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A plug-and-play data processing module for complex faults diagnosis
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AI
DOI：10.1016/j.isatra.2025.07.061.png)
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Abstract
En 中文
• A new method of data enhancement, APCUP, has been proposed. This method expands the sample size and considers complex fault types, effectively increasing the model's accuracy. • A technique known as ALS is developed to create a more reasonable transition between failure categories, prevent overly absolute failure classification, and improve the robustness of the model. • A plug-and-play data processing module is designed to facilitate application in any deep learning model and improve the overall performance of the model. • Based on the experimental data gathered by the industrial robot arm platform, the effectiveness of the module and the feasibility of application in practice are verified.
Keywords:
APCUP
ALS
data enhancement
fault classification
deep learning
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