Thermography spatial-transient-stage mathematical tensor construction and material property variation track

被引：29
作者：
Gao, Bin [1 ]
Yin, Aijun [2 ]
Tian, Guiyun [1 ,3 ]
Woo, W. L. [3 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 610054, Peoples R China
[2] Chongqing Univ, Coll Mech Engn, State Key Lab Mech Transmiss, Chongqing 400044, Peoples R China
[3] Newcastle Univ, Sch Elect & Elect Engn, Newcastle Upon Tyne NE1 7RU, Tyne & Wear, England
来源：
INTERNATIONAL JOURNAL OF THERMAL SCIENCES | 2014年 / 85卷
基金：
中国国家自然科学基金;
关键词：
Thermal analysis; Tensor mathematical model; Non-destructive testing and evaluation; Tucker decomposition; Material properties variation tracking; Gear fatigue evaluation; IDENTIFICATION;
D O I：
10.1016/j.ijthermalsci.2014.06.018
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
Characterizing and tracking the properties variation in conductive material such as electrical conductivity, magnetic permeability and thermal conductivity have promising potential for the detection and evaluation of material state undertaken by fatigue or residual stress. This is a challenge task for the research field of non-destructive testing and evaluation. This paper proposes a spatial-transient-stage tensor mathematical model of inductive thermography system and Tucker decomposition algorithm for characterizing and tracking the variation of properties. The inductive thermography has advantages in such as rapid inspection and high sensitivity of defect detection. The links between mathematical and physics models have been discussed. The simulation experiments of tracking physic properties of steel material are investigated and verified. In addition, the real experiment of the measurement for gears with different cycles of fatigue tests is evaluated. The estimation of normalized stage basis by using Tucker decomposition has shown high correlation relationships with different variation of physics properties in material. (C) 2014 Elsevier Masson SAS. All rights reserved.
引用
收藏
页码：112 / 122
页数：11
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