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Advanced Process Monitoring for Industry 4.0
| Advanced Process Monitoring for Industry 4.0 |
| Autore | Reis Marco S |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (288 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
artificial generation of variability
auto machine learning classification combustion condition monitoring construction industry continuous casting control chart pattern convolutional neural network curve resolution data augmentation data mining data reconciliation decision support systems digital processing discriminant analysis disruption management disruptions expert systems failure mode and effects analysis (FMEA) failure mode effects analysis fault detection fault diagnosis high-dimensional data imbalanced data Industry 4.0 latent variables models load identification membrane monitoring multi-mode model multi-phase residual recursive model multiscale multivariate data analysis n/a neural networks non-intrusive load monitoring online optical sensors OPTICS pasting process PCA plaster production PLS principal component analysis process control process image process monitoring quality control quality prediction real-time risk priority number rolling bearing semiconductor manufacturing signal detection Six Sigma spatial-temporal data spectroscopy measurements statistical process control statistical process monitoring time series classification yield improvement |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557491503321 |
Reis Marco S
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Sensors Fault Diagnosis Trends and Applications
| Sensors Fault Diagnosis Trends and Applications |
| Autore | Witczak Piotr |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (236 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
acoustic emission signals
acoustic-based diagnosis actuator and sensor fault adaptive noise reducer artificial neural network attention mechanism automotive autonomous vehicle bearing fault diagnosis braking control control valve convolutional neural network cryptography decision tree deep learning fault detection fault detection and diagnosis fault detection and isolation fault detection and isolation (FDIR) fault diagnosis fault identification fault isolation fault recovery fault tolerant control faults estimation gaussian reference signal gear fault diagnosis gearbox fault diagnosis hybrid kernel function intelligent leak detection iterative learning control krill herd algorithm lidar machine learning model predictive control n/a NARX neural networks nonlinear systems observer design one against on multiclass support vector machine path tracking control perception sensor performance degradation rolling bearing scan-chain diagnosis Shannon entropy signature matrix stacked auto-encoder statistical parameters support vector machine SVR Takagi-Sugeno fuzzy systems varying rotational speed wavelet denoising weighting strategy wireless sensor networks |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557506603321 |
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Witczak Piotr
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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