Material damage diagnosis and characterization for turbine rotors using three-dimensional adaptive ultrasonic NDE data reconstruction techniques

被引：22

作者：

Guan, Xuefei ^{[1
]}

Zhang, Jingdan ^{[1
]}

Rasselkorde, El Mahjoub ^{[2
]}

Abbasi, Waheed A. ^{[2
]}

Zhou, S. Kevin ^{[1
]}

机构：

[1] Siemens Corp, Corp Technol, Princeton, NJ 08540 USA

[2] Siemens Energy Inc, Pittsburgh, PA 15239 USA

来源：

ULTRASONICS | 2014年 / 54卷 / 02期

关键词：

Damage diagnosis; Rotor; Data reconstruction; Non-destructive examination; Ultrasonic inspection; CLASSIFICATION; PREDICTION; INTERPOLATION; SIZE; LIFE;

D O I：

10.1016/j.ultras.2013.07.019

中图分类号：

O42 [声学];

学科分类号：

070206 ; 082403 ;

摘要：

Damage diagnosis for turbine rotors plays an essential role in power plant management. Ultrasonic non-destructive examinations (NDEs) have increasingly been utilized as an effective tool to provide comprehensive information for damage diagnosis. This study presents a general methodology of damage diagnosis for turbine rotors using three-dimensional adaptive ultrasonic NDE data reconstruction techniques. Volume reconstruction algorithms and data fusion schemes are proposed to map raw ultrasonic NDE data back to the structural model of the object being examined. The reconstructed volume is used for automatic damage identification and quantification using region-growing algorithms and the method of distance-gain-size. Key reconstruction parameters are discussed and suggested based on industrial experiences. A software tool called AutoNDE Rotor is developed to automate the overall analysis workflow. Effectiveness of the proposed methods and AutoNDE Rotor are explored using realistic ultrasonic NDE data. (C) 2013 Elsevier B.V. All rights reserved.

引用

页码：516 / 525

页数：10

共 30 条

[1] SEEDED REGION GROWING [J].