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

Wei Shao,Awei Zhou,Di Zhao,Peng Peng,Quanquan Zhu

doi:10.1155/2018/7527392

Abstract

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 μm to 1.3, 4.0, and 2.4 μm, respectively. The method is of great theoretical significance and practical value.

Highlights

As the blade is one of the essential components of the engine, the measurement of the blade with high efficiency, precision, and consistency in the manufacturing process is fundamental to enhance the manufacturing quality [1, 2]
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
In order to compensate for the error in the blade measuring system, this paper proposes a laser interferometer to measure the error of the spatial nodes of the measurement system based on the findings of previous studies

Summary

Introduction

As the blade is one of the essential components of the engine, the measurement of the blade with high efficiency, precision, and consistency in the manufacturing process is fundamental to enhance the manufacturing quality [1, 2]. The error of the mechanical system mainly includes geometric error, force deformation error, thermal error, and dynamic error [8, 9] These deformations change the spatial position of the measuring head, causing error in the data and affecting the accuracy of the measuring system. Literature [17,18,19,20,21] deals with geometric error and force deformation error of the measuring machine based on meshing [17,18,19,20,21]. In this paper, based on previous research, the laser interferometer is used to measure the error of the spatial nodes of the mechanical structure, and the optimized backpropagation neural network (OA-BPNN) algorithm is applied to adaptively compensate for the error. The method is of great theoretical significance and practical value

Error Analysis of the Blade Measuring System

Error Compensation Experiment

Findings

Conclusions