Design of an Automatic Defect Identification Method Based ECPT for Pneumatic Pressure Equipment

Bo Zhang,Sara Dadras,Hadi Malek,Yuhua Cheng,Chun Yin,Xuegang Huang

doi:10.1155/2018/5423924

Abstract

In this paper, in order to achieve automatic defect identification for pneumatic pressure equipment, an improved feature extraction algorithm eddy current pulsed thermography (ECPT) is presented. The presented feature extraction algorithm contains four elements: data block selection; variable step search; relation value classification; and between-class distance decision function. The data block selection and variable step search are integrated to decrease the redundant computations in the automatic defect identification. The goal of the classification and between-class distance calculation is to select the typical features of thermographic sequence. The main image information can be extracted by the method precisely and efficiently. Experimental results are provided to demonstrate the capabilities and benefits (i.e., reducing the processing time) of the proposed algorithm in automatic defect identification.

Highlights

A novel characteristic identification algorithm that uses the similarity of the typical transient thermal responses (TTRs) with the mixing vectors in Independent Component Analysis (ICA) is proposed
The main features of the infrared image sequence in the pneumatic pressure equipment can be extracted by the typical TTRs
(2) Complex usage environment: pressure vessels and pipes often suffer from high pressure, some special aerodynamic erosion, and environmental corrosion in the open air, which usually lead to cracks, perforation, fatigue damage, and corrosion of the equipment

Summary

Introduction

A novel characteristic identification algorithm that uses the similarity of the typical transient thermal responses (TTRs) with the mixing vectors (the vectors of the pseudo-inverse matrix of the demixing matrix) in ICA is proposed. It solves the poor accuracy and low efficiency of the ICA efficiently by using the choice of a known message. The main features of the infrared image sequence in the pneumatic pressure equipment can be extracted by the typical TTRs. Experimental results indicate the algorithm can select the typical feature more precise than ones of the ICA.

Background

Introduction of Proposed Algorithm in ECPT

Data analysis and comparison

Experimental Design

Result

Conclusion and Future Work