Rolling element bearing fault identification using a novel three-step adaptive and automated filtration scheme based on Gini index

Improved cyclostationary analysis method based on TKEO and its application on the faults diagnosis of induction motors

“…It defines the nonstationary vibration responses as second-order cyclostationary (CS2) signals and the fault feature is periodically modulated from the perspective of statistical characteristics. For example, vibration signals measured from the rotating machines with mechanical faults, such as broken rotor bar (BRB) [20], gear wear [21], bearing failure [22], and cavitation fault [23], present a high level of cyclostationarity that can indicate the operating conditions of the rotating machinery. This makes cyclostationary analysis become a preferred tool for the feature extraction and fault diagnosis of mechanical systems based on vibration signature.…”

Enhancement and extraction of periodic transient based on hybrid intelligent fusion algorithm and its application in rolling bearing fault detection

“…Furthermore, we derive the double discrete Fourier transform of R X L e t n , t m ð Þ represented by SC in formula (12) and corresponding cyclic spectra S k X L e f ð Þ in formula (13), a symbolizes discrete cyclic frequency into a = k=T, f also presents continuous Fourier frequency.…”

Optimal frequency band selection using blind and targeted features for spectral coherence-based bearing diagnostics: A comparative study

“…Harsh service conditions , such as high speed, large load, and multip le interferences, make ro lling bearings one of the parts that are prone to malfunction in rotating mach inery systems [1][2][3]. Therefore, bearing fault diagnostics and prognostics are critical to ensure the safe operation of mechanical systems and have attracted increasing attention in recent years [4].…”