低壓交流串聯(lián)電弧故障檢測(cè)
發(fā)布時(shí)間：2018-08-26 12:51
【摘要】：能源互聯(lián)網(wǎng)快速發(fā)展,電能的生產(chǎn)與利用方式越來(lái)越多樣,現(xiàn)有電力系統(tǒng)電氣保護(hù)體系中遺留的漏洞愈加凸顯。交流串聯(lián)電弧故障ASAF,作為現(xiàn)有電氣保護(hù)漏洞,尚未得到合理解決,由其導(dǎo)致的安全事故頻發(fā)。實(shí)時(shí)準(zhǔn)確檢測(cè)ASAF,并切斷故障電路是避免電弧持續(xù)燃燒以釀成火災(zāi)等事故的有效途徑。自主搭建實(shí)驗(yàn)平臺(tái),通過示波器采集實(shí)驗(yàn)電路電流傳感器輸出電壓信號(hào)OVSCS,獲得研究數(shù)據(jù)。數(shù)字化和智能化的ASAF檢測(cè)算法主要由特征提取算法和故障識(shí)別算法組成。采用短時(shí)過零分析提取ASAF發(fā)生時(shí)OVSCS短時(shí)過零率特征。為降低噪聲對(duì)提取結(jié)果的干擾,并最大限度提取有效特征,應(yīng)用信息熵理論優(yōu)化降噪閾值。為彌補(bǔ)短時(shí)過零分析不能保留OVSCS幅度信息的短板,采用多個(gè)降噪閾值提取OVSCS短時(shí)過零率,構(gòu)成OVSCS短時(shí)過零率矩陣。設(shè)計(jì)模式匹配和隱馬爾可夫模型HMM相結(jié)合的方法實(shí)現(xiàn)ASAF識(shí)別。為降低識(shí)別算法計(jì)算復(fù)雜度和建模難度,根據(jù)實(shí)驗(yàn)觀察結(jié)果,定義ASAF在3種不同時(shí)間尺度下所表現(xiàn)出的狀態(tài),并依次經(jīng)信號(hào)分幀、模式匹配、HMM識(shí)別、宏觀狀態(tài)判別4個(gè)過程完成ASAF識(shí)別。以低成本微控制器為硬件核心,以檢測(cè)算法為軟件基礎(chǔ),設(shè)計(jì)與實(shí)現(xiàn)電弧故障檢測(cè)裝置AFDD和ASAF檢測(cè)試驗(yàn)裝置。所實(shí)現(xiàn)AFDD體積小,成本低,使用附加條件少。所實(shí)現(xiàn)試驗(yàn)裝置具有高精度調(diào)節(jié)電弧電極間距、自動(dòng)重復(fù)實(shí)驗(yàn)、判別ASAF發(fā)生類型的功能。設(shè)計(jì)實(shí)驗(yàn)測(cè)試所實(shí)現(xiàn)AFDD。實(shí)驗(yàn)結(jié)果表明所設(shè)計(jì)AFDD在不間斷供電工作狀態(tài)下,可實(shí)時(shí)、準(zhǔn)確檢測(cè)ASAF,并可處理偶發(fā)交流串聯(lián)電弧故障AASAF,且可靠性良好,發(fā)生“好弧”時(shí)不誤判。
[Abstract]:With the rapid development of the energy Internet, the production and utilization of electric energy is becoming more and more diverse, and the loopholes left over in the existing electrical protection system of power system are becoming more and more prominent. As an existing electrical protection loophole, AC series arc fault (ASAF,) has not been solved reasonably, and the safety accidents caused by it occur frequently. Detecting ASAF, in real time and cutting off the fault circuit is an effective way to avoid continuous arc burning and lead to fire accidents. The experiment platform is built independently, and the research data are obtained by using oscilloscope to collect the output voltage signal of the current sensor of the experimental circuit by OVSCS,. Digital and intelligent ASAF detection algorithm is mainly composed of feature extraction algorithm and fault identification algorithm. Short-time zero-crossing analysis was used to extract the characteristics of short-time zero-crossing rate of OVSCS when ASAF occurred. In order to reduce the interference of the noise to the extraction results and extract the effective features to the maximum extent, the information entropy theory is applied to optimize the threshold of noise reduction. In order to make up for the short board whose OVSCS amplitude information can not be retained in short time zero crossing analysis, OVSCS short time zero crossing rate is extracted by using multiple noise reduction thresholds, which constitutes the OVSCS short time zero crossing rate matrix. Design pattern matching and hidden Markov model (HMM) are combined to realize ASAF recognition. In order to reduce the computational complexity and modeling difficulty of the recognition algorithm, the state of ASAF under three different time scales is defined according to the experimental results. ASAF recognition is completed by four processes of macroscopic state discrimination. The low cost microcontroller is used as the hardware core and the detection algorithm is used as the software base to design and implement the arc fault detection devices AFDD and ASAF. The realized AFDD is small in size, low in cost and less in additional conditions. The experimental device has the function of adjusting arc electrode spacing with high precision, automatically repeating experiments and discriminating the occurrence types of ASAF. Design and Test Institute to implement AFDD. The experimental results show that the designed AFDD can detect ASAF, in real time and accurately under the condition of uninterrupted power supply, and can deal with occasional AC series arc fault AASAF, with good reliability and no misjudgment when "good arc" occurs.
【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
本文編號(hào)：2204923
[Abstract]:With the rapid development of the energy Internet, the production and utilization of electric energy is becoming more and more diverse, and the loopholes left over in the existing electrical protection system of power system are becoming more and more prominent. As an existing electrical protection loophole, AC series arc fault (ASAF,) has not been solved reasonably, and the safety accidents caused by it occur frequently. Detecting ASAF, in real time and cutting off the fault circuit is an effective way to avoid continuous arc burning and lead to fire accidents. The experiment platform is built independently, and the research data are obtained by using oscilloscope to collect the output voltage signal of the current sensor of the experimental circuit by OVSCS,. Digital and intelligent ASAF detection algorithm is mainly composed of feature extraction algorithm and fault identification algorithm. Short-time zero-crossing analysis was used to extract the characteristics of short-time zero-crossing rate of OVSCS when ASAF occurred. In order to reduce the interference of the noise to the extraction results and extract the effective features to the maximum extent, the information entropy theory is applied to optimize the threshold of noise reduction. In order to make up for the short board whose OVSCS amplitude information can not be retained in short time zero crossing analysis, OVSCS short time zero crossing rate is extracted by using multiple noise reduction thresholds, which constitutes the OVSCS short time zero crossing rate matrix. Design pattern matching and hidden Markov model (HMM) are combined to realize ASAF recognition. In order to reduce the computational complexity and modeling difficulty of the recognition algorithm, the state of ASAF under three different time scales is defined according to the experimental results. ASAF recognition is completed by four processes of macroscopic state discrimination. The low cost microcontroller is used as the hardware core and the detection algorithm is used as the software base to design and implement the arc fault detection devices AFDD and ASAF. The realized AFDD is small in size, low in cost and less in additional conditions. The experimental device has the function of adjusting arc electrode spacing with high precision, automatically repeating experiments and discriminating the occurrence types of ASAF. Design and Test Institute to implement AFDD. The experimental results show that the designed AFDD can detect ASAF, in real time and accurately under the condition of uninterrupted power supply, and can deal with occasional AC series arc fault AASAF, with good reliability and no misjudgment when "good arc" occurs.
【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
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，本文編號(hào)：2204923
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