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

Abstract

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.

A Novel Data Augmentation Method for Improving the Accuracy of Insulator Health Diagnosis

“…DTW was first introduced in the 1970s for speech recognition [ 31 , 32 , 33 ]. It tends to be used to determine the similarity of two sequences and to find a nonlinear alignment optimal path by minimizing the cumulative distance between and [ 34 , 35 , 36 ]. The distance between elements of X and Y is defined as where T is the length of sequence X and Y .…”

Invisible track bed defect classification method based on distributed optical fiber sensing system and FFT Attention Transformer model

“…[9][10][11][12][13][14][15][16][17] The distributed sensing detection system of a multiplexing ultra-weak fiber Bragg grating (UWFBG) has attracted the attention of researchers and has been applied to the actual safety inspection of metro corporation due to its advantages of high sensitivity, fast response, and dynamic measurement. 18,19 At present, the application of a sensor system in subway safety detection is mainly in tracking the speed and positioning the subway trains, 20 detecting personnel intrusions, 21 detecting external construction disturbances, and 22 classifying abnormal events. 23 The results of the above research show that the structural safety information of vehicles, rails, and track beds during subway operation is contained in the vibration signals collected by the sensing optical fiber.…”

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

“…Since the tracks are fastened to the track bed by fasteners, it is possible to obtain the fastener condition by monitoring the structural vibration response of the track bed caused by passing trains in terms of the relationship between the vibration response and the structural state. According to the reports in [ 11 , 12 , 18 ], the ultra-weak fiber optic Bragg grating (FBG) sensing technology [ 19 ] is a feasible way to collect the distributed vibration of the track bed along the subway line. To avoid the vibration characteristics caused by fastener loosening being submerged in the vibration response of the track bed, feature extraction should be the most intuitive idea that can improve the effectiveness and efficiency of the fastener’s looseness identification.…”