Recent advances in sensor fault diagnosis: A review
As an essential component of data acquisition systems, sensors have been widely used,
especially in industrial and agricultural sectors. However, sensors are also prone to faults …
especially in industrial and agricultural sectors. However, sensors are also prone to faults …
[HTML][HTML] A review of early fault diagnosis approaches and their applications in rotating machinery
Y Wei, Y Li, M Xu, W Huang - Entropy, 2019 - mdpi.com
Rotating machinery is widely applied in various types of industrial applications. As a
promising field for reliability of modern industrial systems, early fault diagnosis (EFD) …
promising field for reliability of modern industrial systems, early fault diagnosis (EFD) …
Vibration-based anomaly detection using LSTM/SVM approaches
Fault detection is a critical step for machine condition monitoring and maintenance. With
advances in machine learning technologies, automated faulty condition identification can be …
advances in machine learning technologies, automated faulty condition identification can be …
Intelligent fault diagnosis of rolling bearing using hierarchical convolutional network based health state classification
C Lu, Z Wang, B Zhou - Advanced Engineering Informatics, 2017 - Elsevier
Rolling bearing tips are often the most susceptible to electro-mechanical system failure due
to high-speed and complex working conditions, and recent studies on diagnosing bearing …
to high-speed and complex working conditions, and recent studies on diagnosing bearing …
[PDF][PDF] 基于数据驱动的微小故障诊断方法综述
文成林， 吕菲亚， 包哲静， 刘妹琴 - 自动化学报, 2016 - aas.net.cn
摘要能否及时诊断出微小故障是保障系统安全运行并抑制故障恶化的关键,
本文针对微小故障幅值低, 易被系统扰动和噪声掩盖等特点, 从数据驱动的角度对现有研究进行 …
本文针对微小故障幅值低, 易被系统扰动和噪声掩盖等特点, 从数据驱动的角度对现有研究进行 …
An improved bearing fault diagnosis method using one-dimensional CNN and LSTM.
H Pan, X He, S Tang, F Meng - Journal of Mechanical …, 2018 - search.ebscohost.com
As one of the most critical components in rotating machinery, bearing fault diagnosis has
attracted many researchers' attention. The traditional methods for bearing fault diagnosis …
attracted many researchers' attention. The traditional methods for bearing fault diagnosis …
Dilated convolutional neural network based model for bearing faults and broken rotor bar detection in squirrel cage induction motors
Deep learning can play a pivotal role in early fault detection in squirrel cage induction
motors (SCIMs) and achieving Industry 4.0. SCIM finds application in industries like mining …
motors (SCIMs) and achieving Industry 4.0. SCIM finds application in industries like mining …
Application of empirical mode decomposition and artificial neural network for automatic bearing fault diagnosis based on vibration signals
Condition monitoring and fault diagnosis of rolling element bearings (REBs) are at present
very important to ensure the steadiness of industrial and domestic machinery. According to …
very important to ensure the steadiness of industrial and domestic machinery. According to …
[HTML][HTML] Deep learning aided data-driven fault diagnosis of rotatory machine: A comprehensive review
This paper presents a comprehensive review of the developments made in rotating bearing
fault diagnosis, a crucial component of a rotatory machine, during the past decade. A data …
fault diagnosis, a crucial component of a rotatory machine, during the past decade. A data …
[HTML][HTML] An ensemble deep convolutional neural network model with improved DS evidence fusion for bearing fault diagnosis
Intelligent machine health monitoring and fault diagnosis are becoming increasingly
important for modern manufacturing industries. Current fault diagnosis approaches mostly …
important for modern manufacturing industries. Current fault diagnosis approaches mostly …