Multi-Condition Fault Diagnosis of Dynamic Systems: A Survey, Insights, and Prospects

With the increasing complexity of industrial production systems, accurate fault diagnosis is essential to ensure safe and efficient system operation. However, due to changes in production demands, dynamic process adjustments, and complex external environmental disturbances, multiple operating conditions frequently arise during production. The multi-condition characteristics pose significant challenges to traditional fault diagnosis methods. In this context, multi-condition fault diagnosis has gradually become a key area of research, attracting extensive attention from both academia and industry. This paper aims to provide a systematic and comprehensive review of existing research in the field. Firstly, the mathematical definition of the problem is presented, followed by an overview of the current research status. Subsequently, the existing literature is reviewed and categorized from the perspectives of single-model and multi-model approaches. In addition, typical real-world application scenarios are then summarized and analyzed. Finally, the key challenges and prospects in the field are thoroughly discussed. Note to Practitioners—As industrial production systems grow more complex, traditional fault diagnosis methods face considerable challenges in addressing multi-condition issues arising from changing production demands, dynamic process adjustments, and disturbances from complex external environments. As a result, multi-condition fault diagnosis has become a key area of research and has garnered extensive attention in recent years. This paper presents a systematic review of multi-condition fault diagnosis for dynamic systems, ranging from developmental overview to key frameworks to typical application scenarios. To assist researchers in quickly grasping the current trends in the industry, this paper further summarizes the challenges and future prospects within the field.