Process optimization of poplar veneer modification treatment based on artificial neural network

作者：Sun Jian Ping; Wang Feng Hu^*; Hu Ying Cheng

来源：Transactions of Materials and Heat Treatment, 2011, 32(2): 162-166.

• Abrasive resistance
• Artificial Neural Network
• Azobisisobutyronitrile
• Heating treatments
• Modification treatment
• Neural network techniques
• Optimized parameter
• Poplar veneer
• Process optimization
• Process parameters
• Processing technique optimization
• Processing technologies
• Resin liquids
• Surface hardness
• Zinc chloride

Neural network technique was employed to study the technology of producing strengthened poplar-veneer composite material. Three mixed resin liquids were selected and impregnated into poplar veneers. With the heating treatment the resins were polymerized and poplar veneers were strengthened. Five parameters including polymeric temperature, polymeric time, the quantity of cobalt naphthenate, zinc chloride and azobisisobutyronitrile were involved in studying the influence of processing technology on conversion loading of the resins. The quantitative relationship between modification process and conversion loading is established based on neural network, and the process parameters were optimized. The optimized values of polymeric temperature, polymeric time, the quantity of cobalt naphthenate, zinc chloride and azobisisobutyronitrile are 80°C, 7 h, 2%, 6% and 5%, respectively. The surface hardness, abrasive resistance and static bending strength of the poplar-veneer composite material made of three resins after modification treatment using optimized parameters are increased by 1.34 times, 2.35 times and 1.87 times, respectively, compared with that of the un-modified material.

• 出版日期2011
• 单位东北林业大学