Based on the well developed sensing mechanism, and technical means including intelligent algorithms and big data analysis, we has provided online monitoring and intelligent diagnosis services for many types of small equipment in the industrial manufacturing chain, and cooperated with experienced equipment diagnostic experts to provide remote diagnostic services for users, helping enterprises diagnose potential failures of their equipment and providing relevant optimization suggestions. At the same time, the systematic management is carried out in terms of equipment maintenance, inspection, spare parts, and knowledge base to ensure the equipment health and improve the manufacturing efficiency.
With “machine vibration+mechanism model” as the technical core, we has created a product system that integrates software and hardware with full coverage of “data acquisition-data calculation-data utilization”. Based on the well developed sensing mechanism, and technical means including intelligent algorithms and big data analysis, we has provided online monitoring and intelligent diagnosis services for many types of small equipment in the industrial manufacturing chain to ensure the equipment health and improve the manufacturing efficiency.
Chemical engineering, refining, pharmaceutical engineering, papermaking and other key industries.
Provide predictive maintenance services by performing fault diagnosis and lifespan prediction through data acquisition.
Build a “product+platform+service” equipment health management system integrating software and hardware to achieve intelligent monitoring and diagnosis of factory equipment, and provide comprehensive online and offline services to ensure the equipment health and improve the manufacturing efficiency.
Collect equipment production operation status and parameters through intelligent perception layer sensors
Achieve data processing and transmission through edge all-in-one machines, and realize the conversion of AD domain through fast Fourier transform
Diagnose equipment faults through the AI algorithm model and the large equipment fault library of the Yunzhou Equipment Health Management System, ultimately achieving early warning of equipment to avoid equipment failures and ensure the normal operation of the equipment