A survey of fault diagnosis and fault-tolerant techniques—Part I: Fault diagnosis with model-based and signal-based approaches
Z Gao, C Cecati, SX Ding - IEEE transactions on industrial …, 2015 - ieeexplore.ieee.org
With the continuous increase in complexity and expense of industrial systems, there is less
tolerance for performance degradation, productivity decrease, and safety hazards, which …
tolerance for performance degradation, productivity decrease, and safety hazards, which …
A new convolutional neural network-based data-driven fault diagnosis method
Fault diagnosis is vital in manufacturing system, since early detections on the emerging
problem can save invaluable time and cost. With the development of smart manufacturing …
problem can save invaluable time and cost. With the development of smart manufacturing …
The machine learning life cycle in chemical operations–status and open challenges
M Gärtler, V Khaydarov, B Klöpper… - Chemie Ingenieur …, 2021 - Wiley Online Library
Artificial intelligence (AI) has received a lot of attention with many publications in recent
years. Interestingly related projects in the industry are mostly still in their early stages. We …
years. Interestingly related projects in the industry are mostly still in their early stages. We …
Industrial big data for fault diagnosis: Taxonomy, review, and applications
Y Xu, Y Sun, J Wan, X Liu, Z Song - IEEE Access, 2017 - ieeexplore.ieee.org
Fault diagnosis is an important topic both in practice and research. There is intense pressure
on industrial systems to continue reducing unscheduled downtime, performance …
on industrial systems to continue reducing unscheduled downtime, performance …
Fault detection in Tennessee Eastman process with temporal deep learning models
Automated early process fault detection and prediction remains a challenging problem in
industrial processes. Traditionally it has been done by multivariate statistical analysis of …
industrial processes. Traditionally it has been done by multivariate statistical analysis of …
Detection of anomalies in industrial iot systems by data mining: Study of christ osmotron water purification system
MSS Garmaroodi, F Farivar… - IEEE Internet of …, 2020 - ieeexplore.ieee.org
Industry 4.0 will make manufacturing processes smarter but this smartness requires more
environmental awareness, which in case of Industrial Internet of Things, is realized by the …
environmental awareness, which in case of Industrial Internet of Things, is realized by the …
A semi-supervised diagnostic framework based on the surface estimation of faulty distributions
R Razavi-Far, E Hallaji… - IEEE Transactions …, 2018 - ieeexplore.ieee.org
Design of the data-driven diagnostic systems usually requires to have labeled data during
the training session. This paper aims to design a hybrid data-driven framework for …
the training session. This paper aims to design a hybrid data-driven framework for …
Time series prediction method of industrial process with limited data based on transfer learning
Industrial time series, as a kind of data that responds to production process information, can
be analyzed and predicted for effective monitoring of industrial production processes. There …
be analyzed and predicted for effective monitoring of industrial production processes. There …
An effective induction motor fault diagnosis approach using graph-based semi-supervised learning
Machine learning has paved its way into induction motors fault diagnosis area, where
supervised learning and deep learning have been employed. However, both learning …
supervised learning and deep learning have been employed. However, both learning …
A new soft-sensor-based process monitoring scheme incorporating infrequent KPI measurements
YAW Shardt, H Hao, SX Ding - IEEE Transactions on Industrial …, 2014 - ieeexplore.ieee.org
The development of advanced techniques for process monitoring and fault diagnosis using
both model-based and data-driven approaches has led to many practical applications. One …
both model-based and data-driven approaches has led to many practical applications. One …