Inter-domain learning for signal de-generation and validation on S-glass composite in performance estimation

Abstract

The strength of S-glass composite and application in aircraft manufacturing industrial front is a major source of incubating and hence requires a validation of S-glass composite is at higher demand ratio of research. Majority of devices/instruments processing S-glass/ R-glass and E-glass are bound to generate a signal on processing. In this article, the inter-domain learning technique of various signals are acquired via devices computation and processed. The article proposes a signal de-generation and signal framing technique for understanding the behavioral patterns in evaluating the signal nature towards verifying the strength of S-glass composite. The proposed technique uses a novel approach of signal de-generation and signal framing technique for understanding the behavioral pattern in evaluating the signal nature towards verifying the strength of S-glass composite. The proposed technique use a novel approach of signal de-generation via signal segmentation. These approaches are bound on inter-domain signal acquisition via analog instrumentation of S-glass application. The technique, thus estimates the performance ratio of dependencies and S-glass signal via performance parameters such as voltage differences and time attributes with a range of 94.32% in signal segmentation and inter-domain learning.