• Journal of Biosystems Engineering
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• 제11권1호
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• pp.76-85
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• 1986

This study was intended to examine the failure characteristics and breakdowns of the head-fed type combines generally used on farms. The failure distribution was assumed to follow Weibull distribution function and the Weibull parameters of the major parts, units and combine as whole were estimated by using the data collected in a survey. A computer program for the estimation of the Weibull parameter was developed. Monte Carlo method was used in predicting the time between failures. The results of study may be summarized as follows: 1. The number of failures per combine was 4.83 times per year and 0.3 times per hectare of combines of different ages. 2. According to the Kolmogorov-Smirnov test method, it was proved that the Weibull distribution function is well fitted to the characteristics of the failure and breakdowns of combines. 3. Weibull parameters of failure distribution of the combine as a whole were estimated to give the shape parameter ${\beta}$=1.3089 and the scale parameter ${\alpha}$=105.2409. The combining area with 80% reliability was 1.1 ha, and the probability of operating the combine without any failure for a year, was $2.76{\times}10^{-4}$. 4. The mean time between failures (MTBF) of the combines was predicted to be 3.2 ha of operation, which corresponds to 32 hours of operation.

• 한국기계가공학회지
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• 제19권11호
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• pp.94-101
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• 2020

In the age of industry 4.0, artificial intelligence is being widely used to realize machinery condition monitoring. Due to their excellent performance and the ability to handle large volumes of data, machine learning techniques have been applied to realize the fault diagnosis of different equipment. In this study, we performed the failure mode effect analysis (FMEA) of an aluminum electrolytic capacitor by using deep learning and big data. Several tests were performed to identify the main failure mode of the aluminum electrolytic capacitor, and it was noted that the capacitance reduced significantly over time due to overheating. To reflect the capacitance degradation behavior over time, we employed the Vanilla long short-term memory (LSTM) neural network architecture. The LSTM neural network has been demonstrated to achieve excellent long-term predictions. The prediction results and metrics of the LSTM and Vanilla LSTM models were examined and compared. The Vanilla LSTM outperformed the conventional LSTM in terms of the computational resources and time required to predict the capacitance degradation.

• 드라이브 ㆍ 컨트롤
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• 제18권1호
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• pp.24-30
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• 2021

There is an increasing interest in condition-based maintenance for the prevention of economic loss due to failure. Moreover, immense research is being carried out in related technologies in the field of construction machinery. In particular, data-based failure diagnosis methods that employ AI (machine & deep learning) algorithms are in the spotlight. In this study, we have focused on the failure diagnosis and mode classification of reduction gear of excavator's travel device by using the AI algorithm. In addition, a remote monitoring system has been developed that can monitor the status of the reduction gear by using the developed diagnosis algorithm. The failure diagnosis algorithm was performed in the process of data acquisition of normal and abnormal under various operating conditions, data processing and analysis by the wavelet transformation, and learning. The developed algorithm was verified based on three-evaluation conditions. Finally, we have built a system that can check the status of the reduction gear of travel devices on the web using the Edge platform, which is embedded with the failure diagnosis algorithm and cloud.

• 한국산업융합학회 논문집
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• 제24권6_2호
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• pp.819-825
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• 2021

In the industry, the use of lightweight bearings is increasing to minimize motor power loss, and in particular, the application of next-generation systems such as robots and drones is increasing. Bearing manufacturers are producing lightweight bearings by changing the bearing material, but related researches is insufficient. In this paper, life test and structural analysis were performed for lightweight bearings, and shape parameters and scale parameters were derived based on the life test results. It was confirmed that the shape parameter was 2.52 and the scale parameter was 164 hours. As a result of calculating the dynamic load rating based on the B₁₀ life, it was confirmed that the dynamic load rating of the lightweight bearing was 7% compared to the formula suggested by ISO 281. The reason is that the material of the retainer, which is a major failure part, is a polyamide 66 series that reacts sensitively to heat, so It is judged to show a lot of difference from the ISO 281 calculation formula.

• 대한기계학회논문집A
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• 제38권10호
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• pp.1179-1184
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• 2014

일반적으로 신뢰도 배분은 시스템 개발 초기단계에 시스템의 신뢰도 목표 값을 하위 모듈에 배분하기 위해 사용된다. 본 연구에서는 KTX 승강문 시스템의 목표 신뢰도를 하위 모듈에 배분하기 위해 Comprehensive 배분방법을 제시한다. Comprehensive 배분방법은 시스템의 신뢰도를 배분하기 위해 각 모듈에 대한 고장의 중요도, 작동시간 비율, 위험도, 복잡도, 고장률, 수리/정비성, 개발완성도, 사용환경 가혹도, 신뢰도 달성비용의 평가항목을 고려한다. 승강문 시스템의 목표 신뢰도를 만족하기 위해서 시스템을 구성하는 4 가지 모듈의 $B_{10}$ 수명을 제시한다.

• 한국유체기계학회 논문집
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• 제3권4호
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• pp.52-58
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• 2000

The numerical study on the waterhammer was carried out for the intake pumping station of the metropolitan water supply 6th stage project. Because the waterhammer problems as a result of the pump power failure were the most important, these situations were carefully investigated. The surge tank and the stand pipes effectively protected the tunnels md the downstream region of pipeline from the pressure surge. In case the moment of inertia of the pump and motor was above $5080\;kg{\cdot}m^2$, the column separation did not occur in the pipeline between the pumping station and the inlet of 1st tunnel. As the moment of inertia increased, the pressure surges decreased in the pipeline conveying raw water. The pump control valve was chosen as the main surge suppression device for the intake pumping station. After power failure, the valve disc should be rapidly closed in 2.5 seconds and controlled the final closure to 15 seconds by the oil dashpot. If the slamming happened to the pump control valve, there was some danger of this system damaging. As the reverse flow through the valve increased, the upsurge extremely increased.

• 대한기계학회논문집A
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• 제41권9호
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• pp.887-895
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• 2017

본 논문에서는 일반적으로 문틀과 문짝을 연결하여 개폐시 작동하는 부품인 힌지의 가속수명시험법에 대한 연구이다. 힌지는 사용하는 용도에 따라 구조와 고장모드가 상이하며 본 연구에서는 전자파 차폐시설에 사용되는 개폐장치 구성품 중 하나인 힌지에 대해서 고장모드를 분석하고 현장작동조건에서의 이론적 검증과 시험장비에 대한 타당성을 분석하였다. 그리고 형상모수와 가속지수의 추정을 통한 특성수명 예측을 위한 가속수명시험법을 설계하였다.

• 한국유체기계학회 논문집
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• 제8권4호
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• pp.20-26
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• 2005

When the pumps are started or stopped for the operation or tripped due to the power failure, the hydraulic transients occur as a result of the sudden change in velocity. The field tests on the waterhammer were carried out for Pangyo booster pumping station in which had six booster pumps and two in-line pumps with the motor of output 1,700 kW, respectively. The booster pumping station was equipped with the pump control valve as the main surge suppression device, and the surge relief valve as auxiliary one. But the pump control valve had not early controlled in the planned closing mode, the slamming occurred to the valve of which abruptly closed during the large reverse flow. Because the positive pressure wave caused by the pump failure was superposed on the slam surge, the upsurge increased so extremely that the pump control valve was damaged. After the air chambers were additionally installed in the booster pumping station, it was preyed that the water supply system acquire the safety and reliability on the pressure surge.

• 한국해양공학회지
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• 제11권3호
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• pp.170-179
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• 1997

This paper presents a hybrid navigation system for AUV to locate its position precisely in rough sea. The tracking system is composed of various sensors such as an inclinometer, a tri-axis magnetometer, a flow meter, and a super short baseline(SSBL) acoustic position tracking system. Due to the inaccuracy of the attitude sensors, the heading sensor and the flowmeter, the predicted position slowly drifts and the estimation error of position becomes larger. On the other hand, the measured position is liable to change abruptly due to the corrupted data of the SSBL system in the case of low signal to noise ratio or large ship motions. By introducing a sensor fusion technique with the position data of the SSBL system and those of the attitude heading flowmeter reference system (AHFRS), the hybrid navigation system updates the three-dimensional position robustly. A Kalman filter algorithm is derived on the basis of the error models for the flowmeter dynamics with the use of the external measurement from the SSBL. A failure detection algorithm decides the confidence degree of external measurement signals by using a fuzzy inference. Simulation is included to demonstrate the validity of the hybrid navigation system.

• Tribology and Lubricants
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• 제14권2호
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• pp.75-81
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• 1998

Condition monitoring technology was applied for an air compressor lubricating system to achieve a proactive maintenance, which could prevent a catastrophic failure and detect root causes of the conditional failure of the system. For this work, various types of wear monitoring technology were used and compared with the results of vibration and temperature measurements. The Results generally showed that every technology has a limitation to failure detection, and integrated-based condition monitoring should be performed for the best results. In this work, an idea for the implementing integrated wear monitoring was suggested and demonstrated.