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22 April 2020 Texture analysis using a piezoelectric actuator-sensor pair
Jaehoon Chung, Myotaeg Lim, Youngsu Cha
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Proceedings Volume 11376, Active and Passive Smart Structures and Integrated Systems XIV; 113760T (2020) https://doi.org/10.1117/12.2557976
Event: SPIE Smart Structures + Nondestructive Evaluation, 2020, Online Only
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.
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Jaehoon Chung, Myotaeg Lim, and Youngsu Cha "Texture analysis using a piezoelectric actuator-sensor pair", Proc. SPIE 11376, Active and Passive Smart Structures and Integrated Systems XIV, 113760T (22 April 2020); https://doi.org/10.1117/12.2557976
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KEYWORDS
Sensors
Actuators
Neural networks
Classification systems
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