scholarly journals Simulating Displacement and Velocity Signals by Piezoelectric Sensor in Vibration Control Applications

2012 ◽  
Vol 2012 ◽  
pp. 1-7 ◽  
Author(s):  
G. J. Sheu ◽  
S. M. Yang ◽  
W. L. Huang
Keyword(s):  
Vibration Control ◽  
Vibration Suppression ◽  
Piezoelectric Sensor ◽  
Smart Structure ◽  
Velocity Signal ◽  
Active Mass ◽  
Mass Damper ◽  
Active Mass Damper ◽  
Physical Geometry ◽  
Neural Sensor

Intelligent structures with built-in piezoelectric sensor and actuator that can actively change their physical geometry and/or properties have been known preferable in vibration control. However, it is often arguable to determine if measurement of piezoelectric sensor is strain rate, displacement, or velocity signal. This paper presents a neural sensor design to simulate the sensor dynamics. An artificial neural network with error backpropagation algorithm is developed such that the embedded and attached piezoelectric sensor can faithfully measure the displacement and velocity without any signal conditioning circuitry. Experimental verification shows that the neural sensor is effective to vibration suppression of a smart structure by embedded sensor/actuator and a building structure by surface-attached piezoelectric sensor and active mass damper.

Vibration Control of Smart Structures by Using Neural Networks

1997 ◽  
Vol 119 (1) ◽  
pp. 34-39 ◽  
Author(s):  
S. M. Yang ◽  
G. S. Lee
Keyword(s):  
Neural Networks ◽  
System Identification ◽  
Vibration Control ◽  
Vibration Suppression ◽  
Piezoelectric Sensor ◽  
Smart Structure ◽  
The Third ◽  
Parameter Variations ◽  
Physical Geometry ◽  
On Line

Smart structure with build-in sensor(s) and actuator(s) that can actively and adoptively change its physical geometry and properties has been considered one of the best candidates in vibration control applications. Implementation of neural networks to system identification and vibration suppression of a smart structure is conducted in this paper. Three neural networks are developed, one for system identification, the second for on-line state estimation, and the third for vibration suppression. It is shown both in analysis and in experiment that these neural networks can identify, estimate, and suppress the vibration of a composite structure by the embedded piezoelectric sensor and actuator. The controller is also shown to be robust to system parameter variations.

A Study for Vibration Control of a Nonlinear Multi-flexibility Structure using Active Mass Damper

2003 ◽  
Vol 2003.41 (0) ◽  
pp. 307-308
Author(s):  
Toru Takashiba ◽  
Junichi Hino ◽  
Toshio Yoshimura ◽  
Masao Kurimoto
Keyword(s):  
Vibration Control ◽  
Active Mass ◽  
Mass Damper ◽  
Active Mass Damper

Vibration Control for High-Speed Elevator using Active Mass Damper : Controller Design for 2-DOF Model

2003 ◽  
Vol 2003.12 (0) ◽  
pp. 151-154
Author(s):  
Sawako ITOH ◽  
Takayoshi KAMADA ◽  
Masao NAGAI ◽  
Masaaki HIRAI ◽  
Yoshiaki FUJITA ◽  
...  
Keyword(s):  
Vibration Control ◽  
High Speed ◽  
Controller Design ◽  
Active Mass ◽  
Mass Damper ◽  
Active Mass Damper
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