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Sensor Fault Detection and Isolation

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

Deadline for manuscript submissions: closed (30 October 2021) | Viewed by 4495

Special Issue Editor


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Guest Editor
Department of Mechanical, Robotics and Energy Engineering, Dongguk University, Seoul 04620, Korea
Interests: structural health monitoring; smart wireless sensors; system identification; damage detection; data-driven control

Special Issue Information

Dear Colleagues,

Sensors (ISSN 1424-8220) is now soliciting manuscript proposals for a Special Issue entitled “Sensor Fault Detection and Isolation”. Discussions on sensors, data processing, and monitoring the integrity of systems have become increasingly prominent in both private and industrial sectors over the last few decades. Moreover, with the emergence of deep-learning-based data science, the detection and isolation of sensor defects have become critical components of various types of embedded systems or the IoT in Industry 4.0.

This Special Issue aims to gather together recent developments in advanced data-based monitoring of various systems and to provide researchers around the world with an opportunity to present state-of-the-art results as well as literature reviews. Topics of interest to this Special Issue include (but are not limited to):

  • sensor/actuator fault detection;
  • system identification;
  • wireless sensor networks;
  • sensor fusion and data acquisition;
  • data-driven system monitoring;
  • vision-based fault detection;
  • smart mobile sensors;
  • digital twins and surrogate models;
  • deep-learning-based outlier identification;
  • failure monitoring with biosensors.

Prof. Dr. Bong-Hwan Koh
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.

Keywords

  • sensor monitoring
  • signal processing
  • data analysis
  • fault detection
  • system identification
  • data fusion

Published Papers (1 paper)

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Research

32 pages, 16172 KiB  
Article
Edge Structural Health Monitoring (E-SHM) Using Low-Power Wireless Sensing
by Tadhg Buckley, Bidisha Ghosh and Vikram Pakrashi
Sensors 2021, 21(20), 6760; https://0-doi-org.brum.beds.ac.uk/10.3390/s21206760 - 12 Oct 2021
Cited by 11 | Viewed by 3918
Abstract
Effective Structural Health Monitoring (SHM) often requires continuous monitoring to capture changes of features of interest in structures, which are often located far from power sources. A key challenge lies in continuous low-power data transmission from sensors. Despite significant developments in long-range, low-power [...] Read more.
Effective Structural Health Monitoring (SHM) often requires continuous monitoring to capture changes of features of interest in structures, which are often located far from power sources. A key challenge lies in continuous low-power data transmission from sensors. Despite significant developments in long-range, low-power telecommunication (e.g., LoRa NB-IoT), there are inadequate demonstrative benchmarks for low-power SHM. Damage detection is often based on monitoring features computed from acceleration signals where data are extensive due to the frequency of sampling (~100–500 Hz). Low-power, long-range telecommunications are restricted in both the size and frequency of data packets. However, microcontrollers are becoming more efficient, enabling local computing of damage-sensitive features. This paper demonstrates the implementation of an Edge-SHM framework through low-power, long-range, wireless, low-cost and off-the-shelf components. A bespoke setup is developed with a low-power MEM accelerometer and a microcontroller where frequency and time domain features are computed over set time intervals before sending them to a cloud platform. A cantilever beam excited by an electrodynamic shaker is monitored, where damage is introduced through the controlled loosening of bolts at the fixed boundary, thereby introducing rotation at its fixed end. The results demonstrate how an IoT-driven edge platform can benefit continuous monitoring. Full article
(This article belongs to the Special Issue Sensor Fault Detection and Isolation)
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