School of Safety Engineering, North China Institute of Science and Technology

针对瓦斯测压过程中读取数据误差大、操作不方便和周期性长等问题，研发了一套远程、实时在线监测装置，并利用Python多项式回归对数据进行分析预测。研究结果显示，利用传感器、网络交换机和数据监测系统实现了钻孔瓦斯压力远程、精准、实时在线监测，同时相比传统的一元线性回归方法，Python多项式回归方法对数据的拟合度更高预测更准确，有效缩短了测压时间。

Aiming at the problems of large reading data error, inconvenient operation and long periodicity in the process of gas pressure measurement, a set of remote and real-time online monitoring device is developed, and Python polynomial regression is used to analyze and predict the data. The research results show that the remote, accurate and real-time online monitoring of borehole gas pressure is realized by using sensors, network switches and data monitoring system. At the same time, compared with the traditional linear regression method, Python polynomial regression method has higher fitting degree and more accurate prediction of data, which effectively shortens the pressure measurement time.

谢凯熙，王声远，齐黎明. 基于Python多项式回归的钻孔瓦斯压力预测与应用[J]. 煤炭与化工, 2024, 47(3): 103- 106，111..

Xie Kaixi, Wang Shengyuan, Qi Liming. Prediction and application of borehole gas pressure based on Python polynomial regression. CCI, 2024, 47(3): 103- 106，111..