Priyom Goswami

About

Currently working as a PhD research Scholar in the department of Subir Chowdhury School of Quality and Reliability, IIT Kharagpur. My Research interests include Condition Based Maintenance, Prognostics and health management of rotating machinery etc.

Employment

• ExxonMobil Services and Technology Private Limited Reliability Engineer
  2024 - Present
• Defence Research Laboratory Junior Research Fellow
  2019 - 2019

Education

• Indian Institute of Technology Kharagpur PhD
  2020 - Present
• Tezpur University MTech. (Specialization: Thermal and Fluid Engineering)
  2017 - 2019
• Kaziranga University B.Tech
  2012 - 2016

Projects & Funding

Projects & funding information is unavailable.

Publications (13)

• Broken tooth gear fault detection using vibration signals based on convolutional neural network
  International Journal of System Assurance Engineering and Management 2026 DOI: 10.1007/s13198-025-03093-9
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• Water ingressed lubrication oil degradation with cavitation effect detection in gearbox using sound pressure level analysis
  Measurement 2026 DOI: 10.1016/j.measurement.2025.119170
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• Enhanced Gear Fault Diagnosis Using Optimized Spectrogram-Based CNNs for Multiple and Compound Fault Detection
  2026 DOI: 10.1007/978-3-031-95963-9_20
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• Data-driven sensor selection for industrial gearbox fault diagnosis using principal component analysis
  Measurement Science and Technology 2025 DOI: 10.1088/1361-6501/adb06b
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• A Novel Methodology for Chipped Teeth and Worn Tooth Gear Fault Detection Using Minimum Entropy Deconvolution and CEEMDAN
  Journal of Vibration Engineering & Technologies 2025 DOI: 10.1007/s42417-024-01622-7
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• Broken Tooth Gear Fault Detection Using Vibration Signals Based on Convolutional Neural Network
  2024 DOI: 10.21203/rs.3.rs-4949296/v1
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• Principal Component Analysis Based Vibration Sensor selection for Fault Diagnosis of an Industrial Gearbox
  2024 IEEE International Instrumentation and Measurement Technology Conference (I2MTC) 2024 DOI: 10.1109/i2mtc60896.2024.10560836
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• Efficient Vibration Signal Denoising Techniques for Effective Condition Monitoring of Gearbox
  2024 11th International Conference on Signal Processing and Integrated Networks (SPIN) 2024 DOI: 10.1109/spin60856.2024.10512263
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• A Systematic Review on Failure Modes and Proposed Methodology to Artificially Seed Faults for Promoting PHM Studies in Laboratory Environment for an Industrial Gearbox
  Engineering Failure Analysis 2023 DOI: 10.1016/j.engfailanal.2023.107076
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• An Optimum Segmentation of Gear Vibration Signals for an Effective Fault Classification Using Time-Domain Feature and Multi-class Support Vector Machines
  Intelligent Systems 2022 DOI: 10.1007/978-981-19-0901-6_29
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