# A Review of Detection Technologies for Underwater Cracks on Concrete Dam Surfaces
## 5 Summary and Conclusions

Table 2: Recognition methods and results for underwater crack images. vibration methods, electromagnetic methods, temperature tracing methods, and digital image detection methods have been studied for dam underwater crack detection. However, due to the large volume, the large detection area, and the high installation cost of the sensor of the underwater structure of the dam, acoustic and vibration methods, electromagnetic methods, and temperature tracing methods have great limitations and high detection difficulties, which are difficult to apply to the actual underwater crack detection of the dam. An underwater robot combined with the digital image detection method can conduct a comprehensive detection of the underwater dam surface through advanced photography and sonar technology, which greatly reduces the difficulty and cost of underwater crack detection and is more suitable for large-scale underwater dam surface detection. This paper summarizes and reviews the existing methods for underwater crack detection on dam surfaces, and emphatically introduces the underwater robot-based method for image data acquisition and the underwater crack detection method based on digital image processing techniques, aiming to provide a way for researchers to quickly and deeply understand the underwater crack detection on dam surface. Although image acquisition methods based on underwater robots and underwater crack detection methods based on digital image processing techniques have greatly increased the efficiency of crack detection and reduced the work risk, there are also many factors that can adversely affect the results of underwater crack detection. Based on these, this paper discusses the main future research directions from the perspective of image acquisition and image processing, combined with the key challenges faced by underwater crack detection:  
(1) The underwater environment near the dam is complex, and the underwater steel bars and rocks will restrict the operation of the underwater robot. In addition, due to the professionalism of detection requirements, it is necessary to carry out targeted research of underwater robots in combination with actual needs in future work to improve the portability and professionalism of the equipment. (2) The existing above-water crack detection methods cannot be directly applied to underwater detection due to the specificities of the underwater environment. Preprocessing can enhance the quality of underwater images and achieve better detection results in specific situations, but is not universal. Traditional algorithms and deep learning algorithms cannot be widely used in engineering due to their own limitations. The image detection method of underwater cracks is the key technology for identifying underwater cracks on the dam surface. The technical problems that need to be solved in practical applications mainly include low crack detection efficiency, poor real-time recognition, and few quantitative methods. In follow-up study, the following work can be carried out: (a) the characteristics of optical images and sonar images can be combined to achieve the precise location of cracks; (b) the images of underwater cracks on dam surfaces should be collected to establish an image dataset of underwater dam cracks, which is necessary for training an underwater crack intelligent detection neural network; (c) more advanced algorithms are needed to improve the speed and efficiency of crack detection; (d) it is also important to develop a quantitative method of underwater cracks to establish a systematic analysis system of underwater dam cracks. D.C.: conceptualization, methodology, investigation, writing--original draft. B.H. : conceptualization, methodology, investigation, writing--original draft. F.K. : funding acquisition, writing--review and editing. All authors have read and agreed to the published version of the manuscript.