Xie et al., 2019 - Google Patents
Estimating the probability density function of remaining useful life for wiener degradation process with uncertain parametersXie et al., 2019
- Document ID
- 786259044876739330
- Author
- Xie G
- Li X
- Peng X
- Qian F
- Hei X
- Publication year
- Publication venue
- International Journal of Control, Automation and Systems
External Links
Snippet
The effective prediction of remaining useful life is essential to realize system failure diagnosis and health management. The existing researches often assume that the degradation model is constant or the degradation process is measurable. The accurate …
- 238000006731 degradation reaction 0 title abstract description 85
Classifications
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0243—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults model based detection method, e.g. first-principles knowledge model
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
- G05B23/0224—Process history based detection method, e.g. whereby history implies the availability of large amounts of data
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
- G05B23/0283—Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL]
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/50—Computer-aided design
- G06F17/5009—Computer-aided design using simulation
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B17/00—Systems involving the use of models or simulators of said systems
- G05B17/02—Systems involving the use of models or simulators of said systems electric
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32234—Maintenance planning
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41875—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by quality surveillance of production
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Xie et al. | Estimating the probability density function of remaining useful life for wiener degradation process with uncertain parameters | |
Wen et al. | Multiple-phase modeling of degradation signal for condition monitoring and remaining useful life prediction | |
Zhao et al. | Online probabilistic estimation of sensor faulty signal in industrial processes and its applications | |
Zhang et al. | A hybrid method for cutting tool RUL prediction based on CNN and multistage Wiener process using small sample data | |
Xu et al. | PHM-oriented integrated fusion prognostics for aircraft engines based on sensor data | |
Li et al. | A sequential Bayesian updated Wiener process model for remaining useful life prediction | |
Wang et al. | Methods for predicting the remaining useful life of equipment in consideration of the random failure threshold | |
Xue et al. | An improved generic hybrid prognostic method for RUL prediction based on PF-LSTM learning | |
Son et al. | RUL prediction for individual units based on condition monitoring signals with a change point | |
CN113391622B (en) | Spacecraft attitude system anomaly detection method using multivariate multistep prediction technology | |
Huang et al. | A novel Bayesian deep dual network with unsupervised domain adaptation for transfer fault prognosis across different machines | |
Wang et al. | Multivariate relevance vector regression based degradation modeling and remaining useful life prediction | |
Skordilis et al. | A double hybrid state-space model for real-time sensor-driven monitoring of deteriorating systems | |
Peng et al. | Leveraging degradation testing and condition monitoring for field reliability analysis with time-varying operating missions | |
Wang et al. | Lévy process-based stochastic modeling for machine performance degradation prognosis | |
Zhongyi et al. | Remaining useful lifetime prediction for equipment based on nonlinear implicit degradation modeling | |
Zhao et al. | Research on digital twin driven rolling bearing model-data fusion life prediction method | |
Wei et al. | Remaining useful life estimation based on gamma process considered with measurement error | |
Su et al. | A novel multi‐hidden semi‐Markov model for degradation state identification and remaining useful life estimation | |
Xiong et al. | Steering actuator fault diagnosis for autonomous vehicle with an adaptive denoising residual network | |
Jia et al. | Active fault diagnosis for a class of closed-loop systems via parameter estimation | |
Wang et al. | Remaining useful life prediction based on nonlinear random coefficient regression model with fusing failure time data | |
Knödler et al. | The potential of data-driven engineering models: An analysis across domains in the automotive development process | |
Dhakal et al. | UAV fault and anomaly detection using autoencoders | |
Rashid et al. | Automated active and idle time measurement in modular construction factory using inertial measurement unit and deep learning for dynamic simulation input |