[go: up one dir, main page]
More Web Proxy on the site http://driver.im/

Liu et al., 2022 - Google Patents

A CNN-LSTM-based domain adaptation model for remaining useful life prediction

Liu et al., 2022

Document ID
3238362777101685124
Author
Liu H
Chen W
Chen W
Gu Y
Publication year
Publication venue
Measurement Science and Technology

External Links

Snippet

Remaining useful life (RUL) estimation is fundamental to prediction and health management technology. Traditional machine learning generally assumes that the training and testing sets are independent and identically distributed. As distribution differences exist in real …
Continue reading at iopscience.iop.org (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • G06N99/005Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00Computer systems based on biological models
    • G06N3/02Computer systems based on biological models using neural network models
    • G06N3/08Learning methods
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • G06F17/30861Retrieval from the Internet, e.g. browsers
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/62Methods or arrangements for recognition using electronic means
    • G06K9/6267Classification techniques
    • G06K9/6268Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/04Inference methods or devices
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/10Complex mathematical operations
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00Administration; Management
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00Systems or methods specially adapted for a specific business sector, e.g. utilities or tourism

Similar Documents

Publication Publication Date Title
Zhao et al. Bearing fault diagnosis using transfer learning and optimized deep belief network
Yang et al. Bearing remaining useful life prediction based on regression shapalet and graph neural network
Singh et al. Deep learning-based cross-domain adaptation for gearbox fault diagnosis under variable speed conditions
Xu et al. Predicting pipeline leakage in petrochemical system through GAN and LSTM
Zhang et al. Marine systems and equipment prognostics and health management: a systematic review from health condition monitoring to maintenance strategy
Wang et al. A combination of residual and long–short-term memory networks for bearing fault diagnosis based on time-series model analysis
Wu et al. Layer-wise relevance propagation for interpreting LSTM-RNN decisions in predictive maintenance
Liu et al. A CNN-LSTM-based domain adaptation model for remaining useful life prediction
Li et al. Prediction of wind turbine blades icing based on feature Selection and 1D-CNN-SBiGRU
Zhang et al. Rotating Machinery Remaining Useful Life Prediction Scheme Using Deep‐Learning‐Based Health Indicator and a New RVM
An et al. An intelligent fault diagnosis framework dealing with arbitrary length inputs under different working conditions
Lin et al. Attention-based Gate Recurrent Unit for remaining useful life prediction in prognostics
Liang et al. Multi-sensor data fusion and bidirectional-temporal attention convolutional network for remaining useful life prediction of rolling bearing
Zhao et al. A novel bootstrap ensemble learning convolutional simple recurrent unit method for remaining useful life interval prediction of turbofan engines
Xu et al. Multi-resolution LSTM-based prediction model for remaining useful life of aero-engine
Guo et al. MHT: A multiscale hourglass-transformer for remaining useful life prediction of aircraft engine
Kim et al. An adaptive sensor selection framework for multisensor prognostics
Lan et al. Performance degradation prediction model of rolling bearing based on self-checking long short-term memory network
Wang et al. Combining autoencoder with similarity measurement for aircraft engine remaining useful life estimation
Xing et al. VMD-IARIMA-Based Time-Series Forecasting Model and its Application in Dissolved Gas Analysis
Wang et al. Similarity-based probabilistic remaining useful life estimation for an aeroengine under variable operational conditions
Wang et al. Hierarchical graph neural network with adaptive cross-graph fusion for remaining useful life prediction
Wang et al. A denoising semi-supervised deep learning model for remaining useful life prediction of turbofan engine degradation
Deng et al. An intelligent hybrid deep learning model for rolling bearing remaining useful life prediction
Zhang et al. Degradation trend feature generation improved rotating machines RUL prognosis method with limited run-to-failure data