[go: up one dir, main page]

Rosli et al., 2018 - Google Patents

Application of principal component analysis vs. Multiple linear regression in resolving influential factor subject to air booster compressor Motor failure

Rosli et al., 2018

View PDF
Document ID
9226182549110618746
Author
Rosli N
Ibrahim R
Ismail I
Bingi K
Publication year
Publication venue
2018 IEEE 4th International Symposium in Robotics and Manufacturing Automation (ROMA)

External Links

Snippet

Predictive maintenance is vital towards the industrial economy to improve equipment reliability, efficiency and reduce downtime. The main objective of this work was to investigate the most influential factors contributing to the failure of the industrial motor to improve …
Continue reading at www.researchgate.net (PDF) (other versions)

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
    • G05B23/0254—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 based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks
    • 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
    • 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
    • G05B23/024—Quantitative 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
    • 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
    • G05B23/0227—Qualitative history assessment, whereby the type of data acted upon, e.g. waveforms, images or patterns, is not relevant, e.g. rule based assessment; if-then decisions
    • 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
    • G05B23/0275—Fault isolation and identification, e.g. classify fault; estimate cause or root of failure
    • G05B23/0278—Qualitative, e.g. if-then rules; Fuzzy logic; Lookup tables; Symptomatic search; FMEA
    • 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

Similar Documents

Publication Publication Date Title
Wang et al. Wind turbine fault detection and identification through PCA-based optimal variable selection
Afridi et al. Artificial intelligence based prognostic maintenance of renewable energy systems: A review of techniques, challenges, and future research directions
US9483049B2 (en) Anomaly detection and diagnosis/prognosis method, anomaly detection and diagnosis/prognosis system, and anomaly detection and diagnosis/prognosis program
Soylemezoglu et al. Mahalanobis-Taguchi system as a multi-sensor based decision making prognostics tool for centrifugal pump failures
KR102301201B1 (en) Apparatus and method for precise state diagnosis of rotating machinery based on IoT sensor
Bae et al. Condition monitoring of a steam turbine generator using wavelet spectrum based control chart
CN1910434A (en) Method and apparatus to diagnose mechanical problems in machinery
Abbasi et al. Development of predictive maintenance interface using multiple linear regression
CN113189941A (en) Intelligent fault early warning method and system for power plant power generation equipment
Verma et al. Wavelet based fault detection and diagnosis using online mcsa of stator winding faults due to insulation failure in industrial induction machine
KR102694136B1 (en) Oil gas plant equipment failure prediction and diagnosis system based on artificial intelligence
Elhaija et al. A novel dataset and lightweight detection system for broken bars induction motors using optimizable neural networks
CN110469461B (en) Fracture estimation method and device for fan toothed belt and readable storage medium
CN116976191A (en) Method for predicting shafting stability degradation trend of hydroelectric generating set
Barros et al. Failure detection of an air production unit in operational context
CN120030802A (en) Data prediction method and system for thermal power plant equipment
Rosli et al. Application of principal component analysis vs. Multiple linear regression in resolving influential factor subject to air booster compressor Motor failure
Cao et al. Remaining useful life prediction of wind turbine generator bearing based on EMD with an indicator
Giantomassi et al. Signal based fault detection and diagnosis for rotating electrical machines: Issues and solutions
CN117951633A (en) Photovoltaic power generation equipment fault diagnosis method and system
CN115508703A (en) Multi-source information fusion motor fault diagnosis method and system
Abbasi et al. Condition based maintenance of oil and gas equipment: A review
Ferracuti et al. MSPCA with KDE thresholding to support QC in electrical motors production line
CN117672255B (en) Abnormal equipment identification method and system based on artificial intelligence and equipment operation sound
Rosli et al. Application of Principle Component Analysis in Resolving Influential Factor Subject to Industrial Motor Failure