Sensor-Based Fault Diagnosis and Prognosis
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Fault Diagnosis & Sensors".
Deadline for manuscript submissions: 31 July 2026 | Viewed by 103
Special Issue Editors
Interests: fault diagnosis; industrial manufacturing process monitoring; industrial data analysis; process control
Interests: intelligent control and fault diagnosis; system safety
Interests: fault diagnosis and prognostics; fault tolerant control; stochastic distribution control
Interests: fault detection and diagnosis; industrial data analysis; data-driven modeling and diagnosis
Special Issue Information
Dear Colleagues,
With the rapid development of advanced sensors and intelligent monitoring technologies, fault diagnosis and prognosis have entered a new era of precision and reliability. Modern sensors enable continuous data acquisition, real-time analysis, and predictive decision-making, which are critical for ensuring the safety, efficiency, and sustainability of modern engineering systems. This Special Issue seeks to highlight novel theory, methodologies, and applications of sensor-based approaches for fault diagnosis and prognosis. Topics of interest include, but are not limited to, the following: novel sensor technologies; signal processing and feature extraction; machine learning and artificial intelligence for fault detection and prognosis; prognostics and health management; industrial process monitoring; robust and interpretable models; and industrial case studies. Contributions in theoretical development, simulation studies, experimental validation, and engineering applications are all welcome.
Prof. Dr. Ying Zheng
Prof. Dr. Ke Zhang
Prof. Dr. Lina Yao
Dr. Yang Wang
Guest Editors
Manuscript Submission Information
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Keywords
- fault diagnosis
- prognostics and health management (PHM)
- intelligent sensors
- industrial process monitoring
- signal processing and feature extraction
- predictive maintenance
- industrial IoT
- condition monitoring
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