Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles
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-...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2018-01-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/18/1/212 |
| _version_ | 1828394502342049792 |
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| author | Qingyuan Zhu Chunsheng Xiao Huosheng Hu Yuanhui Liu Jinjin Wu |
| author_facet | Qingyuan Zhu Chunsheng Xiao Huosheng Hu Yuanhui Liu Jinjin Wu |
| author_sort | Qingyuan Zhu |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-10T07:56:46Z |
| format | Article |
| id | doaj.art-ef0b58c921bc4a1c8cdce402016f98c9 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-12-10T07:56:46Z |
| publishDate | 2018-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-ef0b58c921bc4a1c8cdce402016f98c92022-12-22T01:56:54ZengMDPI AGSensors1424-82202018-01-0118121210.3390/s18010212s18010212Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy VehiclesQingyuan Zhu0Chunsheng Xiao1Huosheng Hu2Yuanhui Liu3Jinjin Wu4Department of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361005, ChinaDepartment of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361005, ChinaSchool of Computer Science & Electronic Engineering, University of Essex, Wivenhoe Park, Colchester CO4 3SQ, UKDepartment of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361005, ChinaDepartment of Mechanical and Electrical Engineering, Xiamen University, Xiamen 361005, ChinaArticulated 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.http://www.mdpi.com/1424-8220/18/1/212articulated heavy vehiclesmulti-sensor systemattitude and heading reference systemsrollover stabilityvehicle safety |
| spellingShingle | Qingyuan Zhu Chunsheng Xiao Huosheng Hu Yuanhui Liu Jinjin Wu Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles Sensors articulated heavy vehicles multi-sensor system attitude and heading reference systems rollover stability vehicle safety |
| title | Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles |
| title_full | Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles |
| title_fullStr | Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles |
| title_full_unstemmed | Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles |
| title_short | Multi-Sensor Based Online Attitude Estimation and Stability Measurement of Articulated Heavy Vehicles |
| title_sort | multi sensor based online attitude estimation and stability measurement of articulated heavy vehicles |
| topic | articulated heavy vehicles multi-sensor system attitude and heading reference systems rollover stability vehicle safety |
| url | http://www.mdpi.com/1424-8220/18/1/212 |
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