P
Piyush Shakya
Researcher at Indian Institute of Technology Madras
Publications - 14
Citations - 238
Piyush Shakya is an academic researcher from Indian Institute of Technology Madras. The author has contributed to research in topics: Condition monitoring & Rolling-element bearing. The author has an hindex of 6, co-authored 12 publications receiving 134 citations. Previous affiliations of Piyush Shakya include Indian Institute of Technology Delhi.
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Bearing diagnosis based on Mahalanobis–Taguchi–Gram–Schmidt method
TL;DR: In this paper, a methodology is developed for defect type identification in rolling element bearings using the integrated Mahalanobis-Taguchi-Gram-Schmidt (MTGS) method.
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A novel methodology for online detection of bearing health status for naturally progressing defect
TL;DR: In this paper, a methodology for the online detection of health status of rolling element bearing into various damage stages for naturally progressing defect is proposed for online monitoring and damage stage detection, which is successfully verified on the vibration data acquired from the naturally induced and progressed defect experiments.
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Vibration-based fault diagnosis in rolling element bearings: ranking of various time, frequency and time-frequency domain data-based damage identi cation parameters
TL;DR: Shakya et al. as discussed by the authors performed a comparative study of various vibration signal-based damage identification parameters for rolling element bearings and concluded that the results suggest that the ranking is quite consistent, even with a different bearing type and damage characteristic.
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A robust condition monitoring methodology for grinding wheel wear identification using Hilbert Huang transform
TL;DR: The results indicated the robust and reliable wheel wear detection in cylindrical grinding with the use of relatively cheap sensors like accelerometers with an accuracy of 100% with both low and high cutting depths.
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An approach to improve high-frequency resonance technique for bearing fault diagnosis
TL;DR: In this paper, an alternative approach based on empirical mode decomposition and instantaneous energy is proposed to obtain the filtered signal without the need of identifying the resonance frequency band and the objective is to maximize the defect frequency amplitude of the High-Frequency Resonance Technique spectrum.