【摘要】：隨著中國(guó)經(jīng)濟(jì)飛速發(fā)展,人們?cè)絹碓疥P(guān)注生活的品質(zhì)。降低變電站噪聲,可以減輕噪聲對(duì)周圍群眾生活的干擾,大幅提升其生活質(zhì)量。有源噪聲控制系統(tǒng)能有針對(duì)性的降低變電站低頻噪聲,因此,簡(jiǎn)單、經(jīng)濟(jì)、有效的有源降噪系統(tǒng)在電力變壓器噪聲控制領(lǐng)域有著廣闊應(yīng)用前景。目前,大部分研究以線性系統(tǒng)為基礎(chǔ),該系統(tǒng)收斂速度與穩(wěn)態(tài)誤差之間存在不可調(diào)和的矛盾,而且在實(shí)際運(yùn)行中,控制系統(tǒng)中不可避免的存在非線性因素,使這類線性系統(tǒng)的控制性能大打折扣。如果能解決系統(tǒng)中的非線性問題,有源降噪系統(tǒng)就能夠選用含有非線性失真的低價(jià)電聲器件,不僅能提高降噪性能,對(duì)降低系統(tǒng)的成本同樣具有特殊意義。因此,論文以國(guó)家自然科學(xué)基金項(xiàng)目《基于內(nèi)�？刂频年嚵惺诫娏ψ儔浩饔性聪暭夹g(shù)研究》為依托,對(duì)電力變壓器非線性有源噪聲控制技術(shù)及系統(tǒng)收斂速度與穩(wěn)態(tài)誤差的協(xié)調(diào)方法進(jìn)行了研究。論文針對(duì)系統(tǒng)收斂速度與穩(wěn)態(tài)誤差之間的矛盾,將凸組合濾波器引入有源噪聲控制系統(tǒng),對(duì)該結(jié)構(gòu)所采用的組合算法及系統(tǒng)穩(wěn)定性、收斂速度、穩(wěn)態(tài)誤差進(jìn)行了詳細(xì)的理論推導(dǎo),理論證明組合算法能夠兼顧穩(wěn)態(tài)誤差與收斂速度取得良好的綜合性能。分別對(duì)目前非線性噪聲控制系統(tǒng)中采用的兩種主流方法進(jìn)行了研究,一種是基于函數(shù)連接型神經(jīng)網(wǎng)絡(luò)(FLANN)的方法,另一種是基于Volterra濾波器的方法。分別闡述了它們的控制系統(tǒng)基本結(jié)構(gòu)及經(jīng)典算法,并做了可行性分析。分別將這兩種濾波器的組合結(jié)構(gòu)引入非線性有源噪聲控制系統(tǒng),并對(duì)它們采用的組合算法進(jìn)行了理論推導(dǎo),針對(duì)傳統(tǒng)組合算法在收斂過程中出現(xiàn)的停滯現(xiàn)象,采用附加瞬時(shí)轉(zhuǎn)移結(jié)構(gòu)對(duì)算法進(jìn)行優(yōu)化。研究發(fā)現(xiàn)FLANN結(jié)構(gòu)具有結(jié)構(gòu)簡(jiǎn)單、計(jì)算量較小等優(yōu)點(diǎn),主要應(yīng)用于非線性程度較弱的情況。而Volterra濾波器具有較強(qiáng)的非線性處理能力,但核函數(shù)的數(shù)目和計(jì)算量都隨輸入信號(hào)長(zhǎng)度呈指數(shù)式增加。因此,將這兩種濾波器通過凸組合后引入有源噪聲控制系統(tǒng),以結(jié)合它們?cè)诜蔷�性處理能力,計(jì)算復(fù)雜度方面的優(yōu)勢(shì),對(duì)該組合結(jié)構(gòu)及算法進(jìn)行了推導(dǎo)。為降低算法計(jì)算復(fù)雜度,采用修正箕舌線函數(shù)對(duì)聯(lián)合系數(shù)進(jìn)行選取,采用sign函數(shù)對(duì)混合系數(shù)進(jìn)行更新,降低計(jì)算量的同時(shí),能夠避免聯(lián)合參數(shù)趨向0或1時(shí),混合系數(shù)更新緩慢甚至停滯的現(xiàn)象。最后通過大量仿真實(shí)驗(yàn)對(duì)文中研究?jī)?nèi)容進(jìn)行了驗(yàn)證。
[Abstract]:With the rapid development of Chinese economy, people pay more and more attention to the quality of life. Reducing substation noise can reduce the interference of noise to the life of the surrounding people and greatly improve its quality of life. The active noise control system can reduce the low frequency noise of substation. Therefore, the simple, economical and effective active noise reduction system has a broad application prospect in the field of power transformer noise control. At present, most of the research is based on linear system, and there is an irreconcilable contradiction between the convergence rate and steady-state error of the system, and in the actual operation, there are inevitable nonlinear factors in the control system, which greatly reduces the control performance of this kind of linear system. If the nonlinear problems in the system can be solved, the active noise reduction system can select low-cost electroacoustic devices with nonlinear distortion, which can not only improve the noise reduction performance, but also has special significance to reduce the cost of the system. Therefore, based on the National Natural Science Foundation of China project "Research on active noise suppression Technology of Array Power Transformer based on Internal Model Control", the nonlinear active noise control technology of power transformer and the coordination method between convergence speed and steady state error of power transformer are studied in this paper. In view of the contradiction between the convergence speed and the steady-state error of the system, the convex combination filter is introduced into the active noise control system. The combined algorithm, the system stability, the convergence speed and the steady-state error of the structure are deduced in detail. The theory proves that the combined algorithm can achieve good comprehensive performance taking into account the steady-state error and the convergence speed. Two mainstream methods used in nonlinear noise control systems are studied, one is based on functional connection neural network (FLANN), the other is based on Volterra filter. The basic structure and classical algorithm of their control system are described respectively, and the feasibility analysis is made. The combined structures of the two filters are introduced into the nonlinear active noise control system, and the combined algorithms are deduced theoretically. Aiming at the stagnation phenomenon of the traditional combination algorithms in the process of convergence, the additional instantaneous transfer structure is used to optimize the algorithm. It is found that FLANN structure has the advantages of simple structure and small amount of calculation, and is mainly used in the case of weak nonlinear degree. However, Volterra filter has strong nonlinear processing ability, but the number and computation of kernel function increase with the length of input signal. Therefore, the two filters are introduced into the active noise control system after convex combination, in order to deduce the combined structure and algorithm according to their advantages in nonlinear processing ability and computational complexity. In order to reduce the computational complexity of the algorithm, the modified skip tongue line function is used to select the joint coefficient, and the sign function is used to update the mixing coefficient. While the computation is reduced, the phenomenon that the joint parameter tends to 0 or 1 and the mixing coefficient updates slowly or even stagnates can be avoided. Finally, a large number of simulation experiments are used to verify the research content of this paper.
【學(xué)位授予單位】：武漢大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TM41

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