• Proceedings of the KSME Conference
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• 2000.11a
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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.

• Journal of Internet Computing and Services
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• v.18 no.5
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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.

• Asian Oncology Nursing
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• v.12 no.2
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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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• v.2 no.5
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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.

• Korean System Dynamics Review
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• v.17 no.3
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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.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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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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• v.10 no.6
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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.

• IEMEK Journal of Embedded Systems and Applications
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• v.14 no.6
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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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• v.16 no.4
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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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.11
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• pp.4576-4582
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• 2010

Because most of vehicle provide users with the very limited information regarding the performance of vehicle, it is quite difficult for users to drive vehicles safe, and to maintain and repair vehicles properly. In order to solve the above-mentioned problems, several ways of research and development for the vehicle control and diagnosis system have been recently carried out. However, a lot of complicated problems and difficulties were arising due to the complexity of the developed system, degradation of the reliability for the vehicle performance control system, operational malfunction and so on. In this paper, for the purpose of solving the difficult problems and technical limitations, a system for vehicle performance which might be able to diagnose the reliability of vehicle performance by measuring and analyzing the real time performance of vehicle using the satellite telemetry technology was conmance oly defined and deehiced.hihe results derived from the cormance ofdvehiclactivities in this study shall be used as not only fundamental data but also materials for the detailed design for the implementation of vehicle performance diagnosis system in the near future.