Helical Gear Defect Detection System Based on Symmetrized Dot Pattern and Convolutional Neural Network

Helical Gear Defect Detection System Based on Symmetrized Dot Pattern and Convolutional Neural Network

This study proposes a helical gear defect detection system based on Symmetric Dot Pattern (SDP) and Convolutional Neural Network (CNN). By converting the collected time-domain signals into SDP images and processing them with different delay coefficients and weighting coefficients, followed by deep l...

Full description

Saved in:
Bibliographic Details
Main Authors: Ting-En Wu, Shu-Hsien Huang, Chia-Hung Lai
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Enter symmetrized dot pattern
convolutional neural network
vibration analysis
helical gears
defect detection
Online Access:https://ieeexplore.ieee.org/document/10755078/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/10755078/

Similar Items