Adaptive multiwavelets via two-scale similarity transforms for rotating machinery fault diagnosis

Utilising the Wavelet Transform in Condition-Based Maintenance: A Review with Applications

“…Testing results showed that the anti-aliasing lifting scheme performs better than the lifting scheme and the redundant lifting scheme in terms of increasing the accuracy of classification algorithms (ANNs or SVMs) of faulty bearing signals. (Yuan et al, 2009) introduced a new method based on adaptive multi-wavelets via two-scale similarity transforms (TSTs). TSTs are simple methods to construct new biorthogonal multi-wavelets with properties of symmetry, short support and vanishing moments.…”

Adaptive Redundant Multiwavelet Packet and its Application for Compound Faults Detection of Mechanical Equipment

“…In this segment, the construction of adaptive multiwavelet base functions is based on the TSTs theory [7]. A series of new symmetric multiwavelet base functions are developed based on TSTs by taking GHM multiwavelet [8] as original multiwavelet.…”

“…In order to overcome this shortcoming, another TSTs aiming at the new dual multiwavelet is performed. The two feasible TSTs matrices 1 ( ) M ω and 2 ( ) M ω subjected to previous algorithm and theorem are computed as follows [7]. The factors a , b , c , d and f are nonzero constant.…”

Gear fault detection using customized multiwavelet lifting schemes

“…Khadem and Rezaee introduced GHM multiwavelet systems [17] to perform gear fault analysis [18]. Two-scale similarity transforms were utilized to design adaptive multiwavelets for rotating machinery fault diagnosis [19]. In addition, as a simple and effective feature extraction technique, multiwavelet denoising has been developed to improve the signal-to-noise ratio.…”