• Journal of Information Processing Systems
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• v.16 no.3
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• pp.530-540
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• 2020

In order to solve the problem of low tracking accuracy caused by complex noise in the fault diagnosis of complex nonlinear system, a fault diagnosis method of high precision cost reference particle filter (CRPF) is proposed. By optimizing the low confidence particles to replace the resampling process, this paper improved the problem of sample impoverishment caused by the sample updating based on risk and cost of CRPF algorithm. This paper attempts to improve the accuracy of state estimation from the essential level of obtaining samples. Then, we study the correlation between the current observation value and the prior state. By adjusting the density variance of state transitions adaptively, the adaptive ability of the algorithm to the complex noises can be enhanced, which is expected to improve the accuracy of fault state tracking. Through the simulation analysis of a fuel unit fault diagnosis, the results show that the accuracy of the algorithm has been improved obviously under the background of complex noise.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.259-260
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• 2016

Our research group, which was organized by the South Korean and Japanese researchers, have carried out research about natural disaster in our regional heritage villages derived from the concept of ICT(information communication technology)-based DPD(disaster prevention design). In this research, we performed simulation analysis on the fire safety diagnosis in Asan-Oeam folk and JeonjuHanok village for developing our research of ICT-based PBD. In order to do this, we used fire simulation program which was developed by BRI(Building Research Institute) of Japan. Based on the results of fire simulation of Asan-Oeam folk and JeonjuHanokvillage, we can demonstrated that the fire which broken out inregional heritage folk village will be easily expanded to adjacent houses, because the house which are built with wood structure.

• Journal of Mechanical Science and Technology
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• v.20 no.9
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• pp.1410-1417
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• 2006

The metal processing system usually consists of various components such like motors, work rolls, backup rolls, idle rolls, sensors, etc. Even a simple fault in a single component in the system may cause a serious damage on the final product. It is therefore necessary to diagnose the faults of the components to detect and prevent system failure. Especially, the defects in a work roll are critical to the quality of strip. It is especially difficult to detect faults of a roll by using the existing frequency analysis method if the speed of the roll is changing. In this study, a new diagnosis method for roll eccentricity under the roll speed changes was developed. The new method was induced from analyzing the rolling mechanism by using rolling force models, radius-speed relationship, and measured rolling force, etc. Simulation results by using the field data show that the proposed method is very useful.

• Journal of Biosystems Engineering
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• v.26 no.6
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• pp.503-508
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• 2001

In this paper, time-fiequency analysis and multi-dimensional spectral analysis methods are applied for source identification and diagnosis of non-stationary sound/vibration signals. Sound or vibration problems of general vehicle and agricultural machinary are under 500 Hz. So We used linearly increased chirp signals under 500 Hz. By checking the coherences on concerned time, fur time-variant non-stationary signals, this simulation it very well coincident to expected results.

• Proceedings of the IEEK Conference
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• 2005.11a
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• pp.171-174
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• 2005

The circuit simulation analysis and diagnosis methods are used to instruments in detail when they give apparently abnormal readings. In this paper, a new simulator through an analysis of the important circuits modeling under severe accident conditions has been designed, the realization for a body work instead of the two sorts of the Labview & Pspice as an one order command in the Labview program. The program can be shown the output graph form the circuit modeling as an order commend. The procedure for the simulator design was divided into two design steps, of which the first step was the diagnosis methods, the second step was the circuit simulator for the signal processing tool. It has three main functions which are a signal processing tool, an accident management tool, and an additional guide from the initial screen.

• Proceedings of the Korea Society for Simulation Conference
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• 2005.05a
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• pp.154-159
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• 2005

In this paper, We used the microphone unlike existing urodynamic inspection which diagnoses the LUTS(lower urinary tract symptoms) and proposed sound measurement the method which the urination happens and apply at a blockade diagnosis. To analyze the blockade degree, We made the experiment set to modeling the Lower Urinry System of the human body and made the microphone of the stethoscope form for the measurement of the urinary sound which the urination happens. We used PC for the analysis of the urinary sound to be measured and implemented the analysis program to use the MATLAB. Hereafter, An analysis result usage, The Practical use will be possible as one of new inspection methods's.

• The Journal of the Acoustical Society of Korea
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• v.7 no.4
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• pp.77-85
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• 1988

Many kinds of conditioning monitoring technique have been studied, so this study has inverstigated the possibility of checking the trend in the fault diagnosis of ball bearing, one of the elements of rotating machine, by applying the cepstral analyisis method using the adaptive noise cancelling (ANC) method. And computer simulation is conducted in order to verify the usefulness of ANC. The optimal adaptation gain in adaptive filter is estimated, the performance of ANC according to the change of the signal to noise ratio and convergence of least mean square algorithm is considered by simulation. It is verified that cepstral analysis using ANC method is more effective than the conventional cepstral analysis method in bearing fault diagnosis.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.3
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• pp.336-341
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• 2013

Power converter plays a very important role in switched reluctance motor (SRM) systems, and it is also the easiest one to experience failures. Power converter faults will cause the motor to run in non equilibrium states, and a long time fault operation will lead to motor and other modules damaged, and make the system completely lose working stability. This paper uses an asymmetric bridge converter as the research object with three-phase SRM, employs the wavelet packet decomposition for the phase currents. It analyzes and studies the short circuit fault condition of IGBT, uses an energy discrete degree of the wavelet packet nodes as the fault characteristic, and conducts the corresponding experimental and simulation analysis to verify the effectiveness and practicality of the proposed method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.11a
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• pp.575-578
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• 2003

Recently, because GIS equipment has problems on confidence according to long-time usage, development of diagnosis technique has been importantly recognized. Therefore. measurement and analysis of PD has been generally used much equipment of GIS. But, in case of measurement of PD at field, real trouble signals are difficult to classify noise. Accordingly, a variety of trouble conditions for DS were simulated, and detected signals were analyzed by the application of electrical and mechanical methods. For this analysis, detected signals were accumulated according to phase-magnitude with the application of Induction sensor, and then we analyzed the characteristics. For the simulation experiment, we made DS for 170kV GIS and analyzed the characteristics of detected singals with the application of neural network algorithm.

• The Transactions of the Korean Institute of Power Electronics
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• v.21 no.6
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• pp.481-485
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• 2016

When analyzing economic feasibility for installing a PV generation plant at a certain location, the prediction of possible annual power production at the site using the target PV panels should be conducted on the basis of the local weather data provided by a local weather forecasting office. In addition, the prediction of PV generating power under certain weather conditions is useful for fault diagnosis and performance evaluation of PV generation plants during actual operation. This study analyzes PV cell characteristics according to a variety of weather conditions, including ambient temperature and irradiance level. From the analysis and simulation results, this work establishes a proper model that can predict the output characteristics of PV cells under changes in weather conditions.