130 citations · 257 across the 6 of their papers we have counts for
6 papers
Advancing machine fault diagnosis: A detailed examination of convolutional neural networks
Govind Vashishtha, Sumika Chauhan, Mert Sehri +4
The growing complexity of machinery and the increasing demand for operational efficiency and safety have driven the development of advanced fault diagnosis techniques. Among these,…
Local damage detection in rolling element bearings based on a Single Ensemble Empirical Mode Decomposition
Yaakoub Berrouche, Govind Vashishtha, Sumika Chauhan +1
A Single Ensemble Empirical Mode Decomposition (SEEMD) is proposed for locating the damage in rolling element bearings. The SEEMD does not require a number of ensembles from the ad…
A crayfish-optimized wavelet filter and its application to fault diagnosis
Sumika Chauhan, Govind Vashishtha, Radoslaw Zimroz +1
Industrial machine fault diagnosis ensures the reliability and functionality of the system, but identifying informative frequency bands in vibration signals can be challenging due…
An Adaptive feature mode decomposition based on a novel health indicator for bearing fault diagnosis
Sumika Chauhan, Govind Vashishtha, Rajesh Kumar +2
The vibration analysis of the bearing is very crucial because of its non-stationary nature and low signal-to-noise ratio. Therefore, a novel scheme for detecting bearing defects is…
Intelligent fault diagnosis of worm gearbox based on adaptive CNN using amended gorilla troop optimization with quantum gate mutation strategy
Govind Vashishtha, Sumika Chauhan, Surinder Kumar +3
The worm gearbox is a high-speed transmission system that plays a vital role in various industries. Therefore it becomes necessary to develop a robust fault diagnosis scheme for wo…
Non-parametric Ensemble Empirical Mode Decomposition for extracting weak features to identify bearing defects
Anil Kumar, Yaakoub Berrouche, Radosław Zimroz +5
A non-parametric complementary ensemble empirical mode decomposition (NPCEEMD) is proposed for identifying bearing defects using weak features. NPCEEMD is non-parametric because, u…