Develop AI on Predictive Maintenance and Performance Optimization for Main Low Voltage Switchboard

I&T Solution Develop AI on Predictive Maintenance and Performance Optimization for Main Low Voltage Switchboard
(REF: S-1352)
Trial Project
Solution Feature
  • Real-time monitoring (Dashboard)
  • Data preprocessing and storage
  • AI-powered analytics
  • Fault detection and diagnosis
  • Reporting and record-keeping
Trial Application and Expected Outcome
  • Real-time monitoring - The system should provide real-time monitoring of the main low voltage switchboard using smart power analyzers and sensor technologies.
  • Data preprocessing and storage (Pipeline and Warehouse) - The system should ensure that the collected data is clean, complete, and ready for analysis.
  • AI-powered analytics (Training) - The system should incorporate machine learning algorithms that can analyze the collected data and identify potential faults and abnormalities (A anomaly/fault detection).
  • Fault detection and diagnosis (Production) - The system should be able to detect and diagnose faults in the switchboard, such as high impedance on busbars or potential damage to load equipment.
  • Reporting and record-keeping - The system should generate reports that summarize the performance of the switchboard, including any detected faults and recommended optimizations.
Additional Solution Information 20230414_XS_PdM-Inno_Portal-LVSW.pdf
Info on I&T Solution Provider
Solution Provider:XTRA Sensing Limited
Address:Suite 1603, Chinachem Johnston Plaza, 178-186 Johnston Road, Wan Chai, Hong Kong
Contact Person:Nigel Ko
Position:Chief Innovation Officer
Tel:25502330
Email: nigel@xtrasensing.com
Webpage: www.XTRAsensing.com

For details of the above I&T solution, please contact the I&T solution provider.