Research on Bearing Fault Diagnosis Method Based on Abnormal Feature Frequency Matching
With the continuous development of society,all walks of life have also been have also been continu-ously developed,the machinery industry has also been greatly developed.However,due to the many fault problems in the operation of mechanical equipment,a bearing fault diagnosis method based on abnormal feature frequency matching has been studied to address these issues.Firstly,the vibration signal is obtained and preprocessed.Denois-ing filtering is performed through wavelet transform to extract frequency components.Fast Fourier Transform is used to convert time-domain signals into frequency-domain signals and draw frequency spectra.Secondly,Hilbert Transform is applied for envelope analysis to improve the signal-to-noise ratio of the signal and obtain the enve-lope spectrum.Furthermore,the characteristic frequencies of bearing faults are extracted from the envelope spec-trum and compared with the theoretically calculated frequencies to determine the type and severity of the faults.The effectiveness and reliability of the proposed method in fault detection were verified through the bearing fault dataset of Western Reserve University.
万方数据
维普
