Fault detection and identification method: 3D-CNN combined with continuous wavelet transform-Reference-Cited by-同舟云学术

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Fault detection and identification method: 3D-CNN combined with continuous wavelet transform

Published:2024-10 Issue: Volume:189 Page:108791
ISSN:0098-1354
Container-title:Computers & Chemical Engineering
language:en
Short-container-title:Computers & Chemical Engineering

Author:

Ukawa Chinatsu,Yamashita Yoshiyuki^ORCID

Publisher

Elsevier BV

Reference47 articles.

1. The continuous wavelet transform using for natural ECG signal arrhythmias detection by statistical parameters;Alharbey;Alex. Eng. J.,2022

2. Continuous wavelet transformation of seismic data for feature extraction;Ali;SN Appl. Sci.,2020

3. Attention guided 3D CNN-LSTM model for accurate speech based emotion recognition;Atila;Appl. Acoust.,2021

4. A novel orthogonal self-attentive variational autoencoder method for interpretable chemical process fault detection and identification;Bi;Process Saf. Environ. Prot.,2021

5. Detection of probability of occurrence, type and severity of faults in transformer using frequency response analysis based numerical indices;Bigdeli;Measurement,2021

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