Simultaneous Measurement of Particle Size and Particle Velocity by the Spatial Filtering Technique

Petrak, D.

doi:10.1002/ppsc.200290002

Cited by 53 publications

(32 citation statements)

References 11 publications

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“…The most significant change in particle size analysis technology has been attributed to the shift of measurement techniques towards methods that are based on the interaction of particles with light. Petrak (2002) developed a method of using fibre-optic spatial filtering velocimetry (SFV), modified by fibre-optical spot scanning (FSS), in order to determine the particle size. Spatial filtering velocimetry is a method of determining the velocity of an object by observing it through a spatial filter in front of a receiver.…”

Section: Literature Reviewmentioning

confidence: 99%

“…The details of which have been explained in the paper by Aizu and Asakura (1987). The modified spatial filtering technique as described by Petrak (2002) employs fibre-optical spot scanning (FSS) as an addition to the SFV. Fibre-optical spot scanning observes the projected shadow of a particle as it moves across an optical fibre.…”

Section: Literature Reviewmentioning

confidence: 99%

“…13. The width of the shadow (or chord length) is dependent on the particle size, the particle velocity, and the random spatial location of the particle and fibre (Petrak, 2002). In this way the chord length of the projected surface of an individual particle is measured.…”

Section: Literature Reviewmentioning

confidence: 99%

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Mass flow and particle size monitoring of pulverised fuel vertical spindle mills

Archary

Schmitz

Jestin

2016

Chemical and Process Engineering

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The first step towards condition based maintenance of the milling plant is the implementation of online condition monitoring of the mill. The following paper presents and analyses methods of monitoring the key performance factors of a vertical spindle mill that is suited for implementation on older power stations, i.e. the quantity (mass flow rate) and quality (particle fineness) of the pulverised fuel produced by the mill. It is shown herein that the mill throughput can be monitored on-line using a simple mill energy balance that successfully predicts the coal throughput within 2.33% as compared to a calibrated coal feeder. A sensitivity analysis reveals that the coal moisture is a critical measurement for this method to be adopted as an on-line mass flow monitoring tool. A laser based particle size analyser tool was tested for use in the power plant environment as an online monitoring solution to measure pulverised fuel fineness. It was revealed that several factors around the set-up and operation of the instrument have an influence on the perceived results. Although the instrument showed good precision and repeatability of results, these factors must be taken into account in order to improve the accuracy of the reported results before the instrument can be commissioned as an on-line monitoring solution.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

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Mass flow and particle size monitoring of pulverised fuel vertical spindle mills

Archary

Schmitz

Jestin

2016

Chemical and Process Engineering

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“…The SFV technique measures simultaneously the velocity and the chord length distribution of particles as they pass through the laser light and cast a shadow onto the detector (Petrak, 2002;Petrak and Rauh, 2006). The measurement cell of the SFV probe is equipped with sapphire windows that are kept clean via an internal compressed air supply system, preventing window fouling.…”

Section: Introductionmentioning

confidence: 99%

Batch statistical process control of a fluid bed granulation process using in-line spatial filter velocimetry and product temperature measurements

Burggraeve

Kerkhof²,

Hellings³

et al. 2011

European Journal of Pharmaceutical Sciences

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Fluid bed granulation is a batch process, which is characterized by the processing of raw materials for a predefined period of time, consisting of a fixed spraying phase and a subsequent drying period. The present study shows the multivariate statistical modeling and control of a fluid bed granulation process based on in-line particle size distribution (PSD) measurements (using spatial filter velocimetry) combined with continuous product temperature registration using a partial least squares (PLS) approach. Via the continuous in-line monitoring of the PSD and product temperature during granulation of various reference batches, a statistical batch model was developed allowing the real-time evaluation and acceptance or rejection of future batches. Continuously monitored PSD and product temperature process data of 10 reference batches (X-data) were used to develop a reference batch PLS model, regressing the X-data versus the batch process time (Y-data). Two PLS components captured 98.8% of the variation in the X-data block. Score control charts in which the average batch trajectory and upper and lower control limits are displayed were developed. Next, these control charts were used to monitor 4 new test batches in real-time and to immediately detect any deviations from the expected batch trajectory. By real-time evaluation of new batches using the developed control charts and by computation of contribution plots of deviating process behavior at a certain time point, batch losses or reprocessing can be prevented. Immediately after batch completion, all PSD and product temperature information (i.e., a batch progress fingerprint) was used to estimate some granule properties (density and flowability) at an early stage, which can improve batch release time. Individual PLS models relating the computed scores (X) of the reference PLS model (based on the 10 reference batches) and the density, respectively flowabililty as Y-matrix, were developed. The scores of the 4 test batches were used to examine the predictive ability of the model.

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“…The Focused beam reflectance method (FBRM) and spatial filtering technique (SFT) can be used for in-line particle size determination in fluid bed processes. Both methods determine the chord length of particles using a special probe (7,8). The FBRM has been largely applied in crystallization processes, but its usability in fluid bed processes has not been well documented.…”

Section: Introductionmentioning

confidence: 99%

A New Rapid On-Line Imaging Method to Determine Particle Size Distribution of Granules

et al. 2008

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Abstract. The purpose of this research was to study the feasibility of the new image analysis method in the particle size determination of the granules. The method is capable of forming a three-dimensional topographic image of a sample surface from a digital picture. In the method, a flat granule bed surface was illuminated from three different directions, using the three primary colors (red, green, and blue). One color picture was taken by a digital camera, after which a topographic image of the object surface was constructed. The particle size distribution was then calculated from the image data. The particle size analysis method was tested both off-line and on-line. Off-line particle size measurement results determined by the image analysis method corresponded quite well to those of sieve analysis in the size fraction range 250-1,000 μm. In on-line application, images were successfully retrieved and median granule size trend could be calculated and followed during fluid bed granulations.

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Simultaneous Measurement of Particle Size and Particle Velocity by the Spatial Filtering Technique

Cited by 53 publications

References 11 publications

Mass flow and particle size monitoring of pulverised fuel vertical spindle mills

Mass flow and particle size monitoring of pulverised fuel vertical spindle mills

Batch statistical process control of a fluid bed granulation process using in-line spatial filter velocimetry and product temperature measurements

A New Rapid On-Line Imaging Method to Determine Particle Size Distribution of Granules

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