Condition Monitoring

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• Published Subscription Review Article 29 Oct 2026

  TinyML-Based Real-Time Industrial Fault Detection Using Vibration Signals

  By Sarvesh Mahimkar, Bhakti Gavali, Aditi Gavali, Jyoti Ghadage, Vaibhav Godase

  Abstract: Industrial rotating machinery is commonly monitored through vibration measurements because changes in bearing condition can alter signal amplitude, impulsiveness, and spectral distribution. Cloud-centred analytics may introduce communication dependence, bandwidth demand, and response delay. Tiny Machine Learning (TinyML) offers a complementary approach by executing compact inference locally on resource-constrained edge hardware. This paper presents a reproducible, deployment-oriented workflow for vibration-based machine-state classification using statistical and spectral features with small classifiers suitable …

  Published in Journal of Instrumentation Technology & Innovations · Vol. 16, Issue 3, 2026 Read article →

• Published Subscription Original Research 13 Oct 2026

  Impact of Thermal Image Preprocessing Methods on a ResNet50 Model Baseline Performance for Ball Bearing Fault Diagnosis

  By Tanmay Garg, Aditya Singh Tomar, Vaibhav Shivhare

  Abstract: Ball bearings are an important part for the operational rotating machinery. To prevent it from failing, traditional engineering uses many methods. One of these is infrared thermography (IRT). IRT is a useful tool that helps monitor the situation without physical contact. But in the current world, various fields use artificial intelligence to do it more accurately & for fast detection. Deep learning models play an important role in fault detection …

  Published in Trends in Mechanical Engineering & Technology · Vol. 16, Issue 3, 2026 Read article →