• Title/Summary/Keyword: MD(Mahalanobis Distance)

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Experimental Study on the Hydraulic Power Steering System Noise (유압식 동력 조향장치의 소음에 대한 실험적 연구)

  • Lee, Byung-Rim;Choi, Young-Min;You, Chung-Jun
    • Transactions of the Korean Society of Automotive Engineers
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    • v.17 no.2
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    • pp.165-170
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    • 2009
  • Pressure ripple, vibration and noise level are measured in each parts of the power steering system. MD(Mahalanobis Distance) is calculated by using MTS(Mahalanobis Taguchi System) with measured data, and noise sensitive components are selected. The components applied detail design parameters are made and data is measured. After that MD is calculated also. Mean value and SN ratio can be obtained from the MD. Effective noise reduction technique and dominant design parameters in hydraulic power steering system are introduced.

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.

A Study Evaluating Welding Quality in Pressure Vessel Using Mahalanobis Distance (마할라노비스 거리를 이용한 압력용기 용접부 용접성 평가에 관한 연구)

  • Kim, Ill Soo;Lee, Jong Pyo;Lee, Ji Hye;Jung, Sung Myoung;Kim, Young Su;Chand, Reenal Ritesh;Park, Min Ho
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.22 no.1
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    • pp.22-28
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    • 2013
  • Robotic GMA (Gas Metal Arc) welding process is one of widely acceptable metal joining process. The heat and mass inputs are coupled and transferred by the weld arc to the molten weld pool and by the molten metal that is being transferred to the weld pool. The amount and distribution of the input energy are basically controlled by the obvious and careful choices of welding process parameters in order to accomplish the optimal bead geometry and the desired quality of the weldment. To make effective use of automated and robotic GMA welding, it is imperative to predict online faults for bead geometry and welding quality with respect to welding parameters, applicable to all welding positions and covering a wide range of material thickness. MD (Mahalanobis Distance) technique was employed for investigating and modeling the GMA welding process and significance test techniques were applied for the interpretation of the experimental data. To successfully accomplish this objective, two sets of experiment were performed with different welding parameters; the welded samples from SM 490A steel flats. First, a set of weldments without any faults were generated in a number of repeated sessions in order to be used as references. The experimental results of current and voltage waveforms were used to predict the magnitude of bead geometry and welding quality, and to establish the relationships between weld process parameters and online welding faults. Statistical models developed from experimental results which can be used to quantify the welding quality with respect to process parameters in order to achieve the desired bead geometry based on weld quality criteria.

Enhancement of UAV-based Spatial Positioning Using the Triangular Center Method with Multiple GPS

  • Joo, Yongjin;Ahn, Yushin
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.37 no.5
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    • pp.379-388
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    • 2019
  • Recently, a technique for acquiring spatial information data using UAV (Unmanned Aerial Vehicle) has been greatly developed. It is a very crucial issue of the GIS (Geographic Information System) mapping system that passes way point in the unmanned airframe and finally measures the accurate image and stable localization to the desired destination. Though positioning using DGPS (Differential Global Navigation System) or RTK-GPS (Real Time Kinematic-GPS) guarantee highly accurate, they are more expensive than the construction of a single positioning system using a single GPS. In the case of a low-priced single GPS system, the stability of the positioning data deteriorates. Therefore, it is necessary to supplement the uncertainty of the absolute position data of the UAV and to improve the accuracy of the current position data economically in the operating state of the UAV. The aim of this study was to present an algorithm enhancing the stability of position data in a single GPS mode of UAV with multiple GPS. First, the arrangement of multiple GPS receivers through the center of gravity of the UAV were examined. Next, MD (Mahalanobis Distance) is applied to detect instantaneous errors of GPS data in advance and eliminate outliers to increase the accuracy of previously collected multiple GPS data. Processing procedure for multiple GPS reception data by applying the center of the triangular method were presented to improve the position accuracy. Second, UAV navigation systems integrated multiple GPS through configuration of the UAV specifications were implemented. Using the unmanned airframe equipped with multiple GPS receivers, GPS data is measured with the TCM (Triangular Center Method). In addition, UAV equipped with multiple GPS were operated in study area and locational accuracy of multiple GPS of UAV with VRS (Virtual Reference Station) GNSS surveying were compared. The result showed that the error factors are compensated, and the error range are reduced, resulting in the reliability of the corrected value. In conclusion, the result in this paper is expected to realize high-precision position estimation at low cost in UAV using multiple low-cost GPS receivers.