Software of Information-Measurement System for Standardless Diagnostic of Composite Materials

Abstract

This article is devoted to software realization via NI LabVIEW 2011 for system of the standardless diagnostic of technical objects. The solution requires methods that are fast and efficient in diagnostics, adapted for usage condition changes, oriented for wide set of objects under control and without changes in the main software structure. The structure and main modules of developed software is represented in the article. Developed software advantages are in its architecture flexibility, high performance and reliability of data signal processing, human-engineered interface. The software of standardless diagnostics system is based on neural network classifier which provides flexible and stable knowledge base about possible classes of defects, performs effective operations with high dimensional data vectors, adapts its architecture for solving new tasks and provides the high reliability of control. The classifier based on hybrid neural network, ART-2 and Fuzzy-ART neural networks for classification of defects in honeycomb panels were introduced and investigated. Described classifier during the training can automatically change its settings, reaching the highest reliability of the control, detect and classify subsurface defects in honeycomb panels with high reliability and accuracy, as well as defects that are located on the back side of the cladding with plottage larger than 2 cm2 and thickness of composite panel equal to 12.8 mm. The reliability of the nondestructive testing via specified classifier is more than 95%. Results of the developed special software practical usage for honeycomb panels’ technical state classification were represented