The Experts below are selected from a list of 32289 Experts worldwide ranked by ideXlab platform
Sylvie Turri - One of the best experts on this subject based on the ideXlab platform.
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Performance Analysis of an EEMD-based Hilbert Huang Transform as a Bearing Failure Detector in Wind Turbines
2014Co-Authors: Yassine Amirat, Mohamed Benbouzid, Tianzhen Wang, Sylvie TurriAbstract:Sustainability and viability of wind farms are highly dependent on the reduction of the operational and maintenance costs. The most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the degeneration of the generator health, facilitating a proactive response, minimizing downtime, and maximizing productivity. This paper deals then with the assessment of a demodulation technique for Bearing Failure detection through wind turbines generator stator current. The proposed technique is based on a modified version of the Hilbert Huang transform. In this version, the use of the EEMD algorithm allows overcoming the well-known mixed mode.
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Hilbert Transform-Based Bearing Failure Detection in DFIG-Based Wind Turbines
International Review of Electrical Engineering, 2011Co-Authors: Yassine Amirat, Mohamed Benbouzid, Vincent Choqueuse, Sylvie TurriAbstract:Cost-effective, predictive and proactive maintenance of wind turbines assumes more importance with the increasing number of installed wind farms in more remote location (offshore). A well-known method for assessing impeding problems is to use current sensors installed within the wind turbine generator. This paper describes then an approach based on the generator stator current data collection and attempts to highlight the use of the Hilbert transform for Failure detection in a doubly-fed induction generator-based. Indeed, this generator is commonly used in modern variable-speed wind turbines. The proposed Failure detection technique has been validated experimentally regarding Bearing Failures. Indeed, a large fraction of wind turbine downtime is due to Bearing Failures, particularly in the generator and gearbox.
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Hilbert Transform-Based Bearing Failure Detection in DFIG-Based Wind Turbines
International Review of Electrical Engineering-iree, 2011Co-Authors: Yassine Amirat, Mohamed Benbouzid, Vincent Choqueuse, Sylvie TurriAbstract:Cost-effective, predictive and proactive maintenance of wind turbines assumes more importance with the increasing number of installed wind farms in more remote location (offshore). A well-known method for assessing impeding problems is to use current sensors installed within the wind turbine generator. This paper describes then an approach based on the generator stator current data collection and attempts to highlight the use of the Hilbert transform for Failure detection in a doubly-fed induction generator-based. Indeed, this generator is commonly used in modern variable-speed wind turbines. The proposed Failure detection technique has been validated experimentally regarding Bearing Failures. Indeed, a large fraction of wind turbine downtime is due to Bearing Failures, particularly in the generator and gearbox. Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved.
Yassine Amirat - One of the best experts on this subject based on the ideXlab platform.
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Performance Analysis of an EEMD-based Hilbert Huang Transform as a Bearing Failure Detector in Wind Turbines
2014Co-Authors: Yassine Amirat, Mohamed Benbouzid, Tianzhen Wang, Sylvie TurriAbstract:Sustainability and viability of wind farms are highly dependent on the reduction of the operational and maintenance costs. The most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the degeneration of the generator health, facilitating a proactive response, minimizing downtime, and maximizing productivity. This paper deals then with the assessment of a demodulation technique for Bearing Failure detection through wind turbines generator stator current. The proposed technique is based on a modified version of the Hilbert Huang transform. In this version, the use of the EEMD algorithm allows overcoming the well-known mixed mode.
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Hilbert Transform-Based Bearing Failure Detection in DFIG-Based Wind Turbines
International Review of Electrical Engineering, 2011Co-Authors: Yassine Amirat, Mohamed Benbouzid, Vincent Choqueuse, Sylvie TurriAbstract:Cost-effective, predictive and proactive maintenance of wind turbines assumes more importance with the increasing number of installed wind farms in more remote location (offshore). A well-known method for assessing impeding problems is to use current sensors installed within the wind turbine generator. This paper describes then an approach based on the generator stator current data collection and attempts to highlight the use of the Hilbert transform for Failure detection in a doubly-fed induction generator-based. Indeed, this generator is commonly used in modern variable-speed wind turbines. The proposed Failure detection technique has been validated experimentally regarding Bearing Failures. Indeed, a large fraction of wind turbine downtime is due to Bearing Failures, particularly in the generator and gearbox.
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Hilbert Transform-Based Bearing Failure Detection in DFIG-Based Wind Turbines
International Review of Electrical Engineering-iree, 2011Co-Authors: Yassine Amirat, Mohamed Benbouzid, Vincent Choqueuse, Sylvie TurriAbstract:Cost-effective, predictive and proactive maintenance of wind turbines assumes more importance with the increasing number of installed wind farms in more remote location (offshore). A well-known method for assessing impeding problems is to use current sensors installed within the wind turbine generator. This paper describes then an approach based on the generator stator current data collection and attempts to highlight the use of the Hilbert transform for Failure detection in a doubly-fed induction generator-based. Indeed, this generator is commonly used in modern variable-speed wind turbines. The proposed Failure detection technique has been validated experimentally regarding Bearing Failures. Indeed, a large fraction of wind turbine downtime is due to Bearing Failures, particularly in the generator and gearbox. Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved.
Mohamed Benbouzid - One of the best experts on this subject based on the ideXlab platform.
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Performance Analysis of an EEMD-based Hilbert Huang Transform as a Bearing Failure Detector in Wind Turbines
2014Co-Authors: Yassine Amirat, Mohamed Benbouzid, Tianzhen Wang, Sylvie TurriAbstract:Sustainability and viability of wind farms are highly dependent on the reduction of the operational and maintenance costs. The most efficient way of reducing these costs would be to continuously monitor the condition of these systems. This allows for early detection of the degeneration of the generator health, facilitating a proactive response, minimizing downtime, and maximizing productivity. This paper deals then with the assessment of a demodulation technique for Bearing Failure detection through wind turbines generator stator current. The proposed technique is based on a modified version of the Hilbert Huang transform. In this version, the use of the EEMD algorithm allows overcoming the well-known mixed mode.
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Hilbert Transform-Based Bearing Failure Detection in DFIG-Based Wind Turbines
International Review of Electrical Engineering, 2011Co-Authors: Yassine Amirat, Mohamed Benbouzid, Vincent Choqueuse, Sylvie TurriAbstract:Cost-effective, predictive and proactive maintenance of wind turbines assumes more importance with the increasing number of installed wind farms in more remote location (offshore). A well-known method for assessing impeding problems is to use current sensors installed within the wind turbine generator. This paper describes then an approach based on the generator stator current data collection and attempts to highlight the use of the Hilbert transform for Failure detection in a doubly-fed induction generator-based. Indeed, this generator is commonly used in modern variable-speed wind turbines. The proposed Failure detection technique has been validated experimentally regarding Bearing Failures. Indeed, a large fraction of wind turbine downtime is due to Bearing Failures, particularly in the generator and gearbox.
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Hilbert Transform-Based Bearing Failure Detection in DFIG-Based Wind Turbines
International Review of Electrical Engineering-iree, 2011Co-Authors: Yassine Amirat, Mohamed Benbouzid, Vincent Choqueuse, Sylvie TurriAbstract:Cost-effective, predictive and proactive maintenance of wind turbines assumes more importance with the increasing number of installed wind farms in more remote location (offshore). A well-known method for assessing impeding problems is to use current sensors installed within the wind turbine generator. This paper describes then an approach based on the generator stator current data collection and attempts to highlight the use of the Hilbert transform for Failure detection in a doubly-fed induction generator-based. Indeed, this generator is commonly used in modern variable-speed wind turbines. The proposed Failure detection technique has been validated experimentally regarding Bearing Failures. Indeed, a large fraction of wind turbine downtime is due to Bearing Failures, particularly in the generator and gearbox. Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved.
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Induction Motors Bearing Failures Detection and Diagnosis: Park and Concordia Transform Approaches Comparative Study
2007 IEEE International Electric Machines & Drives Conference, 2007Co-Authors: Izzet Y. Önel, Mohamed BenbouzidAbstract:This paper deals with the problem of Bearing Failure detection and diagnosis in induction motors. Indeed, Bearings deterioration is now the main cause of induction motor rotor Failures. In this context, two fault detection and diagnosis techniques, namely the Park transform approach and the Concordia transform, are briefly presented and compared. Experimental tests, on a 0.75-kW two-pole induction motor with artificial Bearing damages, outline the above approaches main features for small and medium size induction motors Bearing Failure detection and/or diagnosis.
Ryszard Szczepanik - One of the best experts on this subject based on the ideXlab platform.
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Analysis of middle Bearing Failure in rotor jet engine using tip-timing and tip-clearance techniques
Mechanical Systems and Signal Processing, 2016Co-Authors: Romuald Rzadkowski, Edward Rokicki, L. Piechowski, Ryszard SzczepanikAbstract:Abstract The reported problem is the Failure of the middle Bearing in an aircraft rotor engine. Tip-timing and tip-clearance and variance analyses are carried out on a compressor rotor blade in the seventh stage above the middle Bearing. The experimental analyses concern both an aircraft engine with a middle Bearing in good working order and an engine with a damaged middle Bearing. A numerical analysis of seventh stage blade free vibration is conducted to explain the experimental results. This appears to be an effective method of predicting middle Bearing Failure. The results show that variance first increases in the initial stages of Bearing Failure, but then starts to decrease and stabilize, and then again decrease shortly before complete Bearing Failure.
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Analysis of Middle Bearing Failure in Rotor Jet Engine Using Tip-Timing and Tip-Clearance Technique
Volume 7A: Structures and Dynamics, 2014Co-Authors: Edward Rokicki, Romuald Rzadkowski, Ryszard Szczepanik, Paweł Majewski, Jarosław Spychała, Marcin DrewczynskiAbstract:The reported problem is the Failure of the middle Bearing in an aircraft rotor engine. Tip-timing and tip-clearance and variance analyses are carried out on a compressor rotor blade in the seventh stage above the middle Bearing. The experimental analyses concern both an aircraft engine with a middle Bearing in good working order and an engine with a damaged middle Bearing. A numerical analysis of the seventh stage blade free vibration are conducted to explain the experimental results. This appears to be an effective method of predicting middle Bearing Failure. The blade vibration variance increases when there is Bearing Failure.© 2014 ASME
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Analysis Of Middle Bearing Failure In So-3 Jet Engine Using Tip-Timing
2011Co-Authors: Ryszard Szczepanik, Edward Rokicki, M. KowalskiAbstract:Failure of the middle Bearing in an SO-3 engine was reported. Tip-timing and pick detector analyses were carried out on a compressor rotor blade in the seventh stage above the middle Bearing. The experimental analyses concerned both an SO-3 engine with a middle Bearing in good working order and an engine with a damaged middle Bearing. A numerical analysis of the free vibration of the seventh stage blade was conducted to verify the experimental ones. Proposed in this paper is a method to prevent middle Bearing Failure.
Vincent Choqueuse - One of the best experts on this subject based on the ideXlab platform.
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Hilbert Transform-Based Bearing Failure Detection in DFIG-Based Wind Turbines
International Review of Electrical Engineering, 2011Co-Authors: Yassine Amirat, Mohamed Benbouzid, Vincent Choqueuse, Sylvie TurriAbstract:Cost-effective, predictive and proactive maintenance of wind turbines assumes more importance with the increasing number of installed wind farms in more remote location (offshore). A well-known method for assessing impeding problems is to use current sensors installed within the wind turbine generator. This paper describes then an approach based on the generator stator current data collection and attempts to highlight the use of the Hilbert transform for Failure detection in a doubly-fed induction generator-based. Indeed, this generator is commonly used in modern variable-speed wind turbines. The proposed Failure detection technique has been validated experimentally regarding Bearing Failures. Indeed, a large fraction of wind turbine downtime is due to Bearing Failures, particularly in the generator and gearbox.
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Hilbert Transform-Based Bearing Failure Detection in DFIG-Based Wind Turbines
International Review of Electrical Engineering-iree, 2011Co-Authors: Yassine Amirat, Mohamed Benbouzid, Vincent Choqueuse, Sylvie TurriAbstract:Cost-effective, predictive and proactive maintenance of wind turbines assumes more importance with the increasing number of installed wind farms in more remote location (offshore). A well-known method for assessing impeding problems is to use current sensors installed within the wind turbine generator. This paper describes then an approach based on the generator stator current data collection and attempts to highlight the use of the Hilbert transform for Failure detection in a doubly-fed induction generator-based. Indeed, this generator is commonly used in modern variable-speed wind turbines. The proposed Failure detection technique has been validated experimentally regarding Bearing Failures. Indeed, a large fraction of wind turbine downtime is due to Bearing Failures, particularly in the generator and gearbox. Copyright © 2011 Praise Worthy Prize S.r.l. - All rights reserved.