Two-dimensional particle shape analysis from chord measurements to increase accuracy of particle shape determination

Powder Technology 284 (2015) 25–31

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Powder Technology journal homepage: www.elsevier.com/locate/powtec

Two-dimensional particle shape analysis from chord measurements to increase accuracy of particle shape determination D. Petrak a,⁎, S. Dietrich b, G. Eckardt b, M. Köhler b a b

Chemnitz University of Technology, Germany Parsum GmbH, Reichenhainer Str. 34-36, D-09126 Chemnitz, Germany

a r t i c l e

i n f o

Article history: Received 14 December 2014 Received in revised form 9 June 2015 Accepted 13 June 2015 Available online 20 June 2015 Keywords: Particle shape Chord length measurement Coating process In-line on-line

a b s t r a c t Some in-process two-dimensional particle sizing methods can provide on-line information about the chord length distribution of a population of particles. The objective of this study is to use the chord measurement not only for the size determination but also for the determination of the particle shape. Main results are the nondimensional aspect ratio or the roundness of the particle. The elongation values can be calculated by three non-dimensional parameters which are derived from the mean, mode or maximal chord length of the number and area based chord distributions. The application of these shape parameters is limited to narrow particle size and shape distributions. The application is demonstrated for coating of elliptical seed particles and spherical pellets (Cellets®1000). An optical probe system (IPP 70, Parsum GmbH, Germany) was used for the measurement of chord lengths during the coating processes. Results of an image analysis were in a good correlation with the results of the chord measurements. The advantage is the simultaneous use of the measured chord lengths for the characterization of the particle size and also the particle shape without any need for additional measurement equipment. Another advantage is the in-line determination of the particle shape without taking a powder sample. © 2015 Elsevier B.V. All rights reserved.

1. Introduction Size and shape are important characteristics of solid particles which determine many properties of powders. Several different physicalbased methods exist for the measurement of particle size and shape and especially in-situ methods are important for process control and optimization. This paper describes a new in-situ method for the determination of particle shape based on chord length measurements. There is a lot of literature on particle shape determination based on image analysis of dispersed particles in the last 10–20 years [1,2]. Some commercial image analysis instruments (Morphologi G3, etc.) are available for particle shape analysis in 2D. Image analysis uses a two-dimensional image of a three-dimensional particle and calculates various size and shape parameters from this particle image. In this article is described how to extend particle sizing by the measurement of chord lengths to the simultaneous determination of particle shapes. There are several methods for in-situ particle sizing using

⁎ Corresponding author at: D-99425 Weimar, Wassily-Kandinsky-Str. 4, Germany. Tel.: +49 3643 400038; fax: +49 3643 497464. E-mail addresses: [email protected] (D. Petrak), [email protected] (S. Dietrich), [email protected] (G. Eckardt), [email protected] (M. Köhler).

http://dx.doi.org/10.1016/j.powtec.2015.06.036 0032-5910/© 2015 Elsevier B.V. All rights reserved.

chord length measurement based on laser beam reflection or spatial filtering technique [3,4]. These measuring systems provide on-line information about the chord length distribution of a population of particles. Each particle detection is independent of all others and each particle is randomly cut by the measured chord. The focus is on the transformation of chord length distributions into particle size distributions [5,6]. In these articles the frequency of the chord length distributions shows a dependency on the particle shape. The objective of this study is to use this dependency on the determination of the overall particle shape of the measured particle system. The chord length distributions are calculated as an example for two particle shapes, sphere and ellipsoids with different ratio of semi-axis lengths. The definition of non-dimensional shape parameters and their dependency on the aspect ratio or circularity are described in the next section. Moreover, by means of simulation results, the applicability of this insitu method will be demonstrated for two particle coating processes.

2. Chord distribution of a sphere An analytical expression for the chord cut probability of a sphere or circle is described by Underwood [7]. The calculation is based on simple geometrical considerations.

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D. Petrak et al. / Powder Technology 284 (2015) 25–31

y

0.1

d q2(s) [1/µm]

0.08

h2

0.06

d = 100 µm

0.04 0.02 0

h1

s2

x

0

s1



q2 sm;i ¼ Fig. 1 shows a circle with diameter d and two chords with lengths s1 and s2 with fixed scanning direction of the measuring system. The symbols h1 and h2 are described by Fig. 1. qffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 d −s21

ð1Þ

d 1 − 2 2

qffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 d −s22

ð2Þ

50 60 sm [µm]

70

80

90 100 110

  s2m;i q0 sm;i M2;0

1 ðs þ siþ1 Þ 2Xi   ¼ s2m;ν q0 sm;ν Δs

ð5Þ

ð6Þ

ν

The denominator M2,0 is necessary to normalize the area distribution

The probability H(s1, s2) of obtaining a chord length within a slice of height h2 − h1 is: qffiffiffiffiffiffiffiffiffiffiffiffiffiffi qffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 2 d −s21 − d −s22 d

:

ð3Þ

The probability distribution Hi(si, si + Δs) is calculated from this equation for a constant value Δs and for a lot of values si and si + Δs. Then we get the number density distribution q0(s) to Hi : Δs

ð4Þ

[8]. Figs. 2 and 3 show the number density distribution q0(s) and the area density distribution q2(s) for a spherical particle with diameter d = 100 μm and with Δs = 5 μm. These density distributions have a maximum very near to the diameter of the spherical particle. 3. Chord distribution of an ellipsoid An ellipsoid is a non-spherical particle which represents a wide range of shapes. In agreement with the chord measurement in a projected plane we have restricted the analysis to 2D. Then the ellipse is the non-circular 2D shape which can be characterized by the dimensionless elongation or by the circularity [9]. The equation that describes the ellipse is as follows: x2

The transformation of the number distribution to an area distribution is derived on the assumption that particle shape does not change

a

þ

 y 2 b

¼1

ð7Þ

where x and y are co-ordinates, and a and b are the semi-axis lengths with a N b. The elongation may be quantified by the aspect ratio a/b of the semiaxis lengths. For a two-dimensional particle projection image the proximity of the image to the outline of a circle can be defined by the circularity Eq. (8):

0.07 0.06

q0(s) [1/µm]

40

sm;i ¼ M 2;0

d 1 h1 ¼ − 2 2

q0 ðsÞ ¼

30

with size. To convert from a number distribution q0(s) to an area distribution q2(s) use the Eqs. (5) and (6). 

h2 −h1 ¼ H ðs1 ; s2 Þ ¼ d=2

20

Fig. 3. Area density distribution q2(s) of chord lengths by random cut of a spherical particle with diameter of 100 μm.

Fig. 1. Two chord lengths s1, s2 of a circle with uniform direction caused by the measurement.

h2 ¼

10

0.05

Ψp;pe ¼

d = 100 µm

0.04 0.03

0.02 0.01 0.00 0

10

20

30

40

50 60 sm [µm]

70

80

90 100 110

Fig. 2. Number density distribution q0(s) of chord lengths by random cut of a spherical particle with diameter of 100 μm.

pffiffiffiffiffiffiffiffi 2  πAp πxp πxp xp ¼ ¼ ¼ ≤1 Up Up πxpe xpe

ð8Þ

with the particle projection area Ap and the perimeter Up of the particle projection area. The diameter xp is the diameter of a circle having the same area as the projection area of the particle image and xpe is the diameter of a circle having the same perimeter as the particle image. The circularity squared equals the form factor [2]. Area Ap and perimeter Up of an ellipse can be calculated to Bronstein–Semendjajew [10]: Ap ¼ πab;

ð9Þ

D. Petrak et al. / Powder Technology 284 (2015) 25–31

27

" #  2      π 1 1  3 2 e4 1  3  5 2 e6 − −… U p ¼ 4aE e; e2 − ¼ 2πa 1− 3 5 2 2 24 246 pffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi 2 a2 −b e¼ ; a ð10Þ where E(e, π/2) is the complete elliptic integral of the second kind. An approximation for the perimeter is Eq. (11)  pffiffiffiffiffiffi U p ¼ π 1:5ða þ bÞ− ab :

ð11Þ

[10]. The accuracy of the perimeter calculation with Eq. (10) up to the tenth term is smaller than 0.3%. Fig. 4 shows the error Ep of the perimeter calculation by the approximation (11) which is smaller than 1.5%. Eq. (12) describes the circularity Ψp,pe of an ellipse with the semiaxis lengths a and b Ψp;pe ¼

pffiffiffiffiffiffi pffiffiffiffiffiffiffiffi 2 πAp 2 ab pffiffiffiffiffiffi ¼ Up 1:5ða þ bÞ− ab

ð12Þ

and the accuracy of the circularity is also smaller than 1.5%. To determine the chord probability distribution for an ellipse with semi-axis lengths a and b, we have used a numerical procedure as illustrated in Fig. 5 [11]. So the angle α and the co-ordinate xs of the chord are random values. There may be the possibility of developing an analytical solution. On each replication (α, xs) we get two equations for the determination of the chord length s: ðx  cos α þ y  sin α Þ2 ð−x  sin α þ y  cos α Þ2 þ ¼ 1: 2 a2 b

ð13Þ

x ¼ xs

ð14Þ

The solution of the equation system consists of the two co-ordinates ys1 and ys2 of the intersections between the chord and the ellipse. Then the chord length s is the sum s ¼ jys1 j þ jys2 j:

ð15Þ

Using all the calculated chords, the number density distribution is a normalized histogram which represents the relative quantity in every chord length interval. Figs. 6 and 7 show the number density distributions q0(s) for two ellipses with different semi-axis lengths a and b. With the increase of ratio

a/b the position of the maximum is shifted to smaller chord length classes. 4. Shape parameter The numerical determination of the chord probability distributions q0(s), q2(s) was realized for ellipses with different ratio a/b of the semi-axis lengths. The aim of these investigations was a connection between individual values of the distributions with the non-dimensional shape ratio a/b or the circularity Ψp,pe. There are three nondimensional shape parameters Pi which can describe the shape of the ellipse by means of the ratio a/b or the circularity Ψp,pe: - P1 = median (q2(s)) / median (q0(s)) - P2 = mode (q2(s)) / mode (q0(s)) - P3 = mode (q0(s)) / smax (q0(s)) where the median divides the distribution in two equal parts, the mode is the value which the frequency is the maximum and smax is the maximum of all chord lengths. The number and area density distributions q0(s) and q2(s) can be calculated for ellipses with different ratio a/b of the semi-axis lengths. The shape parameters Pi follow from the determination of the median, mode and smax. Figs. 8, 9, and 10 show the dependency of the three shape parameters Pi on the ratio a/b of the semi-axis lengths.

1.6 1.4

0.03

Ep = -0.0007(a/b)3 + 0.0266(a/b)2 - 0.0527a/b + 0.0395 R2 = 0.9993

1.2

0.025

q0(s) [1/µm]

Error Ep of the perimeter calculation [%]

Fig. 5. Chord length s by random cut of an ellipse with uniform direction caused by the measurement.

1 0.8

0.6

b = 40 µm a = 50 µm

0.02 0.015 0.01

0.4

0.005

0.2

0 0

0 1

2

3

4

5

6

7

8

9

10

10

20

30

40

50 60 sm [µm]

70

80

90 100 110

a/b Fig. 4. Accuracy of the perimeter calculation by the approximation of Eq. (11).___polynomial of the third order.

Fig. 6. Number density distribution q0(s) of chord lengths by random cut of an elliptical particle with semi-axis lengths a = 50 μm, b = 40 μm, a/b = 1.25 (40,000 chord lengths for 200 angles α and 200 co-ordinates xs).

D. Petrak et al. / Powder Technology 284 (2015) 25–31

q0 (s) [1/µm]

28

0.03

3.5

0.025

3

0.02

2.5

P2

0.015

2

0.01

1.5 0.005

1

0 0

10

20

30

40

50 60 sm [µm]

70

80

1

90 100 110

2

3

4

5

6

7

8

9

10

11

a/b

Fig. 7. Number density distribution q0(s) of chord lengths by random cut of an elliptical particle with semi-axis lengths a = 50 μm, b = 10 μm, a/b = 5 (40,000 chord lengths for 200 angles α and 200 co-ordinates xs).

With approximation to the sphere the values of the shape parameters Pi are equal 1. The shape parameter P1 can be used in the investigated range of the aspect ratio 1 ≤ a/b ≤ 10 and P2 and P3 have a limited range of approximately 1 ≤ a/b ≤ 5. The value of P3 is very sensitive to the coincidence of particles in the measuring volume. The dependency of the ratio a/b of the semi-axis lengths on the shape parameters Pi can be expressed by approximate functions fi a=b ¼ f i ðP i Þ:

ð16Þ

Eq. (17) describes the approximate function f1 for the shape parameter P1 = median (q2(s)) / median (q0(s)): a ¼ −55:35P 51 þ 431P 41 −1313:5P 31 þ 1962:3P 21 −1433:7P 1 b þ 410:34

ð17Þ

with a mean uncertainty of 3%. Eq. (18) describes the approximate function f2 for the shape parameter P2 = mode (q2(s)) / mode (q0(s)) for P2 ≤ 3.2 a ¼ 0:873P 52 −9:731P 42 þ 42:83P 32 −92:74P 22 þ 99:54P 2 −39:75 b

ð18Þ

with a mean uncertainty of 1%. Using the chord measurements the number and area density distributions q0(s) and q2(s) can be calculated. The next step is the determination of the median (q0(s)), median (q2(s)), mode (q2(s)), mode (q0(s)) and the values of P1 or P2 are equal median (q0(s)) / median (q2(s)) and mode (q2(s)) / mode (q0(s)). Then the aspect ratio a/b is given from Eqs. (17) or (18).

Fig. 9. Shape parameter P2 in dependence on the elongation or aspect ratio a/b.

By using Eq. (12) the circularity Ψp,pe can be calculated for different values of the semi-axis lengths a and b. The data can be fitted by an approximation function to  a a2 þ 0:0055 Ψp;pe ¼ 1:125−0:119 b b

ð19Þ

with a mean uncertainty of 2.4%. It should be noted here that the shape parameters Pi characterize the mean elongation or the mean circularity of the particle shape. The application of these shape parameters is limited to narrow particle distributions in size and shape. This is based on the calculation of the area density distribution q2(s) from the number density distribution q0(s). This calculation demands the same shape for all particles or a narrow distribution in particle shape. This is also based on the determination of the mode (q0(s)) and mode (q2(s)) with a high accuracy. The number density distribution should have only one maximum. An advantage is the simultaneous use of the measured chord lengths for the characterization of the particle size and the particle shape, too. 4. Process application The process application is necessary for the proof of the model. Two process examples describe the use of the model for the particle shape characterization. 4.1. Measurement technique The chord length distribution was measured by a modified spatial filtering technique (SFT) which is integrated in the IPP 70 probe of Parsum GmbH, Germany (Fig. 11). A single fiber for spot scanning and a differential-type fiber-optical spatial filter for velocity determination are arrayed together in the detector plane of the probe. The particles are illuminated by a parallel laser beam and the shadows cause a signal on the fiber-optical detector. The probe IPP 70 is constructed from stainless steel and has sapphire

2.5

1 0.8

2

0.6

P1

P3 1.5

0.4 0.2

1

0

1

2

3

4

5

6

7

8

9

10

11

a/b Fig. 8. Shape parameter P1 in dependence on the elongation or aspect ratio a/b.

1

2

3

4

5

a/b Fig. 10. Shape parameter P3 in dependence on the elongation or aspect ratio a/b.

D. Petrak et al. / Powder Technology 284 (2015) 25–31

29

Fig. 11. Illustration of the SFT optical probe.

Fig. 12. a) Seed particles before coating; b) seed particles after coating.

windows. It is suitable for chord measurements in the size range of 50 μm–6000 μm, with velocities of between 0.01 ms−1 and 50 ms−1. The probe can be installed directly in a process line to provide real-time analysis. A range of accessories enables the application to particle systems with high concentration. By feeding compressed air or other gases to the measuring volume, the optical windows are kept clear using different flushing cells. Additionally, a gas-in-line disperser can be used to dilute and disperse the sample flow if the particle concentration is too high [4]. 4.2. Application case: particle coating In the beginning of a coating process, the particle characterization shows very often a narrow size distribution combined with a narrow

shape distribution. Therefore, the shape parameters can be used for detecting the particle shape during the coating process time. A first example describes the coating of elliptical seed particles in an open drum coater. Fig. 12 shows some seed particles at the start point of the coating process and at the end point and in Figs. 13 and 14 the seed particles are characterized in relation to their elongation ratio a/b and pffiffiffiffiffiffiffiffiffiffiffiffiffiffi the equivalent circular diameter xp ¼ 4Ap =π by using an image analysis [2]. The image analysis is based on a manual microscopic evaluation. According to Figs. 13 and 14, the start distributions of the seed particles are narrow in shape and size. During the coating process the seed particles change their shape from elliptic to nearly spherical. The change of particle shape could be detected by application of the shape parameter. A probe system IPP 70 was used for the in-line measurement of chord lengths. Figs. 15, 16 and 17 show the change of the

image analysis 250

frequency

End Coating

frequency

200 Start Coating

150 100 50

160 140 120 100 80 60 40 20 0 1.0

0 1

2

3

4

5

6

1.5

2.0 2.5 xp [mm]

3.0

3.5

a/b Fig. 13. Image analysis of the seed particles relating to the frequency of the aspect ratio a/b.

Fig. 14. Image analysis of the seed particles relating to the frequency of the equivalent circular diameter xp in the process start.

30

D. Petrak et al. / Powder Technology 284 (2015) 25–31

1.7 1.6 1.5

P1

1.4 1.3 1.2 1.1 1 0

10

20

30

40

50

60

process time [min] Fig. 15. Shape parameter P1 = median (q2(s)) / median (q0(s)) in dependence on the process time of coating. Fig. 18. Example dispersion of coated pellets.

5.0 4.5

particles on the glass plate. 2800 particles were analyzed in relation to the circle equivalent diameter xp, aspect ratio a/b and circularity Ψp,pe:

4.0 3.5

a/b

3.0 2.5 2.0 1.5 1.0

0

10

20

30

40

50

60

process time [min]

Using the chord measurements and the shape parameter P1 and P2 the mean particle shape is characterized by:

Fig. 16. Aspect ratio a/b in dependence on the process time of coating.

shape parameter P1 = median (q2(s)) / median (q0(s)), the aspect ratio a/b and the circularity Ψp,pe over the process time by using the approximate function a/b = f1(P1) and Eq. (19). The uncertainties of the aspect ratio a/b and the circularity can be determined by the comparison with the mean values of the image analysis. The error bars have a value of ±8% in both cases. A second example describes the determination of aspect ratio and circularity of coated pellets (Cellets®1000 with coating of Natriumbenzoat, 33% in water as spraying liquid). The lab-scale process equipment was a GF3 Wurster coater with bottom spray (Glatt Ingenieurtechnik Weimar, Germany). Samples of coated particles were characterized by a Morphologi G3SE (Malvern Instruments, Malvern, UK). For the in-line chord measurements the probe IPP 70 was arranged in the downbed zone between outer wall and Wurster tube. The Morphologi G3SE uses microscopic technique with a software package for the measurement of the particle size and shape of the dispersed particles. Fig. 18 shows a microscopic image of the dispersed

1.0 0.9 0.8 0.7 0.6 p,pe

0.5 0.4 0.3 0

10

20

30

40

50

process time [min] Fig. 17. Circularity Ψp,pe in dependence on the process time of coating.

mean xp: 1483.4 μm with standard deviation 129.8 μm, minimum 1090 μm, maximum 2082 μm, mean a/b: 1.08 with standard deviation 0.066, minimum 1.0 μm, maximum 1.88, mean Ψp,pe: 0.941 with standard deviation 0.049, minimum 0.271, maximum 0.984.

60

mean a/b: 1.19 with P1 and 1.0 with P2 mean Ψp,pe: 0.99 with P1 and 1.0 with P2 The uncertainties of the aspect ratio and the circularity can be determined by the mean values of the image analysis to approximately ±8%. There is a good agreement between the results of the image analysis and the application of the shape parameter. The determination of the aspect ratio a/b or the circularity Ψp,pe by the shape parameter can be used as an input signal for the control system of the coating process or to estimate the uniformity of the layer. 5. Conclusions This paper describes the 2D determination of the particle shape by chord measurements. The shape of particles influences the particle behavior in which they flow, pack together and react chemically or physically. Some methods for in-situ particle sizing provide on-line information about the chord length distribution of a population of particles. The frequency of the chord lengths depends also on the particle shape. An ellipsoid is a non-spherical particle which represents a wide range of shapes. In agreement with the chord measurement in a projected plane we have restricted the analysis to 2D. The chord distribution for an ellipse in random orientation is calculated for different aspect ratios a/b up to 10. It was found that the circularity Ψp,pe can be calculated from the aspect ratio a/b with an uncertainty smaller than 1.5%. Three non-dimensional parameters are suitable for the determination of an elongation or circularity value. The parameters are derived from the mean, mode and maximal chord length of the number and area based chord distributions. The shape parameter P1 based on the mean can be used in the investigated range of the aspect ratio 1 ≤ a/b ≤ 10 and P2 and P3 have a limited range of approximately 1 ≤ a/b ≤ 5. The application of these shape parameters is limited to narrow particle distributions in size and shape.

D. Petrak et al. / Powder Technology 284 (2015) 25–31

Two applications were shown for coating processes of elliptical seed particles and spherical pellets (Cellets®1000). Results of the image analysis were in a good correlation with the results of the chord measurements. The uncertainty of the mean aspect ratio or circularity determined by the chord measurements is approximately ±8%. An advantage is the simultaneous use of the measured chord lengths for the characterization of the particle in size and shape without any need for additional measurement equipment. Another advantage is the in-line determination of the particle shape without taking a powder sample. The presented determination of the elongation value might be of interest in some fields of in-line process monitoring related to the particle size and simultaneously to the particle shape. The in-situ determination of the particle shape can be a way for looking on the development of agglomerates during the processes. Future investigations are necessary for different particle characteristics. Symbols and abbreviations a long semi-axis length of an ellipse particle projection area Ap b short semi-axis length of an ellipse d particle diameter for a sphere f frequency of a distribution approximate function fi H probability median (s) median chord length value mode (s) value at which the frequency of the density distribution is a maximum shape parameter Pi density distribution by number q0(s) density distribution by area q2(s) s chord length size above which there are no chord lengths smax Δs width of the chord length interval SFT spatial filtering technique perimeter of the particle projection area Up x particle size, co-ordinate diameter of a circle having the same area as the particle proxp jection area diameter of a circle having the same perimeter as the particle xpe projection area y co-ordinate α angle circularity Ψp,pe

31

[5] P.A. Langston, A.S. Burbidge, T.F. Jones, M.J.H. Simmons, Particle and droplet size analysis from chord measurements using Bayes' theorem, Powder Technol. 116 (2001) 33–42. [6] H.H.J. Bloemen, M.G.M. De Kroon, Transformation of chord length distributions into particle size distributions using least squares techniques, Part. Sci. Technol. 23 (2005) 377–386. [7] E.E. Underwood, Quantitative Stereology, Addison-Wesley Publishing Company, 1970. [8] T. Allen, Particle Size Measurement, fifth ed. Chapman & Hall, London, 1997. [9] ISO 9276-6:2008, Descriptive and quantitative representation of particle shape and morphology. [10] I.N. Bronstein, K.A. Semendjajew, Taschenbuch der Mathematik, B. G. Teubner, Leipzig, 1960. [11] P.A. Langston, T.F. Jones, Non-spherical 2-dimensional particle size analysis from chord measurements using Bayes' theorem, Part. Part. Syst. Charact. 18 (2001) 12–21. Prof. Dr.-Ing. Dieter Petrak, Study of Physics at the University of Jena, PhD at the University of Weimar to the numerical simulation of particle-laden gas flows, habilitation thesis to optical measuring methods for two-phase flows, Research engineer in the industry (ZAB Dessau), Head of a research group at the Institute of Mechanics of the Academy of Sciences in Berlin and Chemnitz, until 2010 Professor at Chemnitz University of Technology with research fields: flow mechanics and mechanical process engineering.

Dipl.-Ing. Stefan Dietrich, Study of Technology of Scientific Apparatus Engineering at the University of Jena with graduation Dipl.-Ing., Research work at Institute of Mechanics Karl-Marx-Stadt, Department of Scientific Instruments, at Chemnitz University of Technology, Research Group of Multiphase Flow, since 1998 Joint Managing Director of Parsum GmbH, Chemnitz, Field of interest: Fiber-optical systems for flow and particle measurement and the industrial application.

Dr.-Ing. Günter Eckardt, Study of Automation Technology with specialization of Engineering Cybernetics at the Technical University of Karl-Marx-Stadt with graduation Dr.-Ing., Research work at electrical appliance industry EAW Treptow, Berlin, Department Research and Development, at Institute of Mechanics Karl-Marx-Stadt, Department of Rheology, at Chemnitz University of Technology, Research Group of Multiphase Flow, since 1998 Managing Director and authorized officer of Parsum GmbH, Chemnitz, Field of interest: Fiber-optical systems for flow and particle measurement and the industrial application.

Acknowledgment This work was supported by the German Federal Ministry of Education and Research (project number 03WKBQ07C). References [1] M.N. Pons, H. Vivier, K. Belaroui, B. Bernard-Michel, F. Cordier, D. Oulhana, J.A. Dodds, Particle morphology: from visualization to measurement, Powder Technol. 103 (1999) 44–57. [2] J.C. Russ, The Image Processing Handbook, third ed. CRC Press, 1998. [3] A.R. Heath, P.D. Fawell, P.A. Bahri, J.D. Swift, Estimating average particle size by focused beam reflectance measurement (FBRM), Part. Part. Syst. Charact. 19 (2002) 84–95. [4] D. Petrak, S. Dietrich, G. Eckardt, M. Köhler, In-line particle sizing for real-time process control by fibre-optical spatial filtering technique (SFT), Adv. Powder Technol. 22 (2011) 203–208.

Dr.-Ing. Michael Köhler, Study of Electrical Engineering/ Microelectronics with main focus Semiconductor Technology at the Technical University of Karl-Marx-Stadt with graduation. Dr.-Ing.: Design, Production and Analysis of pHSensors—Ion Sensitive Field Effect Transistor (ISFET), Research work at Chemnitz University of Technology, Research Group of Multiphase Flow, since 1998 Managing Director of Parsum GmbH, Chemnitz, Field of interest: Fiber-optical systems for flow and particle measurement and the industrial application.