截齿截割煤岩载荷是研制高性能采掘机械和智能化开采的重要基础，通过探究截齿截割煤岩载荷谱的变化规律和特征，为研究高效、高可靠破岩方法提供理论支撑，针对截齿破碎煤岩过程存在随机性，传统的理论推演载荷模型具有单值特性，难以准确描述任意截割条件下煤岩破碎的载荷历程，提出理论推演的截齿载荷幅值模型和有限实验载荷谱相结合方式，采用信息熵理论对理论与实验截割载荷谱进行综合，应用正则化神经网络对载荷谱综合进行模型化重构，根据最小二乘法提出基于有限载荷曲线族预测不同楔入角载荷谱的模型。结合30°~50°楔入角实验不同参数下载荷谱,以不同楔入角截齿的载荷谱和理论推演模型为例，对比分析不同楔入角下载荷谱的综合与正则化神经网络对其模型化重构，以及对不同楔入角的载荷预测。研究表明:构建了过程响应的截割阻力理论推演模型，在此基础上获得了30°~50°楔入角下理论与实验相结合的综合载荷谱，实现了载荷谱幅值与变化规律的表征，给出了载荷谱正则化神经网络模型化重构的方法;根据所建立的不同楔入角的载荷预测模型对30°,33°,50°和55°载荷谱进行预测，其中楔入角为30°和50°的预测载荷谱与正则化神经网络模型化重构载荷谱的互相关系数分别为0.971 7和0.983 9，呈高度相关，其幅值相对误差分别为4.04%和5.21%，表明该模型可以表征载荷幅值与截割煤岩载荷历程，模型具有一定优越性，为研究截齿的破碎机制提供了参考。

The load of cutting coal and rock is an important basis for the development of high-performance mining ma- chinery and intelligent mining. By exploring the variation laws and characteristics of the load spectrum of coal cutting, the theoretical support is provided for the study of high efficiency and highly reliable rock breaking method. In view of the randomness of the coal-rock breaking process by this method,the traditional theoretical load model has single value characteristics,which is difficult to accurately describe the load process of coal rock breaking under different cutting conditions. The theoretical deduction of the pick-to-load amplitude mode,the finite experimental load spectrum and the information entropy theory are proposed to reconstruct the theoretical and experimental cutting load spectrum. The reg- ularized neural network is used to model the reconstructed load spectrum. According to the least square method,the load curve family based on the limited wedge angle is proposed to predict the load spectrum of different wedge angles. Combining the load profiles of different parameters with the wedge angle within 30°-50°,taking the load spectrum and theoretical derivation model of different wedge angles as examples,the load spectrum reconstructed under different wedging angles is compared with that modeled regularized neural network,and the load prediction for different wedging angles is also analyzed. The results suggest that the theoretical deduction model of cutting resistance process response is constructed,and the reconstructed load spectrum under wedge angles within 30°-50° is obtained by the combination of theories and experiments. The characterization of load spectrum amplitude and variation law is achieved,and the regularized neural network modeling method of reconstructed load spectrum is obtained. The load profiles under wedge angles of 30°,33°,50°,and 55°are predicted according to the established load prediction models with different wedge angles. The correlation between the predicted load spectrum with the angles of 30° and 50° and the regularized neural network modeled reconstruction load spectrum is 0. 971 7 and 0. 983 9 respectively,which is highly correlated. The relative errors of the amplitude are 4. 04% and 5. 21% respectively. It is verified that the model can represent the load amplitude and the load history of cutting coal and rock. The model has some ad-vantages which provides a reference for the study of the crushing mechanism.