Blade resonance parameter identification based on tip-timing method without the once-per revolution sensor

Guo, Haotian; Duan, Fajie; Zhang, Jilong

doi:10.1016/j.ymssp.2015.06.016

Cited by 76 publications

(27 citation statements)

References 17 publications

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“…For the last 40 years, several solutions have been developed to face the difficulty of estimating blade vibrations from sub-sampled and irregular tip-timing signals [2,3,4,5,6]. However, the multi-components spectral analysis remains an open issue.…”

Section: Spectral Analysis With Tip-timing Signalsmentioning

confidence: 99%

Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm

Bouchain

Picheral

Lahalle

et al. 2019

Mechanical Systems and Signal Processing

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Blades vibrations must be measured in operations to validate blade design. Tip-timing is one of the classical measurement methods but its main drawback is the generation of sub-sampled and non-uniform sampled signals. Consequently tip-timing signals cannot be processed with conventional methods. Assuming that blade vibration signals yield to line spectra, we introduced a sparse signal model that uses speed variation of the engine. The usual solutions of inverse problems are given with the LASSO method. This paper presents a new approach based on a ℓ 0-regularization. It is solved with the OMP algorithm adapted to our model. Results from synthetic and real signals are presented to illustrate the efficiency of this method, including a real blade crack test case. The main advantages of the proposed method are to provide accurate estimations with a computational cost drastically reduced with respect to existing methods. Besides, the method does not need to set up regularization parameters while taking into account the speed variation of the engines. Finally, results show that this approach greatly reduces frequency aliasings caused by the low sampling frequency of the measured signals.

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Section: Spectral Analysis With Tip-timing Signalsmentioning

confidence: 99%

Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm

Bouchain

Picheral

Lahalle

et al. 2019

Mechanical Systems and Signal Processing

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“…等故障 [1] 。一方面，叶片振动是导致发动机故障的重要原因之一；另一方面，叶片故障通过振动信号能够很好地反映出来。因此，对叶片振动进行监测，及时发现叶片出现的结构故障、损伤，是保证发动机运行安全的有效途径。相对于传统接触式测量方法，BTT 测量技术 [2][3][4] 因其原理简单，操作便捷，安装成本低，灵敏度高，且可以同时监测整圈叶片的振动状态等优点，是叶片振动非接触式在线监测的研究热点。 BTT 测量技术的原理 [5] 是通过安装在固定机匣上的 BTT 传感器来测量叶片的到达时间，并将实际测量时间与叶片无振动时的到达时间进行比较，得到时间偏差序列{∆t}，利用该时间差序列进行计算可以得到叶片叶端的振动位移序列，进而通过参数辨识方法获取叶片的振动特性。典型的 BTT 测量系统除了包含 BTT 传感器外还包含一个参考(Once per revolution, OPR)传感器，其通常安装在靠近转动中心轴线处，对叶片转速进行测量，为后续测量数据的处理提供转速信号和位置时间基准 [6] 。由于参考传感器安装于发动机内部，发动机的复杂工况及恶劣的内部环境不仅会影响参考传感器测量的准确性，且易导致传感器失效甚至发生脱落，轻则造成测量系统失效，重则引发严重的安全事故 [7] 。此外，受限于发动机的结构和内部空间，将参考传感器安装至最佳测量位置往往具有难度。因此，不安装参考传感器的 BTT 测量系统更加符合航空发动机安全性、可靠性及经济性的发展需求。 2005 年德国 MTU 公司的 MICHAEL 等 [8] 首次提出了无参考传感器 BTT 测量的概念。近年来，无参考传感器 BTT 测量和参数辨识方法逐渐引起关注，但公开发表的文献比较少，尚且没有投入到工程应用的测量系统。英国罗罗公司的 RUSSHARD 等 [9] 提出了通过分析估计叶片到达时间与叶片旋转角度的关系产生虚拟参考信号的方法，并对测量过程中出现的计错数的情况进行了分析且提出了相应的解决方案。中国航空发动机集团 606 所的胡伟等 [7] 运用单自由度理论分析了无参考传感器 BTT 测量技术的原理，并研究了无参考传感器条件下影响叶片振动测量误差的因素。天津大学郭浩天等 [10][11] 分别提出了在变速扫频情况下使用三个 BTT 传感器和恒定转速情况下使用五个 BTT 传感器实现无参考传感器叶片同步振动参数辨识的方法。 ZHANG 等 [12] [13] 于 2000 年提出了一种在变速扫频测量下能够同时辨识叶片同步振动振幅及振动倍频的方法。将 BTT 传感器如图 2 所示进行布局，图中的箭头指向表示叶片的旋转方向，α 1 、α 2 分别表示传感器 Tip1、Tip2 与传感器 Tip0 的安装夹角。假定叶片在单频简谐激励作用下产生单自由度振动 [10] ，则…”

Section: 易发生振动，导致叶片疲劳，甚至出现裂纹、断裂unclassified

Research on Blade Synchronous Vibration Parameter Identification Using Blade Tip Timing without the once per Revolution Sensor

Changyi¹,

Hu²,

Yang³

et al. 2019

Journal of Mechanical Engineering

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：Blade tip timing (BTT) is considered a promising technique for monitoring blade vibration online for aero-engine. The majority of BTT measurement and analysis systems require a once-per revolution (OPR) sensor to generate a timing reference and measure the rotating speed of blades. However, one of the challenges in the development of BTT technique is that it's extremely difficult to install the OPR sensor and that the installation of the OPR sensor may cause potential security risks, leading to the failure of the existing BTT measurement. The method of synchronous vibration parameters identification, called two parameter plot method, is improved by mounting an additional BTT sensor and the amplitude and engine order (N e) of blade vibration can be identified through analyzing the vibration displacement change. By numerical simulation and experiments, the results of vibration parameters identification are analyzed, which show validity and feasibility of the arithmetic. The work provides technology means of BTT measurement without the once per revolution sensor.

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“…The basic principle underlying the BTT technique is to measure the difference between theoretical and actual times at which the blade tips sweep across the probes, thereby facilitating the calculation of vibration displacement. This implies that irrespective of whether the measuring method depends on the reference phase or not [8], the rotational speed must be maintained constant. However, in practical turbomachine applications, the speed of rotation hardly remains constant.…”

Section: Conventional Blade Tip-timing Systemmentioning

confidence: 99%

“…Therefore, there exists a need for continuous monitoring of the blade state under various operating conditions. Development of online-monitoring methods for rotating blades has become an important area of research in recent years, and various techniques, such as the strain-gauge technology [1], optical backscatter reflectometer [2], laser Doppler [3], acoustic emission [4], coherent laser radar [5], and blade-tip timing [6]- [8] have been devised. Amongst these methods, the BTT technology is considered to be the most promising owing to its advantages of low cost and non-contact utility [9]- [11].…”

Section: Introductionmentioning

confidence: 99%

Blade Tip-timing Technology with Multiple Reference Phases for Online Monitoring of High-speed Blades under Variable-speed Operation

Zhang

Ding

et al. 2018

Measurement Science Review

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High-speed blades form core mechanical components in turbomachines. Research concerning online monitoring of operating states of such blades has drawn increased attention in recent years. To this end, various methods have been devised, of which, the blade tip-timing (BTT) technique is considered the most promising. However, the traditional BTT method is only suitable for constant-speed operations. But in practice, the rotational speed of turbomachine blades is constantly changing under the influence of external factors, which lead to unacceptable errors in measurement. To tackle this problem, a new BTT method based on multi-phases is proposed. A plurality of phases was arranged as evenly as possible on the rotating shaft to determine the rotation speed. Meanwhile, the corresponding virtual reference point was determined in accordance with the number of blades between consecutive phases. Based on these reference points, equations to measure displacement due to blade vibrations were deduced. Finally, mathematical modeling, numerical simulation and experimental tests were performed to verify the validity of the proposed method. Results demonstrate that the error in measurement induced when using the proposed method is less than 1.8 %, which is much lower compared to traditional methods utilized under variable-speed operation.

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Blade resonance parameter identification based on tip-timing method without the once-per revolution sensor

Cited by 76 publications

References 17 publications

Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm

Blade vibration study by spectral analysis of tip-timing signals with OMP algorithm

Research on Blade Synchronous Vibration Parameter Identification Using Blade Tip Timing without the once per Revolution Sensor

Blade Tip-timing Technology with Multiple Reference Phases for Online Monitoring of High-speed Blades under Variable-speed Operation

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