• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1995년도 추계학술대회 논문집
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• pp.961-964
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• 1995

For geometric accuracy in the net shape machining, the problem of tool deflection should be resolved in some fashion. In particular, this is crucial in finish cut operation where slim tools are used. The purpose of this paper is to verify the validity and effectiveness of the prediction model of the machined surface. Experimental results are presented for the cut of steel material with HSS endmill of diameter 6mm on machining center. The results shows that 1) the machining error due totool deflection is serious even in the low cutting load, 2) by using the mechanistic simulation model with experimental coefficients, the machining error was predicted with maximum prediction error of 10% which was significantly reduced to the desired level by the path modification method.

• Design & Manufacturing
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• 제17권4호
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• pp.24-32
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• 2023

In this study, we introduce research aimed at minimizing machining errors without compromising productivity by compensating for the machining errors caused by tool deformation. Our approach experimentally establishes the direct correlation between cutting depth and machining error, and creates predictive models using mathematical functions. This method allows for the prediction of compensated cutting depths to obtain the desired cutting profiles, thereby maximizing the compensation of machining errors in the cutting process.

• 한국정보통신학회논문지
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• 제17권1호
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• pp.183-189
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• 2013

본 논문에서는 영상의 방향성에 따른 적응적 예측 기법과 컨텍스트 기반 엔트로피 부호화 방법을 주요 구성요소로 한 무손실 영상 압축 방법을 제안한다. 적응적 예측 기법에서는 부호화 픽셀을 중심으로 각 방향에 대한 상관도를 분석하고, 이를 이용하여 적절한 예측 픽셀을 선택한다. 또한 예측 에러를 더욱 줄이기 위하여 주변 픽셀의 복잡도 및 방향성을 이용한 컨텍스트 모델 기반 예측 에러 보정 과정을 수행한다. 정보이론의 관점에서 조건부 엔트로피에 의해 부호화 효율이 더욱 향상된다는 점을 이용하여 본 논문에서는 엔트로피 부호화 방식으로 컨텍스트 기반 Golomb-Rice 부호화를 적용한다. 실험결과 제안한 무손실 영상 압축 방식은 다양한 영상에 대해서 기존의 저 복잡도 및 고효율의 JPEG-LS에 비해 평균 1.3%의 압축효율 향상을 나타내었고, 특히 방향성이 뚜렷한 영상에 대해서 성능이 좋음을 알 수 있다.

• 한국공작기계학회논문집
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• 제17권2호
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• pp.121-127
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• 2008

Micro end-milling has been becoming an important machining process to manufacture a number of small products such as micro-devices, bio-chips, micro-patterns and so on. Despite the importance of micro end-milling, many related researches have given grand efforts to micro end-milling phenomenon, for example, micro end-milling mechanism, cutting force modeling and machinability. This paper strongly concerned actual problem, micro tool deflection, which causes excessive machining errors on the workpiece. To solve this problem, machining error prediction method was proposed through a series of test micro cutting and analysis of their SEM images. An iterative algorithm was applied in order to obtain corrected tool path which allows reducing machining errors in spite of tool deflection. Experiments are carried out to validate the proposed approaches. In result, remarkable error reduction could be obtained.

• 한국통신학회논문지
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• 제28권4C호
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• pp.384-391
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• 2003

Blind channel identification and equalization attempt to identify the communication channel and to remove the inter-symbol interference caused by a communication channel without using any known trainning sequences. In this paper, we propose a blind adaptive channel identification and equalization algorithm with phase offset compensation for single-input multiple-output (SIMO) channel. It is based on the one-step forward multichannel linear prediction error method and can be implemented by an RLS algorithm. Phase offset problem, we use a blind adaptive algorithm called the constant modulus derotator (CMD) algorithm based on condtant modulus algorithm (CMA). Moreover, unlike many known subspace (SS) methods or cross relation (CR) methods, our proposed algorithms do not require channel order estimation. Therefore, our algorithms are robust to channel order mismatch.

• 한국정밀공학회지
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• 제30권7호
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• pp.754-761
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• 2013

Thermal displacement is an important issue in machine tool systems. During the last several decades, thermal error compensation technology has significantly reduced thermal distortion error; this success has been attributed to the development of a precise, robust thermal error model. A major advantage of using the thermal error model is instant compensation for the control variables during the modeling process. However, successful application of thermal error modeling requires correct determination of the temperature sensor placement. In this paper, a procedure for predicting thermal-mode-based thermal error is introduced. Based on this thermal analysis, temperature sensors were positioned for multiple heat-source models. The performance of the sensors based on thermal-mode error analysis, was compared with conventional methods through simulation and experiments, for the case of a slide table in a transient state. Our results show that for predicting thermal error the proposed thermal model is more accurate than the conventional model.

• 대한전자공학회논문지TC
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• 제41권10호
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• pp.45-52
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• 2004

본 논문에서는 에러 예측회로를 사용하여 연집에러 입력시 성능저하를 보완한 경판정 비터비 디코더를 제안하였다. 비터비 디코더는 최대유사복호 알고리즘을 사용하므로 랜덤에러 입력시 정정능력이 뛰어나다. 반면에 연집에러 입력시 에러 정정능력이 매우 떨어지는 단점이 있다. 제안하는 에러 예측회로는 비터비 디코더의 연집에러에 대한 에러 정정특성을 향상시키는 기능으로 비터비 디코더에 에러가 입력됨에 따라 path metric값이 증가하는 것을 이용한다. Path metric의 최대값 증가량을 이용하여 연집에러 구간을 예측, 연집에러 구간에 대한 확률 값을 줄여준다. 제안된 알고리즘을 OFDM방식의 IEEE802.11a WLAN에 적용한 비터비 디코더는 AWGN채널에서는 기존의 비터비 디코더와 동일한 성능을 유지하며, 무선 채널 환경인 다중경로 페이딩 채널에서 발생할 수 있는 연집에러에 대하여 15% 개선된 성능을 보였다.

• 전기학회논문지
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• 제58권1호
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• pp.173-180
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• 2009

It is difficult to predict non-stationary or chaotic time series which includes the drift and/or the non-linearity as well as uncertainty. To solve it, we propose an effective prediction method which adopts data preprocessing and multiple model TS fuzzy predictors combined with model selection mechanism. In data preprocessing procedure, the candidates of the optimal difference interval are determined based on the correlation analysis, and corresponding difference data sets are generated in order to use them as predictor input instead of the original ones because the difference data can stabilize the statistical characteristics of those time series and better reveals their implicit properties. Then, TS fuzzy predictors are constructed for multiple model bank, where k-means clustering algorithm is used for fuzzy partition of input space, and the least squares method is applied to parameter identification of fuzzy rules. Among the predictors in the model bank, the one which best minimizes the performance index is selected, and it is used for prediction thereafter. Finally, the error compensation procedure based on correlation analysis is added to improve the prediction accuracy. Some computer simulations are performed to verify the effectiveness of the proposed method.

• 한국정밀공학회지
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• 제20권5호
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• pp.108-115
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• 2003

This paper is concerned with the development of Internet-based robot system controlled on the remote site via the Internet. In order to draw the public attention into this exciting system, we built the simple system by which a robot is moved in response to answer for the given OX quizzes. As the primary research fer Internet-based robot control, this study focuses on the development of user-friendly interface by which a beginner achieves information for a robot on the remote site from the 3D virtual simulator and the real camera image. for the compensation of Internet time delay, position prediction simulator is implemented in the user interface.

• Journal of Electrical Engineering and Technology
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• 제3권1호
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• pp.14-19
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• 2008

The paper presents an intelligent time series model to predict uncertain electricity market price in the deregulated industry environment. Since the price of electricity in a deregulated market is very volatile, it is difficult to estimate an accurate market price using historically observed data. The parameter of an intelligent time series model is obtained based on the simultaneous perturbation stochastic approximation (SPSA). The SPSA is flexible to use in high dimensional systems. Since prediction models have their modeling error, an error compensator is developed as compensation. The SPSA based intelligent model is applied to predict the electricity market price in the Pennsylvania-New Jersey-Maryland (PJM) electricity market.