MODELING METHOD FOR PRODUCT STRUCTURE MAPPING BASED ON REVERSE SOLVING OF LOCUS AND MOTION

Aiming at the problem of structure design in reverse-design of mechanism, a structure mapping method based on reverse solving of locus and motion （RSLM） is presented. The mechanism scheme meeting the requirements of geometric and structural features is obtained through RSLM. The element instance subsets related to component are established based on the element type mapping, pair structure type mapping and design knowledge mapping between components and elements layer by layer. The assembly position mapping of elements is established based on the topological structure information of mechanism scheme, and the product modeling of structure mapping is realized. The algorithm program and prototype system of product structure mapping based on RSLM are developed. Application samples show that the method implements the integration of scheme design, assembly design and structure design, and modeling for product structure mapping based on RSLM. The feasibility of assembly is analyzed in scheme design that contributes to reducing the design error, and raising the design efficiency and quality.

MECHANISM MAP OF TORSIONAL FATIGUE FRACTURE

Studies have been made of the torsional fatigue fracture life of notched specimens,the macroscopic fractography and microscopic fracture mechanism of steel 40Cr after various tempering treatments under different stresses,With the increase of stress,the fracture model changes from normal stress fracture to longitudinal shear one,and then transversal shear one. Under same stress,with the increase of strength,the fracture mode transfers from shear to normal stress fracture.The mechanism of normal stress fracture may be:transgranular frac- ture→striation+intergranular fracture→dimple+intergranular fracture,and of shear fracture may be:transgranular fracture→shear trace→dimple.Based on the experimental results,a fracture mechanism map of torsional fatigue has been drawn up.

Reduced-complexity multiple parameters estimation via toeplitz matrix triple iteration reconstruction with bistatic MIMO radar

In this advanced exploration, we focus on multiple parameters estimation in bistatic Multiple-Input Multiple-Output(MIMO) radar systems, a crucial technique for target localization and imaging. Our research innovatively addresses the joint estimation of the Direction of Departure(DOD), Direction of Arrival(DOA), and Doppler frequency for incoherent targets. We propose a novel approach that significantly reduces computational complexity by utilizing the TemporalSpatial Nested Sampling Model(TSNSM). Our methodology begins with a multi-linear mapping mechanism to efficiently eliminate unnecessary virtual Degrees of Freedom(DOFs) and reorganize the remaining ones. We then employ the Toeplitz matrix triple iteration reconstruction method, surpassing the traditional Temporal-Spatial Smoothing Window(TSSW) approach, to mitigate the single snapshot effect and reduce computational demands. We further refine the highdimensional ESPRIT algorithm for joint estimation of DOD, DOA, and Doppler frequency, eliminating the need for additional parameter pairing. Moreover, we meticulously derive the Cramér-Rao Bound(CRB) for the TSNSM. This signal model allows for a second expansion of DOFs in time and space domains, achieving high precision in target angle and Doppler frequency estimation with low computational complexity. Our adaptable algorithm is validated through simulations and is suitable for sparse array MIMO radars with various structures, ensuring higher precision in parameter estimation with less complexity burden.