HHT And It's Application On The Structural Health Monitoring

Structure health monitoring has become an important research area in the field of civil engineerin. One of the core techniques in health monitoring is the detection and diagnosis of damage. Damage diagnosis has taken on a new visage and shown a prosperous future with the rapid perfection of sensor, testing technology, computer technology and signal analysis technology.It has become into a cross-marginal subject, which fuse mathematics, physics,chemistry, mechanics, acoustics, photics, computer science and information engineering.This thesis, based on a review of the development of structure health monitoring system and the current theoretical research on damage detection, provided a summary of the extant damage detection methods and the damage diagnosis indices, as well as the problems in their practical applications. Combining the previous research findings and the newly developed dynamic data analysis techniques, this thesis proposed a new method of structure damages, and tested its feasibility and validity through simulation. This thesis adopts a newly developed method:Hilbert-Huang Transform(HHT).An American-Chinese N. E.Huang firstly put the method forward. The key part of the method is the "empirical mode decomposition (EMD)" method with which any complicated data set can be decomposed into a finite and often small number of "intrinsic mode functions (IMF)" that admits well-behaved Hilbert transforms. Since the decomposition is based on the local characteristic time scale of the data, it is applicable to nonlinear and non-stationary processes.In this thesis, the algorithm and application of HHT is introduced, and needed progrms are generated. Also the end effects of EMD method while using the spline fitting were pointed out. A method based on the wavlet natural network has been given to improve the end effects. In practice, the methods are proven to be efficient and simple.This thesis puts forward a vibration energy sequence as a structural condition feature that reflects the integrity of structures. The energy sequence is composed of the margin spectra of IMFs from the nodes that are distributed along the structure. Based on the correlation of sequences formed in undamaged conditions and unknown condition, the abnormaty index of structure is defined in assesment of structure health, especilly in damage alarming. The application of probability statistics in damage diagnosis is also discussed in this thesis.The feasibility and effectiveness of the proposed method are investigated via a numerical simulation. The results showed that the abnormaty index is sensitive to damage. Analysis of data obtained form the benchmark problem operated by researchers of UBC show that the method to evaluate damage probability has feasibility and credibility.The system construction and derections for further research on bridge structure health monitoring were pointed out at last.