Research On Noise Suppression Method Of Ultra-weak Grating Sensor Network

Fiber Bragg Grating(FBG)sensor is a quality optical fiber sensor with characteristics of high sensitivity,wide dynamic measurement range,strong anti-electromagnetic interference ability and easy reuse.It can be widely used in the measurement and monitoring of temperature,stress and other parameters in military,aerospace and power system.With the increasing application demand of FBG sensor,the measurement accuracy,response speed and stability of its requirements are becoming higher and higher.This paper focuses on the basic principle of ultra-weak fiber Bragg grating sensor network,the type and formation mechanism of noise,sensor signal processing method and signal quality evaluation,temperature calibration and demodulation error analysis from four aspects.By studying the characteristics of noise and sensing signals,a signal processing method based on compressed sensing theory is proposed.To improve the performance of ultra-weak fiber Bragg grating sensor system.Reconstruction algorithm is the core of compressed sensing theory.In order to reconstruct signals more accurately,this paper proposes a reconstruction algorithm based on threshold retention orthogonal matching pursuit(TROMP).Experimental results show that,among similar algorithms,this algorithm has the highest probability of successful reconstruction under the condition of the same sparsity,and can reconstruct the signal under fewer observed values with higher reconstruction quality.Secondly,the computational complexity of the algorithm is small,which effectively reduces the signal processing time.In order to evaluate the signal processing effect more objectively,this paper evaluates the quality of sensing signals from four aspects: the retention degree of useful signal after denoising,the residual degree of noise,the degree of signal deviation and similarity.The experimental results show that the signal processed by compressed sensing algorithm not only retains the minute details of the signal,but also has relatively small residuals.In the simulation environment with a signal-to-noise ratio of 10 d B,the signal-to-noise ratio is improved by 10 d B,the root-mean-square error is 0.0036,and the number of mutual relations reaches 0.9958.Finally,the monitoring platform of ultra-weak fiber Bragg grating temperature sensing and demodulation system was built.The compressed sensing algorithm proposed in this paper was applied to de-noising and reconstruction of sensing signals,and the temperature calibration and demodulation error analysis of FBG were carried out in the temperature range of 0℃-73℃.Experimental results show that the average measurement error of the system is about 0.2328℃,which verifies the effectiveness of the proposed signal processing method.