在煤矿巷道TBM掘进中，为及时识别出掘进过程中的破碎围岩状态，提出了1种基于掘进参数的煤矿巷道围岩特征识别方法。首先根据掘进中撑靴油缸行程参数的异常变化，判断TBM掘进由稳定围岩段进入破碎围岩段，由此得到围岩稳定段和转变段数据集，然后基于数据集分析掘进参数的相关性和识别能力，选取识别围岩破碎特征的掘进参数，最后使用长短期记忆(LSTM)模型进行预测，根据掘进参数预测结果分析得到识别指标，完成后续区段围岩破碎状态的识别。将该方法应用在某煤矿瓦斯治理巷道上，LSTM模型对掘进参数预测的精确度高于98%，根据预测结果计算掘进参数的相对误差百分比作为识别指标，以5%的相对误差百分比为阈值识别围岩的破碎状态，识别出在3个数据段存在破碎围岩状态，与撑靴油缸行程的判断一致，表明该方法能够有效识别围岩的破碎特征，具有智能化程度高、对施工干扰少的优点。

In the coal mine tunnel TBM excavation, in order to identify the broken surrounding rock state in time during the excavation process, a method based on tunnel excavation parameters for identifying the surrounding rock characteristics of coal mine tunnels is proposed. Firstly, according to the abnormal changes in the travel parameters of the support boot hydraulic cylinder during the excavation, it is judged that the TBM excavation has entered the broken surrounding rock section from the stable surrounding rock section, thus obtaining the data set of the stable surrounding rock section and the transitional section. Then, based on the data set, the correlation and recognition ability of the tunneling parameters are analyzed, the excavation parameters for identifying the broken rock characteristics are selected, and finally, a long short-term memory (LSTM) model is used for prediction. According to the prediction results of the excavation parameters, the identification index is obtained, and subsequent identification of the rock breaking state in the following sections is completed. This method is applied in a gas control tunnel of a coal mine, and the precision of the LSTM model in predicting the excavation parameters is higher than 98%. Based on the prediction results, the relative error percentage of the excavation parameters is calculated as an identification index. With a threshold of 5% relative error percentage, the identified rock breaking state exists in three data segments, which is consistent with the judgment of the support boot hydraulic cylinder travel. This shows that this method can effectively identify the broken rock characteristics of the surrounding rock, and has the advantages of high intelligence level and little interference in construction.