Overcoming Limited Fault Data: Intermittent Fault Detection in Analog Circuits via Improved GAN

Owing to the characteristics of intermittent faults (IFs), such as short duration and randomness in analog circuits, it is difficult to collect a sufficient amount of manually labeled fault data for training detection model. To this end, this article explores the application of generative adversaria...

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Veröffentlicht in:	IEEE transactions on instrumentation and measurement 2024, Vol.73, p.1-11
Hauptverfasser:	Fang, Xiaoyu, Qu, Jianfeng, Liu, Bowen, Chai, Yi
Format:	Artikel
Sprache:	eng
Schlagworte:	Analog circuits Circuit faults Circuits Convolution Discriminators Electrical fault detection Fault detection generative adversarial network (GAN) Generative adversarial networks Generators intermittent fault (IF) detection limited fault data Low pass filters Machine learning Power amplifiers spatial Fourier convolution (SFC) block Training
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