Digital Block Printing: Diffusion-Based Data Generation for Planetary Gearbox Vibration Signal Crossing Working Condition

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Abstract
Data augmentation and generation are popular solutions for the problem of imbalanced and insufficient data. Aiming to conduct cross-domain data generation, this article proposes a physics-guided data generation framework, termed “digital block printing (DBP).” Its core idea is to use the “Digital Printing Plate” constructed from the simulation data as a reference, and use the “Data Printer” trained with source-domain experimental data to generate synthetic data with a similar distribution to the target-domain experimental data. For a specific case, conditional-diffusion-based vibration signal generation is conducted in this article, with the target-domain data simulated by a phenomenological model as the “Digital Printing Plate,” and the diffusion model trained by source-domain experimental data as the “Data Printer.” The result shows that the method proposed in this article can generate experiment-like synthetic data, which processes both the frequency-domain characteristics similar to the target-domain simulation data, and time-domain characteristics similar to the source-domain experimental data.
Funding Information
  • National Natural Science Foundation of China (52575160)
  • National Natural Science Foundation of China (52575159)
  • Young Elite Scientists Sponsorship Program by the China Association for Science and Technology (YESS20240414)
  • Natural Science Foundation of Hunan Province of China (2024JJ5408)

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