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Sensors Fault Diagnosis Trends and Applications

Resumen/Descripción – provisto por la editorial

No disponible.

Palabras clave – provistas por la editorial

rolling bearing; performance degradation; hybrid kernel function; krill herd algorithm; SVR; acoustic-based diagnosis; gear fault diagnosis; attention mechanism; convolutional neural network; stacked auto-encoder; weighting strategy; deep learning; bearing fault diagnosis; intelligent leak detection; acoustic emission signals; statistical parameters; support vector machine; wavelet denoising; Shannon entropy; adaptive noise reducer; gaussian reference signal; gearbox fault diagnosis; one against on multiclass support vector machine; varying rotational speed; fault detection and diagnosis; faults estimation; actuator and sensor fault; observer design; Takagi-Sugeno fuzzy systems; automotive; perception sensor; lidar; fault detection; fault isolation; fault identification; fault recovery; fault diagnosis; fault detection and isolation (FDIR); autonomous vehicle; model predictive control; path tracking control; fault detection and isolation; braking control; nonlinear systems; fault tolerant control; iterative learning control; neural networks; cryptography; wireless sensor networks; machine learning; scan-chain diagnosis; artificial neural network; NARX; control valve; decision tree; signature matrix; n/a

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Información

Tipo de recurso:

libros

ISBN electrónico

978-3-0365-1049-1

País de edición

Suiza