Coal mining machine prediction diagnosis and health management method based on multi-source data fusion

Abstract

The invention provides a coal cutter prediction diagnosis and health management method based on multi-source data fusion, and belongs to the field of coal mine intellectualization. Comprising a multi-source data acquisition and fusion module, an abnormal working condition real-time monitoring module, a fault diagnosis module, a residual life prediction module and a maintenance decision suggestion module. The working state of the coal mining machine can be monitored in real time through the abnormal working condition real-time monitoring module, faults can be positioned and fault types can be determined in time through the fault diagnosis module, and the residual life of the coal mining machine can be predicted in time through the residual life prediction module. The maintenance decision suggestion module can provide a maintenance strategy for the coal mining machine in time, so that the system can accurately evaluate and forecast the operation health state of the coal mining machine in time, enables the coal mining machine to be in an optimal working state, can greatly improve the reliability of the coal mining machine, avoids unnecessary shutdown, and improves the safety of the coal mining machine. And the coal mining machine is ensured to exert the maximum working capacity, and the method has important significance on guaranteeing the operation reliability and safety of a coal mining system.

Description

technical field [0001] The invention relates to the technical field of coal mine intelligence, in particular to a method for prediction, diagnosis and health management of a coal shearer based on multi-source data fusion. Background technique [0002] The normal operation of the electric traction shearer determines the production efficiency of the fully mechanized mining face. However, the underground working environment is very harsh. The shearer is not only subjected to huge impact loads such as coal and rocks during operation, but also coal dust, gas, etc. In addition, the key components of the shearer will inevitably be worn and damaged during the long-term operation, resulting in the failure of the shearer from time to time. Therefore, it is necessary to carry out research on the health management technology of shearers, to make timely and accurate assessment and forecast of the health status of shearers, and to schedule the shearers in real time according to the operat...

AI Technical Summary

Problems solved by technology

[0002] The normal operation of the electric traction shearer determines the production efficiency of the fully mechanized mining face. However, the underground working environment is very harsh. During operation, the shearer is not only subjected to huge impact loads from coal and rocks, but also subjected to coal dust, gas, etc. pollution, and the key components of the shearer will inevitably be worn and damaged during the long-term operation, resulting in failures of the shearer from time to time

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