| 引用本文: | 苏晶晶,许志红.基于EMD和PNN的故障电弧多变量判据诊断方法[J].电力自动化设备,2019,39(4): |
| SU Jingjing,XU Zhihong.Diagnosis method of multi-variable criterion based on EMD and PNN for arc fault diagnosis[J].Electric Power Automation Equipment,2019,39(4): |
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| 摘要: |
| 故障电弧单变量判据诊断法受不确定因素影响大、特征量提取困难，针对此提出一种基于经验模态分解(EMD)和概率神经网络(PNN)的故障电弧多变量判据的诊断方法。利用经验模态分解分析法对电弧电流进行时频分解，并借助信号相关性理论自动提取故障特征信号；同时，通过分析故障特征信号的无量纲指标，形成多变量特征向量集。在此基础上，构建基于概率神经网络的故障电弧诊断模型。通过分析燃弧前后烧水壶、吸尘器、卤素灯、电钻、荧光灯、计算机的电流波形，验证故障诊断模型的准确性。结果表明，所提方法解决了单变量判据故障诊断中出现的特征量提取困难、交叉重复等问题，准确率超过90%。 |
| 关键词: 电弧 特征信号提取 经验模态分解 概率神经网络 无量纲指标 多变量判据 模型 |
| DOI：10.16081/j.issn.1006-6047.2019.04.016 |
| 分类号:TM501.2 |
| 基金项目:国家自然科学基金资助项目(51707039)；福建省科技厅产学研合作项目(2016H6008) |
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| Diagnosis method of multi-variable criterion based on EMD and PNN for arc fault diagnosis |
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SU Jingjing, XU Zhihong
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Fujian Key Laboratory of New Energy Generation and Power Conversion, School of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350116, China
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| Abstract: |
| Single-variable criterion methods of arc fault diagnosis are greatly influenced by uncertain factors and difficult to extract the characteristic quantities, aiming at which, a multi-variable criterion based on EMD(Empirical Mode Decomposition) and PNN(Probabilistic Neural Network) is proposed. Time-frequency decomposition of arc current is carried out by EMD analysis method, and the fault characteristic signal is extracted by signal correlation theory automatically. The set of multi-variable characteristic vectors is formed by analyzing the dimensionless index of fault characteristic signals. On this basis, an arc fault diagnosis model based on PNN is established. The accuracy of the proposed model is verified by analyzing current waveforms of kettles, vacuum cleaners, halogen lamps, drills, fluorescent lamps and computers before and after arcing. Results show that the proposed method solves the problems of difficult feature extraction and cross-repetition in single-variable criterion fault diagnosis, and its accurate rate is over 90%. |
| Key words: electric arc characteristic signal extraction EMD PNN dimensionless indicator multi-variable criterion models |
