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Selected Papers from the 28th World Congress on Engineering (WCE 2021)

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Fault Diagnosis & Sensors".

Deadline for manuscript submissions: closed (15 February 2022) | Viewed by 5990

Special Issue Editors

School of Computing and Engineering, Department of Engineering and Technology, University of Huddersfield, Queensgate, Huddersfield HD1 3DH, UK
Interests: digital signal processing; structural health monitoring; condition monitoring; artificial intelligence; vibration analysis; motor current signature analysis; adaptation of diagnosis systems
Special Issues, Collections and Topics in MDPI journals
IAENG Secretariat International Association of Engineers, Hong Kong, China
Interests: big data problems; data mining algorithms; intelligent systems and their applications

Special Issue Information

Dear Colleagues,

The 28th World Congress on Engineering (WCE 2021) will be held from 7 to 9 July 2021 in London, UK, and the conference website can be found at http://www.iaeng.org/WCE2021/index.html.

The WCE 2021 is organized by the International Association of Engineers (IAENG). This conference will provide an important platform for scholars, engineers, and students to showcase their innovative research outcomes, transfer new knowledge, and boost interdisciplinary collaboration in areas of the frontier topics in the theoretical and applied engineering and computer science subjects.

This Special Issue of Sensors (IF: 3.275, ISSN 1424-8220) will collect a number of outstanding papers presented at the WCE. Conference participants are invited to submit extended versions of their conference papers to this Special Issue.

Potential topics include, but are not limited to, the following:

  • Fault detection and diagnosis;
  • Fault/failure prognosis;
  • Root cause analysis and troubleshooting of faults/failures;
  • Condition monitoring methods, technologies, and systems;
  • Nondestructive testing (NDT) methods, technologies, and systems;
  • Structural health monitoring methods, technologies, and systems;
  • Advanced and novel sensor types and actuator types;
  • Sensor data fusion;
  • Intelligent sensors and sensor networks;
  • Signal and image processing;
  • Certification;
  • Pattern recognition, machine learning, artificial intelligence, and data analytics;
  • Nonlinear methods, technologies, and systems;
  • Big data;
  • Modal analysis, finite element analysis, and computational fluid dynamics;
  • Modelling;
  • Lubrication and tribology;
  • Nano technologies;
  • Design, architecture, and information technology;
  • Adaptation and automation;
  • Fault tolerant control;
  • Physics and analysis of faults/failures; failure modes;
  • Reliability assessment and quality control;
  • Digital twins;
  • High-performance computing and edge computing;
  • Industry 4.0;
  • Measurement methods, technologies, and systems.

Prof. Dr. Len Gelman
Guest Editor

Dr. Sio Iong Ao
Co-Guest Editor

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.

Published Papers (2 papers)

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Research

12 pages, 10744 KiB  
Communication
Application of C-LSTM Networks to Automatic Labeling of Vehicle Dynamic Response Data for Bridges
Sensors 2022, 22(9), 3486; https://doi.org/10.3390/s22093486 - 03 May 2022
Cited by 5 | Viewed by 1875
Abstract
Maintaining bridges that support road infrastructure is critical to the economy and human life. Structural health monitoring of bridges using vibration includes direct monitoring and drive-by monitoring. Drive-by monitoring uses a vehicle equipped with accelerometers to drive over bridges and estimates the bridge’s [...] Read more.
Maintaining bridges that support road infrastructure is critical to the economy and human life. Structural health monitoring of bridges using vibration includes direct monitoring and drive-by monitoring. Drive-by monitoring uses a vehicle equipped with accelerometers to drive over bridges and estimates the bridge’s health from the vehicle vibration obtained. In this study, we attempt to identify the driving segments on bridges in the vehicle vibration data for the practical application of drive-by monitoring. We developed an in-vehicle sensor system that can measure three-dimensional behavior, and we propose a new problem of identifying the driving segment of vehicle vibration on a bridge from data measured in a field experiment. The “on a bridge” label was assigned based on the peaks in the vehicle vibration when running at joints. A supervised binary classification model using C-LSTM (Convolution—Long-Term Short Memory) networks was constructed and applied to data measured, and the model was successfully constructed with high accuracy. The challenge is to build a model that can be applied to bridges where joints do not exist. Therefore, future work is needed to propose a running label on bridges based on bridge vibration and extend the model to a multi-class model. Full article
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16 pages, 2847 KiB  
Article
Cluster Analysis and Discriminant Analysis for Determining Post-Earthquake Road Recovery Patterns
Sensors 2022, 22(6), 2213; https://doi.org/10.3390/s22062213 - 12 Mar 2022
Cited by 1 | Viewed by 2594
Abstract
The transport network in eastern Japan was severely damaged by the 2011 Tohoku earthquake. To understand the road recovery conditions after a large earthquake, a large amount of time is needed to collect information on the extent of the damage and road usage. [...] Read more.
The transport network in eastern Japan was severely damaged by the 2011 Tohoku earthquake. To understand the road recovery conditions after a large earthquake, a large amount of time is needed to collect information on the extent of the damage and road usage. In our previous study, we applied cluster analysis to analyze the data on driving vehicles in Fukushima prefecture to classify the road recovery conditions among municipalities within the first six months after the earthquake. However, the results of the cluster analysis and relevant factors affecting road recovery from that study were not validated. In this study, we proposed a framework for determining post-earthquake road recovery patterns and validated the cluster analysis results by using discriminant analysis and observing them on a map to identify their common characteristics. In addition, our analysis of objective data reflecting regional characteristics showed that the road recovery conditions were similar according to the topography and the importance of roads. Full article
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