Computer Science ›› 2025, Vol. 52 ›› Issue (11A): 250900008-10.doi: 10.11896/jsjkx.250900008

• Artificial Intelligence • Previous Articles     Next Articles

Research on Substation Camera Inspection Task Scheduling Method Based on Improved Discrete Black-winged Kite Algorithm

LI Haifeng1, CHEN Qing1,2, HUANG Yuehua1,3, CHEN Xi1,3, WEN Bin1,2, WU Xichun4   

  1. 1 College of Electrical Engineering and New Energy,China Three Gorges University,Yichang,Hubei 443002,China
    2 Hubei Provincial Key Laboratory for Operation and Control of Cascaded Hydropower Station,China Three Gorges University,Yichang,Hubei 443002,China
    3 Hubei Provincial Engineering Technology Research Center for Microgrid,China Three Gorges University,Yichang,Hubei 443002,China
    4 State Grid Hubei Electric Power Co.,Ltd.Yichang Power Supply Company,Yichang,Hubei 443000,China
  • Online:2025-11-15 Published:2025-11-10
  • Supported by:
    National Natural Science Foundation of China(62233006),Hubei Provincial Natural Science Foundation of China(2024AFD409) and Science Foundation of China Three Gorges University(2024RCKJ022).

Abstract: Aiming at the problem of uneven task allocation and lack of flexibility in substation camera inspection,which leads to low efficiency of camera work,a camera inspection task scheduling method based on improved discrete black-winged kite algorithm is proposed.Firstly,considering the complex mapping relationship between cameras,substation equipment and inspection tasks,an optimal scheduling model for camera inspection tasks is constructed with inspection completion time,deflection angle and load balancing as the objectives.Then,heuristic joint rules based on the actual inspection-specific information are designed to generate the initial population of the optimization solution,which effectively solves the problem of random initialization uncertainty.Furthermore,the introduction of the discrete difference mutation operation and spiral search migration mechanism are introduced to improve the black-winged kite algorithm with hybrid multi-strategy search to increase the algorithm adaptability and search capability.Scenario test results show that the proposed method effectively improves the efficiency of substation camera inspection,and the method can make the camera have better stability in large-scale and long-cycle inspection tasks.

Key words: Camera inspection, Inspection task scheduling, Improved discrete black-winged kite algorithm, Heuristic joint rule, Multi-strategy search

CLC Number: 

  • TM769
[1]CHEN X,HAN Y F,YAN Y F,et al.A unified algorithm for object tracking and segmentation and its application on intelligent video surveillance for transformer substation[J].Procee-dings of the CSEE,2020,40(23):7578-7587.
[2]JIANG Q,LIU Y D,YAN Y J,et al.Substation inspection robot PTZ camera alignment method for high zoom scenes[J].Proceedings of the CSEE,2024,44(8):3337-3347.
[3]DONG X Y,JI K,ZHU J,et al.A retrofitted ant colony algorithm for inspection robot path planning in UHV substations[J].Power System Protection and Control,2021,49(18):154-160.
[4]QI B,JI M,ZHENG Y P,et al.Application status and development prospect of power internet of things technology in condition assessment of power transmission and transformation equipment[J].High Voltage Engineering,2022,48(8):3012-3031.
[5]PENG M Z,XU Y,HU Y B,et al.Intelligent inspection techno-logy for secondary equipment in substations based on artificial intelligence technology [J].High Voltage Engineering,2023,49(S1):90-96.
[6]TONG J,QI Z H,PU T J,et al.Edge intelligence to power internet of things:concept,architecture,technology and application[J].Proceedings of the CSEE,2024,44(14):5473-5496.
[7]ZHANG C X,LU Z H,LIU X C.Joint inspection technology and its application in a smart substation [J].Power System Protection and Control,2021,49(9):158-164.
[8]ZHANG S J,DU H T,HOU T T.An improved NSGA-Ⅱ algorithm for solving multi-objective dual resource constrained flexible job shop scheduling problem[J].Mechanical Science and Technology for Aerospace Engineering,2023,49(S1):90-96.
[9]PEI H L.Joint scheduling method of machine and handling robot in flexible manufacturing workshop[J].Modern Manufacturing Engineering,2023(3):15-21.
[10]SHI W,ZHOU S,NIU Z,et al.Joint device scheduling and resource allocation for latency constrained wireless federated learning[J].IEEE Transactions on Wireless Communications,2020,20(1):453-467.
[11]ZHOU K,TAN C,WU Y,et al.Research on low-carbon flexible job shop scheduling problem based on improved Grey Wolf Algorithm[J].The Journal of Supercomputing,2024,80(9):12123-12153.
[12]HU R Q,CHENG H,ZHANG Z N.Solving job shop scheduling problem with flexible process sequence based on expression tree model[J].Computer Integrated Manufacturing Systems,2024,30(6):2036-2043.
[13]LU J S,JIN J H,ZHAO W B,et al.Lot streaming hybrid assembly flow shop scheduling on migratory bird algorithm[J].Journal of Zhejiang University(Engineering Science),2022,56(11):2135-2144.
[14]WANG S H,LI Y,LI X Y.An improved whale swarm algorithm for flexible job-shop scheduling problem[J].Journal of Chongqing University,2020,43(1):1-11.
[15]YANG G,YU L.A chimp algorithm based on the foragingstrategy of manta rays and its application[J].Plos One,2024,19(3):e0298230.
[16]ZHANG S J,YANG W Q,GU X S.An improved multi-swarm migrating birds optimization algorithm for hybrid flow shop scheduling[J].Journal of Shanghai Jiao Tong University,2023,57(10):1378-1388.
[17]LEI D M,LIU J Y.Reentrant hybrid flow shop scheduling based on cooperated shuffled frog-leaping algorithm[J].Huazhong Univ.of Sci.& Tech.(Natural Science Edition),2023,51(5):125-130.
[18]WU R R,LI D J,QIN J,et al.System design of an indoor inspection robot driven by a flexible cable in a substation [J].Power System Protection and Control,2021,49(10):89-97.
[19]HALL N G,SRISKANDARAJAH C.A survey of machinescheduling problems with blocking and no-wait in process[J].Operations Research,1996,44(3):510-525.
[20]WANG J,WANG W,HU X,et al.Black-winged kite algorithm:a nature-inspired meta-heuristic for solving benchmark functions and engineering problems[J].Artificial Intelligence Review,2024,57(4):1-53.
[21]ZHANG Z,WANG X,YUE Y.Heuristic optimization algorithm of black-winged kite fused with osprey and its engineering application[J].Biomimetics,2024,9(10):595.
[22]BA Z Y,YUAN Y P,PEI G Q,et al.Hybrid evolutionary algorithm with multi-operation precise joint movement neighborhood structure for job shop scheduling problem[J].Computer Integrated Manufacturing Systems,2024,30(2):537-552.
[23]AMARO D,ROSENKRANZ M,FITZPATRICK N,et al.Acase study of variational quantum algorithms for a job shop scheduling problem[J].EPJ Quantum Technology,2022,9(1):5.
[24]MENG L L,ZHANG B,REN Y P,et al.Hybrid shuffled frog-leaping algorithm for distributed flexible job shop scheduling[J].Journal of Mechanical Engineering,2021,57(17):263-272.
[25]NAWAZ M,ENSCORE J E E,HAM I.A heuristic algorithm for the m-machine,n-job flow-shop sequencing problem[J].Omega,1983,11(1):91-95.
[26]WANG J,LIAO J,ZHOU Y,et al.Differential evolution en-hanced with multiobjective sorting-based mutation operators[J].IEEE Transactions on Cybernetics,2014,44(12):2792-2805.
[27]LI D H,XIONG W Q,WANG Z D.Improving seagull optimization algorithm combined multiple strategies and its application[J].Application Research of Computers,2023,40(5):1360-1367,1374.
[28]DAUZÈRE-PÉRÈS S,DING J,SHEN L,et al.The flexible job shop scheduling problem:A review[J].European Journal of Operational Research,2024,314(2):409-432.
[29]XIONG F L,LI L L.Just-in-time distributed precast scheduling with considering production and transportation costs[J].Computer Integrated Manufacturing Systems,2024,30(12):4386-4405.
[1] WU Liuchen, ZHANG Hui, LIU Jiaxuan, ZHAO Chenyang. Defect Detection of Transmission Line Bolt Based on Region Attention Mechanism andMulti-scale Feature Fusion [J]. Computer Science, 2023, 50(6A): 220200096-7.
[2] LI Fa-guang, YILIHAMU·Yaermaimaiti. Real-time Detection Model of Insulator Defect Based on Improved CenterNet [J]. Computer Science, 2022, 49(5): 84-91.
[3] ZHAO Zhen-bing, CUI Ya-ping, QI Yin-cheng, DU Li-qun, ZHANG Ke, ZHAI Yong-jie. Detection Method of Insulator in Aerial Inspection Image Based on Modified R-FCN [J]. Computer Science, 2019, 46(3): 159-163.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!