Abstract:In the fault identification and diagnosis of gear pump, mechanical signals have such problems as high signal acquisition cost, low signal-to-noise ratio and difficulty in obtaining fault characteristics. To solve these problems, a fault identification method for hydraulic gear pump was presented based on motor current signal.The feasibility of identifying gear pump fault by driving motor current signal was analyzed.The parameters of the VMD method were optimized.Then, the correlation of IMF components was analyzed and the current signal was reconstructed according to the operating conditions of the gear pump.Based on the characteristic samples constructed by the entropy and root mean square, KFCM clustering algorithm was fused to identify and diagnose gear pump faults.At last, the experiments for gear pumps with different fault types were carried out on the electromechanical hydraulic test bench. The experimental results show that the current signal analysis and feature extraction method can be used to identify gear pump faults accurately and effectively.