Abstract

A fast prediction model of flexural strength based on the online measured temperature of fusion deposition composites (FSBT model) was proposed to overcome the drawbacks of traditional destructive flexural experiments. The experimental results show that the FSBT model can effectively, quickly, and accurately predict the flexural strength of FDM parts, without being limited by composites, FDM conditions, and temperature measurement locations. The average relative error of prediction accuracy is 2.9%, and the maximum relative error is controlled within 8.3% for carbon fiber reinforced polyether ether ketone parts. It was found that the prediction accuracy of flexural strength with varying nozzle temperatures is the highest. The parts with a 100% filling rate have excellent prediction accuracy, while due to the high porosity of FDM parts under other filling rates, it is necessary to add correction a porosity factor to the model to improve the prediction accuracy for flexural strength. The proposed FSBT model can be extended to predict the flexural strength of FDM parts of other fiber reinforced composite materials. Moreover, the accommodation mechanism of strength based on the FSBT model is fully discussed. This work provides a new choice for quickly predicting the strength of FDM fiber composite parts.

中文翻译：

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基于熔敷CF/PEEK复合材料在线测量温度和调节机制的弯曲强度预测模型

摘要

为了克服传统破坏性弯曲实验的缺点，提出了一种基于熔融沉积复合材料在线测量温度的弯曲强度快速预测模型（FSBT模型）。实验结果表明，FSBT模型能够有效、快速、准确地预测FDM零件的弯曲强度，且不受复合材料、FDM条件和测温位置的限制。预测精度平均相对误差为2.9%，碳纤维增强聚醚醚酮零件最大相对误差控制在8.3%以内。结果发现，不同喷嘴温度下的弯曲强度预测精度最高。 100%填充率的零件具有优异的预测精度，而由于其他填充率下的FDM零件孔隙率较高，因此需要在模型中添加修正孔隙率因子，以提高弯曲强度的预测精度。所提出的 FSBT 模型可以扩展到预测其他纤维增强复合材料的 FDM 零件的弯曲强度。此外，还充分讨论了基于FSBT模型的力量调节机制。这项工作为快速预测FDM纤维复合材料零件的强度提供了新的选择。