The transformer partial discharge online monitoring system primarily consists of a front-end external pulse current sensor (FIPD-1000), a partial discharge acquisition unit (PD acquisition unit), a computer server, and a partial discharge online monitoring software platform. The front-end sensor senses PD analog signals from different locations and then connects them to the PD monitoring unit via a coaxial cable. The monitoring unit features signal filtering, amplification, and analog-to-digital conversion, filtering, reducing noise, and amplifying the sensor-coupled signals to ensure they fall within the AD conversion range. The PD acquisition unit utilizes a 100MS/s sampling rate and 14-bit resolution, with four channels synchronously acquiring high-frequency discharge pulse signals coupled to the sensors. These signals are synchronized with the power supply phase via a synchronization control unit. A triggered acquisition mode is employed: when the trigger signal reaches the acquisition threshold, the PD acquisition unit immediately acquires PD signals for a specified duration. Because the system uses the same trigger signal to trigger each PD acquisition unit simultaneously, each unit achieves high synchronization, with a time difference of less than 100ns.
● Edge Computing
In line with current IoT terminal design concepts, this approach features edge computing, on-site data processing, remote analysis and judgment, and a data replay and traceability mechanism.
● Flexible Access and Inspection
The detection unit is also suitable for line inspections. Simply bring a computer with partial discharge analysis software and use it with the terminal.
● Stable Data Transmission
The system can utilize Ethernet cables or fiber optic cables, or 4G network transmission. When using fiber optic transmission, the maximum distance between two monitoring nodes can be 20 km, ensuring stable data transmission. Digital transmission is preferred for long-distance data transmission.
● Synchronous Real-Time Sampling
All sampling channels can acquire data continuously and synchronously. Data processing is performed in parallel within the monitoring unit's internal FPGA. Data acquisition, calculation, and pattern recognition are all handled by the acquisition unit. This distributed computing approach allows the backend computer to solely store and display data, including querying measurement results. This results in a more stable overall system.
● Web-based Software Platform
The software utilizes a web-based platform, allowing direct browsing and management via a browser. No additional client software installation is required. By connecting to an external cloud platform, monitoring data can be viewed from any computer. It supports a large database capacity, ensuring stable storage of 10 years of monitoring data.
● Rich Software Features
It can record parameters such as measured discharge volume, discharge phase, and measurement time. It provides discharge trend graphs and features early warning and alarm functions. The database can be queried, deleted, backed up, and printed as reports. Monitoring data can be used to effectively assess the condition of monitored equipment, allowing adjustments to equipment test cycles, reducing unnecessary power outages, and providing early warning of potential faults.
● Rich Graphical Information
The system displays partial discharge signals in various graphical formats, including year-month-day partial discharge trend graphs, phase pulse graphs, and PRPD (2D) and PRPS (3D) graphs, clearly displaying discharge amplitude, time, and phase information. Detailed partial discharge waveforms can be viewed for each monitoring unit at any given moment.
● Extensive software interfaces
Open data architecture, supporting third-party protocols (RESTFul, MQTT, TCP-Modules, RS485-Modules, 61850, and China Southern Power Grid/State Grid protocols)
● Independent display at the station end
An optional LCD screen with station-side display allows on-site personnel to easily view partial discharge data and analyze it in conjunction with backend data.
● High sensitivity
Can detect discharge signals as small as 5 PC and supports discharge calibration.
● Shock resistance
Can withstand 600 kV flashover shocks without damage to the terminal device or data loss.
● Interference resistance
Equipped with time-domain and frequency-domain signal analysis technology, it effectively separates interference signals from partial discharge signals, effectively preventing interference from the instrument power supply.
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