Research on temperature controller of non-closed FDM 3D printer nozzle

ZHANG Jinli; SHI Yiping; LIU Jin; Lü Chenyue; CHENG Zongzheng

doi:10.13873/J.1000-9787(2021)01-0053-03

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Research on temperature controller of non-closed FDM 3D printer nozzle

更新时间：2025-09-11

- Research on temperature controller of non-closed FDM 3D printer nozzle
- Vol. 40, Issue 1, Pages: 53-55+59(2021)
- 作者机构：
  
  上海工程技术大学电子电气工程学院
- 作者简介：
- 基金信息：
- DOI：10.13873/J.1000-9787(2021)01-0053-03
  CLC： TP391.73
- Published：2021
- 稿件说明：
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[1]张金立,施一萍,刘瑾,吕晨悦,程宗政.非封闭式FDM 3D打印机喷头温度控制器研究[J].传感器与微系统,2021,40(01):53-55+59.

ZHANG Jinli, SHI Yiping, LIU Jin, et al. Research on temperature controller of non-closed FDM 3D printer nozzle[J]. 2021, 40(1): 53-55+59.
[1]张金立,施一萍,刘瑾,吕晨悦,程宗政.非封闭式FDM 3D打印机喷头温度控制器研究[J].传感器与微系统,2021,40(01):53-55+59. DOI： 10.13873/J.1000-9787(2021)01-0053-03.

ZHANG Jinli, SHI Yiping, LIU Jin, et al. Research on temperature controller of non-closed FDM 3D printer nozzle[J]. 2021, 40(1): 53-55+59. DOI： 10.13873/J.1000-9787(2021)01-0053-03.

摘要

针对非封闭式熔融沉积成型（FDM）技术3D打印机喷头温度受环境温度、打印机内部加热元件、打印喷头系统的散热性能和空气流速等因素的影响

喷头温度的控制变得复杂且呈非线性

传统比例—积分—微分（PID）控制无法满足打印需求的问题

提出改进鲸鱼优化的反向传播（BP）-PID控制器对PID参数自适应控制

从而对喷头温度精确控制。实验表明:改进的鲸鱼优化算法比遗传算法与粒子群算法寻优能力更强

且经改进鲸鱼算法优化的BP-PID喷头温度控制器稳定速度更快

自适应能力更强。

Abstract

Aiming at the problem that enclosed fused deposition modeling（FDM） 3D printer nozzle temperature affected by environmental temperature

internal heating element of printer

cooling performance of the printing

spray system and the air flow velocity

nozzle temperature control change complicated and non-linear

the traditional proportional-integral-differential（PID） control can’t meet the demand for printing

an improved whales is put forward to optimize back propagation（BP）-PID controller of PID parameter adaptive control

thus can accurately control the nozzle temperature.The experimental results show that optimizing ability of the improved whale optimization algorithm is stronger than the genetic algorithm and particle swarm optimization algorithm

and nozzle temperature controller based on BP-PID optimized by the improved whale algorithm has a faster stable speed and stronger adaptive ability.

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references

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基于自适应权重和柯西变异的鲸鱼优化算法 [J]. 郭振洲,王平,马云峰,王琦,拱长青. 微电子学与计算机 . 2017(09)

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