| 基于BP神经网络的压力传感器误差补偿算法研究 |
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| 引用本文： | 朱龙俊,范君艳. 基于BP神经网络的压力传感器误差补偿算法研究[J]. 仪表工业, 2012, 0(9): 32-36 |
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| 作者姓名： | 朱龙俊 范君艳 |
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| 作者单位： | 上海师范大学,上海201815 |
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| 基金项目： | 上海市“优青基金”（上海高校选拔优秀青年教师科研专项基金）资助项目 |
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| 摘 要： | 采用BP神经网络来建立扩散硅压力传感器的输出输入模型，其网络模型具有三层结构，采用改进型的差分进化算法来优化BP神经网络的权值和阀值，并在MATLAB中进行了仿真。经训练得到补偿后扩散硅压力传感器的输出满量程误差可达到0．035％，结果表明采用基于改进型差分进化算法的BP神经网络建模对提高智能差压传感器的测量准确度具有参考价值。
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| 关 键 词： | 扩散硅压力传感器 误差补偿 BP神经网络 SDE算法 |
The Research of The Pressure Sensor Error Compensation Algorithm Based on BP Neural Network |
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| Abstract: | A three layers＇ input-output model of diffused silicon pressure sensor is built using BP neural network, and then using the improved differential evolution algorithm to optimize the weights and thresholds of BP neural network in MATLAB simulation. Through the training, the compensated diffused silicon pressure sensor＇s output full-scale error can be achieved 0.035%. Theresults show that the BP neural network modeling based on the improved differential evolution algorithm is meaningful to improve the accuracy of the pressure sensor. |
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| Keywords: | Diffusion silicon pressure sensorError compensation BP neural networkSDE algorithm |
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