classified as stable state. Therefore, these methods are improper for detecting the lean blowout of bluff-body stabilized flame at low Reynolds number. However, P k< proposed can be used to detect lean blowout of bluff-body stabilized flame at low Reynolds number.
5.3. Results of lean blowout detection The standard deviation and FFT power at low frequencies related methods are improper to detect lean blowout of the low Reynolds number bluff-body flame, as they first increase and then decrease with the increase of air flow. Lean blowout detection methods require modifications for the combustion at low Reynolds number. Fig. 15 shows histogram of the normalized ion and CH* signals for stable and unstable flames. For Qair = 2.0 L/min, the normalized ion signal exhibits a near Gaussian distribution. For Qair = 3.3 L/min, the Gaussian distribution is distorted as small value signal points occur which is due to the flame liftoff-reattachment. As the air flow is increased to 3.6 L/ min, the normalized ion signal exhibits a near Rayleigh distribution. The distribution of normalized CH* signal also presents similar phenomenon, but is not obvious as compared to normalized ion signal, which is due to the natural flicker. As approaching to lean blowout, the number of small value signal points of each signal increases. Therefore, 8
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Fig. 15. Histogram of the ion signal (a, c, e) and the CH* intensity signal (b, d, f) when the fuel flow is 80 mL/min and the air flow is 2.0 L/min, 3.3 L/min and 3.6 L/ min, respectively.
5.5. Application in detecting blowout caused by high flow velocity
6. Conclusions
The index of P k< was preliminarily used in detecting the blowout caused by high flow velocity. In this part, the equivalence ratio was maintained at 0.73, while the flow velocity was increased from 1 m/s until the flame was blowout. Fig. 20 shows the variation of P k< with flow velocity. It can be seen that P k< calculated from both ion signal and CH* intensity signal increases sharply beyond a critical flow velocity. This indicates that index of P k< can be used to detect the blowout caused by high flow velocity.
The present work focused on detecting lean blowout of the low Reynolds number bluff-body flame. Standard deviation and low frequency energy within 0.2–10 Hz of each signal first increase due to flame liftoff-reattachment and then decrease due to complete flame liftoff with the increase of air flow, leading to that the existing methods, including the normalized root mean square (NRMS), normalized cumulative duration (θ) and fraction of the FFT power at low-frequencies (FFT%[0 − f1 Hz]) first increase and then decrease with the increase of air 9
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Fig. 16. Time series and corresponding mean value of normalized (a) ion signal and (b) CH* intensity signal when the fuel flow is 80 mL/min and the air flow is 3.3 L/min.
Fig. 17. Variation of P k< calculated from (a) the ion probe signal and (b) the CH* intensity signal with air flow for the fuel flow of 70–90 mL/min.
Fig. 18. Variation of P k< calculated from (a) the ion probe signal and (b) the CH* intensity signal with air flow at time duration of 0.1–5 s for the fuel flow of 80 mL/ min.
flow. Histogram of each signal indicates that with the increase of air flow, the percentage of small value signal points increases. Percentage of signal points below the critical value (P k< ) was thus used to detect lean blowout. Experiments indicate for a fixed fuel flow, NRMS, θ and
FFT%[0 − f1 Hz] calculated from either the ion current or the CH* signal first increase to the corresponding peak values and then decrease sharply with the increase of air flow, respectively. Unlike these methods, the percentages of signal points whose values are below the 10
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Fig. 19. Variation of NRMS, θ, FFT%[0.2–10 Hz] and P k< calculated from (a) the ion probe signal and (b) the CH* intensity signal with air flow (The arrows indicate that θ and NRMS correspond to the left Y-axis, while FFT%[0.2–10 Hz] and P k< correspond to the right Y-axis).
References [1] Tong Y, Liu X, Wang Z, et al. Experimental and numerical study on bluff-body and swirl stabilized diffusion flames. Fuel 2018;217:352–64. [2] Hodzic E, Jangi M, Szasz R, et al. Large eddy simulation of bluff-body flame approaching blow-off: A sensitivity study. Combust Sci Technol 2018:1–28. [3] Massey JC, Langella I, Swaminathan N. Large eddy simulation of a bluff body stabilised premixed flame using flamelets. Flow, Turbul Combust 2018;101(4):973–92. [4] Tang P, Geng X, Zhang J, et al. LES investigation the recirculation zone of the Sydney bluff-body burner. J Chizhou Univ 2014;28(06):41–3. [5] Zhang Z, Yu Y, Yuan G, et al. Numerical investigation of a new bluff-body gas stove. Scisence Technol Innovation 2018;14:21–3. [6] Lucky RA, Hossain I. Efficiency study of Bangladeshi cookstoves with an emphasis on gas cookstoves. Energy 2001;26(3):221–37. [7] Hui X, Zhang C, Xia M, et al. Effects of hydrogen addition on combustion characteristics of n-decane/air mixtures. Combust Flame 2014;161(9):2252–62. [8] Jones WP, Marquis AJ, Wang F. Large eddy simulation of a premixed propane turbulent bluff body flame using the Eulerian stochastic field method. Fuel 2015;140:514–25. [9] Berger S, Richard S, Duchaine F, et al. Variations of anchoring pattern of a bluff-body stabilized laminar premixed flame as a function of the wall temperature. Proceedings of ASME Turbo Expo 2016: Turbomachinery Technical Conference and Exposition. 2016. [10] Kedia KS, Ghoniem AF. The anchoring mechanism of a bluff-body stabilized laminar premixed flame. Combust Flame 2014;161(9):2327–39. [11] Kedia KS, Ghoniem AF. The blow-off mechanism of a bluff-body stabilized laminar premixed flame. Combust Flame 2015;162(4):1304–15. [12] Li H, Zhou X, Jeffries JB, et al. Active control of lean blowout in a swirl-stabilized combustor using a tunable diode laser. Proc Combust Inst 2007;31(2):3215–23. [13] T.M. Muruganandam, S. Nair, Y. Neumeier, et al. Optical and acoustic sensing of lean blowout precursors. AIAA 2002-37, 38th AIAA/ASME/SAE/ASEE Joint Propulsion Conference & Exhibit, 2002. [14] M. Thiruchengode, S. Nair, S. Prakash, et al. An active control system for LBO margin reduction in turbine engines. AIAA 2003-1008, 41st Aerospace Sciences Meeting and Exhibit, 2003. [15] T.M. Muruganandam, S. Nair, R. Olsen, et al. Blowout control in turbine engine combustors. AIAA 2004-637, 42nd AIAA Aerospace Sciences Meeting and Exhibit, 2004. [16] Muruganandam TM, Nair S, Scarborough D, et al. Active control of lean blowout for turbine engine combustors. J Propul Power 2005;21(5):807–14. [17] Nair S, Lieuwen T. Acoustic detection of blowout in premixed flames. J Propul Power 2005;21(1):32–9. [18] Yi T, Gutmark EJ. Real-time prediction of incipient lean blowout in gas turbine combustors. AIAA J 2007;45(7):1734–9. [19] Li H, Zhou X, Jeffries JB, et al. Sensing and control of combustion instabilities in swirlstabilized combustors using diode-laser absorption. AIAA J 2007;45(2):390–8. [20] Mahesh S, Mishra DP. Dynamic sensing of blowout in turbulent CNG inverse jet flame. Combust Flame 2015;162(8):3046–52. [21] Li F, Xu L, Du M, et al. Ion current sensing-based lean blowout detection for a pulse combustor. Combust Flame 2017;176:263–71. [22] Docquier N, Candel S. Combustion control and sensors: a review. Prog Energy Combust 2002;28(2):107–50. [23] Balachandran R, Ayoola B, Kaminski C, et al. Experimental investigation of the nonlinear response of turbulent premixed flames to imposed inlet velocity oscillations. Combust Flame 2005;143(1–2):37–55. [24] Peerlings LBW, Manohar VN Kornilov, et al. Flame ion generation rate as a measure of the flame thermo-acoustic response. Combust Flame 2013;160:2490–6. [25] Li F, Cao Z, Xu L, et al. Prediction of equivalence ratio in pulse combustor from ion current amplitude spectrum. Fuel 2018;218:179–87. [26] Shanbhogue SJ, Husain S, Lieuwen T. Lean blowoff of bluff body stabilized flames: Scaling and dynamics. Prog Energy Combust 2009;35(1):98–120. [27] Mahesh S, Mishra DP. Flame stability limits and near blowout characteristics of CNG inverse jet flame. Fuel 2015;153:267–75.
Fig. 20. Variation of P k< calculated from the ion probe signal and the CH* intensity signal with velocity at the equivalence ratio of 0.73.
critical values calculated from the ion current signal (P ion < ) and CH* ∗ signal (P CH < ) first increase to their upper limit and then remain unchanged with the increase of air flow, respectively. The index avoids that the flame at liftoff state was wrongly classified as stable flame. CRediT authorship contribution statement Liuyong Chang: Conceptualization, Methodology, Formal analysis, Validation. Zhang Cao: Software, Investigation, Resources, Data curation. Bo Fu: Writing - review & editing, Funding acquisition. Yuzhen Lin: Formal analysis, Supervision, Project administration. Lijun Xu: Writing - original draft, Funding acquisition. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments This work was supported by the National Natural Science Foundation of China, China (grant number 61620106004 and 61827802) and National Key Research and Development Project, China (2018YFB2003200).
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Full Length Article
Lean blowout detection for bluff-body stabilized flame a
a
Liuyong Chang , Zhang Cao , Bo Fu
a,b
c
, Yuzhen Lin , Lijun Xu
a,⁎
T
a
School of Instrumentation and Opto-Electronic Engineering, Beihang University, Beijing 100191, China BUAA-CCMU Advanced Innovation Center For Big Data-based Precision Medicine, Interdisciplinary Innovation Institute of Medicine and Engineering, Beihang University, Beijing 100191, China c School of Energy and Power Engineering, Beihang University, Beijing 100191, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Bluff-body stabilized flame Flame fluctuation Lean blowout detection Ion current signal CH* detector
The present work proposed an index to extend the previous lean blowout detection method to bluff-body stabilized flame at the condition of low Reynolds number. Dynamic characteristics near lean blowout of low Reynolds number bluff-body flame are not exactly same with that of high Reynolds number bluff-body flame. Thus lean blowout detection index requires modification for low Reynolds number bluff-body flame. The flame images show that, for a fixed fuel flow, increase of air flow to a certain value can cause flame liftoff-reattachment events, and further increase of air flow can lead to complete liftoff and even lean blowout. Temporal and spectral analyses of the ion current and CH* signals exhibit that both standard deviation and low frequency energy within 0.2–10 Hz of each signal first increase due to flame liftoff-reattachment and then decrease due to complete flame liftoff with the increase of air flow. This leads to that the lean blowout detection indexes including the normalized root mean square (NRMS), normalized cumulative duration (θ) and fraction of the fast Fourier transform (FFT) power at low-frequencies (FFT%[0 − f1 Hz]) first increase and then decrease with the increase of air flow. As a result, the flame at the liftoff state may be wrongly classified as stable state. To avoid this, the histogram distributions of two signals were investigated. The number of small value sample points of each signal increases with increase of air flow, indicating that the percentage of small value sample points can be used to detect lean blowout. The mean value of each signal at the liftoff-reattachment state is used as the threshold value to classify small value sample points. For either the ion current signal or CH* signal, percentage of sample points below the corresponding threshold value (P k< ) is used to detect lean blowout. The flame is considered as close to lean blowout when P k< reaches 50%. Experimental results show that P k< can be used for reliable detection of lean blowout for bluff-body stabilized flame at the condition of low Reynolds number.
1. Introduction Bluff-body flame holder has been widely used in practical applications, e.g., gas turbine combustor, scramjet combustor and industrial furnaces [1]. Bluff-body creates a recirculation zone for anchoring the flame. The hot burnt mixture is recirculated into this zone and continuously ignites incoming mixtures, acting as a heat source [2–4]. Besides, bluff-body flame holder is also widely used in Reynolds number combustors such as gas stove [5]. With the increasing attention to environmental protection, indoor air pollution has attracted great concern [6]. Lean combustion was widely adopted to reduce NOX emissions by reducing the flame temperature [7,8]. However, lean combustion is susceptible to lean blowout and bluff-body flame holder is used to ensure the combustion stable at fuel-lean condition. In recent years, low Reynolds number bluff-body flame has received extensive
⁎
concerns. Berger et al. experimentally studied the impact of wall temperature on flame stabilization for low Reynolds number bluff-body flame [9]. Kedia and Ghoniem numerically researched the blow-off and anchoring mechanism of a low Reynolds number bluff-body flame [10,11]. Lean blowout can cause serious problems for combustors and should be avoided. However, lean blowout limit is uncertain and varies with the change of operating parameters, such as fuel compositions, environment temperature and combustor age [12]. NOX production can be reduced and burner lifetime can be increased by operating in a narrower safety margin, which needs accurate detection of lean blowout. A lot of studies have been done in lean blowout detection. In 2002, Muruganandam et al. used the number of local extinction and reignition events in 33 s and the fraction of the total energy in low frequencies (10–200 Hz) to predict lean blowout [13]. In this work,
Corresponding author. E-mail address: [email protected] (L. Xu).
https://doi.org/10.1016/j.fuel.2020.117008 Received 25 September 2019; Received in revised form 13 December 2019; Accepted 2 January 2020 0016-2361/ © 2020 Elsevier Ltd. All rights reserved.
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they used one-quarter of the mean signal value as the threshold to identify the local extinction and reignition events [13]. In 2003, they proposed using double thresholds to identify the local extinction and reignition events [14]. The event starts as the signal drops below onequarter of the mean signal value, and ends when the signal goes above 0.3 times of the mean signal value [14]. In 2004, they extended their work to non-premixed, liquid-fueled combustors [15]. They used 50% of mean signal value as the lower threshold and two times of the standard deviation of the signal above the lower threshold as the upper threshold [15]. In 2005, they used the number of local extinction events per second [16] and the fraction of power in low-frequencies [17] to detect and further control lean blowout. In 2007, Yi and Gutmark studied proposed the normalized cumulative duration (θ) based on the method of Muruganandam et al. to predict the occurrence of lean blowout [18]. Li et al. investigated the swirl flame close to lean blowout using a tunable diode laser, and they found that the fraction of the fast Fourier transform (FFT) power at low-frequencies (FFT%[0 − f1 Hz]) increases exponentially as the flame approaches lean blowout [19]. In 2015, Mahesh and Mishra investigated the inverse jet flame close to lean blowout using a PMT. They used the ratio of standard deviation of the CH* intensity to the mean CH* signal defined as normalized root mean square (NRMS) to predict lean blowout [20]. In 2017, Li et al. proposed using the ratio of the working frequency components energy fraction over the low frequency components energy fraction to detect lean blowout for a pulse combustor [21]. These works focus on high Reynolds number flame and lean blowout detection index steeply increases as lean blowout is approached as shown in Fig. 1(a) [12–19]. A threshold is chosen and the flame is considered to be close to lean blowout when the index goes above the threshold value. In this study, it was found that existing indexes first increase and then decrease as approaching to lean blowout for low Reynolds number bluff-body flame as shown in Fig. 1(b). This is different with the previous studies and the decrease may lead to that the flame near lean blowout was classified as stable flame. Thus an index without sudden decrease is needed for low Reynolds number bluff-body flame, and this is one motivation of the present work. Besides, previous studies usually used acoustic or optic technologies [13–20]. Acoustic and optic detections are global measurement, with low spatial resolution and sensitivity to background noise and luminosity [12]. In addition, optical measurements require complicated optical systems and optical windows [22], and hence is expensive and difficult to use in practice. A technique with simple structure, low cost and applicability in practice is needed to detect lean blowout. Our previous work has proved that ion sensor is easy to install in any interest positions, and is appropriate for the detection of lean blowout for
Fig. 2. Schematic of experimental setup.
pulse combustor [21]. An additional motivation is to test the suitability of ion sensor in detecting lean blowout for bluff-body stabilized flame. 2. Experiment setup and measurement system 2.1. Experiment setup The experimental setup is shown in Fig. 2 which consists of a fuel tank, an air tank, two mass flow controllers (MFC, Sevenstar-CS200A) and a bluff-body burner. The fuel is composed of 80% butane and 20% propane. The burner consists of a conical bluff body, a prop rod and a circular tube. The conical bluff-body (40° half-angle) with diameter D1 = 8 mm is concentrically fitted within the tube and mounted on the rod with diameter of 1 mm. The inner diameter D2 of the tube is 10 mm. Therefore the blockage ratioβ [23] is 0.64, which is defined as:
β=
D12 D22
(1)
2.2. Measurement system The measurement system was built up to capture the flame signals and was shown in Fig. 3. The ion probe and photoelectric detector were used to detect the local oscillation and global oscillation, respectively. The ion probe detected the signal at the flame root, which is crucial for the stability of the bluff-body flame. However, it failed to detect the flame signal when the flame was lifted. This is one reason why the photoelectric detector was used to detect global oscillation rather than
Fig. 1. Schematic variation of existing index with air flow for (a) high Reynolds number flame in previous studies and (b) low Reynolds number bluff-body flame in this study. 2
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ion probe, which benefits by the small size of tungsten electrodes. Therefore, the ion probe has limited effects on the flame stability. During experiments, the operating state was controlled by adjusting the air flow (Qair) and fuel flow (Qfuel). Table 1 lists the operating conditions of the cases. For each experiment, Qfuel remained unchanged, while Qair increased from stable state until the flame was blowout. For the first experiment, Qfuel was set at 70 mL/min and Qair varied in the range of 2.0–3.4 L/min. The flame was blowout when the air flow exceeded 3.4 L/min. For all the experiments, the maximum Reynolds number based on the fluid properties at burner outlet and the bluffbody diameter is 567, which is close to the Reynolds number in the study of Kedia and Ghoniem [11]. Fig. 3. Schematic diagram of the measuring system.
3. Fundamentals
oscillation of the flame root. Besides, the photoelectric detector was used to offer validation for the ion probe and illustrate the difference between the local oscillation and global oscillation. The high speed camera was used to capture the flame events towards blowout. The photoelectric detector adopts the photodiode of Hamamatsu S12698 with a bandpass filter of wavelength 430 ± 7.5 nm. The flame signals were acquired using a data acquisition (DAQ) board at a sampling rate of 50000 Hz for 5 s. The visible flame appearance was captured using a camera (Canon EOS 800D) at 50 frames per second (fps). The high speed events occurring in bluff-body flame towards blowout were captured using a high speed camera (FASTCAM SA-X2) at 500 fps. The ion probe detects the burning rate of the flame by measuring the concentrations of charged ions, e.g., OH−, CHO+ and H3O+ [24,25]. Fig. 4 shows the structure of ion probe, which consists of two tungsten electrodes and a ceramic tube. The diameter of the tungsten electrode is designed as 0.2 mm to decrease its interference on the flow, and electrode stands out for 1.5 mm. The length of tungsten electrodes outside the ceramic tube is 10 mm, so as to avoid the effect of the ceramic tube on the flow. If the resistance of the fluid between two electrodes was Rx, the output voltage can be expressed as,
Vout =
3.1. Lean blowout of bluff-body stabilized flame at low Reynolds number Flame extinction can occur by reducing the equivalence ratio beyond a minimum threshold limit, which is defined as lean blowout. The bluff-body stabilized flame turns from stable to unstable as Qair increases from 2.0 L/min to 3.8 L/min at Qfuel = 80 mL/min. Timeaverage images of stable and unstable bluff-body flames are shown in Fig. 7. In this part, the flame images were captured without ion probe to eliminate the disturbance on the flow. As the air flow increases from 2.0 L/min to 3.8 L/min, the flame presents three state. The first state is stable state of flame as shown in Fig. 7(a and b), and the stable flame consists of a base flame anchored near the burner rim and a main flame seated above the base flame. As the air flow increases from 2.0 L/min to 2.9 L/min, the base flame becomes brighter and the total length of flame decreases. The second state is the liftoff-reattachment state of flame. As the air flow is further increased to 3.3 L/min, the length of the base flame increases, and liftoff-reattachment events are observed as shown in Fig. 8. The liftoff-reattachment events are different with the local extinction and reignition events occurring in high Reynolds number bluff-body flame which can be seen in the results of Shanbhogue et al. [26]. The third state is the complete liftoff state of flame. When the air flow reaches 3.6 L/min, the flame lifts off completely from the burner rim, as shown in Fig. 7(d). At this state, flame cannot reattach to the burner rim. Different with recessed inverse jet flame [27], the bluff-body flame does not blow out abruptly when the flame completely lifts off. The liftoff height increases as the air flow is increased to 3.8 L/min, which can be observed from Fig. 7(e).
−GVin 4(1 +
Rx ) R
(2)
where G is the gain of the amplifier, Vin is the supply voltage and R is the resistance of the bridge arm. Considering that ion probe is a local measurement method, it is important to optimize the measurement position. Ion probe was installed at different positions. The length of tungsten electrodes outside the ceramic tube is 0.5 mm in this part, to ensure that the probe measures local information. Fig. 5(a) shows the coordinate of measurement point. Coordinate center locates at the center of the bluffbody. Fig. 5(b) shows the variation of mean output voltage with measurement position. Results show that mean output voltage is low in recirculation zone. Mean output voltage reaches the maximum at r = 4 mm for h = 1–3 mm. When the height of measurement point exceeds 3 mm, the mean output voltage has no obvious peak. Considering that ion signals are strong at h = 1 mm and r = 4 mm, the electrodes of ion probe are mounted at this position in this study. To explore the effects of ion probe on the stability of the flame, the comparison of blowout air flow with and without ion probe was performed as shown in Fig. 6. It can be found that the blowout air flow with ion prove is a little higher than that without ion probe. However, the difference is very small compared with the blowout air flow without
3.2. Existing indexes for lean blowout detection To detect lean blowout, it is usual to analyze the fluctuation level of flame and then obtain lean blowout indicator [18,20]. The fluctuation level of flame can be quantificationally reflected by the standard deviation σ (I ) in time-domain and the low frequencies energy El in frequency-domain of the flame signal, N
El =
∫0
−
∑i =1 (Ii − I )2/N
σ (I ) = f2
Pf df
(3) (4)
where Ii is the i-th signal point, N is the number of signal points, Pf is the spectral power at frequency f, f2 is the upper boundary of the low frequency range. Previous studies have proposed a series methods to detect lean blowout [12,18–20]. (a) Normalized root mean square Normalized root mean square (NRMS) has been proved as a useful index for lean blowout detection of turbulent inverse jet flame [20], and is defined as the ratio of the standard deviation of signal to the
Fig. 4. Structure of the ion probe. 3
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Fig. 5. Measurement coordinate system and variation of mean output voltage of ion current sensor with the radial position.
Fig. 8. Liftoff-reattachment events of the bluff-body stabilized flame at Qair = 80 mL/min and Qfuel = 3.3 L/min.
Fig. 6. Comparison of blowout air flow with and without ion probe. Table 1 Operating conditions for case studies. Serial number
Qfuel (mL/min)
Qair (L/min)
1 2 3
70 80 90
2.0–3.4 2.0–3.8 2.0–4.2
mean signal,
NRMS =
Fig. 9. Variation of NRMS, θ and FFT%[0.2–10 Hz] calculated by CH* signal with air flow at Qfuel = 80 mL/min (The arrows indicate that NRMS and θ correspond to the left Y-axis, while FFT%[0.2–10 Hz] corresponds to the right Y-axis).
σ (I ) −
I
(5)
−
where I is the mean value of signal.
N(I < n ·I−)
(b) Normalized cumulative duration
θ=
Yi et al. [18] used normalized cumulative duration (θ) of local extinction and reignition events based on the studies of Muruganandam et al. [16] to detect lean blowout of a swirl flame,
where I is the mean of signal, N(I < n ·I−) denotes the number of signal
(6)
N −
−
points below n ·I , n is an factor.
Fig. 7. Time-averaged flame images when the fuel flow is 80 mL/min and the air flow of is (a) 2.0 L/min, (b) 2.9 L/min, (c) 3.3 L/min, (d) 3.6 L/min and (e) 3.8 L/ min, respectively. 4
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Fig. 10. Time series of the ion signal (a, c, e) and the CH* intensity signal (b, d, f) when the fuel flow is 80 mL/min and the air flow is 2.0 L/min, 3.3 L/min and 3.6 L/ min, respectively.
upper boundary of the low frequency range. These indexes have not been used in detecting lean blowout of bluffbody stabilized flame at low Reynolds number. In this work, it is found that NRMS, θ and FFT%[0.2 − 10Hz] calculated by CH* signal increase sharply beyond a critical air flow, and decrease suddenly beyond another critical air flow, as shown in Fig. 9. This is different with the results of previous studies [12,18,20], in which these indexes increase beyond a critical air flow and do not decrease. The difference is caused by the different dynamics near blowout of the flame at low Reynolds
(c) Fraction of the FFT power at low-frequencies The fraction of the FFT power at low-frequencies (FFT%[0 − f1 Hz]) has been successfully used by Li et al. to detect the lean blowout of a swirl flame [12],
FFT%[0 − f1 Hz] =
T rms2 [0, f1 ] T rms2 [0,1000]
(7)
where T rms2 [0, f1] is the variance of low-frequency signals and f1 is the 5
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Fig. 11. Comparison of flame signals and flame images when the fuel flow is 80 mL/min and the air flow is 3.3 L/min.
small value signal points, the liftoff-reattachment state is treated as a critical state. The mean value of ion current signal or CH* signal at this state was used as the threshold value, −
Thk = I1k
(8)
I1k
is the ion signal when k denotes ion and CH* signal when k where denotes CH* at liftoff-attachment state. The percent of signal points below the critical value is expressed as:
P k< =
N(I k < T k ) h
(9)
N Thk ,
N is the total where N(I k < T k ) is the number of signal points below h number of signal points. Physically, this parameter reveals the frequency of liftoff occurring in bluff-body stabilized flame as it approaches blowout. It is noted that this parameter is different with θ as it does not use average value as threshold but uses a certain value Thk . The selection of Thk is significant for this method, and the selection in the present work is based on the analyses of the dynamic characteristic of the flame as approaching to lean blowout.
Fig. 12. Variation of the standard deviation of the normalized ion probe signal and the CH* intensity signal with air flow.
number and high Reynolds number. The low values of NRMS, θ and FFT%[0.2 − 10Hz] when air flow is less than 3 L/min correspond to the stable flame. The increases of NRMS, θ and FFT%[0.2 − 10Hz] in the air flow range of 3.3–3.5 L/min correspond to the flame at liftoff-reattachment state. The decreases of NRMS, θ and FFT%[0.2 − 10Hz] in the air flow range of 3.6–3.8 L/min correspond to the flame at complete liftoff state. The decrease of these indexes may result in that the flame at complete liftoff state was classified as stable state. Thus it is highly desired to modify the index for lean blowout detection of bluff-body flame at low Reynolds number.
5. Results 5.1. Temporal characteristics near blowout Normalized ion and CH* signals for the stable and unstable flames are shown in Fig. 10. It can be seen that for Qair = 2.0 L/min, the fluctuation of normalized CH* signal is stronger than that of ion signal. The difference of fluctuation level between the two signals is due to the natural flicker of the flame. This reveals that the CH* signal is affected by flame flicker, and the ion current signal is insensitive to flame flicker. The fluctuation level of both signals at Qair = 3.3 L/min are higher as compared to the stable flame. To investigate the physical mechanism of increased fluctuation level, the ion and CH* signals are compared with the flame images as shown in Fig. 11. A sudden drop can be found from either ion signal or CH* signal. The flame is attached at 0.15 s, lifted at 0.235 s and reattached at 0.3 s. The decrease of the signal corresponds to the liftoff of flame. Therefore, the sudden drop and spontaneous increase of flame signal are caused by the liftoff and reattachment of flame, respectively. As the air flow is further increased
4. Proposed index for lean blowout detection To avoid that the flame at complete liftoff state was classified as stable as detecting lean blowout of low Reynolds number bluff-body flame, the index is modified in the present work. Histogram of either the ion current signal or the CH* signal indicates that as approaching to lean blowout, the percentage of small value signal points increases. Therefore, the percentage of small value signal points represents the instability of flame. To quantificationally describe the percentage of 6
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Fig. 13. Spectral analysis of the ion signal (a, c, e) and CH* intensity signal (b, d, f) when the fuel flow is 80 mL/min and the air flow is 2.0 L/min, 3.3 L/min and 3.6 L/min, respectively.
events occur, further increase in air flow results in that the flame completely lifts off and does not reattach to the burner rim. The fluctuation level of the flame at complete liftoff state is lower than that at liftoff-reattachment state. Therefore, the standard deviation first increases and then decreases as approaching to lean blowout.
to 3.6 L/min, the fluctuation levels of both signals do not increase but decrease. Fig. 7(d) shows that the flame is completely lifted at this condition. This indicates that the fluctuation of flame at complete state is lower than that at liftoff-reattachment state. The standard deviation of ion and CH* signals with air flow is plotted in Fig. 12. It can be found that the standard deviation first increases and then decreases with the increase of air flow. This is quite different with previous studies about high speed combustion [18,20]. For high speed flame, the standard deviation increases monotonously with the increase of air flow due to intense local extinction and reignition. For low speed bluff-body flame, when liftoff-reattachment
5.2. Spectral characteristics near blowout Power spectral density (PSD) of normalized ion and CH* signals at Qfuel = 80 mL/min and Qair = 2.0–3.6 L/min are shown in Fig. 13. The spectrums have been normalized according to the maximum of PSD 7
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the percentage of small value signal points represents the extent of flame instability. A critical value is hence needed to classify the small value signal points. For a fixed fuel flow, increase in air flow can cause liftoff-reattachment events, and further increase in the air flow can lead to complete liftoff and even blowout. The liftoff-reattachment events can be seen as an indicator for lean blowout. The mean value of each signal at the liftoff-reattachment state is defined as the critical value (Thk ). Fig. 16 shows time series and corresponding mean value of ion and CH* signals at Qfuel = 80 mL/min and Qair = 3.3 L/min, when the liftoffreattachment events occur. Liftoff of the flame can be identified by the signal points below the critical value, while the points above the critical value indicate reattachment. Therefore, the percentage of signal points below the critical value (P k< , defined in Eq. (9)) can be used to evaluate the extent of flame instability. Fig. 17 shows variation of P k< calculated from the ion and CH* signals with air flow. It can be seen that P k< calculated from both ion and CH* signals increases sharply beyond a critical air flow for a particular fuel flow. In this study, threshold P k< value is chosen as 0.5, which means that the number of signals below Thk equals to that above Thk . The threshold lies between the maxim1um and minimum values, providing enough time for control system to prevent blowout. It can be concluded that the method is suitable to detect lean blowout of bluffbody stabilized flame at low Reynolds number. To investigate the effects of time duration (Δt) of signal on P k< , P k< was calculated with different Δt and was shown in Fig. 18. In Fig. 18, Δt = 0.1 s means calculating P k< using the signals in the time range of 0–0.1 s. It can be found for all conditions of time duration, P
Fig. 14. Variation of the integral power within 0.2–10 Hz with air flow.
values at the condition of Qair = 3.3 L/min. For Qair = 2.0 L/min, two peaks are found at 0.8 Hz and 2.3 Hz in the spectrum of ion signal, and three peaks are found at less than 2 Hz in the spectrum of CH* signal. The flame in this case is stable and the spectrum peaks are caused by natural flicker. For Qair = 3.3 L/min, two dominant frequencies are observed in the ion signal spectrum: 2.2 and 4.8 Hz. These two peaks are caused by liftoff-reattachment events. In the CH* signal spectrum, the dominant frequencies are 2, 3.4 and 5 Hz. For Qair = 3.6 L/min, a series of peaks can be found from the enlarged view of ion signal. Three peaks are found at 1 Hz, 3.6 Hz and 4 Hz in the spectrum of CH* signal. The peak frequencies of two signals are different at all cases. One possible explanation for the difference is that the photoelectric detector is a global measurement method. The fluctuation of heat release in all positions of the flame can affect the CH* signal. However, the ion sensor is a point measurement device, resulting in that it is only sensitive to the fluctuation in the local point. Although the peak frequencies are different for two signals, the variation trend of low frequency energy (0.2–10 Hz) with air flow is similar. As the air flow increases to 3.3 L/min from 2.0 L/min, the low frequency energy increases for both signals. As the air flow further increases to 3.6 L/min, the low frequency energy does not further increase but decease. Fig. 14 shows the variation of integral power within 0.2–10 Hz with air flow. The integral power for ion and CH* signals first increases and then decreases with increase of air flow. This is quite different with previous studies about turbulent combustion [12,17,19]. The decrease of low frequency energy in this study is due to that the fluctuation level of the flame at complete liftoff state is lower than that at liftoff-reattachment state.
5.4. Comparison with the three existing indexes Fig. 19 shows the variation of θ, NRMS, FFT%[0.2–10 Hz] and P k< with air flow at Qfuel = 80 mL/min. It is shown that θ and NRMS calculated by both ion and CH* signals increase sharply beyond a critical air flow, and this is just the criterion of detecting blowout. Different with the results of Yi et al. [18] and Mahesh et al. [20], θ and NRMS decrease sharply beyond another critical air flow. It should be noted that the factor n is chosen as 0.8 here, and similar variation trend can be found when taking other values. The decrease will result in that the flame near blowout is classified as stable state. Therefore, θ and NRMS are improper to detect lean blowout of bluff-body stabilized flame at low Reynolds number. FFT%[0.2–10 Hz] calculated by ion signal decrease steeply beyond a critical air flow, which is caucused by liftoff. For FFT%[0.2–10 Hz] calculated by CH* signal, the dynamic range is narrow, and the decrease is also found. Therefore, FFT%[0.2–10 Hz] is also improper to detect lean blowout of bluff-body stabilized flame at low Reynolds number. In general, θ, NRMS and FFT%[0.2–10 Hz] first increase and then decrease as approaching to lean blowout. The sudden decrease may lead to that the flame near blowout is classified as stable state. Therefore, these methods are improper for detecting the lean blowout of bluff-body stabilized flame at low Reynolds number. However, P k< proposed can be used to detect lean blowout of bluff-body stabilized flame at low Reynolds number.
5.3. Results of lean blowout detection The standard deviation and FFT power at low frequencies related methods are improper to detect lean blowout of the low Reynolds number bluff-body flame, as they first increase and then decrease with the increase of air flow. Lean blowout detection methods require modifications for the combustion at low Reynolds number. Fig. 15 shows histogram of the normalized ion and CH* signals for stable and unstable flames. For Qair = 2.0 L/min, the normalized ion signal exhibits a near Gaussian distribution. For Qair = 3.3 L/min, the Gaussian distribution is distorted as small value signal points occur which is due to the flame liftoff-reattachment. As the air flow is increased to 3.6 L/ min, the normalized ion signal exhibits a near Rayleigh distribution. The distribution of normalized CH* signal also presents similar phenomenon, but is not obvious as compared to normalized ion signal, which is due to the natural flicker. As approaching to lean blowout, the number of small value signal points of each signal increases. Therefore, 8
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Fig. 15. Histogram of the ion signal (a, c, e) and the CH* intensity signal (b, d, f) when the fuel flow is 80 mL/min and the air flow is 2.0 L/min, 3.3 L/min and 3.6 L/ min, respectively.
5.5. Application in detecting blowout caused by high flow velocity
6. Conclusions
The index of P k< was preliminarily used in detecting the blowout caused by high flow velocity. In this part, the equivalence ratio was maintained at 0.73, while the flow velocity was increased from 1 m/s until the flame was blowout. Fig. 20 shows the variation of P k< with flow velocity. It can be seen that P k< calculated from both ion signal and CH* intensity signal increases sharply beyond a critical flow velocity. This indicates that index of P k< can be used to detect the blowout caused by high flow velocity.
The present work focused on detecting lean blowout of the low Reynolds number bluff-body flame. Standard deviation and low frequency energy within 0.2–10 Hz of each signal first increase due to flame liftoff-reattachment and then decrease due to complete flame liftoff with the increase of air flow, leading to that the existing methods, including the normalized root mean square (NRMS), normalized cumulative duration (θ) and fraction of the FFT power at low-frequencies (FFT%[0 − f1 Hz]) first increase and then decrease with the increase of air 9
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Fig. 16. Time series and corresponding mean value of normalized (a) ion signal and (b) CH* intensity signal when the fuel flow is 80 mL/min and the air flow is 3.3 L/min.
Fig. 17. Variation of P k< calculated from (a) the ion probe signal and (b) the CH* intensity signal with air flow for the fuel flow of 70–90 mL/min.
Fig. 18. Variation of P k< calculated from (a) the ion probe signal and (b) the CH* intensity signal with air flow at time duration of 0.1–5 s for the fuel flow of 80 mL/ min.
flow. Histogram of each signal indicates that with the increase of air flow, the percentage of small value signal points increases. Percentage of signal points below the critical value (P k< ) was thus used to detect lean blowout. Experiments indicate for a fixed fuel flow, NRMS, θ and
FFT%[0 − f1 Hz] calculated from either the ion current or the CH* signal first increase to the corresponding peak values and then decrease sharply with the increase of air flow, respectively. Unlike these methods, the percentages of signal points whose values are below the 10
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Fig. 19. Variation of NRMS, θ, FFT%[0.2–10 Hz] and P k< calculated from (a) the ion probe signal and (b) the CH* intensity signal with air flow (The arrows indicate that θ and NRMS correspond to the left Y-axis, while FFT%[0.2–10 Hz] and P k< correspond to the right Y-axis).
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Fig. 20. Variation of P k< calculated from the ion probe signal and the CH* intensity signal with velocity at the equivalence ratio of 0.73.
critical values calculated from the ion current signal (P ion < ) and CH* ∗ signal (P CH < ) first increase to their upper limit and then remain unchanged with the increase of air flow, respectively. The index avoids that the flame at liftoff state was wrongly classified as stable flame. CRediT authorship contribution statement Liuyong Chang: Conceptualization, Methodology, Formal analysis, Validation. Zhang Cao: Software, Investigation, Resources, Data curation. Bo Fu: Writing - review & editing, Funding acquisition. Yuzhen Lin: Formal analysis, Supervision, Project administration. Lijun Xu: Writing - original draft, Funding acquisition. Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgments This work was supported by the National Natural Science Foundation of China, China (grant number 61620106004 and 61827802) and National Key Research and Development Project, China (2018YFB2003200).
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