Electrostatic sensors applied to the measurement of electric charge transfer in gas–solids pipelines

Woodhead, Steve; Denham, John; Armour-Chelu, David

doi:10.1088/1742-6596/15/1/018

Cited by 10 publications

(5 citation statements)

References 5 publications

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“…A higher mass flow of particles and a higher velocity induced higher electrostatic signals. The same observations were reported in [1,23] and [7]. Fig.…”

Section: Fig 5 Electrostatic Signal In Relation To Particles' Sizesupporting

confidence: 88%

“…In pneumatic transport, solid particles become electrostatically charged due to particles-to-duct friction, particles-to-particles friction, and particles-to-gas friction. The direct current (DC) that flows between the electrostatic sensor and the ground is caused by the charge being released from the particles to the sensor during their direct contact [23]. In addition, there are alternations of the current (AC) induced by the charged particles [24] bypassing the sensor.…”

Section: Parameters Influencing the Electrostatic Mass-flow Measurementmentioning

confidence: 99%

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An electrostatic measuring technique for monitoring particle size in dilute pneumatic transport

Kuštrin

Jurjevčič²,

Senegačnik

2020

THERM SCI

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The goal of this research is to establish the applicability of an electrostatic measuring technique for monitoring the quality of a coal-milling process in direct-firing systems. Such systems are used in large steam boilers fired with low-rank coal where the pulverized coal is transported pneumatically from the mills to the burner nozzles via ducts with large cross-sections. The electrostatic measuring method, in connection with intrusive rod-type sensors, was studied because it provides good spatial sensitivity and cost effectiveness. A laboratory test rig was constructed, where the pulverized coal carried by ambient air was employed for the experiments emulating the pneumatic transport of coal particles in direct-firing systems. The test rig enables an extensive variation of the most influential parameters, like the mass flow, the velocity and the size of the particles. A linear, multiregression analysis of the results of the experiments was carried out and the appropriate regression model enabling a determination of the mean diameter of the particles using the electrostatic signal was chosen. Based on the results of the study the electrostatic measuring technique can be used for monitoring the size of pneumatically transported particles. The appropriate regression model needs to be chosen for each particular application to describe the dependency of the acquired electrostatic signal on the influential parameters of the pneumatic transport.

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“…A higher mass flow of particles and a higher velocity induced higher electrostatic signals. The same observations were reported in [1,23] and [7]. Fig.…”

Section: Fig 5 Electrostatic Signal In Relation To Particles' Sizesupporting

confidence: 88%

Section: Parameters Influencing the Electrostatic Mass-flow Measurementmentioning

confidence: 99%

An electrostatic measuring technique for monitoring particle size in dilute pneumatic transport

Kuštrin

Jurjevčič²,

Senegačnik

2020

THERM SCI

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“…In order to understand the electrodynamics sensor, a suitable mathematical model is inevitable. The corresponding mathematical models are discussed in detail by the researchers (Xu et al, 2007;Williams and Beck, 1995;Woodhead et al, 2005).…”

Section: Electrodynamics Sensormentioning

confidence: 99%

Image Reconstruction Algorithm for Electrical Charge Tomography System

Rahmat¹,

Isa²,

Jusoff³

et al. 2010

American Journal of Applied Sciences

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Problem statement: Many problems in scientific computing can be formulated as inverse problem. A vast majority of these problems are ill-posed problems. In Electrical Charge Tomography (EChT), normally the sensitivity matrix generated from forward modeling is very ill-condition. This condition posts difficulties to the inverse problem solution especially in the accuracy and stability of the image being reconstructed. The objective of this study is to reconstruct the image cross-section of the material in pipeline gravity dropped mode conveyor as well to solve the ill-condition of matrix sensitivity. Approach: Least Square with Regularization (LSR) method had been introduced to reconstruct the image and the electrodynamics sensor was used to capture the data that installed around the pipe. Results: The images were validated using digital imaging technique and Singular Value Decomposition (SVD) method. The results showed that image reconstructed by this method produces a good promise in terms of accuracy and stability. Conclusion: This implied that LSR method provides good and promising result in terms of accuracy and stability of the image being reconstructed. As a result, an efficient method for electrical charge tomography image reconstruction has been introduced.

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“…Electrodynamic sensors consist of two major functional parts; the sensing electrode and the signal conditioning electronics (Woodhead et al, 2005). The function of the sensing electrode is to detect electric charge in its sensing region.…”

Section: Introductionmentioning

confidence: 99%

“…Electrical charge tomography uses electrodynamic sensors, which detect induced charge and convert it to a voltage (Xu et al , 2009). Electrodynamic sensors consist of two major functional parts; the sensing electrode and the signal conditioning electronics (Woodhead et al , 2005). The function of the sensing electrode is to detect electric charge in its sensing region.…”

Section: Introductionmentioning

confidence: 99%

Application of neural network and electrodynamic sensor as flow pattern identifier

Rahmat

Sabit

Rahim³

2010

Sensor Review

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PurposeSolid particles flowing in a pipeline is a common mode of transport in industries. This is because pipeline transportation can avoid waste through spillage and minimizes the risk of handling of hazardous materials. Pharmaceutical industries, food stuff manufacturing industries, cement, and chemical industries are a few industries to exploit this transportation technique. For such industries, monitoring and controlling material flow through the pipe is an essential element to ensure efficiency and safety of the system. The purpose of this paper is to present electrical charge tomography, which is one of the most efficient, robust, cost‐effective, and non‐invasive tomographic methods of monitoring solid particles flow in a pipeline.Design/methodology/approachProcess flow data are captured by fitting an array of 16 discrete electrodynamic sensors about the circumference of the flow pipe. The captured data are processed using two tomographic algorithms to obtain tomographic images of the flow. Then a neural network tool is used to improve image resolution and accuracy of measurements.FindingsThe results from the above technique show significant improvements in the pipe flow image resolution and measurements.Originality/valueThe paper presents electrical charge tomography, which is one of the most efficient, robust, cost‐effective, and non‐invasive tomographic methods of monitoring solid particles flow in a pipeline.

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Electrostatic sensors applied to the measurement of electric charge transfer in gas–solids pipelines

Cited by 10 publications

References 5 publications

An electrostatic measuring technique for monitoring particle size in dilute pneumatic transport

An electrostatic measuring technique for monitoring particle size in dilute pneumatic transport

Image Reconstruction Algorithm for Electrical Charge Tomography System

Application of neural network and electrodynamic sensor as flow pattern identifier

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