Table of Content

25 June 2025, Volume 45 Issue 3

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Expert Column: Development and Application of New Energy Technology

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Performance Study and Optimization Design of Manifold Microchannel Heat Sink With Rectangular Ribs

LiU Yiwen, CUi Pan, LiU Wei, LiU Zhichun, CUi Haichuan

2025, 45(3):  1-8.  doi:10.3969/j.issn.1008-0198.2025.03.001

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To enhance the comprehensive performance of the manifold microchannel heat sink (MMCHS), a new manifold microchannel heat sink with rectangular ribs (MMCHS-RR) is proposed. Firstly, the three-dimensional numerical simulations are employed to investigate the effects of the arrangement of rectangular ribs, microchannel width, microchannel height, and the ratio of rectangular rib width to microchannel width on the thermal-hydraulic performance. Then the artificial neural network and a multi-objective genetic algorithm are used to optimize the structural parameters. Finally, the TOPSIS decision-making algorithm is applied to select the parameter combination with the best comprehensive performance from the Pareto front. After optimization, compared with the initial heat sink, the maximum temperature on the heated surface is reduced by 6.4 K, the average heat transfer coefficient is increased by 46.3%, and the total pressure drop is reduced by 1.85 kPa at an inlet flow rate of 6 m/s. The research results indicate that the heat sink with rectangular ribs arranged to bypass the jet holes of the inlet manifold and the outflow holes of the outlet manifold exhibits superior comprehensive performance.

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Research on Distribution Network Topology Reconfiguration Method Considering New Energy Consumption and Voltage Deviation

WANG Xuanyuan, Li Qi, WANG Zesen, LiU Jiantao, SUN Zhibo

2025, 45(3):  9-17.  doi:10.3969/j.issn.1008-0198.2025.03.002

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Aiming at the impact of new energy consumption on distribution operation, a distribution network topology reconfiguration method considering both new energy consumption and voltage deviation is proposed to realize the balance and coordination between the two. Firstly, a scenario reduction technique based on scenario similarity is used to obtain representative new energy power samples. Then, a multi-objective stochastic optimization reconfiguration mathematical model is established to optimize the amount of new energy consumption and the voltage deviation at distribution network nodes. Subsequently, a multi-objective particle swarm algorithm guided by a proximal strategy optimization algorithm is employed to efficiently search for the corresponding Pareto solution set. Finally, the technique for order of preference by similarity to ideal solution decision method is applied to balance the trade-off between wind power consumption and voltage deviation and select the final reconfiguration scheme. The improved IEEE-33 node distribution network is used as the test object, and the experimental results verify the effectiveness of the proposed method.

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Capacity Configuration and Operation Optimization of Cascade Hydropower Combined Energy Storage System Considering New Energy Consumption

TiAN Haiping, MO Jian, TAN Xincong, XU Runyi, CHEN Yanqi, ZHANG Ji, HUANG Sheng

2025, 45(3):  18-26.  doi:10.3969/j.issn.1008-0198.2025.03.003

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With the increasing proportion of renewable energy in the power system, the introduction of pumped storage and electrochemical energy storage in the cascade hydropower station can effectively improve the wind and solar energy consumption. A combined wind power-photovoltaic-terrace hybrid pumped storage-electrochemical energy storage system is constructed. Firstly, the economic optimization is taken as the goal to make the optimal capacity configuration of the grid-connected combined system and the operation of each equipment is analyzed. Secondly, the impact of different wind and solar proportions on the optimal capacity configuration of the system is analyzed. Finally, the change of optimal capacity configuration of the off-grid combined system with different wind and solar proportions compared with the grid-connected combined system is analyzed. The results show that, as the proportion of wind and solar power increases, wind and solar power gradually takes up the main load demand, while the turbine capacity of the cascade hybrid pumped storage plant decreases, and the capacity of the electrochemical energy storage increases rapidly to meet the system demand for energy storage equipment. Compared to off-grid systems, grid-connected combined systems are more flexible with both power supply independence.

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Optimal Dispatch of Collaborative Peak Adjustment Between Pumped Storage Power Station and Downstream Hydropower Station

WANG Hui, WANG Zhengwei, CHEN Heng, FAN Lanxin, DONG Changqing, LEi Jing

2025, 45(3):  27-34.  doi:10.3969/j.issn.1008-0198.2025.03.004

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Aiming at the problems of the difficulty to fulfill the power generation task due to low water levels and insufficient water volume in dry water season, and unstable power generation due to high water levels, excessive water volume and excessive water abandonment in abundant water season, a model of a hydroelectric complementary power generation system with joint operation of a hydropower station and pumped storage power station is established, and the original model is transformed into a mixed-integer linear programming model using the stage linear fitting technique. The particle swarm optimization algorithm is used to calculate the downstream hydropower station's peak adjustment and valley filling mechanism by installing a pumped storage power station with an independent reservoir that can store water upstream. The optimal scheduling scheme in the operation cycle is obtained, which significantly improves the stability of hydropower station power generation and solves the problems of excessive water abandonment, unstable power generation, and lower power generation quality of hydropower stations.

Source and Grid Coordination & Conversion and Utilization

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Underwater Detection Technology of Hydraulic Structure With Multi-Equipment Integration

ZHANG Yike, ZHANG Jun, MO Jian, ZHANG Xuewu, ZHANG Zhen

2025, 45(3):  35-41.  doi:10.3969/j.issn.1008-0198.2025.03.005

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To solve the problem of low accuracy of defect detection in the complex underwater dams environment, a defect detection method based on multi-sensor data fusion is proposed. By combining the sonar equipment and optical camera, the sonar data is denoised by Kalman filter, and the optical image contrast is enhanced by the contrast limited adaptive histogram equalization(CLAHE) algorithm. At the same time, the weighted least square method is used to achieve the fusion of the two kinds of data, and the comprehensive image containing the global contours and high-definition details is generated. Then, convolutional neural network(CNN) is used to process the fusion image to realize accurate identification and classification of defects such as cracks and sediments. The experimental results show that the method successfully detected 3 cracks and 2 sediment accumulation areas in the test dam, significantly improving the accuracy and reliability of defect detection.

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Energy Regulation Capability Evaluation Method for Hunan′s Small and Medium Sized Hydropower Stations Based on AHP-CRITIC Fuzzy Comprehensive Evaluation

WEi Jiafu, LiU Huibo, LiU Haoran, DENG Xiaoliang, WANG Pei

2025, 45(3):  42-48.  doi:10.3969/j.issn.1008-0198.2025.03.006

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The constraints on natural resources of small and medium-sized hydropower stations in Hunan Province are characterized by their widespread distribution and inefficient management. To strengthen the unified supervision and enhance regulatory capabilities, a comprehensive evaluation system for energy regulation capacity is constructed. This system takes the reservoir regulation performance and control capabilities as the core criterion, encompassing 14 specific indicators. By combining subjective weighting via the analytic hierarchy process and objective weighting using the critera importance through intercriteria correlation（CRITIC） method, the degree of affiliation for each indicator is calculated to form a comprehensive score for the energy regulation capacity of hydropower stations. An empirical study is conducted on five hydropower stations located in a prefecture-level city within Hunan Province. The evaluation results reveal that two stations reach excellent ratings and three are deemed qualified, which validates the applicability and effectiveness of the evaluation system and can provide quantitative decision support for the refined management of small and medium-sized hydropower stations in Hunan.

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Comprehensive Application of UAV and USV Aerial Survey Technology in High Precision River Section Monitoring

ZHANG Hongqiang, YANG Wenxuan, ZHANG Yike, YiN Zilong, ZHANG Zhen, LiU Huakang

2025, 45(3):  49-53.  doi:10.3969/j.issn.1008-0198.2025.03.007

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For the small hydropower stations in the Xue River basin of Hunan Province, UAV aerial photogrammetry and USV-based underwater topography survey technology are used to accurately collect river channel topography and construct high-precision terrain models. By overlaying and analyzing digital surface models and digital orthophoto maps, the main cross-sections of the principal river are extracted, the issue of mismatched hydrological data is addressed, and the accuracy of the data through post-processing is ensured, so as to provide more reliable data for river management and environmental protection.

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Transient Stability Analysis of Power Systems Based on Extended Equal Area Criterion and Grid Vulnerabilities Identification

WEi Chuanxiang, YANG Lin

2025, 45(3):  54-61.  doi:10.3969/j.issn.1008-0198.2025.03.008

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In order to ensure the safe operation of the power system and accurately assess the transient stability of the power system, a transient stability analysis method integrating vulnerability identification, generator grouping, and the extended equal area criterion (EEAC) is proposed. Firstly, the vulnerabilities in the power system are identified, and the generators are grouped according to the identification results, thereby determining the advanced and lagging generator groups. Then, the EEAC method is used to conduct transient stability analysis and evaluate the impact of different disturbance scenarios on the transient stability of the power system. Through the verification of simulation cases, the results show that the method can effectively judge the transient stability of the power system after being disturbed with high accuracy and reliability and can provide an effective tool for transient stability analysis of power systems.

Power Grid Operation and Control

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Finite Element Analysis of Flexural Stability Bearing Capacity of Cantilever Angle Steel Components in Tunnel Cable Supports

WANG Mingming, WANG Yue, ZHANG Zhiyu, ZHAO Xianghu, GU Wenkao, LiU Wanrong, HU Xuefeng

2025, 45(3):  62-69.  doi:10.3969/j.issn.1008-0198.2025.03.009

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The bending characteristics of angle steel bracket arms for tunnel cable supports exhibit considerable complexity, and improper design and selection can pose serious safety risks to the operation of cable lines. Take a 110 kV cable tunnel project in Jining area as a background, a three-dimensional refined model of the cable angle steel bracket is established using the finite element software ABAQUS, which is utilized to investigate the failure modes and load-displacement curves of cantilever angle steel components subjected to concentrated load. Meanwhile, a series of parameter influence analyses are completed, and design recommendations are provided.

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Research on Equivalent Measurement Method of UHV AC Lines Corona Loss Based on Corona Cage Device

HUO Feng, LiU Siyuan, LiU Qin, YiN Pengbo, Li Yaoqin

2025, 45(3):  70-75.  doi:10.3969/j.issn.1008-0198.2025.03.010

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Research on corona loss in UHV transmission lines holds significant implications for rational control of line losses and enhancement of environmental protection level. In this context, the technical route integrating simulation experiments and theoretical calculations is adopted to study the equivalent measurement method of corona loss of UHV transmission lines based on corona cage test device. Comparative analyses between actual sample measurements and equivalent test results validate the accuracy of corona loss values derived from equivalent methods under both dry and rain-wetting conditions for single conductor and 1 000 kV UHV AC test lines. The findings conclusively demonstrate the validity of corona cage-based equivalent measurement approaches for UHV transmission line corona loss assessment.

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A Denoising Method for Arrester Leakage Current of AC-filter Based on Improved SVD-SVMD

FAN Peipei, MA Xiaowei, Li Teng, LiAO Jun, LU Yixiang

2025, 45(3):  76-83.  doi:10.3969/j.issn.1008-0198.2025.03.011

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Aiming at the problem that the noise of arrester leakage current affects the equipment monitoring work, an improved SVD-SVMD denoising method for AC filter arrester leakage current is proposed. First, the original leakage current data of the arrester undergoes singular value decomposition, during which the differential energy spectrum of singular values is introduced to determine the optimal threshold. The data are then reconstructed based on this optimal threshold to extract the primary harmonic components. Next, the minimum envelope entropy is utilized to optimize the penalty factor for successive variational modal decomposition, which is then applied to decompose the preprocessed data. After the decomposition, the dominant signal components are reconstructed. Finally, an improved wavelet threshold is employed to remove the residual micro-noise, resulting in a denoised leakage current signal of the metal oxide arrester. The effectiveness of the proposed method is validated through simulations and engineering experimental results.

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Research on Detection Method of Detection Sensors for 110 kV XLPE Cables

YU Ting, DUAN Xiaoli, LiU Sanwei, ZHONG Lipeng, Li Shaobin, WANG Feng

2025, 45(3):  84-88.  doi:10.3969/j.issn.1008-0198.2025.03.012

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Aiming at the poor detection effect of traditional partial discharge (hereinafter referred to as PD) of high-voltage XLPE (cross-linked polyethylene) cables, an innovative built-in partial discharge(PD） signal detection device for high-voltage cables is proposed. By improving the structure of cable terminals and intermediate joints, a flange interface is reserved into the tailpipe area of these components for embedding a PD detection antenna, enabling accurate and effective detection of PD signals while avoiding damage to the cable body. With the detection antenna adopting a double-helix structure, precise collection, transmission, analysis, and processing of PD signals ar achieved. Through simulation and testing, the central frequency of the built-in PD detection antenna for 110 kV XLPE high-voltage cables with lengths ranging from 50 to 500 meters is determined to be 20 MHz. Test results demonstrate that the built-in PD detection sensor can effectively detect PD signals.

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Fault Cause Analysis and Hidden Danger Management of Main Circulating Pump for Valve Cooling System in a Flexible DC Converter Station

ZHAO Zhanming, GAO Hongda, TENG Mengfeng, ZHANG Qingyuan, LiU Yang

2025, 45(3):  89-94.  doi:10.3969/j.issn.1008-0198.2025.03.013

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Taking the failure of the main circulating pump in the valve cooling system of a ±500 kV converter station as an example, this paper introduces the failure handling measures, analyzes the failure causes, and concludes that the use of unqualified spring washers for the main circulating pump leads to the failure of the pump shaft fastening connection pair (loosening of the lock nut). Meanwhile, potential hazard inspections are carried out on other in-service main circulating pumps in this station, providing references for the safe operation of main circulating pumps in other in-service converter stations and the selection of main circulating pumps for newly-built converter stations.

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Reactive Power Optimization Method of Photovoltaic Energy Storage Distribution Network Based on Improved Red-Billed Blue Magpie Optimization Algorithm

MA Fanshuo, YU Huijun, Li Jiaxuan, LiU Zeyu, KANG Qinze

2025, 45(3):  95-102.  doi:10.3969/j.issn.1008-0198.2025.03.014

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Aiming at the problems of increased active losses, voltage deviation and uncertainty of load output caused by distributed power supply access to the distribution network, a multi-objective optimization model is constructed for the joint regulation of energy storage system and photovoltaic(PV) power supply with the objectives of minimum active network losses and voltage deviation, and the reactive power optimization model is analyzed by means of the constraints of on-load regulating transformer and capacitor bank actions and the constraints of photovoltaic(PV) power generation and energy storage outputs. An improved red-billed blue magpie optimization algorithm based on chaotic mapping lens initialization, nonlinear parameter factors, and adaptive inertia weights is proposed to prevent the algorithm from premature convergence and enhance the global search capability. Finally, the improved algorithm is applied to simulate the IEEE 33-node system containing a photovoltaic-storage distribution network, and the comparison with other algorithms shows that the algorithm has the advantages of good optimization and high search efficiency, which verifies the efficiency and stability of the proposed algorithm.

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Power Quality Disturbance Classification Method Based on Markov Transition Field and Particle Swarm Optimization and Convolutional Neural Networks

ZHANG Dachi, YANG Shiwei, FENG Shunqiang, YAO Di, XiN Haokuo, XiAO Bai

2025, 45(3):  103-111.  doi:10.3969/j.issn.1008-0198.2025.03.015

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A power quality disturbance classification method based on markov transition field (MTF), convolutional neural network (CNN), and particle swarm optimization (PSO) algorithms is proposed to address the trend of complex and diverse power quality disturbances (PQDs) in new power systems. Firstly, MTF is used to convert one-dimensional time-series power quality disturbance signals into two-dimensional modal images, which creat favorable conditions for subsequent data feature extraction. Secondly, a power quality disturbance classification model based on image modal data is constructed using CNN, and the parameters in the model are optimized using PSO algorithm to achieve optimal learning rate and avoid the phenomenon of underfitting or overfitting. Finally, the optimized classification model is used to obtain the classification results of power quality disturbances, and its performance is evaluated using evaluation indicators. The simulation results show that the constructed classification model can effectively classify power quality disturbance signals, with higher classification accuracy and noise resistance.

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Grid-Connected and Off-Grid Control Strategy for Optical Storage Clusters Based on Phase-Locked-Loop-Free Pre-Synchronisation

ZHENG Qiangren, HU Lijuan, Li Baoju, NiU Geng, XUAN Jingyan, WU Ming

2025, 45(3):  112-121.  doi:10.3969/j.issn.1008-0198.2025.03.016

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The control strategy of virtual synchronous generator (VSG) type grid-connected inverter is investigated, and a phase-locked-loop-free pre-synchronous control strategy is proposed, which aims to reduce the impact of grid-connected inverter on the grid, simplify the computation process and maintain the stable operation of the system. Through simulation verification, the strategy can achieve seamless switching between grid-connected and off-grid, has the advantages of simple calculation and fast response speed, and effectively solves the current impact and voltage oscillation problems in the process of grid-connected VSG inverters.

Artifical intelligence and Digitizatrion in Electrical Power

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Transmission Line Inspection Monocular Ranging Technology Based on Fused Laplace Residual Image Processing

Li Bocheng, YANG Haoyan, LiU Gang, GUO Hao, LiU Lanlan, Li Sai, Xi Yanhui

2025, 45(3):  122-128.  doi:10.3969/j.issn.1008-0198.2025.03.017

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During UAV inspections on ultra-and extra-high-voltage transmission lines, the UAV can approach the lines to capture detailed information. However, too close distance between UAV and transmission lines increases the risk of electromagnetic interference or even collisions. Therefore, it is crucial to accurately obtain the distance between the UAV and the transmission lines. In order to solve this problem, a depth estimation network LapNet(Laplace Net) fused with Laplace residuals is proposed, and U-Net is used as the network infrastructure to construct a multi-scale feature pyramid. A LUB (Laplace U-Block) module is proposed to replace the ordinary convolutional layer of U-Net, and the Laplace pyramid residual structure is introduced into the LUB module to increase the network depth while retaining the high-frequency information in the depth features. This leads to the reconstruction of high-quality depth images for accurate measurement of monocular distances. According to the actual test, the average error of distance detection using UAV monocular lens is 4.786%, and the maximum error is 8.36%, which can realize the accurate measurement of the distance between UAV lens and line.

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A Identifying Method for Turbine Load Deviation Based on DE-MLRF

WEN Wen, HUANG Yujie, TANG Mingzhu, DENG Liming, LUO Cui′e, JiANG Xin

2025, 45(3):  129-134.  doi:10.3969/j.issn.1008-0198.2025.03.018

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Aiming at the problem of load deviation in turbine variable condition operation, a classification model for the reason of turbine load deviation is proposed based on the combination of differential evolution (DE) algorithm and multi-label random forest (MLRF). The associated variables affecting the turbine load output are analyzed by Spearman correlation coefficient. The DE algorithm is used to optimize the parameters of the MLRF model, and the DE-MLRF-based classification model of the causes of turbine load deviation is established. The experimental validation is carried out by combining the actual operation data of a 660 MW turbine, and the results show that the MLRF model optimized by DE algorithm achieves the lowest false alarm rate and missing alarm rate, which are 1.902 4% and 1.854 1% respectively, compared with MLRF models optimized by the other seven algorithms. The DE-MLRF-based model for classifying the causes of turbine load deviation can provide decision support for locating the causes of turbine load deviation.

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Infrared Temperature Measurement Correction Method for Composite Insulators Based on RBF Neural Network Algorithm

Li Bocheng, YANG Haoyan, WU Jian, LiU Yancan, LiU Huazhou, CHEN Bin

2025, 45(3):  135-140.  doi:10.3969/j.issn.1008-0198.2025.03.019

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Aiming at the problem of temperature measurement error caused by distance measurement and visual angle change during UAV infrared patrol inspection of composite insulators, this paper proposes a method to improve the accuracy of infrared temperature measurement and ensure the accuracy and reliability of defect identification. Based on the built 110 kV composite insulator infrared temperature rise experimental platform, the system collects infrared image data at different shooting distances and angles, and uses the real temperature measured by the optical fiber temperature sensor as the calibration benchmark to build an infrared temperature measurement error sample set. Based on the data set, the radial basis function (RBF) neural network is used to establish the error correction model of infrared temperature measurement, and realize the nonlinear correction of the original infrared temperature measurement value. The results show that the average temperature difference of infrared thermometer after RBF model correction is reduced to 0.19℃ (the relative error is 2.07%), which is better than linear, nonlinear and exponential regression methods (the average temperature difference is 0.37~0.82℃), and has stronger generalization ability. This method effectively improves the temperature measurement accuracy of UAV infrared patrol inspections, and provides reliable technical support for the condition assessment of insulators.

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Research and Development of Underwater Inspection and Detection Platform for Hydraulic Structures

MO Jian, ZHANG Zhen, ZHANG Jun, ZHANG Hongqiang

2025, 45(3):  141-146.  doi:10.3969/j.issn.1008-0198.2025.03.020

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Aiming at the numerous challenges the current underwater inspection work facing, such as the complexity and variability of the underwater environment, the inefficiency of the traditional inspection methods and the existence of safety hazards, an underwater inspection and detection platform for hydraulic structures is thoroughly studied. This platform consists of a hardware layer, a network layer, a data layer, a service layer and an application layer. Firstly, the hardware layer utilizes advanced underwater robots to collect critical data such as water quality information around the hydraulic structures, as well as underwater images or videos. Secondly, the network layer ensures real-time and stable data transmission, with the data being stored in the data layer. Thirdly, the service layer transmits the data to a software processing system and combines artificial intelligence technologies such as convolutional neural networks to achieve defect detection in hydraulic structures and route planning for underwater robots. Finally, the application layer provides interfaces for computer browsers and WeChat service accounts, allowing users to view the inspection and detection results visually. Experimental results show that the platform can accurately monitor water quality information around hydraulic structures, provide clear underwater images and video materials, and obtain high-precision defect detection results for hydraulic structures.