Unbalance parameter identification method suitable for polyhedral rotor

Abstract

An unbalance parameter identification method suitable for a polyhedral rotor comprises the following steps: firstly, establishing a kinetic model of a rotor shaft system to obtain a theoretical unbalance response, and then constructing an optimization target in combination with an actual unbalance response; then determining each particle dimension of the particle swarm, initializing the particle swarm, including randomly initializing the position and speed of the particle swarm, and determining a chaotic inertia weight factor of each dimension according to a chaotic attenuation principle; carrying out the particle swarm optimization, updating the particle speed and position, carrying out the iteration until 80% of the total number of iterations is reached, and carrying out a chaotic particle swarm optimization stage; determining a t-th generation optimal particle, taking the t-th generation optimal particle as an initial value, carrying out tent chaotic mapping processing to obtain a chaotic particle swarm, carrying out particle swarm optimization on the chaotic particle swarm to obtain a chaotic optimal particle, and randomly replacing one particle in the original particle swarm;reaching the repeating until the set number of iterations, wherein each parameter of the obtained optimal particle is the solved imbalance parameter. According to the invention, the method meets the requirements of high-precision and simple-operation rotor dynamic balance occasions.

Description

technical field [0001] The invention relates to the technical field of rotor dynamic balance, in particular to an unbalance parameter identification method suitable for multi-faceted rotors. Background technique [0002] The stability of the rotor operation is an important criterion to measure the performance of the rotating machinery. In the actual field, due to the interference of many factors, the rotor will appear unstable, resulting in the dynamic imbalance of the rotor. In order to ensure the normal operation of the rotor, it is necessary to regularly evaluate the performance of the rotor to reduce the impact of unbalanced faults. Many faults that produce rotor unbalance can be roughly divided into two categories according to their causes: static faults and dynamic faults. Static faults refer to unbalanced faults that still exist when the equipment stops running, such as uneven rotor mass distribution and centroid offset caused by machining errors and assembly errors....

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Problems solved by technology

However, both of these two methods have the problem of unbalance parameter solution accuracy. The number of measuring point surfaces for rotor balance detection is less than the number of surfaces to be balanced. The resulting ill-conditioned problem of the solution equation is generally solved by increasing the number of tests. This method still has some limitations

In the rotor unbalance parameter identification problem, the accuracy of the unbalance parameter solution directly determines the quality of a method. Some scholars indirectly achieve high identification accuracy by continuously improving the accuracy of the solution model, and some scholars continue to improve the solution algorithm. In order to obtain higher precision parameter values, but the increased computational complexity due to excessive pursuit of precision also makes these methods difficult to be practically applied

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