Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Surya Teja Kandukuri"'
Autor:
Steffen Haus, Heiko Mikat, Martin Nowara, Surya Teja Kandukuri, Uwe Klingauf, Matthias Buderath
Publikováno v:
International Journal of Prognostics and Health Management, Vol 4, Iss 2, Pp 21-40 (2013)
Future health monitoring concepts in different fields of engineering require reliable fault detection to avoid unscheduled machine downtime. Diagnosis of electrical induction machines for industrial applications is widely discussed in literature. In
Externí odkaz:
https://doaj.org/article/2abf075f80e341f38b4984996104df8b
Publikováno v:
IEEE Transactions on Industry Applications. 55:5109-5118
Pitch systems are one of the components with the most frequent failure in wind turbines. This paper presents a two-stage fault detection and classification scheme for electric motor drives in wind turbine pitch systems. The presented approach is suit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38c0971563d7e8ea67cdfbe9a9e62141
https://doi.org/10.1109/tia.2019.2924866
https://doi.org/10.1109/tia.2019.2924866
Autor:
Martin Nowara, Surya Teja Kandukuri, Matthias Buderath, Steffen Haus, Heiko Mikat, Uwe Klingauf
Publikováno v:
International Journal of Prognostics and Health Management, Vol 4, Iss 2, Pp 21-40 (2013)
Future health monitoring concepts in different fields of engineering require reliable fault detection to avoid unscheduled machine downtime. Diagnosis of electrical induction machines for industrial applications is widely discussed in literature. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::55eab7f75638380b99f554e772428ad7
https://doi.org/10.36001/ijphm.2013.v4i2.2123
https://doi.org/10.36001/ijphm.2013.v4i2.2123
Publikováno v:
IECON
Pitch systems are among the most failure-prone components in wind turbines. Winding failures in pitch motors are common due to high start-up loads and poor ventilation. This article presents a diagnostics scheme that can detect the stator winding fai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f6f2891295b9b3566f6de03f1521a37a
https://doi.org/10.1109/iecon.2019.8926983
https://doi.org/10.1109/iecon.2019.8926983
Publikováno v:
2019 IEEE 12th International Symposium on Diagnostics for Electrical Machines, Power Electronics and Drives (SDEMPED).
This article presents a framework for accurate fault diagnostics in inverter-fed induction machinery operating under variable speed and load conditions within very short time windows. Condition indicators based on fault characteristic frequencies obs
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cbd650a298b0dcd1f88b70c1ab67db21
https://doi.org/10.1109/demped.2019.8864889
https://doi.org/10.1109/demped.2019.8864889
Publikováno v:
2018 21st International Conference on Electrical Machines and Systems (ICEMS).
Pitch systems are among the wind turbine components with most frequent failures. This article presents a multicomponent fault detection for induction motors and planetary gearboxes of the electric pitch drives using only the three-phase motor line cu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a93dfb2c691fd9289a3d1e53cc7c511c
https://doi.org/10.23919/icems.2018.8549293
https://doi.org/10.23919/icems.2018.8549293
Publikováno v:
Structural Control and Fault Detection of Wind Turbine Systems ISBN: 9781785613944
An outline of health management for OWFs has been detailed in this chapter with description of various important elements. The need for such farm level management is explained and benefits are discussed. Key gaps to be filled in order to realize such
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::53f0f6ba75838948f43394ccbb19c821
https://doi.org/10.1049/pbpo117e_ch6
https://doi.org/10.1049/pbpo117e_ch6
Parameter Identification of a Winding Function Based Model for Fault Detection of Induction Machines
Publikováno v:
2018 Eighth International Conference on Information Science and Technology (ICIST).
Prediction of machines' faulty parts is important in industrial applications in order to reduce productivity losses. As far as electrical machines are considered, a model-based fault diagnosis approach is usually used for this purpose. The model is d
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7fcd4470886c22d48bb8053c8e0ec0f4
https://doi.org/10.1109/icist.2018.8426188
https://doi.org/10.1109/icist.2018.8426188
Sensorless control of induction motors using an extended Kalman filter and linear quadratic tracking
Publikováno v:
2017 20th International Conference on Electrical Machines and Systems (ICEMS).
Induction motors are the most commonly used prime-movers in industrial applications. Many induction motors supplied by frequency converters are coupled with a physical angular rotor position/velocity sensor which makes the drive complex and require m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e2683788a153927ad589a2195435adf4
https://doi.org/10.1109/icems.2017.8056264
https://doi.org/10.1109/icems.2017.8056264
Publikováno v:
2017 20th International Conference on Electrical Machines and Systems (ICEMS).
This article presents a two-stage fault detection and classification scheme, for induction motor drives in wind turbine pitch systems. The presented approach is suitable for application in offshore wind farms. The adopted strategy utilizes three phas
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::fe53f2bce1741dbd087c8e6dc5807feb
https://doi.org/10.1109/icems.2017.8056262
https://doi.org/10.1109/icems.2017.8056262