基于涡流传感器的叶尖正时信号高精度提取方法

IF 0.9 Q4 ENGINEERING, MECHANICAL
Ji-wang Zhang, K. Ding, Guang Chen
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引用次数: 5

摘要

高速旋转叶片的在线监测一直是一个热门话题。在各种方法中,基于涡流传感器的叶尖定时(BTT)技术被认为是最有前途的方法。然而,BTT信号容易受到各种因素的影响,这意味着准确提取BTT信号仍然是一个挑战。为了解决这一问题,分析了测量误差产生的原因。建立了产生误差的三个主要原因:叶尖间隙的变化、背景噪声的干扰和叶尖形状的不对称。在此基础上,提出了相应的改进方法,并对叶尖间隙变化引起的误差提出了补偿方法。针对背景噪声引起的误差,提出了一种基于集成经验模态分解(EEMD)的去噪整形算法。此外,针对叶尖形状不对称引起的误差,提出了传感器的最佳安装位置。最后,通过仿真和实验对改进的方法进行了验证。结果表明,该方法对振动幅值和振动频率的测量误差分别小于2.89%和0.17%,大大低于传统方法(分别为24.44%和0.39%)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
High-Precision Extraction Method for Blade Tip-Timing Signal with Eddy Current Sensor
Online monitoring of high-speed rotating blades has always been a hot topic. Of the various methods, the blade tip timing (BTT) technique, based on eddy current sensors, is considered to be the most promising. However, BTT signals are easily influenced by various factors, which means that the accurate extraction of BTT signals remains a challenge. To try to solve this problem, the causes of measurement error were analyzed. The three main reasons for the error were established: the variation in blade tip clearance, the interference of background noise, and the asymmetry of the blade tip shape. Further, pertinent improvement methods were proposed, and a compensation method was proposed for the errors caused by the variation of tip clearance. A new denoising and shaping algorithm based on ensemble empirical mode decomposition (EEMD) was introduced for the errors caused by background noise. Additionally, an optimal installation position of the sensor was also proposed for the errors caused by the asymmetry of the blade tip shape. Finally, simulations and experiments were used to demonstrate the improved methodology. The results show that the measurement error on vibration amplitude and vibration frequency using the proposed method is less than 2.89% and 0.17%, respectively, which is much lower than the traditional method (24.44% and 0.39%, respectively).
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来源期刊
CiteScore
2.40
自引率
0.00%
发文量
10
审稿时长
25 weeks
期刊介绍: This comprehensive journal provides the latest information on rotating machines and machine elements. This technology has become essential to many industrial processes, including gas-, steam-, water-, or wind-driven turbines at power generation systems, and in food processing, automobile and airplane engines, heating, refrigeration, air conditioning, and chemical or petroleum refining. In spite of the importance of rotating machinery and the huge financial resources involved in the industry, only a few publications distribute research and development information on the prime movers. This journal is the first source to combine the technology, as it applies to all of these specialties, previously scattered throughout literature.
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