During the operation of high-voltage switch cabinets, insulation defects are one of the main causes of switch cabinet failures. Partial discharge is the main manifestation of insulation defects and is also the main reason for their further deterioration. With the increasing occurrence of accidents, the detection and monitoring of partial discharge have received more and more attention. With the advancement of condition-based maintenance in the power industry and the development of modern technology, it has provided conditions and necessary technical basis for the online monitoring of partial discharge in switch cabinets.
The on-line monitoring sensor for partial discharge in switch cabinets can perfectly solve this problem. It can display the operating status of the equipment in real time, enable equipment assessment and maintenance, save a lot of human and material resources, and promptly identify problems to prevent accidents.
1. High anti-interference capability, accurate monitoring data
The system adopts various anti-interference measures to effectively remove interference from the on-site environment and accurately extract local discharge signals, thereby determining the operating condition of the equipment.
2. Simple and quick installation
Due to the special nature of the power industry, prolonged power outages are not allowed for construction. The system was designed with simplicity and speed in mind from the beginning. Without modifying the original equipment structure, it can be installed quickly, and after installation, it does not affect the normal operation of the equipment, and maintenance is simple.
3. Query, parameter setting, and maintenance without power outage
The system adopts a modular design and uses a unified data bus method. Without power outage, data can be queried, parameters can be set for each unit.
4. Combination of multiple monitoring methods, more effective measurement data
Combined with acoustic-electric testing (ultrasonic method and ground electric wave method), through the combination and analysis of acoustic-electric data, local discharge signals can be effectively extracted.
5. Multiple data analysis methods
The system can display various graphics such as real-time waveforms, trend charts, and frequency domain analysis diagrams, which can effectively analyze the types of discharges and suspected fault points.
