Identification of Low Frequency Fault Parameters of Magnetic Suspension Compressor Based on Rigid Frequency
Due to the influence of vibration signal acquisition mode and acquisition environment,when parameter identification is carried out for low-frequency faults of magnetic suspension compressor,the filtering degree of vibration signal is usually low,which leads to poor identification effect. In this paper,the identification of low-frequency fault parameters of magnetic suspension compressor based on rigid frequency is proposed. Firstly,the sampling frequency of vibration signal is defined,and each sampling value is mapped to the nearest quantization level. Then the quantized vibration signal is input into the low-pass filter,so as to realize the filtering operation of the signal. Then,the modal analysis of the vibration signal is carried out,and the rigid frequency in the vibration signal is determined by frequency response function. The parameter identification function is constructed in the form of the sum of squares of feature differences. Finally,combined with the sparrow algorithm,the feasible solution of parameter identification is iteratively optimized in the search space by updating the individual optimal value,so as to output the final optimization result. In the experiment,the identification effect of the proposed method is tested. The final test results show that when the proposed method is used to identify the low-frequency fault parameters of magnetic suspension compressor,the coefficient of variation of the identification results is low and it has an ideal identification effect.
Rigid frequencyMagnetic suspension compressorLow frequency faultParameter identificationSparrow algorithm
万方数据
维普
