A One-Dimensional Depthwise Separable Convolutional Neural Network for Bearing Fault Diagnosis Implemented on FPGA

A One-Dimensional Depthwise Separable Convolutional Neural Network for Bearing Fault Diagnosis Implemented on FPGA

This paper presents a hardware implementation of a one-dimensional convolutional neural network using depthwise separable convolution (DSC) on the VC707 FPGA development board. The design processes the one-dimensional rolling bearing current signal dataset provided by Paderborn University (PU), empl...

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Bibliographic Details
Main Authors: Yu-Pei Liang, Hao Chen, Ching-Che Chung
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Sensors
Subjects:
current signal fault diagnosis
depthwise separable convolution (DSC)
neural networks
quantization
fixed-point arithmetic
real-time systems
Online Access:https://www.mdpi.com/1424-8220/24/23/7831
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