冻结站制冷盐水循环系统智能解耦控制

Intelligent decoupling control of freezing station refrigeration brine circulation system

目前煤炭井筒开拓大多采用冻结法凿井,积极冻结期和消极冻结期所需的盐水循环量和温度不同,实际工程根据传统经验采用人工调节管道阀门控制盐水循环,调节螺杆压缩机控制阀控制制冷量,调节精度不够,且造成大量的电能浪费。在已知冻结壁与地层热交换所需制冷量时,可以调节循环盐水温度和流量实现对制冷量的控制。但盐水温度和流量之间存在复杂的耦合关系,设计一个基于模糊神经网络解耦的控制策略实现盐水流量和温度的智能解耦,对冻结站设备实现精确控制。仿真结果表明,可以有效地控制盐水流量和盐水温度,按需控制设备的运转,节约大量的电能,提高经济效益。

At present, coal shaft pioneering mostly uses the freezing shaft sinking method, positive and negative freezing period require different brine circulation and temperature. According to the traditional experience, the practical engineering adjusts pipe valve to control brine circulation, and adjusts screw refrigeration compressor control valve to control refrigerating capacity both in manual work, the precision is not enough and this could cause a lot of energy waste. When the cooling capacity needed in heat exchange between the freezing wall and strata was known, the circulating brine temperature and flow control could be adjusted to achieve the cooling capacity. But the relation between water temperature and flow is complex coupling, an intelligent decoupling control strategy based on fuzzy neural network decoupling of brine flow rate and temperature of freezing was designed, which could realize accurate control. Simulation results show that can effectively control the brine flow and brine temperature, control equipment operation according to the actual needs, save power and make economic benefit.