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Intelligent Structural Health Monitoring for Modern Industrial and Civil Assets

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Keywords
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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Intelligent Sensors".

Deadline for manuscript submissions: closed (25 July 2023) | Viewed by 8079

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Special Issue Editors

Dr. Xiaobin Hong

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Guest Editor

School of Mechanical & Automotive Engineering, South China University of Technology, Guangzhou, China
Interests: structural health monitoring; smart structures; structural dynamics simulation; intelligent nondestructive testing; automatic instrumentation

Dr. Dingcheng Zhang

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Guest Editor

School of Mechanical Engineering, Sichuan University, Chengdu, China
Interests: signal processing; condition monitoring; data-driven diagnosis

Dr. Donghui Yang

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Guest Editor

School of Civil Engineering, Dalian University of Technology, Dalian 116024, Liaoning Province, China
Interests: structural health monitoring and performance evaluation
Special Issues, Collections and Topics in MDPI journals

Dr. Zhe Wang

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Guest Editor

Department of Advanced Design and Systems Engineering, City University of Hong Kong, Hong Kong, China
Interests: structural health monitoring; prognostics and health management; machine learning

Special Issue Information

Dear Colleagues,

Modern industrial and civil structure systems apply diverse functional structures to support normal operation. However, the harsh working environments and long-term service of industrial and civil assets make structures prone to defects, such as cracks and corrosion. The failure of different components has been reported, and these failures have resulted in serious consequences to the economy and society. Intelligent structural health monitoring will be beneficial for the early detection of defects, allowing predictive maintenance to be conducted. Nowadays, advanced sensors and artificial intelligence have progressed rapidly. Scientists can use sensor techniques, signal processing methods, and machine learning tools to realize the monitoring, detection, prognostics, diagnosis, and management of the health status of different structures in industrial and civil assets.

This Special Issue aims to present the current achievements and latest developments made by researchers and industrial and civil engineers in intelligent structural health monitoring for modern industrial and civil assets.

Topics include but are not limited to:

Advanced sensors for structural health monitoring;
Multi-sensor information fusion techniques;
Failure detection and diagnosis of industrial machinery;
Defect detection of electrical devices;
Damage detection and early warnings of structural anomalies in bridges;
Structural inspection and analysis of buildings and bridges;
Advanced feature extraction methods for industrial inspection;
Artificial Intelligence algorithms in prognostics and health management;
Condition monitoring and intelligent fault diagnosis;
Deep learning algorithms for equipment used in environmental sensing applications.

Dr. Xiaobin Hong
Dr. Dingcheng Zhang
Dr. Donghui Yang
Dr. Zhe Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

monitoring sensors
structural health monitoring
industrial equipment
bridge structures
artificial intelligence
signal processing
condition monitoring
prognostics and diagnosis
damage detection and early warning
performance evaluation

Published Papers (4 papers)

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Research

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16 pages, 4380 KiB

Open AccessArticle

Determination of Blast Vibration Safety Criteria for Buried Polyethylene Pipelines Adjacent to Blast Areas, Using Vibration Velocity and Strain Data

by Shengwu Tu, Dongwang Zhong, Linna Li, Xiangchao Gong and Haohao Tao

Sensors 2023, 23(14), 6359; https://doi.org/10.3390/s23146359 - 13 Jul 2023

Viewed by 816

Abstract

In order to ensure the safe operation of buried polyethylene pipelines adjacent to blasting excavations, controlling the effects of blasting vibration loads on the pipelines is a key concern. Model tests on buried polyethylene pipelines under blasting loads were designed and implemented, the vibration velocity and dynamic strain response of the pipelines were obtained using a TC-4850 blast vibrometer and a UT-3408 dynamic strain tester, and the distribution characteristics of blast vibration velocity and dynamic strain were analyzed based on the experimental data. The results show that the blast load has the greatest effect on the circumferential strain of the polyethylene pipe, and the dynamic strain response is greatest at the section of the pipe nearest to the blast source. Pipe peak vibration velocity (PPVV), ground peak particle velocity (GPPV), and the peak dynamic strain of the pipe were highly positively correlated, which verifies the feasibility of using GPPV to characterize pipeline vibration and strain level. According to the failure criteria and relevant codes, combined with the analysis of experimental results, the safety threshold of additional circumferential stress on the pipeline is 1.52 MPa, and the safety control vibration speed of the ground surface is 21.6 cm/s. Full article

(This article belongs to the Special Issue Intelligent Structural Health Monitoring for Modern Industrial and Civil Assets)

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16 pages, 25853 KiB

Open AccessArticle

Real Depth-Correction in Ground Penetrating RADAR Data Analysis for Bridge Deck Evaluation

by Sepehr Pashoutani and Jinying Zhu

Sensors 2023, 23(2), 1027; https://doi.org/10.3390/s23021027 - 16 Jan 2023

Cited by 3 | Viewed by 1944

Abstract

When ground penetrating radar (GPR) is used for the non-destructive evaluation of concrete bridge decks, the rebar reflection amplitudes should be corrected for rebar depths to account for the geometric spreading and material attenuation of the electromagnetic wave in concrete. Most current depth-correction methods assume a constant EM wave velocity in the entire bridge deck and correct GPR amplitudes based on the two-way travel time (TWTT) instead of the actual rebar depth. In this paper, we proposed a depth-correction algorithm based on the real rebar depths. To compare different depth-correction methods, we used gprMax software to simulate GPR signals in four models with various dielectric constants and conductivity. The comparison shows that the TWTT-based depth-correction method tends to over-correct GPR amplitudes so that underestimates the deterioration level of concrete decks at certain locations. Two depth-based correction methods are proposed that use migrated amplitudes and further normalize the corrected amplitude by rebar depth (attenuation rate). These methods are then applied to GPR data collected on two bridges, and the results were validated by other NDE methods and chloride concentration test. Full article

(This article belongs to the Special Issue Intelligent Structural Health Monitoring for Modern Industrial and Civil Assets)

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15 pages, 4068 KiB

Open AccessArticle

A Geometric Approach for Real-Time Forward Kinematics of the General Stewart Platform

by Fangfang Yang, Xiaojun Tan, Zhe Wang, Zhenfeng Lu and Tao He

Sensors 2022, 22(13), 4829; https://doi.org/10.3390/s22134829 - 26 Jun 2022

Cited by 5 | Viewed by 3234

Abstract

This paper presents a geometric approach for real-time forward kinematics of the general Stewart platform, which consists of two rigid bodies connected by six general serial manipulators. By describing the rigid-body motion as exponential of twist, and taking advantage of the product of exponentials formula, a step-by-step derivation of the proposed algorithm is presented. As the algorithm naturally solves all passive joint displacements, the correctness is then verified by comparing the forward-kinematic solutions from all chains. The convergence ability and robustness of the proposed algorithm are demonstrated with large amounts of numerical simulations. In all test cases, the proposed algorithm terminates within four iterations, converging with near-quadratic speed. Finally, the proposed algorithm is also implemented on a mainstream embedded motion controller. Compared with the incremental method, the proposed algorithm is more robust, with an average execution time of 0.48 ms, meeting the requirements of most applications, such as kinematic calibration, motion simulation, and real-time control. Full article

(This article belongs to the Special Issue Intelligent Structural Health Monitoring for Modern Industrial and Civil Assets)

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Other

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14 pages, 7748 KiB

Open AccessEssay

Monitoring and Analysis of the Collapse Process in Blasting Demolition of Tall Reinforced Concrete Chimneys

by Xiaowu Huang, Xianqi Xie, Jinshan Sun, Dongwang Zhong, Yingkang Yao and Shengwu Tu

Sensors 2023, 23(13), 6240; https://doi.org/10.3390/s23136240 - 7 Jul 2023

Cited by 1 | Viewed by 1143

Abstract

Aiming at the problem of displacement of collapse direction caused by the impact of the high-rise reinforced concrete chimney in the process of blasting demolition, combined with the monitoring methods such as high-speed photography observation, piezoelectric ceramic sensor, and blasting vibration monitor, the impact process of the 180 m high chimney was comprehensively analyzed. The results show that the chimney will experience multiple ‘weight loss’ and ‘overweight’ effects during the sit-down process, inducing compressive stress waves in the chimney. When the sit-down displacement is large, the broken reinforced concrete at the bottom can play a significant buffering effect, and the ‘overweight’ effect gradually weakens until the sit-down stops. The stress of the inner and outer sides of the chimney wall is obviously different in the process of collapsing and touching the ground. The waveform of the monitoring point of the piezoelectric ceramic sensor is divided into three stages, which specifically characterizes the evolution process of the explosion load and the impact of the chimney. The vibration induced by explosive explosion is mainly high-frequency vibration above 50 Hz, the vibration induced by chimney collapse is mainly low-frequency vibration below 10 Hz, and the vibration characteristics are obviously different. In the process of blasting demolition and collapse of high-rise reinforced concrete chimney, due to the impact of sitting down, the wall of the support tube is subjected to uneven force, resulting in the deviation of the collapse direction. In practical engineering, the control measures of chimney impact, blasting vibration, and collapse touchdown vibration should be fully strengthened to ensure the safety of the protection target around the blasting demolition object. Full article

(This article belongs to the Special Issue Intelligent Structural Health Monitoring for Modern Industrial and Civil Assets)

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