The Research Of Gross Error Detection Theory And The Stability Of Safety Monitoring Control Network

Observation accuracy and reliability of observational data are the measuring indicator of general observation. The Observation data will obtain optimal solution of adjustment results when it only contain random error, and make use of the method of least squares adjustment processing. However, the individual observations affected by gross errors, even if the adjustment of high precision, the data are unreliable, that is to say, the presence of gross errors affected the reliability of observational data. Therefore, studying the methods of eliminate gross errors of height measurement is very significant.Safety monitoring of building is an important part of the measurement. The life cycle of safety monitoring control network is very long, and the reliability of safety monitoring data is based on its stability, it will directly affect the engineering construction and safety. Therefore, it is necessary to research the methods of network stability analysis and development stability analysis software.This paper has studied data detection methods of gross error detection theory, the selecting power iteration method and selecting power iteration method of examined estimation principle method. Through made a comparison of all results by some analytical methods, we can only tell good from bad by comparison. What's more, learning the analytical method of the control network stability, research a single point of baseline network and the overall stability of the test rank under the condition of rank defect free net adjustment, and under take the case analysis of one of the limited analysis, t inspection method, average clearance inspection method and blocking clearnace inspection method. Using the C++ language of the VisualStudio2008 to develop an analysis software of removing gross error and the stability of base network, and using the OpenCV to achieve the matrix operations, then basically realized the Intelligent from the two data input to eliminate gross errors and the analysis results of stability.