Abstract：A model of aeroengine surge detection based on neural networks immune recognition is proposed. In this model, neural networks-based detectors are constructed based on negative selection principle of artificial immune system. Through neural network training, the pattern features of stall pressure signal are stored in the distributed neural networks-based detectors. These detectors are used to capture the stall pattern features. When a detector is matched up with a feature sample, the detector is activated. A stall point can be found out through the relevant activated detectors. When applied to a certain type of turbo engine, the result shows that the proposed model has high resolution for locations of pressure signal singularities, which are caused by stall air mass in the compressor. The method can be used in the early detection of surge signal.
2010, Vol. 29 
