• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.1015-1019
• /
• 2007

The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Because vibration diagnosis can avoid sudden breakdown of machine and reduce the maintenance costs. In chemical factory, Air-compressor and refrigerator which can affect the performance and capacity of output is important machine. Therefore, in this paper, the vibration of reassembled air-compressor and refrigerator after explosion is measured for checking the machine condition. The result of diagnosis and solution is discussed in this paper.

• Transactions of the Korean Society of Mechanical Engineers
• /
• v.19 no.8
• /
• pp.1787-1798
• /
• 1995

Monitoring and diagnosis of the operating machine mean evaluating the condition of a machine such as the detection of the defects and the prediction of the time to failure in the machine elements, while it is running. In this study, a technique of automatic diagnosis using probability concept is studied and the analyses of the pattern comparison are introduced. An expert system, which is able to analyze the automatic identification of the multiple defects in the ball bearings, is also developed. Finally, to confirm the effectiveness of the programmed algorithms, some tests were made with specimens of the ball bearings involving the multiple defects. The proposed system reasonably predicts the defects.

• Journal of Power System Engineering
• /
• v.12 no.4
• /
• pp.52-56
• /
• 2008

The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Because vibration diagnosis can avoid sudden breakdown of machine and reduce the maintenance costs. In chemical factory, Air-compressor and refrigerator which can affect the performance and capacity of output are important machine. Therefore, in this paper, the vibration of reassembled air-compressor and refrigerator after explosion is measured for checking the machine condition. The result of diagnosis and solution is discussed in this paper.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2014.10a
• /
• pp.833-834
• /
• 2014

In recent years, a pattern recognition method has been widely used by researchers for fault diagnoses of mechanical systems. A pattern recognition method determines the soundness of a mechanical system by detecting variations in the system's vibration characteristics. Hidden Markov model has recently been used as pattern recognition methods in various fields. In this study, a HMM method for the fault diagnosis of a mechanical system is introduced, and a rotating machine with mass unbalance is selected for fault diagnosis. Moreover, a diagnosis procedure to identity the size of a defect is proposed in this study.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2003.11a
• /
• pp.549-555
• /
• 2003

The technology of machine condition monitoring is used effectively to detect the machine faults at an early stage using different machine quantities, such as current, voltage, temperature and vibration. Induction motors are most widely used to drive pumps, compressors and fans in industrial drives. This paper presents approach to data fusion using Dempster-Shafer theory because only one technique has uncertainty. So we can obtain advanced accuracy of the machine fault diagnosis. Vibration and current quantities are applied to diagnose three-phase induction motor.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.15 no.4
• /
• pp.23-29
• /
• 2016

Rotary machine is major equipment in industry. The rotary machine is applied for a machine tool, ship, vehicle, power plant, and so on. But a spindle fault increase product's expense and decrease quality of a workpiece in machine tool. A turbine in power plant is directly connected to human safety. National crisis could be happened by stopping of rotary machine in nuclear plant. Therefore, it is very important to know rotary machine condition in industry field. This study mentioned fault diagnosis algorithm with statistical parameter and empirical mode decomposition. Vibration locations can be found by analyze kurtosis of data from triaxial axis. Support vector of data determine threshold using hyperplane with fault location. Empirical mode decomposition is used to find fault caused by intrinsic mode. This paper suggested algorithm to find direction and causes from generated fault.

• Proceedings of the KIEE Conference
• /
• 2002.07c
• /
• pp.1701-1703
• /
• 2002

This paper introduces a on-line monitoring system for insulation diagnosis of high-voltage motor stator windings. This system monitors the insulation condition of the stator winding with sensor, coupling capacitor. Partial discharge (PD) signals are able to be continuously measured and digitalized with a Peak-hold A/D converter to build the database of the high-voltage motor's insulation condition. This system can communicate with the central monitoring system via RS-485 This paper introduces an economic solution for data acquisition of partial discharges.

• Tribology and Lubricants
• /
• v.20 no.1
• /
• pp.21-26
• /
• 2004

The average frictional coefficient was used generally to analyze the working process of the lubricated machine parts. But it is difficult of taking the correct frictional coefficient because the average frictional coefficient of it is progressed always unstably with a large amplitude on working condition. If the correct analysis of frictional coefficient on working condition for the lubricated machine parts can be possible, it can be effect on condition diagnosis of lubricated machine system. This study was carried out to get the optimum working condition of the hydraulic actuator parts using statistical techniques. From this result, it has the lowest friction coefficient in case of applied load of 3 kg and sliding speed of 120 mm/sec.

• Tribology and Lubricants
• /
• v.3 no.1
• /
• pp.52-60
• /
• 1987

Many kinds of condition monitoring technique as the preventive maintenance technique have been studied, so this study has investigated the possibility of chbcking the trend in the fault diagnosis of ball bearing, one of the important elements of rotating machine, by applying the cepstral analysis method. And computer simulation is conducted in order to identify obviously the physical meaning of cepstral analysis. It is identified that cepstral analysis is effective method to distinguish between the basic and reflected wave by computer simulation, and we know that it is possible to apply the cepstral analysis to the arbitrary elements of rotating machine which are different in fundamental frequency. It is verified that cepstral analysis method is more effective than the other conventional method in bearing fault diganosis.

• Journal of the Korean Society for Nondestructive Testing
• /
• v.30 no.2
• /
• pp.121-125
• /
• 2010

The infrared thermography technology rather than traditional nondestructive methods has benefits with non-contact and non-destructive testings in measuring for the fault diagnosis of the rotating machine. In this work, condition monitoring measurements using this advantage of thermography were proposed. From this study, the novel approach for the damage detection of a rotating machine was conducted based on the spectrum analysis. As results, by adopting the ball bearing used in the rotating machine applied extensively, an spectrum analysis with thermal imaging experiment was performed. Also, as analysing the temperature characteristics obtained from the infrared thermography for in-situ rotating ball bearing under the lubrication condition, it was concluded that infrared thermography for condition monitoring in the rotating machine at real time could be utilized in many industrial fields.