| 陶永*,薛蛟**,杨林**,王潇桐**,刘亚醉**,魏洪兴*.基于GRA-DBN的机器人打磨工艺多目标优化方法[J].高技术通讯(中文),2026,36(2):170~178 |
| 基于GRA-DBN的机器人打磨工艺多目标优化方法 |
| A multi-objective optimization method for robot polishing process based on GRA-DBN |
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| DOI：10. 3772 / j. issn. 1002 - 0470. 2026. 02. 006 |
| 中文关键词: 机器人打磨； 民用飞机机身； 多目标优化； 灰色关联分析； 深度置信网络 |
| 英文关键词: robot polishing, civil aircraft fuselage, multi-objective optimization, grey relational analysis, deep belief network |
| 基金项目: |
| 作者 | 单位 | | 陶永* | （*北京航空航天大学机械工程及自动化学院北京 100191）
（**北京航空航天大学航空发动机研究院北京 100191） | | 薛蛟** | | | 杨林** | | | 王潇桐** | | | 刘亚醉** | | | 魏洪兴* | |
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| 中文摘要: |
| 机器人打磨因其灵活性、广泛的工作空间和高可操作性，已成为提升民用飞机机身表面质量的重要加工方法之一。在民用飞机机身的打磨过程中，表面粗糙度与材料去除率之间存在一定的相互制约关系，因此，如何在二者之间实现最优平衡是当前研究中的一大难点。针对这一问题，本文提出了一种基于灰色关联分析（gray relational analysis，GRA）-深度置信网络（deep belief network，DBN）的机器人打磨工艺多目标优化方法。首先，通过主成分分析（principal component analysis，PCA）优化GRA得到机器人打磨多目标与工艺参数之间的映射关系，将多目标优化转化为单目标优化问题。然后，结合DBN建立机器人打磨工艺参数优化模型。最后，进行实验验证，结果表明，所提出的方法不仅能够有效平衡表面粗糙度与材料去除率，还能提高打磨工艺的稳定性和可靠性。 |
| 英文摘要: |
| Robot polishing has become an important machining method for improving the surface quality of civil aircraft fuselages due to its flexibility, extensive workspace, and high operability. In the polishing process of civil aircraft fuselages, there exists a mutual constraint relationship between surface roughness and material removal rate. Therefore, achieving optimal balance between surface roughness and material removal rate is a significant challenge in current research. To address this issue, this paper proposes a multi-objective optimization method for robot polishing processes based on GRA(grey relational analysis)-DBN(deep belief networks). Initially, principal component analysis (PCA) is employed to optimize GRA and establish the mapping relationship between multi-objectives and process parameters. Subsequently, the multi-objective optimization is transformed into a single-objective optimization problem. Furthermore, integrating DBN facilitates the construction of an optimization model for robot polishing process parameters. Experimental validation demonstrates that the proposed method not only effectively balances surface roughness and material removal rate but also enhances the stability and reliability of the polishing process. |
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