Korean Journal of Air-Conditioning and Refrigeration Engineering (설비공학논문집)

The Society of Air-Conditioning and Refrigerating Engineers of Korea (대한설비공학회)
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Fault Detection and Diagnosis for an Air-Handling Unit Using Artificial Neural Networks

신경망 이용 공조기 고장검출 및 진단

  • Published : 2001.12.01
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Abstract

A scheme for on-line fault detection and diagnosis of an air-handling unit is presented. The fault detection scheme uses residuals which are generated by comparing each measurement with analytical redundancies computed from the reference models. In this paper, artificial neural networks (ANNs) are used to estimate analytical redundancy and to classify faults. The Lebenburg-Marquardt algorithm is used to train feed forward ANNs that provide estimates of continuous states and diagnosis results. The simulation result demonstrated that the ANNs can effectively detect and diagnose faults in the highly non-linear and complex HVAC systems.

Keywords

References

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