Comparison of Novelty Detection Methods for Detection of Various Rotary Machinery Faults

Sensors

Michał Dziendzikowski¹  Adam Jabłoński²  Jakub Górski²  Ziemowit Dworakowski²  Mateusz Heesch² 

[1] Air Force Institute of Technology, Airworthiness Division, ul. Ks. Boleslawa 6, 01-494 Warsaw, Poland;Department of Robotics and Mechatronics, Faculty of Mechanical Engineering and Robotics, AGH University of Science and Technology, 30-059 Krakow, Poland;

关键词: novelty detection;    data stream;    soft computing;    gearbox;    fault detection;   

DOI  :  10.3390/s21103536

来源: DOAJ

【 摘 要 】

Condition monitoring is an indispensable element related to the operation of rotating machinery. In this article, the monitoring system for the parallel gearbox was proposed. The novelty detection approach is used to develop the condition assessment support system, which requires data collection for a healthy structure. The measured signals were processed to extract quantitative indicators sensitive to the type of damage occurring in this type of structure. The indicator’s values were used for the development of four different novelty detection algorithms. Presented novelty detection models operate on three principles: feature space distance, probability distribution, and input reconstruction. One of the distance-based models is adaptive, adjusting to new data flowing in the form of a stream. The authors test the developed algorithms on experimental and simulation data with a similar distribution, using the training set consisting mainly of samples generated by the simulator. Presented in the article results demonstrate the effectiveness of the trained models on both data sets.

【 授权许可】

Unknown