王洪乐,王家序,周青华,熊青春,张磊.航空结构件铣削加工表面波纹度特征提取与研究[J].表面技术,2016,45(9):154-162.
WANG Hong-le,WANG Jia-xu,ZHOU Qing-hua,XIONG Qing-chun,ZHANG Lei.Characteristic Extraction and Study of the Surface Waviness of Aircraft Structure Components in Milling Process[J].Surface Technology,2016,45(9):154-162 |
| 航空结构件铣削加工表面波纹度特征提取与研究 |
| Characteristic Extraction and Study of the Surface Waviness of Aircraft Structure Components in Milling Process |
| 投稿时间：2016-03-05 修订日期：2016-09-20 |
| DOI：10.16490/j.cnki.issn.1001-3660.2016.09.024 |
| 中文关键词: 航空结构件 表面波纹度 频谱分析 Daubechies小波分析 Mallat算法 |
| 英文关键词:aircraft structure components surface waviness frequency spectrum analysis Daubechies wavelet Mallat algorithm |
| 基金项目:国家自然科学基金项目（51435001）；中航工业产学研专项项目（cxy2013CD36） |
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| Author | Institution |
| WANG Hong-le | School of Aeronautics and Astronautics, Sichuan University, Chengdu 610065, China |
| WANG Jia-xu | 1.School of Aeronautics and Astronautics, Sichuan University, Chengdu 610065, China;2.State Key Laboratory of Transmission, Chongqing University, Chongqing 400044, China |
| ZHOU Qing-hua | School of Aeronautics and Astronautics, Sichuan University, Chengdu 610065, China |
| XIONG Qing-chun | 1.School of Aeronautics and Astronautics, Sichuan University, Chengdu 610065, China; 2.AVIC Chengdu Aircraft Industrial (Group) Co., Ltd, Chengdu 610092, China |
| ZHANG Lei | School of Aeronautics and Astronautics, Sichuan University, Chengdu 610065, China |
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| 中文摘要: |
| 目的 由于航空结构件壁薄、结构复杂和刚度低等原因，在多轴联动铣削加工过程中，其表面容易出现波纹度等加工纹理缺陷。准确提取、评价铣削表面波纹度，为控制和消除结构件铣削表面波纹度提供可视化参考依据。方法 提出了一种频谱分析和小波分析相结合的方法。首先对已加工的航空结构件的铣削表面综合形貌进行频谱分析，依据表面形貌划分依据，确定各表面成分有效信息的频率段范围；再采用Daubechies小波分解原表面形貌特征，把含有不同频率成分的信息分解到互不重叠的频率段上；利用Mallat快速算法，计算出各逼近系数和小波系数，并对有效频率段进行重构，以实现表面形貌特征不同频率成分的提取，进而获取表面波纹度的形貌特征信息。结果 针对某型航空结构件的铣削表面，采用文中方法提取到的波纹度形貌特征信息与粗糙度轮廓仪测量的结果基本吻合，验证了该方法的正确性。结论 对于提取铣削表面波纹度特征信息，采用频谱分析和小波分析相结合的方法是可行且有效的。 |
| 英文摘要: |
| Objective Multiple-axis machining may cause surface texture defects, like waviness, on complex aeronautical structure components, which have the characteristics of thin walls, complex structure and low stiffness etc. In order to control and eliminate milling surface waviness, accurately obtaining and evaluating the parameters of the waviness can supply visual reference for them. Methods A method combining frequency spectrum analysis and wavelet analysis was proposed in this paper. Frequency spectrum analysis was firstly conducted to study the comprehensive surface topography to find the frequency band range of valid topography information based on the condition of surface topography characteristics. Then, the original surface topography was decomposed by Daubechies wavelet technique. The information containing different frequency components was arranged into the non-overlapping frequency bands. Approximation coefficients and wavelet coefficients were calculated through the Mallat algorithm and the different frequency components in surface topography characteristics were extracted. Finally surface waviness characteristic information was obtained. Results The extracted surface waviness from an aircraft structure component by the proposed method was compared with the measurement data of a surface profiler. Good agreement was obtained between the results of the two methods, demonstrating the correctness of the proposed method. Conclusion The proposed method is effective for extracting the waviness information on the milling surface. |
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