Research Of The Propellant Grain X-ray Real-time Imaging And Processing System

The propellant grain, as military supplies, the quality and appearance must be strict inconformity with the requirements of the National Military Standards. The grain manufacturingprocess was complexity, due to a variety of factors, it can not completely avoid that theinclusion, shrinkage, pores, cracks and other defects existed in grain. When these defectsbeyond a certain range, would damage the mechanical properties, burning and safetyperformance of the ammunition, lead to dangerous occurrence such as late-bore deep-fried orearly burst. As a convenient, reliable non-destructive testing method, X-ray digital imagingdetection technology was widely used to detect the grain defects in the weapons business.In this paper, according to the accuracy, speed requirements of grain detection inenterprise, our study was focus on the real-time imaging system based on an image intensifier.First, introduced the work principle of the whole system and imaging core components, thenanalysed the factors affecting the image quality analysis and correction method. The mainwork in this aiticle was developing a software system at VC++6.0 platform, including imageand video acquisition and processing, based on the frame grabber. The image processingsection includes three modules: image preprocessing, image segmentation and image analysis.In image pre- processing module, using the traditional method to suppress noise--themulti-frame overlay and KNN median filter, made a good job in smoothing grain-ray imagenoise. Gray-level transformation, histogram equalization and homomorphic filtering wasadopted to enhance grain image, effectively improved image low contrast. Then proposed amethod combined the high frequency emphasis filtering and histogram equalization, enhanceddefect edges more clearly. In image segmentation module, edge detection and thresholdsegment was used. The traditional edge detection operators and wavelet modulus maximaedge detection was applied, results show that the latter can detect clear, accurate defects’edge.To exclude grain background interference, a region-based adaptive threshold segmentationmethod was presented, it can accurately split the defect area. In the image analysis module,the perimeter, area and other geometric features of defects can be automatically measured and displayed. In addition, a row or column gray dynamic scanning function was carried out,made the detection testing analysis more facilitate.