Z
Zhiwei Gao
Researcher at Northumbria University
Publications - 190
Citations - 7971
Zhiwei Gao is an academic researcher from Northumbria University. The author has contributed to research in topics: Fault (power engineering) & Fault detection and isolation. The author has an hindex of 33, co-authored 160 publications receiving 6182 citations. Previous affiliations of Zhiwei Gao include Nankai University & University of Manchester.
Papers
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Journal ArticleDOI
Condition monitoring for the quadruple water tank system using H-infinity Kalman Filtering
Gerasimos Rigatos,Dimitrios Serpanos,V. Siadimas,Krishna Busawon,Zhiwei Gao,Pierluigi Siano,Masoud Abbaszadeh +6 more
TL;DR: In this paper, the authors examined the problem of statistical fault diagnosis for the quadruple watertanks system and proposed a robust state estimator for the approximately linearized model of the four-water tanks system.
Proceedings ArticleDOI
Probabilistic wind power forecasting with an improved sparse-group Lasso-quantile regression neural network
TL;DR: In this paper , an improved non-crossing sparse-group-Lasso deep quantile regression model is presented for probabilistic wind power forecasting, where quantile crossing constraints and a sparse group Lasso algorithm are designed to pursue an interpretable and compact network.
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Small Fault Diagnosis With Gap Metric
TL;DR: In this article , a data-driven gap metric fault detection and isolation (FDI) approach for small multiplicative faults is proposed, where the gap metric is utilized to detect a small fault via the mechanism model and fault detection criterion is derived with the help of the developed fault detectability indicator.
Proceedings ArticleDOI
Robust fault tolerant control for drive train in wind turbine systems with stochastic perturbations
TL;DR: Robust fault tolerant control strategy is implemented to drive the system trajectory convergent and eliminate the effects of faults from both actuators and sensors successfully and is applied to a drive train system of the 4.8 MW benchmark wind wind turbine to validate the effectiveness.
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Special Issue on “Modelling, Monitoring, Control and Optimization for Complex Industrial Processes”
TL;DR: In this article , the authors discuss the complexity of industrial automation systems such as chemical processes, manufacturing processes, power networks, transportation systems, sustainable energy systems, wireless sensor networks, robotic systems, and biomedical systems.