Detrending and Denoising of Industrial Oscillation Data
Author:
Affiliation:
1. Department of Electronic Engineering, Information School, Yunnan University, Kunming, China
2. State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, China
3. HIMA Paul Hildebrandt GmbH, Bruehl bei Mannheim, Germany
Funder
National Natural Science Foundation of China
Training Plan for Young and Middle-Aged Academic and Technological Leaders in Yunnan Province
Yunnan Fundamental Research Projects
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Electrical and Electronic Engineering,Computer Science Applications,Information Systems,Control and Systems Engineering
Link
http://xplorestaging.ieee.org/ielx7/9424/10081096/09816042.pdf?arnumber=9816042
Reference31 articles.
1. Improving Root Cause Analysis by Detecting and Removing Transient Changes in Oscillatory Time Series with Application to a 1,3-Butadiene Process
2. Data-Driven Two-Dimensional Deep Correlated Representation Learning for Nonlinear Batch Process Monitoring
3. Development of EMD-Based Denoising Methods Inspired by Wavelet Thresholding
4. Denoising of Industrial Oscillation Data Using EEMD with CCA
5. Detection and diagnosis of oscillations in process control by fast adaptive chirp mode decomposition
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