An Intelligent Fault Diagnosis and Life Prediction Method for Rocker Arm of Shearer

Abstract

An intelligent fault diagnosis and life prediction method for the rocker arm of a shearer. After measuring the time-domain vibration signals of different shafting parts and different degrees of fault damage of the rocker arm of a shearer under different models and working conditions, the calculation After the characteristic values ​​in the time domain and frequency domain, based on the deep learning of big data, the intelligent algorithm analysis function is constructed, and the weight coefficient of the analysis method is determined to locate the fault point. Further, the remaining service life is calculated by using the polynomial fitting equation through mathematical statistical methods. Intelligent calculation of service life under high confidence conditions. The invention introduces the data-driven multi-angle analysis method into the fault diagnosis of the rocker arm of the coal shearer, which can accurately and intelligently locate the faulty shafting and components step by step, and further predict and calculate the remaining service life of the rocker arm of the coal shearer.

Description

technical field [0001] The invention relates to the technical field of coal shearers, in particular to an intelligent fault diagnosis and life prediction method for rocker arms of coal shearers. Background technique [0002] At present, coal is still the main energy source in my country, accounting for 64% of the energy structure. As the main equipment of coal mine electromechanical equipment in the fully mechanized mining production process, the coal shearer plays a vital role in the mechanized, efficient and safe fully mechanized mining process. , the level of its start-up rate is closely related to the coal output, if the coal shearer breaks down. It is bound to cause great economic losses. As the most important executive part of the fully mechanized mining system, the rocker arm of the coal mining machine is often disturbed by harsh working environments such as shock and dust during the working process, becoming the most frequent fault area, which greatly affects the coa...

AI Technical Summary

Problems solved by technology

[0003] However, the rocker arm of a coal mining machine is a complex system integrating machinery, electricity, and hydraulics. The fault characteristic frequency is modulated by multiple levels, and there is a complex multi-shaft coupling relationship. Monitoring and diagnosis must face nonlinear operating characteristics and complex work. situation

The defect of the current fault diagnosis method based on manual experience lies in the small range and low accuracy of relying on experience; the defect of the fault diagnosis method based on signal analysis lies in the low efficiency of signal processing

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