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Intelligent Sensors and Signal Processing in Industry

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

Deadline for manuscript submissions: 31 December 2025 | Viewed by 563

Special Issue Editors

Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
Interests: magnetic flux leakage testing; electromagnetic ultrasonic guided wave testing; defect inversion imaging; signal processing; intelligent sensors
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Guest Editor
Department of Electrical and Computer Engineering, Michigan State University, East Lansing, MI 48824, USA
Interests: Non-destructive evaluation; Ultrasonics; Structural Health Monitoring; Guided Waves; Measurements and Instrumentation; FE modeling; Microcontrollers; Composite Structures.
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Guest Editor
School of Physical Science and Engineering, Beijing Jiaotong University, 100044, China
Interests: ultrasonic non-destructive testing; rail transit; intelligent sensing

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Guest Editor
School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330013, China
Interests: electromagnetic sensors; electromagnetic ultrasonic non-destructive testing; intelligent imaging

Special Issue Information

Dear Colleagues,

The integration of intelligent sensors and advanced signal processing techniques in industry is revolutionizing traditional manufacturing and operational processes, ushering in a new era of efficiency, precision, and automation. Intelligent sensors, equipped with capabilities such as self-diagnostics, data processing, and communication, are pivotal in transforming raw data into actionable insights. These sensors are employed across a wide range of industrial applications, from monitoring machinery health and predicting failures to optimizing energy consumption and ensuring product quality. Complementing intelligent sensors is advanced signal processing technology. Through real-time data analysis, noise reduction, pattern recognition, and modern artificial intelligence techniques, these technologies further enhance the capabilities of intelligent sensors, enabling more accurate and reliable decision making. It is evident that intelligent sensors and signal processing technology hold significant importance in industries. Their integration brings about more efficient, precise, and automated production methods, driving industrial development and progress. By delving deeper into the exploration and application of intelligent sensors and signal processing technology, we can further enhance industrial competitiveness and achieve sustainable development.

This Special Issue aims to explore the cutting-edge advancements and applications of intelligent sensors and signal processing in various industrial contexts.

In this Special Issue, we look forward to receiving papers on a wide range of research topics, including the following:

  • New materials, technologies, and designs for intelligent sensors.
  • Application of intelligent sensors in NDT, SHM, and fault warning.
  • Various NDT technologies in electric energy, petroleum, transportation, construction, chemical industry, and special equipment.
  • Development and deployment of intelligent sensors in industrial environments.
  • Signal processing technologies in industrial automation and intelligent manufacturing.
  • Machine learning and AI techniques for predictive maintenance and anomaly detection.
  • Sensor fusion and integration in industrial IoT (IIoT) systems.
  • Case studies demonstrating the impact of intelligent sensors on operational efficiency and safety.
  • Emerging trends and future directions in industrial sensor technology.

Dr. Lisha Peng
Dr. Oleksii Karpenko
Dr. Hongyu Sun
Dr. Zhichao Cai
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

  • non-destructive testing
  • structural health monitoring
  • intelligent sensors
  • signal processing
  • industrial applications
  • predictive maintenance
  • machine learning
  • real-time monitoring
  • Industrial IoT (IIoT)

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Published Papers (1 paper)

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Research

11 pages, 5506 KiB  
Article
Crack Detection Method for Wind Turbine Tower Bolts Using Ultrasonic Spiral Phased Array
by Hongyu Sun, Jingqi Dong, Xi Diao, Xincheng Huang, Ziyi Huang and Zhichao Cai
Sensors 2024, 24(16), 5204; https://doi.org/10.3390/s24165204 - 11 Aug 2024
Viewed by 321
Abstract
High-strength bolts are crucial load-bearing components of wind turbine towers. They are highly susceptible to fatigue cracks over long-term service and require timely detection. However, due to the structural complexity and hidden nature of the cracks in wind turbine tower bolts, the small [...] Read more.
High-strength bolts are crucial load-bearing components of wind turbine towers. They are highly susceptible to fatigue cracks over long-term service and require timely detection. However, due to the structural complexity and hidden nature of the cracks in wind turbine tower bolts, the small size of the cracks, and their variable propagation directions, detection signals carrying crack information are often drowned out by dense thread signals. Existing non-destructive testing methods are unable to quickly and accurately characterize small cracks at the thread roots. Therefore, we propose an ultrasonic phased array element arrangement method based on the Fermat spiral array. This method can greatly increase the fill rate of the phased array with small element spacing while reducing the effects of grating and sidelobes, thereby achieving high-energy excitation and accurate imaging with the ultrasonic phased array. This has significant theoretical and engineering application value for ensuring the safe and reliable service of key wind turbine components and for promoting the technological development of the wind power industry. Full article
(This article belongs to the Special Issue Intelligent Sensors and Signal Processing in Industry)
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