• Journal of Korean Institute of Industrial Engineers
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• v.36 no.3
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• pp.154-163
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• 2010

Process monitoring of output variables affecting final performance have been mainly executed in semiconductor manufacturing process. However, even earlier detection of causes of output variation cannot completely prevent yield loss because a number of wafers after detecting them must be re-processed or cast away. Semiconductor manufacturers have put more attention toward monitoring process inputs to prevent yield loss by early detecting change-point of the process. In the paper, we propose the method to efficiently monitor functional input variables in multi-phase semiconductor manufacturing process. Measured input variables in the multi-phase process tend to be of functional structured form. After data pre-processing for these functional input data, change-point analysis is practiced to the pre-processed data set. If process variation occurs, key variables affecting process variation are selected using contribution plot for monitoring efficiency. To evaluate the propriety of proposed monitoring method, we used real data set in semiconductor manufacturing process. The experiment shows that the proposed method has better performance than previous output monitoring method in terms of fault detection and process monitoring.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.11
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• pp.44-52
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• 2002

Since memory technology has been developed fast, test complexity and test time have been increased simultaneously. In practice, March algorithms are used widely for detecting various faults. However, March algorithms cannot detect NPSFs(Neighborhood Pattern Sensitive Faults) which must be considered for DRAMs. This paper proposes an effective algorithm for high fault coverage by modifying the conventional March algorithms.

• Journal of Applied Reliability
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• v.17 no.3
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• pp.224-235
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• 2017

Purpose: Reliability is the most important factor to detect defects as wind turbines are deployed in large blades. The methods of detecting defects are various, such as non-destructive inspection and thermal imaging inspection. We propose the phased array ultrasonic testing method of non-destructive testing. Methods: We propose the active pressure mechanism for wind power blade. The phase array ultrasonic inspection method is used for fault detection inner blade surface. Controlled pressure of mechanism with respect to z-axis is important for guarantee the result of phase array ultrasonic inspection. The model based control and proposed mechanism are utilized for overall system stability and effectiveness of system. Result: The result of proposed pressure mechanism B is more stable than A. Convergence speed is also faster than A. Conclusion: We confirmed the performance of the proposed constant pressure mechanism through experiments. Non-destructive testing was applied to the specimen to confirm the reliability of detecting defects.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.506-515
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• 2023

This study is to find a method to learn engine sound after the start-up of a diesel generator installed in nuclear power plant with an unsupervised deep learning algorithm (CNN autoencoder) and a new method to predict the failure of a diesel generator using it. In order to learn the sound of a diesel generator with a deep learning algorithm, sound data recorded before and after the start-up of two diesel generators was used. The sound data of 20 min and 2 h were cut into 7 s, and the split sound was converted into a spectrogram image. 1200 and 7200 spectrogram images were created from sound data of 20 min and 2 h, respectively. Using two different deep learning algorithms (CNN autoencoder and binary classification), it was investigated whether the diesel generator post-start sounds were learned as normal. It was possible to accurately determine the post-start sounds as normal and the pre-start sounds as abnormal. It was also confirmed that the deep learning algorithm could detect the virtual abnormal sounds created by mixing the unusual sounds with the post-start sounds. This study showed that the unsupervised anomaly detection algorithm has a good accuracy increased about 3% with comparing to the binary classification algorithm.

• Journal of the Korean Institute of Telematics and Electronics
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• v.11 no.4
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• pp.17-22
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• 1974

In this paper, the problem of finding tests to detect faults in combinational logic circuits is considered. At first, the method of fault detection in fan-out-free irredundant circuits is derived, and the result is extended to the fan-out redundant circuits. A fan-out circuit is decomposed into a set of fan-out-free subcircuits by cutting the lines at the internal fan-out points, and the minimal detecting test. sets for each subcircuit are found separately. And then, the compatible tests from each test set are combined maximally into composite tests to generate primary input binary vectors. By this procedure. the minimal complete test sets for reconvergent fan-out circuits are easily found and the detectable and undetectable faults are also classified clearly.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.16 no.5
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• pp.29-37
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• 2002

This paper presents the diagnostic method for fault prevention in metal clad switchgear(MCS) through comparison of signals before and after detecting the partial discharge using electromagnetic detection technique. Electromagnetic waves detected by antennas of the inside and outside of MCS are analyzed and compared by frequency spectrum analysis method which can estimate an insulation abnormality and normality of MCS. As a result of the experiment by the proposed method, we can detect the insulation abnormality as partial discharge in MCS and these results can be applied to preventive diagnosis of MCS.

• Journal of the Korea Society of Computer and Information
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• v.3 no.2
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• pp.69-76
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• 1998

To test all internal faults in the case that the number of Primary Input is N, we need patterns that are composed of PI's of maximum 2N. In this paper, we proposed the method to reduce a search space by dividing the multiple output circuit into subcircuit that is related with output. And this method, called PBM(Partition-Based Method), can generate a set of test pattern. The method can effectively generate a test pattern for evaluating all fault of circuit, because the length of input pattern is smaller than that of full circuit and PBM doesn't search any signal line that is not concerned with detecting fault.

• Journal of Environmental Science International
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• v.25 no.4
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• pp.525-534
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• 2016

The biological wastewater treatment plant, which uses microbial community to remove organic matter and nutrients in wastewater, is known as its nonlinear behavior and uncertainty to operate. Therefore, operation of the biological wastewater treatment process much depends on observation and knowledge of operators. The manual inspection of human operators is essential to manage the process properly, however, it is impossible to detect a fault promptly so that the process can be exposed to improper condition not securing safe effluent quality. Among various process faults, equipment malfunction is critical to maintain normal operational state. To detect equipment faults automatically, the dynamic time warping was tested using on-line oxidation-reduction potential (ORP) and dissolved oxygen (DO) profiles in a sequencing batch reactor (SBR), which is a type of wastewater treatment process. After one cycle profiles of ORP and DO were measured and stored, they were warped to the template profiles which were prepared already and the distance result, accumulated distance (D) values were calculated. If the D values were increased significantly, some kinds of faults could be detected and an alarm could be sent to the operator. By this way, it seems to be possible to make an early detecting of process faults.

• Proceedings of the Korean Geotechical Society Conference
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• 2004.03b
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• pp.904-909
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• 2004

The study area adjoins with Yangsan fault in Sangbuk-myeon, Samsam-ri, Kyongsang-namdo and consist of the natural steep slope. After drawing data layer which have altitude by using digital topography data, it is converted to lattice DEM of $10m{\times}10m$ size. From this, gradient map of unit lattice, slant direction map and shadow relif map are made. Using flow apportioning algorithm, upper slope contributing area and wetness index by established lattice can be calculated. Area that have high wetness index shows lineament structure of northwest-southeast direction, and this agrees with shear fracture system. The result of electricity specific resistance survey in the study area shows that area of high wetness index has low electricity specific resistance anomaly. That is, wetness index conforms with distribution of fractured zone that accompanied chemical weathering of rock. Therefore, wetness index can be used as the method of detecting fractured zones and judging the stability of the area.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.447-448
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• 2015

In order to looking for method of detecting inner fault of a 154kV GIT(Gas Insulated Transformer), it was considered that diagnosis partial discharge(PD) in UHF band and that analyze the ingredients of SF6 insulating gas. UHF PD diagnosis that is optimized to GIS was considered unsuitable through checking of inner part of a transformers which PD is detected excessively. The method analyzing the content of six kinds of gas(SOF2, SO2F2, etc)was decided through analysis of chemical degradation and combination process and discharge experiment. With the result applying this method to analyze the content of insulated gas of eighty five Gas Insulated Transformers.