Gearbox Degradation Prediction through Deep CNN and Bayesian Optimization

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Published Oct 26, 2023
Kai Shen

Abstract

The original dataset, recorded at a high sampling rate of 20,480 Hz, presents a considerable volume of data. To facilitate efficient processing and analysis, we implement a data reduction strategy, which involves downsampling the signal to a more manageable frequency of 2,048 Hz.

How to Cite

Shen, K. (2023). Gearbox Degradation Prediction through Deep CNN and Bayesian Optimization. Annual Conference of the PHM Society, 15(1). https://doi.org/10.36001/phmconf.2023.v15i1.3813
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Keywords

Grearbox, Degradation, Deep CNN, Bayesian Optimization

Section
Data Challenge Papers