基于改進(jìn)壓縮感知的缺損光纖Bragg光柵傳感信號(hào)修復(fù)方法

陳勇; 吳春婷; 劉煥淋

doi:10.11999/JEIT170424

基于改進(jìn)壓縮感知的缺損光纖Bragg光柵傳感信號(hào)修復(fù)方法

doi: 10.11999/JEIT170424 cstr: 32379.14.JEIT170424

1.
(重慶郵電大學(xué)工業(yè)物聯(lián)網(wǎng)與網(wǎng)絡(luò)化控制教育部重點(diǎn)實(shí)驗(yàn)室重慶 400065) ②(重慶郵電大學(xué)光纖通信技術(shù)重點(diǎn)實(shí)驗(yàn)室重慶 400065)

基金項(xiàng)目:

國(guó)家自然科學(xué)基金(61071117)，重慶市研究生科研創(chuàng)新項(xiàng)目(CYS17235)

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- 文章訪問(wèn)數(shù): 1841
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出版歷程
- 收稿日期: 2017-05-09
- 修回日期: 2017-07-21
- 刊出日期: 2018-02-19

A Repaired Algorithm Based on Improved Compressed Sensing to Repair Damaged Fiber Bragg Grating Sensing Signal

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)

Funds:

The National Natural Science Foundation of China (61071117), The Graduate Student Research Innovation Project of Chongqing (CYS17235)

摘要

摘要: 光纖光柵傳感在實(shí)際的應(yīng)用中，存在采樣信號(hào)數(shù)據(jù)丟失問(wèn)題，該文提出一種改進(jìn)重構(gòu)算法的壓縮感知信號(hào)修復(fù)方法。根據(jù)缺損信號(hào)特征，選取與之匹配的觀測(cè)矩陣與稀疏字典。基于壓縮感知重構(gòu)算法，提出匹配光纖布拉格光柵(FBG)信號(hào)特征的自適應(yīng)閾值函數(shù)，同時(shí)增設(shè)閾值判決條件。分析了信號(hào)修復(fù)與傳感測(cè)量精度的關(guān)系，采用重建信號(hào)的尋峰誤差來(lái)驗(yàn)證信號(hào)的修復(fù)效果。仿真結(jié)果顯示，在FBG光譜數(shù)據(jù)缺失30%的情況下，恢復(fù)信號(hào)的平均相對(duì)誤差為10-6；均方根誤差為0.0707，比對(duì)比算法低0.0232~0.1159；且系統(tǒng)平均運(yùn)行時(shí)間遠(yuǎn)低于對(duì)比算法，表明采用該文算法修復(fù)缺損的FBG傳感信號(hào)具有較高的重構(gòu)精度與較好的實(shí)用性。
- 光纖布拉格光柵 /
- 信號(hào)修復(fù) /
- 壓縮感知 /
- 正交匹配追蹤
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 is10-6 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.
- Fiber Bragg Grating (FBG) /
- Signal recovery /
- Compressed Sensing (CS) /
- Orthogonal Matching Pursuit (OMP)

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