Automated remote data acquisition and fault diagnostics of three phase squirrel cage induction motors

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dc.contributor.advisorFernández, Benito R.
dc.creatorVenugopal, Anand
dc.date.accessioned2021-09-30T23:45:02Z
dc.date.available2021-09-30T23:45:02Z
dc.date.issued2004-05-22
dc.description.abstractThe Squirrel Cage Induction Motor(SCIM) is a critical component of many industrial applications and has been over the years the subject of extensive study. Much work has been done on condition monitoring and fault diagnostics, with the objective of reducing uncertainty of operation and thereby preventing costly downtime. However the performance of current monitoring and fault diagnostic strategies warrant the need for a more robust and reliable condition monitoring system. This thesis outlines the work done on the related fields of Data Acquisition and Fault Diagnostics with regard to providing a more efficient and robust condition monitoring system for an Industrial Three Phase SCIM. The Automated Remote Data Acquisition and Signal Analysis architecture implementation involved building a hardware unit to acquire the currents and voltages from the three phases of the SCIM. The Data Acquisition (DAQ) was controlled by a software architecture that has extensive features built into it for automation, remote access, file transfer, data archival, error monitoring and signal analysis. Acquisition parameters can be configured dynamically and results of analysis can be viewed through remote access to a server location. Proper security measures have also been incorporated into the architecture. In the area of fault diagnostics, the thesis provides a comprehensive review of the common faults in SCIM’s, their causes and effects, and existing diagnostic technologies. A theoretical overview and implementation details with regard to the traditional signal-based fault diagnostic approach of Motor Current Signature Analysis (MCSA) is also presented. Focus has been applied on the use of analytical redundancy concepts for model-based fault diagnostics using banks of nonlinear observers for the detection, identification and severity assessment of the major faults occurring in three phase squirrel cage induction motors. Residual generation was done using Extended Kalman Filter (EKF) observers developed for healthy and faulty operating conditions. A comparative study is done against the traditional signal-based current signature analysis method under ideal and nonideal conditions including power supply distortions. Theoretical details and simulation results are presented. The current scope, limitations and future work being undertaken in this area are also outlineden_US
dc.description.departmentMechanical Engineeringen_US
dc.format.mediumelectronicen_US
dc.identifier.urihttps://hdl.handle.net/2152/88298
dc.identifier.urihttp://dx.doi.org/10.26153/tsw/15239
dc.language.isoengen_US
dc.relation.ispartofUT Electronic Theses and Dissertationsen_US
dc.rightsCopyright © is held by the author. Presentation of this material on the Libraries' web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works.en_US
dc.rights.restrictionRestricteden_US
dc.subjectAutomated remote data acquisitionen_US
dc.subjectSquirrel cage induction motoren_US
dc.subjectFault diagnosticsen_US
dc.titleAutomated remote data acquisition and fault diagnostics of three phase squirrel cage induction motorsen_US
dc.typeThesisen_US
dc.type.genreThesisen_US
thesis.degree.departmentMechanical Engineeringen_US
thesis.degree.disciplineManufacturing Systems Engineeringen_US
thesis.degree.grantorUniversity of Texas at Austinen_US
thesis.degree.levelMastersen_US
thesis.degree.nameMaster of Science in Engineeringen_US

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