Inverse crack identification and optimal sensor placement for mechanical structures based on normal modes of vibration

2022 Fiscal Year Final Research Report

• Project/Area Number: 20K11855
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 60100:Computational science-related
• Research Institution: Meiji University
• Principal Investigator: Saito Akira 明治大学, 理工学部, 専任准教授 (40581442)
• Project Period (FY): 2020-04-01 – 2023-03-31
• Keywords: 損傷同定 / 振動解析 / 逆問題

Outline of Final Research Achievements

The aim of this study is to develop a methodology to efficiently identify damages of mechanical structures based on the changes in their natural frequencies and the corresponding mode shapes. To this end, we have conducted the following: development of optimal sensor placement and mode shape selection methods and development of an inverse analysis method that can quantitatively relate measured vibration data with damages in the structure. As a result, with the proposed optimal sensor placement method, it was found that many sensors tend to be placed along the edges where crack is expected to be generated. Moreover, by utilizing the concept of topology optimization, it was found that the accuracy of the proposed damage identification method can greatly be improved.

Free Research Field

機械力学

Academic Significance and Societal Importance of the Research Achievements

本研究の学術的意義は，機械構造物のき裂・損傷の状態を効率的な方法で検出することが可能な固有振動モード選択法・センサ配置手法と，き裂を検出する逆解析アルゴリズムを用いることで，計測された固有振動モードからき裂の場所と程度を自動的に決定する事である．本研究の社会的意義は，振動データを用いたき裂検出手法の機械構造物のヘルスモニタリングへの応用が期待される．