• 대한산업공학회지
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• 제30권2호
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• pp.84-92
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• 2004

A process control procedure is proposed when 100% inspection is performed in a process with excellent capability. Only the incomplete measurement data is assumed to be available, i.e. the specific measurement value of the quality characteristic is not available for each item but it can be determined to be smaller or larger than any prescribed value. In the suggested model, a signal limit is introduced to determine whether the process under study is in control or not. If the quality characteristic of an incoming item exceeds the upper signal or the lower signal limit, the process is determined to be stopped or not by comparing the number of consecutively accepted items with a predetermined threshold number. The procedure is designed based on the type I and II errors. The performance of the model is evaluated by the expected number of items produced under the in-control and out-of-control states until the process is stopped.

• Smart Structures and Systems
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• 제10권4_5호
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• pp.471-483
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• 2012

In this paper, the structural health monitoring (SHM) benchmark problem of the Canton tower is studied. Based on the field monitoring data from the 20 accelerometers deployed on the tower, some modal frequencies and mode shapes at measured degrees of freedom of the tower are identified. Then, these identified incomplete modal data are used to update the reduced finite element (FE) model of the tower by a novel algorithm. The proposed algorithm avoids the problem of subjective selection of updated parameters and directly updates model stiffness matrix without model reduction or modal expansion approach. Only the eigenvalues and eigenvectors of the normal finite element models corresponding to the measured modes are needed in the computation procedures. The updated model not only possesses the measured modal frequencies and mode shapes but also preserves the modal frequencies and modes shapes in their normal values for the unobserved modes. Updating results including the natural frequencies and mode shapes are compared with the experimental ones to evaluate the proposed algorithm. Also, dynamic responses estimated from the updated FE model using remote senor locations are compared with the measurement ones to validate the convergence of the updated model.

• 한국IT서비스학회지
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• 제11권1호
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• pp.239-246
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• 2012

The user increases around the WiBro and in which the mobile broad band service is the wireless internet base technology HSDPA, that is the cellular phone foundation technique, and moreover the issue about the user effective quality guarantee emerges but the quality control of the wireless network is the incomplete actual condition. Therefore, the reliability verification according to the development of the system for the performance measure for the continued wireless data service and it and evaluation are needed for the quality control. In this paper, the wireless data service quality measurement system was implemented with the design. The same test environment as the existing network performance measurement program was built for the reliability verification of the embodied device for measuring quality and evaluation and the cost performance was performed. It could confirm that design and embodied wireless data service quality measurement system operated accurately in this paper through the quality measure result value analysis.

• 대한기계학회논문집
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• 제16권11호
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• pp.2033-2048
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• 1992

본 연구에서는 탄성체 구조물로 형성된 응용에서 좀더 공통된 상황에 관한 것 이다.유일한 선형해석모델의 규명에 필요한 정보제공을 위하여 충분히 넓은 진동수 범위에 걸쳐 응답을 측정하고, 구조물을 기진시키는 것은 불가능하고 비경제적이며 또 는 일반적으로 바람직하지 못할 것으로 생각된다.

• 한국지형학회지
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• 제27권2호
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• pp.19-28
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• 2020

Grain size analysis is the most basic procedure for identifying the origin, transport and sedimentation processes of sediments, and is widely used in geomorphology and sedimentology. Traditionally, grain size was determined by a sieve-pippette method, but the use of automated analyzers is increasing in recent years. These analyzers have many advantages over traditional techniques, but the measurement results are not always the same. It is still difficult to solve the pretreatment problem such as incomplete diffusion and residual organic matter, and inappropriate results may be obtained. This study compared image-based grain size analysis and sieve analysis to verify its statistical reliability, and conducted experiments to enhance the measurement accuracy using shape parameters. The results showed that the image-based analysis overestimated the grain size of sand dunes by about 7% compared to the sieve analysis, but the two measurements were not statistically different. In addition, by using shape parameters, such as aspect ratio, sphericity, and convexity, improved statistics were obtained compared to the original data. Using the morphological properties of the individual grains is a complementary method to the incomplete pretreatment of the grain size analysis process, and at the same time, it will contribute to improving the accuracy and reliability of the results.

• 한국소음진동공학회:학술대회논문집
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• 한국소음진동공학회 1998년도 춘계학술대회논문집; 용평리조트 타워콘도, 21-22 May 1998
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• pp.244-249
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• 1998

The present paper improves the direct identification scheme based upon the equation error formulation with incomplete modal data. First, an indirect estimation technique is considered for estimating unmeasured elements of latent vectors by the combined use of a model and measured incomplete eigen vectors. It is used for estimating the other elements of eigen vectors, which are essential for identification but not available. Next an index is introduced here to indicate the quality of estimation with respect to the mode and the measured positions. A sensitivity formula for eigenvalues with respect to the unknown joint coefficient is also derived to select the modes appropriate for identification. An identification strategy is suggested to meet with practical problems with the help of the index and sensitivity formula. The index and the sensitivity are proved to be useful for selecting measurement positions and modes appropriate for identification A comprehensive simulation study is performed to test the proposed method.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1992년도 춘계학술대회 논문집
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• pp.279-284
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• 1992

This paper presents the theoretical development and qualitiative evaluation of a new concept in the mathematical modeling of dynamicstructures. We use both test data and analytical approximations to identify the parameters of an incomplete model. The model has the capability of prodicting the response of the points of interest on the structure over the frequency range of interest and can be used to predict the changes in natural frequencies and normal modes due to structural changes. The theory was tested by running simulated tests on a relatively simple structure, identifying the parameters of the incomplete model, and using this model to predict the effects on frequency and mode shapes of several mass and stiffness changes. The conditions of the test were varied by selecting different numbers of points of meansurement, varying the frequency range, and by including assumed measurement error. It is recommended that the theroetical development be continued and that applications to more complex structures be carried out in order todevelop a better understanding of the limitations and capabilites of the method. A successful, more definitive evaluation could lead to immediate practical applications.

• 한국실천공학교육학회논문지
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• 제3권1호
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• pp.45-50
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• 2011

유한요소 해석(FEA: finite element analysis)의 발달로 복잡한 기계나 자동차 및 구조물에 대해서도 상세한 진동해석을 할 수 있게 되었다. 그러나, 복잡한 구조물을 정확하게 모형화하기 어렵고, 특히 접합부의 강성과 감쇠 특성을 알기 어렵고, 복잡한 형상을 단순화하는 과정에서 발생하는 오차 등의 이유로 유한요소해석 결과는 부정확할 수 있다. 반면에 실제 구조물의 실험 데이터로부터 추출한 실험적 모드해석(modal testing) 결과는 상세하지는 않지만 정확하다고 볼 수 있다. 그러나 실험 결과가 구조물의 진동 특성을 정확하게 나타낸다는 가정은 여러 가지 측정 오차로 인하여 정확하지 않을 수 있다. 이 논문에서는 실험적 모드해석의 기본이 되는 FRF(frequency response function; 주파수 응답함수)의 측정에 영향을 미치는 오차들을 측정 오차와 신호처리 오차로 구분하여 각각에 대해 세밀히 살펴보고, 그러한 오차들을 감소함으로써 보다 정확한 FRF를 구하는 방법에 대해서 고찰해보았다.

• Advances in nano research
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• 제14권3호
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• pp.225-234
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• 2023

In this study, we aim to use big data resources and statistical analysis to obtain a reliable instruction to reach high-quality and high yield agricultural yields. In this regard, soil type data, raining and temperature data as well as wheat production in each year are collected for a specific region. Using statistical methodology, the acquired data was cleaned to remove incomplete and defective data. Afterwards, using several classification methods in machine learning we tried to distinguish between different factors and their influence on the final crop yields. Comparing the proposed models' prediction using statistical quantities correlation factor and mean squared error between predicted values of the crop yield and actual values the efficacy of machine learning methods is discussed. The results of the analysis show high accuracy of machine learning methods in the prediction of the crop yields. Moreover, it is indicated that the random forest (RF) classification approach provides best results among other classification methods utilized in this study.

• Structural Engineering and Mechanics
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• 제68권1호
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• pp.39-51
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• 2018

In this study, a frequency domain model updating method is presented using power spectral density (PSD) data. It uses the sensitivity of PSD function with respect to the unknown structural parameters through a decomposed form of transfer function. The stiffness parameters are captured with high accuracy through solving the sensitivity equations utilizing the least square approach. Using numerically noise polluted data, the model updating results of a truss model prove robustness of the method against measurement and mass modelling errors. Results prove the capabilities of the method for parameter estimation using highly noise polluted data of low ranges of excitation frequency.