• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control >Computer optimization of transducer transfer functions using constraints on bandwidth, ripple, and loss
【24h】

Computer optimization of transducer transfer functions using constraints on bandwidth, ripple, and loss

机译：使用带宽，纹波和损耗约束来对换能器传递函数进行计算机优化

获取原文
获取原文并翻译 | 示例
       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Transducers, having one piezoelectric layer near its half-wave resonance and N quarter-wave layers, are designed using computer optimization to adjust the thicknesses and impedances of the various layers so as to fit the resulting transfer function to a target function. An augmented Mason model is used to evaluate the transducer. Optimization of fit is by a steepest descent algorithm. Essentially error-free fits are achieved for target functions that match the underlying dynamics. By applying classical filter theory to a lumped-element transducer model, the transducers dynamics are identified as all-pole filters, which are characterized by polynomials of order N to N+1. The design methodology is tested by designing a series of low-loss transducers that explore fractional bandwidths from 45 to 116%. From these studies there appears to be constraints on the minimum Q of the poles, and other properties. Typical power transfer efficiencies of -1 dB are achieved by impedance scale matching. Using a second-order Fano bound, it is shown that the matching layers function as an optimal compensation network for low-loss flat bandpass transducers. Finally, by the inclusion of loss, lower Q poles are demonstrated with a Bessel transducer.
机译：传感器在其半波谐振附近有一个压电层，在N个四分之一波附近有传感器，这些传感器是使用计算机优化设计的，可以调节各个层的厚度和阻抗，以使最终的传递函数适合目标函数。增强的梅森模型用于评估换能器。通过最速下降算法优化拟合。对于与基础动态匹配的目标函数，基本实现了无差错拟合。通过将经典滤波器理论应用于集总换能器模型，可以将换能器动力学识别为全极点滤波器，其特征在于阶数为N到N + 1的多项式。通过设计一系列低损耗换能器来测试设计方法，这些换能器探索从45％到116％的分数带宽。从这些研究中，似乎对极点的最小Q和其他属性有限制。阻抗比例匹配可实现-1 dB的典型功率传输效率。使用二阶Fano边界，表明匹配层可作为低损耗平面带通换能器的最佳补偿网络。最后，通过包含损​​耗，可以用贝塞尔传感器演示较低的Q极。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号