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The Time Grating Rotating Platform Prediction Model Study

Posted on:2015-03-10Degree:MasterType:Thesis
Country:ChinaCandidate:X HuangFull Text:PDF
GTID:2298330431477084Subject:Measuring and Testing Technology and Instruments
Abstract/Summary:PDF Full Text Request
Nowadays,the technology of sensor has become the domain of competition of nation andreflects the nation’s strength.dislpace sensor even more important,for the advanced toolsrequest the check sensor’s precision. To large extent,The Accuracy class of sensor decidethe tools what is goog or bad. The time grid sensor is original and exlusive by ourcountry.it is precisional. It reduced the processing difficulty and the cost and enhances theability of greasy dust and intelligent because it completely avoids the precision machineryscribed line. time gating is a static absolute type measuring sensor according to the timedivide the sample.the machine which is digital and full close loop in the market request thesignal of feedback is absolutly incremental type according to the displace divided sample.it can’t conduct whole closed-loop position feedback directly according to the time equally.In order to solve the key technical issues, the main research contents for the project were asfollows:1) Analys the grating ruler which are absolutly incremental type according to the displacedivided sample. Analys the time gating which are a static absolute type measuringsensor according to the time divide the sample.put forward the idear of forecastingmeasure which can solve the problem of delayed feedback error.show the forecastingmeasure how to solve the problem.2) Study the forecastig domain by the method of time series and wavelet analysis.on baseof wavelet decompositing and recompositing the value of angle displace, Study theseries which are deprived from the wavelet decompositing and recompositing the valueof angle displace how to built model to foecast the angle displace and by whichway,eg wavelet decompositing and recompositing,curve fitting,time series modelscoefficient solve and so on.3) Set up the experiment decive and get the data by experiment.by the waveletdecompositing and recompositing the data deprived by experiment built model toforecast.at last using second order difference the data built model to forecast.precision2″.4) Design the experiment prove the method of forecasting measure is feasible.byexperiment show outcome the method of forecasting measure is feasible.to prove by experiment the.precision2″.
Keywords/Search Tags:time grating, CNC rotary table, time series, predictive measurement, auto-regressionmodel, wavelet analyse
PDF Full Text Request
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