Condition monitoring of induction motors in the nuclear power station environment
| dc.contributor.advisor | Barendse, Paul Stanley | |
| dc.contributor.author | Rylands, Naasef | |
| dc.date.accessioned | 2019-02-19T13:38:53Z | |
| dc.date.available | 2019-02-19T13:38:53Z | |
| dc.date.issued | 2018 | |
| dc.date.updated | 2019-02-19T10:41:59Z | |
| dc.description.abstract | The induction motor is a highly utilised electrical machine in industry, with the nuclear industry being no exception. A typical nuclear power station usually contains more than 1000 motors, where they are used in safety and non-safety application. The efficient and fault-free operation of this machine is critical to the safe and economical operation of any plant, including nuclear power stations. A comprehensive literature review was conducted that covered the functioning of the induction machine, its common faults and methods of detecting these faults. The Condition Based Maintenance framework was introduced in which condition monitoring of induction machines is an essential component. The main condition monitoring methods were explained with the main focus being on Motor Current Signature Analysis (MCSA) and the various methods associated with it. Three analysis methods were selected for further study, namely, Current Signature Analysis, Instantaneous Power Signature Analysis (IPSA) and Motor Square Current Signature Analysis (MSCSA). Essentially, the methodology used in this dissertation was to study the three common motor faults (bearings, stator and rotor cage) in isolation and compare the results to that of the healthy motor of the same type. The test loads as well as fault severity were varied where possible to investigate its effect on the fault detection scheme. The data was processed using an FFT based algorithm programed in MATLAB. The results of the study of the three spectral analysis techniques showed that no single technique is able to detect motor faults under all tested circumstances. The MCSA technique proved the most capable of the three techniques as it was able to detect faults under most conditions, but generally suffered poor results in inverter driven motor applications. The IPSA and MSCSA techniques performed selectively when compared to MCSA and were relatively successful when detecting the mechanical faults. The fact that the former techniques produce results at unique points in the spectrum would suggest that they are more suitable for verifying results. As part of a comprehensive condition monitoring scheme, as required by a large population of the motors on a nuclear power station, the three techniques presented in this study could readily be incorporated into the Condition Based Maintenance framework where the strengths of each could be exploited. | |
| dc.identifier.apacitation | Rylands, N. (2018). <i>Condition monitoring of induction motors in the nuclear power station environment</i>. (). University of Cape Town ,Engineering and the Built Environment ,Department of Electrical Engineering. Retrieved from http://hdl.handle.net/11427/29686 | en_ZA |
| dc.identifier.chicagocitation | Rylands, Naasef. <i>"Condition monitoring of induction motors in the nuclear power station environment."</i> ., University of Cape Town ,Engineering and the Built Environment ,Department of Electrical Engineering, 2018. http://hdl.handle.net/11427/29686 | en_ZA |
| dc.identifier.citation | Rylands, N. 2018. Condition monitoring of induction motors in the nuclear power station environment. University of Cape Town. | en_ZA |
| dc.identifier.ris | TY - Thesis / Dissertation AU - Rylands, Naasef AB - The induction motor is a highly utilised electrical machine in industry, with the nuclear industry being no exception. A typical nuclear power station usually contains more than 1000 motors, where they are used in safety and non-safety application. The efficient and fault-free operation of this machine is critical to the safe and economical operation of any plant, including nuclear power stations. A comprehensive literature review was conducted that covered the functioning of the induction machine, its common faults and methods of detecting these faults. The Condition Based Maintenance framework was introduced in which condition monitoring of induction machines is an essential component. The main condition monitoring methods were explained with the main focus being on Motor Current Signature Analysis (MCSA) and the various methods associated with it. Three analysis methods were selected for further study, namely, Current Signature Analysis, Instantaneous Power Signature Analysis (IPSA) and Motor Square Current Signature Analysis (MSCSA). Essentially, the methodology used in this dissertation was to study the three common motor faults (bearings, stator and rotor cage) in isolation and compare the results to that of the healthy motor of the same type. The test loads as well as fault severity were varied where possible to investigate its effect on the fault detection scheme. The data was processed using an FFT based algorithm programed in MATLAB. The results of the study of the three spectral analysis techniques showed that no single technique is able to detect motor faults under all tested circumstances. The MCSA technique proved the most capable of the three techniques as it was able to detect faults under most conditions, but generally suffered poor results in inverter driven motor applications. The IPSA and MSCSA techniques performed selectively when compared to MCSA and were relatively successful when detecting the mechanical faults. The fact that the former techniques produce results at unique points in the spectrum would suggest that they are more suitable for verifying results. As part of a comprehensive condition monitoring scheme, as required by a large population of the motors on a nuclear power station, the three techniques presented in this study could readily be incorporated into the Condition Based Maintenance framework where the strengths of each could be exploited. DA - 2018 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 2018 T1 - Condition monitoring of induction motors in the nuclear power station environment TI - Condition monitoring of induction motors in the nuclear power station environment UR - http://hdl.handle.net/11427/29686 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/29686 | |
| dc.identifier.vancouvercitation | Rylands N. Condition monitoring of induction motors in the nuclear power station environment. []. University of Cape Town ,Engineering and the Built Environment ,Department of Electrical Engineering, 2018 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/29686 | en_ZA |
| dc.language.iso | eng | |
| dc.publisher.department | Department of Electrical Engineering | |
| dc.publisher.faculty | Faculty of Engineering and the Built Environment | |
| dc.publisher.institution | University of Cape Town | |
| dc.subject.other | Induction Motor | |
| dc.subject.other | Condition Monitoring | |
| dc.subject.other | Spectral Analysis | |
| dc.subject.other | Nuclear Power | |
| dc.title | Condition monitoring of induction motors in the nuclear power station environment | |
| dc.type | Master Thesis | |
| dc.type.qualificationlevel | Masters | |
| dc.type.qualificationname | MSc (Eng) |