Fault Detection Techniques Using by Naghmash Majid (8 results)

Condition: New. pp. 104.

Taschenbuch. Condition: Neu. Fault detection techniques using current signature analysis methods | Optimization of Fast Fourier Transform (FFT) algorithm and Wavelet Transform (WT) based multi resolution analysis | Majid Naghmash (u. a.) | Taschenbuch | 104 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783846555347 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -There are many condition monitoring methods such as vibration monitoring, thermal monitoring, chemical monitoring and acoustic emission monitoring. But all of these monitoring methods require expensive sensors and specialized tools. However, the condition monitoring method and fault diagnosis based on motor current signature are a better option since they do not require additional sensors. In this research, a novel criterion function of wavelet processing signal is introduced to diagnose the broken rotor bars in three-phase squirrel cage induction motors. This criterion function facilitates the precise diagnosis of the faults in induction motors under load variations. It uses wavelet transforms available in LabView software to process the stator current signals in the faulty induction motors to extract the wavelet coefficients in a specific time-frequency bands. Furthermore, spectrum analysis of the stator currents around the fundamental frequency is used to diagnose the faults. It is shown that the amplitudes of the frequency harmonics components fb=fs(1±2s) are influenced by the number of broken rotor bars, the exact location of broken rotor bars and the motor loading condition. 104 pp. Englisch.

Condition: New. Print on Demand pp. 104 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Condition: New. PRINT ON DEMAND pp. 104.

Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Naghmash MajidKhaleel J.Hammady has been a full-time lecturer in the Department of Electronic Techniques, Institute of technology- Baghdad, Ministry of high education and scientific research/Iraq. Received his MS and PhD degree in El.

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -There are many condition monitoring methods such as vibration monitoring, thermal monitoring, chemical monitoring and acoustic emission monitoring. But all of these monitoring methods require expensive sensors and specialized tools. However, the condition monitoring method and fault diagnosis based on motor current signature are a better option since they do not require additional sensors. In this research, a novel criterion function of wavelet processing signal is introduced to diagnose the broken rotor bars in three-phase squirrel cage induction motors. This criterion function facilitates the precise diagnosis of the faults in induction motors under load variations. It uses wavelet transforms available in LabView software to process the stator current signals in the faulty induction motors to extract the wavelet coefficients in a specific time-frequency bands. Furthermore, spectrum analysis of the stator currents around the fundamental frequency is used to diagnose the faults. It is shown that the amplitudes of the frequency harmonics components fb=fs(1±2s) are influenced by the number of broken rotor bars, the exact location of broken rotor bars and the motor loading condition.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 104 pp. Englisch.

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - There are many condition monitoring methods such as vibration monitoring, thermal monitoring, chemical monitoring and acoustic emission monitoring. But all of these monitoring methods require expensive sensors and specialized tools. However, the condition monitoring method and fault diagnosis based on motor current signature are a better option since they do not require additional sensors. In this research, a novel criterion function of wavelet processing signal is introduced to diagnose the broken rotor bars in three-phase squirrel cage induction motors. This criterion function facilitates the precise diagnosis of the faults in induction motors under load variations. It uses wavelet transforms available in LabView software to process the stator current signals in the faulty induction motors to extract the wavelet coefficients in a specific time-frequency bands. Furthermore, spectrum analysis of the stator currents around the fundamental frequency is used to diagnose the faults. It is shown that the amplitudes of the frequency harmonics components fb=fs(1±2s) are influenced by the number of broken rotor bars, the exact location of broken rotor bars and the motor loading condition.