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

Sensors ◽  
2020 ◽  
Vol 20 (8) ◽  
pp. 2179
Author(s):  
Sheng Li ◽  
Xiang Zuo ◽  
Zhengying Li ◽  
Honghai Wang ◽  
Lizhi Sun
Keyword(s):  
Similarity Measure ◽  
Nearest Neighbor ◽  
Distance Measure ◽  
Integrated Approach ◽  
Structural Vibration ◽  
Distributed Monitoring ◽  
Underground Structures ◽  
Long Distance ◽  
Vibration Responses ◽  
Weak Fbg

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.

scholarly journals Identification of Ground Intrusion in Underground Structures Based on Distributed Structural Vibration Detected by Ultra-Weak FBG Sensing Technology

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2160 ◽  
Author(s):  
Weibing Gan ◽  
Sheng Li ◽  
Zhengying Li ◽  
Lizhi Sun
Keyword(s):  
Fiber Optic ◽  
Structural Vibration ◽  
Underground Structures ◽  
Subway Tunnel ◽  
Tunnel Wall ◽  
Sensing Technology ◽  
Detection Approach ◽  
Vibration Responses ◽  
Subway Tunnels ◽  
Weak Fbg

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.

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

Sensors ◽  
2019 ◽  
Vol 19 (12) ◽  
pp. 2666 ◽  
Author(s):  
Qiuming Nan ◽  
Sheng Li ◽  
Yiqiang Yao ◽  
Zhengying Li ◽  
Honghai Wang ◽  
...  
Keyword(s):  
Safety Management ◽  
High Sensitivity ◽  
Underground Structures ◽  
Long Distance ◽  
Sensing Technology ◽  
Frequency Domains ◽  
Envelope Processing ◽  
Critical Issues ◽  
Vibration Responses ◽  
Subway System

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.

scholarly journals Inferring Modes of Colonization for Pest Species Using Heterozygosity Comparisons and a Shared-Allele Test

Genetics ◽  
2003 ◽  
Vol 163 (2) ◽  
pp. 823-831
Author(s):  
J A Sved ◽  
H Yu ◽  
B Dominiak ◽  
A S Gilchrist
Keyword(s):  
Distance Measure ◽  
Fruit Fly ◽  
Small Samples ◽  
Pest Species ◽  
Long Distance ◽  
Resampling Methods ◽  
Shared Allele ◽  
The Core ◽  
Direct Sampling ◽  
Long Distance Movement

Abstract Long-range dispersal of a species may involve either a single long-distance movement from a core population or spreading via unobserved intermediate populations. Where the new populations originate as small propagules, genetic drift may be extreme and gene frequency or assignment methods may not prove useful in determining the relation between the core population and outbreak samples. We describe computationally simple resampling methods for use in this situation to distinguish between the different modes of dispersal. First, estimates of heterozygosity can be used to test for direct sampling from the core population and to estimate the effective size of intermediate populations. Second, a test of sharing of alleles, particularly rare alleles, can show whether outbreaks are related to each other rather than arriving as independent samples from the core population. The shared-allele statistic also serves as a genetic distance measure that is appropriate for small samples. These methods were applied to data on a fruit fly pest species, Bactrocera tryoni, which is quarantined from some horticultural areas in Australia. We concluded that the outbreaks in the quarantine zone came from a heterogeneous set of genetically differentiated populations, possibly ones that overwinter in the vicinity of the quarantine zone.

scholarly journals Dynamic Study of a Rooftop Vertical Axis Wind Turbine Tower Based on an Automated Vibration Data Processing Algorithm

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 3135 ◽  
Author(s):  
Ying Wang ◽  
Wensheng Lu ◽  
Kaoshan Dai ◽  
Miaomiao Yuan ◽  
Shen-En Chen
Keyword(s):  
Wind Turbine ◽  
Vertical Axis ◽  
Dynamic Responses ◽  
Ambient Vibration ◽  
Structural Vibration ◽  
Vertical Axis Wind Turbine ◽  
Mode Identification ◽  
Stochastic Subspace Identification ◽  
Vibration Data ◽  
Vibration Responses

When constructed on tall building rooftops, the vertical axis wind turbine (VAWT) has the potential of power generation in highly urbanized areas. In this paper, the ambient dynamic responses of a rooftop VAWT were investigated. The dynamic analysis was based on ambient measurements of the structural vibration of the VAWT (including the supporting structure), which resides on the top of a 24-story building. To help process the ambient vibration data, an automated algorithm based on stochastic subspace identification (SSI) with a fast clustering procedure was developed. The algorithm was applied to the vibration data for mode identification, and the results indicate interesting modal responses that may be affected by the building vibration, which have significant implications for the condition monitoring strategy for the VAWT. The environmental effects on the ambient vibration data were also investigated. It was found that the blade rotation speed contributes the most to the vibration responses.

scholarly journals A New Similarity Measure for User-based Collaborative Filtering in Recommender Systems

2015 ◽  
Vol 14 (9) ◽  
pp. 6118-6128 ◽  
Author(s):  
T. Srikanth ◽  
M. Shashi
Keyword(s):  
Collaborative Filtering ◽  
Recommender Systems ◽  
Similarity Measure ◽  
Recommender System ◽  
Distance Measure ◽  
Current User ◽  
Challenging Problem ◽  
Popular Approach ◽  
Similarity Calculation

Collaborative filtering is a popular approach in recommender Systems that helps users in identifying the items they may like in a wagon of items. Finding similarity among users with the available item ratings so as to predict rating(s) for unseen item(s) based on the preferences of likeminded users for the current user is a challenging problem. Traditional measures like Cosine similarity and Pearson correlation’s correlation exhibit some drawbacks in similarity calculation. This paper presents a new similarity measure which improves the performance of Recommender System. Experimental results on MovieLens dataset show that our proposed distance measure improves the quality of prediction. We present clustering results as an extension to validate the effectiveness of our proposed method.

Segregation at a Single Trap in the Presence of Fields

1992 ◽  
Vol 290 ◽  
Author(s):  
Haim Taitelbaum ◽  
George H. Weiss
Keyword(s):  
Nearest Neighbor ◽  
Distance Measure ◽  
Random Systems ◽  
Hard Core ◽  
Reaction Rates ◽  
Transition Rates ◽  
Constant Bias ◽  
Random Transition ◽  
Anomalous Reaction ◽  
Global Bias

AbstractThere have been a number of recent investigations of segregation properties of diffusing particles in the presence of a single static trap in low dimensions. We study these properties when the diffusing particles are subject to different forms of external fields: global constant bias, random bias fields (Sinai model) and random transition rates. We discuss two measures of segregation, the distances from the trap either to the point at which the concentration profile reaches a specified fraction of its bulk value, or to the nearest unreacted particle. For the cases of global bias (both away from, and towards the trap) and random fields, we found that both measures of segregation have the same asymptotic temporal behavior, while for random transition rates they differ. We explain this difference by relating the nearest-neighbor distance measure to properties of hard-core diffusion in these systems. We also found anomalous spatial shapes for the profile in the vicinity of the trap in the random systems, as well as anomalous reaction rates.

The Statistical Analysis of a Distribution of Activity Points in Relation to Surface-Like Elements

1988 ◽  
Vol 20 (5) ◽  
pp. 609-620 ◽  
Author(s):  
A Okabe ◽  
T Yoshikawa ◽  
A Fujii ◽  
K Oikawa
Keyword(s):  
Statistical Analysis ◽  
Probability Density Function ◽  
Nearest Neighbor ◽  
Distance Measure ◽  
Computational Method ◽  
Spatial Dependency ◽  
Neighbor Distance ◽  
High Class ◽  
Apartment Buildings ◽  
Nearest Neighbor Distance

The objective of this paper is to formulate a statistical method of testing the hypothesis that the distribution of activity points (such as retail stores) is independent of location of ‘surface-like’ infrastructural elements (such as parks). In order to do this, first, the probability density function of a distance from a random point to the nearest surface-like element is derived. Second, through the use of this function, a measure, R, of spatial dependency on the surface-like elements is defined as the ratio of the average nearest-neighbor distance to the expected average nearest-neighbor distance. This measure is an extension of the ordinary nearest-neighbor distance measure frequently referred to in geography and ecology. Third, the statistical use of measure R is shown. Fourth, as this measure is difficult to compute geometrically, the computational method of calculating the value of R is developed. Last, by use of this method, a test is conducted to decide whether or not the distribution of high-class apartment buildings in Setagaya, Tokyo, is affected by the location of big parks.

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