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

Li et al., 2019 - Google Patents

Framework and case study of cognitive maintenance in Industry 4.0

Li et al., 2019

Document ID
11448307881263371561
Author
Li B
Wang Y
Dai G
Wang K
Publication year
Publication venue
Frontiers of Information Technology & Electronic Engineering

External Links

Snippet

We present a new framework for cognitive maintenance (CM) based on cyber-physical systems and advanced artificial intelligence techniques. These CM systems integrate intelligent deep learning approaches and intelligent decision-making techniques, which can …
Continue reading at link.springer.com (other versions)

Classifications

    • 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
    • G05B23/0243Electric 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
    • 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
    • G05B23/0259Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0283Predictive 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]
    • 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
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00Systems controlled by a computer
    • G05B15/02Systems controlled by a computer electric
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • G06N5/02Knowledge representation
    • G06N5/022Knowledge engineering, knowledge acquisition
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00Program-control systems
    • G05B2219/30Nc systems
    • 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
    • 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
    • G06Q10/06Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00Programme-control systems
    • G05B19/02Programme-control systems electric
    • 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
Siahpour et al. A novel transfer learning approach in remaining useful life prediction for incomplete dataset
Compare et al. Challenges to IoT-enabled predictive maintenance for industry 4.0
Cai et al. Bayesian networks in fault diagnosis
Li et al. Framework and case study of cognitive maintenance in Industry 4.0
Zhang et al. DeepHealth: A self-attention based method for instant intelligent predictive maintenance in industrial Internet of Things
CN102520697B (en) Onsite information preprocessing method of remote cooperative diagnosis
Zhao et al. A novel cap-LSTM model for remaining useful life prediction
CN112085261A (en) Enterprise production status diagnosis method based on cloud fusion and digital twin technology
Zhao et al. Multiscale graph-guided convolutional network with node attention for intelligent health state diagnosis of a 3-PRR planar parallel manipulator
Keshun et al. Towards efficient and interpretative rolling bearing fault diagnosis via quadratic neural network with BI-LSTM
CN109492790A (en) Wind turbines health control method based on neural network and data mining
Chen et al. Kernel extreme learning machine based hierarchical machine learning for multi-type and concurrent fault diagnosis
Zhang et al. A novel fault diagnosis method for wind turbine based on adaptive multivariate time-series convolutional network using SCADA data
CN117454232A (en) Production network construction fault diagnosis, prediction and health management system and method
Mahmoud et al. Designing and prototyping the architecture of a digital twin for wind turbine
Xu et al. A composite quantile regression long short-term memory network with group lasso for wind turbine anomaly detection
Hu et al. Estimate remaining useful life for predictive railways maintenance based on LSTM autoencoder
Bond et al. A hybrid learning approach to prognostics and health management applied to military ground vehicles using time-series and maintenance event data
Wang et al. A survey on fault diagnosis of rotating machinery based on machine learning
CN118568471A (en) Intelligent power distribution station operation fault prediction method and system
El Kihel et al. Maintenance 4.0 Model Development for Production Lines in Industry 4.0 Using a Deep Learning Approach and IoT Data in Real-Time: an Experimental Case Study
Bai et al. Towards trustworthy remaining useful life prediction through multi-source information fusion and a novel LSTM-DAU model
Zhang et al. An unsupervised spatiotemporal fusion network augmented with random mask and time-relative information modulation for anomaly detection of machines with multiple measuring points
Wu et al. Intelligent fault diagnosis system based on big data
Akinci Applications of big data and AI in electric power systems engineering