Transformer Oil Spectral Online Monitoring Device

New Products / New Technology

The online spectral monitoring device for transformer oil performs a preliminary analysis of the types and concentrations of characteristic gases dissolved in the insulating oil, enabling it to identify potential hidden faults within the transformer and predictively determine the nature of any malfunctions, distinguishing between overheating‑related faults and discharge‑related faults. It is an essential tool for assessing the health condition of transformers.

Portable Oil Spectroscopy Monitoring Device

New Products / New Technology

This product builds upon TDLAS technology for detecting dissolved gases in transformer oil, incorporating innovative advancements to deliver a portable testing solution that ensures the risks associated with critical transformer assets remain under control. The project will develop a portable detection system designed to enhance the technical expertise of the company's R&D personnel, strengthen their capacity for independent research and development of new technologies and instruments, and elevate the company's reputation and influence. In addition, through this research, an integrated framework will be established for the device's independent design, R&D, manufacturing, calibration, commissioning, and maintenance, ensuring that core technologies remain self‑reliant and controllable, thereby laying the groundwork for the standardized, commercial production of future products.

Online Partial Discharge Monitoring Device for Generators

New Products / New Technology

The wideband partial discharge online monitoring system for generator neutral points can track trends in partial discharge activity, serving as a critical tool for early detection of insulation degradation and timely implementation of corrective measures, thereby supporting the safe and stable operation of the unit. Compared with conventional equipment, it offers capabilities such as wideband signal monitoring, time–frequency transformation, cluster analysis for feature extraction, pattern recognition based on typical discharge spectra, and data trend analysis and query functions, enabling more accurate and effective assessment of partial discharge and insulation condition in the generator stator windings.