Zhu Qingyuan, Xiao Chunsheng, Hu Huosheng, Liu Yuanhui, Wu Jinjin
Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361005, China.
School of Computer Science & Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UK.
Sensors (Basel). 2018 Jan 13;18(1):212. doi: 10.3390/s18010212.
Articulated wheel loaders used in the construction industry are heavy vehicles and have poor stability and a high rate of accidents because of the unpredictable changes of their body posture, mass and centroid position in complex operation environments. This paper presents a novel distributed multi-sensor system for real-time attitude estimation and stability measurement of articulated wheel loaders to improve their safety and stability. Four attitude and heading reference systems (AHRS) are constructed using micro-electro-mechanical system (MEMS) sensors, and installed on the front body, rear body, rear axis and boom of an articulated wheel loader to detect its attitude. A complementary filtering algorithm is deployed for sensor data fusion in the system so that steady state margin angle (SSMA) can be measured in real time and used as the judge index of rollover stability. Experiments are conducted on a prototype wheel loader, and results show that the proposed multi-sensor system is able to detect potential unstable states of an articulated wheel loader in real-time and with high accuracy.
建筑行业中使用的铰接式轮式装载机是重型车辆，由于其在复杂作业环境中车身姿态、质量和质心位置的不可预测变化，稳定性较差且事故发生率较高。本文提出了一种用于铰接式轮式装载机实时姿态估计和稳定性测量的新型分布式多传感器系统，以提高其安全性和稳定性。使用微机电系统（MEMS）传感器构建了四个姿态和航向参考系统（AHRS），并安装在铰接式轮式装载机的前车身、后车身、后轴和动臂上，以检测其姿态。系统中采用互补滤波算法进行传感器数据融合，从而能够实时测量稳态裕度角（SSMA），并将其用作翻车稳定性的判断指标。在一台原型轮式装载机上进行了实验，结果表明所提出的多传感器系统能够实时、高精度地检测铰接式轮式装载机的潜在不稳定状态。
