Research on the Application of Intelligent Diagnosis of Major Equipment Failures in Coal Mines

Abstract

Currently, the implementation of a coal mine production safety monitoring system, capable of real-time monitoring of the safety condition of large coal mine equipment and timely dispatch management, is crucial for the efficient and safe operation of coal mine enterprises. This paper designs the coal mine major equipment failure process based on the rolling bearing’s vibration mechanism, analyzes the major equipment’s failure signal using both time domain and frequency domain analysis methods, and employs the intelligent fuzzy control method to identify the major equipment failure. We have designed and practically applied a real-time, multi-threaded, and comprehensive fault diagnosis and prediction system for coal mine major equipment, combining information from coal mine safety, production, and operation. The results show that the normal state’s time-domain amplitude approximates (-0.2, 0.2), and the time-domain waveforms all display periodic shock signals when the bearing sustains damage. The faulty vibration amplitude of the inner ring is within 0.08 ms 2 and the faulty vibration amplitude of the outer ring is within 0.44 ms 2, and the diagnostic accuracy using the method of this paper reaches 97.2%. This study demonstrates the effectiveness of remote monitoring and fault analysis of major equipment in coal mines, which effectively improves the equipment start-up rate and ensures coal mine production safety.