비선형회귀모델을 이용한 히트펌프시스템의 열교환기 고장에 대한 고장감지 및 진단에 대한 연구

Abstract

Key Words: Heat Pump(히트펌프), Fault(고장), Detection(감지), Diagnosis(진단), Heat Exchanger(열교환기)초록: 본연구에서는비선형회귀모델을이용한히트펌프시스템에서의고장감지및진단알고리즘을개발하였다. 히트펌프시스템에발생할수있는다양한고장요소중, 열교환기고장에대한연구를수행하였다. 해석식을바탕으로제작한모델을이용하여총4가지작동모드(무고장, 증발기고장, 응축기고장, 응축기와증발기고장)에대한시뮬레이션을수행하였다. 고장감지및진단알고리즘을개발하기위해무고장모드에서의데이터를바탕으로각열교환기의과열도또는과냉도를예측할수있는비선형회귀모델을제시하였다. 고장감지및진단알고리즘은이비선형회귀모델을바탕으로예측한열교환기에서의과열도또는과냉도값과시뮬레이션값을비교하여그차이의정도에따라각열교환기의고장을감지및진단하도록하였다.Abstract: This paper proposed a fault detection and diagnosis (FDD) algorithm using nonlinear regression models,focusing especially on heat exchanger faults. This research concerned four working modes: those with no fault,evaporator fault, condenser fault, and evaporator and condenser faults. This research used no fault mode data tocreate an FDD algorithm. Using the no fault mode data, correlation functions for predicting the degree of superheator subcool of heat exchangers (an evaporator and a condenser) were derived. Each correlation function has fiveinputs and one output. Based on these correlation functions, it is possible to predict the degree of superheat orsubcool of each heat exchanger under various working conditions. The FDD algorithm was developed by comparingthe predicted value and the simulation value. The FDD algorithm works well in all four working modes.