Journal of the Korean Society for Precision Engineering (한국정밀공학회지)

Korean Society for Precision Engineering (한국정밀공학회)
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A Development of Feature Extraction and Condition Diagnosis Algorithm for Lens Injection Molding Process

렌즈 사출성형 공정 상태 특징 추출 및 진단 알고리즘의 개발

  • Baek, Dae Seong (Department of Mechanical Engineering, Graduate School, Sungkyunkwan University) ;
  • Nam, Jung Soo (Department of Mechanical Engineering, Graduate School, Sungkyunkwan University) ;
  • Lee, Sang Won (School of Mechanical Engineering, Sungkyunkwan University)
  • 백대성 (성균관대학교 대학원 기계공학과) ;
  • 남정수 (성균관대학교 대학원 기계공학과) ;
  • 이상원 (성균관대학교 기계공학부)
  • Received : 2014.01.20
  • Accepted : 2014.10.22
  • Published : 2014.11.01
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Abstract

In this paper, a new condition diagnosis algorithm for the lens injection molding process using various features extracted from cavity pressure, nozzle pressure and screw position signals is developed with the aid of probability neural network (PNN) method. A new feature extraction method is developed for identifying five (5), seven (7) and two (2) critical features from cavity pressure, nozzle pressure and screw position signals, respectively. The node energies extracted from cavity and nozzle pressure signals are also considered based on wavelet packet decomposition (WPD). The PNN method is introduced to build the condition diagnosis model by considering the extracted features and node energies. A series of the lens injection molding experiments are conducted to validate the model, and it is demonstrated that the proposed condition diagnosis model is useful with high diagnosis accuracy.

Keywords

References

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Cited by

  1. Development of Injection Mold for Subminiature Lenses Using Shell Runners Containing Multiple Holes vol.32, pp.11, 2015, https://doi.org/10.7736/KSPE.2015.32.11.961
  2. Development of Real-Time Condition Diagnosis System Using LabVIEW for Lens Injection Molding Process vol.33, pp.1, 2016, https://doi.org/10.7736/KSPE.2016.33.1.23