Intelligent recognition of cutting load of coal mining equipment based on vibration wavelet packet feature

In order to solve the problem of indirect identification of cutting load, a method of feature extraction based on vibration signal analysis and processing is presented. This method takes the shearer rocker arm level vibration signal as the object, using the empirical formula to improve the vibration signal is decomposed into several effective time-frequency features, improved the classical wavelet packet method of aliasing and endpoint effect phenomenon, selects the energy characteristics of each order value, explore the relationship between the characteristic value and the coal mining machine payload the. The results show that the analysis of the signal acquisition system of a coal mining machine structure does not change the method, not affect the normal operation of coal mining machine, easy to implement long-term online monitoring, for a large number of basic data collection, in order to improve the quantitative load cutting hardness recognition accumulated data.