湯琴,黃宜堅(jiān)
(華僑大學(xué)機(jī)電及自動(dòng)化學(xué)院,福建泉州 362021)
采用AR模型雙譜估計(jì)的概率篩篩分效率
湯琴,黃宜堅(jiān)
(華僑大學(xué)機(jī)電及自動(dòng)化學(xué)院,福建泉州 362021)
建立概率篩振動(dòng)信號(hào)的自回歸模型,進(jìn)行雙譜估計(jì).從雙譜及其對(duì)角切片中獲得譜特征和篩分效率之間的關(guān)系,并找出最佳篩分效率的譜特征.實(shí)驗(yàn)和研究結(jié)果表明:不同的篩分效率有著不同的譜特征,篩分效率的高低與譜高峰出現(xiàn)的頻率范圍,高峰兩側(cè)陡度的對(duì)稱性和零處的耦合性有很大關(guān)系.
概率篩;自回歸模型;雙譜;對(duì)角切片;篩分效率
概率篩是基于概率篩分理論研制而成的,其應(yīng)用雖然廣泛,但目前的研究主要停留在對(duì)工程實(shí)際的描述或總結(jié),以及采用獨(dú)立因子法分析影響概率篩篩分效率的因素.篩分效率是評(píng)價(jià)該系統(tǒng)動(dòng)力學(xué)品質(zhì)的一項(xiàng)綜合指標(biāo),受多種因素影響,非線性作用特征明顯.高階譜具有從非高斯信號(hào)、非最小相位及非線性系統(tǒng)中獲得功率譜所不能獲得的信息的優(yōu)點(diǎn),在現(xiàn)代信號(hào)處理領(lǐng)域得到廣泛應(yīng)用.目前的高階譜研究主要限于雙譜的應(yīng)用研究[1-2].本文利用基于自回歸(AR)模型估計(jì)的雙譜及其對(duì)角切片,找出譜特征與篩分效率之間的相關(guān)性.
三階累積量C3,x及其雙譜Exxx(f1,f2)[3-4]分別定義為
式(1)中:E[*]是期望算子;τ為滯后時(shí)間;*為共軛復(fù)數(shù);X(f)由xt進(jìn)行Fourier變換得到.
由振動(dòng)概率篩實(shí)驗(yàn)獲得的時(shí)序{xt},可建立AR(n)模型[5-6],即
式(2)中:a(t)是獨(dú)立同分布的.引入后移算子B,則式(2)可表示為
從信息論的角度理解,系統(tǒng)的所有動(dòng)力學(xué)信息都蘊(yùn)藏在參數(shù)φ1,φ2,…,φn中.因此,基于AR模型參數(shù)的雙譜估計(jì)所獲得的雙譜及對(duì)角切片,可以反映系統(tǒng)的動(dòng)力學(xué)品質(zhì).
雙譜是三階累積量C3,x的二次Fourier的變換,可看成是三階矩在頻域內(nèi)的分解,對(duì)分析非對(duì)稱的非線性系統(tǒng)很有意義.由于高斯分布的高階累積量恒為零,即Ck,U=0(k>3),則其雙譜也為零[7-8].如果信號(hào)的概率密度函數(shù)是對(duì)稱的,即峰度等于零,則其雙譜也為零[9].雙譜還可保留相位信息,識(shí)別非線性特征.
將振動(dòng)概率篩系統(tǒng)抽象為如圖1所示的模型.假設(shè)輸入信號(hào)a(t)和輸出信號(hào)y(t)均為零均值的平穩(wěn)隨機(jī)序列,x(t)受到加性噪聲u(t)的干擾,系統(tǒng)的傳遞函數(shù)為h(t),則有
圖1 振動(dòng)概率篩系統(tǒng)的模型Fig.1 Model for the vibratingprobability screen
其中:τ為滯后量;u(t)假設(shè)為高斯噪聲.若白噪聲a(t)是獨(dú)立同分布且非高斯,則三階累積量γa,3=cum[a(t)a(t+τ1)a(t+τ2)]=βδ(τ1,τ2),又加性噪聲u(t)被完全抑制,則輸出信號(hào)y(t)的雙譜[10]可定義為
式(4)中:H(ω)為系統(tǒng)頻響函數(shù).由式(3)可得到
當(dāng)ω1=ω2時(shí),可得雙譜的一維對(duì)角切片譜,其定義[3]為
由于雙譜估計(jì)量的方差大小與功率譜的三重積分成比例,導(dǎo)致信號(hào)的二階特性凸顯[11],高階統(tǒng)計(jì)量的特性減弱,因此,常采用雙譜的歸一化減弱其二階特性.雙譜歸一化后的幅值[12]為
式(7)中:|S|=|γa,3|;S為非高斯白噪聲的峰度.
3.1 實(shí)驗(yàn)原理與測試裝置
圖2 自同步概率篩結(jié)構(gòu)Fig.2 Structure of self-synchronization probability screen
概率篩由1個(gè)箱形框架和3層篩篩網(wǎng)組成,篩網(wǎng)與水平面有一定傾角,大小自上而下遞增,如圖2所示.篩體作業(yè)時(shí),篩箱上的2個(gè)帶偏心塊的激振電機(jī)同步反向旋轉(zhuǎn)產(chǎn)生的激振力,使篩體高頻直線振動(dòng).
考慮對(duì)概率篩篩分效率(η)影響較大的給料速度、概率篩振動(dòng)圓頻率、篩網(wǎng)傾角和振幅4個(gè)工藝參數(shù).其中:給料速度為3.5 t·h-1;概率篩振動(dòng)圓頻率選擇 700,750,800,850, 960,1 100和1 250 r·min-1共7種參數(shù);篩網(wǎng)傾角選擇18°, 19°,20°,21°,22°和26°共6種參數(shù);振幅為3,4,5,6和7 mm共5種參數(shù).在實(shí)驗(yàn)中,采樣頻率設(shè)置為1 024 Hz,讀取頻率為512 Hz.利用N I軟件Labview構(gòu)建檢測平臺(tái),使用 PCI-6014數(shù)據(jù)采集卡,加速度傳感器和位移傳感器,總共獲得69種工況下的振動(dòng)信號(hào)數(shù)據(jù).
3.2 振動(dòng)信號(hào)預(yù)處理
采用中數(shù)法對(duì)實(shí)驗(yàn)數(shù)據(jù)進(jìn)行預(yù)處理,濾去確定信號(hào),保留高頻的有色噪聲信號(hào),如圖3所示.圖3中:n為采樣數(shù)據(jù);a為加速度.
3.3 試驗(yàn)分析
3.3.1 高篩分效率的對(duì)角切片譜分析 通過對(duì)實(shí)驗(yàn)數(shù)據(jù)分析處理,可獲得篩分效率較高的4種類型的對(duì)角切片譜特征,如表1,圖4,5所示.表1中:α為篩面傾角;A為振幅;f為振動(dòng)頻率;η為篩分效率.當(dāng)η高于83%時(shí),定義為高篩分效率;反之,則規(guī)定為低篩分效率.
由圖4可知,在頻率0~π范圍內(nèi),當(dāng)一高峰出現(xiàn)在頻率π/4和3π/8之間,且在0處不出現(xiàn)尖峰時(shí),高峰兩側(cè)陡度相同的切片譜所對(duì)應(yīng)的η一般相對(duì)較高;若一對(duì)角切片譜與之越相似,則其η越高,反之則越來越低.
圖3 預(yù)處理前后的數(shù)據(jù)Fig.3 Data before and after processing
表1 篩分效率最高的4種類型的對(duì)角切片譜特征Tab.1 Characteristics of the diagonal slices with highest screening efficiency for four kinds of spectrum
圖4 篩分效率最高的4種類型的歸一化雙譜圖Fig.4 No rmalized double-spectra bispectrums
圖5 對(duì)應(yīng)圖4的對(duì)角切片F(xiàn)ig.5 Diagonal slices corresponding to the bispectrums in Fig.4
圖6 譜特征與圖5(a)相似的部分對(duì)角切片F(xiàn)ig.6 Partial diagonal slices with characteristics similar to Fig.5(a)
譜特征與圖5相似的部分對(duì)角切片,如圖6~9所示.從圖6可知,圖6的譜特征與圖5(a)相似.即在頻率0~π范圍內(nèi),當(dāng)其切片譜有一耦合高峰,且高頻出現(xiàn)一小峰時(shí),η一般相對(duì)較高,在84%以上.從圖7可知,圖7的譜特征與圖5(b)相似.即在頻率0~π范圍內(nèi),當(dāng)其切片譜有一耦合高峰,且低頻出現(xiàn)一小峰時(shí),則其η一般相對(duì)較高,在84%以上.從圖8可知,圖8的譜特征與圖5(c)相似.即在頻率0~π范圍內(nèi),當(dāng)切片譜有一耦合高峰,且低頻處有極小的波峰時(shí),其η一般相對(duì)較高,在85%以上.但它有特例,即在低頻處的極小峰退化,形成一光滑的高峰,η在83%~88%之間.從圖9可知,圖9的譜特征與圖5(d)相似.即在頻率0~π范圍內(nèi),當(dāng)切片譜有一耦合高峰,且高頻處有一小峰時(shí),其η一般相對(duì)較高,在83%以上.
圖7 譜特征與圖5(b)相似的部分對(duì)角切片F(xiàn)ig.7 Partial diagonal slices with characteristics similar to Fig.5(b)
圖8 譜特征與圖5(c)相似的部分對(duì)角切片F(xiàn)ig.8 Partial diagonal slices with characteristics similar to Fig.5(c)
圖9 譜特征與圖5(d)相似的部分對(duì)角切片F(xiàn)ig.9 Partial diagonal slices with characteristics similar to Fig.5(d)
3.3.2 低篩分效率的對(duì)角切片譜分析 當(dāng)振動(dòng)頻率f為高頻時(shí),即f為1 100 Hz或者1 250 Hz時(shí),其η一般都很低,低于78%,f越高,η越小.另外,當(dāng)出現(xiàn)以下4種情況時(shí),η較低:(1)若對(duì)角切片譜具有高頻時(shí)的切片譜特征,則η一般較低,低于80%,如中間耦合,耦合高峰頂端出現(xiàn)小凹口或有兩不規(guī)則高峰,分別如圖10(a),(b)和(c)所示;(2)在頻率0~π范圍內(nèi),當(dāng)有兩高峰時(shí),且高頻峰較高,其η一般較低,80%左右,如圖10(d)所示;(3)當(dāng)對(duì)角切片譜在邊界發(fā)生明顯線性耦合時(shí),其篩分效率一般很低;(4)若對(duì)角切片譜的主高峰兩側(cè)陡度不等,則其篩分效率一般很低,如圖10(e)所示.
圖10 低篩分效率的對(duì)角切片F(xiàn)ig.10 Diagonal slices with low screening efficiency
數(shù)據(jù)分析后,可以得到有以下3點(diǎn)結(jié)論.
(1)高階譜是處理非高斯、非線性的有力工具,可以從振動(dòng)信號(hào)中提取出影響篩分效率η的譜特征信息.
(2)篩分效率η與雙譜對(duì)角切片的相關(guān)性在頻率0~π范圍內(nèi).當(dāng)一耦合高峰出現(xiàn)在π/4和3π/8之間,且在0處沒有耦合,高峰兩側(cè)陡度相同的對(duì)角切片譜所對(duì)應(yīng)的篩分效率η一般相對(duì)較高,數(shù)值在84%以上.
(3)當(dāng)供料速度為3.5 t·h-1時(shí),可獲得5組最佳參數(shù)組合:(a)當(dāng)α=20°,A=5 mm,f=700 Hz時(shí),篩分效率η為93.9%;(b)當(dāng)α=21°,A=4 mm,f=700 Hz時(shí),篩分效率η為92.6%;(c)當(dāng)α= 20°,A=4 mm,f=750 Hz時(shí),篩分效率η為92.5%;(d)當(dāng)α=20°,A=4 mm,f=800 Hz時(shí),篩分效率η為91.0%;(e)當(dāng)α=22°,A=4 mm,f=700 Hz時(shí),篩分效率η為89.9%.
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(責(zé)任編輯:陳志賢英文審校:崔長彩)
Analysis of Probability Screen Efficiency Using Bispectrum Estimation Based on AR M odel
TANG Qin,HUANG Yi-jian
(College of Mechanical Engineering and Automation,Huaqiao University,Quanzhou 362021,China)
Auto-regressive model for vibration signals of probability screen was used to estimate bispectrum in this paper.From the features of the bispectrum and its diagonal slices,the relationship between the characteristics of the spectrums and screening efficiencies was found,and the spectrum characteristics of the highest screening efficiency were described.Results showed that different screening efficiencies were co rresponding to different spectral features,and it also indicated that the high and low efficiency of the screen is of great relevance with the angle range of a coup ling peak appearing,the symmetric properties of the gradient on two sides of the peak and the coupling at angle 0.
probability screen;auto-regressive model;bispectrum;diagonal slice;screening efficiency
TD 452
A
1000-5013(2011)03-0253-05
2010-10-05
黃宜堅(jiān)(1945-),男,教授,主要從事機(jī)械電子的研究.E-mail:yjhuang@hqu.edu.cn.
國家自然科學(xué)基金資助項(xiàng)目(50975098)