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Please wait a minute... For Selected: Download Citations EndNote Ris BibTeX Toggle Thumbnails Select Resistance Element Welding of Carbon Fiber Reinforced Thermoplastic Composites to High-Strength Steel WANG Yecheng, LI Yang, ZHANG Di, YANG Yue, LUO Zhen Journal of Shanghai Jiao Tong University    2022, 56 (10): 1349-1358.   DOI: 10.16183/j.cnki.jsjtu.2021.271 Abstract （680）   HTML （138）    PDF（pc） （47715KB）（565）       Knowledge map    Save The high strength joining of carbon fiber reinforced nylon 6 composites (CF/PA6) to TWIP980 steel was achieved by resistance element welding (REW). A 304 stainless steel rivet was used as an assistant element. The effect of welding current and welding time on the joint mechanical property was studied. Four joint failure modes with different strengths were identified, and the microstructures of joints, and the interfaces between CF/PA6 and the steel were analyzed. As the melting point and thermal conductivity of CF/PA6 are lower than those of the high-strength steel, it is prone to overheat and decompose during welding. While ensuring the formation of a certain size of weld nugget, avoiding or reducing the decomposition of CF/PA6 is the key to the successful implementation of CF/PA6 high-strength steel REW. By using a hard welding process such as high welding current and short welding time, high strength joints can be obtained while reducing the decomposition of CF/PA6. Based on the failure load of the joint, the weld lobe under the conditions of this study was determined. The process is sensitive to the change of welding time, and the allowable welding time range is narrow. The decomposition of CF/PA6 cannot be avoided completely even when the welding parameters in the weld lobe are employed. Therefore, it is necessary to conduct further research on the temperature field and the nugget formation mechanism of the REW process. Table and Figures | Reference | Related Articles | Metrics | Comments（0） Select Prediction of Modulus of Composite Materials by BP Neural Network Optimized by Genetic Algorithm WANG Zhuoxin, ZHAO Haitao, XIE Yuehan, REN Hantao, YUAN Mingqing, ZHANG Boming, CHEN Ji’an Journal of Shanghai Jiao Tong University    2022, 56 (10): 1341-1348.   DOI: 10.16183/j.cnki.jsjtu.2021.126 Abstract （734）   HTML （127）    PDF（pc） （2532KB）（482）       Knowledge map    Save In order to reduce the cost of testing and shorten the design cycle, this paper studies the prediction method of the modulus of resin matrix composites based on the machine learning method. Using a new prediction method — the neural network in combination with the genetic algorithm (GA-ANN), the strength, the Poisson’s ratio, and the failure strain of the T800/epoxy composite material are used as three input variables of the back propagation (BP) neural network. Then, the optimal threshold and weight are obtained in the genetic algorithm (GA), which are assigned to the corresponding network parameters, and the BP neural network is updated for higher accuracy to predict the modulus of resin matrix composites. Under the same conditions, the Adam algorithm is used to predict. A comparison of these two methods fully proves the feasibility of the GA-ANN algorithm. Table and Figures | Reference | Related Articles | Metrics | Comments（0） Select A Detection Method of Wire Feeding Speed Based on Filtering Algorithm of Distortion Signal LE Jian, LIU Yichun, ZHANG Hua, CHEN Xiaoqi Journal of Shanghai Jiao Tong University    2022, 56 (10): 1334-1340.   DOI: 10.16183/j.cnki.jsjtu.2021.270 Abstract （545）   HTML （83）    PDF（pc） （20772KB）（330）       Knowledge map    Save Wire feeding speed has an important effect on the welding quality. In order to realize robot intelligent welding, it is necessary to study the accurate detection method of the wire feeding speed. First, the working principle of the wire feeding speed detection is studied, thus the wire feeding speed online detection can be realized. Then, a kind of wire feeding speed detection system is designed, which wirelessly transmits the sensing signal of the welding wire to the welding robot. Finally, the detection method of the wire feeding speed based on the filtering algorithm of distortion sensing signal is studied, including the principle of no mutation of adjacent wire feeding speed sensing signal, the interference signal elimination algorithm for adjacent detection signal of multiple sensing signal loss without abrupt change, and the detection method of the wire feeding speed. The experimental results show that the main noise in the original wire feeding speed sensing signal can be eliminated by using the designed algorithm and system, and the accuracy of the wire feeding speed detection can be improved. In addition, the width of weld pass after robot welding can not be affected by the change of the welding current. Table and Figures | Reference | Related Articles | Metrics | Comments（0）