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Identification of Ground Intrusion in Underground Structures Based on distributed Structural vibration Detected by Ultra-Weak FBG Sensing Technology

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SENSORS 2019年第9期19卷 2160.-2160.页

作者： Gan, Weibing Li, Sheng Li, Zhengying Sun, Lizhi Wuhan Univ Technol Natl Engn Lab Fiber Opt Sensing Technol Wuhan 430070 Hubei Peoples R China Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Hubei Peoples R China Univ Calif Irvine Dept Civil & Environm Engn Irvine CA 92697 USA

It is challenging for engineers to timely identify illegal ground intrusions in underground systems such as subways. In order to prevent the catastrophic collapse of subway tunnels from intrusion events, this paper investigated the capability of detecting the ground intrusion of underground structures based on dynamic measurement of distributed fiber optic sensing. For an actual subway tunnel monitored by the ultra-weak fiber optic Bragg grating (FBG) sensing fiber with a spatial resolution of five meters, a simulated experiment of the ground intrusion along the selected path was designed and implemented, in which a hydraulic excavator was chosen to exert intrusion perturbations with different strengths and modes at five selected intrusion sites. For each intrusion place, the distributed vibration responses of sensing fibers mounted on the tunnel wall and the track bed were detected to identify the occurrence and characteristics of the intrusion event simulated by the discrete and continuous pulses of the excavator under two loading postures. By checking the on-site records of critical moments in the intrusion process, the proposed detection approach based on distributed structural vibration responses for the ground intrusion can detect the occurrence of intrusion events, locate the intrusion ground area, and distinguish intrusion strength and typical perturbation modes.

关键词： subway tunnel safety ground intrusion detection ultra-weak FBG distributed vibration dynamic measurement

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Looseness Identification of Track Fasteners Based on Ultra-Weak FBG Sensing Technology and Convolutional Autoencoder Network

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SENSORS 2022年第15期22卷 5653-5653页

作者： Li, Sheng Jin, Liang Jiang, Jinpeng Wang, Honghai Nan, Qiuming Sun, Lizhi Wuhan Univ Technol Natl Engn Res Ctr Fiber Opt Sensing Technol & Net Wuhan 430070 Peoples R China Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Peoples R China Univ Calif Irvine Dept Civil & Environm Engn Irvine CA 92697 USA

Changes in the geological environment and track wear, and deterioration of train bogies may lead to the looseness of subway fasteners. Identifying loose fasteners randomly distributed along the subway line is of great significance to avoid train derailment. This paper presents a convolutional autoencoder (CAE) network-based method for identifying fastener loosening features from the distributed vibration responses of track beds detected by an ultra-weak fiber Bragg grating sensing array. For an actual subway tunnel monitoring system, a field experiment used to collect the samples of fastener looseness was designed and implemented, where a crowbar was used to loosen or tighten three pairs of fasteners symmetrical on both sides of the track within the common track bed area and the moving load of a rail inspection vehicle was employed to generate 12 groups of distributed vibration signals of the track bed. The original vibration signals obtained from the on-site test were converted into two-dimensional images through the pseudo-Hilbert scan to facilitate the proposed two-stage CAE network with acceptable capabilities in feature extraction and recognition. The performance of the proposed methodology was quantified by accuracy, precision, recall, and F1-score, and displayed intuitively by t-distributed stochastic neighbor embedding (t-SNE). The raster scan and the Hilbert scan were selected to compare with the pseudo-Hilbert scan under a similar CAE network architecture. The identification performance results represented by the four quantification indicators (accuracy, precision, recall, and F1-score) based on the scan strategy in this paper were at least 23.8%, 9.5%, 20.0%, and 21.1% higher than those of the two common scan methods. As well as that, the clustering visualization by t-SNE further verified that the proposed approach had a stronger ability in distinguishing the feature of fastener looseness.

关键词： feature identification track fastener looseness distributed vibration convolutional autoencoder network pseudo-Hilbert scan ultra-weak fiber optic Bragg grating

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Combining SDAE Network with Improved DTW Algorithm for Similarity Measure of Ultra-Weak FBG vibration Responses in Underground Structures

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SENSORS 2020年第8期20卷 2179页

作者： Li, Sheng Zuo, Xiang Li, Zhengying Wang, Honghai Sun, Lizhi Wuhan Univ Technol Natl Engn Lab Fiber Opt Sensing Technol Wuhan 430070 Peoples R China Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Peoples R China Univ Calif Irvine Dept Civil & Environm Engn Irvine CA 92697 USA

Quantifying structural status and locating structural anomalies are critical to tracking and safeguarding the safety of long-distance underground structures. Given the dynamic and distributed monitoring capabilities of an ultra-weak fiber Bragg grating (FBG) array, this paper proposes a method combining the stacked denoising autoencoder (SDAE) network and the improved dynamic time wrapping (DTW) algorithm to quantify the similarity of vibration responses. To obtain the dimensionality reduction features that were conducive to distance measurement, the silhouette coefficient was adopted to evaluate the training efficacy of the SDAE network under different hyperparameter settings. To measure the distance based on the improved DTW algorithm, the one nearest neighbor (1-NN) classifier was utilized to search the best constraint bandwidth. Moreover, the study proposed that the performance of different distance metrics used to quantify similarity can be evaluated through the 1-NN classifier. Based on two one-dimensional time-series datasets from the University of California, Riverside (UCR) archives, the detailed implementation process for similarity measure was illustrated. In terms of feature extraction and distance measure of UCR datasets, the proposed integrated approach of similarity measure showed improved performance over other existing algorithms. Finally, the field-vibration responses of the track bed in the subway detected by the ultra-weak FBG array were collected to determine the similarity characteristics of structural vibration among different monitoring zones. The quantitative results indicated that the proposed method can effectively quantify and distinguish the vibration similarity related to the physical location of structures.

关键词： similarity measure subway tunnel distributed vibration feature extraction autoencoder ultra-weak FBG

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A Novel Monitoring Approach for Train Tracking and Incursion Detection in Underground Structures Based on Ultra-Weak FBG Sensing Array

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SENSORS 2019年第12期19卷 2666.-2666.页

作者： Nan, Qiuming Li, Sheng Yao, Yiqiang Li, Zhengying Wang, Honghai Wang, Lixing Sun, Lizhi Wuhan Univ Technol Natl Engn Lab Fiber Opt Sensing Technol Wuhan 430070 Peoples R China Wuhan Univ Technol Sch Informat Engn Wuhan 430070 Peoples R China Univ Calif Irvine Dept Civil & Environm Engn Irvine CA 92697 USA

Tracking operating trains and identifying illegal intruders are two important and critical issues in subway safety management. One challenge is to find a reliable methodology that would enable these two needs to be addressed with high sensitivity and spatial resolution over a long-distance range. This paper proposes a novel monitoring approach based on distributed vibration, which is suitable for both train tracking and incursion detection. For an actual subway system, ultra-weak fiber Bragg grating (FBG) sensing technology was applied to collect the distributed vibration responses from moving trains and intruders. The monitoring data from the subway operation stage were directly utilized to evaluate the feasibility of the proposed method for tracking trains. Moreover, a field simulation experiment was performed to validate the possibility of detecting human intrusion. The results showed that the diagonal signal pattern in the distributed vibration response can be used to reveal the location and speed of the moving loads (e.g., train and intruders). Other train parameters, such as length and the number of compartments, can also be obtained from the vibration responses through cross-correlation and envelope processing. Experimental results in the time and frequency domains within the selected intrusion range indicated that the proposed method can distinguish designed intrusion cases in terms of strength and mode.

关键词： underground structure safety train tracking incursion detection ultra-weak FBG distributed vibration dynamic measurement

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