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Data · dataset · 2025

A Dataset for Training the Denoising Approach Based on CEEMDAN-nlDAE

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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).

Description

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.

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Catalogue records · 1

Topics

Inferred from text
Mechanical engineering 74% · Simulation 75%
Provenance · 1 source records, 12 field assertions
SourceKeyLast seenRaw
ScienceDB10.57760/sciencedb.3197911 d agoJSON v1
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