The generation of 1/f noise is closely related to the quality defects of IGBT devices. In the process of detecting single-tube noise of IGBT, thermal noise and shot noise show obvious white noise characteristics in the low-frequency range. This paper investigates how to accurately detect the 1/f noise under strong white noise, and thus proposes a particle swarm optimization method known as variational mode decomposition. First, the particle swarm optimization algorithm was used twice to search the optimal parameter combination between the penalty parameter and the decomposition modulus of the VMD model. Then, the parameters of the variational mode decomposition algorithm were set in optimal parameter combination. The frequency center and bandwidth of each IMF component were determined by continuous iteration in the variational framework. Finally, the 1/f noise signal was adaptively separated from background noise. Extensive experimental investigations carried out under different signal-to-noise ratios, compared with the optimal wavelet denoising algorithm, revealed that the PSO-VMD algorithm improved the signal-to-noise ratio by 6.6%, 16.82%, and 42.48%, whereas the mean square error is reduced by 7.12%, 19.80%, and 33.76%.
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