TY - GEN
T1 - A path planning method for large-scale blade profile measurement based on neutral network
AU - Zhang, Fei
AU - Jiang, Zhuang De
AU - Ding, Jian Jun
AU - Li, Bing
AU - Chen, Lei
PY - 2008
Y1 - 2008
N2 - For solving the problem of programming measurement path when inspecting Blade Profile, and improving the efficiency and precision, the self-adaptive dynamic path planning model of blade profile measurement is proposed, using Back Propagation Neutral Network, based on the blade measuring characteristic and non-contact measurement system of blade profile detecting in laser triangular principle. For the feature of blade profile measuring, with the factors affecting theProbe precision and efficiency (the range of depth of field, incident angle), we plan the probe position of next measurement point by selecting 3 layer BP networks of l0 × l4×1, using practically measured blade profile as Training Sample, and regarding probe coordinates of corresponding profile measuring point as networks input. This paper discusses and explains the factors affecting measurement path planning, the creating and training of the BP networks profile measurement path planning in details. Because of the use of Neural Network learning the ability of approximating nonlinear mapping in any precision and the application of regarding blade profile data as BP network training sample, measuring movement path can combine with the blade curvature variation closely. Then, practically measuring precision and efficiency are improved, and the Path Planning problem is solved, brought by curvature varying greatly of blade profile in large blade profile measurement. At last, a group of experimental data is given, and the results of experiment are analyzed in detail.
AB - For solving the problem of programming measurement path when inspecting Blade Profile, and improving the efficiency and precision, the self-adaptive dynamic path planning model of blade profile measurement is proposed, using Back Propagation Neutral Network, based on the blade measuring characteristic and non-contact measurement system of blade profile detecting in laser triangular principle. For the feature of blade profile measuring, with the factors affecting theProbe precision and efficiency (the range of depth of field, incident angle), we plan the probe position of next measurement point by selecting 3 layer BP networks of l0 × l4×1, using practically measured blade profile as Training Sample, and regarding probe coordinates of corresponding profile measuring point as networks input. This paper discusses and explains the factors affecting measurement path planning, the creating and training of the BP networks profile measurement path planning in details. Because of the use of Neural Network learning the ability of approximating nonlinear mapping in any precision and the application of regarding blade profile data as BP network training sample, measuring movement path can combine with the blade curvature variation closely. Then, practically measuring precision and efficiency are improved, and the Path Planning problem is solved, brought by curvature varying greatly of blade profile in large blade profile measurement. At last, a group of experimental data is given, and the results of experiment are analyzed in detail.
KW - Laser triangular principle
KW - Neutral network
KW - Path planning
KW - Profile measurement
UR - https://www.scopus.com/pages/publications/57549087391
U2 - 10.1117/12.814566
DO - 10.1117/12.814566
M3 - 会议稿件
AN - SCOPUS:57549087391
SN - 9780819473981
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Ninth International Symposium on Laser Metrology
T2 - 9th International Symposium on Laser Metrology
Y2 - 30 June 2008 through 2 July 2008
ER -