Underwater survey system of dam embankment by remotely operated vehicle

Sugimoto, Hideki; Moriya, Yoichi; Ogasawara, Toshio

doi:10.1109/ut.2017.7890298

Cited by 11 publications

(6 citation statements)

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“…Given this background, Japan's Ministry of Land, Infrastructure, Transport and Tourism has played an important role in leading the development of inspection systems and robots for infrastructure, including dams, in recent years. Several researchers have developed underwater robotic systems for dam inspection (Shimono et al, ; Sugimoto et al, ).…”

Section: Outline Of the Proposed Methodsmentioning

confidence: 99%

“…In addition to visual inspection, it might be possible for AUVs to perform underwater tasks that require physical contact and which generate a reaction force to AUVs. For instance, AUVs might be able to work using tools such as wall thickness gauges, sounding hammers, and cleaning brushes as ROVs (Shimono et al, 2015) (Shimono et al, 2015(Shimono et al, , 2016Sugimoto et al, 2017).…”

Section: Applications For Autonomous Underwater Vehicles and Remotementioning

confidence: 99%

“…The ROV has two arms to maintain its relative position with respect to the dam surface. For dam inspection, one company (Sugimoto, Moriya, & Ogasawara, ) developed an ROV with rods having adjustable length according to the inclination of the dam surface. The ROV uses the GNSS and several sensors to estimate the relative position between the ROV and the dam wall surface.…”

Section: Introductionmentioning

confidence: 99%

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Development of dam inspection robot with negative pressure effect plate

Sakagami

Yumoto²,

Takebayashi

et al. 2019

Journal of Field Robotics

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This paper describes the development of an underwater robot that performs visual inspection while making mechanical contact with a dam surface by a pulling force generated from thrusters with negative pressure effect plates. In general, small and lightweight remotely operated vehicles (ROVs) have low‐power thrusters. Their positioning performance is inferior with respect to external disturbances. Moreover, it is difficult for untrained operators to control the ROV position to check and inspect dams visually. A negative pressure effect plate attached to a thruster produces negative pressure that maintains mechanical contact between the robot and a dam wall surface and ensures stable robot motion on a dam surface to acquire clear continuous images. As described herein, we theoretically investigate the negative pressure effect plate characteristics and experimentally measure the force generated by the pressure difference. Results show that the force of a thruster with the effect plate is five times greater than the nominal thrust force provided by the thruster alone. Based on those results, we designed and developed the underwater robot with the negative pressure effect plates for dam inspection. Moreover, we conducted an experiment in a water tank and a field test at Shorenji Dam, Mie‐prefecture, Japan. The experimentally obtained results indicated that the negative pressure effective plate is effective at generating sufficient force and at realizing stable robot motion on the dam surface. Results demonstrate that the developed robot acquired clear images of the dam surface continuously with no sophisticated operator or controller.

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Section: Outline Of the Proposed Methodsmentioning

confidence: 99%

Section: Applications For Autonomous Underwater Vehicles and Remotementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development of dam inspection robot with negative pressure effect plate

Sakagami

Yumoto²,

Takebayashi

et al. 2019

Journal of Field Robotics

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“…For example, Varughese et al 20 applied ROV as post-construction instrumentation to detect and locate the sources and causes of dam underwater structural defects like seepage, cracks, and corrosion. Sugimoto et al 21 proposed an underwater survey system based on ROV inspection technologies, and then a field verification test was carried out on a dam embankment. Note that one complete underwater inspection task will generate massive image and video data.…”

Section: Introductionmentioning

confidence: 99%

An integrated underwater structural multi-defects automatic identification and quantification framework for hydraulic tunnel via machine vision and deep learning

Bao

Huang

et al. 2022

Structural Health Monitoring

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Underwater structural defects in hydraulic tunnels are highly concealed and difficult to be identified by conventional manual methods. Remotely operated vehicle combined with visible light cameras can provide a noncontact and high spatial resolution damage detection solution. However, manually extracting useful structural damage-related information from massive data is time-consuming and involves high labor cost. This article proposes an integrated pixel-level underwater structural multi-defects instance segmentation and quantification framework for hydraulic tunnels via machine vision and deep learning. Firstly, a tunnel lining underwater structural multi-defects video dataset is developed. Next, an improved You Only Look At CoefficienTs for Edge devices is used to build the detector by exploiting temporal redundancy in videos. Three backbone detectors are used to trade off the balance between detection accuracy and efficiency, and a cross-domain transfer learning strategy is introduced to reduce model training costs and data dependencies. Various complicated tunnel underwater inspection scenarios, including uneven illumination, tilt shooting, high brightness, and motion blur scenarios, are used to evaluate model generalization capability. Experimental results show that ResNet50-based YolactEdge can well trade off the balance between accuracy and speed, which achieves 92.47 bbox mAP, 92.15 mask mAP, and 39.27 FPS in the testing set. A quantification evaluation method is proposed to quantify the detection results and extract the geometric features of structural defects based on digital image processing techniques. The proposed method can accurately identify the number, size, and area of tunnel underwater structural defects, providing data support for subsequent reinforcement.

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“…TriMARES [10] is a hybrid vehicle which can be programmed for AUV or operated as an ROV for the inspection of dam in Brazil. is ROV system which consists of a measuring camera, a cleaning brush, a wall thickness gauge, and a sounding hammer was used to inspect the dam wall surface and the gate equipment [11]. MASKI, which is the latest generation ROV designed by Hydro-Québec, was used to inspect concrete walls, metallic structures, and riverbeds in Quebec [12].…”

Section: Introductionmentioning

confidence: 99%

Image‐Based Underwater Inspection System for Abrasion of Stilling Basin Slabs of Dam

Zhang

Wang

et al. 2019

Advances in Civil Engineering

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The abrasion of stilling basin slabs which is caused by waterborne particles is one of the main surface damages in the operation of hydropower station. For determining whether to repair the stilling basin slabs, periodic inspections of erosion condition of stilling basin slabs are required. The practical problem is how to get the underwater image without unwatering and how to analyse the abrasion though the images. This paper developed a novel underwater inspection system named UIS-1 which consists of a customized underwater robot and special quantitative analysis method for this situation. Firstly, the integrated component was designed for the underwater robot that partially removes the siltation and obtains the image of the concrete surface of stilling basin slabs in the desired position. Secondly, the paper proposed an image algorithm to obtain aggregate exposure ratio for quantitative abrasion analysis. This image algorithm used SLIC superpixel and the SVM machine learning method to detect the coarse aggregate exposure automatically. Then, the aggregate exposure ratio was calculated to analyse the degree of abrasion. Finally, the UIS-1 system was evaluated in the field experiments of a dam in Sichuan, China, and its performance was discussed by comparison.

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Underwater survey system of dam embankment by remotely operated vehicle

Cited by 11 publications

References 0 publications

Development of dam inspection robot with negative pressure effect plate

Development of dam inspection robot with negative pressure effect plate

An integrated underwater structural multi-defects automatic identification and quantification framework for hydraulic tunnel via machine vision and deep learning

Image‐Based Underwater Inspection System for Abrasion of Stilling Basin Slabs of Dam

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