3-D Partial Discharge Patterns Recognition of Power Transformers Using Neural Networks
نویسندگان
چکیده
Partial discharge (PD) pattern recognition is an important tool in HV insulation diagnosis. A PD pattern recognition approach of HV power transformers based on a neural network is proposed in this paper. A commercial PD detector is firstly used to measure the 3-D PD patterns of epoxy resin power transformers. Then, two fractal features (fractal dimension and lacunarity) extracted from the raw 3-D PD patterns are presented for the neuralnetwork-based (NN-based) recognition system. The system can quickly and stably learn to categorize input patterns and permit adaptive processes to access significant new information. To demonstrate the effectiveness of the proposed method, the recognition ability is investigated on 150 sets of field tested PD patterns of epoxy resin power transformers. Different types of PD within power transformers are identified with rather encouraged results.
منابع مشابه
Partial Discharge Classification Using Neural Networks and Statistical Parameters
Partial discharge (PD) pattern recognition is an important tool in high-voltage insulation diagnosis of power systems. A PD pattern classification approach of high-voltage power transformers based on a neural network is proposed in this paper. A commercial PD detector is firstly used to measure the 3-D PD patterns of epoxy resin power transformers. Then, the gray intensity histogram extracted f...
متن کاملApplication of Back-Propagation Neural Network to Power Transformer Insulation Diagnosis
This paper presents a novel approach based on the back-propagation neural network (BPNN) for the insulation diagnosis of power transformers. Four epoxy-resin power transformers with typical insulation defects are purposely made by a manufacturer. These transformers are used as the experimental models of partial discharge (PD) examination. Then, a precious PD detector is used to measure the 3-D ...
متن کاملAnalysis and Diagnosis of Partial Discharge of Power Capacitors Using Extension Neural Network Algorithm and Synchronous Detection Based Chaos Theory
Power capacitors are important equipment of the power systems that are being operated in high voltage levels at high temperatures for long periods. As time goes on, their insulation fracture rate increases, and partial discharge is the most important cause of their fracture. Therefore, fast and accurate methods have great importance to accurately diagnosis the partial discharge. Conventional me...
متن کاملPartial discharge pattern classification using multilayer neural networks - Science, Measurement and Technology, IEE Proceedings A
Partial discharge measurement is an important means of assessing the condition and integrity of insulation systems in high voltage power apparatus. Commercially available partial discharge detectors display them as patterns by an elliptic time base. Over the years, experts have been interpreting and recognising the nature and cause of partial discharges by studying these patterns. A way to auto...
متن کاملImproved Bagging Algorithm for Pattern Recognition in UHF Signals of Partial Discharges
This paper presents an Improved Bagging Algorithm (IBA) to recognize ultra-high-frequency (UHF) signals of partial discharges (PDs). This approach establishes the sample information entropy for each sample and the re-sampling process of the traditional Bagging algorithm is optimized. Four typical discharge models were designed in the laboratory to simulate the internal insulation faults of powe...
متن کامل