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基于小波变换的分频及时移不变性，将小波变换用于示波计时电位法中重叠峰解析的研究。探讨了极化电流大小、频率和示波信号中噪音、分解次数等因素对小波变换结果的影响。实验结果表明：小波变换能从含有噪音和背景的信号中提取有用信息，使信号中重叠峰获得了较好的分离，可用于多组分的定量分析。
Based on wavelet transform frequency division and time-invariant invariance, the wavelet transform is applied to the analysis of overlapping peaks in oscillometric chronopotentiometry. The influence of the factors such as the polarization current, the frequency, the noise in the oscillometric signal and the number of decompositions on the wavelet transform results was discussed. The experimental results show that the wavelet transform can extract useful information from the signal containing noise and background, so that the overlapping peaks in the signal can be well separated and can be used for the quantitative analysis of multi-component.