A method for preprocessing vibration signals of hydropower units

By improving the dung beetle algorithm to optimize the ICEEMDAN algorithm, modal decomposition of the vibration signal of the hydroelectric unit is solved, and the monitoring and analysis problems of the vibration problem of the hydroelectric unit is achieved, and high-precision signal analysis and fault prevention are achieved.

CN119760630APending Publication Date: 2025-04-04YUNNAN ELECTRIC POWER TESTING & RES INST (GRP) CO LTD
0 Cites 3 Cited by

Patent Information

Application Number
CN202411803923.0
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-10
Publication Date
2025-04-04

AI Technical Summary

Technical Problem

The vibration problems of hydropower units are becoming increasingly prominent, affecting the safe and stable operation of the power system. It is difficult for the existing technology to effectively monitor and analyze vibration signals to prevent failures.

Method used

A pre-treatment method for vibration signal of the hydroelectric unit is adopted, and the modal decomposition of the vibration signal is performed through parameter optimization of the ICEEMDAN algorithm, combined with PWLCM chaotic mapping, nonlinear boundary convergence factor, dynamic gold sine, sparrow alerter mechanism and parameter adaptive adjustment strategy.

Benefits of technology

It improves the decomposition accuracy of vibration signals, ensures the accuracy of signal analysis of water-power unit, can effectively monitor and analyze vibration signals, and prevent faults.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The present invention provides a method for preprocessing vibration signals of a hydropower unit. The present invention proposes five strategies to improve the optimization accuracy of a dung beetle algorithm so that it has good robustness. The improved dung beetle algorithm MSIDBO jumps out of the local optimum through PWLCM chaotic mapping, nonlinear boundary convergence factor, rolling ball behavior integrating dynamic golden sine, sparrow alert mechanism and parameter adaptive adjustment to improve the accuracy of the optimization problem. With the minimum envelope entropy as the fitness function, MSIDBO is used to optimize parameters such as the white noise amplitude weight Nstd and the number of noise additions NE of ICEEMDAN, and the optimized ICEEMDAN is used to perform modal decomposition of the vibration signal of the hydropower unit. The MSIDBO algorithm has a faster convergence speed, higher solution accuracy and better applicability than the standard dung beetle algorithm. Through simulation signal analysis, it is concluded that the decomposition accuracy of the optimized ICEEMDAN is higher than that of the conventional decomposition algorithm, which improves the accuracy of the preprocessing of the vibration signal of the hydropower unit and provides a basis for the intelligent vibration monitoring and diagnosis of the hydropower unit.
Need to check novelty before this filing date? Find Prior Art