Data-Driven Feature Extraction for Analog Circuit Fault Diagnosis Using 1-D Convolutional Neural Network

Data-Driven Feature Extraction for Analog Circuit Fault Diagnosis Using 1-D Convolutional Neural Network

The present study applies the one-dimensional convolutional neural network (1D-CNN) to propose an intelligent approach of the feature extraction for the analog circuit diagnosis. The raw signals based on various soft faults from the output terminal of the circuit under test (CUT) are collected with...

Full description

Bibliographic Details
Main Authors: Huahui Yang, Chen Meng, Cheng Wang
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Analog circuit fault diagnosis
convolutional neural network
data-driven method
faults classification
feature extraction
Online Access:https://ieeexplore.ieee.org/document/8966245/

Internet

https://ieeexplore.ieee.org/document/8966245/

Similar Items