Driven by Equipment Operation and Maintenance Data, WTAU Dalian Huarui Ship Unloader Condition Monitoring System was successfully accepted.

Previously, lifting equipment was prone to various faults due to long-term high-load operation. Failures may not only cause equipment downtime and affect production, but also pose safety risks. The fault diagnosis method that relies on manual experience and regular maintenance inspections has low diagnostic accuracy, difficulty in discovering potential faults, and passive maintenance work. Regular maintenance also has the problem of affecting loading and unloading construction.

The WTAU ship unloader status online monitoring system is accurate and efficient, and can monitor equipment online in real time. It can analyze the type, location and degree of faults without stopping the machine or production, and can predict hidden dangers 30 days in advance. The system adopts multi-dimensional comprehensive intelligent diagnosis, collects vibration, sound and temperature data, has a bilingual switching function, and realizes fault diagnosis reports through in-depth analysis of AI algorithms. It can understand the health status of equipment in real time, issue early warnings and scientifically arrange maintenance plans to effectively avoid downtime and accidents.

The successful application of WTAU ship unloader condition monitoring system in Dalian Huarui has promoted the transformation of port crane equipment operation and maintenance mode from "experience-driven" to "data-driven". In the future, WTAU will continue to optimize intelligent monitoring and fault diagnosis technology to provide more efficient and safer equipment management solutions for global ports.