Fault diagnosis of fiber optic current sensor induced by light source based on support vector machines

Yannan Chen; Haitao Li; Bo Li; Long Wan; Lihui Wang

doi:10.1117/12.2639663

23 May 2022 Fault diagnosis of fiber optic current sensor induced by light source based on support vector machines

Yannan Chen, Haitao Li, Bo Li, Long Wan, Lihui Wang

Proceedings Volume 12254, International Conference on Electronic Information Technology (EIT 2022); 1225402 (2022) https://doi.org/10.1117/12.2639663
Event: International Conference on Electronic Information Technology (EIT 2022), 2022, Chengdu, China

Abstract

Performance of SLD light source in fiber optic current sensor is easily affected by temperature, vibration, and device aging failure, and the failure mechanism is not clear. This paper proposes a fault diagnosis method for fiber optic current sensors based on light source monitoring data. In this paper, according to the working principle of fiber optic current sensor and SLD light source, we analyze the influence of light source parameters on fiber optic current sensor and establish light source data monitoring. The feature vector is dimensionalized by feature extraction. Using the light source monitoring data, a support vector machine-based fault diagnosis model with different kernel functions is designed to establish a fault diagnosis model for fiber optic current sensors. Experiment results indicate that the SVM fault diagnosis model takes less time and has better diagnostic performance, which basically meets the field diagnosis requirements.

Citation Download Citation

Yannan Chen, Haitao Li, Bo Li, Long Wan, and Lihui Wang "Fault diagnosis of fiber optic current sensor induced by light source based on support vector machines", Proc. SPIE 12254, International Conference on Electronic Information Technology (EIT 2022), 1225402 (23 May 2022); https://doi.org/10.1117/12.2639663

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