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首页> 外文期刊>Journal of Computational Electronics >Evaluation of a transfer function model using experimental data and numerical analysis: the case of a pyroelectric sensor
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Evaluation of a transfer function model using experimental data and numerical analysis: the case of a pyroelectric sensor

机译:利用实验数据和数值分析评估传递函数模型:热释电传感器的情况

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The purpose of this paper is to present an evaluation study of a pyroelectric sensor model implemented in MATLAB (R)/SIMULINK (R) environment. The sensor model consists of some cascaded transfer functions taking into account the material characteristics and geometrical parameters which have been synthesized in the form of thermal and electrical time constants and a global multiplying coefficient. The model was proposed by Odon to serve as an excellent basis for the analysis of the dynamic behavior of a pyroelectric sensor. The study performed is relevant to evaluate the validity of the model by comparing its simulated response to measurement obtained on a pyroelectric sensor prototype. To achieve this evaluation, an optimization algorithm is used to estimate the parameters values of the transfer function model using a succession of tests and adjustments so that the algorithm converges to and reaches the optimal solution giving an acceptable correlation between simulated and measured responses. The semi-experimental evaluation approach has been applied to two prototype sensors with pyroelectric material thicknesses of 9 and 25 mu m, respectively. In the two cases, the estimated values of the parameters were very interesting in terms of uncertainties (between 1.846 and 6.726% at 1 sigma level) and setting evidence for the existence of two global solutions, i.e., two deep minima for each prototype sensor.
机译:本文的目的是对在MATLAB(R)/ SIMULINK(R)环境中实现的热释电传感器模型进行评估研究。传感器模型由一些级联的传递函数组成,这些函数考虑了材料特性和几何参数,这些特性已以热和电时间常数以及全局倍增系数的形式合成。 Odon提出的模型为热释电传感器的动态行为分析提供了极好的基础。进行的研究与通过将模型的模拟响应与热释电传感器原型上获得的测量结果进行比较来评估模型的有效性有关。为了实现这一评估,使用优化算法通过一系列测试和调整来估计传递函数模型的参数值,以使算法收敛并达到最优解,从而在模拟响应和测量响应之间给出可接受的相关性。半实验评估方法已应用于热电材料厚度分别为9和25μm的两个原型传感器。在这两种情况下,参数的估计值在不确定性方面非常有趣(在1 sigma级别下为1.846%至6.726%),并为存在两个全局解提供了证据,即每个原型传感器有两个深度最小值。

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