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:针对工业过程中存在的高频采样数据重构问题 ,本文提出了一种基于小波多尺度分析理论的误差递阶补偿算法 .首先对含有噪声的低频采样数据在时频域进行滤波 ,然后利用该逼近算法实现高频采样数据的重构 ,并给出了算法的精度分析 .此算法具有能克服噪声影响、重构精度高和物理意义明确的特点 .
In order to solve the problem of high-frequency sampling data reconstruction in industrial process, this paper presents an error-order compensation algorithm based on wavelet multi-scale analysis theory.Firstly, the low frequency sampling data containing noise is filtered in the time-frequency domain, The approximation algorithm is used to reconstruct the high-frequency sampled data, and the precision analysis of the algorithm is given.The algorithm has the characteristics of overcoming the influence of noise, high reconstruction accuracy and clear physical meaning.