Jinxinda Coal Industry Co., Ltd., Shanxi Coal Transportation and Sales Group

针对煤矿井下传统供电系统存在监测不足、可靠性差、故障率高、设备潜在故障无法及时发现等问题,对矿用智能供电监测与故障预警系统进行研究,在分析煤矿井下智能供电监测与故障预警系统功能要求的基础上,提出基于神经网络的矿用供电系统智能监测与故障预警系统,完成硬件系统选型和软件控制系统编程,设计了硬件系统电路图。经在山西煤炭运销集团金辛达煤业供电系统进行安装和调试,结果表明,智能监测与故障预警系统将现场采集到的数据实时上传,信息交互性强,实现对现场供电系统的可靠监测,供电系统故障预警效果明显,温度预测值与实际值之间偏差为0.57℃,误差小,能够满足现场使用要求,可为后期实现煤矿井下供电系统智能化和无人化提供参考依据。

In view of the problems of insufficient monitoring, poor reliability, high failure rate, inability to find equipment potential failures in a timely manner and others in downhole traditional power supply system in coal mines, a study is conducted on the mine used intelligent power supply monitoring and fault early warning system. Based on the analysis of the functional requirements of the downhole intelligent power supply monitoring and fault early warning system in coal mines, a neural network-based intelligent monitoring and fault early warning system for mine used power supply system is proposed. The hardware system type selection and software control system programming are completed, and the hardware system circuit diagram is designed. After installation and debugging of the power supply system in Jinxinda Coal Industry of Shanxi Coal Transportation and Sales Group, the results show that the intelligent detection and fault early warning system uploads data collected on site in real time, with strong information interaction, and achieves reliable monitoring of the on-site power supply system. The fault early warning effect of the power supply system is obvious, and the deviation between the temperature predicted value and the actual value is 0.57 ℃, the error is small, which can meet the requirements of on-site use and provide reference basis for the later realization of intelligent and unmanned downhole power supply system in coal mines.