Survey on IoT based Machine tools condition analysis With Machine Learning

Authors

  • Prof. A. V. Deorankar  Head of Department, Computer Science & Engineering, GCOE, Amravati, Maharashtra, India
  • Snehal M. Shegokar  Master of Technology Scholar, CSE, GCOE, Amravati, Amravati, Maharashtra, India

DOI:

https://doi.org/10.32628/CSEIT2063134

Keywords:

Machine tools condition analysis, Machine learning, IoT, Sound data.

Abstract

Machine condition checking innovation has around for a long time, designed for advancing machine execution and limiting unplanned personal time. Since the appearance of the IoT, nonetheless, there has been development around machine condition observing. An IoT-based model for machine apparatuses condition examination with AI, IoT computerizes and adds knowledge to machine condition checking. In this paper different techniques are studied about machine tools condition analysis and classification. This examination surveys different techniques which are used to classify machine sound data. The center goal is to order the obtained machine sound sign into the comparing machine conditions effectively for example faulty and normal, which is generally a multi- class order issue.

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IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology

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Published

2020-06-30

Issue

Volume 6, Issue 3, May-June-2020

Section

Research Articles

License

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Prof. A. V. Deorankar, Snehal M. Shegokar, " Survey on IoT based Machine tools condition analysis With Machine Learning" International Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 6, Issue 3, pp.664-667, May-June-2020. Available at doi : https://doi.org/10.32628/CSEIT2063134