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A review on the application of blind deconvolution in machinery fault diagnosis
Fault diagnosis is of significance for ensuring the safe and reliable operation of machinery
equipment. Due to the heavy noise and interference, it is difficult to detect the fault directly …
equipment. Due to the heavy noise and interference, it is difficult to detect the fault directly …
Applications of stochastic resonance to machinery fault detection: A review and tutorial
Fault detection is a key tool to ensure the safety and reliability of machinery. In machinery
fault detection, signal processing methods are extensively applied to extract fault …
fault detection, signal processing methods are extensively applied to extract fault …
A parameter-adaptive VMD method based on grasshopper optimization algorithm to analyze vibration signals from rotating machinery
The mode number and mode frequency bandwidth control parameter (or quadratic penalty
term) have significant effects on the decomposition results of the variational mode …
term) have significant effects on the decomposition results of the variational mode …
Toward accurate extraction of bearing fault modulation characteristics with novel time–frequency modulation bispectrum and modulation Gini index analysis
X Zou, H Zhang, Z Jiang, K Zhang, Y Xu - Mechanical Systems and Signal …, 2024 - Elsevier
Rolling bearings are extremely critical rotating mechanical components, and when they fail,
they can damage the equipment, causing safety threats or economic losses. Collecting and …
they can damage the equipment, causing safety threats or economic losses. Collecting and …
Coupled neurons with multi-objective optimization benefit incipient fault identification of machinery
Organisms can sense subtle changes in the environment around them such as temperature,
vibration and magnetic field. That is because biological neural network interconnected …
vibration and magnetic field. That is because biological neural network interconnected …
An intelligent fault diagnosis method enhanced by noise injection for machinery
Machinery generally operates under severe and complex conditions, and therefore, the
monitoring signals acquired from machinery would inevitably be accompanied by various …
monitoring signals acquired from machinery would inevitably be accompanied by various …
A novel strategy for signal denoising using reweighted SVD and its applications to weak fault feature enhancement of rotating machinery
Singular value decomposition (SVD), as an effective signal denoising tool, has been
attracting considerable attention in recent years. The basic idea behind SVD denoising is to …
attracting considerable attention in recent years. The basic idea behind SVD denoising is to …
An adaptive unsaturated bistable stochastic resonance method and its application in mechanical fault diagnosis
In mechanical fault diagnosis, most traditional methods for signal processing attempt to
suppress or cancel noise imbedded in vibration signals for extracting weak fault …
suppress or cancel noise imbedded in vibration signals for extracting weak fault …
A second-order stochastic resonance method enhanced by fractional-order derivative for mechanical fault detection
Stochastic resonance (SR), as a noise-enhanced signal processing tool, has been
extensively investigated and widely applied to mechanical fault detection. However …
extensively investigated and widely applied to mechanical fault detection. However …
Incipient fault diagnosis of bearings based on parameter-optimized VMD and envelope spectrum weighted kurtosis index with a new sensitivity assessment threshold
Due to difficulties in identifying localized and incipient bearing faults, most proposed fault
diagnosis methods focus on detecting these faults. However, it is not clear to what extent of …
diagnosis methods focus on detecting these faults. However, it is not clear to what extent of …