發(fā)布時間：2018-01-23 03:08

  本文關(guān)鍵詞： 變壓器 局部放電 超聲波 定位 粒子群算法　出處：《長沙理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：在電力系統(tǒng)中,大型電力變壓器的絕緣狀況影響著整個系統(tǒng)的安全穩(wěn)定運(yùn)行,變壓器產(chǎn)生的故障大部分是由于變壓器局部放電所引起的,而變壓器絕緣介質(zhì)的劣化是引起局部放電的主要原因,對絕緣狀態(tài)主要根據(jù)絕緣介質(zhì)在劣化過程中的一些特征參數(shù)來進(jìn)行評定,包括電容量、泄漏電流、局部放電等,其中局部放電主要反映了絕緣介質(zhì)的局部狀況,在絕緣檢測中具有不可替代的作用,因此對變壓器局部放電檢測和定位也是電力部門的重點(diǎn)工作之一。超聲波定位法是局部放電檢測和定位的最傳統(tǒng)也是最主要的方法,而超聲波定位法的關(guān)鍵環(huán)節(jié)就是定位算法問題。論文對超聲波定位法及定位算法做了較深入的研究。論文首先分析了變壓器局部放電產(chǎn)生原因及特點(diǎn),同時對局部放電產(chǎn)生超聲波的機(jī)理進(jìn)行研究,并對超聲波在變壓器內(nèi)部傳播的衰減情況及速度進(jìn)行測量,為超聲波定位提供可靠的依據(jù)；其次深入研究了超聲定位算法,針對基本粒子群算法存在的缺點(diǎn)對其進(jìn)行改進(jìn),提出了自適應(yīng)粒子群算法,此算法能很好的克服基本粒子群算法容易陷入局部最優(yōu)的缺點(diǎn),并將自適應(yīng)粒子群算法應(yīng)用到超聲定位中；論文最后建立了超聲定位的數(shù)學(xué)模型,并且將其轉(zhuǎn)化為一種帶約束條件的優(yōu)化問題,然后通過設(shè)計的檢測系統(tǒng)以及現(xiàn)場檢測的數(shù)據(jù)對變壓器局部放電點(diǎn)進(jìn)行定位。
[Abstract]:In the power system, the insulation condition of the large power transformer affects the safe and stable operation of the whole system. The fault caused by the transformer is mostly caused by the partial discharge of the transformer. The deterioration of insulation medium of transformer is the main cause of partial discharge. The insulation state is mainly assessed according to some characteristic parameters of insulation medium in the process of deterioration, including capacitance, leakage current. Partial discharge, among which partial discharge mainly reflects the partial condition of insulating dielectric, plays an irreplaceable role in insulation detection. Therefore, the detection and location of transformer partial discharge is also one of the key tasks in the power sector. Ultrasonic localization is the most traditional and main method of partial discharge detection and location. The key link of ultrasonic positioning is the localization algorithm. This paper makes a deep research on the ultrasonic positioning method and location algorithm. Firstly, this paper analyzes the causes and characteristics of transformer partial discharge. At the same time, the mechanism of ultrasonic wave produced by partial discharge is studied, and the attenuation and velocity of ultrasonic wave propagation in transformer are measured, which provides a reliable basis for ultrasonic positioning. Secondly, the ultrasonic localization algorithm is deeply studied, and the adaptive particle swarm optimization algorithm is proposed to improve the basic particle swarm optimization algorithm. This algorithm can overcome the shortcoming that the basic particle swarm optimization is easy to fall into local optimum, and the adaptive particle swarm optimization algorithm is applied to ultrasonic localization. At last, the mathematical model of ultrasonic localization is established and transformed into an optimization problem with constraints. Then the partial discharge point of transformer is located by the designed detection system and the field detection data.
【學(xué)位授予單位】：長沙理工大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM41
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本文編號：1456528