基于时幅拐点的突发信号特征频率捕获算法

Characteristic Frequency Acquisition Algorithm of Burst Signal Based on Amplitude-Time Inflection Point

针对液体火箭发动机高速轴承振动数据时域信号中隐藏的突变信号难以发现的问题,在时幅拐点曲线的基础上,提出了突发信号特征频率捕获算法.首先构造出5个突变数值参数,通过这些参数对各类突发信号的突发特性进行放大,这些放大的参数可以进一步提供突发信号的频率和时间信息;然后利用这些频率和时间信息对突发信号进行准确分析.理论分析、工程仿真和高速轴承振动数据分析表明,该算法能够捕获突变信号,可以从海量数据和成千上万个频率中聚焦有价值的突发信号.

To solve the problem that it is difficult to find the hidden mutation signal in the vibration data of liquid high speed bearing of rocket engine,the frequency acquisition algorithm is proposed on the basis of the amplitudetime inflection point curve. First,5 mutation numerical parameters are constructed,through which the burst characteristics of all kinds of burst signals are amplified. These amplified parameters can further provide the frequency and time information of burst signals,and then the frequency and time information are used to analyze the burst signals accurately. Theoretical analysis,engineering simulation and high speed bearing vibration data analysis show that the algorithm can capture the mutation signal and focus on the valuable burst signals from the mass data and thousands of frequencies.