基于自适应T-ATFPF算法的1/f噪声检测方法

CONVERTER Pub Date : 2021-07-29 DOI:10.17762/converter.304
Jie Wu, Xiaojuan Chen, Z. Zhang
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引用次数: 0

摘要

1/f噪声的产生与IGBT器件的质量缺陷密切相关。在检测IGBT单管噪声的过程中,热噪声和散弹噪声在低频段表现出明显的白噪声特征,在强白噪声背景下进行检测,1/f噪声可以表征IGBT器件的性能。为此,在时频峰值滤波(TFPF)算法的基础上,提出了一种二维时域自适应T-ATFPF算法,并利用基于切比雪夫不等式的置信区间交叉准则实现自适应分割。可变窗长,用较小的窗长对信号段进行处理,保留了有效信号更详细的信息。使用较大的窗口长度来处理缓冲部分,以确保平稳过渡。采用大窗长对噪声段进行处理,更有效地抑制了噪声的随机性,将T-ATFPF应用于人工合成模型和实际模型。实验结果表明,与传统算法相比,改进后的方法能更好地恢复1/f噪声,信噪比大幅提高约1.3dB。
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An Approach to 1/f Noise Detection Based on Adaptive T-ATFPF Algorithm
The generation of 1/f noise is closely related to the quality defects of IGBT devices. In the process of detecting IGBT single tube noise, thermal noise and shot noise show obvious white noise characteristics in the low frequency band, which are detected under the background of strong white noise 1/f noise can characterize the performance of IGBT devices. Therefore, on the basis of the Time-Frequency Peak Filtering (TFPF) algorithm, a two-dimensional time-domain adaptive T-ATFPF algorithm is proposed, and the adaptive segmentation is realized by means of the confidence interval crossing criterion based on Chebyshev’s inequality. Variable window length,use a small window length to process the signal section, which retains more detailed information of the effective signal.Use a larger window length to process the buffer section to ensure a smooth transition.Use the large window length to process the noise section, which more effectively suppresses randomness for noise, apply T-ATFPF to artificial synthesis model and actual model. Experimental results indicate that compared with the conventional algorithm, the improved method can better recover 1/f noise, and the ratio of signal to noise is greatly improved by about 1.3dB.
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