Fig. 2
From: Attention activation network for bearing fault diagnosis under various noise environments
Structure of Multi-___location Vibration Signal Feature Extractor (MLVFE). The input is the vibration signal of two locations sensors, and the output is the two-dimensional vibration signal feature map of multi-___location fusion. Conv1D n (n = 1,2,3....) is a series of one-dimensional convolution with a convolution kernel of 2n-1, which is used to extract vibration signal features from multiple scales. The dotted box is the weight distribution sub-module, which will extract the extracted features through two-dimensional convolution, RELU activation function, maximum pooling, and finally use Softmax activation function to process and convert them into the weights of different ___location sensor information to realize the dynamic fusion of multi-sensor information.
