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Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles.

Zhu, Q and Xiao, C and Hu, H and Liu, Y and Wu, J (2018) 'Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles.' Sensors, 18 (1). ISSN 1424-2818

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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.

Item Type: Article
Uncontrolled Keywords: articulated heavy vehicles, attitude and heading reference systems, multi-sensor system, rollover stability, vehicle safety
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Elements
Date Deposited: 26 Jun 2018 14:08
Last Modified: 26 Jun 2018 14:08

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