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

机译:压电传感器在振动控制应用中模拟位移和速度信号

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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.
机译:已知具有可主动改变其物理几何形状和/或特性的内置压电传感器和致动器的智能结构在振动控制中是优选的。但是,确定压电传感器的测量值是应变率,位移还是速度信号通常是有争议的。本文提出了一种神经传感器设计来模拟传感器动态。开发了带有误差反向传播算法的人工神经网络,这样嵌入式和连接的压电传感器可以如实地测量位移和速度,而无需任何信号调节电路。实验验证表明,神经传感器对于嵌入式传感器/执行器对智能结构的振动抑制有效,而对表面附着的压电传感器和主动质量阻尼器的建筑结构振动抑制有效。

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