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Protective effect of retaining wall on rock avalanche:A case study of Nayong rock avalanche in China

Journal of Mountain Science 2024年第4期21卷 1215-1230页

作者： WANG Zhongfu SHI Fengge HE Siming ZHANG Xusheng WANG Jingying LIU Enlong North China University of Water Resources and Electric Power Zhengzhou 450046China Hunan Provincial key Laboratory of key Technology on Hydropower Development Changsha 410014China Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu 610041China College of Water Resource and Hydropower Sichuan UniversityChengdu 610065China

Rock avalanches are generally difficult to prevent and control due to their high velocities and the extensive destruction they ***,barrier structures constructed along the path of a rock avalanche can partially mitigate the magnitudes and consequences of such catastrophic *** selected a rock avalanche in Nayong County,Guizhou Province,China as a case to study the effect of the location and height of a retaining wall on the dynamic characteristics of rock avalanche by using both actual terrain-based laboratory-model tests and coupled PFC3D-FLAC3D numerical *** findings demonstrate that a retaining wall can largely block a rock avalanche and its protective efficacy is significantly influenced by the integrity of the retaining *** numerical simulation can serve as a powerful tool for analyzing the interaction between a rock avalanche and a retaining wall,facilitating precise observations of its deformation and *** impact-curve characteristics of the retaining wall depend upon whether or not the rock avalanche-induced destruction is taken into *** location of the retaining wall exerts a greater influence on the outcome compared to the height and materials of the retaining wall,while implementing a stepped retaining-wall pattern in accordance with the terrain demonstrates optimal efficacy in controlling rock avalanche.

关键词： Rock avalanche laboratory model test Retaining wall PFC^(3D) FLAC^(3D) Impact force

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Multi-station Water Quality Prediction Considering Temporal and Spatial Correlation: Based On T-GCN 23

Multi-station Water Quality Prediction Considering Temporal ...

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2023 Intelligent Sensing and Industrial Automation, ISIA 2023

作者： Liu, Hao Li, Dexin Liu, Chengzhao Fang, Bo He, Wei Powerchina Zhongnan Engineering Corporation Limited China Hunan Provincial Key Laboratory of Hydropower Development Key Technology China

ISBN: (纸本)9798400709401

The water quality monitoring data reflects the ecological environment of the river and its changing trend. The accurate analysis and prediction of water quality is of great significance to improve the efficiency of river management and maintenance, ensure the safety and stability of the ecological environment of the river basin. The traditional water quality prediction model combines hydrodynamic theory and water quality change process mechanism, which can represent the overall change trend of water quality. However, this method is mostly aimed at a fixed watershed, with poor portability ability and difficult to accurately predict key areas. Although some new mathematical statistical methods and machine learning methods can achieve high accuracy in the prediction of water quality data from a single station, the spatial correlation characteristics between multiple stations are ignored in the comprehensive water quality prediction of the basin, resulting in a decline in accuracy. In this paper, based on the spatial distribution and graph structure characteristics of multiple water quality monitoring stations in the basin, the temporal graph convolutional neural network is used to analyse the time series characteristics of water quality, and realize the prediction of water quality data from multiple monitoring stations. The analysis of water quality monitoring data of a river located in the Guangdong Province of China proves that, compared with the commonly used model LSTM, the T-GCN model can better fit the spatial correlation characteristics and time series characteristics of water quality monitoring data, and achieve a more accurate water quality predictive analysis. Based on the water quality monitoring data of multiple stations, T-GCN model can reflect the changing trend of water quality in the entire basin, and accurately predict the water quality changing in specific locations. The research results can provide a more accurate and effective reference for river op

关键词： Water quality

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Assisting Wind Turbine Hoisting with Yolov7 and Object Tracking technology 5

Assisting Wind Turbine Hoisting with Yolov7 and Object Track...

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5th International Conference on Internet of Things, Automation and Artificial Intelligence, IoTAAI 2023

作者： Ma, Chenzhe Fang, Bo Liu, Hao Li, Shun Ma, Minmin Powerchina Zhongnan Engineering Corporation Limited Changsha410014 China Hunan Provincial Key Laboratory of Hydropower Development Key Technology Changsha410014 China

ISBN: (纸本)9798400716485

In the process of hoisting wind turbines, the driver of the crane cannot observe the panoramic view of the components being hoisted and is completely dependent on the scheduling of the commander, which restricts the efficiency and safety of hoisting. We propose an assisted hoisting algorithm for wind turbines. A high-definition camera is installed at the hoisting site to capture the hoisting scene in real time, and then Yolov7/ Yolov7-tiny is used to detect the object being hoisted in the frame. The box of the object is used as the input of the Deepsort algorithm to track the hoisting object in real time. Finally, the tracking information is used to adjust the angles of the pan and tilt and the focal length of the camera to provide the crane driver with a clear hoisting panorama. Experiments and engineering applications show that the mAP of Yolov7 reaches 0.88(Yolov7-tiny reaches 0.81), and the real-time tracking speed exceeds 12 FPS, which meets the requirements of use. © 2023 ACM.

关键词： Wind turbines

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Comparison of Pile-Soil-Structure Interaction Modeling Techniques for A 10-MW Large-Scale Monopile Wind Turbine Model Under Wind and Wave Conditions

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China Ocean Engineering 2023年第3期37卷 471-483页

作者： ZENG Yu-xin ZHANG Xiao-ming ZHANG Li-xian SHI Wei WANG Wen-hua LI Xin Hunan Provincial Key Laboratory of Key Technology on Hydropower Development Changsha 410014China PowerChina Zhongnan Engineering Corporation Limited Changsha 410021China State Key Laboratory of Coastal and Offshore Engineering Dalian University of TechnologyDalian 116024China DeepWater Engineering Research Centre Dalian University of TechnologyDalian 116024China Institute for Earthquake Engineering Faculty of Infrastructure EngineeringDalian University of TechnologyDalian 116024China

Considering the large diameter effect of piles,the influence of different pile-soil analysis methods on the design of monopile foundations for offshore wind turbines has become an urgent problem to be *** different pile-soil models were used to study a large 10 MW monopile wind *** modeling the three models in the SACS software,this paper analyzed the motion response of the overall structure under the conditions of wind and *** to the given working conditions,this paper concludes that under the condition of independent wind,the average value of the tower top x-displacement of the rigid connection method is the smalle st,and the standard deviation is the smallest under the condition of independent *** results obtained by the p-y curve method are the most conservative.

关键词： large-scale monopile offshore wind turbine pile-soil model wind-wave load combination

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Intelligent Detection technology for Deformation Rate of Underground Drainage Pipeline Network Based On Deep Learning 23

Intelligent Detection Technology for Deformation Rate of Und...

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2023 Intelligent Sensing and Industrial Automation, ISIA 2023

作者： Liu, Hao Liu, Chengzhao Li, Dexin Ma, Chenzhe Jiang, Mengke Powerchina Zhongnan Engineering Corporation Limited Changsha410014 China Hunan Provincial Key Laboratory of Hydropower Development Key Technology Changsha410014 China

ISBN: (纸本)9798400709401

In order to capture the underground drainage network's shadowy environment, poor-quality photos are often captured. These images typically include little information, have low conventional pipe deformation rate detection accuracy, and have significant 3D modeling constraints. Picture quality and resolution may be greatly enhanced by using the resolution reconstruction and three-dimensional fast modeling techniques. In addition, the recognition effect can ensure the current state of the project, and the speed with which it can determine the deformation rate of pipes at every level. A guarantee for the construction control of pipeline deformation and safe operation is provided by this result, which may be applied to comparable projects. © 2023 ACM.

关键词： 3D modeling

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Research on Small Target Detection technology for River Floating Garbage Based on Improved YOLOv7 23

Research on Small Target Detection Technology for River Floa...

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2023 Intelligent Sensing and Industrial Automation, ISIA 2023

作者： Li, Dexin Liu, Hao Yang, Yingying Fan, Zhixuan Wu, Biquan PowerChina Zhongnan Engineering Corporation Limited China and Hunan Province Key Laboratory of Hydropower Development Key Technology China

ISBN: (纸本)9798400709401

Traditional manual inspection of floating garbage in artificial river channels is time-consuming and labor-intensive. Unmanned aerial vehicles (UAVs) and unmanned boats based on computer vision have become the main methods for river channel inspection. In this paper, a dataset of floating garbage in the study area's river channels was constructed based on UAV aerial images. Deep learning methods were employed for garbage classification and recognition. Considering the relatively small proportion of floating garbage in UAV images and the susceptibility to water mist and vapor interference, targeted improvements were made to the YOLOv7 object detection algorithm in terms of multi-scale detection. Experimental results verified that the improved algorithm, compared to the original algorithm, achieved higher detection accuracy for small targets and effectively mitigated water mist interference, with an increase of 2.24% in mean average precision (mAP) for class-balanced accuracy. The study results demonstrate that the integration of deep learning methods and UAV technology enables efficient and accurate identification and classification of garbage, providing decision-making support for the management of floating garbage in river channels. © 2023 ACM.

关键词： Drones

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Pixel-level crack segmentation of tunnel lining segments based on an encoder–decoder network

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Frontiers of Structural and Civil Engineering 2024年第5期18卷 681-698页

作者： Shaokang HOU Zhigang OU Yuequn HUANG Yaoru LIU State Key Laboratory of Hydroscience and Engineering Tsinghua UniversityBeijing 100084China China Renewable Energy Engineering Institute Beijing 100120China State Key Laboratory of Stimulation and Regulation of Water Cycles in River Basins China Institute of Water Resources and Hydropower ResearchBeijing 100038China Hunan Provincial Water Resources Development&Investment Co. Ltd.Changsha 410007China

Regular detection and repair for lining cracks are necessary to guarantee the safety and stability of *** development of computer vision has greatly promoted structural health *** study proposes a novel encoder–decoder structure,CrackRecNet,for semantic segmentation of lining segment cracks by integrating improved VGG-19 into the U-Net *** image acquisition equipment is designed based on a camera,3-dimensional printing(3DP)bracket and two laser rangefinders.A tunnel concrete structure crack(TCSC)image data set,containing images collected from a double-shield tunnel boring machines(TBM)tunnel in China,was *** data preprocessing operations,such as brightness adjustment,pixel resolution adjustment,flipping,splitting and annotation,2880 image samples with pixel resolution of 448×448 were *** model was implemented by Pytorch in PyCharm processed with 4 NVIDIA TITAN V *** the experiments,the proposed CrackRecNet showed better prediction performance than U-Net,TernausNet,and *** paper also discusses GPU parallel acceleration effect and the crack maximum width quantification.

关键词： tunnel lining segment crack detection semantic segmentation convolutional neural network encoder-decoder structure

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Detection of fan blade defects by visible light and thermal infrared image fusion 6

Detection of fan blade defects by visible light and thermal ...

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6th International Conference on Algorithms, Computing and Artificial Intelligence, ACAI 2023

作者： Ma, Minmin Liu, Hao Tan, Kecheng Gao, Yuxin Huang, Siyang PowerChina Zhongnan Engineering Corporation Limited Changsha410019 China Hunan Province Key Laboratory of Hydropower Development Key Technology Changsha410019 China

ISBN: (纸本)9798400709203

With the increasing proportion of wind energy in energy utilization, fan blade defects detection has become one of the important topics. At present, traditional object detection methods usually use visible light images and can only detect surface defects of fan blades, which cannot detect whether there are defects in the shallow interior of fan blades. In this paper, the defects of fan blades are detected by fusing visible light image and thermal infrared image information. We use a target detection model to detect defects in visible light and thermal infrared images of fan blades. Then fuse visible light and thermal infrared images using a self-attention based image fusion method. Finally, based on the image fusion results and detection decision strategies, the defect detection of fan blades is completed. The experimental results show that the method proposed in this paper achieves an accuracy of 94% for detecting defects in fan blades, and can detect a total of 8 types of internal and external defects in fan blades. The detection method in this article achieves cross validation of the detection results of fan blade defects, realizes the detection of shallow defects inside fan blades, improves the detection accuracy of fan blade faults, and can provide early warning for internal defects of fan blades, remind workers to repair them in a timely manner, and prevent further expansion of defects. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： Energy utilization

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Fully Autonomous Inspection of Wind Turbine Blades Based on Drones and Artificial Intelligence 23

Fully Autonomous Inspection of Wind Turbine Blades Based on ...

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2023 Intelligent Sensing and Industrial Automation, ISIA 2023

作者： Ma, Minmin Liu, Hao Gao, Yuxin Li, Shun Ma, Chenzhe Hu, Daiming Power China Zhongnan Engineering Corporation Limited Changsha410019 China Hunan Province Key Laboratory of Hydropower Development Key Technology Changsha410019 China

ISBN: (纸本)9798400709401

The traditional manual inspection of fan blades is labor-intensive, time-consuming, and subjective, making it impossible to detect internal defects in the blades. Based on artificial intelligence technology and deep learning algorithm, the UAV carries edge computing terminals, high-definition cameras, thermal imagers and other equipment to study the UAV autonomous flight control algorithm and the dual light fusion multi type back mixed defect detection and positioning algorithm, and realizes the fast, efficient and intelligent detection of the internal and external defects of the fan blades in 15-30 minutes. The fully autonomous inspection of wind turbine blades based on drones and artificial intelligence can make up for the shortcomings of traditional methods, greatly improve inspection efficiency, and reduce potential safety accidents in wind farms. © 2023 ACM.

关键词： Drones

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Finite volume method-based numerical simulation method for hydraulic fracture initiation in rock around a perforation

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2023年第1期24卷 56-63页

作者： Yu ZHANG Shaohao HOU Songhua MEI Yanan ZHAO Dayong LI College of Pipeline and Civil Engineering China University of Petroleum(East China)Qingdao 266580China Hunan Provincial Key Laboratory of Key Technology on Hydropower Development Zhongnan Engineering CorporationChangsha 410014China

1 Introduction Hydraulic fracturing is a technique for increasing permeability in oil and gas resource development,grouting reinforcement in mine management,and geostress *** the purpose of enhancing hydraulic fracturing in horizontal wells,oriented perforating methods have been developed(Kurdi,2018;Michael and Gupta,2020a;Yan et al.,2020).Fluid is injected into the rock through perforations,which increases fluid pressure within rock and decreases rock ***,the rock around the perforation is ***,fracture initiation pressure is intimately connected to the reservoir’s physical and mechanical properties,geo-stress,and temperature(Morgan and Aral,2015).

关键词： fracture rock method

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