• Journal of Information Processing Systems
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• v.8 no.1
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• pp.21-54
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• 2012

As we know every software development process is pretty large and consists of different modules. This raises the idea of prioritizing different software modules so that important modules can be tested by preference. In the software testing process, it is not possible to test each and every module regressively, which is due to time and cost constraints. To deal with these constraints, this paper proposes an approach that is based on the fuzzy multi-criteria approach for prioritizing several software modules and calculates optimal time and cost for software testing by using fuzzy logic and the fault tolerance approach.

• Journal of the Korea Society of Computer and Information
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• v.19 no.4
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• pp.55-62
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• 2014

This paper proposes a fault detection method utilizing converted images of acoustic emission signals and texture analysis for identifying bearing's multi-faults which frequently occur in an induction motor. The proposed method analyzes three texture features from the converted images of multi-faults: multi-faults image's entropy, homogeneity, and energy. These extracted features are then used as inputs of a fuzzy-ARTMAP to identify each multi-fault including outer-inner, inner-roller, and outer-roller. The experimental results using ten times trials indicate that the proposed method achieves 100% accuracy in the fault classification.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.562-565
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• 2018

A wide range of IoT applications use information collected from networks of sensors for monitoring and controlling purposes. However, the frequent appearance of fault data makes it difficult to extract correct information, thereby sending incorrect commands to actuators that can threaten human privacy and safety. For this reason, it is necessary to have a mechanism to detect fault data collected from sensors. In this paper, we present a trend-adaptive multi-scale principal component analysis (Trend-adaptive MS-PCA) model for data fault detection. The proposed model inherits advantages of Discrete Wavelet Transform (DWT) in capturing time-frequency information and advantages of PCA in extracting correlation among sensors' data. Experimental results on a real dataset show the high effectiveness of the proposed model in data fault detection.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.12
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• pp.1225-1231
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• 2009

One reaction wheel cluster of satellite usually has four reaction wheels. Each wheel is not arranged parallel to the attitude axis of satellite. Therefore, if one reaction wheel is broken, it is very hard to isolate the fault except using the sensors of wheel itself. In this paper, the isolator of satellite reaction wheel cluster is designed. Using a dual filter, FDP(Fault Detection Parameter) is made to detect fault, and using a multi-hypothesis extended Kalman filter, fault isolation of wheel cluster is done. We verify the improvement of isolation performance of wheel cluster by simulation with 4-reaction wheel cluster.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.18 no.7
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• pp.587-595
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• 2006

A system operating algorithm was developed for the effective operation of a multi-type air-conditioning system. The system operating algorithm includes control algorithms for a safety mode, an initial operating mode, a stabilization mode, a fault diagnosis mode, an efficiency mode, and a tracking mode. Various tests were performed to show the effectiveness of these algorithms. Tests showed good results for the operation of a multi-type air-conditioning system. Therefore, these algorithms developed for this study may be used for the effective control of a multi-type air-conditioning system.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.9
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• pp.675-681
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• 2014

This paper proposes a fault diagnosis system for an induction motor. This system uses empirical mode decomposition(EMD) to extract fault signatures and multi-layer perceptron(MLP) neural network to facilitate an accurate fault diagnosis. EMD can not only decompose a signal adaptively but also provide intrinsic mode functions(IMFs) containing natural oscillatory modes of the signal. However, every IMF does not represent fault signature, an IMF selection algorithm based on harmonics and their energy of each IMF is proposed. The selected IMFs are utilized for fault classification using MLP and this system shows approximately 98 % diagnosis accuracy for the fault vibration signal of the induction motor.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.184-190
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• 2008

The fault location algorithm based on stationary wavelet transform was developed to locate the fault point more accurately. The stationary wavelet transform(SWT) was introduced instead of conventional discrete wavelet transform(DWT) because SWT has redundancy properties which is more useful in noise signal processing. In previous paper, noise cancellation technique based on the correlation of wavelet coefficients at multi-scales was introduced, and the efficiency was also proved in full. In this paper, fault section discrimination and fault location algorithm using noise cancellation technique were tested by ATP simulation on real power cable systems. From these results, the fault can be located even in very difficult and complicated situations such as different inception angle and fault resistance.

• Journal of the Korea Institute of Military Science and Technology
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• v.3 no.2
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• pp.140-148
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• 2000

This paper presents a fault detection and isolation(FDI) method based on Generalized Likelihood Ratio(GLR) test for the tightly coupled SDINS/CPS system. The GLR test is known to have the capability of detecting an assumed change while estimating its occurrence time and magnitude, and isolating the changing part. Once a fault is detected even if we don't know if the fault occurrs at either INS or GPS, multi-hypothesized GLR scheme performs the fault isolation between INS and GPS, and find which satellite malfunctions. However, in the INS faulty case, it turned out to fail to accomodate the fault isolation between accelerometer and gyroscope due to the coupling effects and a poor observability of the system. Hence, to isolate the INS fault, it needs to change the attitude of the vehicle resulting in enhancing the degree of observability.

• Proceedings of the KIEE Conference
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• 1994.11a
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• pp.30-32
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• 1994

This paper presents a new method for the computation of fault location in multi-terminal transmission lines. This technique based upon the distributed model of transmission lines to overcome the problems encountered in traditional approaches. This method uses, the magnitude of the differential currents at each terminal and also uses an algorithm an equivalent conversion from an multi-terminal to a 3 terminal system.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.89-96
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• 2018

When a fault occurs in a power system, the existing analytic models for the power system fault diagnosis could generate multiple solutions under the condition of one or more protective relays (PRs) and/or circuit breakers (CBs) malfunctioning, and/or an alarm or alarms of these PRs and/or CBs failing. Therefore, this paper presents an improved analytic model addressing the above problem. It takes into account the interaction between the uncertainty involved with PR operation and CB tripping and the uncertainty of the alarm reception, which makes the analytic model more reasonable. In addition, the existing analytic models apply the penalty function method to deal with constraints, which is influenced by the artificial setting of the penalty factor. In order to avoid the penalty factor's effects, this paper transforms constraints into an objective function, and then puts forward an improved immune clonal multi-objective optimization algorithm to solve the optimal solution. Finally, the cases of the power system fault diagnosis are served for demonstrating the feasibility and efficiency of the proposed model and method.