In crane safety assessment, both quantitative and qualitative indicators are inevitably influenced by the subjective influence of the evaluator, which is unfavorable to the objective requirements of safety assessment. In response to these problems, this study proposes a crane safety assessment method based on the cloud model and the improved combination weighting method of game theory (ICWGT). This evaluation method constructs a multi-level assessment index system for crane safety status by selecting suitable indicators in layers and groups, according to the crane safety assessment rules, and gives a method for constructing the cloud model of the commentary set, the selection and derivation of the membership function, and the determination of the fuzzy relationship matrix. When performing fuzzy synthetic calculations based on the cloud model, the synthetic operator enhances the effect of expectation on entropy and makes the cloud image significantly deformed; this method uses a fine-tuned synthetic operator to improve the algorithm. Compared with the traditional crane fuzzy synthesis assessment method, this method combines the cloud model and ICWGT to achieve finding a balance between expert experience and sample data information, calculating the combined optimization weights of each index and component layer by layer. In order to verify the effectiveness of the method, we take the metal structure system of the shipyard portal crane as an example to explore the applicability of the method in crane safety assessment. The results show that the assessment method can accurately reflect the safety level of the crane and can provide reference material for crane safety assessment.
Digital image correlation (DIC) is an efficient nondestructive technique for measuring surface displacement in engineering. However, standard DIC is restricted to continuous deformation, and the existing discontinuous DIC (DDIC) techniques are only able to measure small-scale cracks. In this report, a novel subset restore model and a corresponding subset size adaptation algorithm are presented to overcome this limitation for crack-state and displacement field reconstruction for large-scale cracks. The technique introduces a new subset restore method for splicing the segmented subset by tracing the motion trajectory caused by pure discontinuities. The proposed model facilitates the calculation of the rotation angle and the pivot of the subset movement. The subset size adaptation algorithm is designed based on an evaluation of the intensity gradient and correlation coefficient to allow the model to achieve high accuracy. Validation of the approach was performed using two typical crack models, by deforming a numerically synthesized Gaussian speckle image according to the deformation data from finite element analysis (FEA) results and photographing a laboratory tensile test with a high-speed CCD camera, respectively. The results validate the efficacy and high accuracy of the proposed approach compared to standard DIC in the reconstruction of the displacement fields in both continuous and discontinuous regions. The accuracy of resultant displacement reconstruction achieves approximately 0.015 pixels and 0.05 pixels in continuous region and crack vicinity, respectively.
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