Related Experiment Video
Updated: Jul 14, 2025

Original Experimental Approach for Assessing Transport Fuel Stability
Published on: October 21, 2016
Parametric identification of the mathematical model of the micro-arc oxidation process
Anatoliy Semenov1, Ekaterina Pecherskaya1, Pavel Golubkov1
1Department of Information and Measurement Equipment and Metrology, Penza State University, Krasnaya Street 40, Penza 440026, Russia.
Abstract:
The article is aimed at solving the problem of parametric identification of non-linear object models using the example of a mathematical model of the micro-arc oxidation process. An algorithm for parametric identification, based on an experiment in the micro-arc oxidation process, the results of which form a training and control sample is proposed; sequential training of neural networks and calculation of the parameters estimates of the nonlinear model according to experimental data are performed. Experimental testing of the proposed method of neural network parametric identification on the example of the micro-arc oxidation process confirmed that the standard deviation of current and voltage from the nominal values does not exceed ±4%. The obtained results were used in the development of an intelligent hardware-software complex for the production of protective coatings by the micro-arc oxidation method.
Related Concept Videos
Mechanistic Models: Compartment Models in Individual and Population Analysis
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...

