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针对矿井的环境状态进行监测、诊断及预报井下环境状态,并采取相应的控制措施,这是提高矿井安全、高效生产的重要手段。由于煤矿井下的环境较为恶劣,传感监测方法受到限制,监测信息不够全面准确,依靠单一的监测手段和传统的数据处理方法难以完成,建立基于多传感器融合和BP神经网络的矿井环境监测系统是解决问题的有效途径。试验结果表明,笔者设计的基于多传感融合的矿井环境监测系统可有效评估矿井环境的安全状态。
Monitoring, diagnosing and forecasting the underground environment status according to the environmental status of the mine and taking corresponding control measures are the important means to improve the safe and efficient production of the mine. Due to the harsh environment in coal mine, the sensing monitoring method is limited, the monitoring information is not comprehensive enough and accurate, it is difficult to complete with single monitoring method and traditional data processing method. The establishment of mine environmental monitoring system based on multi-sensor fusion and BP neural network is An effective way to solve the problem. The experimental results show that the mine environmental monitoring system based on multi-sensor fusion designed by the author can effectively evaluate the safety status of mine environment.