Nothing Special   »   [go: up one dir, main page]

Li et al., 2023 - Google Patents

Life-cycle modeling driven by coupling competition degradation for remaining useful life prediction

Li et al., 2023

Document ID
15651296504534620004
Author
Li Y
Zhou Z
Sun C
Peng J
Nandi A
Yan R
Publication year
Publication venue
Reliability Engineering & System Safety

External Links

Snippet

Estimating latent degradation states of mechanical systems from observation data provide the basis for their prognostic and health management (PHM). Recently, deep learning models have been employed to extract latent degradation features from observation signals …
Continue reading at www.sciencedirect.com (other versions)

Classifications

    • 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
    • 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
    • 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
    • G06K9/6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
    • G06K9/6232Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods
    • G06K9/6247Extracting features by transforming the feature space, e.g. multidimensional scaling; Mappings, e.g. subspace methods based on an approximation criterion, e.g. principal component analysis
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00Computer systems based on specific mathematical models
    • G06N7/005Probabilistic networks
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F19/00Digital computing or data processing equipment or methods, specially adapted for specific applications
    • G06F19/30Medical informatics, i.e. computer-based analysis or dissemination of patient or disease data
    • G06F19/34Computer-assisted medical diagnosis or treatment, e.g. computerised prescription or delivery of medication or diets, computerised local control of medical devices, medical expert systems or telemedicine
    • G06F19/345Medical expert systems, neural networks or other automated diagnosis
    • 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
    • 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
    • G06K9/6279Classification techniques relating to the number of classes
    • 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
    • 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
Xu et al. Predicting pipeline leakage in petrochemical system through GAN and LSTM
Zhao et al. Multi-scale integrated deep self-attention network for predicting remaining useful life of aero-engine
Xu et al. Fault diagnosis of rolling bearing of wind turbines based on the variational mode decomposition and deep convolutional neural networks
Li et al. A directed acyclic graph network combined with CNN and LSTM for remaining useful life prediction
da Costa et al. Remaining useful lifetime prediction via deep domain adaptation
Xie et al. Graph neural network approach for anomaly detection
Ragab et al. Attention-based sequence to sequence model for machine remaining useful life prediction
Li et al. Life-cycle modeling driven by coupling competition degradation for remaining useful life prediction
Liu et al. Fault diagnosis and cause analysis using fuzzy evidential reasoning approach and dynamic adaptive fuzzy Petri nets
Deng et al. LSTMED: An uneven dynamic process monitoring method based on LSTM and Autoencoder neural network
Wang et al. A Bayesian inference-based approach for performance prognostics towards uncertainty quantification and its applications on the marine diesel engine
Ibrahim et al. Short‐Time Wind Speed Forecast Using Artificial Learning‐Based Algorithms
Yan et al. A deep learning framework for sensor-equipped machine health indicator construction and remaining useful life prediction
Zheng et al. Semi-supervised multivariate time series anomaly detection for wind turbines using generator SCADA data
Xiong et al. Controlled physics-informed data generation for deep learning-based remaining useful life prediction under unseen operation conditions
Li et al. A new generative adversarial network based imbalanced fault diagnosis method
Liu et al. Complex engineered system health indexes extraction using low frequency raw time-series data based on deep learning methods
Xu et al. Global attention mechanism based deep learning for remaining useful life prediction of aero-engine
CN112731890B (en) Method and device for detecting power plant equipment faults
Kong et al. A contrastive learning framework enhanced by unlabeled samples for remaining useful life prediction
Liu et al. Product quality prediction method in small sample data environment
Bai et al. A two-phase-based deep neural network for simultaneous health monitoring and prediction of rolling bearings
Chang et al. Temporal convolution-based sorting feature repeat-explore network combining with multi-band information for remaining useful life estimation of equipment
Guo et al. A stacked ensemble method based on TCN and convolutional bi-directional GRU with multiple time windows for remaining useful life estimation
Guo et al. MHT: A multiscale hourglass-transformer for remaining useful life prediction of aircraft engine