• Title/Summary/Keyword: Conditioning diagnosis

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Conditioning diagnosis & on-line monitoring technology on the traction motor for railway rolling stock (철도차량 견인전동기의 상태진단 및 상시감시 기술)

  • Wang, Jong-Bae;Hong, Seon-Ho;Kim, Sang-Am;Kwak, Sang-Rok
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2003.07a
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    • pp.92-95
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    • 2003
  • 본 논문에서는 철도차량 견인전동기에 대한 상태진단 및 상시감시 기술에 관하여 소개하였다. 권선의 절연상태 진단을 위한 비파괴 시험법에서는 부분방전량 Q에 대한 평균열화도 $\Delta$로 표현되는 D-Map에 의해 잔여 절연내력(residual dielectric strength)을 예측하고, 기기의 운전이력측면에서 기동-정지 횟수와 열적, 전기적 및 열싸이클 스트레스 등에 의해 각 열화 인자를 고려한 운전시간에 기반한 N-Y 수명예측을 수행한다. 그리고 견인전동기의 전류에 대한 온라인 상태감시를 통해 베어링 고장, 고정자 및 전기자 고장, 고장 또는 전동기축 손상에 기인하는 비정상 운전상태 의 감지를 수행한다.

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Fault Detection and Diagnosis Simulation for CAV AHU System (정풍량 공조시스템의 고장검출 및 진단 시뮬레이션)

  • Han, Dong-Won;Chang, Young-Soo;Kim, Seo-Young;Kim, Yong-Chan
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.22 no.10
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    • pp.687-696
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    • 2010
  • In this study, FDD algorithm was developed using the normalized distance method and general pattern classifier method that can be applied to constant air volume air handling unit(CAV AHU) system. The simulation model using TRNSYS and EES was developed in order to obtain characteristic data of CAV AHU system under the normal and the faulty operation. Sensitivity analysis of fault detection was carried out with respect to fault progress. When differential pressure of mixed air filter increased by more than about 105 pascal, FDD algorithm was able to detect the fault. The return air temperature is very important measurement parameter controlling cooling capacity. Therefore, it is important to detect measurement error of the return air temperature. Measurement error of the return air temperature sensor can be detected at below $1.2^{\circ}C$ by FDD algorithm. FDD algorithm developed in this study was found to indicate each failure modes accurately.

An Experimental Study on Multi-Fault Detection and Diagnosis Analysis of HVAC System (HVAC 시스템의 중복고장 검출을 위한 실험적 연구)

  • Cho Sung-Hwan;Hong Young-Ju;Yang Hooncheul;Ahn Byung-Cheon
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.16 no.10
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    • pp.932-941
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    • 2004
  • The objective of this study is to detect the multi-fault of HVAC system using a new pattern classification technique. To classify the effect of single-fault in determining the pattern, supply air temperature, OA-damper, supply fan, and air flowrate were chosen as experimental parameters. The combination of supply temperature, flow rate, supply fan and OA-damper were chosen as multi-fault conditions. Three kinds of patterns were introduced in the analysis of multi-fault problem. To solve multi-fault problem, the new pattern classification technique using residual ratio analysis was introduced to detect the multi-fault as well as single-fault. The residual ratio could diagnose single-fault or multi-fault into several patterns.

A Heuristic Methodology for Fault Diagnosis using Statistical Patterns

  • Kwon, Young-il;Song, Suh-ill
    • Journal of Korean Society for Quality Management
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    • v.21 no.2
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    • pp.17-26
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    • 1993
  • Process fault diagnosis is a complicated matter because quality control problems can result from a variety of causes. These causes include problems with electrical components, mechanical components, human errors, job justification errors, and air conditioning influences. In order to make the system run smoothly with minimum delay, it is necessary to suggest heuristic remedies for the detected faults. Hence, this paper describes a heuristic methodology of fault diagnosis that is performed using statistical patterns generated by quality characteristics The proposed methodology is described briefly as follows: If a sample pattern generated by random variables is similar to the number of prototype patterns, the sample pattern may be matched by any prototype pattern among them to be resembled. This concept is based on the similarity between a sample pattern and the matched prototype pattern. The similarity is calculated as the weighted average of squared deviation, which is expressed as the difference between the relative values of standard normal distribution to be transformed by the observed values of quality characteristics in a sample pattern and the critical values of the corresponding ones in a matched prototype pattern.

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Diagnosis Method of PV Module Mismatch using Voltage and Current Waveforms (태양광 모듈의 전압 및 전류 파형을 이용한 부정합 진단 기법)

  • Ahn, Hee-Wook;Park, Gi-Yob
    • Journal of the Korean Solar Energy Society
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    • v.31 no.3
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    • pp.17-22
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    • 2011
  • Techniques for mismatch loss minimization to increase the PV system efficiency are under development recently. In this paper, a method to make diagnosis of PV module mismatch is presented, which uses a concept of operating point factor. The method is based on the fact that the ratio of the incremental conductance of a PV module to instantaneous conductance is 1 when the module is operating at its maximum power point. The variations of module voltage and current are taking place by the maximum power point tracker in the power conditioning units of PV system. The effectiveness of the method is verified through an application to a real PV system.

Developing the framework of level diagnosis for green data center (그린데이터센터의 수준진단 프레임워크 개발)

  • Ra, Jong-Hei;Lee, Sang-Hak
    • Journal of Digital Convergence
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    • v.9 no.2
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    • pp.141-152
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    • 2011
  • The data center has become an increasingly important part of most business operations. An increasing demand for computation has led to increasing industry energy consumption. Therefore, higher-than-normal rates of energy efficiency have become a core issue in the life cycle of data center. In this paper, we proposed the framework of level diagnosis for green data centre that can be used to diagnose the levels of capability maturity model. This framework contains the 5 key areas such as construction, air-conditioning, electricity, information technology, organization and indicators that can be applied as basic level diagnosis guide for green data center.

A Study on the Improvement of Energy Efficiency in Warehouses (물류센터의 에너지 효율 개선 방안에 관한 연구)

  • Sun, Jong-Keun;Ryoo, Ho-Sang
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.26 no.6
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    • pp.66-72
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    • 2012
  • The main sources of energy consumption in warehouses are MHE(Material Handling Equipment), HVAC(Heating, Ventilating and Air Conditioning) and Lighting. Warehouses in advanced countries raise energy efficiencies with energy consumption diagnosis, technology development and systematic management and improvements for MHE, HVAC and Illuminating, etc. They have managed illuminating system, air conditioning, motor driven system, air circulation method, dock facility, layout, AS/RS, conveyor system and battery management, etc. Ansong Pyeongtaek area investigation resulted that 43.9[%] of enterprises are managing partly energy consumption source. But the data resulted with not substantial management of energy consumption but passive management for only electric bill curtailment. Therefore through survey research & visiting interviews of some companies in Ansong Pyeongtaek area, we understood the status of energy consumption source management and proposed energy efficiency methods on the basis of that results.

A Study for Predicting Building Energy Use with Regression Analysis (회귀분석에 의한 건물에너지 사용량 예측기법에 관한 연구)

  • 이승복
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.12 no.12
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    • pp.1090-1097
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    • 2000
  • Predicting building energy use can be useful to evaluate its energy performance. This study proposed empirical approach for predicting building energy use with regression analysis. For the empirical analysis, simple regression models were developed based on the historical energy consumption data as a function of daily outside temperature, the predicting equations were derived for different operational modes and day types, then the equations were applied for predicting energy use in a building. BY selecting a real building as a case study, the feasibilities of the empirical approach for predicting building energy use were examined. The results showed that empirical approach with regression analysis was fairly reliable by demonstrating prediction accuracy of $pm10%$ compared with the actual energy consumption data. It was also verified that the prediction by regression models could be simple and fairly accurate. Thus, it is anticipated that the empirical approach will be useful and reliable tool for many purposes: retrofit savings analysis by estimating energy usage in an existing building or the diagnosis of the building operational problems with real time analysis.

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On-site Performance Test and Simulation of a 10 RT Air Source Heat Pump

  • Baik, Young-Jin;Chang, Young-Soo;Kim, Young-Il
    • International Journal of Air-Conditioning and Refrigeration
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    • v.12 no.2
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    • pp.61-69
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    • 2004
  • In this study, on-site performance test of an air source heat pump which has a rated capacity of 10 RT is carried out. Since indoor and outdoor air conditions can not be controlled to satisfy the standard test conditions, experiments are done with the inlet air conditions as they exist. To estimate the performance of the heat pump for other conditions, the heat pump is modeled with a small number of characteristic parameters. The values of the parameters are determined from the few measurements measured on-site during steady operation. A simulation program is developed to calculate cooling capacity and power consumption at any other arbitrary operating conditions. The simulation results are in good agreement with the experiment. This study provides a method of an on-site performance diagnosis of an air source heat pump.

A Study on an Acoustical Model for Gas Leak Detection in a Pipeline (배관계의 가스누설탐지를 위한 음향모델 연구)

  • Yang, Yoon-Sang;Lee, Dong-Hoon;Koh, Jae-Pil
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.26 no.2
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    • pp.91-96
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    • 2014
  • An acoustical model for detecting the leak location in a buried gas pipeline has been developed. This model is divided into an experimental model for sound diagnosis, and a theoretical model for sound prediction, which is based on the transfer matrix method, representing the sound pressure and the volume velocity as state variables. The power spectrum is measured by attaching only one microphone to the closed end pipe. It has been shown that the response magnitude of acoustic pressure signals calculated by the acoustical model depends upon the thickness and diameter of a pinhole. The validity for the acoustical model has been verified through a comparison between the measured and calculated results.