【摘要】：電力變壓器是一種靜止的電氣設(shè)備,用來將某一數(shù)值的交流電壓變成頻率相同的另一種或幾種數(shù)值不同的電壓的設(shè)備。它是電力系統(tǒng)中的關(guān)鍵設(shè)備,其是否平安可靠運行關(guān)系著整個電網(wǎng)的平安運行。近些年來,基于振動信號來對變壓器進(jìn)行故障診斷的方法已經(jīng)初具雛形,本文是通過分析傳感器傳輸過來的振動信號來進(jìn)一步的提取特征量,并依據(jù)提取到的特征量來評估變壓器的工作狀況。大量實驗結(jié)果顯示:當(dāng)變壓器發(fā)生故障的時候,其振動信號并不是處在平穩(wěn)狀態(tài),而是非平穩(wěn)狀態(tài)。如何對非平穩(wěn)信號進(jìn)行分析,本文采用小波分析方法來進(jìn)行分析,但是目前基于小波分析的變壓器振動信號故障診斷方法存在一個缺陷,就是它有一個前提條件,認(rèn)為小波分解的系數(shù)符合高斯分布,在實際情況中并非如此,小波變換存在著一種壓縮特性,大多數(shù)的能量只是存在于一小部分的小波系數(shù)中,這與高斯分布的特性有明顯的差異。本文首先對變壓器故障的產(chǎn)生機理進(jìn)行闡述,提出小波變換的分析方法,總結(jié)了小波變換的理論基礎(chǔ)知識,然后,建立變壓器振動模型,將信號分成適當(dāng)?shù)膸追N故障類型。在進(jìn)行故障診斷時,先采用能量譜故障分析方法對信號進(jìn)行故障診斷。然后建立小波域的廣義高斯模型,根據(jù)廣義高斯分布的概率密度函數(shù)對信號進(jìn)行擬合,提取小波系數(shù)的廣義高斯分布的參數(shù)作為特征量對信號進(jìn)行故障診斷并結(jié)合支持向量機對信號進(jìn)行了分類。之后在考慮小波系數(shù)相關(guān)性的時候,結(jié)合能量譜和建立的小波域隱性馬爾可夫模型對信號進(jìn)行故障診斷。最后在VC上實現(xiàn)小波變換和相應(yīng)能量的計算,并且在VC上實現(xiàn)故障信號的診斷。
[Abstract]:Power transformer is a kind of static electrical equipment, which is used to change a certain value of AC voltage into another or several kinds of voltage with the same frequency. It is the key equipment in the power system, and its safe and reliable operation is related to the safe operation of the whole power grid. In recent years, the method of fault diagnosis of transformer based on vibration signal has begun to take shape. In this paper, the feature quantity is further extracted by analyzing the vibration signal transmitted by sensor, and the working condition of transformer is evaluated according to the extracted feature quantity. A large number of experimental results show that when the transformer fails, the vibration signal is not in a stationary state, but in a non-stationary state. In this paper, wavelet analysis method is used to analyze the non-stationary signal, but there is a defect in the fault diagnosis method of transformer vibration signal based on wavelet analysis, that is, it has a prerequisite. It is considered that the coefficient of wavelet decomposition accords with Gaussian distribution, which is not the case in practice, and there is a compression characteristic of wavelet transform. Most of the energy only exists in a small part of wavelet coefficients, which is obviously different from the characteristics of Gaussian distribution. In this paper, the mechanism of transformer fault is described, the analysis method of wavelet transform is put forward, and the theoretical basic knowledge of wavelet transform is summarized. Then, the vibration model of transformer is established and the signal is divided into several appropriate fault types. In the fault diagnosis, the energy spectrum fault analysis method is used to diagnose the signal. Then the generalized Gaussian model in wavelet domain is established, and the signal is fitted according to the probability density function of the generalized Gaussian distribution. The parameters of the generalized Gaussian distribution of the wavelet coefficient are extracted as the characteristic quantity to carry on the fault diagnosis to the signal, and the signal is classified by the support vector machine. Then, when considering the correlation of wavelet coefficients, the energy spectrum and the hidden Markov model in wavelet domain are combined to diagnose the fault of the signal. Finally, wavelet transform and corresponding energy calculation are realized on VC, and fault signal diagnosis is realized on VC.
【學(xué)位授予單位】：哈爾濱工程大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TM41

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