VIT provides a distributed real-time online intelligent monitoring and health management system based on edge computing and artificial intelligence, which enables unified management and real-time monitoring of multiple discretely distributed crane equipment. It can detect abnormal status in a timely manner and notify equipment managers. The entire system adopts B/S architecture, and users can log in to the system through the web page. The system can evaluate and predict the health status of institutional equipment through cloud data analysis, helping equipment managers more accurately grasp the health status of equipment.
As a propulsion power device, the diesel engine is one of the core equipment of the ship. Its operating status will directly affect the normal navigation of the ship. According to statistics, among the many causes of maritime accidents, 22% accidents are caused by mechanical failures, 45% of mechanical failures are engine failures.
Shore container cranes ("quay cranes") are currently the main mechanical equipment used for loading and unloading containers in ports and terminals. Once a failure occurs, it will affect terminal production, delay shipping schedules, and affect the economic benefits of the terminal. Currently, most terminal companies still use traditional planned maintenance methods, but this method can only measure the current health status of the quay crane mechanism and cannot predict future equipment health in the short and medium term.
Comprehensively perceive the health status of key mechanisms and core components of the quay crane equipment, and use comprehensive signal analysis methods to monitor and diagnose the health status of the entire automated quay crane equipment.
Provides functions such as visual remote operation and maintenance of equipment, real-time status monitoring, real-time monitoring of data quality, fault diagnosis and early warning, and data distribution services for enterprise terminal monitoring centers and remote intelligent monitoring platforms to improve the work efficiency of enterprise-related operation and maintenance personnel and also facilitate Enterprise data analysis engineers can obtain equipment-related data and characteristics at any time for secondary research and application to achieve the purpose of reducing costs and increasing efficiency.
Deployment of quay crane at a deep water port in 2019
The diesel engine is one of the most important parts in a ship and is the core device that provides important power for the ship's navigation. However, during the operation of the diesel engine, due to the harsh working conditions, complex machine structure, and high load requirements, faults are prone to occur. Once a malfunction occurs, it will affect the normal navigation of the ship and cause huge economic losses. In serious cases, it may threaten the safety of the entire crew.
Use mechanism models to provide diagnostics, accurately identify failure modes, and promote high-quality maintenance decisions.
Customized data display, user-friendly interface, intuitive display of key data and plots.
Good data openness, API provided for 3rd-enterprise big data platforms.
Shanghai Shipbuilding Research Institute - Diesel engine monitoring and diagnostic analysis system