Intelligent fault detection scheme for constant-speed wind turbines based on improved multiscale fuzzy entropy and adaptive chaotic Aquila optimization-based …
Timely and effective fault detection is essential to ensure the safe and reliable operation of
wind turbines. However, due to the complex kinematic mechanisms and harsh working …
wind turbines. However, due to the complex kinematic mechanisms and harsh working …
Estimating state of health of lithium-ion batteries based on generalized regression neural network and quantum genetic algorithm
A Xue, W Yang, X Yuan, B Yu, C Pan - Applied Soft Computing, 2022 - Elsevier
In order to solve the problem of inaccurate estimation of the state of health (SOH) of electric
vehicle batteries, this paper proposes a novel SOH estimation algorithm based on particle …
vehicle batteries, this paper proposes a novel SOH estimation algorithm based on particle …
Sleep condition detection and assessment with optical fiber interferometer based on machine learning
The prevalence of sleep disorders has increased because of the fast-paced and stressful
modern lifestyle, negatively impacting the quality of human life and work efficiency. It is …
modern lifestyle, negatively impacting the quality of human life and work efficiency. It is …
Soft sensing of lpg processes using deep learning
This study investigates the integration of soft sensors and deep learning in the oil-refinery
industry to improve monitoring efficiency and predictive accuracy in complex industrial …
industry to improve monitoring efficiency and predictive accuracy in complex industrial …
[HTML][HTML] Prediction interval soft sensor for dissolved oxygen content estimation in an electric arc furnace
In this study, a novel soft sensor modeling approach using Takagi–Sugeno (TS) fuzzy
models and Prediction Intervals (PIs) is presented to quantify uncertainties in Electric Arc …
models and Prediction Intervals (PIs) is presented to quantify uncertainties in Electric Arc …
Twinning quality sensors in wastewater treatment process via optimized echo state network-based soft sensors
G Fang, Y Liu - Applied Soft Computing, 2024 - Elsevier
The presence of a large amount of quality-related but hard-to-measure variables usually
makes effective monitoring of industrial processes difficult, and even impossible. Soft …
makes effective monitoring of industrial processes difficult, and even impossible. Soft …
Predictive modeling of quality characteristics–A case study with the casting industry
The foundry environment is dynamic and unpredictable. Variability in casting processes is
usually due to complex interactions of many process variables. The effort in monitoring these …
usually due to complex interactions of many process variables. The effort in monitoring these …
Multistage hybrid model for performance prediction of centrifugal pump
H Deng, Z Xia, Z Sun, S Zheng, Y Liu - Advances in Engineering Software, 2022 - Elsevier
To ensure reliable working and reduce energy consumption of centrifugal pumps, it is
necessary to describe the relationship between performance indices and operation …
necessary to describe the relationship between performance indices and operation …
A review of just‐in‐time learning‐based soft sensor in industrial process
W Sheng, J Qian, Z Song… - The Canadian Journal of …, 2024 - Wiley Online Library
Data‐driven soft sensing approaches have been a hot research field for decades and are
increasingly used in industrial processes due to their advantages of easy implementation …
increasingly used in industrial processes due to their advantages of easy implementation …
Soft sensor for the prediction of oxygen content in boiler flue gas using neural networks and extreme gradient boosting
Oxygen content in the flue gas system of power plants is an essential factor affecting boiler
efficiency. Accurate oxygen content measurement is vital in evaluating boiler combustion …
efficiency. Accurate oxygen content measurement is vital in evaluating boiler combustion …