• Proceedings of the Korean Society of Precision Engineering Conference
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• 1994.10a
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• pp.670-675
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• 1994

Yhis paper describes a fault diagnosis simulation of the Real-Time Multiple Fault Dignosis System (RTMFDS) for forcasting faults in a system and deciding current machine state from signal information. Comparing with other diagnosis system for single fault,the system developed deals with multiple fault diagnosis,comprising two main parts. One is a remotesignal generating and transimission terminal and the other is a host system for fault diagnosis. Signal generator generate the random fault signal and the image information, and send this information to host. Host consists of various modules and agents such as Signal Processing Module(SPM) for sinal preprocessing, Performence Monotoring Module(PMM) for subsystem performance monitoring, Trigger Module(TM) for multi-triggering subsystem fault diagnosis, Subsystem Fault Diagnosis Agent(SFDA) for receiving trigger signal, formulating subsystem fault D\ulcornerB and initiating diagnosis, Fault Diagnosis Module(FDM) for simulating component fault with Hierarchical Artificial Neural Network (HANN), numerical models and Hofield network,Result Agent(RA) for receiving simulation result and sending to Treatment solver and Graphic Agent(GA). Each agent represents a separate process in UNIX operating system, information exchange and cooperation between agents was doen by IPC(Inter Process Communication : message queue, semaphore, signal, pipe). Numerical models are used to deseribe structure, function and behavior of total system, subsystems and their components. Hierarchical data structure for diagnosing the fault system is implemented by HANN. Signal generation and transmittion was performed on PC. As a host, SUN workstation with X-Windows(Motif)is used for graphic representation.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.10
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• pp.1774-1779
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• 2016

This paper proposes a portable cable fault detection system with automatic fault distinction and distance measurement using time-frequency correlation and reference signal elimination method and automatic fault classification algorithm in order to have more accurate fault determination and location detection than conventional time domain refelectometry (TDR) system despite increased signal attenuation due to the long distance to cable fault location. The performance of the developed system method was validated via an experiment in the test field constructed for the standardized performance test of power cable fault location equipments. The performance evaluation showed that accuracy of the developed system is less than 1.34%. Also, an error of automatic fault type and location by detection of phase and peak value through elimination of the reference signal and normalization of correlation coefficient and automatic fault classification algorithm not occurred.

• Journal of Power Electronics
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• v.6 no.1
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• pp.8-17
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• 2006

In this paper, we propose a fault-tolerant control system for the position control and vibration suppression of a flexible arm robot. The proposed control system has a strain gauge sensor signal observer based on a reaction force observer and detects a fault by monitoring an estimated error. In order to improve the estimation accuracy, the plant parameters included in the sensor signal observer are updated by using the strain gauge sensor signal in normal time through the adaptive law. After fault detection, the proposed control system exchanges the faulty sensor signal for the estimated one and switches to a fault mode controller so as to maintain the stability and the control performance. We confirmed the effectiveness of the proposed control system through several experiments.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.709-711
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• 2005

Developing fault location system for underground power cable which can detect its fault location exactly require very high speed data acquisition and signal processing capability. We are developing fault location system which is different from conventional fault locator. This fault location system monitor underground power cable by using on-line speed current sensor and if there are an accident, it record its transient signal and calculate fault location by analyzing it. Signals which acquired when power cable fault arise, showed transient characteristics and its frequency band is very hish. So, to develop fault location system, we designed special high speed data acquisition and signal processing board. In this thesis, we describe on data acquisition and signal processing H/W design for fault location system on underground power cable.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.11
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• pp.874-882
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• 2003

The condition assessment of engineering systems has increased in importance because the manpower needed to operate and supervise various plants has been reduced. Especially, induction motors are at the core of most engineering processes, and there is an indispensable need to monitor their health and performance. So detection and diagnosis of motor faults is a base to improve efficiency of the industrial plant. In this paper, a model-based fault detection system is developed for induction motors, using steady state vibration signals. Early various fault detection systems using vibration signals are a trivial method and those methods are prone to have missed fault or false alarms. The suggested motor fault detection system was developed using a model-based reference value. The stationary signal had been extracted from the non-stationary signal using a data segmentation method. The signal processing method applied in this research is FFT. A reference model with spectra signal is developed and then the residuals of the vibration signal are generated. The ratio of RMS values of vibration residuals is proposed as a fault indicator for detecting faults. The developed fault detection system is tested on 800 hp motor and it is shown to be effective for detecting faults in the air-gap eccentricities and broken rotor bars. The suggested system is shown to be effective for reducing missed faults and false alarms. Moreover, the suggested system has advantages in the automation of fault detection algorithms in a random signal system, and the reference model is not complicated.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.537-543
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• 2003

Transient vibration generated by developing localized fault in gear can be used as indicators in gear fault detection. This vibration signal suffers from the background noise such as gear meshing frequency and its harmonics and broadband noise. Thus in order to extract the information about the only gear fault from the raw vibration signal measured on the gearbox this signal is processed to reduce the background noise with many kinds of signal-processing tools. However, these signal-processing tools are often very complex and time waste. Thus. in this paper. we propose a novel approach detecting the damage of gearbox and analyzing its pattern using the raw vibration signal. In order to do this, the residual signal. which consists of the sideband components of the gear meshing frequent) and its harmonics frequencies, is extracted from the raw signal by the power spectral density (PSD) to obtain the information about the fault and is used as the input data of the artificial neural network (ANN) for analysis of the pattern of gear fault. This novel approach has been very successfully applied to the damage analysis of a laboratory gearbox.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.2
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• pp.139-147
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• 1987

This paper presented a method evaluating the signal reliability for signal stuck-at-type in digital circuits. Here, the signal reliability is defined as the probability that circuit output is correct, even though the fault existed at the internal parts of digital circuit. In evaluating the signal reliability, this paper presented not only fault model and algorithm for signal stuck-at-type fault but also computer program for evaluating the signal reliability with respect to complex and large circuit.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.10 s.175
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• pp.80-89
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• 2005

In this paper, time-frequency analysis using wavelet packet transform and advanced-MDSA (Multiple Dimensional Spectral Analysis) which based on wavelet packet transform is applied fur fault source identification and diagnosis of early detection of fault non-stationary sound/vibration signals. This method is analyzing the signal in the plane of instantaneous time and instantaneous frequency. The results of ordinary coherence function, which obtained by wavelet packet analysis, showed the possibility of early fault detection by analysis at the instantaneous time. So, by checking the coherence function trend, it is possible to detect which signal contains the major fault signal and to know how much the system is damaged. Finally, It is impossible to monitor the system is damaged or undamaged by using conventional method, because crest factor is almost constant under the range of magnitude of fault signal as its approach to normal signal. However instantaneous coherence function showed that a little change of fault signal is possible to monitor the system condition. And it is possible to predict the maintenance time by condition based maintenance for any stationary or non-stationary signals.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.3
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• pp.450-456
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• 2016

STDR (sequence time domain reflectometry) to detect a cable fault using a pseudo noise sequence as a reference signal, and time correlation analysis between the reference signal and reflection signal is robust to noisy environments and can detect intermittent faults including open faults and short circuits. On the other hand, if the distance of the fault location is far away or the fault type is a soft fault, attenuation of the reflected signal becomes larger; hence the correlation coefficient in the STDR becomes smaller, which makes fault detection difficult and the measurement error larger. In addition, automation of the fault location by detection of phase and peak value becomes difficult. Therefore, to improve the cable fault detection of a conventional STDR, this paper proposes the algorithm in that the peak value of the correlation coefficient of the reference signal is detected, and a peak value of the correlation coefficient of the reflected signal is then detected after removing the reference signal. The performance of the proposed method was validated experimentally in low-voltage power cables. The performance evaluation showed that the proposed method can identify whether a fault occurred more accurately and can track the fault locations better than conventional STDR despite the signal attenuation. In addition, there was no error of an automatic fault type and its location by the detection of the phase and peak value through the elimination of the reference signal and normalization of the correlation coefficient.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.11
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• pp.1759-1766
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• 2001

Vibration transient generated by developing localized fault in gear can be used as indicators in gear fault detection. In this paper, we propose the zoomed phase map for a fault signal using continuous wavelet transfers to detect this vibration transient. Local fault induces the abrupt fluctuation of load exciting tooth and phase lag in the vibration signal measured on the gearbox. The relatively large fault like "tip breakage" easily can be detected by the clear fluctuation of exciting load. However, minor fault like "initial pitting"cannot be detected using the load fluctuation. To defect this kind of minor fault, the phase map for a fault signal is taken into account. The phase lag by minor fault is observed well in the zoomed phase map.