Abstract:The mechanical arm of mining equipment is a component with flexible structure. During mining work, the mechanical arm is subjected to heavy load and strong impact, which affects the mining efficiency and working stability of the equipment and leads to equipment failure. Mining equipment work environment is complicated, vibration signal acquisition and fault analysis work is more difficult. Taking the rocker arm of shearer as an example, in order to test the vibration signal of the mechanical arm of mining equipment, a test platform simulating the vibration signal of the rocker arm of shearer is designed. The vibration signals of the rocker arm under various working conditions are collected experimentally, and the network model for analyzing the transverse vibration data of the rocker arm is established. The lateral vibration model of rocker arm is fitted by neural network, which greatly reduces the error of manual analysis and provides data basis for mining equipment working condition monitoring and fault prediction.
