【摘要】：在現(xiàn)代科技不斷進(jìn)步的過程中,電能在人類活動(dòng)各個(gè)方面都具有著不可取代的地位,與此同時(shí),這把雙刃劍也帶給了人類許許多多的危害和麻煩。在人類的活動(dòng)過程中一旦操控過度的電子器件,就會(huì)讓電子網(wǎng)絡(luò)系統(tǒng)處于崩壞瓦解狀態(tài),也就會(huì)讓使用電的團(tuán)體或個(gè)人產(chǎn)生嚴(yán)重的被動(dòng)浪費(fèi)現(xiàn)象。由此可知,如果能夠把實(shí)時(shí)監(jiān)控電路,測(cè)量相關(guān)指標(biāo)這一目標(biāo)實(shí)現(xiàn),將會(huì)帶來很多收益,以此,這一目標(biāo)也將成為現(xiàn)在學(xué)者的首要科研項(xiàng)目。因?yàn)閷?shí)現(xiàn)這一目標(biāo)的關(guān)鍵在于對(duì)相關(guān)信號(hào)的關(guān)注,導(dǎo)致很多很火的現(xiàn)代信號(hào)相關(guān)專業(yè)的途徑與上述目標(biāo)相結(jié)合,已經(jīng)順利的走向佳境。提高電能質(zhì)量首要辦法是要獲取并且減弱電能質(zhì)量中的噪聲存在,這樣才能使得獲取的結(jié)果總有更大的真實(shí)性。這篇文章將在這一方面開展詳細(xì)的探討。第一步,文章將會(huì)對(duì)原來已經(jīng)存在的獲取結(jié)果的途徑開展詳細(xì)的說明介紹。正式因?yàn)檫@些已存在的途徑的存在能足夠讓我們獲取相對(duì)真實(shí)完美的電能質(zhì)量參數(shù)。第二步,這篇文章將會(huì)展現(xiàn)一種處理數(shù)據(jù),分析數(shù)據(jù)的理論,也就是集合卡爾曼濾波法的電能質(zhì)量獲取方法。這個(gè)理論在出現(xiàn)的同時(shí)就馬上被運(yùn)用于各方各面的人類活動(dòng)領(lǐng)域,正是因?yàn)檫@個(gè)理論的運(yùn)算步驟處理迅猛,可以檢測(cè)到單獨(dú)的參數(shù)等優(yōu)勢(shì)。在我們檢測(cè)獲取的過程中,噪聲變化很大,并且沒有規(guī)律可循,這就加大了我們減弱處理噪聲的難度。第三步,這篇文章將會(huì)對(duì)上述處理信號(hào)途徑的背景集合開展創(chuàng)新概念,讓這種方法能更好的運(yùn)用在我們收集采集數(shù)據(jù)過程中。具體步驟是要求我們先獲有一時(shí)刻的背景合集。然后可以通過一系列的運(yùn)算,對(duì)結(jié)果進(jìn)行真實(shí)還原。再利用物理上的觀察運(yùn)算,我們可以檢測(cè)到噪聲的變化,從而描述出噪聲的開始,結(jié)束,變化最大值,最后通過減弱噪聲等方法開展電能質(zhì)量的探討和真實(shí)還原。先用一個(gè)特定的工作系統(tǒng)對(duì)上述的處理途徑開展測(cè)定與深入評(píng)估后發(fā)現(xiàn):上述途徑可以完成較為出色的工作,即可以提供給我們較為完整的噪聲動(dòng)態(tài),也就是在追溯起源,探究進(jìn)展,測(cè)量數(shù)量方面都有著很好的工作成效。在這片論文的結(jié)尾部分還提供了一個(gè)有所創(chuàng)新的事物——LabVIEW.這個(gè)工程在進(jìn)行測(cè)試后可以得知工作性能完好。
[Abstract]:In the process of continuous progress of modern science and technology, electric energy plays an irreplaceable role in all aspects of human activities, at the same time, this double-edged sword also brings a lot of harm and trouble to mankind. In the course of human activities, once the electronic devices are manipulated excessively, the electronic network system will be in a state of collapse and disintegration, which will also cause a serious passive waste of electricity to groups or individuals. It can be seen that if we can realize the goal of real-time monitoring circuit and measuring related indicators, it will bring a lot of benefits, and this goal will also become the primary research project of scholars now. Because the key to achieve this goal is to pay attention to the related signals, leading to a lot of hot modern signal related professional approaches to combine with the above goals, has been smooth to the good environment. The first way to improve power quality is to obtain and reduce the presence of noise in power quality, so that the obtained results are always more authentic. This article will be discussed in detail in this respect. As a first step, the article will introduce the existing ways of obtaining results in detail. Officially because of the existence of these existing channels can allow us to obtain relatively real and perfect power quality parameters. In the second step, this paper will show a theory of data processing and data analysis, that is, the power quality acquisition method based on set Kalman filter. At the same time, this theory has been applied to the field of human activities on all sides. It is precisely because of the rapid processing of the operation steps of this theory, it can detect the advantages of individual parameters and so on. In the process of detection and acquisition, the noise changes greatly and there is no rule to follow, which makes it more difficult for us to reduce the noise. In the third step, this article will develop an innovative concept of the background set of the above signal processing pathways, so that this method can be used better in the collection of data. The concrete step is to require us to first have a set of background at a time. Then through a series of operations, the results can be truly restored. Using the physical observation operation, we can detect the change of noise, and then describe the beginning, end and maximum change of noise. Finally, we can discuss and restore the real power quality by means of reducing noise and so on. First of all, a specific working system was used to test and evaluate the above processing routes. It was found that the above approaches can accomplish better work, that is, they can provide us with more complete noise dynamics, that is, in tracing the origin. Research progress and quantitative measurement have had good results. At the end of the paper, there is something innovative about LabVIEW.LabVIEW. After testing the project, we can see that the working performance is in good condition.
【學(xué)位授予單位】：湖北工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM711;TM930

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 李功新;周文俊;薛尚青;江修波;;動(dòng)態(tài)電壓恢復(fù)器的無跡卡爾曼濾波檢測(cè)方法[J];電力系統(tǒng)保護(hù)與控制;2013年16期

2 李冬明;高璽亮;王文龍;肖洋;;基于LabVIEW和Matlab綜合平臺(tái)的電能質(zhì)量監(jiān)測(cè)系統(tǒng)研究[J];電測(cè)與儀表;2012年03期

3 王靜;;電壓有效值測(cè)量[J];西安郵電學(xué)院學(xué)報(bào);2011年S1期

4 杜航原;郝燕玲;趙玉新;;基于集合卡爾曼濾波的改進(jìn)粒子濾波算法[J];系統(tǒng)工程與電子技術(shù);2011年07期

5 魯波涌;黃文清;;結(jié)合小波變換和能量算子的電壓暫降檢測(cè)方法[J];電工技術(shù)學(xué)報(bào);2011年05期

6 吳國(guó)燦;鄭小谷;李勇;;非線性觀測(cè)算子的集合卡爾曼濾波的改進(jìn)[J];北京師范大學(xué)學(xué)報(bào)(自然科學(xué)版);2010年06期

7 王效孟;周勇;劉繼承;林烽;;檢測(cè)電壓暫降特征量的有效值算法[J];低壓電器;2010年10期

8 崔利娜;林曉梅;黃艷秋;;S3C2410在電能質(zhì)量監(jiān)測(cè)分析儀中的應(yīng)用研究[J];電測(cè)與儀表;2010年02期

9 秦英林;田立軍;;短時(shí)電壓擾動(dòng)檢測(cè)與定位新方法[J];電力系統(tǒng)保護(hù)與控制;2010年04期

10 周龍華;付青;余世杰;李湘峰;;基于小波變換的諧波檢測(cè)技術(shù)[J];電力系統(tǒng)及其自動(dòng)化學(xué)報(bào);2010年01期

相關(guān)碩士學(xué)位論文 前10條

1 周輝;動(dòng)態(tài)海洋環(huán)境下聲速剖面的反演方法研究[D];浙江大學(xué);2013年

2 惠雪峰;基于集合卡爾曼濾波的森林資源動(dòng)態(tài)預(yù)測(cè)[D];南京林業(yè)大學(xué);2012年

3 宋敏;基于DSP和嵌入式平臺(tái)的在線電能質(zhì)量監(jiān)測(cè)系統(tǒng)設(shè)計(jì)[D];上海交通大學(xué);2012年

4 于子寇;基于 LabVIEW 的風(fēng)電場(chǎng)電能質(zhì)量網(wǎng)絡(luò)監(jiān)測(cè)系統(tǒng)[D];燕山大學(xué);2012年

5 王瑜;基于DSP的電能質(zhì)量檢測(cè)儀的研制[D];西南交通大學(xué);2011年

6 曾滔;基于TMS320F2812的電能質(zhì)量檢測(cè)系統(tǒng)設(shè)計(jì)[D];廈門大學(xué);2009年

7 喬小n\;雙分辨率集合卡爾曼濾波方法的研究[D];蘭州大學(xué);2009年

8 張希;基于LabVIEW的電能質(zhì)量監(jiān)測(cè)系統(tǒng)[D];西安科技大學(xué);2009年

9 劉濤;基于虛擬儀器技術(shù)的電能質(zhì)量在線檢測(cè)技術(shù)研究[D];南京理工大學(xué);2008年

10 余希木;基于Kalman濾波的動(dòng)態(tài)電能質(zhì)量監(jiān)測(cè)[D];四川大學(xué);2006年

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