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.
