A spectrum-driven damage identification by minimum constitutive relation error and sparse regularization

This paper proposes a novel model-based damage identification strategy based on minimum constitutive relation error and sparse regularization using the power spectrum density data. Firstly, the stationary random vibration problem is transformed into a series of harmonic vibrations by the pseudo excitation method and the error in constitutive relation is established by the admissible stress field and admissible displacement field. A much more general and simpler strategy so as to build the admissible stress field is addressed by requiring only an extra decomposition of the stiffness matrix. Then, the sparse regularization is added to the original constitutive relation error objective function to circumvent the ill-posedness of the inverse problem. Finally, the solution of this nonlinear optimization problem is solved by the alternating minimization method. The proposed method has the advantage that only measurement power spectrum density data from few limited sensors are needed in the inverse analysis. Numerical and experimental results show the effectiveness and robustness of this approach

Damage identification for frame structures using vision-based measurement

Extracting physical parameters for damage identification problems from full-field measurements is a promising research because of the recent spread of vision-based measurement techniques in the experimental mechanics. This paper presents a vision-based measurement framework using the camera system for damage identification. The framework is composed of four procedures: camera calibration, image processing, system identification and sensitivity analysis. In contrast to traditional finite-point measurements, the camera system allows considerably greater non-contact measurement flexibility. Such flexibility has two important benefits: first, less number of modes is required for modal-based damage identification problems; and second, more physical parameters could be extracted, taking advantage of the plentiful experimental data. A laboratory test comparing the camera system to traditional accelerometer measurement is conducted to confirm the above advantages. Further statistic analysis shows that the major drawback of this technique is that the camera system presents high levels of noise in small vibration responses at higher frequencies. Suitable strategies to circumvent this disadvantage are developed. Moreover, a technique for practical camera calibration without the requirement that the objective plane should be strictly perpendicular to the camera axis is also demonstrated and verified by the proposed laboratory test

Analysis and Application of Extension Correlation and Correspondence under Uncertainty

This paper studies the meaning, nature of extension correspondence and analyzes its superiority in data prediction in extension group decision-making by analyzing the distance and bit value of the correlation function. It puts forward the model and steps of data interval analysis of extension group decision-making based on extension correspondence. Not only does it take the advantages of dynamic classification in extension group decision-making, but also realizes data analysis and interval estimation under uncertainty and helps the promotion of the accuracy and the reliability of multi-factor analysis and multi-project evaluation in extension group decision-making under data uncertainty. Keywords: extension set; extension group decision-making; correlation function; correspondence analysis; uncertaint

Tris{2-meth­oxy-6-[(4-methyl­phen­yl)iminiometh­yl]phenolate-κ2 O,O′}tris­(thio­cyanato-κN)europium(III)

The metal center in the structure of the title compound, [Eu(NCS)3(C15H15NO2)3], is coordinated by three Schiff base 2-meth­oxy-6-[(4-methyl­phen­yl)iminiometh­yl]phenolate (L) ligands and three independent thio­cyanate ions. In the crystal structure, the acidic H atom is located on the Schiff base N atom and hydrogen bonded to the phenolate O atom. The coordination environment of the EuIII ion is nine-coordinate by three chelating methoxy­phenolate pairs of O atoms and three N-atom terminals of the thio­cyanate ions. The compound is isostructural with the CeIII analogue [Liu et al. (2009 ▶). Acta Cryst. E65, m650]

Application of Rough Classification of Multi-objective Extension Group Decision-making under Uncertainty

On account of the problem of incomplete information system in classification of extension group decision-making, this paper studies attribution reduction with decision-making function based on the group interaction and individual preferences assembly for achieving the goal of rough classification of multi-objective extension group decision-making under uncertainty. Then, this paper describes the idea and operating processes of multi-objective extension classification model in order to provide decision-makers with more practical, easy to operate and objective classification. Finally, an example concerning practical problem is given to demonstrate the classification process. Combining by extension association and rough reduction, this method not only takes the advantages of dynamic classification in extension decision-making, but also achieves the elimination of redundant attributes, conducive to the promotion on the accuracy and the reliability of the classification results in multi-objective extension group decision-making. Keywords: extension group decision-making; matter-element analysis; extension association; rough set; attribution reductio