Vibration measurement of a rotating cylindrical structure using subpixel-based edge detection and edge tracking. (1st March 2022) - Javed, Aisha; Lee, Hyeongill; Kim, Byeongil; Han, Youkyung
Highlights: Vibration measurement of a rotating cylindrical structure using video is presented. Proposed method consists of frame magnification, edge detection, and edge tracking. Proposed method is verified through experiments on simulation and real datasets. The performance of the approach is acceptable compared by reference data. Vibrations of both single and multiple frequencies can be measured by our method. Abstract: Acceleration sensors are commonly used for measuring the vibrations of structures. However, these contact-type sensors cannot be installed in some areas, such as on objects located in hazardous areas. Recently, non-contact-type measurement approaches, including photogrammetry techniques (e.g., point tracking, digital image correlation, and target-less approaches) have been introduced using images obtained from cameras. Nevertheless, photogrammetric approaches, e.g., point tracking and digital image correlation, have the same problem because targets or high-contrast speckle patterns need to be mounted on structures. Instead, the target-less approaches for vibration measurement were developed and tested on static structures like bridges and other civil structures. However, analysts have rarely focused on the rotating axis of cylindrical structures, which is a general component of the rotation-based renewable power generation system. Therefore, in this paper, we introduced a subpixel-based vibration measurement method for a cylindrical rotating structure based on the video images acquired from a non-contact sensor. The frames were magnified, and subpixel-based edges were detected in each frame of the video. Then, using the proposed edge tracking technique, the coordinates of the edges in a region of interest were tracked throughout the video for measuring the vibrations. The proposed edge tracking technique keeps the track of the edge locations in the previous frame as well as the locations in the pixels of the current frame. To show the effectiveness of the proposed method, two simulation datasets and one real dataset were constructed. For the simulation datasets, we generated videos by adding sinusoidal noises together with random noise in an image that contains a static cylindrical object. For the real dataset, a video of a rotating cylindrical object was acquired. The results obtained using the proposed method were compared with the results obtained using the existing multi-interval second-order differential edge detection technique and partial area-based technique. From the simulation datasets, vibrations related to both the single and multiple frequencies were effectively detected by applying the proposed method. The proposed method had the lowest root mean square error (RMSE) calculated with the reference data compared to the existing methods. In the real dataset, we could demonstrate that the proposed method could effectively detect the vibrations on the rotating axis of a cylindrical structure with the exact locations of the edges while removing the non-interest edges or false edges. Moreover, during the frequency analysis, the peaks of the proposed method results were at the same frequency at which the object was rotating. Therefore, the proposed method can be a useful solution to detect the vibration of rotating structures located in hazardous areas with uneven backgrounds and uneven brightness.