Machines · 2022 · 22 citations · 56 references
EngineeringIndustrial EngineeringCondition AssessmentLifecycle EngineeringMaintenance EngineeringCondition MonitoringCondition-based MaintenanceEquipment MaintenancePredictive MaintenanceService LifeDegradation ModelingEquipment State EstimationLife PredictionLifetime PredictionRemaining Life EstimationRemaining Life PredictionRemaining Service Life PredictionService Life Prediction
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.
56
Recent advances in convolutional neural networks
Jiuxiang Gu, Zhenhua Wang, Jason Kuen et al. · Pattern Recognition · 2017 · 6.3K citations
Making Large-Scale SVM Learning Practical
Thorsten Joachims · Technical reports · 2006 · 4.3K citations · Full text
Face recognition: a convolutional neural-network approach
Sandra Lawrence, C. Lee Giles, Ah Chung Tsoi et al. · IEEE Transactions on Neural Networks · 1997 · 3.1K citations