Journal of Yangtze River Scientific Research Institute ›› 2023, Vol. 40 ›› Issue (6): 160-165.DOI: 10.11988/ckyyb.20220110

• Engineering Safety and Disaster Prevention • Previous Articles     Next Articles

Auxiliary Water Level Measurement During Automatic Dam Safety Monitoring with Robotic Total Station

ZHOU Jian-guo1, PENG Duo1, JIANG Wei-guo2, LI Jian-zhou3   

  1. 1. School of Civil Engineering, Architecture and Environment, Hubei University of Technology, Wuhan 430068, China;
    2. Hunan Wuling Power Technology Co., Ltd., Changsha 410004, China;
    3. Engineering Safety and Disaster Prevention Department, Changjiang River Scientific Research Institute, Wuhan 430010, China
  • Received:2022-02-11 Revised:2022-04-12 Published:2023-06-01 Online:2023-06-21

Abstract: The water level of reservoir is a crucial element of dam safety monitoring. This paper presents a method to assist in water level measurement using a robotic total station during its displacement monitoring tasks. Initially, the telescope of the robotic total station is precisely aimed at the water level line, and the elevation of water level is calculated using trigonometric leveling principles. Simultaneously, the initial equation for the water level line is manually obtained by capturing a picture with the coaxial camera. During the periodic monitoring stage, the vertical angle of the telescope is adjusted to capture images of the water level line based on the predicted results from the Kalman filter. Subsequently, a series of image processing techniques are employed to extract the water level line from the picture considering the initial slope of the water level line. Adjustments are made to ensure that the captured image is centered on the water level line, and the elevation of the water level line is calculated. The test results demonstrate that this method has a certain engineering application prospect, and is helpful to expand the use of robotic total station in dam safety monitoring.

Key words: dam safety monitoring, water level measurement, robotic total station, image processing, Kalman filter

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