• 핵의학기술
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• 제22권2호
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• pp.105-111
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• 2018

Purpose Quality control of instrument takes up a large part in the Radioimmunoassays. The gamma-ray instrument, which is one of the important instruments in the laboratory, observes the condition and performance of instrument and performs quality control of the instrument by measuring the Normalization, Calibration, Background and etc. However, there are some automation instruments which can't measure the counting efficiency of gamma-ray meters, resulting in insufficient management in terms of performance evaluation of gamma-ray meters. Therefore, the purpose of this paper is to manage the quality control continuously and regularly by suggesting how to measure the counting efficiency of gamma-ray instruments. Materials and Methods In case of a comparative measurement method to a gamma-ray instrument dedicated to nuclear medical examination, the CPM and counting efficiency can be obtained after the measurement of normalization by inserting the I-125 $200{\mu}L$(CPM 50,000~500,000) into the test tube. With this CPM and counting efficiency values, it's possible to calculate the measurement of the DPM value and count the CPM from the automation instrument from the same source, and enter the DPM to calculate the counting efficiency using a comparative measurement method. Another method is to calculate the counting efficiency by estimating the half life using the radiation source information of the tracer in B test reagents of company A. Results According to the calculation formula using the DPM obtained by counting the normalization of gamma-ray meters, the detection efficiency was 75.16% for Detector 1, 76.88% for Detector 2, 77.13% for Detector 3, 75.36% for Detector 4 and 73.2% for Detector 5 respectively. Using another calculation formula estimated from the shelf life, the data of the detection efficiency from Detector 1 to Detector 5 were 74.9%, 75.1%, 76.5%, 74.9% and 73.2% respectively. Conclusion Although the accuracy of counting efficiencies of both methods are insufficient, this is considered to be useful for ongoing management of quality control if counting efficiency is managed after setting the acceptable ranges. For example, if the measurement efficiency is set to 70% or higher, the allowed %difference between measurements is within 3% and the %difference with the detector wall is set within 5%.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2003년도 ICCAS
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• pp.1338-1343
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• 2003

Data is the expression of the language or numerical values that show some characteristics. And information is extracted from data for the specific purposes. The knowledge is utilized as information to construct rules that recognize patterns and make decisions. Today, knowledge extraction and application of the knowledge are broadly accomplished to improve the comprehension and to elevate the performance of systems in several industrial fields. The knowledge extraction could be achieved by some steps that include the knowledge acquisition, expression, and implementation. Such extracted knowledge can be drawn by rules. Clustering (CU, input space partition (ISP), neuro-fuzzy (NF), neural network (NN), extension matrix (EM), etc. are employed for expression the knowledge by rules. In this paper, the various approaches of the knowledge extraction are examined by categories that separate the methods by the applied industrial fields. Also, the several test data and the experimental results are compared and analysed based upon the applied techniques that include CL, ISP, NF, NN, EM, and so on.

• Journal of Multimedia Information System
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• 제6권4호
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• pp.239-244
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• 2019

With the development of Cyber-Physical Systems(CPS), several technologies such as automation control, automotive and intelligent house systems have been developed. To enable communication among various components of such systems, several wired and wireless communication protocols are used. The Controller Area Network(CAN) is one of such wired communication protocols that is popularly used for communication in automobiles and other machinery in the industry. In this paper, we designed and implemented a response time analysis system for CAN communication. The reliable data transfer among various electronic components in a significant time is crucial for the smooth operation of an electric vehicle. Therefore, this system is designed to conveniently analyze the response time of various electronic components of a CAN enabled system. The priority for transmission of the messages in the CAN bus is determined by the message identifier. As the number of nodes increases the transmission of low priority messages is delayed due to the existence of higher priority messages on the bus. We used Raspberry Pi3 and PiCAN2 board to simulate the data transfer for studying the comparative delay in low priority nodes.

• 제어로봇시스템학회논문지
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• 제20권7호
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• pp.782-787
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• 2014

Due to the complicated steel structure and safety concern, it is very difficult to deploy wireless networks in power plants. This paper presents a hybrid network, named as $P^2HYMN$ (Power Plant HYbrid Maintenance Network), encompassing PLC (Power Line Communication), TLC (Telephone Line Communication), and Wireless LAN. The design goal of $P^2HYMN$ is to integrate multimedia data such as design drawings of control equipment, process data, and video image data for maintenance operation in electric power plants. A Multiplex Line Communication (MLC) device was designed and implemented to integrate PLC, TLC, and Wireless LAN into $P^2HYMN$. Performance test of $P^2HYMN$ has been conducted on a testbed under various conditions. The throughput of TLC was shown as 39 Mbps. Because the bandwidth requirement per camera is 8.5 Mbps on average, TLC is expected to support more thant four video camera at the same time.

• International Journal of Control, Automation, and Systems
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• 제2권2호
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• pp.256-262
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• 2004

Conventionally, profile non-uniformity has been characterized by relying on approximated profile with angle or anisotropy. In this study, a new non-uniformity model for etch profile is presented by applying a discrete wavelet to the image obtained from a scanning electron microscopy (SEM). Prediction models for wavelet-transformed data are then constructed using a back-propagation neural network. The proposed method was applied to the data collected from the etching of tungsten material. Additionally, 7 experiments were conducted to obtain test data. Model performance was evaluated in terms of the average prediction accuracy (APA) and the best prediction accuracy (BPA). To take into account randomness in initial weights, two hundred models were generated for a given set of training factors. Behaviors of the APA and BPA were investigated as a function of training factors, including training tolerance, hidden neuron, initial weight distribution, and two slopes for bipolar sig-moid and linear function. For all variations in training factors, the APA was not consistent with the BPA. The prediction accuracy was optimized using three approaches, the best model based approach, the average model based approach and the combined model based approach. Despite the largest APA of the first approach, its BPA was smallest compared to the other two approaches.

• 한국정밀공학회지
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• 제21권11호
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• pp.61-68
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• 2004

Recently, there has been an increasing demand for computer-vision based inspection and/or measurement system as a part of factory automation equipment. Existing manual inspection method can inspect only specific samples and has low measuring accuracy as well as it increases working time. Thus, in order to improve the objectivity and reproducibility, computer-aided analysis method is needed. In this paper, front and side profile inspection and/or data transfer system are developed using computer-vision during the inspection process on three kinds of pipes coming from a forming line. Straight line and circle are extracted from profiles obtained from vision using Laplace operator. To reduce inspection time, Hough Transform is used with clustering method for straight line detection and the center points and diameters of inner and outer circle are found to determine eccentricity and whether good or bad. Also, an inspection system has been built that each pipe's data and images of good/bad test are stored as files and transferred to the server so that the center can manage them.

• 한국컴퓨터정보학회논문지
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• 제23권11호
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• pp.103-109
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• 2018

This paper presents an idea and framework to automate a full cycle business process management and re-engineering by integrating traditional business process management systems, process mining, data mining, machine learning, and simulation. We build our framework on the cloud-based platform such that various data sources can be incorporated. We design our systems to be extensible so that not only beneficial for practitioners of BPM, but also for researchers. Our framework can be used as a test bed for researchers without the complication of system integration. The automation of redesigning phase and selecting a baseline process model for deployment are the two main contributions of this study. In the redesigning phase, we deal with both the analysis of the existing process model and what-if analysis on how to improve the process at the same time, Additionally, improving a business process can be applied in a case by case basis that needs a lot of trial and error and huge data. In selecting the baseline process model, we need to compare many probable routes of business execution and calculate the most efficient one in respect to production cost and execution time. We also discuss the challenges and limitation of the framework, including the systems adoptability, technical difficulties and human factors.

• Nuclear Engineering and Technology
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• 제55권2호
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• pp.603-622
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• 2023

Human error (HE) is an important concern in safety-critical systems such as nuclear power plants (NPPs). HE has played a role in many accidents and outage incidents in NPPs. Despite the increased automation in NPPs, HE remains unavoidable. Hence, the need for HE detection is as important as HE prevention efforts. In NPPs, HE is rather rare. Hence, anomaly detection, a widely used machine learning technique for detecting rare anomalous instances, can be repurposed to detect potential HE. In this study, we develop an unsupervised anomaly detection technique based on generative adversarial networks (GANs) to detect anomalies in manually collected surveillance data in NPPs. More specifically, our GAN is trained to detect mismatches between automatically recorded sensor data and manually collected surveillance data, and hence, identify anomalous instances that can be attributed to HE. We test our GAN on both a real-world dataset and an external dataset obtained from a testbed, and we benchmark our results against state-of-the-art unsupervised anomaly detection algorithms, including one-class support vector machine and isolation forest. Our results show that the proposed GAN provides improved anomaly detection performance. Our study is promising for the future development of artificial intelligence based HE detection systems.

• 한국지반공학회논문집
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• 제23권4호
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• pp.133-147
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• 2007

지반의 전단파 속도 주상도를 도출하는데 있어 다운홀 기법은 하나의 시추공을 이용하고 간단한 지표면 가진원을 사용하므로 매우 경제적이다. 따라서 학교와 현업에서 지반조사 및 연구 목적으로 널리 사용되고 있다. 그러나 올바르지 못한 장비의 구성과 해석과정으로 인하여 결과의 신뢰성에 문제가 있어왔다. 본 연구에서는 다운홀 기법의 상호검증시험(Round Robin Test)을 통해 참여 기관에 대해서 각각의 실험 장비와 결과 해석 과정에 대해 비교함으로써 문제점에 대해 분석하였으며 이를 바탕으로 최적의 수행 시스템을 구성하였다. 효율적인 가진원을 제작하고 적절한 감지기를 도입 혹은 제작하였으며 노트북 기반의 신호 획득 시스템을 구축하였다. 신호 획득 및 관리 프로그램, 결과도출 프로그램을 통해 현장에서 효율적으로 실험을 진행하고 신뢰성 있는 최종 결과를 신속하게 도출할 수 있도록 하였다. 구성된 수행 시스템을 이용하여 현장 적용 실험을 수행하였으며 그 효율성을 확인할 수 있었다.

• 제어로봇시스템학회논문지
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• 제13권10호
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• pp.970-977
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• 2007

Absolute position detector which is one of the major equipment in the field of factory automation, not only perceives the absolute position of the rotary machine but also outputs switch data according to the given angle. Absolute position detector is composed of sensor module and its controller. In this paper, a sensor driver is implemented using FPGA with VHDL. This chip has a less form factor than conventional circuit. A test shows reliable precision within THD(total harmonic distortion) of 0.2% which can be applicable commercially. Also, FPGA-based phase error compensation methods were newly discussed. In the future, more research will be conducted to enhance the precision by the introduction of 3-phase transformer.