• Title/Summary/Keyword: dual detection

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A Micro-defect Detection of Cold Rolled Steel (냉연 강판의 미세 결함 검출 기술)

  • Yun, Jong Pil
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.4
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    • pp.247-252
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    • 2016
  • In this paper, we propose a new defect detection technology for micro-defect on the surface of steel products. Due to depth and size of microscopic defect, slop of surface and vibration of strip, the conventional optical method cannot guarantee the detection performance. To solve the above-mentioned problems and increase signal to noise ratio, a novel retro-schlieren method that consists of retro reflector and knife edge is proposed. Moreover dual switching lighting method is also applied to distinguish uneven micro defects and surface noise. In proposed method, defective regions are represented by a black and white pattern. This pattern is detected by a defect detection algorithm with Gabor filter. Experimental results by simulator for sample defects of cold rolled steel show that the proposed method is effective.

On the Simulation and Performance Evaluation of the DTMT Signal Detection Algorithm Using MG Algorithm (MG를 이용한 DTMF 신호검출 알고리즘의 시뮬레이션 및 성능 평가)

  • 윤달환;임재탁
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.29B no.11
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    • pp.65-72
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    • 1992
  • The economical detection of dual-tone multifrequency(DTMF) signals is a important when developing cost-effective telecommunication equipment. This paper propose that the modified M-channel Goertzel algorithm can reduces the real-time processing and memory waste. By using this M. G. algorithm, it will compare and evaluate to the performance of the digital DTMF receivers using the G. A.

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Dual-band Monopulse Receiver for Tracking Radar (추적 레이다용 Dual-band 모노펄스 수신기)

  • Yang Seong-Uk;Park Dong-Min;Na Young-Jin
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.17 no.8 s.111
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    • pp.767-772
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    • 2006
  • The receiver of this paper is Dual-band monopulse type for prototype of tracking radar. Localization of radar technology is an issue of SamsungThales and go into development. Dual-band radar in comparison with Single-band radar requires higher cost and power consumption but there are many advantages of dealing with jamming, detection range, image signal rejection, cloud-rain influence, clutter, resolution. The receiver is comprised of X-band RF head module, Ka-band RF head module and common IF module. Each signal of X-band and Ka-band is selected by the switch in If module. Phase shifter in IF module of local stage controls the phase of sum, azimuth, elevation channel. In the test result, gain is $40{\pm}3 dB$, isolation of transmitter/receiver is 39 dBc, dynamic range is 110 dB and noise figure of each channel is 4.5dB and 6.9dB.

A Study of a Dual-Electromagnetic Sensor for Automatic Weld Seam Tracking (용접선 자동추적을 위한 이중 전자기센서의 개발에 관한 연구)

  • 신준호;김재응
    • Journal of Welding and Joining
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    • v.18 no.4
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    • pp.70-75
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    • 2000
  • The weld seam tracking system for arc welding process uses various kinds of sensors such as arc sensor, vision sensor, laser displacement and so on. Among the variety of sensors available, electro-magnetic sensor is one of the most useful methods especially in sheet metal butt-joint arc welding, primarily because it is hardly affected by the intense arc light and fume generated during the welding process, and also by the surface condition of weldments. In this study, a dual-electromagnetic sensor, which utilizes the induced current variation in the sensing coil due to the eddy current variation of the metal near the sensor, was developed for arc welding of sheet metal butt-joints. The dual-electromagnetic sensor thus detects the offset displacement of weld line from the center of sensor head even though there's no clearance in the joint. A set of design variables of the sensor were determined for the maximum sensing capability through the repeated experiments. Seam tracking is performed by correcting the position of sensor to the amount of offset displacement every sampling period. From the experimental results, the developed sensor showed the excellent capability of weld seam detection when the sensor to workpiece distance is near less than 5 mm, and it was revealed that the system has excellent seam tracking ability for the butt-joint of sheet metal.

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A Study on a Dual Electromagnetic Sensor System for Weld Seam Tracking of I-Butt Joints

  • Kim, J.-W.;Shin, J.-H.
    • International Journal of Korean Welding Society
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    • v.2 no.2
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    • pp.51-56
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    • 2002
  • The weld seam tracking system for arc welding process uses various kinds of sensors such as arc sensor, vision sensor, laser displacement sensor and so on. Among the variety of sensors available, electro-magnetic sensor is one of the most useful methods especially in sheet metal butt-joint arc welding, primarily because it is hardly affected by the intense arc light and fume generated during the welding process, and also by the surface condition of weldments. In this study, a dual-electromagnetic sensor, which utilizes the induced current variation in the sensing coil due to the eddy current variation of the metal near the sensor, was developed for arc welding of sheet metal I-butt joints. The dual-electromagnetic sensor thus detects the offset displacement of weld line from the center of sensor head even though there's no clearance in the joint. A set of design variables of the sensor was determined far the maximum sensing capability through the repeated experiments. Seam tracking is performed by correcting the position of sensor to the amount of offset displacement every sampling period. From the experimental results, the developed sensor showed the excellent capability of weld seam detection when the sensor to workpiece distance is near less than 5 ㎜, and it was revealed that the system has excellent seam tracking ability for the I-butt joint of sheet metal.

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Development of Vehicle Classification Method using Discriminant Function Based on Detection of Dual Tire (주행차량의 복륜 여부 판정을 통한 차종분류 방안)

  • Oh, Jusam
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.30 no.1D
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    • pp.45-51
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    • 2010
  • Traffic volume is essential data for traffic control or maintenance and rehabilitation planning. The volume especially with respect to the type of vehicles can facilitate to those road operations. In this research, a method for vehicle classification was developed using skewed sensors which can generate traffic signatures. In order to characterize vehicle types, the method investigates whether the second axle of each vehicle consists of dual tires. The presence of dual tire is determined by the discriminate function obtained from discriminant analysis. The validation using 1,878 vehicles recorded from a highway using a CCTV camera indicated significantly accurate results: 96.92% for class 1, 82.91% for class 3 and 79.13% for class 4.

Hybrid Fault Detection and Isolation Techniques for Aircraft Inertial Measurement Sensors

  • Kim, Seung-Keun;Jung, In-Sung;Kim, You-Dan
    • International Journal of Aeronautical and Space Sciences
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    • v.7 no.1
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    • pp.73-83
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    • 2006
  • In this paper, a redundancy management system for aircraft is studied, and fault detection and isolation algorithms of inertial sensor system are proposed. Contrary to the conventional aircraft systems, UAV system cannot allow triple or quadruple hardware redundancy due to the limitations on space and weight. In the UAV system with dual sensors, it is very difficult to identify the faulty sensor. Also, conventional fault detection and isolation (FDI) method cannot isolate multiple faults in a triple redundancy system. In this paper, two FDI techniques are proposed. First, hardware based FDI technique is proposed, which combines a parity equation approach with a wavelet based technique. Second, analytic FDI technique based on the Kalman filter is proposed, which is a model-based FDI method utilizing the threshold value and the confirmation time. To provide the reference value for detecting the fault, residuals are calculated using the extended Kalman filter. To verify the effectiveness of the proposed FDI methods, numerical simulations are performed.

Anomaly-based Alzheimer's disease detection using entropy-based probability Positron Emission Tomography images

  • Husnu Baris Baydargil;Jangsik Park;Ibrahim Furkan Ince
    • ETRI Journal
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    • v.46 no.3
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    • pp.513-525
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    • 2024
  • Deep neural networks trained on labeled medical data face major challenges owing to the economic costs of data acquisition through expensive medical imaging devices, expert labor for data annotation, and large datasets to achieve optimal model performance. The heterogeneity of diseases, such as Alzheimer's disease, further complicates deep learning because the test cases may substantially differ from the training data, possibly increasing the rate of false positives. We propose a reconstruction-based self-supervised anomaly detection model to overcome these challenges. It has a dual-subnetwork encoder that enhances feature encoding augmented by skip connections to the decoder for improving the gradient flow. The novel encoder captures local and global features to improve image reconstruction. In addition, we introduce an entropy-based image conversion method. Extensive evaluations show that the proposed model outperforms benchmark models in anomaly detection and classification using an encoder. The supervised and unsupervised models show improved performances when trained with data preprocessed using the proposed image conversion method.

A Study on Detection of Cutting Tool Fracture by Dual Signal Measurements (이중신호에 의한 공구파손 검출에 관한 연구)

  • 윤재웅;양민양;박화영
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.16 no.4
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    • pp.707-722
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    • 1992
  • Fracture of a cutting tool is one of the most serious problems in machining systems. Therefore, several methods have been proposed so far to detect cutting tool fracture. However, most of them have some problems from the viewpoint of practical applications. In this study, the feasibility of using acoustic emission and cutting force signals for the detection of massive tool breakages as well as small fracture of cutting tools were investigated. Turning experiments were performed using conventional carbide inset tools under realistic cutting conditions and the SM45C steel and heat treated SM45C steel were used as a workpiece. And the sensitivities of the AE and cutting force signals to the fracture of cutting tools were illustrated. Finally, a detection algortithm for the fracture of cutting tools was developed through the analysis of these dual signals in the several types of tool fracture.

Algorithm for Switch Open Fault Detection of Asymmetric 6-phase PMSM Based on Stationary Reference Frame dq-axis Currents (비대칭 6상 영구자석 동기 전동기의 정지 좌표계 DQ축 전류를 이용한 스위치 개방 고장 검출 기법)

  • Lee, Won-Seok;Kim, Han-Eol;Hwang, Seon-Hwan;Lee, Ki-Chang;Park, Jong-Won
    • Journal of IKEEE
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    • v.26 no.2
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    • pp.265-270
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    • 2022
  • This paper proposes the detection algorithm for switch open fault of asymmetric 6-phase PMSM based on stationary reference frame dq-axis currents. In this paper, target motor has an asymmetric structure in which two upper three windings have an electrical phase difference of 30° and a neutral point is separated. As a result, dual 3-phase PWM inverters and the detection techniques due to open failures of switch are definitely required. In this paper, the dual dq-axis current control method is used for driving the asymmetric 6-phase PMSM and the open fault switch should be detected by using variable all pass filter and low pass filter in order to detect the current amplitude. The effectiveness and usefulness of the proposed method is verified by several experiments.