EPE Association: EPE 2001 - Topic 11e: Diagnostics

EPE 2001 - Topic 11e: Diagnostics
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2001 - Conference > EPE 2001 - Topic 11: SYSTEMS ENGINEERING > EPE 2001 - Topic 11e: Diagnostics

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   A new method for broken rotor bar detection in electrical drive
By E.Charnal; G.Clerc; L.Nicolas [View]
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Abstract: In this paper, the electromagnetic radiations of an induction motor, driven by a PWM inverter, are analysed in order to obtain information for the detection of broken rotor bars. Significant variations of the electric and magnetic field spectrums between healthy rotor and rotor with broken bar are observed. The high-frequency spectral analysis of axial radiations provides a new method to detect broken rotor bars in a motor driven by a PWM inverter.

   Induction Motor Load Effect Diagnostic Utilizing Instantaneous Power Spectrum
By M. Drif; N. Benouzza; A. Bendiabdellah; J.A. Dente [View]
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Abstract: Since a load's failure, like a dip of torque for example, has an effect on the machine supply current , then the current spectral analysis approach could be well suited for the study of load anomalies. But the current signature obtained depends on various phenomena and therefore a misunderstanding of the results is quite possible. In this paper an attempt has been made to investigate the monitoring and the diagnostic of a load connected to an induction motor by the use of the instantaneous power spectrum approach. The paper presents at first the effect of different load anomalies, in comparison with other machine anomalies such as broken bar faults. Simulation results are then presented for each kind of load anomalies. The relative merits of the instantaneous power spectrum approach can be well appreciated when its results are compared with those obtained from the current spectrum approach.

   Investigation of the Mechanical Fault Detection for Induction Motors
By Z. Ye; B. Wu [View]
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Abstract: Fault diagnostics of induction motor drive system can be achieved online through the Motor Current Signature Analysis Method. The advantages are obvious: the algorithm can be implemented in the control system scheme with the existing DSP controller and current transducers. Therefore no extra cost is required. However, owning to the fact that the monitored signal is rich in harmonics, with frequent dynamics, and the fundamental frequency of the drive changes within a wide range, the traditional method based on FFT analysis, does not meet the requirement. A novel online fault diagnostic algorithm for electrical faults of induction motors fed by variable speed drive is studied. The innovative approach features wavelet analysis and artificial neural network method. A new set of feature coefficients of the mechanical faults is extracted from the stator current by wavelet packet decomposition. The features are represented with different frequency resolutions. And because of the wavelet function, such a feature extraction method can be used for current signal with transients. It is also found that as long as the samples of each cycle is kept constant, the node numbers of the feature coefficients for the rotor bar breakage will always be around some of the certain nodes at certain Depths, despite the change of the fundamental frequency. These features are advantageous for the fault detection for induction motor drive system where there are many transients, rich harmonics distortion, and variable fundamental frequency. Multiple-layer perceptron network is employed as a tool for the detection algorithm. The feature coefficients with multiple frequency resolutions and the slip speed are used as the inputs of the artificial neural network. The proposed algorithm is evaluated on a 5 HP induction motor drive system and is proved to be able to distinguish between healthy and faulty conditions with high accuracy.

   Optimization of volume of a PFC Flyback structure under EMC constraint
By Ch. Larouci; J.-P. Ferrieux; L. Gerbaud; J. Roudet [View]
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Abstract: This paper presents a sizing and optimisation procedure of a Flyback structure used in Power Factor Correction (PFC) mode. The optimisation aim is to get the passive component optimal volume, to respect EMC standards and to minimise the whole losses in the structure. To avoid timedomain simulation, analytical models of the Flyback structure are developed and used to carry out an optimisation process. The robustness of two software algorithms is tested and different optimisation results are presented.

   Visual Diagnostics Based On Image Wavelet Transform
By Z. Hocenski; S. Rimac-Drlje; T. Keser [View]
[Download]

Abstract: The image processing described in this paper is used for visual quality control in ceramic tile production. The tiles surface quality is described by the surface defects. The described image processing is based on the discrete wavelet transform method. The diagnostic algorithm is described. It is based on comparing of the wavelet coefficients of the original image without surface defects and the real images of ceramic tiles. The method is verified by using the artificial defects on the image and sensitivity testing on failure contrast and size is done. The algorithm is evaluated experimentaly using the real tile images. The analysis of the detection capabilities and sensitivity expressed in nondetected failures and false proclaimed defect is done also. Optimal connection between the segment size and DSL for each type of surface failure could be used to make efficient system for quality control and failure classification in automated production process.

EPE 2001 - Topic 11e: Diagnostics
You are here: EPE Documents > 01 - EPE & EPE ECCE Conference Proceedings > EPE 2001 - Conference > EPE 2001 - Topic 11: SYSTEMS ENGINEERING > EPE 2001 - Topic 11e: Diagnostics
	[return to parent folder]

	A new method for broken rotor bar detection in electrical drive By E.Charnal; G.Clerc; L.Nicolas	[View] [Download]
Abstract: In this paper, the electromagnetic radiations of an induction motor, driven by a PWM inverter, are analysed in order to obtain information for the detection of broken rotor bars. Significant variations of the electric and magnetic field spectrums between healthy rotor and rotor with broken bar are observed. The high-frequency spectral analysis of axial radiations provides a new method to detect broken rotor bars in a motor driven by a PWM inverter.

	Induction Motor Load Effect Diagnostic Utilizing Instantaneous Power Spectrum By M. Drif; N. Benouzza; A. Bendiabdellah; J.A. Dente	[View] [Download]
Abstract: Since a load's failure, like a dip of torque for example, has an effect on the machine supply current , then the current spectral analysis approach could be well suited for the study of load anomalies. But the current signature obtained depends on various phenomena and therefore a misunderstanding of the results is quite possible. In this paper an attempt has been made to investigate the monitoring and the diagnostic of a load connected to an induction motor by the use of the instantaneous power spectrum approach. The paper presents at first the effect of different load anomalies, in comparison with other machine anomalies such as broken bar faults. Simulation results are then presented for each kind of load anomalies. The relative merits of the instantaneous power spectrum approach can be well appreciated when its results are compared with those obtained from the current spectrum approach.

	Investigation of the Mechanical Fault Detection for Induction Motors By Z. Ye; B. Wu	[View] [Download]
Abstract: Fault diagnostics of induction motor drive system can be achieved online through the Motor Current Signature Analysis Method. The advantages are obvious: the algorithm can be implemented in the control system scheme with the existing DSP controller and current transducers. Therefore no extra cost is required. However, owning to the fact that the monitored signal is rich in harmonics, with frequent dynamics, and the fundamental frequency of the drive changes within a wide range, the traditional method based on FFT analysis, does not meet the requirement. A novel online fault diagnostic algorithm for electrical faults of induction motors fed by variable speed drive is studied. The innovative approach features wavelet analysis and artificial neural network method. A new set of feature coefficients of the mechanical faults is extracted from the stator current by wavelet packet decomposition. The features are represented with different frequency resolutions. And because of the wavelet function, such a feature extraction method can be used for current signal with transients. It is also found that as long as the samples of each cycle is kept constant, the node numbers of the feature coefficients for the rotor bar breakage will always be around some of the certain nodes at certain Depths, despite the change of the fundamental frequency. These features are advantageous for the fault detection for induction motor drive system where there are many transients, rich harmonics distortion, and variable fundamental frequency. Multiple-layer perceptron network is employed as a tool for the detection algorithm. The feature coefficients with multiple frequency resolutions and the slip speed are used as the inputs of the artificial neural network. The proposed algorithm is evaluated on a 5 HP induction motor drive system and is proved to be able to distinguish between healthy and faulty conditions with high accuracy.

	Optimization of volume of a PFC Flyback structure under EMC constraint By Ch. Larouci; J.-P. Ferrieux; L. Gerbaud; J. Roudet	[View] [Download]
Abstract: This paper presents a sizing and optimisation procedure of a Flyback structure used in Power Factor Correction (PFC) mode. The optimisation aim is to get the passive component optimal volume, to respect EMC standards and to minimise the whole losses in the structure. To avoid timedomain simulation, analytical models of the Flyback structure are developed and used to carry out an optimisation process. The robustness of two software algorithms is tested and different optimisation results are presented.

	Visual Diagnostics Based On Image Wavelet Transform By Z. Hocenski; S. Rimac-Drlje; T. Keser	[View] [Download]
Abstract: The image processing described in this paper is used for visual quality control in ceramic tile production. The tiles surface quality is described by the surface defects. The described image processing is based on the discrete wavelet transform method. The diagnostic algorithm is described. It is based on comparing of the wavelet coefficients of the original image without surface defects and the real images of ceramic tiles. The method is verified by using the artificial defects on the image and sensitivity testing on failure contrast and size is done. The algorithm is evaluated experimentaly using the real tile images. The analysis of the detection capabilities and sensitivity expressed in nondetected failures and false proclaimed defect is done also. Optimal connection between the segment size and DSL for each type of surface failure could be used to make efficient system for quality control and failure classification in automated production process.