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Structural Health Monitoring for Civil Engineering Materials (Second Volume)

A special issue of Materials (ISSN 1996-1944). This special issue belongs to the section "Advanced Materials Characterization".

Deadline for manuscript submissions: closed (20 June 2022) | Viewed by 1967

Special Issue Editors


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Guest Editor
Department of Engineering Mechanics, School of Naval Architecture, Ocean and Civil Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
Interests: analytical and applied mechanics; structural health monitoring; composite and smart materials; material characterization; sustainable concrete
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Guest Editor
Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China
Interests: theory and method of high-rise building structure design; structural vibration control; structural health monitoring; disaster prevention and mitigation for high-voltage transmission tower systems
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Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian 116024, China
Interests: cable force identification; data fusion; displacement reconstruction; structural health monitoring
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Civil engineering materials have evolved from conventional (such as concrete and steel) to new advanced and high performance (such as composites, high strength steel, and high performance concrete) materials over the last few decades. Considerable amounts of existing civil infrastructure constructed using conventional materials face aging and durability issues, as well as threats from both natural and manmade hazards. Modern and new civil infrastructures, though with better and improved performances, need integrated functionality to make them smarter and safer. Degradation, defect, damage, and even failure of civil infrastructure usually start at the local and material levels, and they, if not detected, assessed, and monitored, would eventually lead to catastrophe and huge economic losses. Thus, effective structural health monitoring for civil engineering materials is essential and critical for maintaining structural safety, sustainability, and resilience.

With significance of structural health monitoring for civil engineering, in general, and its materials, in particular, this Special Issue aims to publish peer-reviewed and open access papers that focus on analytical, experimental, and/or numerical investigations advancing the body of knowledge and its application in this important area of materials. The topics sought include, but are not limited to:

  • Dynamics-based methods for material damage detection and degradation assessment;
  • Diagnosis and prognosis techniques;
  • Mechanics for structural health monitoring;
  • Signal processing techniques;
  • Application of sensors, smart materials and wireless communication;
  • Monitoring of aging and durability as well as structural renewal;
  • Development of bio-inspired sensing or multifunctional materials;
  • Integrated smart material systems and structures;
  • Application of material monitoring techniques for civil infrastructure.

Prof. Dr. Pizhong Qiao
Prof. Dr. Hong-Nan Li
Dr. Xing Fu
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. Materials 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

  • civil engineering materials
  • monitoring of aging, degradation and durability
  • sensor technologies
  • diagnosis and prognosis techniques.

Published Papers (1 paper)

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Research

14 pages, 16741 KiB  
Article
Ball Bearing Fault Diagnosis Using Recurrence Analysis
by Krzysztof Kecik, Arkadiusz Smagala and Kateryna Lyubitska
Materials 2022, 15(17), 5940; https://doi.org/10.3390/ma15175940 - 27 Aug 2022
Cited by 8 | Viewed by 1568
Abstract
This paper presents the problem of rolling bearing fault diagnosis based on vibration velocity signal. For this purpose, recurrence plots and quantification methods are used for nonlinear signals. First, faults in the form of a small scratch are intentionally introduced by the electron-discharge [...] Read more.
This paper presents the problem of rolling bearing fault diagnosis based on vibration velocity signal. For this purpose, recurrence plots and quantification methods are used for nonlinear signals. First, faults in the form of a small scratch are intentionally introduced by the electron-discharge machining method in the outer and inner rings of a bearing and a rolling ball. Then, the rolling bearings are tested on the special laboratory system, and acceleration signals are measured. Detailed time-dependent recurrence methodology shows some interesting results, and several of the recurrence indicators such as determinism, entropy, laminarity, trapping time and averaged diagonal line can be utilized for fault detection. Full article
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