Texture analysis using a piezoelectric actuator-sensor pair

Jaehoon Chung, Myotaeg Lim, Youngsu Cha

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    In this paper, we propose a piezoelectric actuator-sensor pair that can classify several objects. It consists of two polyvinylidene-fluoride films above a polyethylene-terephthalate substrate. Herein, the actuator is connected to an voltage supplier, and the sensor output signal is acquired through a measuring equipment. Specifically, this pair is installed on a robot hand. When the objects are grasped by the robot hand in static state, the actuator oscillates as sinusoidal input voltages with frequency sweep are applied for a few seconds. At the same time, the sensor data is obtained and undergoes preprocessing procedure for learning process. The neural network classifier model is trained by learning process. After conducting the learning process, we test the feasibility of the actuator-sensor pair by demonstrating the real-time recognition system.

    Original languageEnglish
    Title of host publicationActive and Passive Smart Structures and Integrated Systems IX
    EditorsJae-Hung Han, Gang Wang, Shima Shahab
    PublisherSPIE
    ISBN (Electronic)9781510635296
    DOIs
    Publication statusPublished - 2020
    EventActive and Passive Smart Structures and Integrated Systems IX 2020 - None, United States
    Duration: 2020 Apr 272020 May 8

    Publication series

    NameProceedings of SPIE - The International Society for Optical Engineering
    Volume11376
    ISSN (Print)0277-786X
    ISSN (Electronic)1996-756X

    Conference

    ConferenceActive and Passive Smart Structures and Integrated Systems IX 2020
    Country/TerritoryUnited States
    CityNone
    Period20/4/2720/5/8

    Bibliographical note

    Funding Information:
    This work was supported by the Technology Innovation Program for Development of robotic work control technology capable of grasping and manipulating various objects in everyday life environment based on multimodal recognition and using tools funded by the Ministry of Trade, Industry, and Energy under grant number 20001856. The authors would like to thanks Chaewon Oh for helps with drawing schematics.

    Publisher Copyright:
    © 2020 SPIE.

    Keywords

    • Actuator-sensor pair
    • Object classification
    • Piezoelectric material

    ASJC Scopus subject areas

    • Electronic, Optical and Magnetic Materials
    • Condensed Matter Physics
    • Computer Science Applications
    • Applied Mathematics
    • Electrical and Electronic Engineering

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