Special Issue "Fault Detection and Diagnosis in Mechatronics Systems"

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Mechanical Engineering".

Deadline for manuscript submissions: 30 September 2018

Special Issue Editor

Guest Editor
Prof. Dr. Nicola Bosso

Department of Mechanical and Aerospace Engineering, Politecnico di Torino, 10129 Torino, Italy
Website | E-Mail
Interests: railway vehicles (design and simulation); wheel/rail contact; railway dynamics; vehicle monitoring and diagnostics; heavy vehicles; multibody codes; machine design; experimental mechanics

Special Issue Information

Dear Colleagues,

The mechatronic approach is, nowadays, applied to many industrial sectors, and allows the integration in multi-disciplinary, environment, different technologies with the purpose of enhancing the performance of a system. A mechatronic system typically includes sensors, data acquisition, actuators (that operate in synergy) driven by specific control algorithms to perform a desired function on a controlled device.

One of the most recent and promising application of mechatronics concerns its application to improve the safety of complex systems. With this aim, it can be applied to different sectors: Transportation systems, vehicles, wind turbines, industrial processes, manufacturing, food industry, automation, and many others.

This Special Issue aims to collect papers concerning recent advances and challenges in application of “Mechatronics on Fault Detection and Diagnosis”, articulated over a wide range of sectors.

Papers submitted to this Special Issue are expected to provide an original contribution, proposing new solutions, improvements to existing solutions, and new applications in emerging sectors. The paper can address the solution of specific problems in the sector of interest using algorithms, experimental tests, and numerical analysis. 

Prof. Dr. Nicola Bosso
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 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. Applied Sciences is an international peer-reviewed open access monthly 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 1400 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

  • Fault diagnosis
  • Fault detection
  • Fault tolerant control
  • Diagnostic algorithms
  • Intelligent fault diagnosis
  • System active monitoring
  • Real-time monitoring
  • Monitoring systems
  • Mechatronic systems

Published Papers (2 papers)

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Research

Open AccessArticle Fault Detection and Isolation for Redundant Inertial Measurement Unit under Quantization
Appl. Sci. 2018, 8(6), 865; https://doi.org/10.3390/app8060865 (registering DOI)
Received: 5 May 2018 / Revised: 21 May 2018 / Accepted: 23 May 2018 / Published: 25 May 2018
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Abstract
Fault detection and isolation with redundant strapdown inertial measurement unit is critical for ensuring the reliability of the guidance or navigation system in the fields of both aeronautics and astronautics. Although the parity space approach is used widely, it cannot detect the soft
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Fault detection and isolation with redundant strapdown inertial measurement unit is critical for ensuring the reliability of the guidance or navigation system in the fields of both aeronautics and astronautics. Although the parity space approach is used widely, it cannot detect the soft fault which affects navigation performance under pulse quantization. This paper develops the three-channel filters to detect the soft fault and conducts theoretical implementation. The constraint conditions of their parameters are explored and the influence of the weight of different ratios is analyzed. The Monte Carlo simulation is carried out in order to verify the validity of the fault detection and isolation method. The simulation results and their analysis provide a theoretical reference for fault detection and isolation with redundant strapdown inertial measurement unit. Full article
(This article belongs to the Special Issue Fault Detection and Diagnosis in Mechatronics Systems)
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Open AccessArticle Fault Detection in a Multistage Gearbox Based on a Hybrid Demodulation Method Using Modulation Intensity Distribution and Variational Mode Decomposition
Appl. Sci. 2018, 8(5), 696; https://doi.org/10.3390/app8050696
Received: 16 March 2018 / Revised: 22 April 2018 / Accepted: 27 April 2018 / Published: 1 May 2018
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Abstract
It is critical to detect hidden, periodically impulsive signatures caused by tooth defects in a gearbox. A hybrid demodulation method for detecting tooth defects has been developed in this work based on the variational mode decomposition algorithm combined with modulation intensity distribution. An
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It is critical to detect hidden, periodically impulsive signatures caused by tooth defects in a gearbox. A hybrid demodulation method for detecting tooth defects has been developed in this work based on the variational mode decomposition algorithm combined with modulation intensity distribution. An original multi-component signal is first non-recursively decomposed into a number of band-limited mono-components with specific sparsity properties in the spectral domain using variational mode decomposition. The hidden meaningful cyclostationary features can be clearly identified in the bi-frequency domain via the modulation intensity distribution (MID) technique. Moreover, the reduced frequency aliasing effect of variational mode decomposition is evaluated as well, which is very useful for separating noise and harmonic components in the original signal. The influences of the spectral coherence density and the spectral correlation density of the modulation intensity distribution on the demodulation were also investigated. The effectiveness and noise robustness of the proposed method have been well-verified using a simulated signal compared with the empirical mode decomposition algorithm associated with modulation intensity distribution. The proposed technique is then applied to detect four different defects in a multi-stage gearbox. The results demonstrated that the demodulated numerical information and pigmentation directly illustrated in the bi-frequency plot of the modulation intensity distribution can be successfully used to quantitatively differentiate the four gear defects. Full article
(This article belongs to the Special Issue Fault Detection and Diagnosis in Mechatronics Systems)
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