Elevator fault pre-warning method based on bidirectional gating circulating neural network
A cyclic neural network, two-way door technology, used in elevators, transportation and packaging, etc., can solve problems such as the inability to reflect the health status of elevators in real time, and the inability to predict failures in advance, so as to reduce adverse effects, compress rescue time, and improve rescue success rate. Effect
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[0089] 1. Parameter setting and application of bidirectional gated recurrent neural network prediction model.
[0090] The elevator waveform sequence is used as the data set, and each cycle of the waveform sequence contains 256 sampling points. Here, 100,000 sequences are used as the overall samples, 70% of which are used as training samples and 30% are used as test samples. Using 7 layers of neural network layers, the Relu function is used as the activation function between neurons in each layer, the input layer is a fully connected layer, the hidden layer is four layers of bidirectional gated recurrent neural network layers and a fully connected layer , the output layer is a softmax layer, and the final classification is extracted from the softmax layer. The input sequence shape is [70000,256,1], that is, 70,000 samples, 256 steps correspond to 256 sampling points, and the input data dimension is 1. The output sequence sample is [70000,256,1], that is, the output data is co...
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