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Measurement Science Review

The Journal of Institute of Measurement Science of Slovak Academy of Sciences

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Volume 18, Issue 6


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

Zhang Ji-wang / Zhang Lai-bin
  • College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ Ding Ke-Qin / Duan Li-xiang
  • College of Mechanical and Transportation Engineering, China University of Petroleum, Beijing 102249, China
  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
Published Online: 2018-11-30 | DOI: https://doi.org/10.1515/msr-2018-0033


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.

Keywords: BTT technology; variable speed; online monitoring; multiple reference phases (MRP)


  • [1] Tavakolpour-Saleh, A.R., Setoodeh, A.R., Gholamzadeh, M. (2016). A novel multi-component strain-gauge external balance for wind tunnel tests: Simulation and experiment. Sensors and Actuators A: Physical, 247, 172-186.Google Scholar

  • [2] Sierra-Pérez, J., Torres-Arredondo, M.A., Güemes, A. (2016). Damage and nonlinearities detection in wind turbine blades based on strain field pattern recognition. FBGs, OBR and strain gauges comparison. Composite Structures, 135, 156-166.Google Scholar

  • [3] Rothberg, S.J., Allen, M.S., Castellini, P. (2017). An international review of laser Doppler vibrometry: Making light work of vibration measurement. Optics and Lasers in Engineering, 99, 11-22.Google Scholar

  • [4] Tang, J., Soua, S., Mares, C. (2016). An experimental study of acoustic emission methodology for in service condition monitoring of wind turbine blades. Renewable Energy, 99, 170-179.Google Scholar

  • [5] Talbot, J., Wang, Q., Brady, N. (2016). Offshore wind turbine blades measurement using Coherent Laser Radar. Measurement, 79, 53-65.Google Scholar

  • [6] Battiato, G., Firrone, C.M., Berruti, T.M. (2017). Forced response of rotating bladed disks: Blade Tip-Timing measurements. Mechanical Systems and Signal Processing, 85, 912-926.Google Scholar

  • [7] Lin, J., Hu, Z., Chen, Z.-S. (2016). Sparse reconstruction of blade tip-timing signals for multimode blade vibration monitoring. Mechanical Systems and Signal Processing, 81, 250-258.Google Scholar

  • [8] Guo, H., Duan, F., Zhang, J. (2016). Blade resonance parameter identification based on tip-timing method without the once-per revolution sensor. Mechanical Systems and Signal Processing, 66-67, 625-639.Google Scholar

  • [9] dos Santos, F.L.M., Peeters, B., van der Auweraer, H. (2016). Vibration-based damage detection for a composite helicopter main rotor blade. Case Studies in Mechanical Systems and Signal Processing, 3, 22-27.Google Scholar

  • [10] Rzadkowski, R., Rokicki, E., Piechowski, L. (2016). Analysis of middle bearing failure in rotor jet engine using tip-timing and tip-clearance techniques. Mechanical Systems and Signal Processing, 76-77, 213-227.Google Scholar

  • [11] Rigosi, G., Battiato, G., Berruti, T.M. (2017). Synchronous vibration parameters identification by tip timing measurements. Mechanics Research Communications, 79, 7-14.Google Scholar

  • [12] Neumann, M., Dreier, F., Günther, P. (2015). A laseroptical sensor system for blade vibration detection of high-speed compressors. Mechanical Systems and Signal Processing, 64-65, 337-346.Google Scholar

  • [13] Allport, J.M., Jupp, M.L., Pezouvanis, A. (2012). Turbocharger blade vibration: Measurement and validation through laser tip-timing. In 10th International Conference on Turbochargers and Turbocharging, 173-181.Google Scholar

  • [14] Chen, Z., Yang, Y., Xie, Y. (2013). Non-contact crack detection of high-speed blades based on principal component analysis and Euclidian angles using opticalfiber sensors. Sensors and Actuators A: Physical, 201, 66-72.Google Scholar

  • [15] Di Maio, D., Ewins, D.J. (2012). Experimental measurements of out-of-plane vibrations of a simple blisk design using Blade Tip Timing and Scanning LDV measurement methods. Mechanical Systems and Signal Processing, 28, 517-527.Google Scholar

  • [16] Günther, P., Dreier, F., Pfister, T. (2011). Measurement of radial expansion and tumbling motion of a high-speed rotor using an optical sensor system. Mechanical Systems and Signal Processing, 25, 319-330.Google Scholar

  • [17] Zhou, Z., Chen, S., Li, W. (2018). Experiment study of aerodynamic performance for the suction-side and pressure-side winglet-cavity tips in a turbine blade cascade. Experimental Thermal and Fluid Science, 90, 220-230.Google Scholar

  • [18] Ma, H., Lu, Y., Wu, Z., Tai, X. (2016). Vibration response analysis of a rotational shaft–disk–blade system with blade-tip rubbing. International Journal of Mechanical Sciences, 107, 110-125.Google Scholar

  • [19] Tahani, M., Maeda, T., Babayan, N. (2017). Investigating the effect of geometrical parameters of an optimized wind turbine blade in turbulent flow. Energy Conversion and Management, 153, 71-82.Google Scholar

  • [20] Heath, S., Imregun, M. (1996). An improved singleparameter tip-timing method for turbomachinery blade vibration measurements using optical laser probes. International Journal of Mechanical Sciences, 38, 1047-1058.Google Scholar

  • [21] Xie, F., Ma, H., Cui, C. (2017). Vibration response comparison of twisted shrouded blades using different impact models. Journal of Sound and Vibration, 397, 171-191.Google Scholar

  • [22] Huang, H., Baddour, N., Liang, M. (2018). Bearing fault diagnosis under unknown time-varying rotational speed conditions via multiple time-frequency curve extraction. Journal of Sound and Vibration, 414, 43-60.Google Scholar

  • [23] Feng, Z., Chen, X., Wang, T. (2017). Time-varying demodulation analysis for rolling bearing fault diagnosis under variable speed conditions. Journal of Sound and Vibration, 400, 71-85.Google Scholar

  • [24] Mishra, C., Samantaray, A.K., Chakraborty, G. (2016). Rolling element bearing defect diagnosis under variable speed operation through angle synchronous averaging of wavelet de-noised estimate. Mechanical Systems and Signal Processing, 72-73, 206-222.Google Scholar

  • [25] Wang, T., Liang, M., Li, J. (2015). Bearing fault diagnosis under unknown variable speed via gear noise cancellation and rotational order sideband identification. Mechanical Systems and Signal Processing, 62-63, 30-53.Google Scholar

  • [26] Abboud, D., Antoni, J., Sieg-Zieba, S. (2017). Envelope analysis of rotating machine vibrations in variable speed conditions: A comprehensive treatment. Mechanical Systems and Signal Processing, 84, 200-226.Google Scholar

  • [27] Guo, Y., Li, G., Chen, H. (2017). Development of a virtual variable-speed compressor power sensor for variable refrigerant flow air conditioning system. International Journal of Refrigeration, 74, 73-85.Google Scholar

  • [28] Han, D., Pastrikakis, V., Barakos, G.N. (2016). Helicopter performance improvement by variable rotor speed and variable blade twist. Aerospace Science and Technology, 54, 164-173.Google Scholar

  • [29] Yang, J., Song, D., Dong, M. (2016). Comparative studies on control systems for a two-blade variablespeed wind turbine with a speed exclusion zone. Energy, 109, 294-309.Google Scholar

  • [30] Wang, W., Ren, S., Chen, L., Shao, H. (2017). The blade vibration measurement research based on the key phase interpolation method. Journal of Vibration, Measurement & Diagnosis, 37, 361-365.Google Scholar

  • [31] Blundell, M., Harty, D. (2014). Multibody systems simulation software. In The Multibody Systems Approach to Vehicle Dynamics (Second Edition). Butterworth-Heinemann, 87-184Google Scholar

About the article

Received: 2018-04-09

Accepted: 2018-11-07

Published Online: 2018-11-30

Published in Print: 2018-10-01

Citation Information: Measurement Science Review, Volume 18, Issue 6, Pages 243–250, ISSN (Online) 1335-8871, DOI: https://doi.org/10.1515/msr-2018-0033.

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© 2018 Zhang Ji-wang et al., published by Sciendo. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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