• The method uses wavelet transform and principle component analysis to preprocess fault signal, afterward training and testing wavelet neural network with the preprocessed fault characteristic data.

    方法首先利用变换成分分析故障信号进行预处理然后处理后的故障特征数据对小波神经网络进行训练测试

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  • In addition, creation of digital maps base on MFL signal after preprocessed, clear visual display wall of the overall situation.

    同时预处理漏磁信号分析为依据创建清晰直观地显示管壁整体状况。

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  • The MLR mathematical model that established with orthogonal signal correction plus first derivative and mean centre preprocessed spectra shows the best result for glucose and fructose.

    研究结果表明,原始光谱均值中心化、阶微分正交信号校正预处理后,运用多元线性回归法所建葡萄糖果糖定量分析模型优。

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  • The MLR mathematical model that established with orthogonal signal correction plus first derivative and mean centre preprocessed spectra shows the best result for glucose and fructose.

    研究结果表明,原始光谱均值中心化、阶微分正交信号校正预处理后,运用多元线性回归法所建葡萄糖果糖定量分析模型优。

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