Application of image-based flow measurement technology in drainage ditches of high-arch dam galleries

Abstract

[Objective] Image-based flow measurement is an effective non-contact method for discharge measurement, which has been widely used in open channels and natural rivers. However, its applicability in confined and complex environments such as the drainage ditches of high-arch dam galleries has not been fully validated. The aim is to systematically evaluate the performance of this technology in this specific scenario. [Methods] Validation was conducted using a combination of model tests and field tests. Camera calibration was performed by placing control points. In the model tests, three camera perspectives(upstream, downstream, and lateral) were tested while controlling discharge variations. Water levels were obtained using a monocular vision-based method without a staff gauge, and surface flow fields were calculated using the particle image velocimetry(PIV) technique. Comparisons were made between conditions with and without tracer particles, as well as before and after image preprocessing. Field tests were conducted in a real gallery drainage ditch. Measurements from staff gauges and a measuring weir were used as benchmarks to validate the engineering applicability of this technology. [Results] The result showed that in the model tests, the relative errors of the image-based water level recognition method were all below 7%. Under conditions with tracer particles, the flow measurement errors across different camera perspectives were all less than 4%. The accuracy of the flow measurement result from the lateral perspective was lower than that from the upstream and downstream perspectives. The flow calculation error increased with the increase of discharge, rising from 5.77% at a low discharge(21.40 m³/h) to 35.17% at a high discharge(65.10 m³/h). After image preprocessing, the errors could be reduced to the range of 3.60%~28.74%. In the field tests, the water level measurement error was 0.78%. Under conditions with tracer particles and under conditions without tracer particles but with image preprocessing, the relative errors of discharge calculation reached 1.17% and 1.81%, respectively. [Conclusion] The result show that image-based flow measurement technology is suitable for discharge monitoring in the drainage ditches of high-arch dam galleries, and the upstream and downstream perspectives are the optimal camera perspectives. Under conditions with natural or artificial tracers, this technology can achieve high measurement accuracy. Image preprocessing can enhance the flow measurement performance, while an increase in discharge can reduce the algorithm's ability to identify flow field features, thereby decreasing the accuracy of image-based flow measurement. By analyzing the application of image-based flow measurement technology in both model and field settings, it is confirmed that this technology has good potential for application in the drainage ditches of high-arch dam galleries and is expected to provide a valuable reference for algorithm optimization and broader application.

Keywords

image-based flow measurement / water level recognition / gallery drainage ditches / high-arch dam / applicability / discharge / tracer particles / relative error