AI and Data-Driven Methods for Fault Detection and Diagnosis

Dear Colleagues,

This Special Issue is dedicated to recent developments and breakthroughs in intelligent systems monitoring, fault detection, and diagnosis. It seeks submissions on innovative technologies and methodologies for fault detection, real-time monitoring, predictive maintenance, and data-driven diagnosis using artificial intelligence, machine learning, and signal processing techniques. Contributions that address the challenges of improving equipment reliability, reducing downtime, and optimizing performance across diverse industrial applications are particularly encouraged.

The aim is to bring together researchers and practitioners from multidisciplinary fields to share their insights, foster collaboration, and promote the adoption of advanced intelligent diagnostic tools. All submissions will undergo rigorous peer review to ensure high standards of quality, originality, and practical relevance. This Special Issue will be widely promoted to maximize visibility and citation impact, contributing to the ongoing discourse in intelligent fault detection and diagnosis.

Prof. Dr. Yiwei Cheng
Dr. Zuoyi Chen
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. Applied Sciences 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.