A method for automatic identification of modal parameters for mechanical equipment structures

Abstract

The invention discloses a method for automatic identification of modal parameters for mechanical equipment structures. The method includes the following steps: dividing the entire frequency domain interval into frequency sub-sections with the same width according to the interval width, and counting the natural frequencies falling in each frequency sub-section. The total number of poles in the interval; the poles in the frequency sub-area whose total number of poles is less than the threshold value are removed as calculated poles, and the remaining poles are reserved as physical poles; then, using the minimum variance criterion, from the remaining poles in the above steps Automatically identify the modal parameters of each order. This identification method can effectively distinguish the calculation poles from the structural physical poles, automatically identify the modal parameters of the structure, obtain the dynamic characteristic parameters of the mechanical structure in the working state, effectively reduce the manual participation in the modal analysis, and contribute to the online detection of the mechanical structure. , damage identification, etc. provide a favorable way.

Description

technical field [0001] The invention belongs to the field of dynamic analysis of mechanical equipment structures, and more specifically relates to an automatic identification method for modal parameters of mechanical equipment structures. Background technique [0002] The dynamic characteristics of the mechanical equipment structure are very important to improve its processing performance and optimize the structural design. At present, the main method to obtain the dynamic characteristics of the mechanical equipment structure is the experimental modal analysis method. The main feature of this method is to apply a specific excitation force to the machine tool structure to stimulate the dynamic characteristics of the machine tool, that is, the machine tool mode, and simultaneously measure The excitation force and the vibration response of the machine tool structure identify machine tool poles. Each pole corresponds to a set of modal parameters: natural frequency ω, damping ra...

AI Technical Summary

Problems solved by technology

[0003] At the same time, for each order mode, there will be estimates of multiple modal parameters identified under mathematical models of different orders. For example, for the natural frequency ω of the first order mode, the orders on the mathematical model are respectively 6 to 30, will identify the 25 estimated values ​​of the natural frequency ω, and finally need to manually select the estimated values ​​of the modal parameters of each order. However, different operators have different experience, which is easy to cause human error, that is, for the same set of data, different operators may choose different estimates, thus causing bias

Therefore, the reliance on human experience severely restricts the development of online automatic identification of modal parameters

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