Rapid classification and detection method for metal materials based on quantitative analysis of characteristic elements

The invention discloses a rapid classification and detection method for metal materials based on quantitative analysis of characteristic elements. The method comprises the following steps: 1, establishing a metal material state multi-source information database according to element content information of a metal material; 2, determining main factors influencing the operation state of the metal material from the metal material state multi-source information database, taking the main factors as input layer neurons of a BP neural network model, and constructing a learning sample; 3, establishing a three-layer neural network based on a BP algorithm; 4, setting a learning rate, training times and a training target error, and training and verifying the neural network; and 5, establishing a simple and efficient model according to the trained neural network. According to the method, neural networks are combined to establish the convolutional neural network model for metal element content classification, the model is