Abstract
This paper introduces the mechanism-based fault diagnosis model of the main equipment of the milling system, and adopts the trend state detection and failure mode recognition methods according to the detection data for comprehensive diagnosis. The experimental results show that it can effectively detect the coal blocking and coal breaking faults of the coal feeder and the coal mill, effectively reduce the system false alarm rate, accurately capture the abnormal moment of the indicator, and relatively manual observation is a little early, ensuring the stable operation of the milling system, reducing the workload of the operating personnel and improving the safety and economy of the unit.
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CITATION STYLE
Cai, J., Chen, W., Wang, D., Ding, N., Zhang, J., Dong, L., … Cai, P. (2022). Research and Application of Coal Blockage Early Warning Judgment in Coal Pulverizing System of Thermal Power Generating Units. IEEE Journal of Radio Frequency Identification, 6, 911–916. https://doi.org/10.1109/JRFID.2022.3212441
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