• Journal of the Korean Society of Propulsion Engineers
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• v.9 no.4
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• pp.81-88
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• 2005

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV(Unmanned Aerial Vehicle). In order to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. When the performance analysis is performed at far away operation conditions from the design point, in case of use of e component map by the traditional scaling method, the error of the performance analysis results is greatly increasing. In the other hand, if in case of use of the compressor map generated by the proposed GAs scheme, the performance analysis results are closely met with those by the performance deck, EEPP.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2005.11a
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• pp.149-153
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• 2005

In order to estimate the gas turbine engine performance precisely, the component maps containing their own performance characteristics should be needed. In this study a component map generation method which may identify compressor map conversely from a performance deck provided by engine manufacturer using genetic algorithms was newly proposed. As a demonstration example for this study, the PW 206C turbo shaft engine for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle). In ordo to verify the proposed method, steady-state performance analysis results using the newly generated compressor map was compared with them performed by EEPP(Estimated Engine Performance Program) deck provided by engine manufacturer. And also the performance results using the identified maps were compared with them using the traditional scaling method. In this investigation, it was found that the newly proposed map generation method would be more effective than the traditional scaling method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.1
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• pp.97-102
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• 2016

Since vibrations in rotating machinery is a direct cause of performance degradation and failures, it is very important to predict the level of vibrations as well as have a method to lower the vibrations to an acceptable level. However, the changes in balancing during installation and the vibrational modes of the support structure are difficult to predict. This paper presents a method for predicting the unbalanced response of a turbo-compressor supported by active magnetic bearings (AMBs). Transfer functions of the rotor are obtained through system identification using AMBs. These transfer functions contain not only the dynamics of the rotor but also the vibrational modes of the support structure. Using these transfer functions, the unbalanced response is calculated and compared with the run-up data obtained from a compressor prototype. The predictions revealed the effects of the support structure, validating the efficacy of the method.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.283-285
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• 2023

이상 탐지는 데이터에서 일반적인 범주에서 크게 벗어나는 인스턴스 또는 패턴을 식별하는 중요한 작업이다. 본 연구에서는 시계열 데이터의 특징 추출을 위한 비지도 학습 기반 방법과 정규화 흐름의 결합을 통한 이상 탐지 프레임워크를 제안한다. 특징 추출기는 1차원 합성곱 신경망 기반의 오토인코더로 구성되며, 정상적인 시퀀스로만 구성된 훈련 데이터를 압축하고 복원하는 과정을 통해 최적화된다. 추출된 시계열 데이터의 특징 맵은 가능도를 최대화하도록 훈련된 정규화 흐름의 입력으로 사용된다. 이와 같은 방식으로 훈련된 이상 탐지 시스템은 테스트 샘플에 대한 이상치를 계산하며, 최종적으로 임계값과의 비교를 통해 이상 여부를 예측한다. 성능 평가를 위해 시계열 이상 탐지를 위한 공개 데이터셋을 이용하여 공정하게 이상 탐지 성능을 비교하였으며, 실험 결과는 제안하는 정규화 흐름 기법이 시계열 이상 탐지 시스템에 활용될수 있는 잠재성을 시사한다.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.130-139
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• 2024

Artificial intelligence models are being used to detect facility anomalies using physics data such as vibration, current, and temperature for predictive maintenance in the manufacturing industry. Since the types of facility anomalies, such as facility defects and failures, anomaly detection methods using autoencoder-based unsupervised learning models have been mainly applied. Normal or abnormal facility conditions can be effectively classified using the reconstruction error of the autoencoder, but there is a limit to identifying facility anomalies specifically. When facility anomalies such as unbalance, misalignment, and looseness occur, the facility vibration frequency shows a pattern different from the normal state in a specific frequency range. This paper presents an N-segmentation anomaly detection method that performs anomaly detection by dividing the entire vibration frequency range into N regions. Experiments on nine kinds of anomaly data with different frequencies and amplitudes using vibration data from a compressor showed better performance when N-segmentation was applied. The proposed method helps materialize them after detecting facility anomalies.

• 전자공학회논문지 IE
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• v.48 no.2
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• pp.32-39
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• 2011

The output image of the uncooled thermal infrared camera is difficult the identification of target because of the limited dynamic range and the various noises. Retinex algorithm based on the theory of the human visual perception is known to be effective contrast enhancement technique. However, the image quality is insufficient when it is adopted to the narrow dynamic range image as the infrared image. In this paper, we propose the revised retinex algorithm to enhance the contrast of the infrared image. To improve the contrast enhancement performance, we designed the new dynamic range compression function instead of log function. To reduce the noise and compensate the loss of edge, we added the contrast compensation procedure in the MSR image generation process. According to the output picture comparing and numerical analysis, the proposed algorithm shows the better contrast enhancement performance and the more suitable method for the infrared image enhancement.