Multi-state monitoring system of optical fiber sensor network for process control

Ying Qin

doi:10.1117/12.3029146

6 May 2024 Multi-state monitoring system of optical fiber sensor network for process control

Ying Qin

Proceedings Volume 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024); 131072X (2024) https://doi.org/10.1117/12.3029146
Event: Fourth International Conference on Sensors and Information Technology (ICSI 2024), 2024, Xiamen, China

Abstract

In order to realize real-time monitoring and online control of industrial process control, a multi-state monitoring and feedback control system based on optical fiber sensor network is designed. The system is composed of frequency sweep laser, fiber demodulation module, PC processing module, fiber sensor network and state control unit. A multi-state monitoring algorithm is proposed, which combines the FBG wavelength response values at each point of temperature and strain with weights, and then maps and models with four common state anomalies, and then gives feedback adjustment parameters through state analysis. In the experiment, the temperature field inside the tank and the stress field outside the tank are collected, and the online detection of the strain 0-5000με and the temperature 30-150°C is calibrated. The results show that the mean value of the corrected strain sensitivity is 0.499pm/με and the mean value of temperature sensitivity is 7.425pm/°C. The feedback control has the ability to adjust the state fluctuation online, and the feedback time of different abnormal types is different. The deviation of temperature and strain wavelength after correction in four cases is less than ±1°C and ±50με The feasibility of the system is verified.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ying Qin "Multi-state monitoring system of optical fiber sensor network for process control", Proc. SPIE 13107, Fourth International Conference on Sensors and Information Technology (ICSI 2024), 131072X (6 May 2024); https://doi.org/10.1117/12.3029146

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