Combined inspection strategy of bionic substation inspection robot based on improved Biological Inspired Neural Network. (November 2021)

• Record Type: Journal Article
• Authors: Wang, Zhenwei; Cheng, Zhiyu; Yang, Kejun; Zhang, Tianzhong; Liu, Qun; Zhang, Fan; Mu, Hong; Li, Kunpeng
• Is Part Of: Energy reports. Volume 7(2021)Supplement 7
• Page Start: 549
• Page End: 558
• Publication Date: 2021-11
• Subjects: Substation -- Biological Inspired Neural Network algorithm -- Inspection robots -- Route plan; Power resources -- Periodicals; Energy industries -- Periodicals; Power resources; Periodicals; Electronic journals; 621.04205
• DOI: 10.1016/j.egyr.2021.10.007
• Languages: English
• ISSNs: 2352-4847

Abstract

Abstract: Aiming at the problem of complex and low efficiency of intelligent patrol paths in 220/500 kV bionic substations, this paper proposes a method for collaborative inspection of multiple patrol robots. Firstly, the deficiencies of the Biological Inspired Neural Network algorithm(BINN) in complex paths and large corner scenarios are analyzed, and an improved method for solving the neuron activity value near the boundary and an improved method for the neuron activity value near the obstacle are proposed, in order to solve the phenomenon that the decrease of neurons that can transmit activity values in the neighborhood leads to generally low neuron activity values, which leads to unreasonable path planning; Secondly, establish a substation area segmentation model based on the variable tangent method, divide the substation area into several sub-intervals without obstacles, and use the priority heuristic algorithm to select the robot travel path, so as to realize the multi-robot joint inspection task ; Finally, the method proposed in this paper reduces the path length, number of turns and rotation angle by 11.38%, 38, 89% and 20.51, respectively, compared with the BINN algorithm, and by 5.75%, 18.18%, and 16.68 compared with the A* algorithm, which verifies the feasibility and effectiveness of the proposed method.