Rotating equipment virtual measuring point construction method and system based on finite element analysis

Abstract

The invention discloses a rotating equipment virtual measuring point construction method based on finite element analysis, and the method comprises the following steps: collecting and obtaining a time-based vibration data sequence at a plurality of entity collection points on rotating equipment, constructing a 3D computer aided design model of the rotating equipment, and constructing a finite element analysis model of the rotating equipment by utilizing finite element software; performing computer-aided simulation according to the finite element analysis model, and performing calculating to obtain a simulation result of each mass unit of the rotating equipment under the condition of the rotating speed of the high-speed shaft; calculating a dimensionless projection coefficient of any one virtual measuring point on the rotating equipment; and according to the dimensionless projection coefficient of any virtual measuring point on the rotating equipment, calculating vibration data of any point on the rotating equipment. Based on the computer aided technology, the existing entity monitoring points and the finite element analysis technology can be combined to construct any number of virtual monitoring points, so that the vibration data of any point of the rotating equipment can be obtained.

Description

technical field [0001] The invention relates to the technical field of computer-aided optimization, in particular to a method and system for constructing virtual measuring points of rotating equipment based on finite element analysis. Background technique [0002] The health status monitoring and failure prediction of rotating equipment has always received high attention. Rotating equipment is subjected to alternating loads for a long time during production and operation, resulting in failures. For mechanical equipment with complex supporting structures and greatly affected by operating conditions and environmental conditions, the vibration signal of the equipment is collected by the vibration sensor to realize the analysis and judgment of the fault signal. The vibration signal often contains prominent noise components. Due to the limited installation position of the vibration sensor, it may not be able to be installed in a position sensitive to equipment failure. When the...

AI Technical Summary

Problems solved by technology

The patent with the publication number CN 111967189A uses the digital twin model to synchronize the fault information of the equipment locally, and then uses the Bayesian network to diagnose locally. The digital twin does not enhance the diagnosis result

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