基于函数型数据分析算法的电阻性本质安全电路电弧放电模型

doi:10.19595/j.cnki.1000-6753.tces.230161

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摘要

区别于电感性和电容性本质安全电路,电阻性本质安全电路的电弧放电波形因具有三种类型而一直无法被准确描述,且电阻性电路本质安全判据的不完善描述会导致实际运行条件下爆炸事故的多发性。对此,该文考虑电阻性本质安全电路的放电过程及波形特征,基于函数型数据分析回归算法,建立了高维、参数强相关、适用范围广的电阻性电路电弧放电数学模型,并基于模型建立了相应的本质安全能量判据。采用该模型模拟电阻性电路放电过程并提出一种电弧放电波形分类方法,发现在特定电路参数条件下,当电路正常工作电流I≤0.15 A或I≥0.6 A时,电弧放电基本呈现典型放电形式。最后搭建火花放电试验平台,验证了所建电弧模型的可行性与预测效果的准确性。

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	朱冉
	徐礼文
	孟庆海

关键词 ：电弧放电数学模型, 本质安全, 函数型数据, 能量判据

Abstract：

Different from the traditional inductive and capacitive intrinsically safe circuits, the resistive intrinsically safe circuit is difficult to describe accurately due to its three different discharge waveforms. The experimental waveform and theoretical analysis show that the arc of the resistive circuit has multi-dimensional characteristics, and there is a strong correlation between it and environmental factors. It is difficult to solve it directly by traditional modeling methods, which makes the intrinsic safety criterion of the resistive circuit lack a complete theoretical system, resulting in multiple accidents in the actual operating environment. In order to solve such problems, this paper proposes a discharge model based on functional data analysis regression algorithm on the basis of studying the arc discharge characteristic curve of resistive intrinsically safe circuit, and establishes the arc discharge energy criterion of resistive intrinsically safe circuit based on this model.
Firstly, the functional data analysis regression algorithm framework is constructed, and the mathematical models of arc discharge voltage and current are established respectively based on the three essential different discharge waveform characteristics of low energy arc discharge when the electrode of IEC spark test device is disconnected. Secondly, a power model independent of voltage and current model is proposed theoretically. Based on the power model, the energy criterion of resistive intrinsically safe circuit is supplemented. The model is simulated by MATLAB software and a classification method of arc discharge waveform is proposed. Finally, a spark discharge test platform is built to verify the feasibility of the arc model and the accuracy of the prediction effect. The model does not require any restrictions on the frequency of data acquisition, and converts the dynamic function curve into ' original data ', which has infinite dimensional spatial characteristics and reduces the error caused by the simplification of the formula in the derivation process. The comparison between the experimental data and the simulation results shows that under the experimental conditions carried out in this paper, at least 80% of the actual data of the three different discharge waveforms can be described by the model, which proves the feasibility and universality of the functional data analysis regression model. The evaluation of the prediction effect of the discharge model established by the functional data analysis regression algorithm shows that at least 87% of the actual data can be predicted by the arc voltage, current and power model under the test conditions in this paper. It solves the problem that the arc discharge waveform of resistive intrinsically safe circuit cannot be accurately described because of three types. In addition, the model is used to explore the circuit parameter conditions of three cases of arc discharge in resistive circuits. It is found that under the condition of the power supply voltage parameter of 24 V≤E≤48 V and the resistance range of 20 Ω≤R≤360 Ω, when the normal working current of the circuit is I≤0.15 A or I≥0.6 A, the arc discharge is characterized by an early increase in power ; when the normal operating current value is 0.15 A<I<0.6 A, the arc discharge is characterized by the initial power basically unchanged and the later rapid decline.
Through simulation and experimental results, the following conclusions are drawn: (1) The proposed functional data analysis arc model solves the problem that the arc discharge waveform of the resistive intrinsically safe circuit cannot be accurately described due to three types. (2) The proposed model uses the idea of functional data analysis to transform the dynamic function curves of different characteristics into ' original data ' for analysis, which reduces the error caused by formula simplification. (3) Compared with the traditional model, the proposed model can predict the discharge arc voltage and current values at different discharge times, which solves the problem that the traditional model cannot explore the numerical solution.

Key words： Arc discharge mathematical model intrinsic safety functional data energy criterion

PACS:	TD685
	TM133

通讯作者: 孟庆海男,1986年生,研究员,研究方向为电气安全技术。E-mail：mengqinghai@ncut.edu.cn

作者简介: 朱冉女,1999年生,硕士研究生,研究方向为电气安全技术。E-mail：2602440779@qq.com

引用本文:

朱冉, 徐礼文, 孟庆海. 基于函数型数据分析算法的电阻性本质安全电路电弧放电模型[J]. 电工技术学报, 0, (): 230161-230161. Zhu Ran, Xu Liwen, Meng Qinghai. Research on Arc Discharge Model of Resistive Intrinsically Safe Circuit Based on Functional Data Analysis Algorithm. Transactions of China Electrotechnical Society, 0, (): 230161-230161.

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