A dynamic load identification method for rock roadheaders based on wavelet packet and neural network

Abstract

As a part of automatic control system of the rock roadheader, the identification of dynamic load is of great significance to improve the intelligent level and increase lifetime of roadheaders. In order to solve the problem of rock roadheaders such as dynamic load real-time identification, a recognition method based on wavelet packet and neural network is proposed. The vibration signals, the current and hydraulic cylinder pressure signals are collected in real time. The characteristic vectors of the corresponding signals, which are chosen as input values for the neural network, are gained through wavelet packets decomposition. It has shown by experiments that the accuracy rate of dynamic load realtime identification is up to 0.93 and such a method can meet the requirement of dynamic load real-time identification system.