HVAC air handling systems have strong dynamic time-varying and batch-dynamic characteristics.In order to effectively diagnose the detected fault patterns,this paper constructs a fault diagnosis mode based on enhanced long short-term memory(LSTM)network,which can efficiently identify the sparse and slow features of the fault data.A case study based on the ASHRAE research project RP-1312 experimental dataset shows that the proposed method has a significant improvement in identifying air handling system faults compared with the related fault identification methods.
维普
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