Research and Application of Coal Blockage Early Warning Judgment in Coal Pulverizing System of Thermal Power Generating Units

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 de...

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Bibliographic Details
Published inIEEE journal of radio frequency identification (Online) Vol. 6; pp. 911 - 916
Main Authors Cai, Junyu, Chen, Weiwen, Wang, Delei, Ding, Ning, Zhang, Jiangfeng, Dong, Libin, Zhang, Xinsheng, Cai, Pingping
Format Journal Article
LanguageEnglish
Published Piscataway IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Boilers
Coal
coal pulverizing system
early warning judgment
Failure modes
False alarms
Fault detection
Fault diagnosis
Generator set
Grinding (comminution)
plugging coal
Power generation
Power systems
Temperature distribution
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Summary: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.
ISSN:2469-7281
2469-729X
DOI:10.1109/JRFID.2022.3212441