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 …
Fault detection and diagnosis for smart buildings: State of the art, trends and challenges
Worldwide, buildings account for ca. 40% of the total energy consumption and ca. 20% of
the total CO2 emissions. While most of the energy goes into primary building use, a …
the total CO2 emissions. While most of the energy goes into primary building use, a …
A deep learning approach for anomaly detection based on SAE and LSTM in mechanical equipment
Anomaly in mechanical systems may cause equipment to break down with serious safety,
environment, and economic impact. Since many mechanical equipment usually operates …
environment, and economic impact. Since many mechanical equipment usually operates …
Robust interpretable deep learning for intelligent fault diagnosis of induction motors
In modern manufacturing processes, motivations for automatic fault diagnosis (FD) are
increasingly growing as a result of the great trends toward achieving zero breakdowns …
increasingly growing as a result of the great trends toward achieving zero breakdowns …
Stator fault analysis of three-phase induction motors using information measures and artificial neural networks
The three-phase induction motors are considered one of the most important elements of the
industrial process. However, in this environment, these machines are subject to electrical …
industrial process. However, in this environment, these machines are subject to electrical …
A novel deep learning framework based RNN-SAE for fault detection of electrical gas generator
The electrical generator is the key part of the electrical generation system for the oil and gas
industry, and it is easy to fail, which disturbs the availability and reliability of the electrical …
industry, and it is easy to fail, which disturbs the availability and reliability of the electrical …
A self-adaptive multiple-fault diagnosis system for rolling element bearings
The inevitable simultaneous formation of multiple-faults in bearings generates severe
vibrations, causing premature component failure and unnecessary downtime. For accurate …
vibrations, causing premature component failure and unnecessary downtime. For accurate …
A fault diagnosis approach based on 2D-vibration imaging for bearing faults
Background The widely used rolling element bearings in rotating machines undergo
progressive degradation with continuous operation. To identify bearing faults, complex time …
progressive degradation with continuous operation. To identify bearing faults, complex time …
Diagnosis of combined faults in Rotary Machinery by Non-Naive Bayesian approach
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 …
A neural network-based model for MCSA of inter-turn short-circuit faults in induction motors and its power hardware in the loop simulation
A Mejia-Barron, G Tapia-Tinoco… - Computers & Electrical …, 2021 - Elsevier
Induction motors (IMs) are one of the most commonly used rotating machines in industry. In
order to avoid downtimes and economical losses, development of condition monitoring …
order to avoid downtimes and economical losses, development of condition monitoring …