The Application of Sensors in Fault Diagnosis and Prognosis

Dear Colleagues,

With the advent of Industry 4.0, Industrial Internet of Things (IoT), the proliferation of inexpensive sensing technology, and advances in prognostics and health management, customers are not only requiring reliable physical asset investment, but also that their assets diagnose and prognose faults and alert maintenance staff when components need to be replaced. These assets often have substantial sensor systems capable of generating millions of data points a minute. The availability and access to these massive and multidimensional sensor data open the door to a wide gamut of opportunities for powerful approaches for smart, autonomous, and online early fault detection and prognostics of remaining useful life. This Special Issue invites contributions concerning the Application of Sensors to Fault Diagnosis and Prognosis. The Guest Editors encourage authors to submit research articles with original perspectives and advanced thinking on this topic and related issues. Potential topics should include, but not be limited to, the following:

• Physics-based model and hybrid methods for multi-sensor fusion in fault diagnosis and prognosis
• Data-driven approaches, including deep learning-based models, for multi-sensor fusion in fault diagnosis and prognosis
• Structural health monitoring
• Prognostics and health management (PHM)
• Predictive maintenance
• Decision making in reliability and maintenance

Prof. Enrique López Droguett
Guest Editor

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