摘要
针对飞参系统记录的剩余燃油信号量化噪声较大且呈非线性、非平稳性的特点以及经验模态分解(empirical mode decomposition,简称EMD)中存在的模态混叠给燃油消耗率提取带来的问题,提出了基于复数据经验模态分解(complex empirical mode decomposition,简称CEMD)的燃油消耗率提取方法。首先,提取记录信号中的关键信息,并利用非线性支持向量回归构造与真实信号形态上接近的模拟信号;然后,在CEMD中利用模拟信号来指导记录信号同步分解以减小模态混叠;最后,从分解结果中估算真实的剩余燃油信息并对其求一阶导数得到燃油消耗率。仿真结果表明,该方法相对于其他方法具有明显的性能优势,可以提取出精确的燃油消耗率参数。
A method of fuel consumption extraction based on complex empirical mode decomposition is proposed to solve the fuel consumption extraction problems resulting from high quantization noise,and nonlinear and non-stationary characteristics of residual fuel volume recorded by a flight data recorder,as well as the mode mixing in empirical mode decomposition.First,a simulated signal with a similar morphology to the real signal is constructed with nonlinear support vector regression using the recorded signal's key message.Second,the mode mixing can be reduced by using a simulant signal to synchronously guide the decomposition of the recorded signal in complex empirical mode decomposition.Finally,the fuel consumption is equivalent to the first-order derivative of real residual fuel volume estimated from the decomposition results.Simulation results show that this method has more advantages compared with other methods,and is adequate for extracting precious fuel consumption.
出处
《振动.测试与诊断》
EI
CSCD
北大核心
2015年第5期902-907,992,共6页
Journal of Vibration,Measurement & Diagnosis
基金
国家自然科学基金资助项目(61372027)
关键词
经验模态分解
模态混叠
复数据经验模态分解
非线性支持向量回归
燃油消耗率
empirical mode decomposition(EMD)
mode mixing
complex empirical mode decomposition(CEMD)
nonlinear support vector regression
fuel consumption