Leak diagnosis in pipelines using a combined artificial neural network approach
EJ Pérez-Pérez, FR López-Estrada… - Control Engineering …, 2021 - Elsevier
Leakages in pipelines affect the reliability of fluid transport systems causing environmental
damages, economic losses, and pressure reduction at the delivery points. Therefore, this …
damages, economic losses, and pressure reduction at the delivery points. Therefore, this …
Industrial fault diagnosis based on active learning and semi-supervised learning using small training set
C Jian, K Yang, Y Ao - Engineering Applications of Artificial Intelligence, 2021 - Elsevier
Industrial fault diagnosis has been investigated for many years, and many approaches have
been proposed to identify industrial faults. However, the size of the actual training set is …
been proposed to identify industrial faults. However, the size of the actual training set is …
Learning transfer feature representations for gas path fault diagnosis across gas turbine fleet
B Li, YP Zhao, YB Chen - Engineering Applications of Artificial Intelligence, 2022 - Elsevier
Intelligent data-driven fault diagnosis based on conventional machine learning techniques
has been extensively studied in recent years. However, these methods often assumed that …
has been extensively studied in recent years. However, these methods often assumed that …
[HTML][HTML] Integrating PCA and structural model decomposition to improve fault monitoring and diagnosis with varying operation points
Fast and efficient fault monitoring and diagnostics methods are essential for fault diagnosis
and prognosis tasks in Health Monitoring Systems. These tasks are even more complicated …
and prognosis tasks in Health Monitoring Systems. These tasks are even more complicated …
Wind turbine generator failure analysis and fault diagnosis: A review
H Liu, YZ Wang, T Zeng, HF Wang… - IET Renewable …, 2024 - Wiley Online Library
The large scale deployment of modern wind turbines and the yearly increase of installed
capacity have drawn attention to their operation and maintenance issues. The development …
capacity have drawn attention to their operation and maintenance issues. The development …
Group reduced kernel extreme learning machine for fault diagnosis of aircraft engine
B Li, YP Zhao - Engineering Applications of Artificial Intelligence, 2020 - Elsevier
The original kernel extreme learning machine (KELM) employs all training samples to
construct hidden layer, thus avoiding the performance fluctuations caused by the ELM …
construct hidden layer, thus avoiding the performance fluctuations caused by the ELM …
An integrated methodology for system-level early fault detection and isolation
J Wang, X Sun, C Zhang, X Ma - Expert Systems with Applications, 2022 - Elsevier
Fault diagnosis is an indispensable technique to ensure the high-performance operation of
a mechanical system during its life-cycle. Existing research works mainly limits in the …
a mechanical system during its life-cycle. Existing research works mainly limits in the …
Real-time dynamic prediction model of carbon efficiency with working condition identification in sintering process
Accurate prediction of carbon efficiency is a prerequisite for achieving energy saving and
consumption reduction in an iron ore sintering process, and is the key to guaranteeing the …
consumption reduction in an iron ore sintering process, and is the key to guaranteeing the …
Automated design of grey-box recurrent neural networks for fault diagnosis using structural models and causal information
D Jung - Learning for Dynamics and Control Conference, 2022 - proceedings.mlr.press
Behavioral modeling of nonlinear dynamic systems for control design and system monitoring
of technical systems is a non-trivial task. One example is fault diagnosis where the objective …
of technical systems is a non-trivial task. One example is fault diagnosis where the objective …
[HTML][HTML] Modeling of forced-vibration systems using continuous-time state-space neural network
Dynamic analysis of forced-vibration systems in civil engineering could be computationally
inefficient or even hard to converge if the systems are stiff or highly complicated. Rapid …
inefficient or even hard to converge if the systems are stiff or highly complicated. Rapid …