基于卡尔曼滤波的智能消防头盔系统研究  

Research on smart fire helmet system based on Kalman filter

作　　者：赵孟轩 赵祺 吕展博 刘国宁[1] Zhao Mengxuan;Zhao Qi;Lv Zhanbo;Liu Guoning(School of Mechanical and Power Engineering,Zhengzhou University,Henan Zhengzhou 450001,China)

机构地区：[1]郑州大学机械与动力工程学院,河南郑州450001

出　　处：《消防科学与技术》2023年第4期545-548,554,共5页Fire Science and Technology

基　　金：河南省产学研重点支持项目(172107000008)。

摘　　要：为了消防员可以准确了解火场情况,设计了一种基于卡尔曼滤波的智能消防头盔系统,该头盔集成了微控制器系统、气体传感器、温度传感器、无线通信模块、佩戴异常检测、报警装置等功能,据此设计系统的软件和硬件。硬件系统以STM32为处理核心,定位采用GPS无线定位模块和惯性导航定位模块相互补偿技术,同时包括环境信息采集传感器等。软件上应用卡尔曼滤波算法对采集的数据进行处理,减小了传感器延时性和噪声对系统测量的影响,以达到对系统状态的准确预测,同时姿态检测算法实现了对消防员状态的准确识别,并对监测系统软件进行了验证。对智能消防头盔进行了人机工学分析,将各部件融合在头盔上。经测试,该系统运行稳定、准确率高。In order for firefighters to accurately understand the fire situation,we design a smart helmet system based on kalman filter which has integrated the microcontroller system,gas sensors,temperature sensors,wireless communication module,anomaly wearing detection module and alarm module,and the system design consists of the design of software system and hardware system.The hardware system takes the STM32 microprocessor as the core,and wireless GPS module is adopted together with inertial navigation module for the purpose of higher positioning owing to their compensation effects.And it also includes an environmental information acquisition sensor.On the software,the Kalman filtering algorithm is applied to process the collected data,which reduces the influence of sensor delay and noise on the system measurement,so as to achieve accurate prediction of the system state,and the monitoring system software was verified.At the same time,the attitude detection algorithm realizes the accuracy of the firefighter state identify.This paper also conducts an ergonomic analysis of the intelligent fire helmet,and integrates the various components on the helmet.After testing,the system runs stably and has high accuracy.

关 键 词：消防头盔 卡尔曼滤波 定位技术 人机工学 

分 类 号：TP274[自动化与计算机技术—检测技术与自动化装置] TP212[自动化与计算机技术—控制科学与工程]