Bearing Fault Diagnosis Based on Iterative 1.5-Dimensional Spectral Kurtosis

• Main Authors: Xiong Zhang, Shuting Wan, Yuling He, Xiaolong Wang, Longjiang Dou
• Format: Article
• Language: English
• Published: IEEE 2020-01-01
• Series: IEEE Access
• Subjects: Bearing diagnosis; kurtogram; WPT; iterative 15D spectrum
• Online Access: https://ieeexplore.ieee.org/document/9200336/

The key step of bearing fault diagnosis is to select a suitable resonance frequency band, so as to filter out interference components to the maximum extent and retain fault information in the resonance band. Kurtogram algorithm can locate the resonance frequency band well, which has been widely researched and applied in recent years, and has produced many derivative algorithms. The statistical indicators used by these methods to identify frequency band features are divided into time domain indicators and frequency domain indicators. Time domain indicators are more sensitive to a single accidental impact components, while frequency domain indicators are easily affected by harmonics in the time domain, that is, single or several frequency extremes in the frequency domain. In order to overcome the impact of non-periodic transient impulse components and modulation harmonic components, this article proposes a new method. This method uses wavelet packet transform (WPT) to divide the frequency band plane, and adopts 3 iterations 1.5-dimensional spectrum (1.5D spectrum) method, which can eliminate the impulse interference that has no coupling relationship in the time domain and frequency domain. Based on the above process, the K_I-1.5D gram method is constructed, which can realize more accurate positioning of the fault information. Finally, through simulated and experimental analysis, the effectiveness of the proposed method is verified.