BTW Xinyu Company Achieves Complete Domestic Production of GIS Partial Discharge Online Monitoring Device

Recently, the TWMG-100 Fixed GIS Partial Discharge Online Monitoring Device, independently developed by BTW Xinyu Company, has officially passed the ecosystem product certification for the Dianhong IoT Operating System of China Southern Power Grid. It has become one of the first monitoring devices to achieve full domestic production in terms of "hardware + operating system + application software," marking that BTW's power equipment condition monitoring products have completely broken free from dependence on foreign software and hardware systems. This provides an independent and controllable solution for the construction of new power systems.

The device is equipped with the Dianhong IoT Operating System independently developed by China Southern Power Grid and adopts a domestic chip processor, achieving deep compatibility with the Dianhong IoT OS. It features functions such as OTA (Over-the-Air) updates, plug-and-play, security authentication, near-field operation and maintenance, status detection, network awareness, unified communication protocols, and AI capabilities. Integrating advanced technologies such as sensing technology, high-speed acquisition technology, and high-speed Ethernet communication technology, it utilizes combined UHF (ultra-high frequency) and ultrasonic monitoring modes to achieve data acquisition, comprehensive analysis, and condition assessment for GIS equipment. This ensures precise defect localization, effectively improves operational inspection efficiency, and guarantees the safe and stable operation of equipment.

Device Highlights:

1.       The system can analyze and calculate partial discharge parameters such as maximum discharge magnitude, current discharge magnitude, discharge phase, and discharge count. It provides multiple spectrum displays including PRPS (Phase Resolved Partial Discharge) and PRPD (Phase Resolved Partial Discharge Pattern) diagrams, enabling precise analysis of discharge signal characteristics and development processes from different dimensions, greatly enhancing the accuracy of discharge fault diagnosis.

2.       Utilizing artificial intelligence technology, it automatically identifies typical defects such as metal particles, floating potentials, internal corona, internal defects in solid insulation, and surface discharge along solid insulation.

3.       Using statistical positioning algorithms, it automatically determines the discharge location within the GIS, with a positioning accuracy of less than 20 centimeters.

4.       Addressing the rapid development characteristic of GIS discharge faults, it can capture signals during sudden changes and achieve second-level alarms.