郭常盈 吳冉
摘 要: 現(xiàn)有的相位測(cè)量算法進(jìn)行光反饋?zhàn)曰旌细缮嫖灰茖?shí)時(shí)跟蹤測(cè)量時(shí),未考慮原始光反饋?zhàn)曰旌细缮嫘盘?hào)中的噪聲干擾,導(dǎo)致測(cè)量精度差。因此,對(duì)光反饋?zhàn)曰旌细缮嫖灰茖?shí)時(shí)跟蹤測(cè)量算法進(jìn)行改進(jìn),采用自適應(yīng)濾波系統(tǒng)去除光反饋?zhàn)曰旌细缮嫘盘?hào)中的噪聲,通過(guò)去噪后的自混合信號(hào)實(shí)施變換處理獲取解析信號(hào),提取解析信號(hào)的包裹相位突變點(diǎn),根據(jù)相位突變點(diǎn)與正負(fù)單位脈沖的乘積定位相位突變點(diǎn)的正確方向,得到自混合干涉條紋;去除自混合干涉條紋中的小數(shù)條紋獲取全部整數(shù)條紋點(diǎn),對(duì)條紋點(diǎn)進(jìn)行賦值、差值和平滑處理,獲取外部目標(biāo)重構(gòu)位移軌跡,即光反饋?zhàn)曰旌细缮嫖灰啤?shí)驗(yàn)結(jié)果表明,所提算法具有較高的光反饋?zhàn)曰旌细缮嫖灰茖?shí)時(shí)跟蹤測(cè)量精度。
關(guān)鍵詞: 光反饋; 自混合干涉; 去噪; 相位突變點(diǎn); 整數(shù)條紋; 位移測(cè)量
中圖分類(lèi)號(hào): TN247?34 文獻(xiàn)標(biāo)識(shí)碼: A 文章編號(hào): 1004?373X(2018)16?0108?04
Abstract: The noise interference in original optical feedback self?mixing interference signals is not considered when the current phase measurement algorithm is used for real?time tracking measurement of optical feedback self?mixing interference displacement, resulting in poor measurement accuracy. Therefore, improvement of the real?time tracking measurement algorithm for optical feedback self?mixing interference displacement is conducted. The adaptive filtering system is adopted to remove the noises in optical feedback self?mixing interference signals. The transform processing of denoised self?mixing signals is conducted to obtain the analytic signals. The mutation points for the wrapped phase of analytic signals are extracted. The correct direction of phase mutation points is located according to the product of the phase mutation point and the positive or negative unit pulse, so as to obtain self?mixing interference stripes. The decimal stripes in self?mixing interference stripes are removed to obtain all the integer stripe points. The stripe points are assigned, interpolated and smoothed to obtain the displacement track of external target reconfiguration, that is, optical feedback self?mixing interference displacement. The experimental results show that the proposed algorithm has high accuracy in real?time tracking measurement of optical feedback self?mixing interference displacement.
Keywords: optical feedback; self?mixing interference; denoising; phase mutation point; integer stripe; displacement measurement
隨著激光技術(shù)廣泛使用,光反饋?zhàn)曰旌细缮婕夹g(shù)脫穎而出,以高分辨率、非接觸測(cè)量、精確度高等優(yōu)點(diǎn)應(yīng)用于工業(yè)中不同測(cè)量環(huán)節(jié),在物體震動(dòng)測(cè)量、位移測(cè)量、速度測(cè)量等方面發(fā)揮不可替代的作用[1]。實(shí)現(xiàn)光反饋?zhàn)曰旌细缮嫖灰茖?shí)時(shí)跟蹤測(cè)量的算法種類(lèi)繁多,近年來(lái)一般采用相位測(cè)量法、條紋計(jì)數(shù)法、相位解卷法等算法。
傳統(tǒng)相位測(cè)量算法進(jìn)行光反饋?zhàn)曰旌细缮嫖灰茖?shí)時(shí)跟蹤測(cè)量時(shí),未考慮原始光反饋?zhàn)曰旌细缮嫘盘?hào)中的噪聲干擾,導(dǎo)致測(cè)量精度不理想,本文對(duì)此加以改進(jìn),引入自適應(yīng)濾波系統(tǒng)對(duì)原始光反饋?zhàn)曰旌细缮嫘盘?hào)實(shí)施去噪處理,一方面能夠降低后期測(cè)量的難度,另一方面提高測(cè)量的精確度[2]。實(shí)驗(yàn)結(jié)果表明,所提算法的測(cè)量精準(zhǔn)度高、誤差小,為工業(yè)測(cè)量提供新的測(cè)量手段,具有較高的應(yīng)用價(jià)值。
光反饋?zhàn)曰旌细缮嫖灰茖?shí)時(shí)跟蹤測(cè)量算法的核心思想為:采集全部整數(shù)干涉條紋點(diǎn),獲取相應(yīng)的目標(biāo)運(yùn)動(dòng)方向[3]。自混合信號(hào)的整數(shù)條紋與小數(shù)條紋均能描述外部目標(biāo)激光器的波長(zhǎng),整數(shù)干涉條紋等于半個(gè)激光器波長(zhǎng),小數(shù)條紋等于[14]個(gè)激光器波長(zhǎng)。在此基礎(chǔ)上賦值全部整數(shù)條紋點(diǎn),對(duì)位移信號(hào)實(shí)施3次樣條插值重構(gòu)操作,至此完成[14]個(gè)激光器波長(zhǎng)分辨率位移測(cè)量。光反饋?zhàn)曰旌细缮妫∣FSMI)信號(hào)中往往存在噪聲,干擾測(cè)量參數(shù)的獲取,導(dǎo)致最終位移測(cè)量精度下降,為提高光反饋?zhàn)曰旌细缮嫖灰茖?shí)時(shí)跟蹤測(cè)量的精確度,本文改進(jìn)光反饋?zhàn)曰旌细缮嫖灰茖?shí)時(shí)跟蹤測(cè)量算法,在進(jìn)行測(cè)量之前對(duì)光反饋?zhàn)曰旌细缮嫘盘?hào)實(shí)施濾波去噪處理[4]。改進(jìn)的光反饋?zhàn)曰旌细缮嫖灰茖?shí)施跟蹤測(cè)量算法流程見(jiàn)圖1。
1.1 光反饋?zhàn)曰旌细缮嫘盘?hào)噪聲去除
OFSMI信號(hào)中的噪聲分為多種,本文對(duì)常見(jiàn)的低頻波動(dòng)攜帶的信號(hào)包絡(luò)噪聲進(jìn)行深入探究[5]。文章引入自適應(yīng)濾波系統(tǒng)去除OFSMI信號(hào)中的噪聲,如圖2所示。分析圖2能夠看出,該濾波系統(tǒng)包含上通道與下通道,非理想信號(hào)從上通道輸入,參考信號(hào)從下通道輸入,其中非理想信號(hào)用[g′t]描述,參考信號(hào)用[nt]描述;[nt]是噪聲且位于[g′t]中,從LD驅(qū)動(dòng)中可獲取該噪聲。子適應(yīng)函數(shù)的轉(zhuǎn)移函數(shù)用[Hz]描述,濾波器的輸出用[Yt]描述,誤差信號(hào)用[gt]描述,能夠去除低頻包絡(luò)中的自混合信號(hào)。最后通過(guò)最小均方誤差方法更新濾波器的抽頭權(quán)重,獲取去除噪聲的信號(hào)[Pon]。
1.2 相位突變點(diǎn)提取與正確方向定位
1.2.1 相位突變點(diǎn)提取
基于噪聲去除后的自混合信號(hào)實(shí)施變換處理獲取解析信號(hào),采用atan2根據(jù)解析信號(hào)虛實(shí)兩部分計(jì)算相應(yīng)的包裹相位[6],由于檢測(cè)包裹相位[-π,π]的相位突變點(diǎn)就能得到包裹相位的條紋,所以包裹相位的條紋點(diǎn)可以在提取包裹相位突變點(diǎn)基礎(chǔ)上得到,也就是自混合干涉條紋[7]。相位突變點(diǎn)獲取步驟:給完成微分操作后的包裹相位定義正確閾值,進(jìn)行全部負(fù)主峰值點(diǎn)提取同時(shí)取符號(hào)函數(shù)。
1.2.2 相位突變點(diǎn)正確方向定位
基于上述相位突變點(diǎn)提取結(jié)果,為相位突變點(diǎn)找到正確方向定位十分關(guān)鍵。由于信號(hào)噪聲消除過(guò)程中,自混合信號(hào)會(huì)伴有相應(yīng)的運(yùn)動(dòng)方向信息,取自混合信號(hào)的符號(hào)函數(shù),再取反,獲取相應(yīng)的正負(fù)單位脈沖[8]。相位突變點(diǎn)的正確方向是根據(jù)相位突變點(diǎn)與正負(fù)單位脈沖的乘積進(jìn)行定位,獲取方向正確的條紋點(diǎn)[9],如圖3所示。坐標(biāo)系中,條紋遠(yuǎn)離激光器運(yùn)動(dòng)用縱軸1描述,條紋靠近激光器運(yùn)動(dòng)用縱軸-1描述。
1.3 條紋賦值與插值重構(gòu)
分析圖3,小數(shù)條紋點(diǎn)用添加圓圈來(lái)描述。其中小數(shù)條紋點(diǎn)雖占少數(shù),但將小數(shù)條紋點(diǎn)看成整數(shù)條紋點(diǎn)實(shí)施波長(zhǎng)賦值則會(huì)降低位移測(cè)量的精確度,所以對(duì)小數(shù)條紋點(diǎn)進(jìn)行清除獲取的全部整數(shù)條紋點(diǎn)如圖4所示。根據(jù)并列條紋的兩種情況進(jìn)行相應(yīng)賦值:第一,并列條紋點(diǎn)存在相同值,則條紋點(diǎn)間的目標(biāo)運(yùn)動(dòng)方向未改變,進(jìn)行條紋賦值時(shí)整條紋位移矢量波長(zhǎng)的加減是由條紋點(diǎn)的符號(hào)值控制的[10];第二,并列條紋點(diǎn)存在不同值,此時(shí)條紋點(diǎn)間的目標(biāo)運(yùn)動(dòng)方向產(chǎn)生變化,因?yàn)樾?shù)條紋存在并列條紋點(diǎn)之間,在條紋點(diǎn)的中間部分對(duì)小數(shù)條紋補(bǔ)償[14]激光器波長(zhǎng)。對(duì)賦值完畢的條紋點(diǎn)實(shí)施插值與平滑處理,獲取外部目標(biāo)重構(gòu),重構(gòu)結(jié)果則是光反饋?zhàn)曰旌细缮娴奈灰平Y(jié)果。
2.1 實(shí)驗(yàn)設(shè)置
為驗(yàn)證本文提出的改進(jìn)光反饋?zhàn)曰旌细缮嫖灰茖?shí)時(shí)跟蹤測(cè)量算法的有效性,采用本文算法構(gòu)建測(cè)量系統(tǒng),進(jìn)行實(shí)驗(yàn)分析。實(shí)驗(yàn)所需光反饋狀態(tài)可通過(guò)調(diào)試衰減器來(lái)掌握,PZT的運(yùn)動(dòng)采用正弦信號(hào)進(jìn)行驅(qū)動(dòng),0~150 V是其電壓可調(diào)范圍,10~100 Hz為驅(qū)動(dòng)頻率。設(shè)定激勵(lì)信號(hào)的峰?峰值分別是14.78 V,28.07 V,41.02 V,30 Hz為此時(shí)的驅(qū)動(dòng)頻率。三種情況下獲取的自混合干涉實(shí)驗(yàn)信號(hào)如圖5所示。
2.2 實(shí)驗(yàn)結(jié)果分析
三種不同驅(qū)動(dòng)電壓值下外部物體位移測(cè)量結(jié)果如表1所示,其中:測(cè)量誤差用[γΔLjΔLj]描述;驅(qū)動(dòng)信號(hào)波形圖如圖6所示;重構(gòu)外部物體運(yùn)動(dòng)軌跡如圖7所示。
分析圖6、圖7,本文算法獲取的重構(gòu)外部物體運(yùn)動(dòng)軌跡走勢(shì)大致相同,說(shuō)明本文算法能夠獲取較好的外部物體重構(gòu)結(jié)果,進(jìn)而獲取較高的位移測(cè)量精度。
分析表1能夠看出,3種數(shù)值電壓設(shè)置下,本文算法與PE4位移測(cè)量結(jié)果相比,誤差維持在0.35%左右,誤差較小,基本接近實(shí)際位移測(cè)量結(jié)果,說(shuō)明本文算法的精確度較高。由于本文算法沒(méi)有光條件的限制,所以在適度光反饋與弱光反饋下均能進(jìn)行位移測(cè)量,本文算法的適用性較好。
本文對(duì)光反饋?zhàn)曰旌细缮嫖灰茖?shí)時(shí)跟蹤測(cè)量算法進(jìn)行改進(jìn),對(duì)原始OFSMI信號(hào)進(jìn)行去噪處理,降低位移測(cè)量難度的同時(shí)提高位移測(cè)量的精確度。實(shí)驗(yàn)結(jié)果表明,所提算法能夠獲取精準(zhǔn)的外部物體重構(gòu)結(jié)果,測(cè)量精度高、穩(wěn)定性強(qiáng)。
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