Development of Advanced Technologies for Structural Damage Identification and Prediction

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Highly efficient damage identification methodologies are essential to ensuring the operational efficiency and reliability of a wide range of engineering structures (e.g. beam, plate, or shell elements in vehicle frames and civil infrastructure). These methods must be sensitive, accurate, fast, and easy to operate and must provide detection, evaluation, and localization of damage. Many challenges have yet to be addressed to develop efficient identification techniques especially for structures with damages at initial stages under varying load conditions. An efficient condition monitoring system for mechanical structures will require advanced technologies and methods, which can identify and predict the occurrence and propagation of structural damage at its earliest stages. Real-time operation of the monitoring system is also essential for its adoption as a practical application. The proposed work will explore and develop new methods in structural static and dynamic analysis, advanced signal processing algorithm, new sensing network, and machine learning technique. First, a new load transfer analysis method will be developed and combined with stress calculations to provide a clear sign of possible damage at an early stage. Second, a novel tunable Entropy algorithm with a proper noise filter will be created that can reliably identify damage under practical noisy working conditions. A flexible piezoelectric nanocomposite paint will be introduced to create a new sensor network design that can cover a large area of monitored objects. With both time and space domain signals from the piezoelectric sensor, it will be possible to localize the damages. To attain real time structural analysis for damage identification, proper machine learning algorithms will be introduced and developed to learn and estimate the load transfer path and Entropy results quickly and accurately. Finally, all of the components listed above will be combined to produce a comprehensive damage identification system. Outcomes of this research will lead to comprehensive damage identification platforms and practical (easy to operate and maintain) engineering solutions to warn impending structural damage and failure by detecting them in the initial stages. The proposed research will ensure the reliability, integrity and safety of different types of engineering structures through practical applications as a long-term goal. The proposed damage assessment methods will be inexpensive and easy to apply in industrial settings for the direct benefit of Canadian industries. Highly qualified personnel trained under this program will gain the theoretical and practical expertise necessary to promote and advance superior mechanical structural condition monitoring in Canada.