Abstract-We study the problem of sequential binary hypothesis testing in a distributed multi-sensor network in nonGaussian noise. To this end, we develop three robust extensions of the Consensus+Innovations Sequential Probability Ratio Test (CISPRT), namely, the Median-CISPRT, the M-CISPRT, and the Myriad-CISPRT, and validate their performance in a shiftin-mean as well as a change-in-variance test. Simulations show the superiority of the proposed algorithms over the alternative R-CISPRT.

This article presents an engineering method based on the collaborative optimization consistency constraint function for selecting shared components in modular platforms; the method allows the operator to minimize the differences in design variables across various models simultaneously. A case study using the body-in-white information on three vehicles serves as an example. Static bending conditions and static torsion conditions are comprehensively considered with the mass and the maximum displacement as the optimization objectives in Isight and Hyperworks (both of which are commercially available software applications commonly used by automotive engineers.) The results suggest that this method can be easily and effectively utilized in the conceptual phase of car design.

Since product development lead-time needs to be as short as possible in contemporary enterprises, it is necessary to assess and optimize the performance of the structure in conceptual design phase for avoiding the time consuming production of trial models for vehicle body. This paper proposes a conceptual design tool based on optimization algorithms for global body frames named Vehicle Concept Design-Intelligent CAE system (VCD-ICAE). A multilevel optimization algorithm is applied to optimize the body performance, decide the size parameters, and generate cross-sectional shapes that satisfy design engineers’ required characteristics. The global body stiffness and vibration property would be optimized while decreasing the mass of body. The paper describes the implementation of the optimal algorithm, and Genetic algorithms are applied to solve the optimization problem. A case of optimization for a real car is given to verify the validity of the algorithm.

No abstract