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Overview of Equipment Health State Estimation and Remaining Life Prediction Methods

Jingyi Zhao, Chunhai Gao, Tao Tang, Xiao Xiao, Ming Luo, Binbin Yuan

2022Machines22 citationsDOIOpen Access PDF

Abstract

Health state estimation can quantitatively evaluate the current degradation state of equipment, and remaining life prediction can quantitatively predict the remaining service time of equipment. These two technologies can provide a basis for condition-based maintenance and predictive maintenance of equipment, respectively. In recent years, a large amount of research has been implemented in these two technologies. However, there is not any systematic review that covers these two technologies, and their engineering applications, comprehensively. To fill the gap, this paper makes a comparative analysis of existing health state estimation and remaining life prediction methods, and details the characteristics and limitations of various methods. The engineering applications of these two methods are summarized, and their applicable objects are briefly given. Finally, these two methods are summarized, and their feasibility for engineering application is discussed. This work provides guidance for the selection of industrial equipment health assessment and remaining life prediction methods.

Topics & Concepts

Reliability engineeringEstimationComputer sciencePredictive maintenanceState (computer science)Risk analysis (engineering)Selection (genetic algorithm)State of healthEngineeringSystems engineeringMachine learningBattery (electricity)MedicineQuantum mechanicsAlgorithmPhysicsPower (physics)Reliability and Maintenance OptimizationMachine Fault Diagnosis TechniquesNon-Destructive Testing Techniques
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