• Proceedings of the KIEE Conference
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• 2003.07c
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• pp.1894-1896
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• 2003

In this paper, a novel monitoring system, data acquisition & diagnosis unit (DADU), for high-voltage rotating machines is proposed. This system monitors the insulation condition, current, voltage, vibration, and temperature of the stator winding by on-line measurements of partial discharge (PD), flux, etc. This helps more efficient operation and maintenance of the rotating machines.

• Industrial Engineering and Management Systems
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• v.2 no.1
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• pp.1-8
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• 2003

Among many dimensional or dimensionless amplitude parameters, kurtosis and ID Factor are said to be sensitive good parameters for machine diagnosis. In this paper, a simplified calculation method for both parameters is introduced when impact vibration arise in the observed data. Compared with the past papers' results, this new method shows a good result which fit well. This calculation method is simple enough to be executed even on a pocketsize calculator and is very practical at the factory of maintenance field. This can be installed in microcomputer chips and utilized as a tool for early stage detection of the failure.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.68-74
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• 2005

Among many dimensional and dimensionless amplitude parameters, kurtosis (4-th normalized moment of probability density function) is generally regarded as a sensitive good parameter for machine diagnosis. However, higher order moment may be supposed to be much more sensitive. Bicoherence is an absolute deterioration factor whose range is 1 to 0. The theoretical value of n-th moment divided by n-th moment calculated by measured data would behave in the same way. We propose a simplified calculation method for an absolute index of n-th moment and name this as simplified absolute index of n-th moment. Some favorable results are obtained.

• Smart Structures and Systems
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• v.30 no.3
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• pp.263-271
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• 2022

In this paper we present an overview of damage diagnosis algorithms that have been developed over the past two decades using vibration signals obtained from structures. Then, the paper focuses primarily on algorithms that can be used following an extreme event such as a large earthquake to identify structural damage for responding in a timely manner. The algorithms presented in the paper use measurements obtained from accelerometers and gyroscope to identify the occurrence of damage and classify the damage. Example algorithms are presented include those based on autoregressive moving average (ARMA), wavelet energies from wavelet transform and rotation models. The algorithms are illustrated through application of data from test structures such as the ASCE Benchmark structure and laboratory tests of scaled bridge columns and steel frames. The paper concludes by identifying needs for research and development in order for such algorithms to become viable in practice.

• Nuclear Engineering and Technology
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• v.35 no.5
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• pp.454-470
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• 2003

In this paper, a preliminary study for development of a fault diagnosis is presented for monitoring and diagnosing faults in the agitator driving system of a high temperature reduction reactor. In order to identify a fault occurrence and classify the fault cause, vibration signals measured by accelerometers on the outer shroud of the agitator driving system are firstly decomposed by wavelet transform (WT) and the features corresponding to each fault type are extracted. For the diagnosis, the fuzzy ARTMAP is employed and thereby, based on the features extracted from the WT, the robust fault classifier can be implemented with a very short training time - a single training epoch and a single learning iteration is sufficient for training the fault classifier. The test results demonstrate satisfactory classification for the faults pre-categorized from considerations of possible occurrence during experiments on a small-scale reduction reactor.

• Earthquakes and Structures
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• v.18 no.1
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• pp.97-111
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• 2020

Cylindrical steel tanks are important components of industrial facilities. Their safety becomes a crucial issue since any failure may cause catastrophic consequences. The aim of the paper is to show the results of comprehensive FEM numerical investigation focused on the response of cylindrical steel tanks under mining tremors and moderate earthquakes. The effects of different levels of liquid filling, the influence of non-uniform seismic excitation as well as the aspects of diagnosis of structural damage have been investigated. The results of the modal analysis indicate that the level of liquid filling is really essential in the structural analysis leading to considerable changes in the shapes of vibration modes with a substantial reduction in the natural frequencies when the level of liquid increases. The results of seismic and paraseismic analysis indicate that the filling the tank with liquid leads to the substantial increase in the structural response underground motions. It has also been observed that the peak structural response values under mining tremors and moderate earthquakes can be comparable to each other. Moreover, the consideration of spatial effects related to seismic wave propagation leads to a considerable decrease in the structural response under non-uniform seismic excitation. Finally, the analysis of damage diagnosis in steel tanks shows that different types of damage may induce changes in the free vibration modes and values of natural frequencies.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.87-91
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• 2019

The diagnosis of the failure for the existing electrical facilities was based on regular preventive maintenance, but this preventive maintenance was limited in preventing a lot of cost loss and sudden system failure. To overcome these shortcomings, fault prediction and diagnostic techniques are critical to increasing system reliability by monitoring electrical installations in real time and detecting abnormal conditions in the facility early. As the performance and quality deterioration problem occurs frequently due to the increase in the number of users of the motor pump, the purpose is to build an intelligent control system that can control the motor pump to maximize the performance and to improve the quality and reliability. To this end, a vibration sensor, temperature sensor, pressure sensor, and low water level sensor are used to detect vibrations, temperatures, pressures, and low water levels that can occur in the motor pump, and to build a system that can identify and diagnose information to users in real time.

• Proceedings of the KIEE Conference
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• 2005.10b
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• pp.264-266
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• 2005

Recently, on-line diagnosis methods through wired and wireless networks are widely adopted in the diagnosis of industrial Electric Facilities, such as generators, transformers and motors. Also smart sensors which includes sensors, signal conditioning circuits and micro-controller in one board are widely studied in the field of condition monitoring. This paper suggests an self-powered system suitable for condition-monitoring smart sensors, which uses parasitic vibrations of the facilities as energy source. First, vibration-driven noise patterns of the electric facilities are presented. And then, an electromagnetic generator which uses mechanical mass-spring vibration resonance are suggested and designed. Finally energy consumption of the presented smart sensor, which consists of MEMS vibration sensors, signal conditioning circuits, a low-power consumption micro-controller, and a ZIGBEE wireless tranceiver, are presented. The usefulness and limits of the presented electromagnetic generators in the field of electric facility monitoring are also suggested.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2008.04a
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• pp.742-746
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• 2008

With the trend of factory automation, nowadays, much industrial machinery tends to be put into 24-hours operation a day. However, these trends in industrial equipments also increase the possibility of various mechanical problems and bring about innumerable maintenance cost. There is a strong need of the condition monitoring and diagnosis for industrial equipment, especially rotating machinery, since they are connected not only to the reduction in the maintenance costs but also connected to the enhancement of production efficiency. Generally, to evaluate the operating conditions in the machinery in the industrial field, various physical properties are monitored. Among them, vibration and Noise signals are the mist important indicator and it is effectively used in many diagnosis systems for machinery. Much previous research is based in the FFT (Fast Fourier Transform) method. The spectral analysis is assumed that the signal is stationary. However, almost random signals are non-stationary. The wavelet transform has been recognized an efficient Method. Most interesting sounds have time-varying features. Signal processing techniques for the analysis of transient sound have been not clearly given yet.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1995.04a
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• pp.571-571
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• 1995