• International Journal of Aeronautical and Space Sciences
• /
• 제15권3호
• /
• pp.302-308
• /
• 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.

• 디지털산업정보학회논문지
• /
• 제7권2호
• /
• pp.1-8
• /
• 2011

In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The finite failure non-homogeneous Poisson process models presented and the life distribution applied extreme distribution which used to find the minimum (or the maximum) of a number of samples of various distributions. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error.

• 전기학회논문지
• /
• 제59권6호
• /
• pp.1025-1033
• /
• 2010

This paper proposes a method to improve and analysis error cause of FI(Fault Indicator) information to be used for detecting fault section in distribution automation system. FI error cause is made by consideration fault current magnitude and time. So, a new method to prevent FI error is proposed to include fault current magnitude, time and direction. Therefore, it's considered network environments that grounded and ungrounded network in distribution automation system. The proposed method is proved by Matlap Simulink. By the result in this research, it's possible to quickly restoration, supplying stability and reliability power to customer.

• 대한산업공학회지
• /
• 제39권2호
• /
• pp.109-118
• /
• 2013

We propose a method for estimating coefficients of AR (autoregressive) model which named MLPAR (Maximum Likelihood of Pearson system for Auto-Regressive model). In the present method for estimating coefficients of AR model, there is an assumption that residual or error term of the model follows the normal distribution. In common cases, we can observe that the error of AR model does not follow the normal distribution. So the normal assumption will cause decreasing prediction accuracy of AR model. In the paper, we propose the MLPAR which does not assume the normal distribution of error term. The MLPAR estimates coefficients of auto-regressive model and distribution moments of residual by using pearson distribution system and maximum likelihood estimation. Comparing proposed method to auto-regressive model, results are shown to verify improved performance of the MLPAR in terms of prediction accuracy.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
• /
• pp.85-87
• /
• 2000

In pattern classification, the Bhattacharyya distance has been used as a class separability measure and provides useful information for feature selection and extraction. In this paper, we propose a method to predict the classification error for multimodal data based on the Bhattacharyya distance. In our approach, we first approximate the pdf of multimodal distribution with a Gaussian mixture model and find the bhattacharyya distance and classification error. Exprimental results showed that there is a strong relationship between the Bhattacharyya distance and the classification error for multimodal data.

• Journal of the Korean Data and Information Science Society
• /
• 제13권2호
• /
• pp.1-10
• /
• 2002

A Bayes estimator of the scale parameter in an exponential distribution will be considered by a LINEX error, then the risk of the Bayes estimator using a LINEX loss will be compared with that of a Bayes estimator using a square error.

• 지구물리
• /
• 제5권2호
• /
• pp.131-142
• /
• 2002

일반적으로 지자기 전달함수는 관측치와 예측치의 차이를 최소화하는 관점에서 해가 추정된다. 오차의 구조가 가우스 분포를 따르면 최소자승 추정이 최적의 추정이지만, 그렇지 않은 경우 전달 함수 추정을 심각하게 왜곡시킬 수 있으므로 오차 구조에 대한 정보가 요구된다. 본 연구에서는 Q-Q plot을 이용한 오차 구조으 검증을 통하여 실제 오차 구조에 대한 정보를 획득하였고 가우스 분포 가정을 벗어나는 오차 구조에 대해 외치(outlier)에 의한 영향을 최소로 하며 해를 추정하는 로버스트 추정(regression M-estimate)을 적용하였다. 오차가 가우스 분포를 따르는 경우, 최소자승 추정과 로버스트 추정은 유사한 결과를 나타내나, 오차가 가우스 분포를 벗어나는 경우 로버스트 추정이 최소자승 추정보다 부드러운 결과를 나타냄을 확인하였다.

• 전자공학회논문지B
• /
• 제30B권12호
• /
• pp.1-11
• /
• 1993

This paper concentrates on models useful for analyzing the error performance of ML(Maximum Likelihood) estimators of a single unknown signal parameter: that is the error intensity model. We first develop the point process representation for the estimation error and the conditional distribution of the estimator as well as the distribution of error candidate point process. Then the error intensity function is defined as the probability dessity of the estimate and the general form of the error intensity function is derived. We then develop several intensity models depending on the way we choose the candidate error locations. For each case, we compute the explicit form of the intensity function and discuss the trade-off among models as well as the extendability to the case of multiple parameter estimation.

• 품질경영학회지
• /
• 제29권3호
• /
• pp.66-78
• /
• 2001

This paper deals with problem of determining process target value under automated visual inspection(AVI) system. Three independent error sources - digitizing error, illumination error, and positional error - which have a close relationship with the performance of the AVI system, are considered. Assuming that digitizing error is uniformly or normally distributed and illumination and positional errors are normally distributed, respectively, the distribution function for the error of measured lengths is derived when the length of a product is measured by the AVI system. Then, Optimal target values under two error models of AVI system are obtained by minimizing the total expected cost function which consists of give away, rework and penalty cost. To validate two process setting models, AVI system for drinks filling process is made up and test results are discussed.

• 한국기계가공학회지
• /
• 제11권3호
• /
• pp.116-121
• /
• 2012

In recent years, world is faced with a transportation energy dilemma, and the transportation is dependent on a single fuel - petroleum. However, Hybrid Electric Vehicle(HEV) technology holds more advantages to reduce the demand for petroleum in the transportation by efficiency improvements of petroleum consumption. Therefore, there is a trend that lower gear noise levels are demanded in HEV for drivers to avoid annoyance and fatigue during operation. And meshing transmission error(T.E.) is the excitation that leads to the tonal noise known as gear whine, and radiated gear whine is also the dominant source of noise in the whole gearbox. This paper presents a method for the analysis of gear tooth profile and lead modification, and the predictions of transmission error and load distribution are shown under one loaded torque for the 1st gear pair of HEV gearbox. The test is also obtained before tooth micro-modification under the torque. At last, the appropriate tooth modification is used to minimize the transmission error and load distribution under the loaded torque. It is a good approach which the simulated result is used to improve the design in order to minimize the radiation gear whine noise.