• Journal of Advanced Marine Engineering and Technology
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• v.28 no.7
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• pp.1092-1100
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• 2004

This paper describes the application of fault tree technique to analyze of compressor failure. Fault tree analysis technique involves the decomposition of a system into the specific form of fault tree where certain basic events lead to a specified top event which signifies the total failure of the system. In this research. fault trees for failure analysis of screw type air compressor are made. This fault trees are used to obtain minimal cut sets from system failure and system failure rate for the top event occurrence can be calculated. It is Possible to estimate air compressor reliability by using constructed fault trees through compressor failure example. It is Proved that FTA is efficient to investigate the compressor failure modes and diagnose system.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.1
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• pp.127-138
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• 1994

The application of fault tree technique to the analysis of compressor failure is considered. The techniques involve the decomposition of the system into a form of fault tree where certain basic events lead to a specified top event which signifies the total failure of the system. In this paper, fault trees are made by using fault train of screw type air compressor failure. The fault trees are used to obtain minimal cut sets from the modes of system failure and, hence the system failure rate for the top event can be calculated. The method of constructing fault trees and the subsequent estimation of reliability of the system is illustrated through compressor failure. It is proved that FTA is efficient to investigate the compressor failure modes and diagnose system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.04b
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• pp.305-309
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• 1993

The application of fault tree technique to the analysis of compressor failure is considered. The techniques involve the decomposition of the system into a logic diagram or fault tree in whichcertain basic or primary events lead to a specified top event which signifiss the total failure of the system. The fault trees are used to obtain miniumal cut sets from whichthe modes of system failure and, hence the reliability for the top event can be calculated. The method of constructing fault trees and the subsequent estimation of reliability of the system is illustrated through a compressor failure. FTA is roved to be efficient to investigate the compressor fault train.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.1381-1386
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• 2008

In this study, we studied failure cause of check valve through analysing characteristic of it used in turbo compressor. We researched how to improve to reduce chaterring occurrence which is cause of main failure mode and suggested how to improve reliability of check valve through it.

• Transactions of the Korean hydrogen and new energy society
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• v.26 no.2
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• pp.192-198
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• 2015

Fault Tree Analysis to predict the lifetime in the design process of LNG compressor is considered. Fault Trees for P & ID of the compressor are created. Individual components that comprise the compressor are configured with the basic event. The failure rates in the PDS and OREDA are applied. As results, the system failure rate and the reliability over time are obtained. Further, the power transmission and the shaft seal system is confirmed to confidentially importantly contribute to the overall lifetime of the system. These techniques will help to improve the reliability of design of large scale machinery such as a plant.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.11
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• pp.1025-1032
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• 2010

Gas turbine compressor blades used in a combined cycle power plant are possibly damaged and fractured during their operation. There are two possible causes of the failure of compressor blades; one is a defect of material quality which can be detected through some microscopic inspections for the fracture section, the other is high cycle fatigue problem caused by vibration and can be diagnosed by carrying out dynamic characteristics analysis for the blades. In this paper, in order to determine the cause of the failure of compressor blades in a combined cycle power plant, examination of the fracture section and the propagation mechanism of the crack via stress analysis are performed. Dynamic characteristics analysis via FRF estimation is also performed to identify the cause of failure.

• Korean Journal of Materials Research
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• v.17 no.11
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• pp.580-586
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• 2007

To enhance the reliability of a newly designed reciprocating compressor applied in a domestic compressor, accelerated life tests were developed using new definitions of the sample size and the $B_1$ life index. In $1^{st}$ accelerated life testing, the compressor was locked due to the fracture of the suction reed valve. The failure modes and mechanisms of the suction reed valve in the accelerated tests were found to be similar to that of the failed product in the field. The root cause of the failure was the overlap between the suction reed valve and the valve plate in the suction port. The missing parameters in the design phase were modified by expanding the trespan size, introducing tumbling process, changing the material and thickness for the valve, introducing a ball peening and brushing process for the valve plate. In $2^{nd}$ accelerated life testing, the compressor was locked due to the interference between the crank shaft and thrust washer. The corrective plan was to heat treat the crank shaft. The $B_1$ life of the compressor improved from 1.5 to 12.9 years.

• Journal of the Korean Society of Marine Environment & Safety
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• v.27 no.1
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• pp.127-134
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• 2021

In this study, an anomaly detection (AD) algorithm was implemented to detect the failure of a marine air compressor. A lab-scale experiment was designed to produce fault datasets (time-series electric current measurements) for 10 failure modes of the air compressor. The results demonstrated that the temporal pattern of the datasets showed periodicity with a different period, depending on the failure mode. An AD model with a convolutional autoencoder was developed and trained based on a normal operation dataset. The reconstruction error was used as the threshold for AD. The reconstruction error was noted to be dependent on the AD model and hyperparameter tuning. The AD model was applied to the synthetic dataset, which comprised both normal and abnormal conditions of the air compressor for validation. The AD model exhibited good detection performance on anomalies showing periodicity but poor performance on anomalies resulting from subtle load changes in the motor.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.6 s.123
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• pp.484-490
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• 2007

A reciprocating compressor used in domestic refrigerators can be subjected to many different forms of shock. These shocks are usually experienced during transporting the products from a manufacturer to customers. The hermetic structure of this kind of compressor makes it difficult to conduct drop tests for identifying the failure mechanism and their drop behaviors. The drop/impact simulation for a reciprocating compressor has been carried out with the explicit code LS-DYNA and its validation has been experimentally verified. Simulation results are in good agreement with those of drop test. The present method of drop/impact simulation provides an efficient and powerful solution to improve the design quality and reduce the design period.

• Journal of the Korean Society of Safety
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• v.20 no.3 s.71
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• pp.19-26
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• 2005

There are three reasoning method in fault diagnosis process. The shallow reasoning is based on the experiential knowledge and deep reasoning is based on physical model. Hybrid reasoning is mixing two type reasoning. This study describes about fault train embodiment of screw type air compressor that is used widely in industrial facilities by using various experimental method and shallow reasoning. We investigate macroscopic failure cause of air compressor through naked eye observation and then microscopic failure cause by various experimental method. We composed fault train with fault knowledge based on empirical data and scientific data that is acquired through several experiments. It is possible to analysis system reliability and failure rate with these fault train.