EXPLORATION OF INTELLIGENT TECHNOLOGIES FOR SMART EXPRESSWAY ELECTROMECHANICAL SYSTEMS
Abstract
With the rapid development of intelligent transportation systems, smart expressways demand higher reliability, integration, and intelligence of electromechanical (EM) systems. However, existing EM systems often suffer from fragmented architectures, limited data utilization, and low intelligence in operation and maintenance (O&M). To address these issues, this paper proposes a methodology-oriented framework for the intelligent upgrading of smart expressway EM systems. The framework integrates condition-based monitoring, a layered intelligent management platform, and a data-driven O&M mechanism. Multi-source operational data are utilized to enable real-time equipment monitoring, fault prediction, and predictive maintenance. A centralized data architecture and QR code–based field operations are introduced to enhance data traceability and maintenance efficiency. The proposed approach improves system reliability, maintainability, and operational efficiency, providing a scalable solution for smart expressway EM systems.
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