ISSN 1991-2927
 

ACP № 4 (58) 2019

Author: "Michael Genrikhovich Bron"

Vadim Viktorinovich Shishkin, Ulyanovsk State Technical University, Candidate of Engineering, Associate Professor; graduated from the Faculty of Radio-Engineering at Ulyanovsk Polytechnical Institute; Professor at the Measuring-Computing Complexes Department of Ulyanovsk State Technical University, Dean of the Faculty of Information Systems and Technologies at UlSTU, an author of articles in the field of automated design of industrial products and intellectual data analysis. [e-mail: shvv@ulstu.ru]V. Shishkin,

Denis Igorevich Stenyushkin, Ulyanovsk State Technical University, graduated from the Faculty of Information Systems and Technologies at Ulyanovsk State Technical University; Post-Graduate Student at the Measuring-Computing Complexes Department of Ulyanovsk State Technical University, an author of articles in the field of automated design of industrial products and intellectual data analysis. [e-mail: denisstenyushkin@yandex.ru]D. Stenyushkin,

Michael Genrikhovich Bron, R&D in ScanMaster Systems (IRT) Ltd. (Israel), graduated from the Faculty of Radio-Engineering at Ulyanovsk State Technical University; Vice President of R&D in ScanMaster Systems (IRT) Ltd. (Israel); an author of articles in the field of ultrasonic inspection in industry. [e-mail: misha@scanmaster-irt.com]M. Bron

Mathematical Models and Methods for Real-time Analysis of Railway Rails Ultrasonic Defectograms 38_8.pdf

The article describes a system of mathematical models and methods devoted to a real-time analysis of the ultrasonic defectograms of railway rails during a testing process. The system includes models and methods for a preliminary ultrasonic data processing including a data reading, a range adjusting and a data combining for separate channels and also for a defect search and classification. The preliminary data processing is based on the ultrasonic data reading with a signal queue and their further algebraic modifications aiming to make them suitable for a further processing. The defect search and classification is based on an artificial neural network of Simplified Fuzzy ARTMAP architecture that is modified in order to deal with the input array elements with a wide value range. A decision making method based on a decision tree is introduced in order to solve the occurring conflicts. The introduced models and methods can be effectively implemented basing on modern parallel computing approaches. The tests showed out that the defect recognition rate is not less than 85%.

Defectogram analysis, rails defects detection, neural networks.

2014_ 4

Sections: Information systems

Subjects: Information systems, Mathematical modeling.


© FRPC JSC 'RPA 'Mars', 2009-2018 The web-site runs on Joomla!