联合收割机清选损失传感器谷粒冲击信号的混沌检测

Chaos detection of grain impact at combine cleaning loss sensor

该文利用混沌算法来实现联合收割机清选损失谷粒冲击信号的检测,以达到降低清选损失检测系统成本、提高系统可靠性的目的。应用LS-DYNA仿真谷粒冲击传感器的过程,得到谷粒以3 m/s的速度冲击传感器时的位移信号;建立了单Duffing振子检测系统和双耦合Duffing检测系统的simulink仿真模型;得到2个检测系统对正弦信号幅值的检测下限;利用周期图像法检测白噪声的功率谱密度,得到2个检测系统白噪声的临界功率谱密度;同时加入信号和白噪声,检测出两个检测系统的信噪比,双耦合Duffing振子检测系统可以检测出单颗谷粒的冲击,可以发现Duffing振子检测系统在微弱信号检测方面比传统时域检测方法有更大的优越性。该研究可以应用于联合收割机谷物清选损失的检测。

A novel detecting method of grain impacting combine cleaning loss sensor was suggested. The simulation model of grain impacting force-sensitive components was established in LS-DYNA platform. The displacement signal of grain impacting force-sensitive component at a speed of 3 m/s was acquired by simulation. Both Duffing oscillator detection and Coupled Duffing Oscillators detecting system were built to detect weak grain impact signal. The power spectral density of white noise by cycle image method was detected and the critical power spectral density of the two detecting systems was got. The signal to noise ratios of the two systems were detected while adding the weak grain impact signal and white noise. Single grain impact signal could be detected by the Coupled Duffing Oscillators detecting system directly and quickly. It was found that Duffing oscillator detecting system have great advantages in detecting weak grain impact signal under strong noise background. The research has a potential applying prospect in combine cleaning loss detection.