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In order to increase the diagnosis efficiency of plunger wear fault, a recognition method is developed using sensitivity analysis and probability neural network. Firstly, 17 time domain characteristics of vibration signal are extracted. Then analyzed the sensitivity of characteristics to failure to select sensitive characteristics parameters. Finally, PNN method to identify the degree of plunger wear was proposed. A hydraulic pump fault simulation experiment was designed, and validated the proposed method by experimental data. The results show that the method can quickly and effectively identify the degree of plunger wear.

A recognition method of plunger wear degree of plunger pump using probability neural network