In order to characterize different damage modes, real-time detection of the tensile cracking process for AZ31 magnesium alloy was performed using acoustic emission （AE） technique. Results showed that elastic deforma...In order to characterize different damage modes, real-time detection of the tensile cracking process for AZ31 magnesium alloy was performed using acoustic emission （AE） technique. Results showed that elastic deformation, plastic deformation, microcracking, stable and unstable propagation occurred during crack damage. Four damage modes were determined using AE multiparameter analysis. Dislocation motion signals with amplitudes 〈70 dB and twinning signals with 70-100 dB were found. Microcrack signal energy was concentrated from 2400 aJ to 4100 aJ, mainly at a rise time of less than 800 gs. A stable crack propagation signal had high peak to counts in the 20 to 50 range, whereas its ring count was in the 20 to 2000 range. The average frequency of unstable propagation signals was approximately 100 kHz, with duration from 2000 gs to 10s gs. The damage mechanisms and AE resources from different crack propagation steps were discussed. Various damage modes could be characterized by different AE signal parameters when they appeared simultaneously during crack propagation.展开更多
This paper presents a new algorithm to predict locations and severities of damage in structures by changing modal parameters. An existing algorithm of damage detection is reviewed and the new algorithm is formulated t...This paper presents a new algorithm to predict locations and severities of damage in structures by changing modal parameters. An existing algorithm of damage detection is reviewed and the new algorithm is formulated to improve the accuracy of damage locating and severity estimation by eliminating the erratic assumptions and limits in the existing algorithm. The damage prediction accuracy is numerically assessed for each algorithm when applied to a two-dimensional frame structure for which pre-damage and post-damage modal parameters are available for only a few modes of vibration. The analysis results illustrate the improved accuracy of the new algorithm when compared to the existing algorithm.展开更多
基金Project(2213K3170027) supported by the Shenzhen Polytechnic Project Fund,China
文摘In order to characterize different damage modes, real-time detection of the tensile cracking process for AZ31 magnesium alloy was performed using acoustic emission （AE） technique. Results showed that elastic deformation, plastic deformation, microcracking, stable and unstable propagation occurred during crack damage. Four damage modes were determined using AE multiparameter analysis. Dislocation motion signals with amplitudes 〈70 dB and twinning signals with 70-100 dB were found. Microcrack signal energy was concentrated from 2400 aJ to 4100 aJ, mainly at a rise time of less than 800 gs. A stable crack propagation signal had high peak to counts in the 20 to 50 range, whereas its ring count was in the 20 to 2000 range. The average frequency of unstable propagation signals was approximately 100 kHz, with duration from 2000 gs to 10s gs. The damage mechanisms and AE resources from different crack propagation steps were discussed. Various damage modes could be characterized by different AE signal parameters when they appeared simultaneously during crack propagation.
基金The project was financially supported by the National Natural Science Foundation of China （No. 50479027）.
文摘This paper presents a new algorithm to predict locations and severities of damage in structures by changing modal parameters. An existing algorithm of damage detection is reviewed and the new algorithm is formulated to improve the accuracy of damage locating and severity estimation by eliminating the erratic assumptions and limits in the existing algorithm. The damage prediction accuracy is numerically assessed for each algorithm when applied to a two-dimensional frame structure for which pre-damage and post-damage modal parameters are available for only a few modes of vibration. The analysis results illustrate the improved accuracy of the new algorithm when compared to the existing algorithm.
