作者：罗瑛1, 朱杨洋2, 王宗平2, 殷国富2
作者单位：1. 成都工业学院，四川 成都 611700;
2. 四川大学机械工程学院，四川 成都 610065
关键词：叶片型面检测;线激光器;回转中心;多视数据重构损失
摘要：
航发叶片型面检测是保证叶片加工质量、工作性能和使用寿命的关键环节。对此，该文开发一套基于线激光器的叶片型面检测平台；在完成线激光器与叶片相对位姿校准及z向测量基准建立基础上，实现叶片型面特定截面处型线数据的多视采集；提出一种基于多视数据重构损失标定回转中心的型线重构方法。以两种典型燃气轮机导向叶片为检测对象，所提出方法获取的检测数据与三坐标测量机检测数据的对比结果表明，轮廓度检测平均绝对偏差在0.022 mm以内，最大标准偏差为0.0186 mm，最大rms估计为0.0251 mm；特征参数检测最大偏差为0.0401mm。实验结果验证了所提出方法面向叶片型面检测的可行性。
optical measurement of blade profile based on multi-view data reconstruction loss calibration
luo ying1, zhu yangyang2, wang zongping2, yin guofu2
1. chengdu technological university, chengdu 611700, china;
2. school of mechanical engineering,sichuan university, chengdu 610065, china
abstract: profile measurement for aero-engine blades is essential to ensure their processing quality, working performance, and service life. therefore, a measurement platform based on laser scanning sensor is first developed for blade profile measurement. by calibrating the relative position between the blade and laser scanning sensor and establishing a measurement datum along the z-direction, multi-view data acquisition of blade profile at specific cross-sections is achieved. finally, a blade profile reconstruction method based on multi-view data reconstruction loss is proposed to calibrate rotational center. compared with the measurement data obtained by coordinate measurement machine (cmm) on two typical gas turbine blades, the average absolute deviation on the measurement data obtained by the proposed method is within 0.022 mm, the maximum standard deviation is 0.0186 mm, the maximum root mean square (rms) estimation is 0.0251 mm, and the maximum deviation of the main characteristic parameters is 0.0401 mm. the experimental results demonstrate the feasibility of the proposed method for blade profile measurement.
keywords: blade profile measurement;laser scanning sensor;rotational center;multi-view data reconstruction loss
2024, 50(8):118-124 收稿日期: 2022-12-13;收到修改稿日期: 2023-02-11
基金项目: 四川省智能制造专项经费项目（2018cd00225）
作者简介: 罗瑛（1983-），女，四川西充县人，讲师，硕士，主要研究方向为数字化设计制造技术与工业工程。
参考文献
"[1] 夏桂书, 吴虹星, 魏永超, 等. 旋转状态下的航空发动机叶片形变测量[j]. 中国测试, 2022, 48(12): 40-44.
xia g s, wu h x, wei y c, et al. deformation measurement of aero-engine blades under rotating state[j]. china measurement & test, 2022, 48(12): 40-44.
[2] 黄智, 李超, 李凯, 等. 航空叶片型面三坐标检测技术现状及发展趋势[j]. 航空制造技术, 2017(540): 73-79.
huang z, li c, li k, et al. status and prospect of detection technology of coordinate measuring machine for blade surface of aeroengine[j]. aeronautical manufacturing technology, 2017(540): 73-79.
[3] peng w, wang y, miao z, et al. viewpoints planning for active 3-d reconstruction of profiled blades using estimated occupancy probabilities (eop)[j]. ieee t ind electron, 2020, 68(5): 4109-4119.
[4] 郑昊天, 殷鸣, 王宗平, 等. 基于前缘特征标定的叶片型面光学检测[j]. 组合机床与自动化加工技术, 2022(4): 74-78.
zheng h t, yin m, wang z p, et al. optical measurement for blade profile based on leading edge feature calibration[j]. modular machine tool & automatic manufacturing technique, 2022(4): 74-78.
[5] xie l, zhu y, yin m, et al. self-feature-based point cloud registration method with a novel convolutional siamese point net for optical measurement of blade profile[j]. mech syst signal pr, 2022, 178: 109243.
[6] yin m, zhu y, yin g, et al. deep feature interaction network for point cloud registration, with applications to optical measurement of blade profiles[j]. ieee transactions on industrial informatics, 2023, 19(8): 8614-8624.
[7] wang z p, yin m, dong j, et al. multi-view point clouds registration method based on overlap-area features and local distance constraints for the optical measurement of blade profiles[j]. ieee-asme transactions on mechatronics, 2022, 27(5): 2729 - 2739.
[8] li w, wu a, li z, et al. a new calibration method between an optical sensor and a rotating platform in turbine blade inspection[j]. meas sci technol, 2017, 28(3): 035009.
[9] 刘浩浩, 殷鸣, 王宗平, 等. 基于线结构光的叶片型面特征检测方法研究[j]. 中国测试, 2021, 47(2): 6-12.
liu h h, yin m, wang z p, et al. research on feature detection method of blade surface based on line structured light[j]. china measurement & test, 2021, 47(2): 6-12.
[10] sun b, li b. a rapid method to achieve aero-engine blade form detection[j]. sensors-basel, 2015, 15(6): 12782-12801.
[11] he w t, zhong k, li z w, et al. accurate calibration method for blade 3d shape metrology system integrated by fringe projection profilometry and conoscopic holography[j]. optics and lasers in engineering, 2018(110): 253-261.
[12] 傅屈晨, 谢核, 贺峥嵘, 等. 三维测量系统中基于圆锥拟合的旋转台轴线标定新方法[j]. 装备制造技术, 2018(6): 176-180.
fu q c, xie h, he z r, et al. a turntable calibration method based on conic-fitting for 3d measurement system[j]. equipment manufacturing technology, 2018(6): 176-180.
[13] wang z p, yin m, ou d y, et al. optical measurement method for blade profiles based on blade self-features[j]. ieee transactions on industrial electronics, 2022, 69(2): 2067-2076.
[14] 欧登荧, 殷鸣, 王宗平, 等. 基于侧边基准面标定的叶片型面光学检测[j]. 组合机床与自动化加工技术, 2022(1): 98-102.
ou d y, yin m, wang z p, et al. research on optical inspection method of blade profile based on side datum plane calibration[j]. modular machine tool & automatic manufacturing technique, 2022(1): 98-102.
[15] 冯田, 冯志辉, 南亚明, 等. 基于特征向量提取的点云配准算法[j]. 电子测量技术, 2022, 45(15): 57-62.
feng t, fen z h, nan y m, et al. point cloud registration algorithm based on feature vector extraction[j]. electronic measurement technology, 2022, 45(15): 57-62.
