Purpose - The use of pneumatic conveying of solid bulk over long distance has become a popular technique due to low operational cost, low maintenance requirement, layout flexibility and ease of automation. The purpose...
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Purpose - The use of pneumatic conveying of solid bulk over long distance has become a popular technique due to low operational cost, low maintenance requirement, layout flexibility and ease of automation. The purpose of this paper is to identifity the flow regime in a pneumatic conveyor system by electrodynamic sensor placed around the pipe using fuzzy logic tools. Design/methodology/approach - Electrical charge tomography is used to detect the existence of inherent charge on the moving particles through the pipe. linear back projection algorithm and filtered backprojectionalgorithm are employed to produce tomography image. Baffles of different shapes are inserted to create various flow regimes, such as full flow, three quarter flow, half flow and quarter flow. Fuzzy logic tools are used to identify different flow regimes and produce filtered back concentration profiles for each flow regime. Findings - The results show significant improvement in the pipe flow image resolution and measurement. Originality/value - This paper presents a flow identifier method using electrical charge tomography and fuzzy logic to monitor solid particles flow in pipeline.
An image reconstruction algorithm based on regularization optimization for Process Tomography is proposed in this paper. Through the comparison of the images reconstructed by linear back projection algorithm, Sensitiv...
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ISBN:
(纸本)9781424409723
An image reconstruction algorithm based on regularization optimization for Process Tomography is proposed in this paper. Through the comparison of the images reconstructed by linear back projection algorithm, Sensitivity Coefficient algorithm, singular value decomposition algorithm and the regularization optimization algorithm proposed in this paper, it is apparent that images can be reconstructed clearly and quickly by the regularization optimization algorithm. The regularization optimization algorithm is a very good image reconstruction algorithm both in image quality and the reconstruction speed.
An image reconstruction algorithm based on regularization optimization for Process Tomography is proposed in this *** the comparison of the images reconstructed by linear back projection algorithm, Sensitivity Coeffic...
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An image reconstruction algorithm based on regularization optimization for Process Tomography is proposed in this *** the comparison of the images reconstructed by linear back projection algorithm, Sensitivity Coefficient algorithm, singular value decomposition algorithm and the regularization optimization algorithm proposed in this paper, it is apparent that images can be reconstructed clearly and quickly by the regularization optimization *** regularization optimization algorithm is a very good image reconstruction algorithm both in image quality and the reconstruction speed.
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