Fast Calculation Method of Abnormality Degree for Real Time Abnormality Detection in Vehicle Equipment

Minoru KONDO, Yo SAKAIDANI
2020 Quarterly Report of RTRI  
Vibration monitoring is effective for early detection of equipment failure. In the vibration monitoring system proposed in this paper, abnormality detection is performed by applying the nearest neighbor method (NN) to the octave band analysis results of vibration. However, the NN requires a long calculation time and is not suitable for detecting abnormalities in real time. Therefore, applying the One Class Support Vector Machine (OCSVM) to abnormality detection was considered. In this paper,
more » ... OCSVM was applied to actual vibration data, and the calculation time was compared with those of the NN. The result shows that the calculation time is significantly reduced compared to the NN approach. Keywords: vibration analysis in octave bands, condition monitoring, machine learning Conclusions This paper describes the study of a method using OC-SVM as an abnormality detection method to detect abnormalities in real time in a condition monitoring system that monitors the vibration of vehicle equipment and applies an
doi:10.2219/rtriqr.61.3_165 fatcat:bspamgtxq5agpbpcw2i2ji4mhe