基于遗传算法的涡街信号随机共振检测方法

涡街流量计在工业现场工作时,输出信号易叠加噪声,尤其在小流量测量时,涡街信号易被现场噪声淹没,导致测量受限。针对涡街信号处理,提出一种基于遗传算法的双调制随机共振方法。该方法对输入信号进行频率和幅值双调制后进入非线性双稳系统,以系统输出信号的信噪比为适应度函数,通过二进制编码,将调制频率和幅值组合成一个二进制字符串,同时对两个参数进行并行寻优,得到最优解,使系统产生随机共振,增强涡街信号。搭建涡街流量计实验装置,实验结果表明,使用遗传算法可以有效搜索出调制频率和幅值最优解,搜索效率高,解决现有多参数寻优的困难,适用于涡街信号特别是小流量信号处理,能准确获取涡街频率,实现流量测量。

Stochastic resonance detection method of vortex signal based on genetic algorithm

While the vortex flowmeter is used in the industrial site,the vortex signal is easy to be added the environment noise leading to the limitation of measurement,especially for small flow measurements.For vortex signal processing,a dual modulated stochastic resonance method based on genetic algorithm was proposed.The input signal was dual modulated in frequency and amplitude before getting into the nonlinear bistable system.The signal-to-noise ratio of the output signal was used as the fitness function.The modulation frequency and amplitude were combined to a binary sting by binary coding to find the optimal values simultaneously to generate the stochastic resonance and enhance the vortex signal.The vortex flowmeter experimental device was set up for flow measurement.The experimental results indicate that the genetic algorithm can obtain the optimal solution of modulation frequency and amplitude with high search efficiency,solving the difficulty of multi parameter optimization.The method is suitable for the processing of vortex signal especially in the low flowrate situation.The vortex frequency can be obtained accurately to realize the flowrate measurement.