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Prediction and Analysis of Acoustic Displacement Field Using the Method of Neural Network

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Neural Information Processing (ICONIP 2023)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1961))

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Abstract

Micro/nano manipulation technology holds significant value in diverse fields, such as biomedicine, precision killing, and material chemistry. Among these applications, acoustic manipulation technology stands out as a crucial approach for micro/nano manipulation. However, the determination of a control equation for acoustic manipulation proves challenging due to the complex motion characteristics exhibited by micro/nano targets. The mastery of acoustic displacement field information is essential for successful manipulation of micro targets. Addressing this challenge, this paper presents a novel method that utilizes neural networks for predicting sound wave displacement fields. Which involves collecting raw data on acoustic displacement changes under specific excitation frequencies and times utilizing the acoustic manipulation experimental platform. Using the data to train the neural network model. The network takes the initial position information of the micro target as input and accurately predicts the displacement field across the entire thin plate area, achieving a remarkable prediction accuracy of 0.5mm. Through a comprehensive analysis of the network’s prediction performance using test set data, the effectiveness of the designed network in solving the acoustic displacement field problem with high accuracy is demonstrated. This research significantly contributes to the advancement of acoustic manipulation technology, enabling precise control and manipulation of micro/nano targets across various applications.

Supported by College of Artificial Intelligence, Nankai University.

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Acknowledgment

This work was supported by the National Natural Science Foundation of China (Grant No. 61973172, 62003177, 62103204, 62003175 and 61973175), Joint Fund of the Ministry of Education for Equipment Pre research (Grant No. 8091B022133) and General Terminal IC Interdisciplinary Science Center of Nankai University.

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Authors and Affiliations

  1. College of Artificial Intelligence, Nankai University, Tianjin, China

    Xiaodong Jiao, Hao Sun & Qinglin Sun

  2. Silo AI, Helsinki, 00100, Finland

    Jin Tao

Authors
  1. Xiaodong Jiao
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  2. Jin Tao
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  3. Hao Sun
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  4. Qinglin Sun
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Corresponding authors

Correspondence to Hao Sun or Qinglin Sun .

Editor information

Editors and Affiliations

  1. School of Automation, Central South University, Changsha, China

    Biao Luo

  2. Institute of Automation, Chinese Academy of Sciences, Beijing, China

    Long Cheng

  3. Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou, China

    Zheng-Guang Wu

  4. School of Automation, Guangdong University of Technology, Guangzhou, China

    Hongyi Li

  5. School of Electrical Engineering and Telecommunications, UNSW Sydney, Sydney, NSW, Australia

    Chaojie Li

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Jiao, X., Tao, J., Sun, H., Sun, Q. (2024). Prediction and Analysis of Acoustic Displacement Field Using the Method of Neural Network. In: Luo, B., Cheng, L., Wu, ZG., Li, H., Li, C. (eds) Neural Information Processing. ICONIP 2023. Communications in Computer and Information Science, vol 1961. Springer, Singapore. https://doi.org/10.1007/978-981-99-8126-7_11

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  • DOI: https://doi.org/10.1007/978-981-99-8126-7_11

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