This paper aims at the problems of unclear scheduling model and low intelligence in the scheduling technology of bulk cargo terminals, analyzes the business process and characteristics of bulk cargo terminals based on the current situation and demand of the scheduling business of bulk cargo terminals, according to the actual scheduling characteristics and use rules of the berths and yards of bulk cargo terminals, and combined with the characteristics of complex coordination factors between the berths and yards of bulk cargo terminals, A multi resource collaborative scheduling model of bulk cargo terminal based on particle swarm optimization algorithm is proposed, and the algorithm is analyzed. This paper also proposes an optimization scheme for bulk cargo terminal scheduling.
This paper aims at the problems of unclear scheduling model and low intelligence in the scheduling technology of bulk cargo terminals, analyzes the business process and characteristics of bulk cargo terminals based on the current situation and demand of the scheduling business of bulk cargo terminals, according to the actual scheduling characteristics and use rules of the berths and yards of bulk cargo terminals, and combined with the characteristics of complex coordination factors between the berths and yards of bulk cargo terminals, A multi resource collaborative scheduling model of bulk cargo terminal based on particle swarm optimization algorithm is proposed, and the algorithm is analyzed. This paper also proposes an optimization scheme for bulk cargo terminal scheduling.
In this paper, taking the conveying equipment as the research object, aiming at the main characteristics and intelligent requirements of the current dry bulk terminal conveying system, a monitoring and diagnosis model of the dry bulk terminal conveying equipment based on the edge-cloud collaborative technology is proposed. The technical advantages of the company can jointly realize the tasks of perception, integration, monitoring and diagnosis of the conveying equipment, improve the monitoring and diagnosis function of the conveying equipment in the dry bulk terminal, and improve the safety supervision ability of the dry bulk terminal.
Aiming at the sensing, monitoring and control requirements of the belt conveyor equipment in the dry bulk cargo wharf, this study combines the monitoring system with the control system. On the premise of comprehensive sensing of the equipment, by transmitting the signal obtained by the sensing terminal to the central control room, the interaction and linkage between the real-time state of the belt conveyor and the automatic control system of the wharf are realized, and the incomplete sensing of the key equipment of the wharf is solved The belt conveyor intelligent monitoring system not only meets the needs of intelligent monitoring and unmanned monitoring, but also reduces the risk of workers working in complex environment, and fully realizes the goal of safe, stable and efficient operation of the production system of dry bulk terminal.
The traditional granary ventilation system generally adopts upper-cage ventilation and floor trough ventilation, which leads to serious vertical stratification of grain moisture. In order to overcome the defects of the existing technology and fully consider the special storage environment of the dry bulk terminal, this paper studies and designs an intelligent ventilation system suitable for the grain storage bin of the dry bulk terminal. The combined method, equipped with an external mobile fan on the basis of the internal axial flow fan, solves the problem of poor heat dissipation effect of the ventilation system in the special environment of the dry bulk terminal through the structural cooperation of the annular main air duct and the horizontal air duct.
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