An efficient multi-peak random uncertainty analysis method

Abstract

By combining a univariate dimensionality reduction method (UDRM) and a maximum entropy method (MEM), the invention provides an efficient random uncertainty analysis method for processing multi-peak distribution random variables. According to the method, an MEM is expanded from a fourth-order moment constraint to an n-order moment constraint, then the order of a response statistical moment (or themoment constraint of the MEM) during response distribution convergence is determined through UDRM + MRM circulation, and on the basis, response probability distribution and response point probabilities are obtained through a UDRM + MEM method. According to the method, multi-peak distribution random variables and multi-peak distribution responses can be processed at the same time, so that the problem that the Jacobian matrix G is close to singularity or illness is well solved, and the solvability of an equation set is improved; Meanwhile, on the premise that the result accuracy is guaranteed, the requirement for the sample scale can be greatly reduced, and high calculation precision can be obtained only through a small number of samples.

Description

technical field [0001] The invention belongs to the field of random uncertainty analysis methods and relates to an efficient multi-peak random uncertainty analysis method. Background technique [0002] In engineering, it is hoped that the product will be reliable, stable and safe, but various uncertain factors such as manufacturing errors, changes in material properties, changes in the use environment, and incomplete understanding will adversely affect product quality. It is of great significance to effectively measure and control these uncertainties to ensure the quality and reliability of products. Uncertainty is usually divided into two types: random uncertainty and cognitive uncertainty. Random uncertainty, also known as objective uncertainty, comes from the inherent randomness and volatility of physical systems or environments. Uncertainty that is eliminated with the improvement of cognitive level is also the research object of the present invention. [0003] There ar...

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Problems solved by technology

If the traditional method is used, it is difficult to obtain better calculation accuracy due to its own limitations, and it is also difficult to accurately estimate the bimodal characteristics of the response

[0004] In view of the above-mentioned problems in the traditional method of dealing with multimodal stochastic uncertainty and the lack of research on multimodal stochastic uncertainty, it is necessary to propose an efficient stochastic uncertainty analysis for dealing with multimodal random variables method

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