线性双折射效应是限制光学电流传感器实用化的关键因素。
Linear birefringence effect is the primary factor that makes optical current sensor unpractical.
线性双折射效应是限制光学电流互感器实用化的关键因素。
Linear birefringent effect is the primary factor that makes optical current transducer unpractical.
作者采用人工神经网络来实现光学电流互感器线性双折射效应的补偿。
The authors realize the compensation of optical current transducer's linear birefringent effect by using artificial neural networks.
本文介绍了BP神经网络的基本原理，论述了线性双折射效应的具体补偿方法，结果表明该方法具有精度高和简便实用的特点，从而是行之有效的。
The paper introduces the principle of BP neural network, analyses the way to compensate and draws a conclusion:the method has high precision and is actually effective.
线性双折射的波长积累效应涉及到用单色光模型替代复色光系统是否合理与可行的问题，因此有必要予以研究。
The wavelength accumulation effect of linear birefringence was examined in order to determine if it is reasonable and feasible to use a monochromatic light model for describing broad-band systems.
分析了强光条件下光纤非线性双折射及引起的偏振演化（NPE）效应，据此对NALM环功率传输特性基本表达式进行了修正。
Thirdly, the equations of NALM power transmission are amended including the nonlinear polarization evolution (NPE) induced by nonlinear birefringence at high input power.
分析了强光条件下光纤非线性双折射及引起的偏振演化（NPE）效应，据此对NALM环功率传输特性基本表达式进行了修正。
Thirdly, the equations of NALM power transmission are amended including the nonlinear polarization evolution (NPE) induced by nonlinear birefringence at high input power.
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