本文選題：寄生式時柵 + 不確定度評定改進方案��； 參考：《安徽理工大學》2017年碩士論文

【摘要】：目前已有的寄生式時柵傳感器不確定度評定方案沒有建立傳感器加工誤差、安裝誤差以及多普勒效應與總不確定度之間的傳遞關(guān)系,寄生式時柵也沒有建立高精度的動態(tài)測量誤差修正模型,其結(jié)構(gòu)只是依據(jù)實驗經(jīng)驗設計,缺少指導結(jié)構(gòu)優(yōu)化設計的理論依據(jù)。為了建立更全面的寄生式時柵不確定度評定體系,本文對原有的寄生式時柵不確定度評定方案進行改進,建立傳感器加工誤差、安裝誤差以及多普勒效應與總不確定度之間的傳遞關(guān)系。為了建立高精度的寄生式時柵動態(tài)測量誤差模型,本文以84對極寄生式時柵為研究對象,設計實驗采集寄生式時柵整圓周動態(tài)誤差,分析動態(tài)誤差各個成分與誤差來源的對應關(guān)系,選用插入標準值的貝葉斯預測算法建立寄生式時柵整圓周動態(tài)誤差模型,另選用三次樣條插值和BP神經(jīng)網(wǎng)絡建模方法對寄生式時柵整圓周動態(tài)誤差建模,并與之對比。驗證結(jié)果表明,貝葉斯插入標準值建模方法可在較短的時間以較少的數(shù)據(jù)量獲得較高的建模精度。利用Ansoft Maxwell仿真分析傳感器安裝誤差和多普勒效應對寄生式時柵測量精度的影響,并設計實驗進行驗證。從仿真和實驗結(jié)果可知,測頭與轉(zhuǎn)子的間隙越小,傳感器測量精度越高,實驗確定的最佳安裝間隙為0.2mm;測頭的俯仰角和偏擺角變化對測量精度的影響規(guī)律復雜,故文中建立相應的誤差補償模型;隨著轉(zhuǎn)子轉(zhuǎn)速增大,多普勒效應對傳感器測量精度的影響越大。為了實時修正寄生式時柵安裝誤差引起的傳感器測量誤差,將渦流傳感器結(jié)構(gòu)耦合進寄生式時柵傳感器結(jié)構(gòu)中,利用三點法誤差分離技術(shù)實時測量被測對象轉(zhuǎn)角,實時補償寄生式時柵因安裝誤差導致的測角誤差,從而設計一種自補償式寄生式時柵傳感器,對其機械結(jié)構(gòu)和處理電路進行設計,利用Ansoft Maxwell對傳感器感應信號進行仿真分析。本文對已有的寄生式時柵不確定度評定方案進行了改進,建立了高精度的寄生式時柵整圓周動態(tài)誤差模型,分析了安裝誤差與多普勒效應對傳感器測量精度的影響。為了消除安裝誤差的影響,設計了一種自補償寄生式時柵傳感器。
[Abstract]:The existing methods for evaluating the uncertainty of parasitic time grating sensors have not established the processing error, installation error and the transfer relationship between Doppler effect and total uncertainty.The parasitic time-grid has not established a high-precision dynamic measurement error correction model, and its structure is only designed according to the experimental experience, and lacks the theoretical basis to guide the optimization design of the structure.In order to establish a more comprehensive evaluation system of parasitic time-grid uncertainty, the original evaluation scheme of parasitic time-grid uncertainty is improved in this paper, and the sensor machining error is established.The transfer relationship between the installation error and the Doppler effect and the total uncertainty.In order to establish a high precision dynamic measurement error model of parasitic time grating, 84 pairs of parasitic time gratings are taken as the research object in this paper, and the experimental data are designed to collect the whole circle dynamic errors of parasitic time gratings.Based on the analysis of the relationship between the components of dynamic error and the source of error, the Bayesian prediction algorithm with standard values is used to establish the dynamic error model of parasitic time grid.In addition, cubic spline interpolation and BP neural network are used to model the dynamic error of parasitic time grating.The results show that the Bayesian insertion standard value modeling method can achieve higher modeling accuracy with less data in a short time.The influence of sensor installation error and Doppler effect on the measurement accuracy of parasitic time grating is analyzed by Ansoft Maxwell simulation, and the experiment is designed to verify it.The results of simulation and experiment show that the smaller the gap between the probe and the rotor, the higher the measuring accuracy of the sensor, and the optimum installation clearance determined by the experiment is 0.2mm. the influence of the pitch angle and the yaw angle of the probe on the measurement accuracy is complex.Therefore, the corresponding error compensation model is established in this paper, and with the increase of rotor speed, the effect of Doppler effect on the measurement accuracy of the sensor is greater.In order to correct the sensor measurement error caused by parasitic time grid installation error in real time, the eddy current sensor structure is coupled into the parasitic time grating sensor structure, and the rotation angle of the measured object is measured in real time by using the three-point error separation technique.In order to compensate the angle measurement error caused by the installation error of parasitic time grating in real time, a self-compensating parasitic time grating sensor is designed, its mechanical structure and processing circuit are designed, and the sensing signal of the sensor is simulated and analyzed by Ansoft Maxwell.In this paper, the existing schemes for evaluating the uncertainty of parasitic time-grid are improved, and a high-precision dynamic error model of parasitic time-grating is established. The effects of installation error and Doppler effect on the measurement accuracy of the sensor are analyzed.In order to eliminate the influence of installation error, a self-compensating parasitic time grating sensor is designed.
【學位授予單位】：安徽理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP212

【相似文獻】

相關(guān)期刊論文 前10條

1 洪邁生;;關(guān)于相關(guān)、動態(tài)誤差與不失真條件[J];振動.測試與診斷;1988年01期

2 桑恩方;采樣和量化動態(tài)誤差分析[J];哈爾濱船舶工程學院學報;1982年01期

3 李莉,張鳳菊,劉利民;減小熱電偶動態(tài)誤差的方法[J];一重技術(shù);2003年03期

4 許珀文;;掃頻法調(diào)測幅頻特性動態(tài)誤差的減小[J];電視技術(shù);1988年03期

5 孔力,程晶晶,鐘志平,劉文中;γ射線透射組分測量的動態(tài)誤差分析[J];選煤技術(shù);2001年02期

6 肖正林;牟建華;;慣導平臺調(diào)平動態(tài)誤差消除方法研究[J];宇航學報;2008年02期

7 林紅斌;解靜;王妍;;基于正弦直線過載的慣組動態(tài)誤差標定方法[J];系統(tǒng)工程與電子技術(shù);2013年10期

8 郝魁紅,王化祥,潘勇;射線法兩相流測量的動態(tài)誤差研究[J];核電子學與探測技術(shù);2004年06期

9 趙磊;楊杰;;基于Solidworks Simulation的三坐標測量儀動態(tài)誤差分析[J];機床與液壓;2012年01期

10 羅成芳，，柏建國;動態(tài)誤差的自動補償[J];四川輕化工學院學報;1994年04期

相關(guān)會議論文 前4條

1 蔣敏蘭;費業(yè)泰;;動態(tài)誤差分解與溯源理論與方法研究[A];第三屆全國信息獲取與處理學術(shù)會議論文集[C];2005年

2 王慶剛;裴東興;祖靜;劉鵬;;測壓器應用環(huán)境校準的研究[A];2004全國測控、計量與儀器儀表學術(shù)年會論文集（上冊）[C];2004年

3 杜亮;;示波器測量上升時間的動態(tài)誤差評估[A];2007年度中國航空學會計量技術(shù)專業(yè)委員會計量與質(zhì)量專題學術(shù)交流會論文集[C];2007年

4 查月;魏學通;李瑩;;基于Simulink的捷聯(lián)慣導系統(tǒng)動態(tài)誤差特性仿真研究[A];2008年船舶通信導航學術(shù)年會論文集[C];2008年

相關(guān)碩士學位論文 前8條

1 鄧夢;基于RTCP的五軸聯(lián)動數(shù)控機床動態(tài)誤差溯源方法研究[D];電子科技大學;2014年

2 周園;工業(yè)機器人柔性動態(tài)誤差分析及補償策略研究[D];燕山大學;2016年

3 章劉沙;寄生式時柵角位移傳感器動態(tài)誤差分析與結(jié)構(gòu)改進[D];安徽理工大學;2017年

4 成曉南;差動變壓器式位移傳感器動態(tài)誤差分析及補償技術(shù)研究[D];武漢科技大學;2015年

5 王欣;三坐標測量機動態(tài)誤差分析[D];西安理工大學;2007年

6 周騰飛;Bernstein基多項式函數(shù)的高精度計算及其動態(tài)誤差分析研究[D];國防科學技術(shù)大學;2011年

7 胡茂留;多功能動態(tài)精度研究實驗系統(tǒng)的結(jié)構(gòu)設計與誤差分析[D];合肥工業(yè)大學;2010年

8 楊偉光;捷聯(lián)慣性導航系統(tǒng)動態(tài)誤差標定與補償算法研究[D];國防科學技術(shù)大學;2009年

本文編號：1770921