Partial Fault Detection of Cooling Tower in Building HVAC System

摘要

The high false alarm rate and the difficulty of modeling are the main problems in the field of cooling tower system fault detection which is an important energy consumption optimization method in heating, ventilation, and air-conditioning (HVAC) system. This paper proposes an effective solution that is used to reduce the false alarm rate and built a gray box model which simplified from the physical principle of a cooling tower. The Kalman filter is used to forecast the running state of the cooling tower system, and the dynamic control limit set by the statistical process control (SPC) is used to reduce the false alarm rate. Through the final experimental results in the Sino-German building, located in the northeastern part of China, it can be seen that the control limit can be effectively adjusted according to the fluctuation of the natural environment, and the false alarm rate can be well controlled.