Research on Equipment Fault Prediction Methods Based on Adaboost and BP Neural Networks
In order to improve the accuracy of equipment fault prediction,the paper proposes the equipment fault prediction method based on Adaboost and BP neural network.Multiple groups of BP neural network are set up as an independent fault weak pre-dictor to predict faults,and the prediction results are input into Adaboost fault weak predictor,and the fault strong predictor is formed through the weight setting of multiple groups of neural networks,so as to accurately predict faults.The study shows that the proposed method has high prediction accuracy and stability,and can be widely used in the field of equipment fault prediction,and can provide an effective solution for equipment fault prediction.
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