Fault Diagnosis and Prognosis of Mechatronic Systems Using Artificial Intelligence and Estimation Theory

Dear Colleagues,

Industry 4.0 is the fourth industrial revolution in human history. Industry 4.0 standards assume, among others, an increase in efficiency and reduction of operating costs associated with the intensive automation of industrial processes. It is obvious that such a massive paradigm shift in the industrial sector will mean that various fields of technology must also change and adapt to be used in a new industry concept.

Industrial processes, production systems, transportation systems, and related mechatronic systems are becoming more and more complex and may fail, affecting their reliability, safety, and quality of industrial production. Therefore, monitoring, diagnostics, and prognostics of the condition of machines and devices are one of the critical areas that must be taken into account during all changes related to the implementation of the Industry 4.0 idea.

In particular, obtaining objective diagnostic decisions through the use of artificial intelligence and estimation theory methods and techniques in fault detectors and damage classifiers, as well as in failure prognostic models for mechatronic systems, can facilitate the planning of maintenance and repair inspections of production lines and other devices in industrial plants. It will allow diagnosing and classifying damages of individual elements of these systems in real time at the initial stage of their development, as well as predicting failure development and remaining useful life-time of the failing component/system. Such actions will increase the reliability and efficiency of various industrial processes.

Therefore, the purpose of this Special Issue is to present current trends, advanced methods, and innovative technical solutions (in the field of hardware and software) used in the diagnosis and prognosis of mechatronic systems and their components (electronic, electrical, and mechanical), with particular regard to artificial intelligence methods: shallow and deep neural networks, fuzzy inference, as well as estimation theory.

We encourage you to send articles containing the results of original research, as well as review articles on topics including, among others:

• General paradigms in fault diagnostics and prognostics of industrial systems and processes
• Mathematical modeling of faulted mechatronic systems for symptoms generation
• Initial fault detection of mechatronic systems, single and multiple fault diagnosis
• Failure prognostic models for industrial systems and their elements, including robots
• Neural network application for diagnostic/prognostic procedures and unsupervised and supervised training with an emphasis on deep learning networks
• Fuzzy reasoning and neuro-fuzzy structures for diagnostic/prognostic applications
• Estimation theory and stochastic methods for diagnostics/prognostics
• Integrated diagnostic/prognostic methodologies
• Diagnostic/prognostic system architectures

Prof. Dr. Teresa Orlowska-Kowalska
Dr. Marcin Wolkiewicz
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 250 words) can be sent to the Editorial Office for assessment.

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. Electronics 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 2400 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.