【摘要】：針對機械振動信號提取時面臨的去噪問題,在小波包多閾值準則去噪法的基礎上,提出一種改進的小波包多閾值準則綜合去噪方法(改進FMC去噪法)。該方法首先采用探測插值法對機床原始振動信號進行預處理,剔除受外界干擾產生的突變噪聲信號;再以小波包分析為基礎,根據(jù)有用信號的最小頻率確定最大分解層數(shù),并按最小代價原理確定信號分解的最佳小波包基;最后采用小波包多閾值降噪準則對振動信號進行重構,得到去噪后的機床振動信號。針對含噪blocks信號、doppler信號及模擬的含噪振動信號進行的仿真實驗結果表明,改進后的FMC去噪法去噪效果優(yōu)于傳統(tǒng)方法。將該方法應用于氣囊修整機振動信號分析中,結果表明,改進FMC去噪法能夠有效剔除振動信號各頻段的噪聲,提高信號特征的可分離性。
[Abstract]:Aiming at the problem of de-noising in mechanical vibration signal extraction, an improved wavelet packet multi-threshold criterion comprehensive denoising method (improved FMC denoising method) is proposed based on wavelet packet multi-threshold criterion de-noising method. In this method, the original vibration signal of the machine tool is preprocessed by detecting interpolation method, and the sudden noise signal caused by external interference is eliminated, and then the maximum decomposition layer number is determined according to the minimum frequency of the useful signal based on wavelet packet analysis. The optimal wavelet packet basis for signal decomposition is determined according to the principle of minimum cost. Finally, the vibration signal is reconstructed by wavelet packet multi-threshold de-noising criterion, and the vibration signal of machine tool after denoising is obtained. The simulation results of the noisy blocks signal and the simulated noisy vibration signal show that the improved FMC denoising method is better than the traditional method. The method is applied to the vibration signal analysis of air bag repair machine. The results show that the improved FMC denoising method can effectively eliminate the noise of the vibration signal and improve the separability of the signal characteristics.
【作者單位】： 廈門大學航空航天學院;
【基金】：國家自然科學基金資助項目(51675453) 深圳科技計劃資助項目(JCYJ20160517103720819)
【分類號】：TN911.7

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