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Waste Disposal & Sustainable Energy
Waste Disposal & Sustainable Energy  2021, Vol. 3 Issue (1): 21-30    DOI: 10.1007/s42768-020-00065-6
    
针对外界扰动下热声振荡启动阶段声压波动的预测
Prediction of sound pressure fluctuations in the start-up phase of thermoacoustic oscillations under external perturbation
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摘要： 为了抑制燃气轮机的热声不稳定性，须预测燃烧室中的压力变化。基于非线性理论，结合Rijke型燃烧器在外部声源干扰下的声压波动时间序列数据，建立了一种新型数据驱动模型来预测外部声源干扰下的燃烧器内部声压波动。提出了一种改进的粒子群优化（PSO）算法对支持向量回归（SVR）模型的参数进行优化，改进后的PSO算法所需的参数优化时间仅为改进前的3/5。结果表明，改进的数据驱动模型可以至少提前0.94ms准确地预测声压振荡信号。改进的PSO-SVR模型与多层感知器（MLP）模型和高斯过程回归（GPR）模型相比，能够更准确地预测变工况下的声压波动，为预测和消除实际燃烧室中的热声振荡提供有效的指导。
Abstract: To suppress excessive thermoacoustic instabilities in the gas turbine, it must be possible to predict pressure changes in the combustion chamber. The time-series data of acoustic pressure fluctuations in the Rijke type burner under external sound source interference were studied combined via nonlinear theory, and a new data-driven model for predicting internal sound pressure fluctuations under such conditions was established. An improved particle swarm optimization (PSO) algorithm was proposed to optimize the parameters of the support vector regression (SVR) model, and the parameter optimization time required for the improved PSO algorithm is only 3/5 of that before the improvement. The results show that at least 0.94 ms ahead, the improved data-driven model can accurately predict sound pressure oscillation signals. The improved PSO-SVR model proved to be more accurate than the Multilayer Perceptron (MLP) model and Gaussian process regression (GPR) model in predicting the fluctuation of sound pressure under variable conditions and can provide effective guidance for predicting and eliminating the thermoacoustic oscillations in the actual combustion chambers.
出版日期: 2021-06-27
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Zi-Hua Liu
Hao Zhou
Cheng-Fei Tao
Muhammad Waryal Dahri & Ming-Xi Zhou

引用本文:

Zi-Hua Liu, Hao Zhou, Cheng-Fei Tao, Muhammad Waryal Dahri & Ming-Xi Zhou. Prediction of sound pressure fluctuations in the start-up phase of thermoacoustic oscillations under external perturbation. Waste Disposal & Sustainable Energy, 2021, 3(1): 21-30.

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https://www.zjujournals.com/wdse/CN/10.1007/s42768-020-00065-6    或    https://www.zjujournals.com/wdse/CN/Y2021/V3/I1/21

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