本文選題：故障電弧 + 傅里葉分析��； 參考：《沈陽(yáng)工業(yè)大學(xué)》2017年碩士論文

【摘要】：自19世紀(jì)人類發(fā)明了電以來(lái),電已經(jīng)得到了很廣泛的應(yīng)用。在現(xiàn)如今人們的生活中家用電器得到了大量的普及,并且還有很多新型的家用電器不斷涌現(xiàn),電氣火災(zāi)的發(fā)生的頻率也越來(lái)越高、造成的危害也越來(lái)越大。這其中故障電弧是引發(fā)火災(zāi)的最主要原因。傳統(tǒng)的保護(hù)電器可以對(duì)相間短路故障和接地短路故障時(shí)進(jìn)行有效的保護(hù),是針對(duì)大電流的過(guò)流保護(hù)。而串聯(lián)故障電弧的特點(diǎn)是電流小,溫度高,持續(xù)時(shí)間短,當(dāng)發(fā)生故障電弧時(shí),傳統(tǒng)的過(guò)流保護(hù)并不能有效的對(duì)線路進(jìn)行保護(hù)。因此,對(duì)串聯(lián)故障電弧進(jìn)行有效的檢測(cè)和識(shí)別具有重要的意義。目前,國(guó)內(nèi)對(duì)低壓故障電弧的研究主要停留在論文階段,幾乎沒(méi)有產(chǎn)品出現(xiàn),而國(guó)外對(duì)于故障電弧的研究要比國(guó)內(nèi)成熟的多,國(guó)外已經(jīng)有AFCI的相關(guān)產(chǎn)品并且已經(jīng)得到了應(yīng)用。國(guó)內(nèi)對(duì)于故障電弧的主要研究方法主要是通過(guò)對(duì)故障電弧電流、電壓波形的特征分析,采用小波分析、傅里葉分析、自回歸參數(shù)模型以及獨(dú)立分量分析等方法分別在時(shí)域和頻域上對(duì)故障電弧進(jìn)行分析。然而由于建筑電氣中具有負(fù)載多樣性的特點(diǎn),有些負(fù)載正常運(yùn)行時(shí)的電流特性和故障電弧電流的特性很相似。此外,很多學(xué)者對(duì)故障電弧電流特性的研究大多采用的單一負(fù)載,對(duì)混合型負(fù)載研究的較少。因此本文根據(jù)國(guó)內(nèi)外的研究成果搭建了故障電弧實(shí)驗(yàn)平臺(tái),采集了多種負(fù)載正常運(yùn)行時(shí)和發(fā)生故障電弧時(shí)的電流波形。通過(guò)對(duì)采集的負(fù)載電流波形進(jìn)行分析,觀察負(fù)載電流正常運(yùn)行時(shí)和發(fā)生故障電弧時(shí)的電流波形的不同點(diǎn)。然后采用MATLAB軟件對(duì)電流波形進(jìn)行傅里葉分析,提取出負(fù)載中正常運(yùn)行時(shí)和發(fā)生故障電弧時(shí)的電流波形的諧波分量,對(duì)兩種情況下的諧波分量進(jìn)行對(duì)比分析,找到其發(fā)生故障電弧時(shí)的特征量,然后通過(guò)spss軟件分別對(duì)其進(jìn)行單參數(shù)的t-分布檢驗(yàn)和k-s檢驗(yàn),確定特征量的分布類型為對(duì)數(shù)正態(tài)分布,然后確定故障電弧判據(jù)的特征量的閾值范圍。由此本文提出了一種基于5次諧波分量的故障電弧識(shí)別方法,為故障電弧的檢測(cè)提供了可靠的參考依據(jù)。
[Abstract]:Electricity has been widely used since the invention of electricity in the 19 th century. Nowadays, the household appliances have been widely used in people's lives, and there are many new types of household appliances, and the frequency of electric fires is higher and higher, and the harm caused is more and more serious. The fault arc is the main cause of the fire. The traditional protective apparatus can effectively protect the interphase short circuit fault and the ground short circuit fault, which is aimed at the overcurrent protection of high current. The characteristics of series fault arc are low current, high temperature and short duration. When fault arc occurs, the traditional over-current protection can not effectively protect the line. Therefore, it is of great significance to detect and identify the series fault arc effectively. At present, the domestic research on low-voltage fault arc mainly stays in the paper stage, almost no products appear, but the foreign research on the fault arc is much more mature than at home. There have been related products of AFCI in foreign countries and have been applied. The main research methods of fault arc in China are the characteristic analysis of fault arc current and voltage waveform, wavelet analysis and Fourier analysis. The autoregressive parameter model and independent component analysis are used to analyze the fault arc in time domain and frequency domain respectively. However, due to the diversity of loads in building electricity, the current characteristics of some loads during normal operation are similar to those of fault arc currents. In addition, many scholars study the characteristics of fault arc current mostly using a single load, and less research on hybrid load. Therefore, based on the domestic and foreign research results, a fault arc experimental platform is built, and the current waveforms of various loads during normal operation and fault arc are collected. Through the analysis of the collected load current waveform, the differences between the load current waveform and the fault arc wave are observed. Then using MATLAB software to carry on the Fourier analysis to the current waveform, extract the harmonic component of the current waveform in the normal operation of the load and the fault arc, and carry on the contrast analysis to the harmonic component of the two kinds of cases. The characteristic quantity of the fault arc is found, and the single parameter t-distribution test and k-s test are carried out by spss software, and the distribution type of the characteristic quantity is determined as logarithmic normal distribution. Then the threshold range of the characteristic quantity of the fault arc criterion is determined. In this paper, a method of fault arc identification based on the fifth harmonic component is proposed, which provides a reliable reference for fault arc detection.
【學(xué)位授予單位】：沈陽(yáng)工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM501.2;TU85

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