Failure recognition method and system based on neural network self-learning
A neural network and fault identification technology, which is applied in the direction of biological neural network models, can solve problems such as low efficiency, high risk, and heavy workload, and achieve faster speed, faster fault identification, and labor cost savings.
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[0037] The present invention will be described in detail below through specific embodiments and drawings.
[0038] The method and system for fault identification based on neural network self-learning in this embodiment is composed of the following parts: CSM-based data acquisition subsystem, data preprocessing subsystem, feature selection subsystem, model training subsystem, and real-time data analysis subsystem System and self-learning subsystem. It is used to solve the technical problems of large workload, low efficiency and high risk when manually diagnosing railway signal system faults in the prior art.
[0039] Neural network is mainly composed of neurons, and the structure of neurons is like figure 2 As shown, a1~an are the components of the input vector
[0040] w1~wn is the weight of each synapse of neuron
[0041] b is bias
[0042] f is the transfer function, usually a nonlinear function. Generally there are sigmod(), travelingd(), tansig(), hardlim(). The following defau...
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