The purpose of this work is the development of an efficient and high-sensitive damage localization technique for truss structures, based on the rank-revealing QR decomposition (RRQR) of the difference-of-flexibility matrix. The method is an enhancement of the existing techniques of damage detection, which rely on the set of socalled damage locating vector (DLV). The advantages of the RRQR decomposition-based DLV (RRQR-DLV) method are its less computational effort and high sensitivity to damage. Compared with the frequently used stochastic DLV (SDLV) method, RRQR-DLV offers higher sensitivity to damage, which has been validated based on the presented numerical simulation. The effectiveness of the proposed RRQR-DLV method is also illustrated with the experimental validation based on a laboratory-scale Bailey truss bridge model. The proposed method works under ambient excitation such as traffic excitation and wind excitation; therefore, it is promising for real-time damage monitoring of truss structures.
To diagnose the state of stay cables, a vibration-based model-free damage diagnosis method of stay cables using the changes in natural frequencies is further proposed and validated. The structural frequency is rapidly and easily acquired; moreover, it is simple and reliable for damage diagnosis. The frequency would change after the stay cable is damaged, so the frequency change could be used as the damage index. However, the stay cables are very long in long-span cable-stayed bridges, and their frequencies are very small; the frequency change due to small damage of the stay cable would be submerged by the surrounding noise and error of parameter identification process. A temporary diagonal steel bar–based method is used to solve this issue. The steel bar is installed with one end on the stay cable close to the bottom anchor head and the other end on the bridge deck; thus, the stay cable is divided into a short part and a long part by the steel bar. The frequency of a stay cable with a given tension force increases with the decrease in its length; according to the qualitative analysis, the frequency of the short part increases dramatically, and the local frequency change of the short part due to the same damage in the whole stay cable is amplified dramatically; thus, the small damage of a stay cable can be diagnosed easily. Numerical simulations of a stay cable selected from a cable-stayed bridge and a laboratorial stay cable are used to validate the method and also give a recommended rule for design of the temporary diagonal steel bar; experimental validation has also been conducted. All the results indicate that the proposed method works very well in damage diagnosis of stay cables. The proposed method is an output-only, model-free, fast and economical damage diagnosis method for stay cables.
This paper investigated the forming defects causation and related resolving measures by
combining numerical method with experimental technique. A practical case of one auto-body panel
stamped parts with forming defects was studied in detail. A new approach determining the
causation of forming defects and finding out resolving ways was proposed. Firstly, uses numerical
method to analyze the characteristics of the whole forming process by dividing the forming process
into virtual steps, so as to obtain the forming feature such as stress & strain distribution during the
stamping process. Secondly, uses experimental grid method to measure the real plastic strain
distribution of the defective area thus to analyze the forming rule of this area. By synthesizing both
methods and carrying out extensive analysis, it is possible to make sure the cause of the defects and
put out solving scheme further. The study shows that numerical combined with experimental
method is an effective way in analyzing and resolving forming defects for auto-body parts.
In this paper, ultrasonic materials testing researches are reviewed. The latest progress of ultrasonic testing technology is introduced, including water-squirting ultrasonic C-scan testing, laser ultrasound, ultrasonic feature scan imaging, signal processing and pattern recognition technology in the application of ultrasonic testing.
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