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This paper addresses the problem of inefficient inspection path planning for metering equipment by proposing a quantum annealing (QA) based optimization method. They develop a mathematical model for the inspection path and introduce a novel qubit measurement and state update mechanism to improve the convergence of the QA algorithm. Simulation results demonstrate the algorithm's ability to generate shorter inspection paths with strong global convergence compared to existing methods, suggesting improved inspection efficiency.
Quantum annealing can optimize inspection paths for metering equipment, slashing path lengths and boosting efficiency in real-world scenarios.
In order to address inefficiencies in the inspection path planning of metering equipment and minimize inspection path lengths, this study proposes a novel optimization method based on the quantum annealing algorithm. A mathematical model for metering equipment inspection path planning is developed, accompanied by a new qubit measurement and state update mechanism designed to enhance algorithm convergence speed. Simulation experiments validate the effectiveness of the proposed algorithm, demonstrating its ability to plan inspection paths under diverse conditions while achieving the shortest path lengths and maintaining strong global convergence. The results highlight the algorithm’s potential to significantly improve inspection efficiency and adaptability in real-world scenarios.
