Construction and Application of Intelligent Regulation System for Main Gas Drainage Pipeline Based on LSTM Prediction and Pump-Valve Coordination

Objective To address the problems of strong nonlinear coupling between extraction pumps and electric valves in coal mine gas drainage trunk pipelines, as well as the lag in pure gas flow tracking and control target mismatch caused by severe fluctuations in gas emission, Methods an intelligent regulation method integrating Long Short-Term Memory (LSTM)-based trend prediction with a hierarchical "valve-first, pump-second" collaborative control strategy was proposed. A closed-loop regulation framework consisting of state perception, trend prediction, collaborative deci-sion-making, and dynamic execution was established. The LSTM model utilized pure gas flow rate, valve opening, pump frequency, and extraction negative pressure as inputs to achieve rolling pre-diction of pure gas flow over the next 3 min. A collaborative control strategy prioritizing valve adjustment and employing pump frequency regulation when necessary was developed, together with a dynamic target updating mechanism triggered by consecutive regulation failures. Compar-ative experiments were conducted based on the monitoring and control data of the gas drainage trunk pipeline at the Nanfeng Well pumping station of Jiulishan Mine. Results During periods of severe gas emission fluctuations, the maximum dynamic deviation of the pump-valve collaborative intelligent regulation was ±6.2 m3/min, while the mean absolute percentage error (MAPE) was 6.8%, representing reductions of 63% and 45% compared with manual experience-based regulation and conventional PID control, respectively (p<0.01). The average response time was reduced to 45 s, the frequency conversion actions of the extraction pump decreased from 12.4 to 6.1 times/24 h, and the unit energy consumption per pure gas flow decreased by 18.7%. The dynamic target up-dating mechanism enabled online reconstruction of control targets under gas drainage compliance constraints. Conclusions: The proposed method provides a high-precision and low-impact adaptive control approach for the regulation of coal mine gas drainage trunk pipelines.