research-article

A Study on the Extraction Method of Wheel Rotation Signal Characteristic Quantity

Authors:

Yuqing LiuAuthors Info & Claims

AIAM2020: Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture

Pages 284 - 289

https://doi.org/10.1145/3421766.3421858

Published: 26 October 2020 Publication History

Abstract

Wheel rotation parameter is one of the key parameters reflecting driving safety. The existing characteristic quantity of wheel rotation signal adopts an extraction method of wheel radial acceleration curve, by which the measurement range of wheel radial acceleration sensor is quite large, with low sensitivity and resolution ratio, which is difficult to express the true status of radial acceleration and extract characteristic quantity of wheel rotation signal accurately. This article proposes a new method to extract characteristic quantity of wheel rotation signal through the curve of tangential acceleration. To acquire the tangential acceleration signal by installing an acceleration unit on the wheel, apply wavelet packet to make wavelet de-noising on the wheel tangential acceleration signal and then extract the characteristic quantity of wheel rotation signal by STFT. The experimental results indicate that the measuring error of wheel frequency under experimental conditions is -0.79%. This new approach can realize the high-precision measurement on the characteristic quantity of wheel rotation signal, and make further efforts to monitor and evaluate wheel brake performance.

References

[1]

Mueller F, Wenzel A. Intelligent monitoring and adaptive competence assignment for driver and vehicle [J]. IEEE Intelligent Vehicles Symposium, 2007, (1): 1254--1259.

[2]

Liu Guixiong, Pan Mengyao, Xu Jianlong, Gao Yi. vehicle wheel rotational signal characteristics extraction technology base on tangential acceleration curve: ZL2011101532308 [P].2011.06.

[3]

Pan Mengyao, Wang Feng, Huan Ruitie, Zhong Yuling. A dynamic monitoring method and system for vehicle wheel safety performance:ZL201810742552.8 [P]. 2019.08.

[4]

Li Donglin, LIN Tusheng. Analysis of automobile braking performance monitoring using tire accelerometers [J]. Transducerand Mierosystem Technologies. 2006, 25(12): 15--17.

[5]

Pan Mengyao. Study on the novel mode of vehicle operating safe state monitoring [D]. Guangzhou: South China University of Technology, 2012.

[6]

Mengyao Pan, Guixiong Liu. Study on vehicle operating safe state monitoring parameter and measurement model [J]. Procedia Engineering, 2012, (29):2496--2500.

[7]

Chen Zehao, Xu Yongpeng, Li Zhe, et al.Leakage current analysis of DC cable based on wavelet packet decomposition [J]. Chinese Journal of Scientific Instrument, 2018, 39(9): 163--170.

[8]

Xin Yuanming, Tan Feng, Tian Fangming. Research on denoising method of plant electrical signal based on wavelet transform [J]. Journal of Electronic Measurement and Instrument, 2019, 33(12): 190--196.

[9]

Yan Jiahan, Guo Chengjun. Research on SINS attitude calculation algorithm based on Elman neural network [J].Journal of Electronic Measurement and Instrument.2018, 32(06):1--5.

[10]

Shi Gang, Li Xisheng, Wang Zhe, Bai Yanru, Zheng Chengcai. Research on correcting output attitude information of magnetic sensor [J].Chinese Journal of Scientific Instrument.2019, 40(03):47--53.

[11]

Yan Yan, Xing Hongyan. Sea clutter de-noising based on wavelet packet multi-threshold method [J].Journal of Electronic Measurement and Instrument.2018, 32(08):172--178.

[12]

Li Yuanjun, Sun Jixuan. Car motor bearing fault diagnosis based on fault feature extraction and recognition stages[J].Journal of Electronic Measurement and Instrument.2019, 33(02):56--63.

[13]

Jiang Dong, Zhao Yanchao, Wang Deyu. Research on highway flatness measurement based on wavelet analysis [J].Journal of Electronic Measurement and Instrument.2020, 34(01):17--24.

[14]

NXP Semiconductors.MMA1200D Datasheet [M]. www.nxp.com.cn, 2020.

[15]

NXP Semiconductors.MMA6900 Datasheet [M]. www.nxp.com.cn, 2020.

Cited By

Mengyao PShaowei CFeng WRuitie HYuqing L(2021)Novel technology for acquiring wheel motion attitude information based on WEIS2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)10.1109/IPEC51340.2021.9421265(368-375)Online publication date: 14-Apr-2021
https://doi.org/10.1109/IPEC51340.2021.9421265

Index Terms

A Study on the Extraction Method of Wheel Rotation Signal Characteristic Quantity
1. Applied computing
  1. Physical sciences and engineering
    1. Engineering
      1. Computer-aided design

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AIAM2020: Proceedings of the 2nd International Conference on Artificial Intelligence and Advanced Manufacture

October 2020

566 pages

ISBN:9781450375535

DOI:10.1145/3421766

Copyright © 2020 ACM.

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Association for Computing Machinery

New York, NY, United States

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Published: 26 October 2020

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AIAM2020

AIAM2020: 2nd International Conference on Artificial Intelligence and Advanced Manufacture

October 15 - 17, 2020

Manchester, United Kingdom

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AIAM2020 Paper Acceptance Rate 100 of 285 submissions, 35%;

Overall Acceptance Rate 100 of 285 submissions, 35%

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Cited By

Mengyao PShaowei CFeng WRuitie HYuqing L(2021)Novel technology for acquiring wheel motion attitude information based on WEIS2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC)10.1109/IPEC51340.2021.9421265(368-375)Online publication date: 14-Apr-2021
https://doi.org/10.1109/IPEC51340.2021.9421265

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