Applications of machine learning to machine fault diagnosis: A review and roadmap
Intelligent fault diagnosis (IFD) refers to applications of machine learning theories to
machine fault diagnosis. This is a promising way to release the contribution from human …
machine fault diagnosis. This is a promising way to release the contribution from human …
Development of intelligent fault-tolerant control systems with machine leaprning, deep learning, and transfer learning algorithms: A review
Abstract Intelligent Fault-Tolerant Control (IFTC) refers to the applications of machine
learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The …
learning algorithms for fault diagnosis and design of Fault-Tolerant Control (FTC). The …
Fault diagnosis of rotating machinery based on multiple probabilistic classifiers
Intelligent fault diagnosis of rotating machinery is vital for industries to improve fault
prediction performance and reduce the maintenance cost. The new fault diagnostic …
prediction performance and reduce the maintenance cost. The new fault diagnostic …
Meta-heuristic algorithms in car engine design: A literature survey
MH Tayarani-N, X Yao, H Xu - IEEE Transactions on …, 2014 - ieeexplore.ieee.org
Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution
of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of …
of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of …
Sparse Bayesian extreme learning committee machine for engine simultaneous fault diagnosis
The automotive engine is prone to various faults due to its complex structure and running
conditions. Development of a fast response and accurate intelligent system for fault …
conditions. Development of a fast response and accurate intelligent system for fault …
Probability based vehicle fault diagnosis: Bayesian network method
Y Huang, R McMurran, G Dhadyalla… - Journal of Intelligent …, 2008 - Springer
Fault diagnostics are increasingly important for ensuring vehicle safety and reliability. One of
the issues in vehicle fault diagnosis is the difficulty of successful interpretation of failure …
the issues in vehicle fault diagnosis is the difficulty of successful interpretation of failure …
Adding interpretability to predictive maintenance by machine learning on sensor data
B Steurtewagen, D Van den Poel - Computers & Chemical Engineering, 2021 - Elsevier
Condition-based maintenance (CBM) is becoming more commonplace within the
petrochemical industry. While we find that previous research leveraging machine learning …
petrochemical industry. While we find that previous research leveraging machine learning …
Inn: An interpretable neural network for ai incubation in manufacturing
Both artificial intelligence (AI) and domain knowledge from human experts play an important
role in manufacturing decision making. Smart manufacturing emphasizes a fully automated …
role in manufacturing decision making. Smart manufacturing emphasizes a fully automated …
AI Cupper: A fuzzy expert system for sensorial evaluation of coffee bean attributes to derive quality scoring
J Livio, R Hodhod - IEEE Transactions on Fuzzy Systems, 2018 - ieeexplore.ieee.org
In the coffee industry,“cupping” is the process of sensorial evaluation of coffee beans, also
known as sample evaluation. This process is done for three major reasons: 1) to determine …
known as sample evaluation. This process is done for three major reasons: 1) to determine …
Android-based universal vehicle diagnostic and tracking system
A Tahat, A Said, F Jaouni… - 2012 IEEE 16th …, 2012 - ieeexplore.ieee.org
This system aims to provide a low-cost means of monitoring a vehicle's performance and
tracking by communicating the obtained data to a mobile device via Bluetooth. Then the …
tracking by communicating the obtained data to a mobile device via Bluetooth. Then the …