Modelling and prediction of machining errors using ARMAX and NARMAX structures

DOI10.1016/S0307-904X(03)00071-4zbMath1040.62113OpenAlexW1981127419MaRDI QIDQ1433249

D. Massart

Publication date: 15 June 2004

Published in: Applied Mathematical Modelling (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0307-904x(03)00071-4

zbMATH Keywords

Neural networksForecastingRecursive parameter estimationARMAX and NARMAX modelsextended least squareMachine error compensation

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Applications of statistics in engineering and industry; control charts (62P30) Application models in control theory (93C95)

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Structural damage detection using ARMAX time series models and cepstral distances ⋮ Indirect prediction system for variables that have gaps in their time series ⋮ A neural network approach for the real-time detection of faults ⋮ Modeling and prediction of chaotic systems with artificial neural networks ⋮ An improved high precision measuring method for shaft bending deflection ⋮ On consistency of recursive least squares identification algorithms for controlled auto-regression models

Cites Work

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• Using ARMA models to forecast workpiece roundness error in a turning operation
• Adaptive control
• Representations of non-linear systems: the NARMAX model

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