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基于神经网络算法的LVDT传感器非线性补偿方法设计
Design of LVDT Nonlinear Compensation Method Based on Neural Network Algorithm
【摘要】 针对线性可变差动变压器式传感器(Linear Variable Differential Transformer,LVDT)存在非线性缺陷,提出了一种新的级联补偿方法。它是一种基于传感系统的以函数连接型人工神经网络FLANN模型为线性变量的自适应非线性补偿方法,FLANN复杂度不高却拥有高精度的优点。首先分析了LVDT传感器产生非线性的原因,然后利用神经网络算法进行非线性校正,经过实验分析与结果比对,证明了该方法具有较强的可行性、有效性,达到了理想的实验要求。
【Abstract】 Considering nonlinear defects of a linear variable differential transformer( LVDT),a new cascade compensation method was proposed. It’s an adaptive nonlinear compensation method which has a sensing system based and has a functionally-linked artificial neural network model( FLANN) taken as the linear variable.The FLANN has advantages of low complexity and high precision. Analyzing the causes of non-linearity of the LVDT sensor and then using the neural network algorithm to implement nonlinear correction and comparing the results prove both feasibility and effectiveness of this method.
【Key words】 LVDT; artificial neural network; cascade compensation; adaptive nonlinear compensation;
- 【文献出处】 化工自动化及仪表 ,Control and Instruments in Chemical Industry , 编辑部邮箱 ,2017年09期
- 【分类号】TP183;TP212
- 【被引频次】2
- 【下载频次】100