Journal of South China University of Technology (Natural Science Edition) ›› 2005, Vol. 33 ›› Issue (8): 1-5.

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Intelligent Recogn ition of Crack Depth in Ultrason ic Testing

Chen Guo-hua1  Zhang Xin-mei1  Xie Chang-huan2  He Xiang-bo1   

  1. 1. College of Industrial Equipment and Control Engineering, South China Univ. of Tech. , Guangzhou 510640, Guangdong, China; 2. Guangzhou Institute of Boiler & Pressure Vessel Supervisory Inspection, Guangzhou 510080, Guangdong, China
  • Received:2004-10-15 Online:2005-08-25 Published:2005-08-25
  • Contact: 陈国华(1967-) ,男,教授,博士生导师,主要从事工业安全与风险评价技术及管理信息系统、过程装备可靠性与风险评价研究. E-mail:mmghchen@scut. edu. cn
  • About author:陈国华(1967-) ,男,教授,博士生导师,主要从事工业安全与风险评价技术及管理信息系统、过程装备可靠性与风险评价研究.
  • Supported by:

    国家自然科学基金资助项目(50005006)

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Abstract:

In order to quantitatively recognize crack dep th and effectively imp rove the accuracy of ultrasonic tes-ting, the wavelet analysis and artificial neural network (ANN) are introduced to the intelligent recognition of crack dep th. The p roposed recognition method is then discussed in detail in terms of the basic p rincip le of ultrasonic tes-ting, the determination of defect dep th characteristics, the abstraction of dep th characteristics bywavelet, the struc-tural parameters of ANN as well as the training and testing networks. Moreover, the feasibility of the intelligent quantitative recognition of crack dep th by ANN is discussed, and an intelligent experimental system is finally set up, by which a flaw samp le is quantitatively recognized and analyzed. The results indicate that the introduction of the wavelet analysis and ANN p rovides a feasible app roach to the quantitative recognition of cracks in ultrasonic tes-ting feasible.

Key words: ultrasonic testing, crack depth, intelligent recognition, quantitative method