• Title/Summary/Keyword: Error Inspection Algorithm

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Development of surface defect inspection algorithms for cold mill strip (냉연 표면흠 검사 알고리듬 개발에 관한 연구)

  • Kim, Kyoung-Min;Park, Gwi-Tae;Park, Joong-Jo;Lee, Jong-Hak;Jung, Jin-Yang;Lee, Joo-Kang
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.2
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    • pp.179-186
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    • 1997
  • In this paper we suggest a development of surface defect inspection algorithms for cold mill strip. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment and co-occurrence matrix features are calculated. For the defect classification, multilayer neural network is used. The proposed algorithm showed 15% error rate.

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The Quality Assurance Technique of Resistance Spot Welding Pieces using Neuro-Fuzzy Algorithm (뉴로-퍼지 알고리즘을 이용한 점용접재의 강도추론 기술)

  • Kim, Joo-Seok;Choo, Youn-Joon;Lee, Sang-Ryong
    • Journal of the Korean Society for Precision Engineering
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    • v.16 no.10
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    • pp.141-151
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    • 1999
  • The resistance Spot Welding is widely used in the field of assembling the plates. However we don't still have any satisfactory solution, which is non-destructive quality evaluation in real-time or on-line, against it. Moreover, even though the rate of welding under the condition of expulsion has been high until now, quality control of welding against expulsion hasn't still been established. In this paper, it was proposed on the quality assurance technique of resistance spot welding pieces using Neuro-Fuzzy algorithm. Four parameters from electrode separation signal in the case of non-expulsion, and dynamic resistance patterns in the case of expulsion are selected as fuzzy input parameters. The parameters consist of Fuzzy Inference System are determined through Neuro-Learning algorithm. And then, fuzzy Inference System is constructed. It was confirmed that the fuzzy inference values of strength have within ${\pm}$4% error specimen in comparison with real strength for the total strength range, and the specimen percent having within ${\pm}$1% error was 88.8%. According to KS(Korean Industrial Standard), tensile-shear strength limit for electric coated of zinc is 400kgf/mm2. Judging to the quality of welding is good or bad, according to this criterion and the results of inference, the probability of misjudgement that good quality is valuated into poor one was 0.43%, on contrary it was 2.59%. Finally, the proposed Neuro-Fuzzy Inference System can infer the tensile-shear strength of resistance spot welding pieces with high performance for all cases-non-expulsion and expulsion. And On-Line Welding Quality Inspection System will be realized sooner or later.

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Determination of Optimal Locations for Measuring Displacements to Adjust Cable Tension Forces of Cable-Stayed Bridges (사장교 시공 중 케이블 장력 보정을 위한 최적 변위계측 위치 결정)

  • Shin, Soobong;Lee, Jung-Yong;Kim, Jae-Cheon;Jung, Kil-Je
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.13 no.2 s.54
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    • pp.129-136
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    • 2009
  • The paper presents an algorithm of selecting optimal locations for measuring displacements(OLD) to adjust cable tension forces during the construction of cable-stayed bridges. The rank for optimal locations can be determined from the effective independence distribution vectors(EIDV) that are computed from the Fisher Information Matrices(FIM) formulated with the displacement sensitivities. To examine the efficiency and reliability of the proposed algorithm for determining OLD, a simulation study on a cable-stayed bridge has been carried out. The results using FIM formulated with displacements are compared with those using FIM with displacement sensitivities through the simulation study. The effects of measurement noise and error in cable length on the adjustment of cable tension forces are evaluated statistically by applying the Monte Carlo scheme.

Measurement and Correction of PCB Alignment Error for Screen Printer Using Machine Vision (1) (머신비전을 이용한 PCB 스크린인쇄기의 정렬오차측정 및 위치보정 (1))

  • 신동원
    • Journal of the Korean Society for Precision Engineering
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    • v.20 no.6
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    • pp.88-95
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    • 2003
  • This paper presents the measurement and correction method of PCB alignment errors for PCB screen printer. Electronic equipment is getting smaller and yet must satisfy high performance standard. Therefore, there is a great demand for PCB with high density. However conventional PCB screen printer doesn't have enough accuracy to accommodate the demand fur high-resolution circuit pattern and high-density mounting capacity of electronic chips. It is because the alignment errors of PCB occur when it is loaded to the screen printer. Therefore, this study focuses on the development of the system which is able to measure and correct alignment errors with high-accuracy. An automatic optical inspection part measures the PCB alignment errors using machine vision, and the high-accuracy 3-axis stage makes correction for these errors. This system used two CCD cameras to get images of two fiducial marks of PCB. The geometrical relationship between PCB, cameras, and xy$\theta$ stage is derived, and analytical equations for alignment errors are also obtained. The unknown parameters including camera declining angles and etc. can be obtained by initialization process. Finally, the proposed algorithm is verified by experiments by using test bench.

Development of a Nuclear Steam Generator Tube Inspection/maintenance Robot

  • Shin, Ho-Cheol;Kim, Seung-Ho;Seo, Yong-Chil;Jung, Kyung-Min;Jung, Seung-Ho;Choi, Chang-Hwan
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2508-2513
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    • 2003
  • This paper presents a nuclear steam generator tube inspection/maintenance robot system. The robot assists in automatic non-destructive testing and the repair of nuclear steam generator tubes welded into a thick tube sheet that caps a hemispherical or quarter-sphere plenum which is a high-radiation area. For easy carriage and installation, the robot system consists of three separable parts: a manipulator, a water-chamber entering and leaving device for the manipulator and a manipulator base pose adjusting device. A software program to control and manage the robotic system has been developed on the NT based OS to increase the usability. The software program provides a robot installation function, a robot calibration function, a managing and arranging function for the eddy-current test, a real time 3-D graphic simulation function which offers remote reality to operators and so on. The image information acquired from the camera attached to the end-effecter is used to calibrate the end-effecter pose error and the time-delayed control algorithm is applied to calculate the optimal PID gain of the position controller. The developed robotic system has been tested in the Ulchin NPP type steam generator mockup in a laboratory.

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Stable lateral-shearing interferometer for in-line inspection of aspheric pick-up lenses (생산 라인에서의 광 Pick-up용 비구면 대물 렌즈 측정을 위한 안정된 층밀리기 간섭계)

  • 조우종;김병창;김승우
    • Korean Journal of Optics and Photonics
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    • v.8 no.3
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    • pp.189-193
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    • 1997
  • Aspheric pick-up lenses are increasingly used in consumer products such as computer and multimedia, as their mass production has become possible owing to the injection molding process. However still much work needs to be done for more effective manufacture of aspheric lenses, one area of which is the in-line inspection of produced lenses. In this paper, we present a lateral-shearing interferometer that has specially been designed to have a high immunity to external vibration and atmospheric disturbance. The interferometer comprises four prisms. They are directly attached to each other using an immersion oil so that relative sliding motions between the prisms are allowed. Their relative displacement can readily generate necessary lateral-shearing and phase-shifting to determine the wavefront of the beam collimated by the lens under inspection. A special phase-measuring algorithm of arbitrary-bucket is adopted to compensate the phase-shifting error caused by the thickness reduction in the immersion oil. Zernike polynomial fitting has done for determinating quantitative aberration of aspheric pick-up lenses. The interferometer built in this work is robust to external mechanical vibration and atmospheric disturbance so that experimental results show that it has a repeatability of less than λ/100.

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Simplified Bridge Weigh-In-Motion Algorithm using Strain Response of Short Span RC T-beam Bridge with no Crossbeam installed (가로보가 없는 단지간 RC T빔교의 변형률 응답을 이용한 단순화된 BWIM (Bridge Weigh-In-Motion) 알고리즘)

  • Jeon, Jun-Chang;Hwang, Yoon Koog;Lee, Hee-Hyun
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.25 no.3
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    • pp.57-67
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    • 2021
  • A thorough administration of the arterial road network requires a continuous supply of updated and accurate information about the traffic that travels on the roads. One of the ways to effectively obtain the traffic volume and weight distribution of heavy vehicles is the BWIM technique, which is actively being studied. Unlike previous studies, this study was performed to develop a simplified Bridge Weigh-In-Motion (BWIM) algorithm that can easily estimate the axle spacing and weight of a traveling vehicle by utilizing the structural characteristics of the bridge. A short span RC T-beam bridge with no crossbeam installed was selected for the study, and then the strain response characteristics of bridge deck and girder was checked through preliminary field test. Based on the preliminary field test results, a simplified BWIM algorithm suitable for the bridge to be studied was derived. The validity and accuracy of the BWIM algorithm derived in this study were verified through field test. As a result of the verification test, the proposed BWIM algorithm can estimate the axle spacing and gross weight of the travelling vehicles with the average percent error of less than 3%.

Efficient Image Segmentation Using Morphological Watershed Algorithm (형태학적 워터쉐드 알고리즘을 이용한 효율적인 영상분할)

  • Kim, Young-Woo;Lim, Jae-Young;Lee, Won-Yeol;Kim, Se-Yun;Lim, Dong-Hoon
    • The Korean Journal of Applied Statistics
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    • v.22 no.4
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    • pp.709-721
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    • 2009
  • This paper discusses an efficient image segmentation using morphological watershed algorithm that is robust to noise. Morphological image segmentation consists of four steps: image simplification, computation of gradient image and watershed algorithm and region merging. Conventional watershed segmentation exhibits a serious weakness for over-segmentation of images. In this paper we present a morphological edge detection methods for detecting edges under noisy condition and apply our watershed algorithm to the resulting gradient images and merge regions using Kolmogorov-Smirnov test for eliminating irrelevant regions in the resulting segmented images. Experimental results are analyzed in both qualitative analysis through visual inspection and quantitative analysis with percentage error as well as computational time needed to segment images. The proposed algorithm can efficiently improve segmentation accuracy and significantly reduce the speed of computational time.

Visual Bean Inspection Using a Neural Network

  • Kim, Taeho;Yongtae Do
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2003.09a
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    • pp.644-647
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    • 2003
  • This paper describes a neural network based machine vision system designed for inspecting yellow beans in real time. The system consists of a camera. lights, a belt conveyor, air ejectors, and a computer. Beans are conveyed in four lines on a belt and their images are taken by a monochrome line scan camera when they fall down from the belt. Beans are separated easily from their background on images by back-lighting. After analyzing the image, a decision is made by a multilayer artificial neural network (ANN) trained by the error back-propagation (EBP) algorithm. We use the global mean, variance and local change of gray levels of a bean for the input nodes of the network. In an our experiment, the system designed could process about 520kg/hour.

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On-Line Sorting of Cut Roses by Color Image Processing (영상처리에 의한 장미 선별)

  • 배영환;구현모
    • Journal of Biosystems Engineering
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    • v.24 no.1
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    • pp.67-74
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    • 1999
  • A prototype cut-flower sorter was developed and tested for its performance with five varieties of roses. Support plates driven by a chain mechanism transported the roses into an image inspection chamber. Color image processing algorithms were developed to evaluate the length, thickness, and straightness of stem and color, height, and maturity of bud. The average absolute errors of the system for the measurements of stem length, stem thickness, and height of bud were 19.7 mm, 0.5 mm, and 3.8 mm, respectively. The results of classification by the sorter were compared with those of a human inspector for straightness of stem and maturity of bud. The classification error for the straightness of stem was 8.6%, when both direct image and reflected image by a mirror were analyzed. The accuracy in classifying the maturity of bud varied among the varieties, the smallest for‘Nobless’(1.5%) and the largest for‘Rote Rose’(13.5%). The time required to process a rose averaged 2.06 seconds, equivalent to the capacity of 1,600 roses per hour.

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