• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.571-578
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• 2018

The deteriorated pipline often causes the unexpected leakage and crack. Negligence and late maintenance leads the enormous damage for gas and water resource. This paper proposes early fault detection and diagnosis algorithm for pipeline using acoustic emission (AE) signals. Early fault detection method for pipeline compares the frequency amplitude of the spectrum to that of the spectrum in normal condition. Larger amplitude of the spectrum indicates abnormal condition. Early fault diagnosis algorithm uses support vector machines (SVM), which is trained for normal and abnormal conditions to diagnose the measured AE signal from the target pipeline. In the experiment, a pipeline testbed is constructed similarly to real industrial pipeline. Normal, 5mm cracked, 10mm holed pipelines are installed and tested in this study. The proposed fault detection and diagnosis technique is validated as an efficient approach to detect early faulty condition of pipeline.

• Proceedings of the KIEE Conference
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• 2004.11d
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• pp.53-55
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• 2004

부분방전 검출을 이용한 XLPE 케이블 진단은 중간 및 종단 접속재의 계면에 존재하는 결합을 검출할 수 있는 가장 효과적인 방법으로 제시되고 있지만 현장의 큰 노이즈로 인하여 신뢰성 있는 진단이 쉽지 않다. 하지만 국내에서 많은 연구가 이루어진 송전케이블 진단 기술을 바탕으로 배전케이블 진단에 적용하여 종단접속부에서 발생된 부분방전을 성공적으로 검출하였고 해체 조사를 통하여 결함을 검출하였다. 본 논문은 참고문헌[1]에 발표한 논문에 연결되는 논문으로 전편은 2004년 2월 부분방전 검출사례를 보고한 논문이고 본 논문에서는 8월 계획정전을 통하여 문제된 접속함을 교체한 후 해체조사를 통하여 결함을 검출한 사례보고이다.

• Journal of the Microelectronics and Packaging Society
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• v.30 no.1
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• pp.30-41
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• 2023

With the aggressive down-scaling of advanced integrated circuits (ICs), electronic packages have become the bottleneck of both reliability and performance of whole electronic systems. In order to resolve the reliability issues, Institute of Electrical and Electronics Engineers (IEEE) laid down a roadmap on fault detection and diagnosis (FDD), thrusting the digital twin: a combination of reliability physics and artificial intelligence (AI). In this paper, we especially review research works regarding the signal-based FDD approaches on the electronic packages. We also discuss the research trend of FDD utilizing AI techniques.

• Proceedings of the KIEE Conference
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• 2004.11d
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• pp.50-52
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• 2004

국내 154kV XLPE 케이블 시스템은 장기운전에 따른 열화진단 및 유지보수의 필요성이 증대되고 있다. 헌재 실선로 진단에 적용되고 있는 기술은 열화상 측정, 부분방전 검출 시스순환전류분석 및 저감기술등이 있다. 본 논문에서는 상기의 진단기술을 운전중인 154kV 실선로에 적용하여 결함을 검출한 사례를 기술하였다. 특히 부분방전 진단의 경우 접속함 내부에 존재하는 결함을 검출하여 사고를 미연에 방지한 것으로 사료된다.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.351-356
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• 1993

최근의 프로세스 공업화에 있어서 생산Line의 장치나 기계류는 점차 대형화, 고속화,연속화,복잡화되고 있다. 또한, 기계가공공업,자동차공업,기계,전자부품의 가공조립등의 생산설비는 각설비가 고도로 자동화되고 있는 실정으로 공장 전체의 유기체적인 제어 및 감독을 필요로 하고 있다. 마찬가지로 기계부품제작산업도 CNC.FMS등으로 점차 조작화,자동화됨에 따라 공작기계 장치나 기계류등의 이상이나 고장으로 생산 및 품질에 미치는 영향도 종래와 비교할 수 없을 정도로 중요시 되고 있는 실정이다, 이와같이 설비의 안전성을 도모하고 고신뢰도를 부여하기위해서는 기계설비의 이상 및 고장진단이 필수적이며, 공장 자동화와 함께 공작기계자체의 고장 및 이상진단을 실시하고, 검출된 신호의 크기등으로 고장상태를 판정해야만 한다. 공작기계에서 동적인 회전시스템을 이루는 주축용베어링의 손상은 제작하고자 하는 제품의 정밀도 표면거칠기등의 저하 뿐만아니라 시스템 전체의 기능까지도 떨어뜨리는 요인이 될수 있으므로 베어링 상태를 진단하여 송상유무를 판단하는것은 필수적이라 생각된다.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.20 no.1
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• pp.132-137
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• 2006

The second part of paper related rotor failure is to evaluate that the axial magnetic flux measurement could be used as a tool of the condition monitoring system for the induction motor and to develope the diagnostic algorithm for the various fault in the electric motors. The magnetic leakage flux signal is captured by the flux coil located at the end of motor without the disturbance of the operation. And the signal is analyzed both time and frequency domain to detect the failure of the motor. Specific signature can be described in tin and frequency domain for each fault of the motor. The experimental test found that the rotor failures - broken rotor bar, broken end ing and rotor eccentricity, could be detected from the spectrum with high resolution. The method of detecting the rotor fault was found by analysing the specific frequency and the sideband of the rotor bar pass frequency from axial leakage flux spectrum. In addition the optimal flux coil and measuring equipment for the axial leakage flux measurement was verified and the diagnostic method for the detection of the rotor related failure was developed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.50 no.8
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• pp.541-550
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• 2022

An effective real time fault diagnosis approach for UAV engine is drawn from IMM filter and GLRT methods. For this purpose based on the linear diagnosis model derived from engine dynamic performance analysis the Kalman filter for residual estimation and each method are applied to the fault diagosis of the actuator for engine control sensors. From the process of the IMM filter application the effective FDI measure is obtained and the state responses due to actuator fault are estimated. Likewise from the GLRT method the fault magnitudes of actuator and sensors are estimated associated with some FDI functionings. The numerical simulations verify the effectiveness of the IMM filter for FDI and the GLRT in estimating the fault magnitudes of each fault mode.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.1
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• pp.59-70
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• 2022

In this paper, we proposed an active fault tolerant control (AFTC) method for the position control of a quadrotor with complete loss of effectiveness of one motor. We obtained the dynamics of a quadrotor using Lagrangian equation without small angle assumption. For detecting the fault on a motor, we designed a fault detection module, which consists of the fault detection and diagnosis (FDD) module and the fault detection and isolation (FDI) module. For the FDD module, we designed a nonlinear observer that observes the states of a quadrotor based on the obtained dynamics. Using the observed states of a quadrotor, we designed residual signals and set the appropriate threshold values of residual signals to detect the fault. Also, we designed an FDI module to identify the fault location using the designed additional conditions. To make a quadrotor track the desired path after detecting the fault of a motor, we designed a fault tolerant controller based on the multiple sliding surface control (MSSC) technique. Finally, through simulations, we verified the effectiveness of the proposed AFTC method for a quadrotor with complete loss of effectiveness of one motor.

• Journal of the Korean Society for Nondestructive Testing
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• v.29 no.4
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• pp.374-382
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• 2009

Steam generator(SG) tube, as a barrier isolating primary to the secondary coolant system of nuclear power plants(NPP), must maintain the structural integrity far the public safety and its efficient power generation capacity. And SG tubes bearing defects must be timely detected and taken repair measures if needed. For the accomplishment of these objectives, SG tubes have been periodically examined by eddy current testing(ECT) on the basis of administrative notices and intensified SG management program(SGMP). Stress corrosion cracking(SCC) on the SG tubes is not easily detected and even missed since it has lower signal amplitude and other disturbing factors against its detection. However once SCC is developed, that can cause detrimental affects to the SG tubes due to its rapid propagation rate. Accordingly SCC is categorized as prime damage mechanism challenging the soundness of the SG tubes. In this study, reproduced EDM notch specimens are examined for the detectability and quantitative characterization of the axial ODSCC by +PT MRPC probe, containing pancake, +PT and shielded pancake coils apart in a single plane around the circumference. The results of this study are assumed to be applicable fur providing key information of engineering evaluation of SCC and improvement of confidence level of ECT on SG tubes.