Challenges and opportunities of deep learning models for machinery fault detection and diagnosis: A review
In the age of industry 4.0, deep learning has attracted increasing interest for various
research applications. In recent years, deep learning models have been extensively …
research applications. In recent years, deep learning models have been extensively …
Comprehensive overview on computational intelligence techniques for machinery condition monitoring and fault diagnosis
W Zhang, MP Jia, L Zhu, XA Yan - Chinese Journal of Mechanical …, 2017 - Springer
Computational intelligence is one of the most powerful data processing tools to solve
complex nonlinear problems, and thus plays a significant role in intelligent fault diagnosis …
complex nonlinear problems, and thus plays a significant role in intelligent fault diagnosis …
The novel emergency hospital services for patients using digital twins
The Digital twins will duplicate the actual objects, create the virtual world and execute using
IoT devices and Sensors. The Emergency Room Service (ERS) is a critical phase for …
IoT devices and Sensors. The Emergency Room Service (ERS) is a critical phase for …
Diagnosis of combined faults in Rotary Machinery by Non-Naive Bayesian approach
MY Asr, MM Ettefagh, R Hassannejad… - Mechanical Systems and …, 2017 - Elsevier
When combined faults happen in different parts of the rotating machines, their features are
profoundly dependent. Experts are completely familiar with individuals faults characteristics …
profoundly dependent. Experts are completely familiar with individuals faults characteristics …
Multi-stage feature selection by using genetic algorithms for fault diagnosis in gearboxes based on vibration signal
There are growing demands for condition-based monitoring of gearboxes, and techniques to
improve the reliability, effectiveness and accuracy for fault diagnosis are considered …
improve the reliability, effectiveness and accuracy for fault diagnosis are considered …
Critical evaluation and comparison of psychoacoustics, acoustics and vibration features for gear fault correlation and classification
PV Kane, AB Andhare - Measurement, 2020 - Elsevier
Gear fault diagnosis has gained importance in the last few decades with the focus of fault
diagnosis function for maintenance purpose. This paper investigates the ability of various …
diagnosis function for maintenance purpose. This paper investigates the ability of various …
A domain adaptation model for early gear pitting fault diagnosis based on deep transfer learning network
In recent years, research on gear pitting fault diagnosis has been conducted. Most of the
research has focused on feature extraction and feature selection process, and diagnostic …
research has focused on feature extraction and feature selection process, and diagnostic …
Hierarchical feature selection based on relative dependency for gear fault diagnosis
Feature selection is an important aspect under study in machine learning based diagnosis,
that aims to remove irrelevant features for reaching good performance in the diagnostic …
that aims to remove irrelevant features for reaching good performance in the diagnostic …
Comparison of fault detection and isolation methods: A review
M Thirumarimurugan, N Bagyalakshmi… - … on Intelligent Systems …, 2016 - ieeexplore.ieee.org
Fault Detection and Isolation (FDI) is important in many industries to provide safe operation
of a process. To determine the kind, size, location and time of fault, many Fault detection and …
of a process. To determine the kind, size, location and time of fault, many Fault detection and …
A framework for now-casting and forecasting in augmented asset management
Asset Management of a complex technical system-of-systems needs cross-organizational
operation and maintenance, asset data management and context-aware analytics …
operation and maintenance, asset data management and context-aware analytics …