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An Acoustic Discrimination Method for Impact Load Based on Artificial Neural Network

  • Zhenhan Wang
  • , Li Ma
  • , Qianru Zhan
  • , Qinghua Li
  • , Fuguo Li
  • Northwestern Polytechnical University Xian

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

In order to meet the engineering requirements of non-contact measurement of impact load and realize the intelligent identification of its characteristic parameters, this paper attempts to establish a method to analyze and learn the audio characteristics generated by accidental loads, such as impact and explosion, and to identify the impact load characteristics in reverse. The method, which is based on energy conservation, momentum conservation and strokes law, used p-norm in mathematics to extract the basic characteristics of impact load, and the frequency analysis to find the inevitable connection between the audio characteristics impulse-induced and the impact load characteristics. At last, "Acoustic Discrimination for Impact Load Identification (ADII)" by adopting the functions of artificial neural networks about learning, categorization and generalization was implemented.

Original languageEnglish
Article number012032
JournalIOP Conference Series: Earth and Environmental Science
Volume455
Issue number1
DOIs
StatePublished - 24 Mar 2020
Event6th International Conference on Environmental Science and Civil Engineering, ESCE 2020 - Nanchang, China
Duration: 4 Jan 20205 Jan 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Impact load
  • acoustic discrimination
  • artificial neural network
  • characteristic identification

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