Stratum Subsidence Optical Fiber Discrete Data Modeling Reserch

Data interpolation is to point to a group of messy (also called non-uniform) distributionof data sampling points in the whole region on constructing a of the basic functions of theprocess. In a large number of engineering in engineering practice, such issues as an importantlink solve engineering problems, according to the engineering structure and the actualengineering construction environment, we will according to different monitoring equipmentmonitoring to a lot of the initial data, such as the construction parameters, but these largeamounts of data is between discrete, through these discrete data, can get monitoring theattributes of the position, and other position is according to these discrete data to estimate itsattribute value, and these estimates attribute value and can’t meet our construction precision ofrequirements. The problem for many science and engineering field has important practicalvalue because the practice that can measure or to generate data is often sparse and irregular ofdistribution. In order to solve this problem, need to known parameters analysis of the dataprocessing. Make the necessary interpolation, fitting, in order to achieve the construction needdata accuracy..This article describes several of the main interpolation methods and the fitting method,and then discuss in detail the method of spline interpolation and spline fitting, and the looselayer of the East China the prevalence of deep Quaternary strata mine coal seam deeplong-term water loss compression lead to surface subsidence caused a large number of coalmine shaft lining to rupture as the background, monitoring technology and testing in a fiberBragg grating loose layer of finite layer of stress variation with depth data object of study,research is focused through interpolation fitting finite layer of monitoring data to analyze,organize, come to any layer numerical model of stress, from a mathematical point of view amore comprehensive forecast of the loose layer of stress changes. In response to these discrete mathematical problems through the analysis of the currentinterpolation method with the fitting method (Lagrange interpolation, Newton interpolation,linear interpolation, spline interpolation, inverse distance weighted interpolation method, theinterpolation curve; spline intended together, linear regression, nonlinear curve fitting, thefitting curve) to interpolate the discrete data of the monitoring of fiber grating analysisFinally, use a variety of interpolation methods for data processing, and compare thevarious methods of error precision elect the optimal interpolation of data have been observed.MATLAB numerical computing software to write the above interpolation methods, graphics,data tables obtained interpolation results and fitting curve.