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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.