气流床气化炉排渣系统的数值模拟和检测方法
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摘要
气流床煤气化技术是我国煤炭清洁、高效转化的重要途径和发展方向之一。目前,由于气流床排渣系统故障而导致气化炉下渣口堵渣和水冷壁“烧坏”等问题制约气流床气化炉长期稳定运行。因此,有必要对气流床气化炉进行深入的研究。Shell煤气化技术在当今大规模煤气化技术中具有明显的竞争力,因此本文以Shell气化炉为例,首先通过有限单元法建立气流床气化炉水冷壁的温度计算模型,考察固态渣层的厚度、渣钉长度、渣钉的导热系数、水侧对流换热系数和气化炉炉膛的温度对水冷壁温度分布的影响,揭示“以渣抗渣”的机理。其次,以声发射技术为检测手段,对排渣系统中煤灰渣粘度、渣池排出的循环水(黑水)粘度、大块渣的生成和块渣堆积高度进行较为系统的研究,期望实现排渣系统的故障预警。论文的主要工作：
1.利用有限单元法建立气化炉水冷壁的温度分布的计算模型,分析固态渣层厚度、渣钉长度、渣钉导热系数、气化炉近壁面温度和水侧对流换热系数对气化炉水冷壁温度的影响。发现,随着固态渣层厚度增加,固态渣层和液态渣层交界面的温度升高,渣钉的温度降低,水冷管温度和金属壁面的温度基本不变；随着渣钉长度的增加,固态渣层和液态渣层交界面的温度降低,渣钉温度增加,水冷管温度和金属壁面温度基本不变；随着渣钉导热系数增加,渣钉温度降低,水冷管温度升高,金属壁面温度降低；随着水侧对流换热系数的增加,水冷管温度、金属壁面温度和渣钉温度基本不变；随着气化炉近壁面温度增加,水冷管温度、金属壁面温度和渣钉温度随之增加。
进一步分析得到,固态渣层和液态渣层共同组成水冷壁的主要热阻,隔绝水冷管,金属壁面和渣钉与液态渣层和气化炉内部反应气体的直接接触,保证其不受气化炉内部气化反应腐蚀、不受高温烧蚀、不受熔渣磨蚀,达到“以渣抗渣”的目的；渣钉主要起到支撑固态渣层和导热的作用；
2.建立羧甲基纤维素(CMC)—水体系的粘度预测模型,期望对液态熔渣的粘度实现在线检测。对液态流体流动产生的声信号进行快速傅里叶变换,分析发现声信号主频位移随粘度的增加而增加,进而建立煤灰渣的粘度预测模型,即f=αΔf+b,其中Δf为气化炉内声发射信号频率谱图特征峰的主频位移,α和b为拟合参数,由预测模型得到的检测结果与真实值的相关系数为0.979,平均相对偏差为5.47%,交叉验证误差均方根为0.074,验证该粘度预测模型的准确性。
3.建立蔗糖水溶液的粘度预测模型,期望对黑水的粘度实现在线检测。对流体流动产生的声信号进行小波分析和R/S分析,发现声波特征信号频段能量随流体粘度呈现规律性的变化,以流体撞击壁面产生信号特征区域的声能量值为特征参数,建立蔗糖水溶液粘度的预测模型,由预测模型得到的检测结果与真实值的相关系数为0.970,平均相对偏差为11.9%,交叉验证误差均方根为1.228。
4.基于声发射技术,提出气化炉内大块渣生成的判据,即当渣池壁面处声信号的能量和方差出现突变时,即能量E>1.5E0,方差S>1.2S0,表明此时气化炉内有大块渣的生成。以水-玻璃珠体系为例,与目测法相比,声发射技术检测大块渣生成时刻的结果最大误差不超过2s,表明该方法能比较好的检测气化炉内大块渣生成。
5.利用声发射技术,基于气化炉壁面产生声发射信号的机理,结合能量、方差和频谱分析等处理手段,揭示声波信号特征频段能量沿渣池高度的规律性变化,提出声波法测量渣池块渣堆积高度的方法,即声信号的特征频度能量值的第一次发生阶跃变化所对应的测量高度即为块渣堆积高度。以水-玻璃珠体系,声发射技术检测块渣堆积高度的结果与目测法的结果平均相对误差为3.94%,表明该方法能较好地检测渣池的块渣堆积高度。
The entrained flow coal gasification technology become one of the important means and directions in clean coal and coal conversion technology in our country. Blocking slag and water wall "burn out" by failure of slag discharge restrict long term stable operation of entrained flow gasifier. So it is necessary to research into the entrained flow gasifier. In today's large-scale coal gasification technology shell coal gasification technology has significant competitive. Therefore this article take shell coal gasification technology as the example, Firstly, an entrained flow gasifier wall model is established by finite element method. The effect of the thickness of solid slag, slag nail length, the thermal conductivity of slag nail, the water-side heat transfer coefficient and the temperature of the gasifier furnace on temperature distribution were investigated, to study the working principle of "the slag resists the slag". Secondly, make a relatively systemic research about the coal-ash viscosity, black water (circulating water from slag pool), criterion of big slag generation and stack height of slag, using acoustic emission (AE), expectation early-warning of Fault in the gasifier. The innovative results can be summarized as follows:
1. An entrained flow gasifier wall temperature distribution model is established by finite element method, the effect of the thickness of solid slag, slag nail length, the thermal conductivity of slag nail, the water-side heat transfer coefficient and the temperature of the gasifier furnace on temperature distribution were investigated. When the thickness of solid slag increases, the temperature at the interface between solid slag and liquid slag increases, the temperature of slag nail decreases, the temperature of water cooled tube and metal wall unchanged; when slag nail length increases, the temperature at the interface between solid slag and liquid slag decreases, the temperature of slag nail increases, the temperature of water cooled tube and metal wall unchanged; when the thermal conductivity of slag nail increases, the temperature of slag nail decreases, the temperature of water cooled tube increases, the temperature of metal wall decreases; when the water-side heat transfer coefficient increases, the temperature of water cooled tube, metal wall and slag nail increases; when the temperature of the gasifier furnace increases, the temperature of water cooled tube metal wall and slag nail unchanged.
According to results, solid slag and liquid slag comprise the main thermal resistance of water wall, seclude water cooled tube, metal wall and slag nail from high temperature gas in the gasifier, ensure them not to be high temperature corrosion, high temperature corrosion ablative and high temperature fretting corrosion, to achieve "the slag resists the slag".
2. The viscosity prediction models for Carboxymethylcellulose(CMC)-water system are obtained, desire to on-line inspection for viscosity of liquid slag. A characteristic frequency band of acoustic emission (AE) signals, was obtained by using wavelet transform. Then it was observed that the energy of AE signals at dominant frequency changed regularly with increasing fluid viscosity. A new method for building prediction model of viscosity was presented based on this regular behavior, that isμ=aΔf+b, whichΔfis displacement of dominant frequency, a and b is fitting parameters, this new method show that the correlation coefficient(r), average relative deviation (ARD) and root mean square error of cross validation (RMSECV) between actual viscosity and predictive values obtained by prediction model, were 0.979, 5.47% and 0.074, respectively. It is concluded that multi-scale analysis of AE is feasible for predicting fluid viscosity.
3. The viscosity prediction models for sucrose-water system are obtained, desire to on-line inspection for viscosity of circulating water from slag pool. A characteristic frequency band of acoustic emission (AE) signals was obtained by using wavelet transform and Hurst analysis. Then it was observed that the energy of AE signals at different frequencies changed regularly with increasing black water viscosity. A new method for building prediction model of black water viscosity was presented based on this regular behavior. This new method was verified by the aqueous sucrose solutions system in a stirred vessel, which showed that the correlation coefficient(r), average relative deviation (ARD) and root mean square error of cross validation (RMSECV) between actual viscosity and predictive values obtained by prediction model, were 0.970,11.9% and 1.228. respectively. It is concluded that multi-scale analysis of AE is feasible for predicting black water viscosity.
4. A criterion for the generation of large slag is presented based on acoustic emission (AE), namely the curve of energy and variance appears spike means that the generation of large slag, namely, energy E>1.5Eo, variance S>1.2S0, the average absolute relative deviation (AARD) is 0.34% when compared with ones by the method of visual observation. So this criterion cans detection the generation of large slag.
5. A characteristic frequency band of acoustic emission (AE) signals, which represented the impact of the slag on the wall, was obtained by using wavelet transform and Hurst analysis. Then it was observed that the energy of AE signals at different frequencies changed regularly with increasing the height of slag pool, namely the height of the first step change in the characteristic energy curve is the stack height. Take water-glass beads for example, the average absolute relative deviation (AARD) is 3.94% when compared with ones by the method of visual observation. So this criterion cans detection the stack height.
1.利用有限单元法建立气化炉水冷壁的温度分布的计算模型,分析固态渣层厚度、渣钉长度、渣钉导热系数、气化炉近壁面温度和水侧对流换热系数对气化炉水冷壁温度的影响。发现,随着固态渣层厚度增加,固态渣层和液态渣层交界面的温度升高,渣钉的温度降低,水冷管温度和金属壁面的温度基本不变；随着渣钉长度的增加,固态渣层和液态渣层交界面的温度降低,渣钉温度增加,水冷管温度和金属壁面温度基本不变；随着渣钉导热系数增加,渣钉温度降低,水冷管温度升高,金属壁面温度降低；随着水侧对流换热系数的增加,水冷管温度、金属壁面温度和渣钉温度基本不变；随着气化炉近壁面温度增加,水冷管温度、金属壁面温度和渣钉温度随之增加。
进一步分析得到,固态渣层和液态渣层共同组成水冷壁的主要热阻,隔绝水冷管,金属壁面和渣钉与液态渣层和气化炉内部反应气体的直接接触,保证其不受气化炉内部气化反应腐蚀、不受高温烧蚀、不受熔渣磨蚀,达到“以渣抗渣”的目的；渣钉主要起到支撑固态渣层和导热的作用；
2.建立羧甲基纤维素(CMC)—水体系的粘度预测模型,期望对液态熔渣的粘度实现在线检测。对液态流体流动产生的声信号进行快速傅里叶变换,分析发现声信号主频位移随粘度的增加而增加,进而建立煤灰渣的粘度预测模型,即f=αΔf+b,其中Δf为气化炉内声发射信号频率谱图特征峰的主频位移,α和b为拟合参数,由预测模型得到的检测结果与真实值的相关系数为0.979,平均相对偏差为5.47%,交叉验证误差均方根为0.074,验证该粘度预测模型的准确性。
3.建立蔗糖水溶液的粘度预测模型,期望对黑水的粘度实现在线检测。对流体流动产生的声信号进行小波分析和R/S分析,发现声波特征信号频段能量随流体粘度呈现规律性的变化,以流体撞击壁面产生信号特征区域的声能量值为特征参数,建立蔗糖水溶液粘度的预测模型,由预测模型得到的检测结果与真实值的相关系数为0.970,平均相对偏差为11.9%,交叉验证误差均方根为1.228。
4.基于声发射技术,提出气化炉内大块渣生成的判据,即当渣池壁面处声信号的能量和方差出现突变时,即能量E>1.5E0,方差S>1.2S0,表明此时气化炉内有大块渣的生成。以水-玻璃珠体系为例,与目测法相比,声发射技术检测大块渣生成时刻的结果最大误差不超过2s,表明该方法能比较好的检测气化炉内大块渣生成。
5.利用声发射技术,基于气化炉壁面产生声发射信号的机理,结合能量、方差和频谱分析等处理手段,揭示声波信号特征频段能量沿渣池高度的规律性变化,提出声波法测量渣池块渣堆积高度的方法,即声信号的特征频度能量值的第一次发生阶跃变化所对应的测量高度即为块渣堆积高度。以水-玻璃珠体系,声发射技术检测块渣堆积高度的结果与目测法的结果平均相对误差为3.94%,表明该方法能较好地检测渣池的块渣堆积高度。
The entrained flow coal gasification technology become one of the important means and directions in clean coal and coal conversion technology in our country. Blocking slag and water wall "burn out" by failure of slag discharge restrict long term stable operation of entrained flow gasifier. So it is necessary to research into the entrained flow gasifier. In today's large-scale coal gasification technology shell coal gasification technology has significant competitive. Therefore this article take shell coal gasification technology as the example, Firstly, an entrained flow gasifier wall model is established by finite element method. The effect of the thickness of solid slag, slag nail length, the thermal conductivity of slag nail, the water-side heat transfer coefficient and the temperature of the gasifier furnace on temperature distribution were investigated, to study the working principle of "the slag resists the slag". Secondly, make a relatively systemic research about the coal-ash viscosity, black water (circulating water from slag pool), criterion of big slag generation and stack height of slag, using acoustic emission (AE), expectation early-warning of Fault in the gasifier. The innovative results can be summarized as follows:
1. An entrained flow gasifier wall temperature distribution model is established by finite element method, the effect of the thickness of solid slag, slag nail length, the thermal conductivity of slag nail, the water-side heat transfer coefficient and the temperature of the gasifier furnace on temperature distribution were investigated. When the thickness of solid slag increases, the temperature at the interface between solid slag and liquid slag increases, the temperature of slag nail decreases, the temperature of water cooled tube and metal wall unchanged; when slag nail length increases, the temperature at the interface between solid slag and liquid slag decreases, the temperature of slag nail increases, the temperature of water cooled tube and metal wall unchanged; when the thermal conductivity of slag nail increases, the temperature of slag nail decreases, the temperature of water cooled tube increases, the temperature of metal wall decreases; when the water-side heat transfer coefficient increases, the temperature of water cooled tube, metal wall and slag nail increases; when the temperature of the gasifier furnace increases, the temperature of water cooled tube metal wall and slag nail unchanged.
According to results, solid slag and liquid slag comprise the main thermal resistance of water wall, seclude water cooled tube, metal wall and slag nail from high temperature gas in the gasifier, ensure them not to be high temperature corrosion, high temperature corrosion ablative and high temperature fretting corrosion, to achieve "the slag resists the slag".
2. The viscosity prediction models for Carboxymethylcellulose(CMC)-water system are obtained, desire to on-line inspection for viscosity of liquid slag. A characteristic frequency band of acoustic emission (AE) signals, was obtained by using wavelet transform. Then it was observed that the energy of AE signals at dominant frequency changed regularly with increasing fluid viscosity. A new method for building prediction model of viscosity was presented based on this regular behavior, that isμ=aΔf+b, whichΔfis displacement of dominant frequency, a and b is fitting parameters, this new method show that the correlation coefficient(r), average relative deviation (ARD) and root mean square error of cross validation (RMSECV) between actual viscosity and predictive values obtained by prediction model, were 0.979, 5.47% and 0.074, respectively. It is concluded that multi-scale analysis of AE is feasible for predicting fluid viscosity.
3. The viscosity prediction models for sucrose-water system are obtained, desire to on-line inspection for viscosity of circulating water from slag pool. A characteristic frequency band of acoustic emission (AE) signals was obtained by using wavelet transform and Hurst analysis. Then it was observed that the energy of AE signals at different frequencies changed regularly with increasing black water viscosity. A new method for building prediction model of black water viscosity was presented based on this regular behavior. This new method was verified by the aqueous sucrose solutions system in a stirred vessel, which showed that the correlation coefficient(r), average relative deviation (ARD) and root mean square error of cross validation (RMSECV) between actual viscosity and predictive values obtained by prediction model, were 0.970,11.9% and 1.228. respectively. It is concluded that multi-scale analysis of AE is feasible for predicting black water viscosity.
4. A criterion for the generation of large slag is presented based on acoustic emission (AE), namely the curve of energy and variance appears spike means that the generation of large slag, namely, energy E>1.5Eo, variance S>1.2S0, the average absolute relative deviation (AARD) is 0.34% when compared with ones by the method of visual observation. So this criterion cans detection the generation of large slag.
5. A characteristic frequency band of acoustic emission (AE) signals, which represented the impact of the slag on the wall, was obtained by using wavelet transform and Hurst analysis. Then it was observed that the energy of AE signals at different frequencies changed regularly with increasing the height of slag pool, namely the height of the first step change in the characteristic energy curve is the stack height. Take water-glass beads for example, the average absolute relative deviation (AARD) is 3.94% when compared with ones by the method of visual observation. So this criterion cans detection the stack height.
引文
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