• Journal of the Korean Society for Railway
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• v.9 no.5 s.36
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• pp.612-617
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• 2006

As the on-board electric devices determine the performances of vehicles, production of reliable devices is important. To keep the reliability of devices constant, management of performance evaluation of the on-board devices is crucial. Because temperature has a serious effect on failures of the components of the devices, its measurement is the first step for good management. In this study, we described performance characteristics of domestic auxiliary block developed through G7 project. We measured the performances of auxiliary block during test running by the developed on-line measurement system. After we save the input real-time data from each signal of Korean High Speed Train through the network line, we can acquire necessary information through post-processing program. We verify the motor block characteristics of Korean High Speed Train by this system.

• Journal of the Korean Society for Precision Engineering
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• v.30 no.7
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• pp.679-686
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• 2013

The reduction unit is one of the most important components in railway cars, due to the transmission of torque from the motor to the wheels. Faulty reduction gears in high-speed trains result from excessive wear on the gear or damage to the gear. These types of gear defects have a significant effect on high-speed rail operation and safety; thus, a diagnosis system for the reduction unit is needed. Vibration diagnosis technology is one of the most effective diagnostics. In this paper, the vibration parameters of a reduction unit were evaluated during a driving-gear test and a full-vehicle test, using kurtosis and the crest factor. These tests were performed under normal operating conditions; a specimen tester was used to diagnose problems in defective gears.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2077-2078
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• 2011

Now a days, the induction motor is widely used in industry automation. Without monitoring the motor fault, maintenance cost is increased undesirably high. The slip frequency is included in the feature frequency, so rotating rotor speed is needed. In this paper, a sensorless motor speed estimation method, rotor slot harmonic(RSH) method is suggested and a solution of rotor bar diagnosis is proposed for motor running with light-load. When the rotor is rotating, it shows the harmonic signal of back-emf voltage related with number of rotor slot. So from the power spectrum of current signal, we can find the rotor speed.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.7
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• pp.868-875
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• 1999

In this paper, digital motor control center using protection relay is developed in order to protect power systems by means of timely fault detection and diagnosis during operation for induction motor which have various load environments and capacities in power systems. Digital motor control center is employed by power supervisory control systems without separate remote terminal unit and transducers adding communicational ability. Also we develope a maximum demand controller to control the load effectively at peak status and a power factor controller to minimize real power losses and improve the power factor. Therefore, when using the developed controller, real time computation is possible by loading DSP in hardware and applying real-time kernel which can convert each algorithm to task module.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.878-882
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• 2004

In this paper, we propose a hierarchical hybrid neural network for detecting faults of induction motor. Implementing the classifier based on the input and output data, we apply appropriate transform and classification method at each step. In the proposed method, after obtaining the current of state of motor for each period, we transform it by Principle Component Analysis(PCA) to reduce its dimension. Before the training process, we use the conditional Fuzzy C-means(FCM) for obtaining the initial parameters of neural network for more effective learning procedure. From the various simulations, we find that the proposed method shows better performance to detect and diagnosis of induction motor and compare than other methods.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.2075-2076
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• 2011

The stator winding faults diagnosis technique based on MCSA is as follows. Firstly, collecting the 3 phase motor currents, that signal is transformed by (d-q transform, $i_d$, $i_q$). Park's vector pattern, the circle that is down by d-q transformed currents($i_d$, $i_q$). The circle is widely used for stator winding faults detection. The current distortion ratio(DR), defined by the ratio of max-axis and min-axis of ellipse of Park's vector's pattern. In this study, distortion ratio of Park's vector pattern is suggested for Auto diagnosis of stator winding short fault and usefulness of distortion ratio is verified through simulation using LabVIEW program.

• Proceedings of the KIEE Conference
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• 2000.07b
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• pp.1371-1373
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• 2000

In this paper, the complex accelerating degradation of traction motor driven with VVVF controlled inverter were performed on the form coil samples with the 200 Class insulation system. in order to evaluate the reliability and the long-term life. After aging, the dielectric and PD properties were investigated on the 10 cycles aging sample in the range of $20{\sim}160[^{\circ}C]$ and AC $250{\sim}2250[V]$ to diagnosis the condition of end-life and find the dominative factors of degradation.

• Proceedings of the KIEE Conference
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• 2003.07b
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• pp.801-803
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• 2003

Faults in induction motors can be categorized into mechanical faults and electrical faults, and most mechanical faults result from inferiority or damage of the bearing, while most electrical faults derive from insulation faults of stator windings and rotor bar cracks. When a crack appears on the rotor bar, its efficiency decreases, which increases energy consumption and temperature, reducing the life span of the motor. This kind of fault can only be sensed by the protection relay after the condition has worsened to a certain degree, bringing massive economic loss. This paper will deal with the diagnosis method of rotor bar faults through the load current analysis method of the motor used during operation.

• Proceedings of the KIEE Conference
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• 2001.07b
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• pp.635-637
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• 2001

The faults of the squirrel cage induction motor is grew increasingly complex as the faults resulting in the shorting of a stator winding and the broken rotor bar or cracked rotor end ring, bearing faults, and so on. The users of electrical machines initially relied on simple protections such as over-current, over-voltage, earth-fault, etc. to ensure safe and reliable operation. but this method cause heavy financial losses and the threat of safety therefore it has now become very important to diagnose faults at there very inception. in this paper, we are going to discuss the detection method of broken rotor bar of squirrel cage induction motor by the motor current signal analysis(MCSA) and the opening terminal voltage signal analysis.

• Smart Structures and Systems
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• v.22 no.2
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• pp.185-192
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• 2018

Participants in the Asia Pacific Conference of the Prognostics and Health Management Society 2017 (PHMAP 2017) Data Challenge were given measured vibration signals from motor-driven gearboxes used in pulverizers. Using this information, participants were requested to predict failure dates and the faulty components. The measured signals were affected by significant noise and disturbance, as the pulverizers in the provided data worked under actual operating conditions. This paper thus presents a fault prediction method for a motor-driven gearbox in a pulverizer system that can perform under external noise and disturbance conditions. First, two fault features, an RMS value in the higher frequency zones (HRMS) and an amplitude of a period for high-speed shaft in the quefrency domain ($QA_{HSS}$), were extracted based on frequency analysis using the higher and lower sampling rate data. The two features were then applied to each pulverizer based on results of frequency responses to impact loadings. Then, a regression analysis was used to predict the failure date using the two extracted features. A weighted regression analysis was used to compensate for the imbalance of the features in the given period. In addition, the faulty components in the motor-driven gearboxes were predicted based on the modulated frequency components. The score predicted by the proposed approach was ranked first in the PHMAP 2017 Data Challenge.