Fault detection and isolation of multi-variate time series data using spectral weighted graph auto-encoders
Fault or anomaly detection is one of the key problems faced by the chemical process
industry for achieving safe and reliable operation. In this study, a novel methodology …
industry for achieving safe and reliable operation. In this study, a novel methodology …
[HTML][HTML] A graph embedding based fault detection framework for process systems with multi-variate time-series datasets
Due to the enormous potential of modelling, graph-based approaches have been used for
various applications in the process industries. In this study, we propose a fault detection …
various applications in the process industries. In this study, we propose a fault detection …
[HTML][HTML] A Review on Fault Detection and Diagnosis of Industrial Robots and Multi-axis Machines
AH Sabry, UABU Amirulddin - Results in Engineering, 2024 - Elsevier
Industrial Robots and Multi-axis Machines have become increasingly popular in recent
years, in a diverse range of industries. These complex and expensive machines are …
years, in a diverse range of industries. These complex and expensive machines are …
Application and requirements of AIoT-enabled industrial control units
EH Nishimura, Y Iano, GG de Oliveira… - Brazilian Technology …, 2021 - Springer
Industrial Automation control systems are highly demanding devices regarding real-time
control. They excel at this task and have been perfected since their introduction till today …
control. They excel at this task and have been perfected since their introduction till today …
[PDF][PDF] A novel, machine learning-based feature extraction method for detecting and localizing bearing component defects
Vibration analysis for conditional preventive maintenance is an essential tool for the
industry. The vibration signals sensored, collected and analyzed can provide information …
industry. The vibration signals sensored, collected and analyzed can provide information …
A Critical Insight and Evaluation of AI Models for Predictive Maintenance under Industry 4.0
An efficient production line and regular preventive maintenance is a key of success for any
manufacturing industry as it avoids the costly breakdowns and is principal factor for increase …
manufacturing industry as it avoids the costly breakdowns and is principal factor for increase …
[PDF][PDF] Machine Learning based Predictive Maintenance in Manufacturing Industry.
N Iftikhar, YC Lin, FE Nordbjerg - IN4PL, 2022 - scitepress.org
Predictive maintenance normally uses machine learning to learn from existing data to find
patterns that can assist in predicting equipment failures in advance. Predictive maintenance …
patterns that can assist in predicting equipment failures in advance. Predictive maintenance …
Ensemble Learning Approach for Predictive Maintenance in Investment Casting Process
Beyond the Automation Pyramid, industries are currently embracing intelligence. One of the
challenges in Industry 4.0 is to conduct Predictive maintenance (PdM) for the Investment …
challenges in Industry 4.0 is to conduct Predictive maintenance (PdM) for the Investment …
Bearing Fault Diagnosis Using Machine Learning Models Check for updates
S Chandrvanshi, S Sharma, MP Singh… - Micro-Electronics and …, 2024 - books.google.com
The bearing serves as a crucial element of any machinery with a gearbox. It is essential to
diagnose bearing faults effectively to ensure the machinery's safety and normal operation …
diagnose bearing faults effectively to ensure the machinery's safety and normal operation …
An Experiment on Anomaly Detection for Fault Vibration Signals Using Autoencoder-Based N-Segmentation Algorithm
YK Lee, K Park - PHM Society European Conference, 2024 - papers.phmsociety.org
Most manufacturing facilities driven by motors generate vibration and noise representing
critical symptoms against facility malfunctioning conditions in the manufacturing industry …
critical symptoms against facility malfunctioning conditions in the manufacturing industry …