Development of a fault diagnosis method for heating systems using neural networks
- Centre Scientifique et Technique du Batiment, Marne La Vallee (France). HVAC Dept.
The application of artificial neural networks (ANNs) for developing a fault diagnosis (FD) method in complex heating systems is presented in this paper. The six operating modes with faults used to develop this FD method came from the results of a detailed investigation in cooperation with heating system maintenance experts and are among the most important operating faults for this type of system. Because a daily diagnosis is generally sufficient, the ANNs have been developed using the daily values obtained by a preprocessing of the numerical simulation data. This paper presents the first step of the method development. It demonstrates the feasibility of using ANNs for fault diagnosis of a specific heating, ventilating, and air-conditioning (HVAC) system provided training data representative of the behavior of the system with and without faults are available. The next step will consist of developing a generic method that requires less training data.
- OSTI ID:
- 392489
- Report Number(s):
- CONF-960254--
- Country of Publication:
- United States
- Language:
- English
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