| 基于ARMA模型滤波的微弱信号辨识 |
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| 引用本文： | 高丽丽,何松柏.基于ARMA模型滤波的微弱信号辨识[J].四川理工学院学报(自然科学版),2012,25(2):51-54. |
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| 作者姓名： | 高丽丽 何松柏 |
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| 作者单位： | 1. 四川理工学院理学院,四川自贡,643000
2. 电子科技大学电子工程学院,成都,610054 |
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| 摘 要： | 双线性时频分布能更全面地表征复杂背景下瞬态机械故障信号特征,但双线性时频变换固有的交叉项干扰严重影响了算法的时频分辨率。探讨了双线性时频分析技术在微弱瞬态信号辨识中的应用,提出采用ARMA模型滤波的方法来抑制双线性Wigner-Ville时频变换的交叉项干扰,并给出算法推导。结合实验数据,对比平滑伪Wigner-Ville算法的信号辨识结果,表明基于ARMA模型预滤波的双线性时频分析能更好的抑制交叉项干扰,具备更高的时频分辨能力和瞬态微弱信号辨识能力。
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| 关 键 词： | ARMA模型滤波 双线性时频分布 微弱信号辨识 |
Time-Frequency Identification of Weak Signal Using ARMA Filter |
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| GAO Li-li,HE Song-bai.Time-Frequency Identification of Weak Signal Using ARMA Filter[J].Journal of Sichuan University of Science & Engineering:Natural Science Editton,2012,25(2):51-54. |
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| Authors: | GAO Li-li HE Song-bai |
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| Institution: | 1.School of Science,Sichuan University of Science & Engineering,Zigong 643000,China; 2.School of Electronic Engineering,University of Electronic Science and Technology of China,Chengdu 610054,China) |
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| Abstract: | Bilinear time-frequency distribution can token overall mechanical failure signal characteristics,but it’s found that strong cross-terms exist which results in frequency aliasing and information loss.The time-frequency analyze is used to identificate the weak winking signal in complex background.Arithmetic based on ARMA model filter is bring forward to solve cross-terms problem.It is simulated in experiment data and contrasted to Smooth-Puppet Wigner-Ville arithmetic.The conclusion is that arithmetic of ARMA model pre-filter restrained cross-terms disturbance better and is of better weak winking signal identification ability. |
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| Keywords: | ARMA model pre-filter bilinear time-frequency distribution weak signal identification |
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