• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.6
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• pp.447-454
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• 2013

A model-based method is proposed to diagnose the gear crack in the gearbox under variable loading condition with the objective to apply it to the wind turbine CMS(Condition Monitoring System). A simple test bed is installed to illustrate the approach, which consists of motors and a pair of spur gears. A crack is imbedded at the tooth root of a gear. Tachometer-based order analysis, being independent on the shaft speed, is employed as a signal processing technique to identify the crack through the impulsive change and the kurtosis. Lumped parameter dynamic model is used to simulate the operation of the test bed. In the model, the parameter related with the crack is inversely estimated by minimizing the difference between the simulated and measured features. In order to illustrate the validation of the method, a simulated signal with a specified parameter is virtually generated from the model, assuming it as the measured signal. Then the parameter is inversely estimated based on the proposed method. The result agrees with the previously specified parameter value, which verifies that the algorithm works successfully. Application to the real crack in the test bed will be addressed in the next study.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.22 no.5
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• pp.413-421
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• 2012

In industry, various rotating machinery such as pumps, gas turbines, compressors, electric motors, generators are being used as an important facility. Due to the industrial development, they make high performance(high-speed, high-pressure). As a result, we need more intelligent and reliable machine condition diagnosis techniques. Diagnosis technique using hidden Markov-model is proposed for an accurate and predictable condition diagnosis of various rotating machines and also has overcame the speed limitation of time/frequency method by using compensation of the rotational speed of rotor. In addition, existing artificial intelligence method needs defect state data for fault detection. hidden Markov model can overcome this limitation by using normal state data alone to detect fault of rotational machinery. Vibration analysis of step-up gearbox for wind turbine was applied to the study to ensure the robustness of diagnostic performance about compensation of the rotational speed. To assure the performance of normal state alone method, hidden Markov model was applied to experimental torque measuring gearbox in this study.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.922-923
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• 2015

풍력발전기는 2000년대 초반에 발전기 회전자 직경이 80m에 이르는 2MW급 풍력발전기들이 여러 회사에서 개발되면서 경제성 및 신뢰성도 향상되어 비약적인 발전을 이루게 되었다. 풍력발전시장의 신규발주와 설치장소가 한계점에 이르게 됨으로써 경제성이 뛰어난 대형 풍력발전기의 필요성이 대두되고 있다. 이와 같이 풍력발전기의 대형화 추세는 대형화를 통해 에너지 효율의 증대뿐만 아니라 단위 용량 당 건설비 및 설비비 절감이 가능하기 때문에 풍력발전기 대형화를 위한 기술개발이 활발히 진행되고 있다. 하지만 현재 풍력발전기에 사용되는 기계적 기어박스는 윤활유 주입 및 보수 점검의 문제점이나 소음, 진동, 마찰에 의한 열 발생 등의 문제점들을 가지고 있다. 이러한 문제점을 해결하기 위하여 기계적 기어박스를 마그네틱 기어를 이용하여 구성하고자 한다. 따라서 본 논문에서는 마그네틱 기어를 이용하여 10MW급 풍력발전기의 기어박스를 설계하고 그 가능성을 검토하고자 한다.

• Journal of Aerospace System Engineering
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• v.8 no.4
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• pp.7-17
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• 2014

Objective of this paper is to introduce a new technology known as prognostics and health management (PHM) which enables a real-time life prediction for safety critical systems under extreme loading conditions. In the PHM, Bayesian framework is employed to account for uncertainties and probabilities arising in the overall process including condition monitoring, fault severity estimation and failure predictions. Three applications - aircraft fuselage crack, gearbox spall and battery capacity degradation are taken to illustrate the approach, in which the life is predicted and validated by end-of-life results. The PHM technology may allow new maintenance strategy that achieves higher degree of safety while reducing the cost in effective manner.