基于自適應(yīng)觀測器的風(fēng)力發(fā)電機(jī)液壓變槳系統(tǒng)故障診斷
胡昌選，文傳博
（上海電機(jī)學(xué)院 電氣學(xué)院，上海 201306）
摘 要：液壓變槳系統(tǒng)是風(fēng)力發(fā)電機(jī)組中故障多發(fā)的重要部件，對其展開故障診斷具有重要意義。針對受到丟包和狀態(tài)延時影響的風(fēng)機(jī)變槳系統(tǒng)故障，提出一種基于自適應(yīng)觀測器的故障診斷方法。將復(fù)雜的變槳系統(tǒng)轉(zhuǎn)化為相應(yīng)的狀態(tài)空間模型，并根據(jù)相應(yīng)的系統(tǒng)故障模型設(shè)計出自適應(yīng)觀測器。將故障模型進(jìn)行離散化之后，設(shè)置合理的系統(tǒng)增益矩陣以及自適應(yīng)調(diào)節(jié)律，并對觀測器的穩(wěn)定性展開了證明。仿真結(jié)果證明了觀測部分能夠準(zhǔn)確地對真實值進(jìn)行跟蹤，實現(xiàn)了對變槳系統(tǒng)故障診斷的目標(biāo)。
關(guān)鍵詞：風(fēng)力發(fā)電機(jī)組；狀態(tài)時延和丟包；變槳系統(tǒng)；自適應(yīng)觀測器；故障診斷
中圖分類號：TM614 文獻(xiàn)標(biāo)識碼：A 文章編號：1007-3175(2019)11-0005-06
Fault Diagnosis of Wind Turbine Hydraulic Variable Pitch System Based on Adaptive Observer
HU Chang-xuan , WEN Chuan-bo
（School of Electrical Engineering, Shanghai Dianji University, Shanghai 201306, China）
Abstract: The hydraulic variable pitch system of wind turbine is the main multi-fault component, so it is very necessary to carry out fault diagnosis. A fault diagnosis method based on adaptive observation was proposed for the fault of wind turbine variable pitch system affected by state delay and loss of package. The complex variable pitch system was transformed into the corresponding state space model, and the adaptive observer was designed according to the corresponding system fault model. After the fault model was discretized, a reasonable gain matrix and adaptive regulation law are set up, and the stability of the observer was proved. The simulation results show that the observer part can accurately track the real value and realize the goal of fault diagnosis for the variable pitch system.
Key words: wind turbine; state delay and packet loss; variable pitch system; adaptive observer; fault diagnosis
參考文獻(xiàn)
[1] 謝小榮，劉華坤，賀靜波，等. 直驅(qū)風(fēng)機(jī)風(fēng)電場與交流電網(wǎng)相互作用引發(fā)次同步振蕩的機(jī)理與特性分析[J]. 中國電機(jī)工程學(xué)報，2016，36(9)：2366-2372.
[2] 曾軍，陳艷峰，楊蘋，等. 大型風(fēng)力發(fā)電機(jī)組故障診斷綜述[J]. 電網(wǎng)技術(shù)，2018，42(3)：849-860.
[3] XU L, LIN R, DING L, et al.Enhancing the LVRT Capability of PMSG-Based Wind Turbines Based on R-SFCL[C]//IOP Conference Series: Materials Science and Engineering，2018，322(7)：072044.
[4] XIAO C, JIAO Z, SUN J, et al.Fault prediction of variable pitch system of wind turbine based on wavelet BP neural network[J]. Renewable Energy Resources，2017，35(6)：893-899.
[5] CHEN X, YAN R, LIU Y.Wind Turbine Condition Monitoring and Fault Diagnosis in China[J]. IEEE Instrumentation & Measurement Magazine，2016，19(2)：22-28.
[6] YAO Z, YU Y, YAO J.Artificial neural networkbased internal leakage fault detection for hydraulic actuators: An experimental investigation[J]. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering，2018，232(4)：369-382.
[7] GONG X, QIAO W.Bearing Fault Diagnosis forDirect-Drive Wind Turbines via Current- Demodulated Signals[J].IEEE Transactions on Industrial Electronics，2013，60(8)：3419-3428.
[8] 李學(xué)偉. 基于數(shù)據(jù)挖掘的風(fēng)電機(jī)組狀態(tài)預(yù)測及變槳系統(tǒng)異常識別[D]. 重慶：重慶大學(xué)，2012.
[9] LAOUTI N, OTHMAN S, ALAMIR M, et al. Combination of Model-Based Observer and Support Vector Machines for Fault Detection of Wind Turbines[J].International Journal of Automation & Computing，2014，11(3)：274-287.
[10] 張柯，姜斌，劉京津. 基于自適應(yīng)觀測器控制系統(tǒng)的快速故障調(diào)節(jié)[J]. 控制與決策，2008，23(7)：771-775.
[11] 賀乃寶，姜長生. 基于Lyapunov方法的非線性系統(tǒng)自適應(yīng)觀測器設(shè)計[J]. 南京航空航天大學(xué)學(xué)報，2006，38(3)：267-270.
[12] 祝喬，崔家瑞. 非線性延時系統(tǒng)的觀測器設(shè)計[J].控制工程，2012，19(3)：374-376.
[13] 朱張青，周川，胡維禮. 短時延網(wǎng)絡(luò)控制系統(tǒng)的魯棒H2/H∞狀態(tài)觀測器設(shè)計[J]. 控制與決策，2005，20(3)：280-284.
[14] SLOTH C, ESBENSEN T, STOUSTRUP J.Robust and fault-tolerant linear parameter-varying control of wind turbines[J].Mechatronics，2011，21(4)：645-659.
[15] WANG Y L, HAN Q L.Observer-based continuoustime networked control system design[C]// Proceedings of the American Control Conference，2012：5694-5699.
[16] BEILZADEH H, MARQUEZ H J.Multirate output feedback control of nonlinear networked control systems[J].IEEE Transactions on Automatic Control，2015，60(7)：1939-1944.
[17] BESANCON G,TICLEA A.On adaptive observers for systems with state and parameter nonlinearities[J].IFAC-PapersOnLine，2017，50(1)：15416-15421.
[18] 吳定會，劉穩(wěn)，宋錦. 基于SDW-LSI算法的風(fēng)力機(jī)故障估計與容錯控制[J]. 電力系統(tǒng)保護(hù)與控制，2017，45(4)：64-71.
[19] 楊洪玖，夏元清，李惠光.Delta算子系統(tǒng)簡述[J].控制理論與應(yīng)用，2015，32(5)：569-578.
