引用本文: | 孙晓明,秦亮,刘涤尘.继电保护测试装置线性功率放大器的数字预畸[J].电力自动化设备,2018,(4): |
| SUN Xiaoming,QIN Liang,LIU Dichen.Digital predistortion of linear power amplifier for relay protection test devices[J].Electric Power Automation Equipment,2018,(4): |
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摘要: |
针对继电保护测试装置线性功率放大器(LPA)的非线性,提出一种基于自适应神经-模糊推理系统(ANFIS)的数字预畸器。ANFIS数字预畸器仅需修改软件,即可升级传统继电保护测试装置,不仅满足故障波形重现的精度要求,还能充分利用有限的频带宽度和输出容量。ANFIS数字预畸器对LPA及其负载的整体非线性进行自适应学习,故可降低对单一部件的精度要求,并修正任意部件引起的非线性失真。采用准在线学习方式,ANFIS数字预畸器可在普通微处理器上实现,从而保持传统继电保护测试装置的高性价比。 |
关键词: 继电保护 继电保护测试装置 故障波形重现 线性功率放大器 自适应神经-模糊推理系统 数字预畸 |
DOI:10.16081/j.issn.1006-6047.2018.04.029 |
分类号:TM77 |
基金项目:国家自然科学基金青年科学基金资助项目(5120-7115);重庆市教育委员会科学技术研究项目(KJ1603605);永川区自然科学基金计划项目(Ycstc, 2016nc3001) |
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Digital predistortion of linear power amplifier for relay protection test devices |
SUN Xiaoming1, QIN Liang2, LIU Dichen2
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1.Department of Electrical Engineering, Chongqing Water Resources and Electric Engineering College, Chongqing 402160, China;2.School of Electrical Engineering, Wuhan University, Wuhan 430072, China
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Abstract: |
Aiming at the nonlinearity of LPA(Linear Power Amplifier) in relay protection test devices, a digital predistorter based on ANFIS(Adaptive Neuro-Fuzzy Inference System) is proposed. The ANFIS digital predistorter can upgrade the traditional relay protection test devices only by modifying the software, which can not only satisfy the accuracy requirement of fault waveform regeneration, but also make full use of limited bandwidth and output capacity. Also, the ANFIS digital predistorter adaptively learns the total nonlinearity of both LPA and the load, so the accuracy requirement of a single element is reduced and the nonlinear error caused by any element can be modified. With the quasi-online learning mode, the ANFIS digital predistorter can be realized on general microprocessors, thus maintaining the high cost effective ratio of traditional protection relay test devices. |
Key words: relay protection relay protection test device fault waveform regeneration linear power amplifier adaptive neuro-fuzzy inference system digital predistortion |