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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 online resource (290 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
abnormal case removal
alumina concentration aluminum reduction process anti-noise attention mechanism autonomous underwater vehicle auxiliary model Bayesian network bearing fault detection belief rule base canonical correlation analysis canonical variate analysis case-based reasoning convolution fusion convolutional neural network data augmentation data-driven deep residual network distributed predictive control disturbance detection dynamic autoregressive latent variables model dynamics event-triggered control evidential reasoning evidential reasoning rule fault detection fault diagnosis fault tolerant control filter flywheel fault diagnosis fractional-order calculus theory fuzzy fault tree analysis gated recurrent unit gearbox fault diagnosis hammerstein output-error systems high-speed trains information transformation intelligent fault diagnosis interval type-2 Takagi-Sugeno fuzzy model just-in-time learning k-nearest neighbor analysis local outlier factor LSSVM multi-innovation identification theory n/a nonlinear networked systems ocean currents operational optimization parameter optimization power transmission system process monitoring PSO robust optimization sintering process spatiotemporal feature fusion stacked pruning sparse denoising autoencoder state identification statistical local analysis subspace identification system modelling thruster fault diagnostics variable time lag wavelet mutation |
| 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 / Anastasios Dounis
| Intelligent Control in Energy Systems / Anastasios Dounis |
| 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 |
9783039214167
3039214160 |
| 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) / Joeri VAN Mierlo
| Plug-in Hybrid Electric Vehicle (PHEV) / Joeri VAN Mierlo |
| Autore | VAN Mierlo Joeri |
| Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
| Descrizione fisica | 1 electronic resource (230 p.) |
| Soggetto topico | History of engineering and technology |
| 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 |
9783039214549
3039214543 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| 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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