Fault Prognosis Of Hvac Air Handling Unit And Its Components Using Hidden-Semi Markov Model And Statistical Process Control

Air handling units are key sub-systems of heating, ventilation and air conditioning systems, which are used to condition air to satisfy human comfort requirements. Fault prognosis allows maintenance crews to identify the Remaining Useful Life (RUL) of a system, thus unexpected breakdowns are avoided, leading to a decrease in maintenance costs. To estimate RULs, a Hidden Semi-Markov Model (HSMM)-based method is proposed. To estimate states of HSMMs accurately, a revised scaled method is developed to guarantee that state estimates do not approximate to infinity. Additionally, a new discrete statistical process control method is developed to filter out false state estimates of HSMMs. To estimate RULs of components and systems accurately and effectively, a backward recursive method is developed to integrate HSMMs' parameters of time-duration distributions for multiple failure modes to generate those of components and systems directly, thus low computational effort is achieved. Experimental results illustrate that the RULs of components/systems can be predicted by our method accurately in an efficient way.(c) 2021 Elsevier B.V. All rights reserved.