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- W2380825059 abstract "A new fault detection model of immune recognition was proposed based on neural networks. In this model, neural networks-based detectors were constructed based on the principle of immune recognition. Taking advantage of neural networks training, the information of fault patterns was stored in the distributed neural networks-based detectors. These detectors were used to capture the anomalous pattern features. When a detector was matched up with a feature sample, the detector was stimulated. Through the relevant stimulated detectors, a fault could be found out. The principle and structure of the model were proposed, and its training algorithm was derived. The fault diagnosis scheme using this model was investigated. Defect detection simulations of rolling bearings shows that the proposed model has high resolution for locations of signal singularities, which are caused by impacts between defect and its mating surface in the bearing. This method is contributive for rolling bearing status monitoring and it can be easily extended to other relative industrial application areas." @default.
- W2380825059 created "2016-06-24" @default.
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- W2380825059 date "2009-01-01" @default.
- W2380825059 modified "2023-09-24" @default.
- W2380825059 title "Immune Recognition Fault Detection Model Based on Neural Networks" @default.
- W2380825059 hasPublicationYear "2009" @default.
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