| 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],45(9):154-162 |
| Characteristic Extraction and Study of the Surface Waviness of Aircraft Structure Components in Milling Process |
| Received:March 05, 2016 Revised:September 20, 2016 |
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| DOI：10.16490/j.cnki.issn.1001-3660.2016.09.024 |
| KeyWord:aircraft structure components surface waviness frequency spectrum analysis Daubechies wavelet Mallat algorithm |
| Author | Institution |
| WANG Hong-le |
School of Aeronautics and Astronautics, Sichuan University, Chengdu , China |
| WANG Jia-xu |
1.School of Aeronautics and Astronautics, Sichuan University, Chengdu , China;2.State Key Laboratory of Transmission, Chongqing University, Chongqing , China |
| ZHOU Qing-hua |
School of Aeronautics and Astronautics, Sichuan University, Chengdu , China |
| XIONG Qing-chun |
1.School of Aeronautics and Astronautics, Sichuan University, Chengdu , China; 2.AVIC Chengdu Aircraft Industrial Group Co., Ltd, Chengdu , China |
| ZHANG Lei |
School of Aeronautics and Astronautics, Sichuan University, Chengdu , China |
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| Abstract: |
| 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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