Research on Mechanical Properties of Domestic T700S Carbon Fibers

Abstract

Two types of domestic T700S carbon fibers (CF1 and CF2) were investigated in three batches to find out their mechanical properties, including tensile properties of multifilament, tensile and bending properties of composites. The results showed that the mechanical properties of domestic T700S CF are comparable to those of Toray T700S CF with a small discrete coefficient obtained from experiments for the three batches of CF, and that the unidirectional CF2 composite laminates has the biggest tensile strength discrete coefficient, 3.84%. The difference of properties between the two types of fiber composites was analyzed using the optical contact angle measuring device. It was found that CF2 and resin have better wettability. The two types of carbon fibers were examined by the Ø150 mm standard pressure vessel. Temperature (high temperature, low temperature, and temperature impact) tests and aging tests revealed that: high temperature, low temperature, and temperature impact have little effect on the characteristic index of the pressure vessel; after 800h aging, the characteristic index of the pressure vessel decreased by 15.2%.

Automatic flaw detection of carbon fiber prepreg using a CFP-SSD model during preparation

“…Composite materials have found extensive use in a number of industries, including aerospace, automotive application, industrial manufacturing, new energy, and others [1]. Carbon fiber composite materials predominate in these industries due to their high strength-to-weight ratio, low weight, high stiffness, and resistance to corrosion [2,3]. Carbon fiber prepreg is a midstream and downstream product in the carbon fiber industry.…”

“…(1) A carbon fiber prepreg surface flaw detection platform is built using machine vision, and the data set of surface flaw images for carbon fiber prepreg is collected, and the data augmentation approach is employed to boost our selfmade data set's capacity for generalization. (2) The backbone of the CFP-SSD model uses a modified-Resnet50. In the modified-Resnet50, the channelintroducing attention mechanism SE is introduced to carry out channel weight re-calibration, which improves the network feature extraction effect.…”