High-Precision Measuring System for Internal Deformation Monitoring Pipeline of Rockfill Dams: Design and Validation

Yin, Yu; Chen, Zhipeng; Li, Qingquan; Zhang, Dejin; Liang, Anbang; Lv, Shiwang

doi:10.1109/jsen.2023.3265023

Cited by 5 publications

(1 citation statement)

References 18 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In recent years, some scholars have utilized flexible small-caliber pipelines to conduct research on deformation detection and safe operation and maintenance of large-scale infrastructures, such as the measurement of settlement deformation inside dams. Li et al [5][6][7] buried flexible pipes in the horizontal plane inside the dam, and measured the shape change of the flexible pipes by PMR (Figure 1) with an integrated odometer, so as to obtain the vertical and horizontal deformation inside the dam. Unlike general urban underground pipelines and energy pipelines, where the measurement accuracy is about 0.2% to 0.03% of the length of the pipeline, the measurement accuracy of the pipeline for monitoring the internal deformation of the dam is much higher, and the accuracy of the pipeline for a length of 100 meters needs to reach the millimeter level, i.e., no more than 0.01% of the length of the pipeline.…”

Section: Introductionmentioning

confidence: 99%

Pipeline inertial measurement mileage correction method based on pipeline junction detection

Chen,

Wang,

Chen

et al. 2024

J. Phys.: Conf. Ser.

View full text Add to dashboard Cite

A pipeline measurement robot(PMR) is an important tool for pipeline shape measurement and disease detection. Flexible pipelines in the horizontal plane inside dams are used for internal deformation monitoring, which is characterized by small caliber, no ground marking assistance, and higher accuracy requirements, so the accuracy of the data fusion algorithm needs to be improved. In this paper, we propose a pipeline inertial measurement odometry correction method based on pipeline junction detection, which establishes a reference model of pipeline junction locations, detects pipeline junction gap locations along the measurement route using k-mean clustering, corrects odometer data based on the difference between the detected and reference locations, fuses IMU and odometer data and evaluates the internal compliance accuracy. The proposed method is validated using the measured data of the internal pipeline of Tianchi Dam, and the results show that the method proposed in this paper reduces the root-mean-square error (RMSE) by about 46% compared with the results without detection correction and direct fusion. Therefore, the method has good results and practical applications.

show abstract

Section: Introductionmentioning

confidence: 99%