Grant-in-Aid for Developmental Scientific Research (B).
|Research Institution||Tokai University|
KITAHARA Michihiro Tokai University School of Marine Science and Technology Associate Professor, 海洋学部, 助教授 (60135522)
野竹 正義 三菱総合研究所, 数理工学部, 室長
鈴木 英男 小野測器, 音響技術研究所, 部長
HAMADA Masanori Tokai University School of Marine Science and Technology Professor, 海洋学部, 教授 (30164916)
SAKODA Shigemi Tokai University School of Marine Science and Technology Associate Professor, 海洋学部, 助教授 (50056230)
SUZUKI Hideo Ono Sokki, Acoustics Laboratory, Manager
NOTAKE Masayoshi Mitsubishi Research Institute, Mathematical Engineering Dept., Manager
|Project Fiscal Year
1991 – 1992
Completed(Fiscal Year 1992)
|Budget Amount *help
¥3,900,000 (Direct Cost : ¥3,900,000)
Fiscal Year 1992 : ¥1,000,000 (Direct Cost : ¥1,000,000)
Fiscal Year 1991 : ¥2,900,000 (Direct Cost : ¥2,900,000)
|Keywords||Interface / Ultrasonics / Damage evaluation / Knowledge base / 異種材料界面 / 超音波 / 損傷評価 / 波動知識ベース / 波動知識ベ-ス|
An ultrasonic knowledge base has been developed for the evaluation of interface defects of structural materials. The knowledge base is based on elastodynamic theory and experimental measurement. A system to e valuate an interface defect has also been proposed. The following is the summary of results in each phase of the research.
1. Knowledge base from elastodynamic theory
(1) Introduction of the spring model is a versatile way to represent the various situations of interface conditions.
(2) To evaluate the elastodynamic far-fields, it is important to introduce the following two steps:
a) evaluation of near-fields by using the full space Green's function and
b) evaluation of far-fields by using the Green's function which satisfies the interface condition.
(3) Back-scattered wave fields from interface defects have been calculated in some configurations of pulse-echo and pitch-catch methods of ultrasonics.
2. Knowledge base from experiment
Complemental back-scattered wave fields have been accumulated from experimental measurements.
3. Development of evaluation system
A neural network system to evaluate a defect has been proposed by utilizing the knowledge base developed in the phases of 1. and 2.