The Design Of γ Spectrum Analysis Software Based On Qt, QWT

In recent years, radioactive pollution as a social problem has been more and more attention, especially in the past few years after the nuclear leakage accident occurred in Japan’s Fukushima nuclear power plant. Along with the rapid development of electronic technology, the nuclear signal data acquisition capability and analysis methods have also been improved. In this paper, based on the measurement principle of nuclear signal acquisition, by analyzing how to development the spectrum data acquisition and analysis software based on ARM Cortex-A7 A20 (AllWinner) open source board computer using QT4 platforms, this paper introduces the QT embedded development, the use of QWT plug-in library, nuclear spectrum data acquisition theory and the analysis method etc., this paper has done the following work to carry out the relevant design work.By analyzing the actual need to build overall system architecture, design trade-offs of cost, scalability, ease of development and other factors. Using recent special popular Linux OS (Raspbian) as a system, using open source cross-platform Qt4 graphical user interface as the embedded development tools and platforms, including the use of QWT library.In work carried out above, according to the functional requirements of spectrum analysis, completed the spectrum software based on Qt and QWT. The entire software function module is divided into five units:file operations, data acquisition, spectrum analysis, instrument calibration, help documentation. The entire energy spectrum analysis software has three characteristics:cross-platform, extensible, easy operation.In the data acquisition unit, designed USB to serial communication mode to capture spectroscopy data. When processing smooth spectrum data, least squares fitting (optional smoothing window width) and FIR Gaussian window smoothing methods were used; Symmetrical zero area peak seeking method and first-order derivat (second-order derivative) peak search method were used to find peaks; Simplex Gaussian fitting method combined with fixed peak area boundary constraints improve the accuracy of the peak area. Through the function test of the software on the ARM platform, it achieves the expected goal. At last, the paper summarizes some problems in the research and the further improvement of the optimization.