The performance of gearbox vibration monitoring techniques may degrade due to the signal distortion and attenuation which is usually caused by the complicated transmission path. The fiber Bragg grating sensing technique has attracting characteristics such as the small size, multiple measurement points on one fiber and resistance to oil corrosion. Therefore, this paper proposes a new approach for online monitoring of gearboxes based on fiber Bragg grating based strain sensors, in which the fiber Bragg grating sensors can be mounted closely to the meshing position of gear teeth. In this study, the working principle of the fiber Bragg grating and the configuration of the test rig is firstly presented. Then, the tooth root dynamic strain signals measured by fiber Bragg gratings under the healthy and gear pitting conditions were presented and compared with the finite element simulations. The comparison between the measured and simulated signals agrees well, which validates the feasibility of the employment of fiber Bragg gratings for the online monitoring of gearboxes. Furthermore, a novel diagnostic algorithm based on dynamic time warping is proposed to process the measured signals using fiber Bragg grating based strain sensors. The results show the proposed algorithm is able to diagnose the healthy and gear pitting conditions without the need of the pre-measured baselines.
|Original language||English (US)|
|Title of host publication||Proceedings - 11th International Conference on Prognostics and System Health Management, PHM-Jinan 2020|
|Editors||Chuan Li, Dejan Gjorgjevikj, Zhe Yang, Ziqiang Pu|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - Oct 2020|
|Event||11th International Conference on Prognostics and System Health Management, PHM-Jinan 2020 - Virtual, Jinan, China|
Duration: Oct 23 2020 → Oct 25 2020
|Name||Proceedings - 11th International Conference on Prognostics and System Health Management, PHM-Jinan 2020|
|Conference||11th International Conference on Prognostics and System Health Management, PHM-Jinan 2020|
|Period||10/23/20 → 10/25/20|
Bibliographical noteFunding Information:
ACKNOWLEDGMENT This research is supported by National Natual Science Foundation of China (Grant No. 51605349) and the Fundamental Research Funds for the Central Universities
© 2020 IEEE.
Copyright 2021 Elsevier B.V., All rights reserved.
- FBG sensors
- dynamic time warping
- fault diagnosis
- gear pitting