Dr PURUSHOTTAM GANGSAR
Assistant Professor
Shri G. S. Institute of Technology & Science, 23,Park Road, Indore - 452003
Madhya Pradesh
Expertise:
Multidisciplinary Engineering
16
Publications
1
Projects
1255
Scopus Citations
1152
CrossRef
8 Years 5 Months Total Experience
Scopus
1,255
Citations
12
h-index
CrossRef
1,152
Citations
12
h-index
Google Scholar
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Professional Recognition
Young Scientist award to attend international conference in university of Lisbon, Portugal
2018
SERB/MHRD
Community & Membership
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Personal Details
Doctor of Philosophy
2018
N/A
Master of Technology
2014
N/A
Bachelor of Engineering
2012
Homi Bhabha National Institute, Mumbai
Assistant Professor
Apr 2018 – Present
Shri G. S. Institute of Technology & Science, 23,Park Road, Indore - 452003
Engineering and Technology
Scholarly Work
Development of a flexible fault diagnosis technique for induction motor based on artificial intelligence
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Scholarly Publications
Signal based condition monitoring techniques for fault detection and diagnosis of induction motors: A state-of-the-art review
A support vector machine based fault diagnostics of Induction motors for practical situation of multi-sensor limited data case
Diagnostics of mechanical and electrical faults in induction motors using wavelet-based features of vibration and current through support vector machine algorithms for various operating conditions
Online Diagnostics of Mechanical and Electrical Faults in Induction Motor Using Multiclass Support Vector Machine Algorithms Based on Frequency Domain Vibration and Current Signals
Performance Analysis of Support Vector Machine and Wavelet Packet Transform Based Fault Diagnostics of Induction Motor at Various Operating Conditions
Effect of noise on support vector machine based fault diagnosis of im using vibration and current signatures
Open AccessMultifault Diagnosis of Induction Motor at Intermediate Operating Conditions Using Wavelet Packet Transform and Support Vector Machine
Analysis of time, frequency and wavelet based features of vibration and current signals for fault diagnosis of induction motors using SVM
Showing 1 to 8 of 16 publications