JO-OM400B transformer local on-line monitoring system
The JO-OM400B transformer partial on-line monitoring system uses an ultra-high frequency antenna to detect and receive ultra-high frequency (UHF) signals generated by the partial discharge of the transformer to realize on-line monitoring of the partial discharge of the transformer. This system can use lE061850 protocol to output signals, and can be directly connected to the integrated online detection platform of the substation.
1. Based on UHF full frequency band dynamic sweep frequency partial discharge detection technology; 2. Provide built-in or plug-in UHF sensor, working frequency bandwidth, high sensitivity, UHF sensor signal output terminal and ground terminal are equipotential, and work with transformer The circuit does not have any electrical connection, which is safer and more reliable for both the test device and the operator, and can be overhauled electronically; 3. Four-channel high-speed synchronous sampling; 4. Composite noise removal technology and automatic threshold wavelet noise removal principle; 5. Neural network expert system based on discharge map library; 6. DL/T860 (lE061850) standard protocol can be adopted;
1. The ultra-high frequency (UHF) sensor system can be equipped with a manhole (hand hole) sensor or an oil valve sensor according to different needs. The manhole (hand hole) sensor is installed in the transformer production process, and the oil valve sensor Install at the transformer installation site.
2. On-site data processor The on-site data processing unit is connected to the UHF sensor through a high-performance coaxial cable, and through anti-interference technologies such as hardware filter circuit, mixing amplification, high-speed sampling and wavelet threshold filtering, extracts effective internal office Amplify the signal, and report the extracted partial discharge signal to the central processing unit after analysis and processing.
3. Background processing system The background processing system summarizes the signals of the field data processing unit, builds a fault mode database, uses fingerprint recognition, dual neural network engines, and diagnoses the type of partial discharge faults in the transformer