Automatic Target Recognition of Substation 3D Scene for Digital Twin

doi:10.16182/j.issn1004731x.joss.22-0867

Abstract

Abstract:

In order to improve the accuracy of automatic target recognition and promote the effect on substation operation and maintenance, automatic target recognition of substation 3D scene for digital twin is proposed. The automatic target recognition model for the three-dimensional scene of the substation is constructed. The perception module of the model is used to collect the real-time status data of substation, and the communication module is used to transmit the data to digital twin modules. This module, based on the received data information, realizes the deep fusion and panoramic mapping of substation information through the knowledge base constructed by the knowledge map and the virtual and real data processing unit of the service module. Non-uniform rational b-splines(NURBS) surface reconstruction method is used to create a three-dimensional scene model of substation. The forward looking automatic target recognition unit uses the forward looking template matching technology to accurately recognize the single target and multiple targets in the three-dimensional scene model of the substation according to the knowledge base. The experimental results show that the model has excellent 3D modeling effect in both simple and complex scenes. In cloudy and foggy days, the model can still accurately identify all the targets in substation.

Key words: digital twin, substation, 3D scene, forward looking automatic target, identification model, forward looking template matching

CLC Number:

TP311

Tu Qian, Li Jun, Fan Dongliang, Kong Qi, Shen Jie. Automatic Target Recognition of Substation 3D Scene for Digital Twin[J]. Journal of System Simulation, 2023, 35(12): 2594-2601.

Figures/Tables 6

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Table 1

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图像编号	边缘像素数	4连同域数	8连同域数	O/M	O/N
Q1	12 368	49 467	1 484	0.12	0.03
Q2	15 469	18 282	2 011	0.13	0.11
Q3	17 521	9 347	1 402	0.08	0.15
Q4	12 359	5 088	865	0.07	0.17
Q5	14 552	20 013	1 601	0.11	0.08
P1	13 456	22 433	1 346	0.10	0.06
P2	17 568	17 567	2 108	0.12	0.12
P3	13 267	4 420	663	0.05	0.15
P4	11 029	11 033	993	0.09	0.09
P5	12 314	13 436	1 478	0.12	0.11

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