Fault Diagnosis of Rotary Machines using Deep Convolutional Neural Network with three axis signal input

06/06/2019
by   Davor Kolar, et al.
0

Recent trends focusing on Industry 4.0 concept and smart manufacturing arise a data-driven fault diagnosis as key topic in condition-based maintenance. Fault diagnosis is considered as an essential task in rotary machinery since possibility of an early detection and diagnosis of the faulty condition can save both time and money. Traditional data-driven techniques of fault diagnosis require signal processing for feature extraction, as they are unable to work with raw signal data, consequently leading to need for expert knowledge and human work. The emergence of deep learning architectures in condition-based maintenance promises to ensure high performance fault diagnosis while lowering necessity for expert knowledge and human work. This paper presents developed technique for deep learning-based data-driven fault diagnosis of rotary machinery. The proposed technique input raw three axis accelerometer signal as high-definition image into deep learning layers which automatically extract signal features, enabling high classification accuracy.

READ FULL TEXT

page 1

page 3

page 5

research
04/14/2023

Real Time Bearing Fault Diagnosis Based on Convolutional Neural Network and STM32 Microcontroller

With the rapid development of big data and edge computing, many research...
research
02/29/2020

Quantum Computing Assisted Deep Learning for Fault Detection and Diagnosis in Industrial Process Systems

Quantum computing (QC) and deep learning techniques have attracted wides...
research
10/05/2020

FaultNet: A Deep Convolutional Neural Network for bearing fault classification

The increased presence of advanced sensors on the production floors has ...
research
10/24/2017

Pre-Processing-Free Gear Fault Diagnosis Using Small Datasets with Deep Convolutional Neural Network-Based Transfer Learning

Early fault diagnosis in complex mechanical systems such as gearbox has ...
research
02/12/2015

Towards zero-configuration condition monitoring based on dictionary learning

Condition-based predictive maintenance can significantly improve overall...
research
04/23/2022

Logistic-ELM: A Novel Fault Diagnosis Method for Rolling Bearings

The fault diagnosis of rolling bearings is a critical technique to reali...

Please sign up or login with your details

Forgot password? Click here to reset