Abstract: Blade tip timing measurement was a key measurement technology in aero-engine blade vibration monitoring systems. As an important part of timing signal preprocessing, the trend term fitting was the basis and premise of high-precision parameter identification of the blade vibrations. Under the continuous variable operating conditions of aero-engines, the current trend item fitting method could not adaptively adjust the width of the fitting windows, resulting in the poor quality of eliminating the trend items and seriously affecting the subsequent blade vibration analyses. Aiming at the problems of timing signal trend item fitting under continuing variable operating conditions, this paper used correlation coefficient as the evaluation of trend item fitting quality, and proposed a trend item fitting method with the window widths of adaptive adjustment. The tip-timing test data of an aero-engine high-pressure compressor was used for verification. The results show that the method may ensure the optimal fitting quality of the trend item due to adaptively adjusting the widths of the window. Under the premise of removing the trend item, the original vibration information may be completely retained, which is of great significance to achieve high-precision parameter identification of the blade vibrations.

Key words: blade tip timing measurement, trend term fitting, adaptive, correlation coefficient

摘要： 叶尖定时测量是航空发动机叶片振动监测关键技术，趋势项拟合作为定时信号预处理中的重要研究内容，是高精度叶片振动参数辨识的基础与前提。在航空发动机连续变工况运行条件下，当前趋势项拟合方法无法自适应调整拟合窗宽度，导致消除趋势项效果差，严重影响后续叶片振动分析。针对变工况条件下定时信号趋势项拟合难题，以相关系数作为趋势项拟合效果评价指标，提出趋势项自适应调节窗宽度拟合方法。采用航空发动机高压压气机叶尖定时试验数据进行验证，结果表明，所提方法由于能够自适应调节拟合窗宽度，可保证趋势项拟合效果最优，在满足有效去除趋势项的前提下能够完全保留原始振动信息，对实现高精度叶片振动参数辨识具有重要意义。

关键词: 叶尖定时测量, 趋势项拟合, 自适应, 相关系数