PHM 기반 공조설비의 고장 패턴 학습을 통한 미세먼지 저감 알고리즘 개발

초록

In this paper, we designed an algorithm that can control the state of PM by learning the chain failure pattern of PHM based air conditioning facility. It is an inevitable spread of PM due to the downtime caused by the failure of the air conditioning facility. The algorithm developed by us is to establish a PM management system through PHM, and it is an algorithm that maintains a constant stabilization state through learning the stop/operation pattern of the air conditioner and manages PM based on this. As a result of the simulating at a subway station for the performance qualification of the algorithm, it was verified that the concentration of PM reduces by 30% on average. In the case of stations with many passengers using the subway, the concentration of PM exceeded the Ministry of Environment Standards(100 ㎍/㎥), but it was verified that the concentration of PM was improved at all stations where the simulation was conducted. In the future research is to expand the system to comprehensively manage not only PM but also pollutants such as CO2, CO, and NO2 in subway stations.

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