基于滑动平均滤波的矿用光离子化传感器设计

Design of Mine Photoionization Sensor Based on Moving Average Filtering

针对矿山中常见的尘埃、湿气和振动等干扰,提出了一种新颖的滤波方案,采用滑动平均滤波技术对传感器输出进行实时处理,以降低噪声和抑制干扰信号。为验证所提滤波方案的有效性,进行了一系列实验。实验结果表明,与传统传感器相比,基于滑动平均滤波的矿用光离子化传感器在尘埃密集、湿度较高和机械振动较剧烈的矿山环境中表现出更强的抗干扰能力和更为稳定的输出性能。同时,该传感器还表现出更长的使用寿命和更低的维护成本,极大地提高了矿山监测系统的可靠性和经济性。

In response to common disturbances such as dust,moisture,and vibration in mine,proposed a novel filtering scheme that uses moving average filtering technology to process the sensor output in real-time to reduce noise and suppress interference signals.To verify the effectiveness of the proposed filtering scheme,a series of experiments were conducted.The experimental results show that compared with traditional sensors,the mining photoionization sensor based on moving average filtering exhibits stronger anti-interference ability and more stable output performance in mining environments with dense dust,high humidity and severe mechanical vibration.At the same time,the sensor also exhibits a longer service life and lower maintenance costs,greatly improves the reliability and economy of the mine monitoring system.