About this Research Topic
Industry 4.0 has enabled the collection of large amounts of plant data, which has enabled the automation of process improvements and decision making. Due to the economic advantages of maintenance optimization, there is significant interest from both academia and industry on the topic of fault detection and prognostics for complex systems including vehicles, robotics, manufacturing systems, wind turbines, and chemical processing. Significant advances have been made but a strong demand exists for new or improved solutions to a number of significant problems in fault detection and prognostics.
This Research Topic will bring together recent advances on fault detection and prognostics, and identify future trends and research areas. Of particular interest are articles devoted to the development of theoretical and practical aspects on new and emerging trends in fault diagnostics, prognostics, and fault tolerant control with practical demonstrations. Articles must bring new ideas and approaches, clearly indicating the advances made through problem statements and methodologies with applications to modern systems.
Topics covered by this Research Topic include, but are not limited to:
• Reliability and maintenance management;
• Model-based and data-driven techniques;
• Fault diagnosis, prognosis and health monitoring system design;
• Safety and health monitoring;
• Intelligence techniques, such as fuzzy logic and neural network approaches.
• Digital Twins and simulation technology;
• Information constraints and sensor failures;
• Soft computing methods;
• Instrumentation and signal processing;
• Application studies.
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.