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January 27, 2026MAPAN

Fault Diagnosis in Roller Bearings by Using an Advanced Artificial Intelligence-Based Metrology

Ekta Yadav V. K. Chawla Navdeep Sanjay Yadav

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Key Points

Effective fault diagnosis improves reliability and efficiency in roller bearings, reducing unexpected failures.
AI-based metrology techniques enhance detection accuracy, achieving up to 95% diagnosis rate in specific tests.
Assessment using machine learning algorithms provides real-time monitoring and analysis of roller bearing conditions.
Highlights the need for ongoing development of predictive maintenance strategies in industrial settings.

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Implication

Observational analysis reveals effective fault diagnosis in roller bearings using advanced AI, indicating improved maintenance strategies.

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Cite This Study

Yadav et al. (2026) studied this question.

synapsesocial.com/papers/69a75b3ac6e9836116a222b5 https://doi.org/10.1007/s12647-026-00887-5

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