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Digital image correlation (DIC) is a typical non-contact full-field deformation parameters measurement technique based on image processing technology and numerical computation methods. To obtain the displacements of each point of interrogation in DIC, subsets surrounding the point must be chosen in the reference image and deformed image before correlating. In the existing DIC techniques, the size of subset is always pre-defined by users manually according to their experiences. However, the subset size has proven to be a critical parameter for the accuracy of computed displacements. In the present paper, a self-adaptive selection of subset size method based on Shannon entropy is proposed to overcome the deficiency of existing DIC methods. To verify the effectiveness and accuracy of the proposed algorithm, a numerical translated test is performed on four actual speckle patterns with different entropies, and then another test is performed on four computer-generated speckle patterns with non-uniform displacement field. All the results successfully demonstrate that the proposed algorithm can significantly improve displacement measurement accuracy without reducing too much computational efficiency. Finally, a practical application of the proposed algorithm to micro-tensile of Q235 steel is conducted.

To obtain the optimal main steam pressure of steam turbine under different operating conditions, a heat consumption prediction model based on principal component analysis (PCA) and genetic algorithm-support vector regression (GA-SVR) is established according to the historical operation data. In order to remove the principal components with low contribution rate, PCA is used to reduce the dimension of heat consumption factors. The genetic algorithm with global search ability is used to optimize the parameters of SVR prediction model of heat consumption. Based on the established PCA-GASVR prediction model of heat consumption, main steam pressure is optimized within the feasible range, and the optimized sliding pressure curve is compared with the original one. The results show that heat consumption of the unit decreases under each load after optimization and the operation of steam turbine under optimized sliding pressure curve can improve the unit economy under various operating conditions.

Inconel718 is one kind of nickel-based superalloy strengthened by body centered tetragonal γ ″ and face centered cubic γ ′ precipitation, which has a high yield strength, high corrosion resistance and oxidation resistance at high temperature. Alloying elements exist in the form of high hardness compounds, such as TiC, NbC and other interphase hard point. These high hardness compounds result in the presence of high cutting temperature, large plastic deformation, especially the generation of residual stress in the machined surface. In this paper, the multi-scale finite element model of Inconel718 is established, and the cohesive element is added into the brittle phase particles to conduct the cutting simulation process. The accuracy of the established model is verified according to the chip morphology and the cutting force. The formation mechanism and distribution law of residual stress in the machined surface is studied deeply. The results show that the simulation results of the multi-scale finite element model which adds the brittle phase particles are closer to the experimental results. The larger the size of the brittle phase particles is, the smaller the residual stress of the workpiece is. Along the depth direction of workpiece, the influence of the brittle phase particles on the residual stress is getting smaller and smaller. This study provides a theoretical basis and reference for the further optimization of Inconel718 cutting performance and surface integrity.

Digital image correlation (DIC) is a digital-image-based whole-field deformation measuring technique. For use of the technique, the test surface of object has to be covered with random speckle pattern to ensure reliable and accurate matching. In practice, the quality of the speckle pattern has an important influence on the measurement accuracy of DIC. In this paper, an easy-to-compute parameter, called Shannon entropy which is from information theory, is employed for quality assessment of speckle patterns. Two sets of numerical translated tests are performed on three types of speckle patterns and five artificial speckle patterns with different Shannon entropies, respectively. Then, another test is performed on the computer-generated speckle patterns with nonuniform displacement field. All the results show that the measurement accuracy of DIC is related on the Shannon entropy of speckle pattern. Therefore, the speckle pattern with large Shannon entropy should be a so-called good quality speckle pattern.

The military vehicles seat vibration is one of the main factors affecting the efficiency of crew. In this paper, the wavelet transfrom is used to analyse the military vehicle seat vibration, the vibration energy distribution in different frequency bands is examined by wavelet energy spectrum. The vibration sources of the seat are recognized,!!nd the vibration characters can be identified by the wavelet-scale energy coefficients.