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Accès ouvert déclaré 2022 article

Optical Penetration and “Fingerprinting” Analysis of Automotive Optical Liquid Silicone Components Based on Wavelet Analysis and Multiple Recognizable Performance Evaluation

5Citations signalées, ce qui n’est pas une note de qualité
1Institutions déclarées
1Pays d’affiliation déclarés

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Le résumé fourni par la source

The residual stress phenomenon in the injection process of an optical lens affects the quality of optical components, and the refractive error caused by geometric errors is the most serious, followed by the degradation of the accuracy and function of optical components. It is very important to ensure that the lens geometry remains intact and the refractive index is low. Therefore, a parameter design method for an optical liquid silicon injection molding was proposed in this study. Wavelet analysis was applied to the noise reduction and feature extraction of the cavity pressure/pressure retaining curve of the injection molding machine, and multiple identifiable performance evaluation methods were used to identify and optimize the parameters of the molding process. Taking an automotive LED lens as an example, Moldex3D simulation software was used to simulate the molding of an LED lens made of LSR material, and two key injection molding factors, melt temperature and V/P switching point, were analyzed and optimized. In this paper, the transmittance and volume shrinkage of LED lenses are taken as quality indexes, and parameters are optimized by setting different V/P switching points and melt temperature schemes. The experimental results show that the residual stress is negatively correlated with transmittance, and the higher the residual stress, the lower the transmittance. Under the optimum process parameters generated by this method, the residual stress of plastic parts is significantly optimized, and the optimization rate is above 15%. In addition, when the V/P switching point is 98 and the melt temperature is 30 °C, the product quality is the best, the volume shrinkage rate is the smallest, and the size is 2.895%, which also means that the carbon emissions are the lowest.

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Le contrôle bibliographique ouvert

DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.

Titre Crossref
Optical Penetration and “Fingerprinting” Analysis of Automotive Optical Liquid Silicone Components Based on Wavelet Analysis and Multiple Recognizable Performance Evaluation
Date Crossref
25/12/2022
Éditeur
MDPI AG
Type
journal-article

Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.

Où se fait cette recherche

  • Shantou University Intelligent Manufacturing Key Laboratory of Ministry of Education pays non établi dans la notice
    Université ou école supérieure
  • College of Engineering Department of Mechanical Engineering pays non établi dans la notice
    Université ou école supérieure

Intelligent Manufacturing Key Laboratory of Ministry of Education — Shantou University et Department of Mechanical Engineering — College of Engineering.

Une affiliation ne permet pas de déduire la nationalité d’un auteur.

Les sujets associés

Injection Molding Process and PropertiesManufacturing Process and OptimizationAdvanced machining processes and optimization

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