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Optimization of distances measurement by an ultrasonic sensor
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ScienceDirect Materials Today: Proceedings 19 (2019) 33–39
www.materialstoday.com/proceedings
NANOTEXNOLOGY2018
Optimization of distances measurement by an ultrasonic sensor A. Rocchi1*, E. Santecchia1,2, G. Barucca1, P. Mengucci1 2
1 Dipartimento SIMAU , Università Politecnica delle Marche, I-60131 Ancona, Italy Consorzio Interuniversitario Nazionale per la Scienza e Tecnologia dei Materiali (INSTM-UdR Ancona), Italy
Abstract The problem of environmental disasters due to oil spills has characterized recent history from first years of '900 and still represents an important risk factor for environmental protection. The equipment and techniques currently in use for monitoring the marine water are very expensive. The scope of this research is the design and optimization of a non-contact ultrasonic sensor system capable of providing the water level in marine environment. This system is a part of a very low-cost device to detect pollution due to the presence of non-conductive liquids (i.e. hydrocarbons floating in the sea), exploiting the different conductivity of the fluids involved. The work focuses on the characterization of the SRF05 ultrasonic, providing the Time Of Flight (microseconds) of transmitted wave which interacts with a surface target, and on its configuration inside a floating organ as a result of data obtained from laboratory tests. Experimental tests were conducted using a micrometric sledge in a climatic chamber, in order to study the effect of the climatic conditions variations, such as temperature and humidity, on the velocity of ultrasonic waves, with the aim to establish the best operating range in terms of sensor resolution and architecture of the buoy. In order to improve the accuracy of the system and to overcome issues linked with the climatic conditions, the adoption of a sensor system consisting of the combination of two SRF05 sensors, is suggested. One of these sensors can detect the speed of sound, based on a fixed distance, while the other should be arranged to detect the water surface. The final device is controlled by an Atmega328P low-power microcontroller through an algorithm, and can detect the level of liquid surface (sea water or contaminant) with sensibility of about 1 mm. © 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of International Conferences & Exhibition on Nanosciences & Nanotechnologies and Flexible Organic Electronics 2018, June 30th - July 6th, 2018 Keywords: non-contact ultrasonic sensor; fluids contactivity
* Corresponding author. Tel.: 00393381947938 E-mail address: [email protected] 2214-7853 © 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of International Conferences & Exhibition on Nanosciences & Nanotechnologies and Flexible Organic Electronics 2018, June 30th - July 6th, 2018
34
A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
1. Introduction Oil spills disasters represent the most dangerous causes of environmental impact in the world. Only to mention the last accident happened around China’s coast on 6th January 2018, when an Iranian oil tanker, about 136000 tonnes of light oil were spilled on a sea area of approximately 130 km2, after the collision between an oil tank and a merchant ship. Oil spill surveillance represents the best way to preserve the Earth ecosystem and to reduce intervention cost. For this purpose, many sensors were developed in recent years, and the most commonly applied in this field are:
Visible remote sensing [1-3] Infrared sensors [4-6] Ultraviolet sensors [7] Radar system [8] Microwave sensors [9] Laser fluorosensors [10]
This paper presents the preliminary study on a level sensor system implemented in an innovative device, able to detect hydrocarbons floating on the sea. This device [11-12] is essentially composed of two adaptable sensor systems. The first, is an ultrasonic wave system that measures the level of fluid surface, while the second is made by two columns of electrodes, which detect the flow of electrical current at different heights. Given that floating hydrocarbons are insulating fluids while sea water is conductive, any hydrocarbon pollution will result in a lower current flow through the system at the sea surface. However, considering that the air medium is also not conductive, it is crucial to detect the position of the fluid surface to determine the presence of eventual hydrocarbons layers. This configuration allows to calculate also the thickness of hydrocarbons fluids. The most important feature of this novel device is the low cost of instrumentations which is going to allow a large-scale production and, therefore, the possibility to monitor large areas of the sea. This system provides an immediate response due to its communication protocols and to the facilitated localization by the incorporated GPS system. In fact, actions of pollution response must be fast and geographically smart. Concerning the level fluid measurement system, various kinds of sensors are available on the market, everyone with its price, operating range, resolution, and accuracy. For our aim the SRF05 sonar sensor was selected. This sensor provides the Time Of Flight (TOF) of a reflected ultrasonic wave by a target after being transmitted by transducer capsule. Through the measure of TOFs it is possible to obtain a target distance in millimetres from the sensor by the following equation (Eq. (1)): d = (t · v) / 2
(1),
where d is the distance from the target, t is the Time Of Flight, and v is the speed of sound. It is well known that the speed of sound in air depends on the climate conditions. The most influential parameter that causes an increase of the speed of sound is the temperature. Being the SRF05 sensor used typically for industrial and domotics applications, it does not include a temperature compensation module. Therefore, to improve the accuracy of the level measurement and to account for environmental effects, the ultrasonic system was optimized by adding another SRF05 module. This second sonar sensor, placed at a fixed distance from a steel target, provides TOFs values connected to the climatic conditions of the marine environment. This information about the precise speed of sound in the air, is transferred to the other SRF05, and it is used to reduce the error in the measurement of the fluid surface level. The overall sensors system configuration was validated through a set-up built in a climate chamber, in order to modify environmental parameters such temperature and relative humidity. The present paper shows the results of the system characterization in an extended range of climatic conditions.
A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
35
2. Material and methods 2.1 Sonar Sensor The sensor chosen for this project is the SRF05. It is a PING module assembled with two transducer capsules. The transmission module sends an ultrasonic burst at 8 cycles at 40 kHz and simultaneously increases the echo line in HIGH. When the reflected ultrasonic wave returns to the receiving capsule, the echo line is dropped to LOW. The final length square wave echo gives the Time Of Flight values of the ultrasonic wave. The reflected ultrasonic wave interacts with an exponential threshold, generated by the RC circuit, in an op-amp voltage comparator (Fig. 1), placed in the SRF05 microprocessor.
Fig. 1. Block diagram of the SRF05 sensor.
After the threshold - echo signal intersection, the SRF05 microprocessor counts three peak waves before dropping in LOW the echo line, to prevent false echoes from producing significant errors in the TOFs results. If no signals are intercept, the SRF05 will still lower its echo line after 30 ms. Given its typical applications, this sonar sensor is optimized for an operating interval going from 0,02 m to 4 m, but according to the final configuration of the overall system, the sonar sensor should be able to work correctly near its minimum operative range. 2.2 Measurement set-up A micrometric linear stage (High-Performance Precision Translation Stages NEW PORT) was used to move the sonar sensor perpendicularly to a fixed metal target of dimensions 25 x 25 cm2 and thickness of 3 mm. The ultrasonic sensor was attached to the linear stage, which was shifted by step of 1 mm using an external digital control dispositive. The ultrasonic sensor was controlled with an 8-bit ATmega328p microprocessor, which guarantees the performance required for the measurement system, as well as the correct amount of FLASH and RAM memory needed for analytic operations. The reading of data was done through a Serial Port with the protocol RS232 at 9600 bps.
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A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
Fig. 2. Schematic measurement Set-up
In order to evaluate the performance of the SRF05 sensor under different climatic conditions, the measurement set-up, shown in Fig. 2, was placed inside a climatic chamber (ACS – CLIMATIC CHAMBER CHALLENGE 250). The internal room dimensions of the climate chamber (600 mm x 535 mm x 700 mm) allowed to provide TOFs values corresponding to distances close to the lower operating range of the SRF05 sonar sensor, from 122 to 150 mm, which is the one of interest for the targeted application. 300 values of TOFs were detected for each distance. The set of measurements was divided in 2 phases. During the first phase, the relative humidity was fixed at a value of 30%, while the internal temperature was changed from 5 °C to 40 °C. In the second set, the temperature was fixed at 25 °C, while the relative humidity was varied in an interval ranging from 30% to 60%. These climatic conditions were chosen according to the operative temperature conditions of the linear stage, in order to prevent micrometric localized deformations of the sled's screw as a result of temperature gradients. 3. Result and discussion 3.1. Temperature effect As mentioned above, the behaviour of the SRF05 sonar system was analysed in its lower operating range, from 122 to 150 mm. The tests were conducted by changing the temperature in the climatic chamber, from 5 °C to 40 °C, using steps of 5 °C for each sensor-target distance, while the relative humidity was set at 30%. The graph reported in Fig. 3 shows the TOFs values detected by the sonar sensor while varying the distance from the target. Different symbols correspond to different temperatures, namely 10, 20, 30 and 40 °C. The reed lines in Fig. 3 represent the fitting curve of the corresponding data and confirm an increase in TOFs values while increasing the sensor-target distance (as a check of the correct mode of operation of the low cost SRF05 sensor). The mean square roots calculated between experimental and fitting curves result to be 2.21 µs, 2.26 µs, 1.62 µs and 1.90 µs, for the 10, 20, 30 and 40 °C curves, respectively. These results reveal a limited dispersion of the experimental data and, therefore, the high degree of reliability of the present measurement system.
A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
37
900
TOF outputs (µs)
850
800
750
10 °C 20 °C 30 °C 40 °C
700
650 120
125
130
135
140
145
150
distance (mm) Fig. 3. TOFs measured at 10, 20, 30, and 40 °C.
Another important aspect to point out about Fig. 3, is that in the considered set of sensor-target distances (from 122 to 150 mm), the measured TOF values undergo a decrease of 14.2 µs for each temperature raise of 10 °C. In order to fully characterize the sensor, it is important to verify that the measured values of sound’s speed do not vary at a fixed temperature. Therefore, following a theoretical model already reported in literature [13], a comparison between calculated and measured values of the speed of sound is reported in Figure 4. The theoretical model is based on the following equation ((Eq. (2)): = 0.62
+ 331.41
(2),
where is the temperature in Celsius degrees (°C), and is the velocity of sound. As can be seen from Fig. 4, the angular coefficient of the regression line at temperatures of 25 °C and 40 °C is close to 0. This result confirms that the speed of sound, at stable temperature, does not depend on a particular distance from the target. The velocity of sound at 25 °C and 40 °C results to be 349.0 ± 0.8 m/s and 358.0 ± 0.9 m/s. The sensor system behaviour at a temperature of 25 °C has been reported being this the typical environmental condition taken as a reference.
38
A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
Experimental and Theoretical Speed of Sound
368
Speeed of Sound (m/s)
364 360 356 352 348 344
40°C exp. 40°C th. 25°C exp. 25°C th.
340 120
125
130
135
140
145
150
Distance (mm)
Fig. 4. Experimental and theoretical values of the speed of sound.
The results reported in Fig. 4 highlight an increase of 2 m/s in the measured values of the speed of sound (red lines) compared to the mathematical model (black lines). In the considered operating range of the sensor, from 122 to 150 mm, at 25 °C the calculated error due to difference between experimental and theoretical data, results to be 0.56 mm. On the other hand, taking into account only the experimental data provided by the sonar sensor at the same temperature, the measured speed of sound is affected by an error of about ±0.82 m/s, which results in a distance error of about ±0.31 mm. The measured values of the speed of sound (open symbols in Fig. 4), show systematic fluctuations which take place at distance steps of 5 mm, and are characterized by fitting curves having exactly the same angular coefficient (0.6). This result was observed at all the investigated temperatures, and suggest a link with the circuital features of the SRF05 sonar sensor. Despite these measured fluctuations, the distance error obtained considering only the measured values of the speed of sound, is lower than the one given by the theoretical model. Therefore, the best option to adopt for the speed of sound check is the experimental one. 3.2. Humidity effect The second set of measurements was carried out to evaluate the influence of relative humidity on the Times Of Flight values collected by the sonar sensor. The sensor was placed at a distance of 122 mm from the metal target used for experiments described above. The temperature was kept at 25°C. The climatic chamber was programmed for a ramp of relative humidity (HR) values of 30%, 40%, 50% and 60%. A total of 900 values of TOFs were collected for each distance. As reported in literature, the variation of measured distance with the relative humidity increase from 30% to 60%, is about 0.06 mm [14-15]. Table 1. Correlation between TOFs average data and relative humidity. Relative Humidity
Average TOFs
(HR%)
TOFs (µs)
30 %
722.5 ± 0.4
40 %
722.2 ± 1.0
50%
721.9 ± 0.9
60%
721.5 ± 1.6
A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
39
Table 1 shows the TOFs values form three set of measurement performed and no appreciable differences can be observed (the error in relative humidity can be considered within the error caused by temperature). For the considered relative humidity ramp from 30% to 60%, taking as a reference the sensor-target distance measured at 25 °C and 30% HR, the calculated error associated with the distance is in the range between 0.04 mm and 0.09 mm, or rather well below the accuracy required by the sensor system. Given the particular operating range selected for the SRF05 sonar sensor, the effect of relative humidity on the measured performed can be neglected. 4. Conclusions This paper presents the optimization of the low cost ultrasonic sensor SRF05 for water level detection, to be implemented in a device for pollution detection in marine environment. The characterization of the SRF05 sensor under different environmental conditions has revealed, for the considered range of sensor-target distances (from 122 to 150 mm), that the temperature has a remarkable effect on the measured Time Of Flight of the ultrasonic wave, while relative humidity is a negligible condition. Furthermore, it was evidenced that is not possible to estimate correctly the sound’s speed using theoretical equations, being the difference with the experimental data of about 2 m/s. References [1] D. Wang, D. Pan, Y. Zhan, and Q. Zhu, SPIE – Int. Soc. Opt. Eng., 7831 (2010) 78311. [2] H.-Y. Shen, P.-C. Zhou, S.-R. Feng, S. Hui-yan, Z. Pu-cheng, and F. Shao-ru, Proc. SPIE Int. Soc. Opt. Eng. 8193 (2011). [3] R. F. Kokaly Brady R.Couvillion, JoAnn M.Holloway, Dar A.Roberts, Susan L.Ustin, Seth H.Peterson, ShrutiKhanna, Sarai C.Piazza, Remote Sens Environ 129 (2013) 210–230. [4] Pinel N., Monnier G., Sergievskaya I., Bourlier C., Proc. SPIE Int. Soc. Opt. Eng. 9638 (2015) 85–88. [5] A. Samberg, Proc. SPIE 5791, Laser Radar Technology and Applications X 5791 (2005) 308. [6] M. Fingas and C. E. Brown, Oil Spill Science and Technology, Elsevier, 2011, pp. 111–169. [7] R. Goodman, Spill Sci Technol Bull 1 (1994) 11–21. [8] F. Nunziata, M. Migliaccio, and P. Sobieski, Int Geosci Remote Sens Symp, 4 (2008) 593–596. [9] O. Calla, H. K. Dadhich, and S. Singhal, Indian J Radio Sp Phys 42 (2013) 52–59. [10] C. E. Brown, “Laser Fluorosensors,” in Oil Spill Science and Technology, Elsevier, 2011, pp. 171–184. [11] G.Barucca, P.Mengucci, D.Tiberi , Italian PATENT N.0001420869 [12] G.Barucca, P.Mengucci, D.Tiberi, International PATENT N. WO 2015/079471 A1 [13] T. Dahl, J. L. Ealo, H. J. Bang, S. Holm, and P. Khuri-Yakub, Ultrasonics, 54 (2014) 1912–1921.. [14] Cramer O., J Acoust Soc Am 93(1993) 2510–2516. [15] G. S. K. Wong and T. F. W. Embleton, J. Acoust. Soc. Amer 77 (1985) 1710-1712.
ScienceDirect Materials Today: Proceedings 19 (2019) 33–39
www.materialstoday.com/proceedings
NANOTEXNOLOGY2018
Optimization of distances measurement by an ultrasonic sensor A. Rocchi1*, E. Santecchia1,2, G. Barucca1, P. Mengucci1 2
1 Dipartimento SIMAU , Università Politecnica delle Marche, I-60131 Ancona, Italy Consorzio Interuniversitario Nazionale per la Scienza e Tecnologia dei Materiali (INSTM-UdR Ancona), Italy
Abstract The problem of environmental disasters due to oil spills has characterized recent history from first years of '900 and still represents an important risk factor for environmental protection. The equipment and techniques currently in use for monitoring the marine water are very expensive. The scope of this research is the design and optimization of a non-contact ultrasonic sensor system capable of providing the water level in marine environment. This system is a part of a very low-cost device to detect pollution due to the presence of non-conductive liquids (i.e. hydrocarbons floating in the sea), exploiting the different conductivity of the fluids involved. The work focuses on the characterization of the SRF05 ultrasonic, providing the Time Of Flight (microseconds) of transmitted wave which interacts with a surface target, and on its configuration inside a floating organ as a result of data obtained from laboratory tests. Experimental tests were conducted using a micrometric sledge in a climatic chamber, in order to study the effect of the climatic conditions variations, such as temperature and humidity, on the velocity of ultrasonic waves, with the aim to establish the best operating range in terms of sensor resolution and architecture of the buoy. In order to improve the accuracy of the system and to overcome issues linked with the climatic conditions, the adoption of a sensor system consisting of the combination of two SRF05 sensors, is suggested. One of these sensors can detect the speed of sound, based on a fixed distance, while the other should be arranged to detect the water surface. The final device is controlled by an Atmega328P low-power microcontroller through an algorithm, and can detect the level of liquid surface (sea water or contaminant) with sensibility of about 1 mm. © 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of International Conferences & Exhibition on Nanosciences & Nanotechnologies and Flexible Organic Electronics 2018, June 30th - July 6th, 2018 Keywords: non-contact ultrasonic sensor; fluids contactivity
* Corresponding author. Tel.: 00393381947938 E-mail address: [email protected] 2214-7853 © 2019 Elsevier Ltd. All rights reserved. Selection and peer-review under responsibility of International Conferences & Exhibition on Nanosciences & Nanotechnologies and Flexible Organic Electronics 2018, June 30th - July 6th, 2018
34
A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
1. Introduction Oil spills disasters represent the most dangerous causes of environmental impact in the world. Only to mention the last accident happened around China’s coast on 6th January 2018, when an Iranian oil tanker, about 136000 tonnes of light oil were spilled on a sea area of approximately 130 km2, after the collision between an oil tank and a merchant ship. Oil spill surveillance represents the best way to preserve the Earth ecosystem and to reduce intervention cost. For this purpose, many sensors were developed in recent years, and the most commonly applied in this field are:
Visible remote sensing [1-3] Infrared sensors [4-6] Ultraviolet sensors [7] Radar system [8] Microwave sensors [9] Laser fluorosensors [10]
This paper presents the preliminary study on a level sensor system implemented in an innovative device, able to detect hydrocarbons floating on the sea. This device [11-12] is essentially composed of two adaptable sensor systems. The first, is an ultrasonic wave system that measures the level of fluid surface, while the second is made by two columns of electrodes, which detect the flow of electrical current at different heights. Given that floating hydrocarbons are insulating fluids while sea water is conductive, any hydrocarbon pollution will result in a lower current flow through the system at the sea surface. However, considering that the air medium is also not conductive, it is crucial to detect the position of the fluid surface to determine the presence of eventual hydrocarbons layers. This configuration allows to calculate also the thickness of hydrocarbons fluids. The most important feature of this novel device is the low cost of instrumentations which is going to allow a large-scale production and, therefore, the possibility to monitor large areas of the sea. This system provides an immediate response due to its communication protocols and to the facilitated localization by the incorporated GPS system. In fact, actions of pollution response must be fast and geographically smart. Concerning the level fluid measurement system, various kinds of sensors are available on the market, everyone with its price, operating range, resolution, and accuracy. For our aim the SRF05 sonar sensor was selected. This sensor provides the Time Of Flight (TOF) of a reflected ultrasonic wave by a target after being transmitted by transducer capsule. Through the measure of TOFs it is possible to obtain a target distance in millimetres from the sensor by the following equation (Eq. (1)): d = (t · v) / 2
(1),
where d is the distance from the target, t is the Time Of Flight, and v is the speed of sound. It is well known that the speed of sound in air depends on the climate conditions. The most influential parameter that causes an increase of the speed of sound is the temperature. Being the SRF05 sensor used typically for industrial and domotics applications, it does not include a temperature compensation module. Therefore, to improve the accuracy of the level measurement and to account for environmental effects, the ultrasonic system was optimized by adding another SRF05 module. This second sonar sensor, placed at a fixed distance from a steel target, provides TOFs values connected to the climatic conditions of the marine environment. This information about the precise speed of sound in the air, is transferred to the other SRF05, and it is used to reduce the error in the measurement of the fluid surface level. The overall sensors system configuration was validated through a set-up built in a climate chamber, in order to modify environmental parameters such temperature and relative humidity. The present paper shows the results of the system characterization in an extended range of climatic conditions.
A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
35
2. Material and methods 2.1 Sonar Sensor The sensor chosen for this project is the SRF05. It is a PING module assembled with two transducer capsules. The transmission module sends an ultrasonic burst at 8 cycles at 40 kHz and simultaneously increases the echo line in HIGH. When the reflected ultrasonic wave returns to the receiving capsule, the echo line is dropped to LOW. The final length square wave echo gives the Time Of Flight values of the ultrasonic wave. The reflected ultrasonic wave interacts with an exponential threshold, generated by the RC circuit, in an op-amp voltage comparator (Fig. 1), placed in the SRF05 microprocessor.
Fig. 1. Block diagram of the SRF05 sensor.
After the threshold - echo signal intersection, the SRF05 microprocessor counts three peak waves before dropping in LOW the echo line, to prevent false echoes from producing significant errors in the TOFs results. If no signals are intercept, the SRF05 will still lower its echo line after 30 ms. Given its typical applications, this sonar sensor is optimized for an operating interval going from 0,02 m to 4 m, but according to the final configuration of the overall system, the sonar sensor should be able to work correctly near its minimum operative range. 2.2 Measurement set-up A micrometric linear stage (High-Performance Precision Translation Stages NEW PORT) was used to move the sonar sensor perpendicularly to a fixed metal target of dimensions 25 x 25 cm2 and thickness of 3 mm. The ultrasonic sensor was attached to the linear stage, which was shifted by step of 1 mm using an external digital control dispositive. The ultrasonic sensor was controlled with an 8-bit ATmega328p microprocessor, which guarantees the performance required for the measurement system, as well as the correct amount of FLASH and RAM memory needed for analytic operations. The reading of data was done through a Serial Port with the protocol RS232 at 9600 bps.
36
A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
Fig. 2. Schematic measurement Set-up
In order to evaluate the performance of the SRF05 sensor under different climatic conditions, the measurement set-up, shown in Fig. 2, was placed inside a climatic chamber (ACS – CLIMATIC CHAMBER CHALLENGE 250). The internal room dimensions of the climate chamber (600 mm x 535 mm x 700 mm) allowed to provide TOFs values corresponding to distances close to the lower operating range of the SRF05 sonar sensor, from 122 to 150 mm, which is the one of interest for the targeted application. 300 values of TOFs were detected for each distance. The set of measurements was divided in 2 phases. During the first phase, the relative humidity was fixed at a value of 30%, while the internal temperature was changed from 5 °C to 40 °C. In the second set, the temperature was fixed at 25 °C, while the relative humidity was varied in an interval ranging from 30% to 60%. These climatic conditions were chosen according to the operative temperature conditions of the linear stage, in order to prevent micrometric localized deformations of the sled's screw as a result of temperature gradients. 3. Result and discussion 3.1. Temperature effect As mentioned above, the behaviour of the SRF05 sonar system was analysed in its lower operating range, from 122 to 150 mm. The tests were conducted by changing the temperature in the climatic chamber, from 5 °C to 40 °C, using steps of 5 °C for each sensor-target distance, while the relative humidity was set at 30%. The graph reported in Fig. 3 shows the TOFs values detected by the sonar sensor while varying the distance from the target. Different symbols correspond to different temperatures, namely 10, 20, 30 and 40 °C. The reed lines in Fig. 3 represent the fitting curve of the corresponding data and confirm an increase in TOFs values while increasing the sensor-target distance (as a check of the correct mode of operation of the low cost SRF05 sensor). The mean square roots calculated between experimental and fitting curves result to be 2.21 µs, 2.26 µs, 1.62 µs and 1.90 µs, for the 10, 20, 30 and 40 °C curves, respectively. These results reveal a limited dispersion of the experimental data and, therefore, the high degree of reliability of the present measurement system.
A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
37
900
TOF outputs (µs)
850
800
750
10 °C 20 °C 30 °C 40 °C
700
650 120
125
130
135
140
145
150
distance (mm) Fig. 3. TOFs measured at 10, 20, 30, and 40 °C.
Another important aspect to point out about Fig. 3, is that in the considered set of sensor-target distances (from 122 to 150 mm), the measured TOF values undergo a decrease of 14.2 µs for each temperature raise of 10 °C. In order to fully characterize the sensor, it is important to verify that the measured values of sound’s speed do not vary at a fixed temperature. Therefore, following a theoretical model already reported in literature [13], a comparison between calculated and measured values of the speed of sound is reported in Figure 4. The theoretical model is based on the following equation ((Eq. (2)): = 0.62
+ 331.41
(2),
where is the temperature in Celsius degrees (°C), and is the velocity of sound. As can be seen from Fig. 4, the angular coefficient of the regression line at temperatures of 25 °C and 40 °C is close to 0. This result confirms that the speed of sound, at stable temperature, does not depend on a particular distance from the target. The velocity of sound at 25 °C and 40 °C results to be 349.0 ± 0.8 m/s and 358.0 ± 0.9 m/s. The sensor system behaviour at a temperature of 25 °C has been reported being this the typical environmental condition taken as a reference.
38
A. Rocchi et al. / Materials Today: Proceedings 19 (2019) 33–39
Experimental and Theoretical Speed of Sound
368
Speeed of Sound (m/s)
364 360 356 352 348 344
40°C exp. 40°C th. 25°C exp. 25°C th.
340 120
125
130
135
140
145
150
Distance (mm)
Fig. 4. Experimental and theoretical values of the speed of sound.
The results reported in Fig. 4 highlight an increase of 2 m/s in the measured values of the speed of sound (red lines) compared to the mathematical model (black lines). In the considered operating range of the sensor, from 122 to 150 mm, at 25 °C the calculated error due to difference between experimental and theoretical data, results to be 0.56 mm. On the other hand, taking into account only the experimental data provided by the sonar sensor at the same temperature, the measured speed of sound is affected by an error of about ±0.82 m/s, which results in a distance error of about ±0.31 mm. The measured values of the speed of sound (open symbols in Fig. 4), show systematic fluctuations which take place at distance steps of 5 mm, and are characterized by fitting curves having exactly the same angular coefficient (0.6). This result was observed at all the investigated temperatures, and suggest a link with the circuital features of the SRF05 sonar sensor. Despite these measured fluctuations, the distance error obtained considering only the measured values of the speed of sound, is lower than the one given by the theoretical model. Therefore, the best option to adopt for the speed of sound check is the experimental one. 3.2. Humidity effect The second set of measurements was carried out to evaluate the influence of relative humidity on the Times Of Flight values collected by the sonar sensor. The sensor was placed at a distance of 122 mm from the metal target used for experiments described above. The temperature was kept at 25°C. The climatic chamber was programmed for a ramp of relative humidity (HR) values of 30%, 40%, 50% and 60%. A total of 900 values of TOFs were collected for each distance. As reported in literature, the variation of measured distance with the relative humidity increase from 30% to 60%, is about 0.06 mm [14-15]. Table 1. Correlation between TOFs average data and relative humidity. Relative Humidity
Average TOFs
(HR%)
TOFs (µs)
30 %
722.5 ± 0.4
40 %
722.2 ± 1.0
50%
721.9 ± 0.9
60%
721.5 ± 1.6
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Table 1 shows the TOFs values form three set of measurement performed and no appreciable differences can be observed (the error in relative humidity can be considered within the error caused by temperature). For the considered relative humidity ramp from 30% to 60%, taking as a reference the sensor-target distance measured at 25 °C and 30% HR, the calculated error associated with the distance is in the range between 0.04 mm and 0.09 mm, or rather well below the accuracy required by the sensor system. Given the particular operating range selected for the SRF05 sonar sensor, the effect of relative humidity on the measured performed can be neglected. 4. Conclusions This paper presents the optimization of the low cost ultrasonic sensor SRF05 for water level detection, to be implemented in a device for pollution detection in marine environment. The characterization of the SRF05 sensor under different environmental conditions has revealed, for the considered range of sensor-target distances (from 122 to 150 mm), that the temperature has a remarkable effect on the measured Time Of Flight of the ultrasonic wave, while relative humidity is a negligible condition. Furthermore, it was evidenced that is not possible to estimate correctly the sound’s speed using theoretical equations, being the difference with the experimental data of about 2 m/s. References [1] D. Wang, D. Pan, Y. Zhan, and Q. Zhu, SPIE – Int. Soc. Opt. Eng., 7831 (2010) 78311. [2] H.-Y. Shen, P.-C. Zhou, S.-R. Feng, S. Hui-yan, Z. Pu-cheng, and F. Shao-ru, Proc. SPIE Int. Soc. Opt. Eng. 8193 (2011). [3] R. F. Kokaly Brady R.Couvillion, JoAnn M.Holloway, Dar A.Roberts, Susan L.Ustin, Seth H.Peterson, ShrutiKhanna, Sarai C.Piazza, Remote Sens Environ 129 (2013) 210–230. [4] Pinel N., Monnier G., Sergievskaya I., Bourlier C., Proc. SPIE Int. Soc. Opt. Eng. 9638 (2015) 85–88. [5] A. Samberg, Proc. SPIE 5791, Laser Radar Technology and Applications X 5791 (2005) 308. [6] M. Fingas and C. E. Brown, Oil Spill Science and Technology, Elsevier, 2011, pp. 111–169. [7] R. Goodman, Spill Sci Technol Bull 1 (1994) 11–21. [8] F. Nunziata, M. Migliaccio, and P. Sobieski, Int Geosci Remote Sens Symp, 4 (2008) 593–596. [9] O. Calla, H. K. Dadhich, and S. Singhal, Indian J Radio Sp Phys 42 (2013) 52–59. [10] C. E. Brown, “Laser Fluorosensors,” in Oil Spill Science and Technology, Elsevier, 2011, pp. 171–184. [11] G.Barucca, P.Mengucci, D.Tiberi , Italian PATENT N.0001420869 [12] G.Barucca, P.Mengucci, D.Tiberi, International PATENT N. WO 2015/079471 A1 [13] T. Dahl, J. L. Ealo, H. J. Bang, S. Holm, and P. Khuri-Yakub, Ultrasonics, 54 (2014) 1912–1921.. [14] Cramer O., J Acoust Soc Am 93(1993) 2510–2516. [15] G. S. K. Wong and T. F. W. Embleton, J. Acoust. Soc. Amer 77 (1985) 1710-1712.