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Material damage diagnosis and characterization for turbine rotors using three-dimensional adaptive ultrasonic NDE data reconstruction techniques
Authors:Xuefei Guan  Jingdan Zhang  El Mahjoub Rasselkorde  Waheed A Abbasi  S Kevin Zhou
Institution:1. Siemens Corporation, Corporate Technology, 755 College Rd. E., Princeton, NJ 08540, USA;2. Siemens Energy, Inc., 841 Old Frankstown Road, Pittsburgh, PA 15239-2246, USA
Abstract: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.
Keywords:Damage diagnosis  Rotor  Data reconstruction  Non-destructive examination  Ultrasonic inspection
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