• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.37 no.6
• /
• pp.72-84
• /
• 2000

The test patterns for path delay faults consist of two patterns. So in order to test the delay faults, a new weight generation algorithm that is different from the weight generation algorithm for stuck-at faults must be applied. When deterministic test patterns for weight calculation are used, the deterministic test patterns must be divided into several subsets, so that Hamming distances between patterns are not too long. But this method makes the number of weight sets too large in delay testing, and may generate inaccurate weights. In this pater, we perform fault simulation without pattern partition. Experimental results for ISCAS 89 benchmark circuits prove the effectiveness of the new weight generation algorithm proposed in this paper.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.44 no.7 s.361
• /
• pp.112-121
• /
• 2007

In this paper, we propose a new checkpointing strategy for dual modular redundancy real-time systems. For every checkpoints the execution results from two processors, and the result saved in the previous checkpoint are compared to detect faults. We devised an operation algorithm in chectpoints to recover from transient faults as well as permanent faults. We also develop a Markov model for the optimization of the proposed checkpointing strategy. The probability of successful task execution within its deadline is derived from the Markov model. The optimal number of checkpoints is the checkpoints which makes the successful probability maximum.

• Journal of the Korea Society of Computer and Information
• /
• v.20 no.5
• /
• pp.73-81
• /
• 2015

Most of the software fault prediction studies focused on the binary classification model that predicts whether an input entity has faults or not. However the ability to predict entity fault-proneness in various severity categories is more useful because not all faults have the same severity. In this paper, we propose fault prediction models at different severity levels of faults using traditional size and complexity metrics. They are ternary classification models and use four machine learning algorithms for their training. Empirical analysis is performed using two NASA public data sets and a performance measure, accuracy. The evaluation results show that backpropagation neural network model outperforms other models on both data sets, with about 81% and 88% in terms of accuracy score respectively.

• Journal of the Institute of Electronics Engineers of Korea SD
• /
• v.47 no.2
• /
• pp.51-59
• /
• 2010

Two logic transformations, De Morgan and re-substitution, are sufficient to convert a unate gate network (UGN) to a more general balanced inversion parity (BIP) network. Circuit classes of interest are discussed in detail. We prove that De Morgan and re-substitution transformations are test-set preserving for path delay faults. Using the results of this paper, we can easily show that a high-level test set for a function z that detects all path delay faults in any UGN realizing z also detects all path delay faults in any BIP realization of z.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.4
• /
• pp.1450-1458
• /
• 2018

Commutation failures can deteriorate the availability of high-voltage direct current (HVDC) links and may lead to outage of the HVDC system. Most commutation failures are caused by voltage reduction due to ac system faults on inverter side. The commutation failure process can be divided into two stages. The first stage, from the occurrence to the clearing of faults, is called 'Deterioration Stage'. The second stage, from the faults clearing to restoring the power system stability, is called 'Recovery Stage'. Based on the analysis of the commutation failure process, this paper proposes a direct-current fuzzy controller including prevention and recovery controller. The prevention controller reduces the direct current to prevent Commutation failures in the 'Deterioration Stage' according to the variation of ac voltage. The recovery controller magnifies the direct current to speed up the recovery of power system in the 'Recovery Stage', based on the recovery of direct voltage. The validity of this proposed fuzzy controller is further proved by simulation with CIGRE HVDC benchmark model in PSCAD/EMTDC. The results show the commutation failures can be mitigated by the proposed direct-current fuzzy controller.

• Journal of Electrical Engineering and Technology
• /
• v.13 no.5
• /
• pp.1831-1840
• /
• 2018

During a power swing, distance relays may mistakenly spread fault throughout the power grid, causing a great deal of damage. In some cases, such mistakes can cause global outages. For this reason, it is critical to make a distinction between power swings and faults in distance relays. In this paper, a new method is proposed based on RMS measurement to differentiate between faults and power swings. The proposed method was tested on two standard grids, demonstrating its capability in detecting a power swing and simultaneous fault with power swing. This method required no specific configurations, and was independent of grid type and zoning type of distance relays. This feature in practice allows the relay to be installed on any grid with any kind of coordination. In protective relays, the calculations applied to the microprocessor is of great importance. Distance relays are constantly calculating the current RMS values for protection purposes. This mitigates the computations in the microprocessor to detect power swings. The proposed method was able to differentiate between a fault and a power swing. Furthermore, it managed to detect faults occurring simultaneously with power swings.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.272-275
• /
• 1992

A novel fault diagnosis method based on likelihood decomposition is proposed for linear stochastic systems described by autoregressive (AR) model. Assuming that at some time instant .tau. the fault of one of the following two types is occurs: innovation fault (actuator fault); and observation fault (sensor fault), the log-likelihood function is decomposed into two components based on the observations before and after .tau., respectively, Then, the type of the fault is determined by comparing the log-likelihoods corresponding two types of faults. Numerical examples demonstrate the usefulness of the proposed diagnosis method.

• Journal of Integrative Natural Science
• /
• v.7 no.1
• /
• pp.67-73
• /
• 2014

We consider the mean value function for NHPP software reliability model and time series regression model in software failure data. We estimate parameters for the proposed models from two data sets. The values of SSE and MSE is presented from two data sets. We compare the predicted number of faults with the actual two data sets using the mean value function and regression curve.

• The Journal of Engineering Geology
• /
• v.13 no.2
• /
• pp.193-205
• /
• 2003

Fine grained granite, porphyritic granite and biotite granite together with intruded and extruded andesitic rocks are distributed in the study area which is bounded by the Yangsan and Dongrae faults. A new domestic road is being constructed along the area between the two major faults. The NNE trending Bupki fault and NE trending Myungkog fault are also developed within the area cross the road. The sheeting joints with dips of less than 30 degrees are only developed in the area of granite outcrop. High angle joints can be divided into 3 sets, such as, NE trending, NW trending and nearly EW trending joints. The joint space is mostly more than 20cm and the joint compressive strength is more than 100 MPa. These data show that even though the study area is situated between large faults, the ground condition is good because the damage zone of the Yangsan and Dongrae faults is relatively narrow.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1439-1444
• /
• 2005

Induction motors are the most commonly used electrical drives because they are rugged, mechanically simple, adaptable to widely different operating conditions, and simple to control. The most common faults in squirrel-cage induction motors are bearing, stator and rotor faults. Surveys conducted by the IEEE and EPRI show that the most common fault in induction motor is bearing failure (${\sim}$40% of failure). Thence, this paper addresses experimental results for diagnosing faults with different rolling element bearing damage via motor current spectral analysis. Rolling element bearings generally consist of two rings, an inner and outer, between which a set of balls or rollers rotate in raceways. We set the experimental test bed to detect the rolling-element bearing misalignment of 3 type induction motors with normal condition bearing system, shaft deflection system by external force and a hole drilled through the outer race of the shaft end bearing of the four pole test motor. This paper takes the initial step of investigating the efficacy of current monitoring for bearing fault detection by incipient bearing failure. The failure modes are reviewed and the characteristics of bearing frequency associated with the physical construction of the bearings are defined. The effects on the stator current spectrum are described and related frequencies are also determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. We utilized the FFT, Wavelet analysis and averaging signal pattern by inner product tool to analyze stator current components. The test results clearly illustrate that the stator signature can be used to identify the presence of a bearing fault.