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Article

Multi-Sensor Fusion and Error Compensation of Attitude Measurement System for Shaft Boring Machine

1
School of Mechanical Electronic and Information Engineering, China University of Mining and Technology, Beijing 100083, China
2
College of Mechanical and Equipment Engineering, Hebei University of Engineering, Handan 056038, China
3
Tiandi Science and Technology Co., Ltd., Beijing 100013, China
4
CCTEG Shenyang Research Institute, Fushun 113122, China
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(22), 5007; https://doi.org/10.3390/s19225007
Received: 24 October 2019 / Revised: 11 November 2019 / Accepted: 14 November 2019 / Published: 16 November 2019
(This article belongs to the Section Electronic Sensors)
To ensure that the shaft boring machine (SBM) runs along the pre-designed axis steadily, the role of the attitude measurement system is essential, but its accuracy and reliability cannot be guaranteed. Currently, there is no effective technology to meet the actual requirements, and there is a lack of relevant theoretical research in this field. Through further study of the attitude analysis method and multi-sensor fusion technology, this paper presents a dual coordinate method, which can be used to describe the attitude characteristics of the SBM. Moreover, this paper discusses the relationships between the attitude changes and the values of the angle as well as displacement and analyzes the implementation complexity and computational efficiency of related algorithms in software and hardware. According to the working characteristics of the SBM, the hardware design and the reasonable layout of the attitude measurement system are provided. Based on multi-sensor data, this paper puts forward an improved method combining a complementary filter with an extended Kalman filter (EKF) for attitude estimation and error compensation. The simulation experiments of different working processes verify the steady-state response and dynamic response performance of the method. Experimental results show that the dual coordinate method and the proposed filter are more suitable for attitude estimation of the SBM compared to other methods. View Full-Text
Keywords: shaft boring machine (SBM); attitude measurement; multi-sensor fusion; dual coordinate method; complementary filter; extended Kalman filter (EKF) shaft boring machine (SBM); attitude measurement; multi-sensor fusion; dual coordinate method; complementary filter; extended Kalman filter (EKF)
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MDPI and ACS Style

Wang, X.; Liu, J.; Liu, Y.; Fu, W.; Zhu, L. Multi-Sensor Fusion and Error Compensation of Attitude Measurement System for Shaft Boring Machine. Sensors 2019, 19, 5007. https://doi.org/10.3390/s19225007

AMA Style

Wang X, Liu J, Liu Y, Fu W, Zhu L. Multi-Sensor Fusion and Error Compensation of Attitude Measurement System for Shaft Boring Machine. Sensors. 2019; 19(22):5007. https://doi.org/10.3390/s19225007

Chicago/Turabian Style

Wang, Xinliang, Jiangong Liu, Yang Liu, Wenjun Fu, and Lei Zhu. 2019. "Multi-Sensor Fusion and Error Compensation of Attitude Measurement System for Shaft Boring Machine" Sensors 19, no. 22: 5007. https://doi.org/10.3390/s19225007

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