A Repaired Algorithm Based on Improved Compressed Sensing to Repair Damaged Fiber Bragg Grating Sensing Signal
CHEN Yong① WU Chunting① LIU Huanlin②
①(Key Laboratory of Industrial Internet of Things and Network Control, Ministry of Education, Chongqing University of Posts and Telecommunications, Chongqing 400065, China) ②(Key Laboratory of Optical Fiber Communication Technology, Chongqing University, Chongqing 400065, China)
Abstract：To solve the problem of data loss in the field of Fiber Bragg Grating (FBG) sensing, a signal repaired method based on compressed sensing with improved reconstruction algorithm is proposed. According to the characteristics of signal, the suitable observation matrix and sparse dictionary are selected to repair the damaged spectral signal. An adaptive threshold function, which is used to match the characteristics of signal, is proposed in the reconstruction algorithm, and the criterion of threshold rationality is added. The relationship between the recovery precision of signal and sensing accuracy of fiber Bragg grating is analyzed, and the repairing effects are validated by peak-detected error of reconstructed signal. Simulation results show that the average relative error is 10-6 when 30% of the data is lost. The root mean square error is 0.0707, which is 0.0232~0.1159 lower than the contrast algorithms. The peak-detected error is lower than the others. Besides, the average running time of the system is much lower than the compared algorithms. All the results show that the proposed algorithm can well achieve the recovery of missing data, so as to improve the measurement precision of fiber Bragg grating sensor.
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