Data-Driven Approach for Fault Detection and Diagnosis in Industrial Processes
A Special Issue of Processes (ISSN 2227-9717) belonging to the section "Process Control, Modeling and Optimization".
Deadline for manuscript submissions: 10 November 2026 | Viewed by 250
Editors
Interests: fault detection and diagnosis; machine learning; current sensing
Interests: intelligent fault diagnosis; current measurement; data analysis
Interests: data-driven modeling; high voltage discharge; intelligent fault diagnosis
Special Issue Information
Dear Colleagues,
This Special Issue focuses on intelligent detection and diagnosis for faults in modern industrial systems. These years have witnessed the development of modern industrial systems toward increasing scale, complexity and intelligence. On the plus side, these advances have greatly improved production efficiency and system performance. On the negative side, new challenges have been introduced in ensuring system safety and reliability. Due to the strong nonlinearity, multivariable coupling and uncertainty of industrial processes, traditional fault detection and diagnosis methods are often compromised by poor robustness under complex operating conditions. Against this background, data-driven approaches, supported by massive process data and intelligent algorithms, have emerged as promising solutions.
This Special Issue on “Data-Driven Approach for Fault Detection and Diagnosis in Industrial Processes” seeks high-quality research and review papers. Topics include, but are not limited to, the following:
-Data-driven fault detection and diagnosis for industrial systems (e.g., energy systems and manufacturing systems);
-Smart sensing and multi-source information fusion for industrial fault detection and diagnosis;
-Health prognostics and predictive maintenance for industrial systems;
-Modeling and stability analysis of complex industrial systems.
Dr. Run Jiang
Dr. Yifan Huang
Dr. Baohong Guo
Dr. Xinyu Liu
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes 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.
Keywords
- data-driven approach
- fault detection
- fault diagnosis
- industrial systems
- intelligent
- system reliability
- system safety
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