中国矿山工程

Coal mine electromechanical equipment is an important factor that directly affects coal production efficiency. In order to accurately predict the safety evaluation level of coal mine electromechanical equipment, three main influencing factors are proposed, namely enterprise organizational management factors, coal mine underground environmental factors, and electromechanical equipment status factors. Four safety evaluation level indicators are established, and a CNN-SVM model is constructed to classify and predict the characteristic values of coal mine electromechanical equipment factors with multiple vectors. The results showed that the training and prediction results of CNN-SVM model were similar to those of CNN-GRU model and CNN BiLSTM model, both of which had slightly lower prediction accuracy for safety level III. However, the prediction accuracy of this model for safety level III was higher than the above two models. Especially in the test set prediction results, the prediction accuracy of safety level III was 96.3%, far lower than the 77.8% and 88.9% of CNN-GRU model and CNN BiLSTM model. The overall prediction accuracy of CNN-SVM model for coal mine electromechanical safety evaluation level was higher than the other two models, and the model prediction results were basically consistent with the actual evaluation results.