Wood-Plastic Composites CT Testing Based On Multifractal Theory

Wood-plastic composite is a kind of new environment-friendly material based on the wood materials and waste plastic, it provides a new way to ease the tight of timber resources and to protect the ecological environment. In this paper, we selected the computed tomography (CT) technology to detect the wood-plastic composite materials as the nondestructive testing method, and obtained the fault CT value of wood-plastic composite materials and its defect images.Based on the research of computed tomography principle to wood-plastic composite materials, we scanned several wood-plastic composite materials such as pine-powder composite and poplar-powder composite materials. Then we calculated and set the parameter values of equipment in the processing of wood-plastic composite materials testing, it provided the possibility to realize the rapid detection. According to the relationship between the detected fault CT values of wood plastic composites and the actual measured density values, established a mathematical model between the CT value and density. It provided a new possibility to realize the rapid detection for the density of the wood-plastic composite materials. At the same time, depended on the fault CT values distribution of pine-powder composite materials and poplar-powder composite materials, we get the density distribution image of the two materials. And we found that the two materials had a high-density near edges in the width direction and had a low density in intermediate region, shown as a V-shape, particularly, the changing of density in pine-powder composite materials. It provided some basis for analyzing and improving the material quality.In this paper, the CT image of wood-plastic composite material voids was pretreated by enhancement method. And we detected the hollow edge in the image by using traditional edge detection methods. After preprocessing, the information of defects in the image had been enhanced. By applying the multifractal that have these characteristics:multi-regional, multi-level and multi-local conditions can describe the precise information of sub-physical structure, descripted and characterized the average and whole conditions of the wood-plastic composites voids image, and acquired the defect detection image in different spectrums. Through careful observation and analysis, we can have the conclusion that multifractal theory has the strong points of accuracy, clearness and humanization in defect detection, and it provided a new method to the detection of wood-plastic composite material quality, classification and the confirmation of defect location and size.