2026-10-14T08:50:04Z https://www.scidb.cn/oai

10.57760/sciencedb.31979 2025-11-26T17:06:29Z

2025-11-26 A Dataset for Training the Denoising Approach Based on CEEMDAN-nlDAE doi:10.57760/sciencedb.31979 en To address the challenges of complex noise during data acquisition in real shop-floor environments, we propose a denoising approach that combines complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and a noise-learning-based denoising autoencoder (nlDAE). Gauge block measurements are used to train the denoising model.This dataset provides the data used to train the CEEMDAN-nlDAE model in this study, including data of simulation experiment and gauge block measurement. Denoising; CEEMDAN; nlDAE Li Ji PUBLIC https://creativecommons.org/licenses/by-nc/4.0/ dataset http://www.doi.org/10.1016/j.measurement.2026.120883 Science Data Bank