High-speed train body random response detection method of confidence interval

Abstract

The invention relates to a high-speed train body random response detection method of confidence interval, comprising the following steps: a step of expressing nondeterminacy of random vibration and structure parameters of a train and generating a random sample; a step of analyzing the random response sample based on a pseudo excitation method; and a step of carrying out statistic analysis on the random response sample and providing a confidence interval. According to the invention, nondeterminacy of train's structure parameters and randomness of track excitation are both taken into consideration, and statistic analysis of composite random vibration response is carried out. With the combination of an efficient method of computational mechanics and with the application of the pseudo excitation method to take a track spectrum containing statistical information as a motivator, the input problem of random excitation is solved. By the symplectic-mathematics theory, a track model is simplified and a hybrid coordinates equation is established, thus making it possible to calculate a large-capacity sample. Statistics provides a certain confidence level of random response estimation, thus providing a basis for a dynamic design for raising operation safety and comfort of a train.

Description

technical field [0001] The invention relates to a method for calculating the random response of a high-speed train body, in particular to a method for detecting the confidence interval of the random response of a high-speed train body considering uncertain factors. Background technique [0002] The high requirements of high-speed trains on operating comfort and safety determine that the influence of uncertain factors must be considered in its power design. On the one hand, the train is subjected to random excitations caused by track irregularities; on the other hand, due to processing, manufacturing and other reasons, there are a large number of uncertain factors in the structural parameters of the train, and the deterministic analysis model usually adopted is only It is an idealized model of the actual structure. In order to accurately predict the dynamic behavior of the train system and its matching relationship with line performance, it is necessary to reasonably take in...

AI Technical Summary

Problems solved by technology

[0004] The above work uses a relatively simplified model to explore the problem of uncertain vehicle-structure interaction, but it is far from enough for practical applications

The analysis of complex uncertain dynamical systems still faces many challenges, especially in the aspects of random loads on structures, probabilistic description of uncertain properties of materials, and structural analysis methods related to computational mechanics.

Images