流化床压力波动冷态试验研究
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摘要
目前循环流化床锅炉压力测点都是安装在炉膛壁面上,由于大量物料循环,频繁摩擦撞击测点,使得测点堵塞磨损问题非常严重,造成测量不准确甚至测点损坏。针对这一问题,本文在搭建冷态鼓泡流化床试验台上,将压力测点布置在风室风帽入口的壁面上,通过压力信号采集系统,将采集到的压力信号转变为数字信号存储于计算机中。在试验过程中,通过调整和改变试验的控制条件,采集多种正常工况与扰动工况下的压力波动信号,并对信号进行深入的研究分析,探讨流化床内的压力波动状况。
基于Matlab编程,利用自相关函数的傅里叶变换的方法,将采集到的时域信号转变为频域信号,从得到的信号频谱图上可以清楚的看到,风帽入口压力波动与流化床内静床高和表观气速等参数变化密切相关,并且压力波动能量主要表现为低频压力波动,说明在风帽处采集的监测信号能够反映流化床内压力波动状况。接着对信号进行消噪处理,通过对比分析工程滤波法与小波消噪法,结果证明小波消噪法优于工程滤波法,并进一步通过对比选择不同的小波基进行消噪,结果表明利用db2小波基三层分解消噪方法,能达到良好的去噪效果。
试验中,模拟了现场流化床中压力信号监测失败、加放料产生扰动、风帽堵塞等扰动工况,利用时域分析、频域分析以及小波包法分析,对比了正常工况与扰动工况下的不同,建立了故障信号的诊断识别的方法。利用时域分析,通过设定置信区间的方法,来判定压力信号是否发生了故障;利用频域分析,对比了正常工况与加放料扰动工况频谱的不同,确定了频谱作为特征向量,实现故障诊断识别;利用小波包分析,将压力信号进行三层分解与重构,对比正常与扰动工况下各个节点功率谱的不同,结果表明信号在结点s30的功率谱p30可以作为特征向量,判定流化床内是否出现风帽堵塞等问题,实现了故障诊断,为现场应用提供理论参考及依据。
Currently the boiler pressure measuring points of the circulating fluidized bed are all installed in the furnace walls. Extensive recycling of materials, and frequent frication and clash of measuring points make the plug wear problem at the measuring points very serious, resulting in inaccurate measurements or damage of the measuring points. To solve the problem, in this thesis I arrange pressure measuring points on the walls at the entrance of the wind chamber hood when setting up cold bubbling fluidized bed test rig, then the collected pressure signals are transformed into digital signals with pressure signal acquisition system,and the digital signals are stored in the computer. During the test, I collect pressure fluctuation signals in normal operating conditions and disturbance conditions by adjusting and changing the test’s control conditions and carry out in-depth analysis and research of the signals to probe pressure fluctuation conditions in fluidized bed.
Based on Matlab programming and using autocorrelation function of the Fourier transform method, the time domain signals are transformed into frequency domain signals. From the received signal spectrum we can clearly see that the pressure fluctuation at the hood inlet is closely related to some parameters such as static bed height of fluidized bed and superficial gas velocity, in addition pressure wave energy is mainly manifested by low-frequency pressure fluctuations, which show that monitoring signals collected at hood entrance can reflect the status of pressure fluctuation in fluidized bed. Then I denoise the signals,by comparative analysis of project filter method and wavelet denoising method,wavelet denoising method is proved better than project filter method. Further by selective comparison of different wavelet bases for denoising, it is concluded that db2 wavelet three-layer decomposition denosing method can be used to achieve the best denosing effects.
During the test, I stimulate some disturbance conditions such as failure of monitoring pressure signals in fluidized bed scene, disturbance generated by placing materials and hood blocking. By using time domain analysis, frequency domain analysis and wavelet packet analysis, I reach different results in normal conditions and disturbance conditions and establish the fault signals’diagnosis and recognition method. I use time domain analysis, by using method of setting confidence interval, to determine whether pressure signals go wrong. I use frequency domain analysis, by comparing different spectrums in normal conditions and placing materials disturbance conditions, to serve spectrum as feature vector and achieve fault diagnosis recognition. By using wavelet packet analysis, carrying out three-layer decomposition of the pressure signals and reconstructing them, and comparing different node powers at each node in normal and disturbance conditions, it is concluded that the signal power spectrum at p30 can serve as feature vector to determine whether hood block arise in circulating fluidized bed, achieve fault diagnosis and provide a theoretical reference and basis for field application.
基于Matlab编程,利用自相关函数的傅里叶变换的方法,将采集到的时域信号转变为频域信号,从得到的信号频谱图上可以清楚的看到,风帽入口压力波动与流化床内静床高和表观气速等参数变化密切相关,并且压力波动能量主要表现为低频压力波动,说明在风帽处采集的监测信号能够反映流化床内压力波动状况。接着对信号进行消噪处理,通过对比分析工程滤波法与小波消噪法,结果证明小波消噪法优于工程滤波法,并进一步通过对比选择不同的小波基进行消噪,结果表明利用db2小波基三层分解消噪方法,能达到良好的去噪效果。
试验中,模拟了现场流化床中压力信号监测失败、加放料产生扰动、风帽堵塞等扰动工况,利用时域分析、频域分析以及小波包法分析,对比了正常工况与扰动工况下的不同,建立了故障信号的诊断识别的方法。利用时域分析,通过设定置信区间的方法,来判定压力信号是否发生了故障;利用频域分析,对比了正常工况与加放料扰动工况频谱的不同,确定了频谱作为特征向量,实现故障诊断识别;利用小波包分析,将压力信号进行三层分解与重构,对比正常与扰动工况下各个节点功率谱的不同,结果表明信号在结点s30的功率谱p30可以作为特征向量,判定流化床内是否出现风帽堵塞等问题,实现了故障诊断,为现场应用提供理论参考及依据。
Currently the boiler pressure measuring points of the circulating fluidized bed are all installed in the furnace walls. Extensive recycling of materials, and frequent frication and clash of measuring points make the plug wear problem at the measuring points very serious, resulting in inaccurate measurements or damage of the measuring points. To solve the problem, in this thesis I arrange pressure measuring points on the walls at the entrance of the wind chamber hood when setting up cold bubbling fluidized bed test rig, then the collected pressure signals are transformed into digital signals with pressure signal acquisition system,and the digital signals are stored in the computer. During the test, I collect pressure fluctuation signals in normal operating conditions and disturbance conditions by adjusting and changing the test’s control conditions and carry out in-depth analysis and research of the signals to probe pressure fluctuation conditions in fluidized bed.
Based on Matlab programming and using autocorrelation function of the Fourier transform method, the time domain signals are transformed into frequency domain signals. From the received signal spectrum we can clearly see that the pressure fluctuation at the hood inlet is closely related to some parameters such as static bed height of fluidized bed and superficial gas velocity, in addition pressure wave energy is mainly manifested by low-frequency pressure fluctuations, which show that monitoring signals collected at hood entrance can reflect the status of pressure fluctuation in fluidized bed. Then I denoise the signals,by comparative analysis of project filter method and wavelet denoising method,wavelet denoising method is proved better than project filter method. Further by selective comparison of different wavelet bases for denoising, it is concluded that db2 wavelet three-layer decomposition denosing method can be used to achieve the best denosing effects.
During the test, I stimulate some disturbance conditions such as failure of monitoring pressure signals in fluidized bed scene, disturbance generated by placing materials and hood blocking. By using time domain analysis, frequency domain analysis and wavelet packet analysis, I reach different results in normal conditions and disturbance conditions and establish the fault signals’diagnosis and recognition method. I use time domain analysis, by using method of setting confidence interval, to determine whether pressure signals go wrong. I use frequency domain analysis, by comparing different spectrums in normal conditions and placing materials disturbance conditions, to serve spectrum as feature vector and achieve fault diagnosis recognition. By using wavelet packet analysis, carrying out three-layer decomposition of the pressure signals and reconstructing them, and comparing different node powers at each node in normal and disturbance conditions, it is concluded that the signal power spectrum at p30 can serve as feature vector to determine whether hood block arise in circulating fluidized bed, achieve fault diagnosis and provide a theoretical reference and basis for field application.
引文
[1]李建锋,郝继红,冀慧敏,等.我国循环流化床锅炉发展现状以及未来[J].电力技术, 2009, 1(4): 12-16
[2]黄来生.国内大型循环流化床锅炉的发展和现状[J].江西科学, 2009, 27(4): 608-613
[3]骆仲泱,何宏舟,王勤辉,等.循环流化床锅炉技术的现状及发展前景[J].动力工程, 2004, 24(6): 761～767
[4] L Lafanechere, L Jestin. Study of a circulating fluidized bed furnace behavior in order to scale it up to 600Mwe[A]. 13th international conference on fluidized bed combustion. Orlando: USA, 1995
[5]周一工.中国循环流化床锅炉的发展:从低压到超临界[J].锅炉技术, 2009, 40(2): 22-27
[6]邢伟.大容量循环流化床锅炉技术研发现状及建议[J].热力发电, 2008, 37(4): 10-12
[7] Sun Xian bin, Jiang Min hua, Yu Long, et al. R&D and Demonstration of large Domestic CFB Boilers[J]. Electricity, 2008, 19(3): 32-35
[8]孙献斌.循环流化床锅炉大型化的发展与应用[J].电站系统工程. 2005, 25(4): 1-5
[9]赵果然.循环流化床锅炉国内外现状概述[J].锅炉制造, 2009, 4:19-21
[10] Lan Jing, Shen Lai hong. Wavelet Analysis of Pressure Fluctuation in a Bubbling Fluidized Bed[J]. BOILER TECHNOLOGY, 2003, 34(4): 42-46
[11]张少峰,王琦,高川博,等.液固两相外循环流化床压力波动信号的统计及频谱分析[J].过程工程学报, 2006, 6(6): 878-883
[12] Chen Y, Tian Z, Miao Z. Detection of singularities in the pressure fluctuations of circulating fluidized beds based on wavelet modulus maximum method[J]. Chemical Engineering Science, 2004, (59): 3569-3575
[13] Marzocchella A, Zijerveld R C, Schouten J C. Chaotic Behavior of Gas-Solid Flow in the Riser of a Laboratory-scale Circulating Fluidized Bed[J]. AIChE J,1997, 43(6): 1458-1468
[14] Ren Jinqiang, Mao Qiming, Li Jinghai, et al. Wavelet Analysis of Dynamic Behavior in Fluidized Beds[J]. Chemical Engineering Science, 2001, 56: 981-988
[15] J.van der schaaf, J.C.Schouten, C.M.van et al, Orighin Propagation And Attenuation of Pressure Waves in Gas-Golid Fluidized Beds[J]. Powder Technology, 1998, 95: 220-233
[16] Fan L T, Kang Y, Neogi D et al. Fractal analysis of fluidized particle behavior in liquid-solid fluidized beds[J]. AIChE J. 1993, 39(3): 513-516
[17] Schouten J C, Vander Stappen M L M, Vanden Bleek C M. Scale-up of Chaotic Fluidized Bed Hydrodynamics[J]. Chem. Eng.Sci, 1996, 51(10): 1991-2000
[18]赵贵兵,李天铎,阳永荣,等.气固两相流压力波动信号分析[J].中国粉体技术, 2001, 7(3): 23-28
[19]马丽萍.循环流化床波动信号的非线性分析[D].成都:四川大学, 2002
[20]赵贵兵,陈纪忠.流化床压力波动混沌性质探讨[J].化工学报, 2002, 6(53): 655-659
[21] Bai D, Bi H T, Grace J R. Chaotic Behavior of Fluidized Beds Based on Pressure and Voidage Fluctuations[J]. AIChE J, 1997, 43(5): 1357-1361
[22]张贤达.现代信号处理[M].北京:清华大学出版社, 2001, 46-48
[23] Pallares D, Johnsson F. Macroscopic modelling offluid dynamics in large-scale circulating fluidized beds[J]. Progress in Energy and Combustion Science. 2006, 32(5/6): 539-569
[24]田子平,陈永国,缪正清.循环流化床压力波动信号的小波多分辨率分析[J].过程工程学报, 2004, 22(4): 5-8
[25]赵明阳,黄志尧,王保良等.高阶统计量在气固流化床中的应用研究[J].浙江大学学报(工学版), 2002, 36(6): 680-684
[26]程乐鸣,周星龙,郑成航,等.大型循环流化床锅炉的发展[J].动力工程, 2008, 28(6): 817-825
[27] Ji H, Ohara H, Kuramoto K, et al. Nonlinear Dynamics of Gas–Solid Circulating Fluidized-bed System[J]. Chem. Eng. Sci, 2000, 55(4): 403-410
[28]张伟.循环流化床锅炉床内流动特性研究[D].保定:华北电力大学, 2010
[29] Dong Jing wei, Yu Guang yan. FFT Spectrum Analysis and IIR Digital Filter Design Based on MATLAB Programming[J]. Software Guide, 2008, 7(10): 128-129
[30]吴新杰,王师.基于小波变换处理两相流信号的方法[J].东北大学学报, 2000, 21(1): 12-14
[31]高成,董长虹,李阳明,等. MATLAB小波分析及应用[M].北京:国防工业出版社, 2007, 104-106
[32]林阿彪.循环流化床压力波动特性试验研究[D].保定.华北电力大学, 2009
[33] Platt N, Spiegel E A, Tresser C. On-off Intermittency:A Mechanism for Bursting[J]. Phys. Rev. Lett, 1993, 70(3): 279-282
[34] Manneville P, Pomeau Y. Intermittency and the Lorenz Model[J]. Physics Letters A, 1979, 75(2): 1-2
[35]陈鸿伟,林阿彪,危日光,等.循环流化床压力波动信号小波消噪分析[J].华北电力大学学报, 2008, 35(6): 83-86
[36] Guenther Chris, Breault Ronald. Wavelet analysis to characterize cluster dynamics in a circulating fluidized bed[J]. Powder Technology, 2007, 173 (3): 163-173
[37] Xie Ke cheng. Cofiring of coal and refuse derived fuel in a new type of internally circulating fluidized bed system[J]. Energy Sources, 2003, 25(11): 1073-1081
[38]黄海,黄轶伦,张卫东.气固流化床压力脉动的Wigner谱分析[J].化工学报, 1998, 50(4): 477-482
[39] Tong Qin ye, Kong Jun, Xu Jing hua. A note on analyzing schizophrenic EEG with complexity measure[J]. Choas Solitionsand Fractals, 1996, 7(3): 371-375
[40] Wu B.Y, Kantzas A, Bellehumeur C.T, et al. Multiresolution Analysis of Pressure Fluctuations in a Gas-solids Fluidized Bed:Application to Glass Beads and Polyethylene Powder Systems[J]. Chemical Engineering Journal, 2007, 131(1-3): 23-33
[41] Sasic S, Leckner B, Johnsson F. Time-frequency Investigation of Different Modes of Bubble Flow in a Gas-solid Fluidized Bed[J]. Chemical Engineering Journal, 2006, 121(1): 27-35
[42]王新峰,邱静.机电BIT故障特征选择方法研究[J].中国机械工程, 2004, 6(15): 66-68
[43] A L Blum, P Langley. Selection of Relevant Feature and Examples in Machine Learning [J]. Artificial Intelligence, 1997, 97: 245-271
[44] S B Serpico, L Bruzzone. A New Search Algorithm for Feature Selection in Hyper Spectral Remote Sensing Images[J]. IEEE Trans on Geoscience and Remote Sensing, 2001, 39(7): 1360-1367
[45]王娟,慈林林,姚康泽.特征选择方法综述[J].计算机工程与科学, 2005, 27(12): 68-71
[46] Grace R. Reflections on Turbulent Fluidization and Dense Suspension Flow[J]. Powder Technology, 2000, 113(4): 242-248
[47] Wackerbauer R, Witt A, Atmanspacher H. A comparative classification of complexity measures [J]. Chaos Solitons and Fractals, l994, 4(1): l33-173
[48]周巍巍,石炎福.气固循环流化床压力波动时间序列非线性分析[J].石化技术与应用, 2002, 2(20): 83-87
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[50] Ajar A. Stabilization of Chaotic Behavior in a Two-phase Autocatalytic Reactor[J]. Choas Solutions and Fractals, 2001, 12(3): 903-918
[2]黄来生.国内大型循环流化床锅炉的发展和现状[J].江西科学, 2009, 27(4): 608-613
[3]骆仲泱,何宏舟,王勤辉,等.循环流化床锅炉技术的现状及发展前景[J].动力工程, 2004, 24(6): 761～767
[4] L Lafanechere, L Jestin. Study of a circulating fluidized bed furnace behavior in order to scale it up to 600Mwe[A]. 13th international conference on fluidized bed combustion. Orlando: USA, 1995
[5]周一工.中国循环流化床锅炉的发展:从低压到超临界[J].锅炉技术, 2009, 40(2): 22-27
[6]邢伟.大容量循环流化床锅炉技术研发现状及建议[J].热力发电, 2008, 37(4): 10-12
[7] Sun Xian bin, Jiang Min hua, Yu Long, et al. R&D and Demonstration of large Domestic CFB Boilers[J]. Electricity, 2008, 19(3): 32-35
[8]孙献斌.循环流化床锅炉大型化的发展与应用[J].电站系统工程. 2005, 25(4): 1-5
[9]赵果然.循环流化床锅炉国内外现状概述[J].锅炉制造, 2009, 4:19-21
[10] Lan Jing, Shen Lai hong. Wavelet Analysis of Pressure Fluctuation in a Bubbling Fluidized Bed[J]. BOILER TECHNOLOGY, 2003, 34(4): 42-46
[11]张少峰,王琦,高川博,等.液固两相外循环流化床压力波动信号的统计及频谱分析[J].过程工程学报, 2006, 6(6): 878-883
[12] Chen Y, Tian Z, Miao Z. Detection of singularities in the pressure fluctuations of circulating fluidized beds based on wavelet modulus maximum method[J]. Chemical Engineering Science, 2004, (59): 3569-3575
[13] Marzocchella A, Zijerveld R C, Schouten J C. Chaotic Behavior of Gas-Solid Flow in the Riser of a Laboratory-scale Circulating Fluidized Bed[J]. AIChE J,1997, 43(6): 1458-1468
[14] Ren Jinqiang, Mao Qiming, Li Jinghai, et al. Wavelet Analysis of Dynamic Behavior in Fluidized Beds[J]. Chemical Engineering Science, 2001, 56: 981-988
[15] J.van der schaaf, J.C.Schouten, C.M.van et al, Orighin Propagation And Attenuation of Pressure Waves in Gas-Golid Fluidized Beds[J]. Powder Technology, 1998, 95: 220-233
[16] Fan L T, Kang Y, Neogi D et al. Fractal analysis of fluidized particle behavior in liquid-solid fluidized beds[J]. AIChE J. 1993, 39(3): 513-516
[17] Schouten J C, Vander Stappen M L M, Vanden Bleek C M. Scale-up of Chaotic Fluidized Bed Hydrodynamics[J]. Chem. Eng.Sci, 1996, 51(10): 1991-2000
[18]赵贵兵,李天铎,阳永荣,等.气固两相流压力波动信号分析[J].中国粉体技术, 2001, 7(3): 23-28
[19]马丽萍.循环流化床波动信号的非线性分析[D].成都:四川大学, 2002
[20]赵贵兵,陈纪忠.流化床压力波动混沌性质探讨[J].化工学报, 2002, 6(53): 655-659
[21] Bai D, Bi H T, Grace J R. Chaotic Behavior of Fluidized Beds Based on Pressure and Voidage Fluctuations[J]. AIChE J, 1997, 43(5): 1357-1361
[22]张贤达.现代信号处理[M].北京:清华大学出版社, 2001, 46-48
[23] Pallares D, Johnsson F. Macroscopic modelling offluid dynamics in large-scale circulating fluidized beds[J]. Progress in Energy and Combustion Science. 2006, 32(5/6): 539-569
[24]田子平,陈永国,缪正清.循环流化床压力波动信号的小波多分辨率分析[J].过程工程学报, 2004, 22(4): 5-8
[25]赵明阳,黄志尧,王保良等.高阶统计量在气固流化床中的应用研究[J].浙江大学学报(工学版), 2002, 36(6): 680-684
[26]程乐鸣,周星龙,郑成航,等.大型循环流化床锅炉的发展[J].动力工程, 2008, 28(6): 817-825
[27] Ji H, Ohara H, Kuramoto K, et al. Nonlinear Dynamics of Gas–Solid Circulating Fluidized-bed System[J]. Chem. Eng. Sci, 2000, 55(4): 403-410
[28]张伟.循环流化床锅炉床内流动特性研究[D].保定:华北电力大学, 2010
[29] Dong Jing wei, Yu Guang yan. FFT Spectrum Analysis and IIR Digital Filter Design Based on MATLAB Programming[J]. Software Guide, 2008, 7(10): 128-129
[30]吴新杰,王师.基于小波变换处理两相流信号的方法[J].东北大学学报, 2000, 21(1): 12-14
[31]高成,董长虹,李阳明,等. MATLAB小波分析及应用[M].北京:国防工业出版社, 2007, 104-106
[32]林阿彪.循环流化床压力波动特性试验研究[D].保定.华北电力大学, 2009
[33] Platt N, Spiegel E A, Tresser C. On-off Intermittency:A Mechanism for Bursting[J]. Phys. Rev. Lett, 1993, 70(3): 279-282
[34] Manneville P, Pomeau Y. Intermittency and the Lorenz Model[J]. Physics Letters A, 1979, 75(2): 1-2
[35]陈鸿伟,林阿彪,危日光,等.循环流化床压力波动信号小波消噪分析[J].华北电力大学学报, 2008, 35(6): 83-86
[36] Guenther Chris, Breault Ronald. Wavelet analysis to characterize cluster dynamics in a circulating fluidized bed[J]. Powder Technology, 2007, 173 (3): 163-173
[37] Xie Ke cheng. Cofiring of coal and refuse derived fuel in a new type of internally circulating fluidized bed system[J]. Energy Sources, 2003, 25(11): 1073-1081
[38]黄海,黄轶伦,张卫东.气固流化床压力脉动的Wigner谱分析[J].化工学报, 1998, 50(4): 477-482
[39] Tong Qin ye, Kong Jun, Xu Jing hua. A note on analyzing schizophrenic EEG with complexity measure[J]. Choas Solitionsand Fractals, 1996, 7(3): 371-375
[40] Wu B.Y, Kantzas A, Bellehumeur C.T, et al. Multiresolution Analysis of Pressure Fluctuations in a Gas-solids Fluidized Bed:Application to Glass Beads and Polyethylene Powder Systems[J]. Chemical Engineering Journal, 2007, 131(1-3): 23-33
[41] Sasic S, Leckner B, Johnsson F. Time-frequency Investigation of Different Modes of Bubble Flow in a Gas-solid Fluidized Bed[J]. Chemical Engineering Journal, 2006, 121(1): 27-35
[42]王新峰,邱静.机电BIT故障特征选择方法研究[J].中国机械工程, 2004, 6(15): 66-68
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