Lamb waves defects imaging research based on multi-parameter compensation and pixel optimization

Ultrasonic guided waves detecting technology has promising application prospects in structural health monitoring. In order to detect defects in the aluminum sheet, a kind of defect localization imaging algorithm, combining multi-parameter compensation and pixel partitioning optimization is proposed in this paper. Based on the analysis of imaging principles, the waveform signal of time domain was mapped onto the wavenumber domain through a backward propagation compensation, so dispersion parameters can be compensated. Reference signal compensation can be achieved by the baseline signal differential method from wavenumber domain, which overcame influences of environmental changes. During the imaging process, a reasonable threshold was used for pixel partitioning and optimization to improve image quality. Experimental results demonstrated that positioning error about the algorithm is small, defects imaging of sheet is clear and intuitive, this optimization and compensation of guided-wave defects imaging can be used in structural health monitoring

Non-visual vibration shape reconstruction for smart plate structure with bonded FBG sensors

A novel non-visual vibration shape reconstruction method based on orthogonal curvilinear net is proposed in paper for shape detection and reconstruction of plate structure. Its iteration process is deduced and analyzed. A high precision experimental verification platform is constructed. Real time experiments are done for pure bending deformation, torsional deformation and dynamic vibration. Reconstruction precision and performance is compared with the modal approach using displacement-strain transformation techniques. Experimental results show that the proposed method and the modal approach have good shape reconstruction performance for the static deformation with large amplitude and dynamic low frequency vibration. The reconstruction precision of the proposed algorithm was higher than modal approach for deformation with small amplitude. But the modal approach is better for dynamic high frequency vibration. The reconstruction efficiency of the proposed algorithm is superior to the modal approach

Microphase separation, stress relaxation and creep behavior of polyurethane nanocomposites

The microphase separation of polyurethane (PU) nanocomposite was studied. The result suggests that the addition of clay leads to a decrease in the size of hard domain and an increase in the degree of microphase separation. The stress relaxation and creep behavior of blank PU and PU/clay nanocomposites were investigated. The relaxation time spectrum and retardant time spectrum were derived according to the generalized Maxwell model and Voigt model with a Tikhonov regularization method. The characteristic relaxation time was identified with the corresponding relaxation process. At a small strain, the relaxation was mainly attributed to uncoiling/disentangling of soft segment chain network in the soft phase, with a single characteristic relaxation time in the range of 5~100s. The increase in the hard segment content leads to a decrease in the relaxation time, and the addition of clay leads to an increase in the relaxation time. At large strains, the multi-peak relaxations occurred, and they were attributed to the breakup of interconnected hard domains and pull-out of soft segment chains from hard domains, together with the disentangling of soft segment chain network in the soft phase. The creep results are in consistent with that of the stress relaxation. The relaxation and creep behavior were related to microphase separation of polyurethane. This study suggested that the relaxation spectrum H(ï´) can be used to examine the complicated relaxation processes for a multi-phase and multi-component polymer system

Application of remote sensing method in coal fire identification in Ningwu Coalfield

Coal fire cause serious influence on environment, economy and safety of surrounding area. It is of great significance to accurately identify the scope of coal fire caused by spontaneous combustion in coal field for monitoring and controlling coal fire. Relevant scholars identified the scope of coal fire by extracting surface thermal anomaly or surface deformation information respectively, but due to the single method and means, there are many factors causing the occurrence of coal fire, so the experimental results are not accurate enough. In order to improve the accuracy of coal fire identification, the coal fire identification method combining satellite thermal infrared technology and radar technology is applied to the fire area identification of Ningwu Coalfield in Shanxi Province through practical application research. Firstly, the ASTER–TES(Temperature-Emissivity Separation) algorithm is used to retrieve land surface Temperature from ASTER thermal infrared data at night. At the same time, surface subsidence information is inverted using The Sentinel-1 data of SBAS–InSAR(Small Baseline Subset InSAR) technology, and then the abnormal high temperature area and abnormal settlement area in the study area are extracted by threshold segmentation method, and then the range of suspected coal field fire area is obtained by fusion processing. Finally, the experimental results are compared and verified by the coal fire range determined by the field survey method of measuring radon. The results show that the accuracy of the proposed method is as high as 93.78%, which is 43.29% and 62.23% higher than that of the single temperature inversion method and the settlement anomaly method. However, some fire zones have not been identified, mainly because it is difficult to obtain the threshold of identifying fire zones using surface deformation. The results show that the cooperative identification method of thermal infrared technology and radar technology can effectively overcome the deficiency of single identification method, significantly improve the identification accuracy of coal fire range, and provide a powerful reference for accurately determining the control range of fire area. In order to obtain more comprehensive and accurate range of coal fire, it is necessary to study the characteristics of surface deformation detection method in the future

Bio-material polylactic acid/poly(butylene adipate-co-terephthalate) blend development for extrusion-based additive manufacturing

Bio-material polylactic acid and poly(butylene adipate-co-terephthalate) were blended to achieve increased ductility of the blend. Cloisite was added to improve the stiffness of the blend. The blends were made into filament suitable for extrusion-based additive manufacturing. Melt flow index of the filament and mechanical properties of the printed bars were tested. Preliminary results showed that the melt flow index increases significantly with cloisite and the modulus of polylactic acid/poly(butylene adipate-co-terephthalate) improved slightly. The notched impact strength of the blend increased with increasing content of cloisite, and it increased significantly after annealing, especially for blends without cloisite. Ke