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Acoustic Emission-Based Grinding Wheel Sharpness Monitoring Using Machine Learning Classifier

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Trends in Manufacturing and Engineering Management

Part of the book series: Lecture Notes in Mechanical Engineering ((LNME))

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Abstract

Grinding is one of the important secondary manufacturing processes used to improve the dimensional accuracy, surface finish and geometric form of the component. Grinding wheel consists of abrasive particles, which perform the metal removal function. The sharpness of the grinding wheel is one of the important factors for achieving the required surface geometry in the component. In this study, a simple device used to measure the sharpness of the abrasive particles of the grinding wheel is designed and fabricated. Aluminium oxide grinding wheel conditions are established using the sharpness of the abrasive grinding wheel. Grinding process is monitored using acoustic emission (AE) Sensor. AE features are extracted in time domain and dominated features which contain useful information about the grinding wheel that are identified. A correlation between grinding wheel condition and AE feature is established using ANN-based machine learning classifier.

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Acknowledgements

This research is supported by Directorate of Extramural Research and Intellectual Property Rights (ER & IPR), Defense Research and Development Organization (DRDO), ERIP/ER/0803740/M/01/1194, 13 January 2010.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Amrita School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore, 641112, India

    J. Revant,  Rahul Sree Kumar, K. Rameshkumar & D. S. B. Mouli

Authors
  1. J. Revant
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  2. Rahul Sree Kumar
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  3. K. Rameshkumar
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  4. D. S. B. Mouli
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Corresponding author

Correspondence to K. Rameshkumar .

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Editors and Affiliations

  1. Sri Sivasubramaniya Nadar College of Engineering, Chennai, Tamil Nadu, India

    S. Vijayan

  2. University of Sussex, Brighton, UK

    Nachiappan Subramanian

  3. National Institute of Technology Puducherry, Puducherry, India

    K. Sankaranarayanasamy

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Revant, J., Rahul Sree Kumar, Rameshkumar, K., Mouli, D.S.B. (2021). Acoustic Emission-Based Grinding Wheel Sharpness Monitoring Using Machine Learning Classifier. In: Vijayan, S., Subramanian, N., Sankaranarayanasamy, K. (eds) Trends in Manufacturing and Engineering Management. Lecture Notes in Mechanical Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-4745-4_45

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  • DOI: https://doi.org/10.1007/978-981-15-4745-4_45

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-15-4744-7

  • Online ISBN: 978-981-15-4745-4

  • eBook Packages: EngineeringEngineering (R0)

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