Convolutional neural networks for robust angular measurement with xMR sensor arrays

被引：5
|
作者：
Meier, Phil [1 ]
Rohrmann, Kris [1 ]
Sandner, Marvin [1 ]
Streitenberger, Martin [2 ]
Prochaska, Marcus [1 ]
机构：
[1] Ostfalia Univ Appl Sci, Fac Elect Engn, Wolfenbuettel, Germany
[2] Univ Appl Sci & Arts, Fac Elect Engn, Hannover, Germany
来源：
2019 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC) | 2019年
关键词：
xMR; magnetoresistive sensors; sensor array; neural network; ALGORITHM; SPEED;
D O I：
10.1109/i2mtc.2019.8827051
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The contactless and wear-free measurement of angles, rotational speeds and currents is of prime importance for many industrial applications with several different measurement setups and concepts in use. In the automotive area the deployment of magnetic field sensors based on Hall- or magnetoresistive-(MR) effects increases steadily. Especially MR-based sensors play a dominant role in angular position sensing applications because of their high accuracy and robustness. Nevertheless, upcoming vehicle concepts lead to increasing requirements for such sensors, which cannot be fulfilled by the applied concepts completely. However, in many application fields artificial neural networks have proven the capability to enhance existing solutions. Therefore, in this paper the potential use of neural network computing is examined with regard to stray field immunity for xMR angular position sensors.
引用
收藏
页码：1393 / 1398
页数：6
相关论文
共 50 条
  • [11] Robust Fingerprint Matching Based on Convolutional Neural Networks
    Zhu, Yanming
    Yin, Xuefei
    Hu, Jiankun
    MOBILE NETWORKS AND MANAGEMENT (MONAMI 2017), 2018, 235 : 56 - 65
  • [12] Robust face alignment using convolutional neural networks
    Duffner, Stefan
    Garcia, Christophe
    VISAPP 2008: PROCEEDINGS OF THE THIRD INTERNATIONAL CONFERENCE ON COMPUTER VISION THEORY AND APPLICATIONS, VOL 2, 2008, : 30 - 37
  • [13] Robust Place Recognition using Convolutional Neural Networks
    Lugo Sanchez, Omar E.
    Sossa, Humberto
    Zamora, Erik
    COMPUTACION Y SISTEMAS, 2020, 24 (04): : 1589 - 1605
  • [14] Robust Spatial Filtering With Graph Convolutional Neural Networks
    Such, Felipe Petroski
    Sah, Shagan
    Dominguez, Miguel Alexander
    Pillai, Suhas
    Zhang, Chao
    Michael, Andrew
    Cahill, Nathan D.
    Ptucha, Raymond
    IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 2017, 11 (06) : 884 - 896
  • [15] Robust face analysis using convolutional neural networks
    Fasel, B
    16TH INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION, VOL II, PROCEEDINGS, 2002, : 40 - 43
  • [16] Robust smile detection using convolutional neural networks
    Bianco, Simone
    Celona, Luigi
    Schettini, Raimondo
    JOURNAL OF ELECTRONIC IMAGING, 2016, 25 (06)
  • [17] Robust spatial filtering with graph convolutional neural networks
    2017, arXiv
  • [18] Fast and Robust Compression of Deep Convolutional Neural Networks
    Wen, Jia
    Yang, Liu
    Shen, Chenyang
    ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, ICANN 2020, PT II, 2020, 12397 : 52 - 63
  • [19] Accelerating Sparse Convolutional Neural Networks with Systolic Arrays on FPGA
    Nehete, Hemkant
    Verma, Gaurav
    Yadav, Shailendra
    Kaushik, Brajesh Kumar
    APPLICATIONS OF MACHINE LEARNING 2023, 2023, 12675
  • [20] An object recognition system based on convolutional neural networks and angular resolutions
    Achmad Lukman
    Chuan-Kai Yang
    Multimedia Tools and Applications, 2021, 80 : 16059 - 16085
12345