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Special Issue "Sparsity-based Sensing in Nondestructive Testing and Structural Health Monitoring"
Deadline for manuscript submissions: 30 June 2020.
Interests: Acoustic and Ultrasonic Sensors; Structural Health Monitoring; Lamb Waves Inspections; Embedded Systems; Modal Analysis; Mixed Signal Processing
Special Issues and Collections in MDPI journals
Interests: wave simulation; signal processing; wavelet analysis; sparse representation; structural health monitoring; blade tip timing; finite element method; modal analysis; damage detection; fault diagnosis; non-destructive evaluation
Interests: wave simulation; signal processing; inverse problem; and the development of multi-wave imaging techniques; Elasticity characterization for medical ultrasound and non-destructive evaluation
Insufficient sampling rates and/or missing data in spatial or time domains may hamper the possibility of achieving high wavenumber or frequency resolution, which is fundamental for reliable signal interpretation in structural health monitoring (SHM) and nondestructive testing and evaluation (NDT&E) applications.
To minimize the risk of misinterpretation, long acquisition procedures or dense sensor networks have to be used. However, in many of these applications, the collected signals usually have an extremely sparse representation in proper domains, which can be used to simplify the signal acquisition and interpretation. In fact, considering the sparsity of the important information of interest (e.g., the model parameters, defect localization, etc.), novel paradigms can overcome what is dictated by the conventional Nyquist sampling theory and significantly facilitate the sensing efficiency. From the signal processing point of view, sparsity-promoting strategies can be applied to obtain high-resolution signal representations, and to provide an efficient solution to the ill-posed problem encountered in many large-scale media monitoring due to the intrinsically limited nature of sensor networks’ cardinality.
This Special Issue will focus on sparse sensing, optimal sensor networks, and sparse signal processing for theoretical, analytical, and experimental investigations which may pave new paths to data acquisition and smart sensing in a broad range of SHM and NDT&E applications.
Potential topics include, but are not limited to:
- Sparse and smart sensor networks in NDT/SHM;
- Sparse methods for sensor network optimization;
- Compressed sensing and sparse data representation;
- Sparse projection of high-resolution transform, such as high-resolution Radon transform and dispersive Radon transform;
- Inverse problem involving sparse methods;
- Sparse sensing for non-destructive defect imaging;
- High-resolution media characterization, such as high-resolution dispersion curves extraction;
- Sparse data-driven strategies and deep-learning methods for NDT/SHM.
Dr. Luca De Marchi
Prof. Dr. Zhibo Yang
Prof. Dr. Kailiang Xu
Dr. Joel B. Harley
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 papers will be 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 2000 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.