• Transactions of the Korean Society of Mechanical Engineers A
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• v.36 no.7
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• pp.813-822
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• 2012

Abnormal operating sounds radiated from a moving transfer robot in LCD (liquid crystal display) product lines have been used for the fault detection line of a robot instead of other source signals such as vibrations, acoustic emissions, and electrical signals. Its advantage as a source signal makes it possible to monitor the status of multiple faults by using only a microphone, despite a relatively low sensitivity. The wavelet packet transform for feature extraction and the artificial neural network for fault classification are employed. It can be observed that the abnormal operating sound is sufficiently useful as a source signal for the fault diagnosis of mechanical components as well as other source signals.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.1
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• pp.23-26
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• 2005

This paper describes the algorithm for deciding the status of the operating machines in the power plants. It is very important to decide whether the status of the operating machines is good or not in the industry to protect the accidents of machines and improve the operation efficiency of the plants. There are two steps to analyze the status of the running machines. First, we extract the features from the input original data. Second, we classify those features into normal/abnormal condition of the machines using the wavelet transform and the input RMS vector through the K-means algorithm. In this paper we developed the algorithm to detect the fault operation using the K-means method from the sound of the operating machines.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.1
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• pp.141-148
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• 2017

Recently, localized heavy rain storms have been occurring frequently due to global warming, and it is difficult to shield a large number of facilities against disaster with limited manpower. The unmanned water treatment system uses five senses to analyze various judgment criteria, which are set according to field situations such as machine vibrations, the temperature of bearings, the sound of the operating machines, and the hydraulic pressure, current, and voltage of the hydraulic floodgates. It thus judges normal or abnormal operation status and conducts unmanned control of such machines. It automatically applies a system to the interruption of communications and therefore improves the reliability of its unmanned irrigation facilities. It maximizes the operational efficiency of managers responsible for various fields, enabling them to discharge water before the situation escalates to a crisis within the golden time, and to protect against damage to humans and property.