• 동력기계공학회지
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• 제11권4호
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• pp.65-71
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• 2007

According to the survey, abnormal condition of the system is the main source for interrupting an elevator service, especially faults in worm gears used for the traction machine. Worm gear is popularly used in traction machine for middle and low speed elevators. Elevators need high reliability and stability, because they are closely related to human life. Usually, traction machine is applied to drive the elevators that have height about 35 m and it is an important mechanical unit for riding quality in elevators. There are some research results about types of vibration fault for worm gear in International Association Elevator Engineers (IAEE). But this study concerns with diagnosis of various faults in elevator worm gear using vibration signal. The analysis of fault characteristics is compared with previous researches in traction machine.

• 한국정밀공학회지
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• 제30권7호
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• pp.679-686
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• 2013

The reduction unit is one of the most important components in railway cars, due to the transmission of torque from the motor to the wheels. Faulty reduction gears in high-speed trains result from excessive wear on the gear or damage to the gear. These types of gear defects have a significant effect on high-speed rail operation and safety; thus, a diagnosis system for the reduction unit is needed. Vibration diagnosis technology is one of the most effective diagnostics. In this paper, the vibration parameters of a reduction unit were evaluated during a driving-gear test and a full-vehicle test, using kurtosis and the crest factor. These tests were performed under normal operating conditions; a specimen tester was used to diagnose problems in defective gears.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 2006년도 춘계학술대회논문집
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• pp.1328-1333
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• 2006

For fault diagnosis of machines and equipments, knowledge-based method has been used widely but has some limitations for complex systems. These can be covered by model-based method. As one kind of model-based method, Qualitative modeling diagnosis method is developed in this research. The developed method uses output signal only. In this method quantization of the output signal mattes automata which can characterize the flow of the signal pattern to normal and fault respectively. As an example of the qualitative diagnosis method, an electric tool which has faults at gear and bearing were examined in this research. The result shows that the developed method can diagnose the fault clearly for the two fault cases.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제12권10호
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• pp.445-454
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• 2023

최근에는 협동 로봇의 데이터를 활용한 다양한 결함진단 연구가 수행되고 있다. 협동 로봇의 결함진단을 수행하는 기존 연구들은 기존 연구의 학습 데이터는 미리 정의된 기기의 동작을 가정하고 수집한 정적 데이터를 사용한다. 따라서 결함진단 모델은 학습한 데이터 패턴에 대한 의존성이 높아지는 한계가 있다. 또한 단일 모터를 사용한 실험으로 다관절이 동작하는 협동 로봇의 특성을 반영한 진단이 이루어지지 못했다는 한계가 있다. 본 논문에서는 앞서 언급한 두 가지 한계점을 해결할 수 있는 LSTM 진단 모델을 제안한다. 제안하는 방법은 단일 축 및 다중 축 작업 환경에서의 진동 및 전류 데이터의 상관분석을 사용하여 정상 대표 패턴을 선정하고, 정상 대표 패턴과의 차이를 통해 잔차 패턴을 생성한다. 생성된 잔차 패턴을 입력으로 축별 기어 마모 진단을 수행할 수 있는 LSTM 모델을 생성한다. 해당 결함진단 모델은 동작별 대표 패턴을 통해 모델의 학습 데이터 패턴에 대한 의존성을 낮출 수 있을 뿐 아니라 다중 축 동작 수행 시 발생하는 결함을 진단할 수 있다. 마지막으로, 내부 및 외부 데이터의 특성을 모두 반영하여 결함진단 성능을 개선한 결과 98.57%의 높은 진단 성능을 보였다.

• Journal of Mechanical Science and Technology
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• 제20권11호
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• pp.1781-1789
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• 2006

Fourier methods are not generally an appropriate approach in the investigation of faults signals with transient components. This work presents the application of a new signal processing technique, the Hilbert-Huang transform and its marginal spectrum, in analysis of vibration signals and faults diagnosis of gear. The Empirical mode decomposition (EMD), Hilbert-Huang transform (HHT) and marginal spectrum are introduced. Firstly, the vibration signals are separated into several intrinsic mode functions (IMFs) using EMD. Then the marginal spectrum of each IMF can be obtained. According to the marginal spectrum, the wear fault of the gear can be detected and faults patterns can be identified. The results show that the proposed method may provide not only an increase in the spectral resolution but also reliability for the faults diagnosis of the gear.

• 소음진동
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• 제8권5호
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• pp.929-935
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• 1998

Safety diagnosis of electric train driving system is performed using vibration signals of running electric train. Safety diagnosis is tried on the viewpoints of the appreciation of superannuation and the fault diagnosis of motor, reduction gear and bogie. The appreciation of superannuation is checked by the vibration levels of driving parts and the fault diagnosis is done by analyzing the frequencies of the vibration signals which are measured directly from a running electric train. The results shows that the vibration levels of each parts increase as the train gets older and each parts have their own frequency patterns of the vibration. Vibration propagation path is also investigated using calculated the coherence value between bogie and driving system. As the results, it is known that vibration signal can be utilized successfully for the safety diagnosis of the driving part of electric train.

• 한국안전학회지
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• 제15권2호
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• pp.1-7
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• 2000

This paper presents the approach involving fault detection and diagnosis of gears using pattern recognition and Wavelet transform. It describes result of the comparison between KDI (Kullback Discrimination Information) with the nearest neighbor classification rule as one of pattern recognition methods and Wavelet transform to know a way to detect and diagnosis of gear damages experimentally. To model the damages 1) Normal (no defect), 2) one tooth is worn out, 3) All teeth faces are worn out 4) One tooth is broken. The vibration sensor was attached on the bearing housing. This produced the total time history data that is 20 pieces of each condition. We chose the standard data and measure distance between standard and tested data. In Wavelet transform analysis method, the time series data of magnitude in specified frequency (rotary and mesh frequency) were earned. As a result, the monitoring system using Wavelet transform method and KDI with nearest neighbor classification rule successfully detected and classified the damages from the experimental data.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.1569-1570
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• 2013

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2013년도 춘계학술대회 논문집
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• pp.1593-1594
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• 2013

• 한국철도학회논문집
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• 제16권1호
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• pp.26-31
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• 2013

감속구동장치는 모터에 회전력을 차륜에 전달하는 중요한 장치로써 가장 큰 고장원인 중 하나는 기어의 접촉 피로손상에 의한 것이다. 이로 인해 주행 시 심각한 영향을 미칠 수 있기 때문에 주행안전성 확보를 위한 이상진단 모니터링시스템 기술이 요구되고 있으며, 이상진단을 위한 모니터링 시스템 개발을 위해 고장이 없는 감속구동장치의 기초 데이터 분석이 중요하다. 기어의 주요 이상진단방법 중 고장원인파악 및 조기진단에 주로 사용되는 진동신호분석법을 적용하여, 본 논문에서는 고장이 없는 고속철도차량(KTX, KTX II) 감속구동장치를 대상으로 실물시험과 실차시험을 수행함으로써 고장이 없는 감속구동장치의 이상진단에 필요한 진동특성분석을 실시하였다.