RESEARCH PAPER
Degradation assessment of bearing based on machine learning classification matrix
1
Delhi Technological University, Delhi, India
Publication date: 2021-06-30
Eksploatacja i Niezawodność – Maintenance and Reliability 2021;23(2):395-404
HIGHLIGHTS
- Machine learning classification matrix is used to model the degraded behavior of bearing
- Prior state of art considers the various diagnostic and prognostic model of bearing
- Classification model is developed to assess the degradation of bearing.
- The analysis results show that the percentage of accuracy of different models
KEYWORDS
ABSTRACT
In the broad framework of degradation assessment of bearing, the final objectives of bearing
condition monitoring is to evaluate different degradation states and to estimate the quantitative analysis of degree of performance degradation. Machine learning classification matrices
have been used to train models based on health data and real time feedback. Diagnostic and
prognostic models based on data driven perspective have been used in the prior research
work to improve the bearing degradation assessment. Industry 4.0 has required the research
in advanced diagnostic and prognostic algorithm to enhance the accuracy of models. A classification model which is based on machine learning classification matrix to assess the degradation of bearing is proposed to improve the accuracy of classification model. Review work
demonstrates the comparisons among the available state-of-the-art methods. In the end,
unexplored research technical challenges and niches of opportunity for future researchers
are discussed.
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