Research on Health Management Technology and Application of Lifting Machinery

Abstract

Abstract Lifting machinery is a key facility for the development of modern industry. It’s not noly an important support for the construction of major national projects but also one of the core competitiveness of my country’s equipment manufacturing industry. With the development of large-scale, high-parameterization and intelligentization of lifting appliances, technologies such as safety monitoring and health monitoring have been gradually applied to industrial fields such as ports and metallurgy. In order to further develop the data-driven health management technology and engineering application of cranes, on the basis of elaborating the health management needs of cranes, the current status and development trends at home and abroad, we explored and proposed a technical framework for health management of cranes, and analyzed the lifting Key technologies such as machinery safety monitoring, health monitoring, health status diagnosis, failure trend prediction, and predictive maintenance decisions. Finally combined with a 200t casting crane in a steel plant, carried out safety monitoring and data-driven diagnosis, prediction and system visualization management. The results show that: the hoisting machinery health management system can monitor and monitor in real time and carry out early warning and forecasting to avoid the occurrence of unexpected accidents; based on predictive maintenance decisions, it helps enterprises to reasonably arrange maintenance cycles and maintenance methods to reduce the maintenance cost of the enterprise; reduce hoisting machinery downtime Time to enhance the effective value of assets; and enhance the level of enterprise information management.