The accurate identification of mechanical manufacturing equipment conditions is important for determining the current health status and stability of equipments and doing scientific evaluation of the operational efficiency of equipment operators.An improved zero crossings with peak amplitude (ZCPA) auditory model optimized by a genetic algorithm was used to extract the characteristics of the vibration signal of the device,and the current condition of the device was identified by the correlations analysis between various state standard auditory spectra.The optimized ZCPA auditory model can be used to imitate human auditory systems to extract the features of the input signal,to make up the defects of poor adaptability and low recognition rate of the traditional hearing model,and to increase the difference between different state features and improve the recognition rate of the equipment.Taking an ordinary lathe as an example,the condition recognition rate of the lathe vibration signal processed by the optimized ZCPA model reaches more than 95%.