Multi-axis random load fatigue life prediction method

Abstract

The invention discloses a multi-axis random load fatigue life prediction method, which is characterized by comprising the following steps: aiming at each random load borne by a component, obtaining the position of a structural dangerous point through a finite element method, extracting a key load, and grading the key load; based on the dominant load, constructing a combined load spectrum block corresponding to the key load; and based on a linear damage accumulation principle, predicting the fatigue life under the multi-axis random load by using a multi-axis constant-amplitude load fatigue life estimation method. The multi-axis random load fatigue life prediction precision is high, the operation efficiency can be effectively improved, and engineering application is facilitated.

Description

technical field [0001] The invention relates to a method for predicting multiaxial fatigue life, more specifically, a method for predicting fatigue life of components under multiaxial random loads. Background technique [0002] Multiaxial fatigue refers to the fatigue of components under multidirectional stress or strain. When the component stress is complex, the stress state of the structural dangerous point is often manifested as a multiaxial stress state, and two or three stress (or strain) components change periodically with time independently. [0003] At present, the main multiaxial fatigue research methods include the critical plane method, equivalent stress-strain method and energy method; among them, the critical plane method is based on the fracture model and crack initiation mechanism, and is considered to be more effective today because of its clear physical meaning. a method of analysis. Based on the critical plane method, domestic and foreign scholars have pr...

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Problems solved by technology

However, multi-axis rainflow counting is an extremely complicated process, and the determination of the critical plane also needs to cycle through multiple parameters at the same time. The entire analysis process has particularly high requirements for time and space complexity, especially when the load data is huge.

In addition, the cost of multi-axis fatigue analysis instruments and equipment in today's engineering applications is high, the precision requirements are strict, and the manpower and material resources are consumed. However, the current multi-axis random load life prediction method requires a lot of calculations and takes up a lot of machine hours, so the significance of engineering applications is not obvious

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