An Image-Based Turbine Blade Parameter Inspection Method

doi:10.12096/j.2096-4528.pgt.21146

Abstract

Abstract:

Accurate inspection of the feature parameters of the blade is a pivotal step to conduct the performance diagnosis and reverse modeling. To improve the inspection efficiency, an image-based parameter inspection method was proposed. First, the skeleton extraction algorithm was used to locate the middle arc of the blade. Then, the middle arc function and the blade thickness distribution function were obtained by the 3-order polynomial curve fitting algorithms. Finally, an optimization algorithm was derived to improve the inspection accuracy. Experimental results show that the proposed image-based feature parameter inspection method has high accuracy, and the relative measurement error is less than 1.5%. It provides a new solution for the rapid and accurate measurement of blade geometric parameters.

Key words: gas turbine, blade parameter inspection, image processing, skeleton extraction

CLC Number:

TK 05

Zeyang CUI, Xiangling KONG, Jinglun FU, Jiajun SHI. An Image-Based Turbine Blade Parameter Inspection Method[J]. Power Generation Technology, 2024, 45(1): 106-112.

Figures/Tables 13

Fig. 1 Steps of the proposed image-based blade parameter inspection method

Fig. 2 Definitions of background point, internal point and contour point

Fig. 3 Feature parameters of the blade

Fig. 4 Skeleton extraction for a blade image

Fig. 5 Experimental setting for image acquisition

Fig. 4 Software interface of the proposed image-based blade feature parameter inspection method

Tab. 1 Feature parameters of a blade

参数	L/mm	R_f/mm	R_r/mm	R_max/mm	P_max/mm	T/mm	α_f/(°)	α_r/(°)
真实值	70	3	2	8	25	24	45	40

Fig. 6 Preprocessing for the turbine blade image

Tab. 2 Error analysis between the inspected feature parameters and the standard values

叶型参数	真实值	测量值	绝对误差
L/mm	70	68.41	1.59
R_f/mm	3	3.07	0.07
R_r/mm	2	1.99	0.01
R_max/mm	8	7.84	0.16
P_max/mm	25	23.49	1.51
T/mm	24	24.41	0.41
α_f/(°)	45	42.10	2.90
α_r/(°)	40	40.05	0.05

Fig. 7 Comparison between the original and the turbine blade reconstruction using inspected feature parameters

Fig. 8 Convergence of the feature parameter optimization

Tab. 3 Error analysis between the optimized feature parameters and the standard values

叶型参数	真实值	优化值	绝对误差
L/mm	70	70.02	0.02
R_f/mm	3	3.04	0.04
R_r/mm	2	2.02	0.02
R_max/mm	8	8.01	0.01
P_max/mm	25	24.81	0.19
T/mm	24	23.89	0.11
α_f/(°)	45	45.42	0.42
α_r/(°)	40	39.41	0.59

Fig. 9 Comparison between the original and the turbine blade reconstruction using optimized feature parameters

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