Design and topology optimization of air conditioning suspension bracket for metro.

During the operation of subway vehicles, the vibration of air conditioning units is mainly transmitted to the vehicle body through the suspension support, which seriously affects the stability and comfort of the vehicle during operation. Therefore, the design and optimization of the suspension support of air conditioning units has become a hot topic in the research of the dynamic characteristics of subway vehicles. In this paper, the rigid and flexible coupling dynamic model of metro is firstly calculated to simulate the stress of the suspension point of air conditioning of the vehicle body when the vehicle is running. The initial structure design of the suspension support is carried out, and the stress of the air conditioning suspension point is taken as the load input to analyze the stiffness and strength of the initial structure of the suspension support. Then, the fatigue life is taken as the topology constraint, and the variable density method (SIMP) is used to optimize the topology of the suspension bracket. Finally, the optimized suspension support is validated. The results show that after topological optimization, the maximum displacement and maximum stress of the suspension support under vertical, horizontal, and vertical loads are reduced by 80%, 93%, and 99%, respectively, compared with the original structure model, and the maximum stress under vertical loads is reduced by 50%.

A de-illumination scheme for face recognition based on fast decomposition and detail feature fusion.

Almost all the face recognition algorithms are unsatisfied due to illumination variation. Feature with high frequency represents the face intrinsic structure according to the common assumption that illumination varies slowly and the face intrinsic feature varies rapidly. In this paper, we will propose an adaptive scheme based on FBEEMD and detail feature fusion. FBEEMD is a fast version of BEEMD without time-consuming surface interpolation and iteration computation. It can decompose an image into sub-images with high frequency matching detail feature and sub-images with low frequency corresponding to contour feature. However, it is difficult to determine by quantitative analysis that which sub-images with high frequency can be used for reconstructing an illumination-invariant face. Thus, two measurements are proposed to calculate weights for quantifying the detail feature. With this fusion technique, one can reconstruct a more illumination-neutral facial image to improve face recognition rate. Verification experiments using classical recognition algorithms are tested with Yale B, PIE and FERET databases. The encouraging results show that the proposed scheme is very effective when dealing with face images under variable lighting condition.