van der Laan, 2016 - Google Patents

System reliability analysis of belt conveyor

van der Laan, 2016

View PDF
Document ID
11845630799651410355
Author
van der Laan B
Publication year
Publication venue
Transportation engineering

External Links

Continue reading at repository.tudelft.nl (PDF) (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
    • 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
    • G05B23/0224Process history based detection method, e.g. whereby history implies the availability of large amounts of data
    • G05B23/024Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural 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
    • G05B23/0259Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
    • G05B23/0275Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
    • G05B23/0278Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA

Similar Documents

Publication Publication Date Title
Ahmad et al. An overview of time-based and condition-based maintenance in industrial application
Daniyan et al. Artificial intelligence for predictive maintenance in the railcar learning factories
Saon et al. Predicting remaining useful life of rotating machinery based artificial neural network
Van Tung et al. Machine fault diagnosis and prognosis: The state of the art
Guo et al. Mechanical fault time series prediction by using EFMSAE-LSTM neural network
Roemer et al. Development of diagnostic and prognostic technologies for aerospace health management applications
Mazurkiewicz Maintenance of belt conveyors using an expert system based on fuzzy logic
Herzog et al. Machine and component residual life estimation through the application of neural networks
Krenek et al. Application of artificial neural networks in condition based predictive maintenance
Sun et al. Benefits analysis of prognostics in systems
Shimada et al. A statistical approach to reduce failure facilities based on predictive maintenance
Daniyan et al. Artificial intelligence system for enhancing product’s performance during its life cycle in a railcar industry
von Hahn et al. Knowledge informed machine learning using a weibull-based loss function
van der Laan System reliability analysis of belt conveyor
SikorA et al. Monitoring and maintenance of a gantry based on a wireless system for measurement and analysis of the vibration level
Xingxin et al. Research on online fault detection tool of substation equipment based on artificial intelligence
El Kihel et al. Method of Implementing Maintenance 4.0 in Industry-A Case study of an Industrial System
Mohan et al. LSTM based artificial intelligence predictive maintenance technique for availability rate and OEE improvement in a TPM implementing plant through Industry 4.0 transformation
Heng Intelligent prognostics of machinery health utilising suspended condition monitoring data
Karadayi et al. Fault-related Alarm Detection of a Wind Turbine SCADA System
Wang et al. Accurate prediction of RUL under uncertainty conditions: Application to the traction system of a high-speed train
Asmai et al. A framework of an intelligent maintenance prognosis tool
Arabgol et al. Artificial neural network and ewma-based fault prediction in wind turbines
Li et al. Health state prediction and performance evaluation of belt conveyor based on dynamic Bayesian network in underground mining
Zemenkova et al. Timely intellectual control of safety and reliability of operation of power-mechanical equipment during transportation of oil and petroleum products