• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 추계학술대회논문집A
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• pp.856-860
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• 2000

Liquid ejector is widely used for power plant water pump, marine pump and transportation of solid materials. It has high working confidence and simple configuration. However, It is not easy to know performance degradation of ejectors in field. When the geometry of ejector is complicate, the diagnosis of faults is required more skillful method without disassemble. This paper gives numerical method to predict cause of $45^{\circ}$ slurry suction ejector performance degradation.

• 인터넷정보학회논문지
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• 제18권5호
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• pp.113-121
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• 2017

Company A's core competency is IT internet security services. The Web diagnosis team analyzes the vulnerability of customer's internet web servers and provides remedy reports. Traditionally, Company A management has utilized a simple table format report for resource planning. But these reports do not notify the timing of human resource commitment. So, upper management asked its team leader to organize a task team and design a visual dashboard for decision making with the help of outside professional. The Task team selected the web security diagnosis practice process as a pilot and designed a dashboard for performance evaluation. A structural design process was implemented during the heuristic working process. Some KPI (key performance indicators) for checking the productivity of internet web security vulnerability reporting are recommended with the calculation logics. This paper will contribute for security service management to plan and address KPI design policy, target process selection, and KPI calculation logics with actual sample data.

• 종양간호연구
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• 제12권2호
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• pp.156-165
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• 2012

Purpose: This study was to identify predictors of sexual function in gynecologic cancer patients. Methods: The participants were 154 patients treated at a university medical center in A city, Korea. The data collection was performed through a structured questionnaire from July to December, 2010. The instruments used in this study were Female Sexual Function Index (FSFI) perceived health status scale, Eastern Cooperative Oncology Group (ECOG) performance status, body image, and depression. Data were analyzed using descriptive statistics, Mann-Whitney test, Kruskal-Wallis test and stepwise multiple regression with the SPSS 18.0. Results: The mean score of perceived health status was 8.42 and sexual function was 8.42. The lowest score among sexual function was lubrication. The scores of sexual function was significantly different by age, job, marital status, period after diagnosis of cancer and diagnosis. There were significant correlations between sexual function, perceived health status, ECOG performance, body image and depression. In multiple regression analysis, predictors were identified as ECOG performance, age, diagnosis and period after diagnosis of cancer (Adj.$R^2$=.28). The most powerful predictor of female sexual function was ECOG performance (19.0%). Conclusion: The above findings indicate that it is necessary to develop a more effective and personalized sexual function improvement program for gynecologic cancer patient.

• Journal of Electrical Engineering and information Science
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• 제2권5호
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• pp.45-50
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• 1997

This paper present an advanced fault diagnosis expert system to assist the operators at local control center. The system utilizes all th information available in a local control center for the better diagnostic performance. The major feature of the system is dealing with multiple faults diagnosis based on the certainty factor method for the reasoning process. the overall performance and the generality are also enhanced by utilizing the general topological knowledge. ASCADA simulator is also developed for he test and demonstration.

• 한국시스템다이내믹스연구
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• 제17권3호
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• pp.145-173
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• 2016

This study aims to develop strategic diagnosis framework of performance by identifying and analysing the dynamics of the technology commercialization ecosystem in innovative region. To achieve the purpose of this study, the systems thinking approach is used. The systems thinking approach connects feedback structure and behavior more explicitly to diagnosis vicious feedback loop in the regional technology commercialization ecosystem. In terms of an ecological point of view, it will be possible to explore dominant feedback structure and find leverages to overcome the limitations of regional technology commercialization performance. The diagnosis of reenforcing and balancing feedback structure is based on the statistical analysis of the survey data which has been collected in a cluster random sampling method, targeting on the 200 firm located in the Pangyo and Daeduk region. The results from this research showed that the regional technology commercialization ecosystem was immature and faced limit to the growth. An important finding of this study was that regional technology commercialization ecosystem need to activation of startups and reinforcement of virtuous feedback structures of technology commercialization market systems.

• 대한임베디드공학회논문지
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• 제19권1호
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• pp.57-64
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• 2024

In the industrial field, robots are used to increase productivity by replacing labors with dangerous, difficult, and hard tasks. However, failures of individual industrial robots in the entire production process may cause product defects or malfunctions, and may cause dangerous disasters in the case of manufacturing parts used in automobiles and aircrafts. Although requirements for early diagnosis of industrial robot failures are steadily increasing, there are many limitations in early detection. This paper introduces methods for diagnosing robot failures using sound-based data and deep learning. This paper also analyzes, compares, and evaluates the performance of failure diagnosis using various deep learning technologies. Furthermore, in order to improve the performance of the fault diagnosis system using deep learning technology, we propose a method to increase the accuracy of fault diagnosis based on an inference window. When adopting the inference window of deep learning, the accuracy of the failure diagnosis was increased up to 94%.

• Journal of Power Electronics
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• 제10권6호
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• pp.702-708
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• 2010

In this paper, a fault diagnosis algorithm for brushless DC (BLDC) motor drives is proposed to maintain control performance under switch open-damage. The proposed fault diagnosis algorithm consists of a simple algorithm using measured phase current information and it detects open-circuit faults based on the operating characteristic of BLDC motors. The proposed algorithm quickly recovers control performance due to its short detection time and its reconfiguration of the system topology. It can be embedded into existing BLDC drive software as a subroutine without additional sensors. The feasibility of the proposed fault diagnosis algorithm is proven by simulation and experimental results.

• 대한임베디드공학회논문지
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• 제14권6호
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• pp.287-294
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• 2019

With the automation of production lines in the manufacturing industry, the importance of real-time fault diagnosis of facility is increasing. In this paper, we propose a fault diagnosis algorithm of LM (Linear Motion)-guide based on deep learning using vibration signals. Generally, in order to guarantee the performance of the deep learning, it is necessary to have a sufficient amount of data, but in a manufacturing industry, it is often difficult to obtain enough data due to physical and time constraints. To solve this problem, we propose a convolutional neural networks (CNN) model based on transfer learning. In addition, the spectrogram image is input to the CNN to reflect the frequency characteristic of the vibration signals with time. The performance of fault diagnosis according to various load condition and transfer learning method was compared and evaluated by experiments. The results showed that the proposed algorithm exhibited an excellent performance.

• KIEAE Journal
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• 제16권4호
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• pp.71-77
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• 2016

Purpose : The energy saving in a residential building (apartment) sector is known as one of the effective solution of energy reduction. In South Korea, the government has recently reinforced regulations associated with the energy performance of buildings. However, there is a lack of research on the methods for the energy performance diagnosis that is used to analyze the wall thermal performance of the existing apartments. Because a reliable diagnosis is necessary to save the building energy, this study analyzed wall thermal performance of an existing apartment in Seoul. Method : This paper applied two methods for analysis of the thermal insulation performance; HFM(Heat Flow Meter) method and ASTR(Air-Surface Temperature Ratio) method. The HFM method is suggested by ISO9869-1 code to measure the thermal performance. The ASTR method is proposed by this study for the simplified In-situ measurement and it uses three temperature data (interior wall surface, interior and exterior air) and the overall heat transfer coefficient. This study conducted the experiment of an existing apartment in Seoul using these methods and analyzed the results. Furthermore, the energy simulation tool of the building was used to suggest retrofit of the building based on the results of measurements. Result : The error rate of HFM method and ASTR method was analyzed in about 17 to 20%. As the results of comparison between the initial design values of the wall and the measured values, the 26% degradation of insulation thermal performance was measured. Lastly, the energy simulation tool of the building shows 10.8% energy savings in accordance with the construction of suggested retrofit.

• 한국산학기술학회논문지
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• 제11권11호
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• pp.4576-4582
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• 2010

현재 대부분의 차량은 사용자에게 차량 성능에 관한 일부 정보만을 제공하기 때문에 차량의 안전 운행 및 유지 보수에 어려움이 따른다. 이러한 문제점 등을 해결하기 위하여 최근에 차량 제어 및 진단시스템에 대한 다양한 방식의 연구개발이 진행되고 있지만, 시스템 구현의 복잡성, 성능진단의 신뢰성 저하, 오동작 등 여러 가지 문제점이 나타나고 있다. 본 논문에서는 위에서 언급한 문제점을 해결할 목적으로 위성 원격측정기술을 이용하여 차량 성능을 실시간으로 측정하고 분석하여 차량 성능의 신뢰성을 진단할 수 있는 차량 성능진단시스템에 관한 개념 설계를 수행하였다. 본 연구에서 도출된 개념 설계 결과는 향후 차량 성능진단시스템 구현을 위한 상세설계의 기반 데이터 및 자료로 이용될 것이다.