A path planning method for large-scale blade profile measurement based on neutral network

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 the Probe 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 , 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.