基于STM32的故障电弧检测装置设计

佟为明; 佟春天; 金显吉

doi:10.11884/HPLPB201931.180320

基于STM32的故障电弧检测装置设计

doi: 10.11884/HPLPB201931.180320

哈尔滨工业大学电气工程系，哈尔滨 150000

基金项目:

哈尔滨市应用技术研究与开发项目 2017RAXXJ005

国家国际科技合作重大项目 2011DFR70910

详细信息

作者简介:
佟为明(1964—)，男，教授，博士，研究方向为智能电网通信与信息安全技术、开关电源与谐波抑制等；dianqi@hit.edu.cn

中图分类号: TM501.2
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- 被引次数: 0
出版历程
- 收稿日期: 2018-11-14
- 修回日期: 2019-02-18
- 刊出日期: 2019-03-15

Design of fault arc detection device based on STM32

Department of Electrical Engineering, Harbin Institute of Technology, Harbin 150000, China

摘要

摘要: 检测负载电流信号特征是判断低压配电线路中是否发生电弧故障的有效方法之一。依据国家标准GB/T 31143-2014《电弧故障保护电器(AFDD)的一般要求》，搭建模拟串联故障电弧实验平台，研究故障电弧发生时电流波形的特征，并采用db4小波函数作为小波基函数，对降噪后的电流波形进行小波分解重构，提取小波高频分量，计算小波高频分量的周期方差值，将周期方差值作为主要特征值来进行电弧故障检测；为了在硬件上验证该检测算法的可行性和有效性，将电弧故障检测算法移植到STM32平台，设计了基于STM32的故障电弧检测装置，该装置可以实现电流信号采集、数据处理和串联电弧故障检测识别功能。在以阻性负载、LED灯、吸尘器和微波炉为屏蔽负载的实验结果表明，该装置能够检测出串联电弧故障，且可靠性高，不会在没有产生故障电弧的情况下产生误判。
- 故障电弧检测 /
- 小波函数 /
- 特征量 /
- 周期方差值 /
- STM32
Abstract: The detection of the load current signal is one of the effective methods for judging whether an arc fault occurs in the low-voltage distribution line; according to the national standard GB/T 31143-2014 "General Requirements for Arc Fault Protection Devices (AFDD)", the analog series fault arc is built. The experimental platform studies the characteristics of the current waveform when the fault arc occurs. The db4 wavelet function is used as the wavelet basis function to decompose and reconstruct the current waveform after noise reduction, and extract the wavelet high-frequency component, calculate the periodic variance value of the wavelet high-frequency component, and detect the arc fault according to this value; The feasibility and effectiveness of the detection algorithm are verified. The arc fault detection algorithm is transplanted to the STM32 platform, and the fault arc detection device based on STM32 is designed. The device can realize the functions of current signal acquisition, data processing and series arc fault detection and recognition. Experiments with resistive loads, LED light, vacuum cleaners and microwave ovens have shown that the device can detect series arc faults with high reliability and will not cause false positives without generating fault arcs.
- fault arc detection /
- wavelet function /
- feature amount /
- period variance /
- STM32

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图 1 小波高频分量周期方差值

Figure 1. Wavelet high frequency component period variance value

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图 2 故障电弧检测装置硬件总体设计框图

Figure 2. Block diagram of the overall design of the fault arc detection device hardware

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图 3 电流信号调理电路

Figure 3. Current and voltage signal conditioning circuit

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图 4 AD转换电路图

Figure 4. Diagram of AD conversion circuit

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图 5 以太网接口电路

Figure 5. Ethernet interface circuit

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图 6 故障电弧检测装置软件总体设计框图

Figure 6. Block diagram of faulty arc detection device software overall design

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图 7 故障电弧检测程序流程图

Figure 7. Flow chart of fault arc detection program

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表 1 故障电弧特征值对比

Table 1. Fault arc characteristic value comparison

working conditions		normal	arc weak	arc fierce
resistive load	high frequency range	[-0.0227, 0.0239]	[-0.3133, 0.2814]	[-0.9264, 0.8209]
	volatility	3.010 7×10^-5	1.951 3×10^-4	9.273 5×10^-4
	period variance range	[0, 0.01]	[0.02, 0.16]	[0.02, 0.25]
inductive load	high frequency range	[-0.0245, 0.0236]	[-0.1410, 0.1451]	[-0.3725, 0.3669]
	volatility	2.914 5×10^-5	1.677 5×10^-4	2.544 2×10-^-4
	period variance range	[0, 0.0005]	[0.001, 0.007]	[0.002, 0.011]
capacitive load	high frequency range	[-0.020 5, 0.0215]	[-0.1235, 0.1217]	[-0.5843, 0.664]
	volatility	2.962 4×10^-5	2.544 2×10^-4	3.015 2×10^-4
	period variance range	[0, 0.0005]	[0.002, 0.01]	[0.002, 0.015]

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表 2 固定负载检测结果

Table 2. Fixed load test results

load type	successful recognition rate/%	failure rate/%
resistive load	100	0
vacuum cleaner	99	1
LED light	98	2
microwave oven	99	1

下载: 导出CSV

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