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Deep Learning-Based Machinery Fault Diagnostics
| Deep Learning-Based Machinery Fault Diagnostics |
| Autore | Chen Hongtian |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (290 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
process monitoring
dynamics variable time lag dynamic autoregressive latent variables model sintering process hammerstein output-error systems auxiliary model multi-innovation identification theory fractional-order calculus theory canonical variate analysis disturbance detection power transmission system k-nearest neighbor analysis statistical local analysis intelligent fault diagnosis stacked pruning sparse denoising autoencoder convolutional neural network anti-noise flywheel fault diagnosis belief rule base fuzzy fault tree analysis Bayesian network evidential reasoning aluminum reduction process alumina concentration subspace identification distributed predictive control spatiotemporal feature fusion gated recurrent unit attention mechanism fault diagnosis evidential reasoning rule system modelling information transformation parameter optimization event-triggered control interval type-2 Takagi-Sugeno fuzzy model nonlinear networked systems filter gearbox fault diagnosis convolution fusion state identification PSO wavelet mutation LSSVM data-driven operational optimization case-based reasoning local outlier factor abnormal case removal bearing fault detection deep residual network data augmentation canonical correlation analysis just-in-time learning fault detection high-speed trains autonomous underwater vehicle thruster fault diagnostics fault tolerant control robust optimization ocean currents |
| ISBN | 3-0365-5174-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910619469103321 |
Chen Hongtian
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| MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Intelligent Control in Energy Systems
| Intelligent Control in Energy Systems |
| Autore | Dounis Anastasios |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (508 p.) |
| Soggetto non controllato |
energy management system
artificial neural network control architecture intelligent buildings sensitivity analysis neural networks active balance photovoltaic system fast frequency response artificial intelligence MPPT operation model uncertainty load frequency control decision tree multi-agent control hybrid power plant Fault Ride Through Capability optimization small scale compressed air energy storage (SS-CAES) smart micro-grid current distortion hybrid electric vehicle parameter estimation railway ANFIS solar monitoring system urban microgrids phase-load balancing model reduction high-speed railway energy internet coordination of reserves differential evolution photovoltaic array ancillary service adjacent areas instantaneous optimization minimum power loss model predictive control HVAC systems sliding mode control MPPT: maximum power point tracking power oscillations thyristor interaction minimization occupancy model fuzzy logic controller power transformer winding RLS integrated energy systems vibration characteristics battery safety error estimation error compensation static friction convolutional neural network forecasting continuous voltage control medium voltage bridgeless SEPIC PFC converter building climate control PEM fuel cell proton exchange membrane fuel cell compound structured permanent-magnet motor occupancy-based control four phases interleaved boost converter long short term memory line switching lithium-ion battery pack back propagation (BP) neural network doubly-fed induction generator double forgetting factors current controller design repetitive controller exhaust gas recirculation (EGR) valve system neural network controller step-up boost converter internal short circuit resistance electric power consumption electric vehicle multiphysical field analysis energy efficiency multi-energy complementary system identification ?-synthesis network sensitivity intelligent control ?-class function frequency support multi-step forecasting frequency containment reserve orthogonal least square rule-based control industrial process hierarchical Petri nets wind integrated power system probabilistic power flow voltage controlling adaptive backstepping AC-DC converters line loss demand side management energy systems short-circuit experiment winding-fault characteristics neutral section stochastic power system operating point drift neural network algorithm operation limit violations fractional order fuzzy PID controller preventive control AC static switch battery packs model-based fault detection automotive application nonlinear power systems adaptive damping control pilot point energy management position control frequency control dead band fuzzy voltage violations distribution network planning frequency regulation energy management strategy multiple-point control electric meter polynomial expansion commercial/residential buildings system modelling three-stage soft internal short circuit demand response |
| ISBN | 3-03921-416-0 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910367565403321 |
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Dounis Anastasios
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Plug-in Hybrid Electric Vehicle (PHEV)
| Plug-in Hybrid Electric Vehicle (PHEV) |
| Autore | VAN Mierlo Joeri |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (230 p.) |
| Soggetto non controllato |
hybrid energy storage system
plug-in hybrid electric vehicle Li-ion battery emerging electric machines lithium-ion capacitor electric vehicles (EVs) efficient energy management strategies for hybrid propulsion systems plug-in hybrid attributional electric vehicle energy system energy efficiency modified one-state hysteresis model air quality adaptive neuron-fuzzy inference system (ANFIS) Markov decision process (MDP) simulated annealing Paris Agreement mobility needs interleaved multiport converte dynamic programming state of health estimation strong track filter LCA modelling consequential losses model voltage vector distribution parallel hybrid electric vehicle electricity mix time-delay input convex optimization lifetime model artificial neural network (ANN) Li(Ni1/3Co1/3Mn1/3)O2 battery battery power CO2 capacity degradation regenerative braking open-end winding novel propulsion systems group method of data handling (GMDH) state of charge Well-to-Wheel energy storage systems including wide bandgap (WBG) technology wide bandgap (WBG) technologies marginal lithium polymer battery life-cycle assessment (LCA) energy management dual inverter lithium-ion battery measurements plug-in hybrid electric vehicles (PHEVs) emerging power electronics Q-learning (QL) fuel consumption characteristics Plugin Hybrid electric vehicle Energy Storage systems meta-analysis range-extender engine-on power reinforcement learning (RL) multi-objective genetic algorithm power sharing energy management strategy power distribution hybrid electric vehicles system modelling |
| ISBN | 3-03921-454-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Altri titoli varianti | Plug-in Hybrid Electric Vehicle |
| Record Nr. | UNINA-9910367565103321 |
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VAN Mierlo Joeri
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| MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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