Volume 14 Issue 2
Mar.  2021
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ZHANG Ying, DING Hong-chang, ZHAO Chang-fu, ZHOU Yi-gen, CAO Guo-hua. The normal alignment method for freeform surfaces based on multiple laser sensor assembly[J]. Chinese Optics, 2021, 14(2): 344-352. doi: 10.37188/CO.2020-0205
Citation: ZHANG Ying, DING Hong-chang, ZHAO Chang-fu, ZHOU Yi-gen, CAO Guo-hua. The normal alignment method for freeform surfaces based on multiple laser sensor assembly[J]. Chinese Optics, 2021, 14(2): 344-352. doi: 10.37188/CO.2020-0205

The normal alignment method for freeform surfaces based on multiple laser sensor assembly

Funds:  Supported by National Key Research and Development Program of Major Scientific Instruments and Equipment’s Development (No. 2017YFF0105304); Jilin Provincial Industrial Innovation Special Fund Project (No. 2018C038-4); Jilin Province Science and Technology Development Plan Project (No. 20200401117GX)
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  • In large aircraft product automation, the accuracy requirements for hole position detection are gradually increasing, and the vertical accuracy of a drill is the most important evaluation condition for this standard. When drilling and riveting are performed by automatic robotic systems, assembly error, bumps, offsets and other adverse conditions can reduce the accuracy of manufacturing and detection, and in turn the fatigue performance of the entire structure. To solve this problem, we proposed a technique for detecting a freeform surface’s normal-direction based on the adaptive alignment method using multiple laser sensor assemblies, built a mathematical model for posture alignment, and studied the calibration method and process required by the detection device. Additionally, we investigated techniques for error compensation using an electronic theodolite and other devices when the adaptive method is used for detection. In our verification experiments, multiple sets of results demonstrated that the key technical indicators were as follows: normal accuracy < ±0.5°, average deviation after correction is 0.0667°. This method can effectively compensate for the errors affecting hole making in automated manufacturing, and further improve the positioning accuracy and normal-direction detection accuracy of a robot.

     

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