• CN: 11-2187/TH
  • ISSN: 0577-6686

Journal of Mechanical Engineering ›› 2024, Vol. 60 ›› Issue (24): 35-44.doi: 10.3901/JME.2024.24.035

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Research on Improved Vibration Measurement of Rotating Machinery Based on Image Phase and General Curvelet Transform

ZHANG Wendi1,2, LI Hongguang1,2, ZHOU Jiwen1,2, WANG Jinhong1,2, LI Zhenping3   

  1. 1. Institute of Vibration, Shock and Noise, Shanghai Jiao Tong University, Shanghai 200240;
    2. State Key Laboratory of Mechanical System and Vibration, Shanghai Jiao Tong University, Shanghai 200240;
    3. China North Vehicle Research Institute, Beijing 100072
  • Received:2023-12-18 Revised:2024-09-14 Online:2024-12-20 Published:2025-02-01

Abstract: With the development of digital camera and data storage technology, vision-based measurement technology has attracted extensive attention of researchers. Recently, a phase-based motion estimation algorithm has been developed rapidly by advantages of its strong adaptability, sub-pixel accuracy and high spatial resolution. However, several key technologies, such as image multiscale decomposition and spatial frequency estimation, still have shortcomings. Thus, on the basis of phase-based motion estimation algorithm, an improved phase-based motion estimation algorithm is developed to improve the computation accuracy. First, general curvelet transform is used to perform image multiscale analysis for the images in video, and the images are decomposed into frequency domain response subbands with more compact spatial support along radial and circumferential directions; Secondly, combined with the O’Shea optimization strategy, the double filter algorithm is used to estimate and optimize the spatial frequency; Again, the time domain displacement signals are calculated using the phase difference and the estimated spatial frequency; Finally, the rotor system is tested for dynamic response displacement extraction under constant and rise speed, and the results of this method are compared with the results of eddy current sensors and existing methods in the time and frequency domains, which verifies the accuracy of the proposed method.

Key words: visual vibratory, multiscale decomposition, general curvelet transform, double filtering, rotating machinery

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