• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.11
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• pp.1949-1957
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• 2003

A hybrid finite element analysis was used to analyze the influence of ring gear rim thickness and spline number on the static properties of a planetary gear system with manufacturing errors. Both of these parameters affected the bearing force and critical stress. The effect of changes in the rim thickness on the load sharing between the gears depended on the type of manufacturing error. Ring flexibility improved the load sharing between planetary gears only in systems with planet tooth thickness or planet tangential errors; for other types of error, ring flexibility worsened the load sharing. To improve load sharing, rim thickness and spline number should be controlled within a specific range. The minimum rim thickness limit should be determined considering not only the critical stress but also the load sharing. The effect of the ring gear boundary condition was more apparent in a system with errors than in a normal system.

• Journal of Advanced Navigation Technology
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• v.9 no.2
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• pp.140-146
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• 2005

In this paper, we proposed the frequency offset compensation algorithm and tracking algorithm which could improve the accumulated phase error for HDR-WPAN system. The proposed frequency offset compensation technique estimated each sample phase error by autocorrelation characteristics of CAZAC sequence, estimated phase error multiple each sample in a symbol, and finally compensated for the frequency offset. After frequency offset compensation using two steps, coarse and fine frequency offset, tracking algorithm have to use to compensate for the accumulated phase error. Because there is no pilot symbol in payload, more phase rotation occurred in received signal constellations due to the accumulated phase error as the payload length increase. Tracking algorithm compensates for a cumulative phase error ${\theta}$ between payload data.

• Transactions of The Korea Fluid Power Systems Society
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• v.8 no.3
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• pp.1-7
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• 2011

As the technologies of electronic device have advanced these days, most of mechanical systems are designed with electronic control unit to take advantage of control parameter adaption to operating conditions and firmware flexibilities as well. On-board diagnosis, which detects the system malfunction and identifies potential source of error with its own diagnostic criteria, and fail-safe that can switch the mode of operation in view of recognized error characteristics enables easy maintenance and troubleshooting as well as system protection. This paper dealt with the development of diagnosis and fail-safe function for proportional flow control valve. All type of errors related to valve control system components are investigated and assigned to a specific hexadecimal codes. Cumulative error detection algorithm is applied in order for the sensitivity and reliability to be appropriate. Embedded simulator which runs simultaneously with system program provides the virtual error simulation environment for expeditious development of error detection algorithm. The diagnosis function was verified both with solenoid valve and embedded simulator test and it will enhance the valve control system monitoring function.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.5C
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• pp.487-495
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• 2007

When error occurs during the network transmission of the image, the quality of the restored image is very serious. Therefore to maintain the received image quality, the error concealment technique is necessary. This paper presents an efficient spatial error concealment method using adaptive edge-oriented interpolation. It deals with errors on slice level. The proposed method uses boundary matching method having 2-step processes. We divide error block into external and internal region, adaptively restore each region. Because this method use overall as well as local edge characteristics, it preserves edge continuity and texture feature. The proposed technique reduces the complexity and provide better reconstruction quality for damaged images than the previous methods.

• Proceedings of the ESK Conference
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• 1996.04a
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• pp.113-127
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• 1996

In Human Reliability Analysis(HRA), the uncertainties involved in many factors that affect human reliability have to be represented as the quantitative forms. Conventional probability- based human reliability theory is used to evaluate the effect of those uncertainties but it is pointed out that the actual human reliability should be different from that of conventional one. Conventional HRA makes use of error rates, however, it is difficult to collect data enough to estimate these error rates, and the estimates of error rates are dependent only on engineering judgement. In this paper, the error possibility that is proposed by Onisawa is used to represent human reliability, and the error possibility is obtained by use of fuzzy reasoning that plays an important role to clarify the relation between human reliability and human error. Also, assuming these factors are connected to the top event through Fault Tree structure, the influence and correlation of these factors are measured by fuzzy operation. When a fuzzy operation is applied to Fault Tree Analysis, it is possible to simplify the operation applying the logic disjuction and logic conjuction to structure function, and the structure of human reliability can be represented as membership function of the top event. Also, on the basis of the the membership function, the characteristics of human reliability can be evaluated by use of the concept of pattern recognition.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.1
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• pp.479-483
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• 2006

Indoor positioning is recently highlighted and various kinds of indoor positioning systems are under developments. Since positioning systems have their own characteristics, proper positioning scheme should be chosen according to the required specifications. Positioning methods are often classified into time-based and angle-based one, and this paper presents the error analysis of these location methods. Because measurement equations of these methods are nonlinear, linearization is usually needed to get the position estimate. In this paper, Gauss-Newton method is used in the linearization. To analyze the position error, we investigate the error ellipse parameters that include eccentricity, rotation angle, and the size of ellipse. Simulation results show that the major axes of error ellipses of TOA and AOA method lie in different quadrants at most region of workspace, especially where the geometry is poor. When the TOA/AOA hybrid scheme is employed, it is found that the error ellipse is reduced to the intersection of ellipses of TOA and AOA method.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.25-25
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• 2023

The ensemble optimal interpolation (EnOI) scheme is a sub-optimal alternative to the ensemble Kalman filter (EnKF) with a reduced computational demand making it potentially more suitable for operational applications. Since only one model is integrated forward instead of an ensemble of model realizations, online estimation of the background error covariance matrix is not possible in the EnOI scheme. In this study, we investigate two Gaussian noise based ensemble generation strategies to produce dynamic covariance matrices for assimilation of water level observations into a distributed hydrological model. In the first approach, spatially correlated noise, sampled from a normal distribution with a fixed fractional error parameter (which controls its standard deviation), is added to the model forecast state vector to prepare the ensembles. In the second method, we use an adaptive error estimation technique based on the innovation diagnostics to estimate this error parameter within the assimilation framework. The results from a real and a set of synthetic experiments indicate that the EnOI scheme can provide better results when an optimal EnKF is not identified, but performs worse than the ensemble filter when the true error characteristics are known. Furthermore, while the adaptive approach is able to reduce the sensitivity to the fractional error parameter affecting the first (non-adaptive) approach, results are usually worse at ungauged locations with the former.

• International Journal of Aeronautical and Space Sciences
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• v.17 no.1
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• pp.64-72
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• 2016

The coverage area of a GNSS regional ionospheric delay model is mainly determined by the distribution of GNSS ground monitoring stations. Extrapolation of the ionospheric model data can extend the coverage area. An extrapolation algorithm, which combines observed ionospheric delay with the environmental parameters, is proposed. Neural network and least square regression algorithms are developed to utilize the combined input data. The bi-harmonic spline method is also tested for comparison. The IGS ionosphere map data is used to simulate the delays and to compute the extrapolation error statistics. The neural network method outperforms the other methods and demonstrates a high extrapolation accuracy. In order to determine the directional characteristics, the estimation error is classified into four direction components. The South extrapolation area yields the largest estimation error followed by North area, which yields the second-largest error.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1159-1166
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• 2010

To improve prediction quality of a nonlinear prediction system, the system's capability for uncertainty of nonlinear data should be satisfactory. This paper presents a TSK fuzzy prediction system that can consider and deal with the uncertainty of nonlinear data sufficiently. In the design procedures of the proposed system, HCBKA(Hierarchical Correlationship-Based K-means clustering Algorithm) was used to generate the accurate fuzzy rule base that can control output according to input efficiently, and the first-order difference method was applied to reflect various characteristics of the nonlinear data. Also, multiple prediction systems were designed to analyze the prediction tendencies of each difference data generated by the difference method. In addition, to enhance the prediction quality of the proposed system, an error compensation method was proposed and it compensated the prediction error of the systems suitably. Finally, the prediction performance of the proposed system was verified by simulating two typical time series examples.

• International Journal of Aeronautical and Space Sciences
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• v.15 no.3
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• pp.302-308
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• 2014

In this paper, a detailed investigation of the random vibration test is presented for strapdown inertial navigation systems (INS). The effect of the random vibration test has been studied from the point of view of navigation performance. The role of distribution functions and RMS value is represented to determine a feasible method to reject or reduce vibration related error in position and velocity estimation in inertial navigation. According to a survey conducted by the authors, this is the first time that the effect of the distribution function in vibration related error has been investigated in random vibration testing of INS. Recorded data of navigation grade INS is used in offline static navigation to examine the effect of different characteristics of random vibration tests on navigation error.