【摘要】：針對(duì)機(jī)械振動(dòng)信號(hào)提取時(shí)面臨的去噪問題,在小波包多閾值準(zhǔn)則去噪法的基礎(chǔ)上,提出一種改進(jìn)的小波包多閾值準(zhǔn)則綜合去噪方法(改進(jìn)FMC去噪法)。該方法首先采用探測(cè)插值法對(duì)機(jī)床原始振動(dòng)信號(hào)進(jìn)行預(yù)處理,剔除受外界干擾產(chǎn)生的突變?cè)肼曅盘?hào);再以小波包分析為基礎(chǔ),根據(jù)有用信號(hào)的最小頻率確定最大分解層數(shù),并按最小代價(jià)原理確定信號(hào)分解的最佳小波包基;最后采用小波包多閾值降噪準(zhǔn)則對(duì)振動(dòng)信號(hào)進(jìn)行重構(gòu),得到去噪后的機(jī)床振動(dòng)信號(hào)。針對(duì)含噪blocks信號(hào)、doppler信號(hào)及模擬的含噪振動(dòng)信號(hào)進(jìn)行的仿真實(shí)驗(yàn)結(jié)果表明,改進(jìn)后的FMC去噪法去噪效果優(yōu)于傳統(tǒng)方法。將該方法應(yīng)用于氣囊修整機(jī)振動(dòng)信號(hào)分析中,結(jié)果表明,改進(jìn)FMC去噪法能夠有效剔除振動(dòng)信號(hào)各頻段的噪聲,提高信號(hào)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(xué)航空航天學(xué)院;
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(51675453) 深圳科技計(jì)劃資助項(xiàng)目(JCYJ20160517103720819)
【分類號(hào)】：TN911.7

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