Search results for "fault diagnosi"

showing 5 items of 25 documents

Real-Time Detection of Incipient Inter-Turn Short Circuit and Sensor Faults in Permanent Magnet Synchronous Motor Drives Based on Generalized Likelih…

2022

This paper presents a robust model-based technique to detect multiple faults in permanent magnet synchronous motors (PMSMs), namely inter-turn short circuit (ITSC) and encoder faults. The proposed model is based on a structural analysis, which uses the dynamic mathematical model of a PMSM in an abc frame to evaluate the system’s structural model in matrix form. The just-determined and over-determined parts of the system are separated by a Dulmage–Mendelsohn decomposition tool. Subsequently, the analytical redundant relations obtained using the over-determined part of the system are used to form smaller redundant testable sub-models based on the number of defined fault terms. Furthermore, fo…

VDP::Teknologi: 500VDP::Teknologi: 500::Maskinfag: 570fault diagnosis; inter-turn short circuit; sensor fault; structural analysis; generalized likelihood ratio test; PM synchronous motorElectrical and Electronic EngineeringBiochemistryInstrumentationAtomic and Molecular Physics and OpticsAnalytical ChemistrySensors (Basel, Switzerland)
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Monitoring and Diagnosis of Failures in Squirrel-Cage Induction Motors Due to Cracked or Broken Bars

2011

In this paper three diagnostic procedures, based on on the vibration, current and instantaneous power monitoring for the detection and monitoring of incipient faults as cracks or bar breaks on squirrel cage motors are briefly reminded. The experimental investigations, carried out at the SDESLab (Sustainable Development Energy Savings Laboratory) of the University of Palermo in order to underline merits and drawbacks of the methods applied to the same die cast squirrel cage induction motor, are presented. The results of the investigations confirmed the effectiveness of the diagnostic procedures here considered.

VibrationEngineeringbusiness.industrySquirrel-cage rotorStructural engineeringInduction machines squirrel cage fault diagnosis broken rotor bar.Settore ING-IND/32 - Convertitori Macchine E Azionamenti ElettricibusinessInduction motor
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Quantitative Rotor Broken Bar Evaluation in Double Squirrel Cage Induction Machines under Dynamic Operating Conditions

2013

Advanced monitoring techniques leading to fault diagnosis and prediction of induction machine faults, operating under non-stationary conditions have gained strength because of its considerable influence on the operational continuation of many industrial processes. In case of rotor broken bars, fault detection based on sideband components issued from currents, flux, instantaneous control or power signals under different load conditions, may fail due to the presence of inter-bar currents that reduce the degree of rotor asymmetry, especially for double squirrel cage induction motors. But the produced core vibrations in the axial direction, can be investigated to overcome the limitation of the …

discrete wavelet transformEngineeringbusiness.industryRotor (electric)Squirrel-cage rotorBar (music)squirrel cage motorSettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciFault (power engineering)FAULT DIAGNOSISFault detection and isolationPower (physics)law.inventionVibrationTime-Frequency AnalysisControl theorylawAC Machine Condition monitoring Double cage rotor fault diagnostics induction motor wavelet TransformbusinessInduction motor
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Fault diagnosis of induction motors broken rotor bars by pattern recognition based on noise cancelation

2014

Current signal monitoring (CSM) can be used as an effective tool for diagnosing broken rotor bars fault in induction motors. In this paper, fault diagnosis and classification based on artificial neural networks (ANNs) is done in two stages. In the first stage, a filter is designed to remove irrelevant fault components (such as noise) of current signals. The coefficients of the filter are obtained by least square (LS) algorithm. Then by extracting suitable time domain features from filter's output, a neural network is trained for fault classification. The output vector of this network is represented in one of four categories that includes healthy mode, a 5 mm crack on a bar, one broken bar, …

removing irrelevant fault componentsEngineeringArtificial neural networkneural networkRotor (electric)Bar (music)business.industryComputer Science::Neural and Evolutionary ComputationFilter (signal processing)Fault (power engineering)law.inventionNoisefault diagnosis and classificationControl and Systems Engineeringlawfault diagnosis and classification; neural network; removing irrelevant fault components; Stator current signal monitoring; Electrical and Electronic Engineering; Control and Systems EngineeringElectronic engineeringTime domainElectrical and Electronic EngineeringStator current signal monitoringbusinessAlgorithmInduction motor2014 IEEE 23rd International Symposium on Industrial Electronics (ISIE)
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Use cases for operational decision support system

2008

vikadiagnoositvian eristäminenmittausoperaatiotylläpitomittauksetpäätöksentekotiedonhallintafault isolationfault diagnosisepävarmuuscollaborationyhteistyöoperationprosessiteollisuusoptimointihuoltooptimization
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