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Accurate Adaptive Compensation Method for Mechanical Structure Error of the Blade Measuring System

机译：叶片测量系统机械结构误差的精确自适应补偿方法

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摘要

In view of the high precision requirement for mechanical structure of aeronautical blade measuring system, this paper proposes a laser interferometer to measure the error of the spatial nodes of the measuring system based on a comprehensive analysis of domestic and foreign error compensation methods for the measuring system. The optimized algorithm backpropagation (BP) neural network (OA-BPNN) compensation method is utilized to adaptively compensate for the systematic error of the mechanical system. Compared with the traditional polynomial fitting and genetic algorithm BP neural network (GA-BPNN) algorithm, the results show that the OA-BPNN algorithm is characterized by the best adaptability, precision, and efficiency for the adaptive error compensation. The spatial errors in the XYZ directions are reduced from 10.9, 60.1, and 84.2 mu m to 1.3, 4.0, and 2.4 mu m, respectively. The method is of great theoretical significance and practical value.
机译：鉴于对航空叶片测量系统机械结构的高精度要求，本文在对国内外测量系统误差补偿方法进行综合分析的基础上，提出了一种激光干涉仪来测量测量系统空间节点的误差。 。利用优化算法的BP神经网络（OA-BPNN）补偿方法，对机械系统的系统误差进行自适应补偿。与传统的多项式拟合和遗传算法BP神经网络（GA-BPNN）算法相比，结果表明OA-BPNN算法具有自适应误差补偿的最佳适应性，精度和效率。 XYZ方向的空间误差分别从10.9、60.1和84.2μm减少到1.3、4.0和2.4μm。该方法具有重要的理论意义和实用价值。

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