Single point bearing fault diagnosis using simplified frequency model

A Review of Early Fault Diagnosis Approaches and Their Applications in Rotating Machinery

“…Chen et al [133] used mean envelope kurtosis to determine the optimum frequency band, and envelope analysis was used to detect the bearing faults. Masmoudi et al [134] proposed a reduced frequency model to provide an accurate estimation of the fault frequency. Dong et al [135] proposed the frequency-shifted bispectrum to analyze amplitude modulated and frequency modulated signals for qualitative and quantitative diagnosis of bearing faults.…”

“…[126] Short-time Fourier-transform-based estimator of the spectral kurtosis Antoni J. [127] Fast computation of the kurtogram Li et al [132] Particle Filter + Kurtogram Wang et al [125] Minimum entropy de-convolution + Fast Kurtogram Cong et al [129] Spectral kurtosis + autoregressive model Jeong et al [130] Spectral kurtosis Chen et al [133] Mean envelope Kurtosis + envelope analysis Jia et al [131] Maximum correlated kurtosis deconvolution Masmoudi et al [134] Time synchronous averaging Dong et al [135] Frequency-shifted bispectrum Zhou et al [136] Cyclic bispectrum Dong et al [137] Wigner-Ville spectrum Yuan et al [138] Multi-fractal analysis Siegel et al [139] Tachometer-less synchronously averaged envelope Park et al [140] Minimum variance cepstrum Fu et al [141] Adaptive fuzzy-means clustering Li et al [142] Informative frequency band Liu et al [143] Adaptive SR + quantum particle swarm Liao et al [144] Improved genetic algorithm Kedadouche et al [124] Approximate entropy + sample entropy + Lempel-Ziv Complexity. Javorskyj et al [145] Periodically correlated random processes Igba et al [146] Root mean square (RMS) + peak values Shao et al [147] RMS in angle domain Sharma et al [148] Modified time synchronous averaging Jin et al [149] Mahalanobis distance…”