A method and system for early warning of the tipping moment of a thermoacoustic system under Lévy noise

By using a stochastic differential equation model of Lévy noise and time-varying control parameters, combined with the Shannon entropy index, the problem of accurate early warning of tipping time in thermoacoustic systems was solved, achieving timely and reliable early warning for thermoacoustic systems.

CN122154137APending Publication Date: 2026-06-05QINGDAO UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
QINGDAO UNIV OF TECH
Filing Date
2025-11-14
Publication Date
2026-06-05

AI Technical Summary

Technical Problem

Existing technologies struggle to accurately simulate extreme events in real-world noise environments and neglect the rate of change of control parameters, resulting in inaccurate tipping warnings for thermoacoustic systems and an inability to provide timely and effective active control guidance.

Method used

Lévy noise was used to simulate extreme events, and a stochastic differential equation model of time-varying control parameters was established. Shannon entropy was used as an early warning indicator. The dynamic characteristics of the system were solved by Monte Carlo simulation and stochastic fourth-order Runge-Kutta numerical method to determine the early warning time and generate the early warning domain.

Benefits of technology

This improves the reliability of early warning results, accurately reflects the dynamic evolution of the thermoacoustic system, and enables timely early warning of tipping moments, thereby enhancing the accuracy and reliability of early warnings.

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Abstract

The application provides a warning method and system for the tipping moment of a thermoacoustic system under Lévy noise, and relates to the technical field of thermoacoustic system stability analysis and early warning control, which comprises the following steps: based on the physical model of the thermoacoustic system, a non-uniform wave equation describing the pressure and velocity fluctuation of the system is constructed; the Galerkin modal expansion and Taylor expansion truncation are performed on the equation, and a random differential equation model is established by combining the time-varying control parameters and Lévy noise; the random differential equation model is solved by the Monte Carlo simulation and the random fourth-order Runge-Kutta numerical method, and the amplitude sequence of the thermoacoustic system changing with time is obtained; based on the probability distribution of the amplitude sequence, the change of the system dynamics characteristics is quantified by calculating the Shannon entropy, and the sequence of the Shannon entropy changing with time is obtained; the warning moment when the Shannon entropy sequence first passes through the preset threshold is determined, and the warning domain is generated according to the time difference between the warning moment and the actual tipping moment of the thermoacoustic system, so that the warning for the tipping moment of the thermoacoustic system is realized.
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