• Title/Summary/Keyword: Mahalanobis-Distance

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Predictive Maintenance of the Robot Trouble Using the Machine Learning Method (Machine Learning기법을 이용한 Robot 이상 예지 보전)

  • Choi, Jae Sung
    • Journal of the Semiconductor & Display Technology
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    • v.19 no.1
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    • pp.1-5
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    • 2020
  • In this paper, a predictive maintenance of the robot trouble using the machine learning method, so called MT(Mahalanobis Taguchi), was studied. Especially, 'MD(Mahalanobis Distance)' was used to compare the robot arm motion difference between before the maintenance(bearing change) and after the maintenance. 6-axies vibration sensor was used to detect the vibration sensing during the motion of the robot arm. The results of the comparison, MD value of the arm motions of the after the maintenance(bearing change) was much lower and stable compared to MD value of the arm motions of the before the maintenance. MD value well distinguished the fine difference of the arm vibration of the robot. The superior performance of the MT method applied to the prediction of the robot trouble was verified by this experiments.

Selecting Optimal Design Condition Based on Automobile Brake Feeling Using Mahalanobis Taguchi System (Mahalanobis Taguchi System을 이용한 자동차 브레이크 성능 만족도를 고려한 설계조건 선정에 관한 연구)

  • Hong, Jung-Eui;Kwon, Hong-Kyu
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.30 no.1
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    • pp.41-47
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    • 2007
  • Mahalanobis Taguchi-System (MTS) is a pattern information technology, which has been used in different diagnostic ap plications to make quantitative decisions by constructing a multivariate system using data analytic methods without any as sumption regarding statistical distribution. MTS performs Taguchi's fractional factorial design based on the Mahalanobis distance as a performance metric In this work, MTS used for analyzing automotive brake feeling system, which measured as a brake feel index (BFI) from 9 attributes. The automobile which has a good BFI score treated as a normal group for constructing Mahalanobis space. The results of this research show that two attributes (Pre load & Max deceleration) have a minus gain value and can be removed from further analysis. The difference of MD value between using all 9 attributes and just using significant attribute compared.

Application of Mahalanobis Taguchi System for Analysis of Multivariate System (Mahalanobis Taguchi System을 이용한 다변량 시스템의 해석에 관한 연구)

  • Hong, Jeong-Eui;Kim, Yong-Beom
    • Proceedings of the Safety Management and Science Conference
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    • 2005.11a
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    • pp.300-310
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    • 2005
  • Mahalanobis Taguchi System (MTS) is developed by Genishi Taguchi as a part of his quality engineering methodology. The basic idea of Taguchi's quality engineering is looking for the way of effectiveness of analyzing multivariate system. In the MTS, with the standardized variables of healthy normal data, Mahalanobis Distance(MD) calculated and that can be discriminate between normal and abnormal objects. If this discrimination process is successful, next step is optimization which is try to reduce number of attributes by neglecting less effective attributes to MD. Orthogonal Array (OA) and Signal to Noise ratio (S/N) are used to evaluate the amount contribution of each attribute to the MD. Wisconsin Breast Cancer study, from machining learning repository at University of California at Irvine, used for examining the discriminant ability of MTS.

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Optimal Design of Injection Molding Process using the Mahalanobis Taguchi System (Mahalanobis Taguchi System을 이용한 사출 공정의 최적설계)

  • Kim, Kyung-Mo;Park, Jong-Cheon
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.16 no.1
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    • pp.1-8
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    • 2017
  • Warpage is a major defect frequently found in the injection molding process, and the reduction of warpage is a very challenging problem because of the uncontrollable factors, such as variations in the process parameters. Without any countermeasure against these noises, attempts to reduce the defects often lead to failure. In this research, a new robust design methodology, based on the Mahalanobis Taguchi System (MTS) to reduce warpage, is presented. The MTS performs the orthogonal array experiments and uses the signal-to-noise (SN) ratio of the Mahalanobis distance as a performance metric. The validity of the proposed method is illustrated through an optimal design of the injection molding process of a CPU base plate.

Selecting Optimal Design Condition based on Automobile Ride Satisfaction Using Mahalanobis Taguchi System (Mahalanobis Taguchi System을 이용한 자동차 승차감 만족도를 고려한 설계조건 선정에 관한 연구)

  • Hong, Jung-Eui
    • Proceedings of the Safety Management and Science Conference
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    • 2009.11a
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    • pp.99-107
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    • 2009
  • Mahalanobis Taguchi-System (MTS) has been used in different diagnostic applications to make quantitative decisions by constructing a multivariate system using data analytic methods without any assumption regarding statistical distribution. MTS performs Taguchi's fractional factorial design based on the Mahahlanobis distance as a performance metric. In this study, MTS used for analyzing automotive ride satisfaction, which measured as a CSR(Customer Satisfaction Rating). The automobile which has a good CSR score treated as a normal group for constructing Mahalanobis space. The results of this research show that two attribute (Impact Hardness and Memory Shake) have a minus gain value and can be removed from further analysis. With the linear regression model, the difference of CSR between using all 6 attributes and just using significant 4 attributes compared.

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Exponential Probability Clustering

  • Yuxi, Hou;Park, Cheol-Hoon
    • Proceedings of the IEEK Conference
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    • 2008.06a
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    • pp.671-672
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    • 2008
  • K-means is a popular one in clustering algorithms, and it minimizes the mutual euclidean distance among the sample points. But K-means has some demerits, such as depending on initial condition, unsupervised learning and local optimum. However mahalanobis distancecan deal this case well. In this paper, the author proposed a new clustering algorithm, named exponential probability clustering, which applied Mahalanobis distance into K-means clustering. This new clustering does possess not only the probability interpretation, but also clustering merits. Finally, the simulation results also demonstrate its good performance compared to K-means algorithm.

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Digitalization System of Historical Hanja Documents using Mahalanobis Distance-based Rejection

  • Kim, Min-Soo;Kim, Jin-Hyung
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.2
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    • pp.313-325
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    • 2005
  • In Korea, there exists a large corpus of handwritten historical documents that serve as a valuable resource. Most of them are hand-written by the King's chroniclers and secretaries. Recently, the historical archives of Lee dynasty have been digitalized. Since it is extremely difficult to utilize conventional OCR system, most of the processes have been performed manually. In this paper, we propose OCR-based digitalization system using Mahalanobis distance-based rejection and interface for eye inspection about historical Hanja documents. Compared with our previous work, experimental results show that the proposed system can help enhancing the overall efficiency of the process.

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Statistical Consideration on the Similarity in Dissolution Profile of Two Fast Releasing Tablets (속용성 정제간의 용출유사성에 대한 통계학적 고찰)

  • Cho, Jung-Hwan;Lee, Se-Hee;Kim, Hee-Sun;Oh, Seaung-Youl
    • Journal of Pharmaceutical Investigation
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    • v.30 no.2
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    • pp.85-91
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    • 2000
  • We have studied the dissolution kinetics of two fast releasing tablets in four media, and the similarity of dissolution profiles was compared using 3 methods. Two of the methods were introduced from statistical algorithm of distance methods, which are maximum distance and Mahalanobis distance. The dissolution kinetics were also analysed using FDA method for similarity evaluation, and the results were compared with those obtained using the distance methods.

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Fuzzy c-Means Clustering Algorithm with Pseudo Mahalanobis Distances

  • ICHIHASHI, Hidetomo;OHUE, Masayuki;MIYOSHI, Tetsuya
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.148-152
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    • 1998
  • Gustafson and Kessel proposed a modified fuzzy c-Means algorithm based of the Mahalanobis distance. Though the algorithm appears more natural through the use of a fuzzy covariance matrix, it needs to calculate determinants and inverses of the c-fuzzy scatter matrices. This paper proposes a fuzzy clustering algorithm using pseudo mahalanobis distance, which is more easy to use and flexible than the Gustafson and Kessel's fuzzy c-Means.

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Defect Detection of ‘Fuji’ Apple using NIR Imaging(I) -Optical characteristics of defects and selection of significant wavelelength- (근적외선 영상을 이용한 후지사과의 결점 검출에 관한 연구 (I) -결점의 광학적 특성 구명 및 유의파장 선정-)

  • 이수희;노상하
    • Journal of Biosystems Engineering
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    • v.26 no.2
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    • pp.169-176
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    • 2001
  • Defect of apple was depreciated the product value and causes storage disease seriously. To detect the defect of ‘Fuji’apple with machine vision system, the optical characteristics of defect should be investigated. In this research, absorbance spectra of defect were acquired by spectrophotometer in the range of visible and NIR region(400∼1,100nm) and L*a*b* color values were also acquired by colorimeter. NIR machine vision system was constructed with B&W camera, frame grabber, 16 tungsten-halogen lamps, variable focal length lens and NIR bandpass filter which was mounted to lens outward. Average gray values of defect at 15 NIR wavelength were acquired and the significant NIR wavelength was selected by comparing Mahalanobis distance between sound and defective apple. As the result of Mahalanobis distance analysis, the significant wavelength to discriminate the defectives in ‘Fuji’apple were found to be 720nm for scab and 970nm for bruise and cuts and 920nm was also effective regardless of defective types.

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