Spectral Oscillation Amplitude Estimation for Turbulent Flow Instability
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Solution Overview
Problem
Predicting the onset and amplitude of oscillatory instabilities in turbulent flow systems, such as gas turbines and wind turbines, is challenging due to complex processes, and existing methods rely heavily on flame describing functions and acoustic boundary conditions, which are difficult to measure, especially at high pressures.
Innovation Solution
A system comprising a sensor, analog-to-digital converter, amplitude estimator, processing unit, and controller that estimates the spectral measure of time series signals to predict the amplitude of limit cycle oscillations and control system parameters to prevent instability, without requiring flame describing function data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional methods using flame describing function and acoustic boundary conditions are used to estimate oscillation amplitude, then prediction accuracy may be improved, but measurement difficulty increases significantly at high pressures
Solution Approach 1:
The patent extracts the essential information needed for amplitude prediction from the complex Flame Describing Function by identifying and measuring only the key spectral characteristics (spectral measure) of the oscillatory signal. This extraction approach allows accurate amplitude estimation without requiring complete FDF characterization, thereby reducing measurement difficulty while maintaining prediction accuracy.
Solution Approach 2:
The patent replaces the conventional mechanical/acoustic measurement approach (requiring physical boundary condition measurements and FDF determination) with a signal processing approach using spectral analysis of sensor data. This substitution eliminates the need for difficult high-pressure acoustic measurements while preserving the ability to predict oscillation amplitudes accurately.
2Reliability
If flame describing function data is obtained through conventional methods, then amplitude prediction can be performed, but system complexity and operational difficulty increase
Solution Approach 1:
The system uses the existing oscillatory signals already present in the combustor during normal operation to directly estimate amplitude, rather than requiring separate FDF measurement procedures. The spectral measure is extracted from the self-generated oscillatory signal, eliminating the need for additional measurement equipment or complex procedural steps.
Solution Approach 2:
The patent changes the approach from measuring physical parameters (acoustic boundary conditions, FDF characteristics) to analyzing spectral parameters (spectral measure of the oscillatory signal). This parameter transformation simplifies the measurement process while maintaining the reliability of amplitude predictions.
3Measurement precision
If large amplitude oscillations are excited to determine flame describing function, then FDF accuracy improves, but system stability is compromised and operational safety is reduced
Solution Approach 1:
The patent uses partial action by extracting only the necessary spectral information from small-amplitude oscillations that occur during normal operation, rather than requiring full FDF characterization from large-amplitude excitation. This partial measurement approach is sufficient for amplitude prediction while maintaining system stability.
Solution Approach 2:
The system performs preliminary spectral analysis on oscillatory signals during normal stable operation to predict future amplitude behavior. By analyzing the spectral measure in advance during stable conditions, the system can predict impending instabilities without needing to excite large oscillations that would compromise stability.
Data Source
AI summary
Embodiments herein provide a system (100) to estimate the amplitude of oscillations in a turbulent flow system (102) that exhibits oscillatory instabilities. The system (100) comprises of a sensor (102A) mounted on the turbulent flow system (102) to detect an oscillatory variable in the system obtaining a signal, a signal conditioner (104) that conditions the signal from the sensor, an amplitude estimator (110) that estimates the amplitude of the limit cycle oscillations, and also predict the proximity of the system to the oscillatory instability, a processor (108) connected to the amplitude estimator (110) to compare the predicted oscillation amplitude with a threshold value. The amplitude is estimated by estimating the spectral measure of the time series signal obtained from the system.