Measurement and Prediction of Stress-strain for Extruded Oilseed Using Neural Networks Under Uniaxial Cold Pressing

  • Xiao Zheng
  • Guoxiang Lin
  • Dongping He
  • Jingzhou Wang
Conference paper
Part of the The International Federation for Information Processing book series (IFIPAICT, volume 258)

A visualization of testing apparatus was developed to measure property of oilseeds relevant to physical mechanics during mechanical pressing for oil extraction. Stress-strain relationships were measured for extruded peanut, soybean, sesame and linseed compressed at thirteen pressures under uniaxial cold pressing. The prediction model of the stress-strain relationship was developed based on BP neural network. Results indicated that the stress-strain relationships were nonlinear. Over 50% strains for extruded soybean, sesame and linseed occurred at stress below 20MPa. Over 60% strain for extruded peanut occurred at stress below 10MPa. No more than 13% strain occurred at stress over 20MPa for extruded soybean sesame and linseed, and no more than 13% strain occurred at stress over 10MPa for extruded peanut. The maximum error between prediction and measurement for the stress-strain relationship was less than 0.0084 and the maximum training times was less than 88.

Keywords

measurement prediction stress-strain neural networks oilseed cold pressing 

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Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Xiao Zheng
    • 1
  • Guoxiang Lin
    • 1
  • Dongping He
    • 2
  • Jingzhou Wang
    • 1
  1. 1.Department of Mechanical EngineeringWuhan Polytechnic UniversityChina
  2. 2.Department of Food Science and EngineeringWuhan Polytechnic UniversityChina

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