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정풍량 공조시스템의 고장검출 및 진단 시뮬레이션Fault Detection and Diagnosis Simulation for CAV AHU System
- Other Titles
- Fault Detection and Diagnosis Simulation for CAV AHU System
- Issue Date
- 2010
- Publisher
- 대한설비공학회
- Keywords
- Fault detection and diagnosis(고장검출 및 진단); HVAC equipment(공조설비); Normalized distance method(표준화 거리 기법); Classifier(분류기)
- Citation
- 설비공학 논문집, v.22, no.10, pp.687 - 696
- Indexed
- KCI
- Journal Title
- 설비공학 논문집
- Volume
- 22
- Number
- 10
- Start Page
- 687
- End Page
- 696
- ISSN
- 1229-6422
- Abstract
- 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℃ by FDD algorithm. FDD algorithm developed in this study was found to indicate each failure modes accurately.
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Collections - College of Engineering > Department of Mechanical Engineering > 1. Journal Articles
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