基于激光自准直的发动机轴孔同轴度在线检测方法

Translated title of the contribution: Online Detection Method for Shaft Holes Coaxiality of Engine Based on Laser Autocollimation

Ting Zhi Hu, Zhong Qing Zhang, Mu Zheng Xiao*, Zhi Jing Zhang, Xin Jin, Yi Min Pu, Shi Ming Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

The quality and working condition of the turbofan engine are greatly affected by the coaxiality of the stator shaft holes, hence the coaxiality error is one of the most important factors for engine quality. Since reducing coaxiality error can improve the operation quality of the engine, the requirement of precise detection of engine coaxiality error is getting higher and higher. The existing manual detection methods have the problems of low efficiency and poor precision, and sometimes the position of measuring holes are too deep to be tested directly by general testing instruments. By analyzing the research status of coaxiality detection, the detection method and device based on laser autocollimation, which combined the laser alignment technology and hole self-centering technology, are proposed. The deformation of designed coaxial detection device is approximately 4μm, and the centering error is less than 4μm. Furthermore, a general method for detecting the coaxiality error of the engine stator shaft holes is obtained. It promises to accomplish the goal of online detection, consequently, the assembly time can be effectively shortened and the assembly process can also be optimized.

Translated title of the contributionOnline Detection Method for Shaft Holes Coaxiality of Engine Based on Laser Autocollimation
Original languageChinese (Traditional)
Pages (from-to)2099-2104
Number of pages6
JournalTuijin Jishu/Journal of Propulsion Technology
Volume40
Issue number9
DOIs
Publication statusPublished - 1 Sept 2019

Fingerprint

Dive into the research topics of 'Online Detection Method for Shaft Holes Coaxiality of Engine Based on Laser Autocollimation'. Together they form a unique fingerprint.

Cite this