A variable air volume（VAV）system exhibits the feature of limited sensors and similar characteristics of fault conditions. A traditional passive fault detection and diagnosis（FDD）method does not diagnose all faults in VAV systems due to limited information. Thus

it is necessary to obtain more diagnostic information while not necessitating additional sensors and labor. In the study

a proactive fault detection and diagnosis method was proposed to solve the problem. The method obtains more valuable diagnosis information via the introduction of small disturbances during working time immediately when faults occur. Hence

this further aids in diagnosing suspicious faults that cannot be separated via passive methods. The passive method was also combined with proactive methods to improve the FDD efficiency. In order to verify the feasibility of the method

a VAV air conditioning system was constructed in the TRNSYS simulation platform. Additional diagnosis information was obtained by introducing faults in VAV terminals and introducing proactive action. Additionally

the simulation results indicate that the method can effectively detect and diagnose 12 common faults in VAV terminals. Furthermore

the diagnostic and detection mechanism is more advanced when compared with that of traditional passive methods.