基于不确定度理论的稳态检测方法及其应用
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摘要
本文基于不确定度理论提出了一种多变量稳态检测方法,该方法通过将各主要运行参数对汽轮机性能指标随机不确定的影响控制在规定的范围内来提取稳态信息,并能自适应地确定稳态区间长度。采用该方法对某超超临界1 000 MW火电机组运行数据进行稳态检测。结果表明:电功率和给水流量是系统稳态评价的关键指标;利用检测出的稳态工况计算得到的性能指标准确度高、一致性好,可用于汽轮机组的性能监测与诊断。将稳态检测结果与滑动窗口法对比,发现该稳态检测方法具有更高的检测灵敏度和准确度。因此,本文提出的稳态检测方法为利用历史运行数据进行火电机组性能监测与评价、故障检测与诊断奠定了基础,具有一定的工程应用价值。
On the basis of the uncertainty theory, a multi-variable steady-state detection method is proposed. This method extracts steady state information by controlling the influence of each main operating parameter on random uncertainty of the performance index within a specified limits, which can adaptively determine the steady-state interval length. Moreover, this method is applied to carry out steady-state detection for operating data of an ultra-supercritical 1 000 MW thermal power unit. The results show that, the power and feed water flow are key indicators for the system's steady state evaluation, the performance index calculated by the detected steady state condition has high accuracy and good consistency, which can be applied for performance monitoring and diagnosis of steam turbines. By comparing the steady-state detection results with the sliding window method, it finds that this method has higher detection sensitivity and accuracy. Therefore, the steady state detection method proposed in this paper lays a foundation for thermal power units' performance monitoring and evaluation, fault detection and diagnosis by using historical operational data, which alleviates many problems faced by current steam turbines' thermal performance tests and has certain engineering application values.
On the basis of the uncertainty theory, a multi-variable steady-state detection method is proposed. This method extracts steady state information by controlling the influence of each main operating parameter on random uncertainty of the performance index within a specified limits, which can adaptively determine the steady-state interval length. Moreover, this method is applied to carry out steady-state detection for operating data of an ultra-supercritical 1 000 MW thermal power unit. The results show that, the power and feed water flow are key indicators for the system's steady state evaluation, the performance index calculated by the detected steady state condition has high accuracy and good consistency, which can be applied for performance monitoring and diagnosis of steam turbines. By comparing the steady-state detection results with the sliding window method, it finds that this method has higher detection sensitivity and accuracy. Therefore, the steady state detection method proposed in this paper lays a foundation for thermal power units' performance monitoring and evaluation, fault detection and diagnosis by using historical operational data, which alleviates many problems faced by current steam turbines' thermal performance tests and has certain engineering application values.
引文
[1]刘吉臻,高萌,吕游,等.过程运行数据的稳态检测方法综述[J].仪器仪表学报,2013,34(8):1739-1748.LIU Jizhen,GAO Meng,LV You,et al.Overview on the steady-state detection methods of process operating data[J].Chinese Journal of Scientific Instrument,2013,34(8):1739-1748.
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[9]刘吉臻,杨光军,谭文.一种基于数据驱动的电站状态稳定性能评价指标[J].热力发电,2008,37(1):45-49.LIU Jizhen,YANG Guangjun,TAN Wen.An index based data-driven for evaluating the state stability in power plant[J].Thermal Power Generation,2008,37(1):45-49.
[10]JIANG T,CHEN B,HE X,et al.Application of steady-state detection method based on wavelet transform[J].Computers&Chemical Engineering,2003,27(4):569-578.
[11]饶宛,方立军,张晗,等.基于Fisher有序聚类的汽轮机试验数据稳态检测方法[J].电站系统工程,2016,32(1):64-66.RAO Wan,FANG Lijun,ZHANG Han,et al.Steady state detection of turbine performance test data based on fisher ordered clustering method[J].Power System Engineering,2016,32(1):64-66.
[12]毕小龙,王洪跃,司风琪,等.基于趋势提取的稳态检测方法[J].动力工程,2006,26(4):503-506.BI Xiaolong,WANG Hongyue,SI Fengqi,et al.Amethod based on tendency distillation for ascertaining state steadiness[J].Journal of Power Engineering,2006,26(4):503-506.
[13]吕游,刘吉臻,赵文杰,等.基于分段曲线拟合的稳态检测方法[J].仪器仪表学报,2012,33(1):194-200.LV You,LIU Jizhen,ZHAO Wenjie,et al.Steady state detecting method based on piecewise curve fitting[J].Chinese Journal of Scientific Instrument,2012,33(1):194-200.
[14]Test uncertainty:ASME PTC19.1-2005[S].New York:The American Society of Mechanical Engineers,2006:5.
[15]Steam turbines performance test codes:ASME PTC-2004[S].New York:The American Society of Mechanical Engineers,2005:12-13.
[16]施雨.应用数理统计[M].西安:西安交通大学出版社,2013:58-60.SHI Yu.Apply mathematical statistics[M].Xi’an:Xi’an Jiaotong University Press,2013:58-60.
[2]NARASIMHAN S,MAH R S H,TAMHANE A C.Acomposite statistical test for detecting changes of steady states[J].Aiche Journal,2010,32(9):1409-1418.
[3]NARASIMHAN S,KAO C S,MAH R S H.Detecting changes of steady states using the mathematical theory of evidence[J].Aiche Journal,1987,33(11):1930-1932.
[4]MORENO R D P.Steady state detection,data reconciliation,and gross error detection:development for industrial processes[D].The University of New Brunswick,2010:2-6.http://www.doc88.com/p-9052093220989.html.
[5]李初福,陈丙珍,何小荣,等.用于含过失误差数据稳态检测的改进滤波法[J].清华大学学报(自然科学版),2004,44(9):1160-1162.LI Chufu,CHEN Bingzhen,HE Xiaorong,et al.Inproved filtering method for steady state tests with measurements containing gross error[J].Journal of Tsinghua University:Natural Science Edition,2004,44(9):1160-1162.
[6]陈文驰,刘飞.一种改进的基于多项式滤波的稳态检测方法[J].控制工程,2012,19(2):195-197.CHEN Wenchi,LIU Fei.An improved steady-state identification method based on polynomial filtering[J].Control Engineering of China,2012,19(2):195-197.
[7]付克昌,戴连奎,吴铁军.基于多项式滤波算法的自适应稳态检测[J].化工自动化及仪表,2006,33(5):18-22.FU Kechang,DAI Liankui,WU Tiejun.Method of adaptive steady state detection based on polynomial filtering[J].Control and Instruments in Chemical Industry,2006,33(5):18-22.
[8]陈玉玲,徐聿晟,沈珂敏,等.基于过程系统测量数据的稳态检测与数据处理方法[J].化工自动化及仪表,2013,40(2):222-225.CHEN Yuling,XU Yusheng,SHEN Kemin,et al.Steady state detection and data processing based on measurement data of process system[J].Control and Instruments in Chemical Industry,2013,40(2):222-225.
[9]刘吉臻,杨光军,谭文.一种基于数据驱动的电站状态稳定性能评价指标[J].热力发电,2008,37(1):45-49.LIU Jizhen,YANG Guangjun,TAN Wen.An index based data-driven for evaluating the state stability in power plant[J].Thermal Power Generation,2008,37(1):45-49.
[10]JIANG T,CHEN B,HE X,et al.Application of steady-state detection method based on wavelet transform[J].Computers&Chemical Engineering,2003,27(4):569-578.
[11]饶宛,方立军,张晗,等.基于Fisher有序聚类的汽轮机试验数据稳态检测方法[J].电站系统工程,2016,32(1):64-66.RAO Wan,FANG Lijun,ZHANG Han,et al.Steady state detection of turbine performance test data based on fisher ordered clustering method[J].Power System Engineering,2016,32(1):64-66.
[12]毕小龙,王洪跃,司风琪,等.基于趋势提取的稳态检测方法[J].动力工程,2006,26(4):503-506.BI Xiaolong,WANG Hongyue,SI Fengqi,et al.Amethod based on tendency distillation for ascertaining state steadiness[J].Journal of Power Engineering,2006,26(4):503-506.
[13]吕游,刘吉臻,赵文杰,等.基于分段曲线拟合的稳态检测方法[J].仪器仪表学报,2012,33(1):194-200.LV You,LIU Jizhen,ZHAO Wenjie,et al.Steady state detecting method based on piecewise curve fitting[J].Chinese Journal of Scientific Instrument,2012,33(1):194-200.
[14]Test uncertainty:ASME PTC19.1-2005[S].New York:The American Society of Mechanical Engineers,2006:5.
[15]Steam turbines performance test codes:ASME PTC-2004[S].New York:The American Society of Mechanical Engineers,2005:12-13.
[16]施雨.应用数理统计[M].西安:西安交通大学出版社,2013:58-60.SHI Yu.Apply mathematical statistics[M].Xi’an:Xi’an Jiaotong University Press,2013:58-60.
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