【作者】 杨化动；

【导师】 徐鸿；

【作者基本信息】 华北电力大学 ， 动力机械及工程， 2014， 博士

【摘要】 轴流式压气机是燃气轮机发电机组中重要的组成部分之一,由于机组功率的50%-60%由压气机消耗,因此压气机性能的高低直接影响发电机组的效率。在压气机的众多失效模式中,积垢造成的压气机性能退化达到70%-85%,因此研究压气机积垢的形成机理,分析积垢对轴流式压气机性能的影响,讨论压气机积垢的监测与控制策略,对于燃气轮机机组的安全、高效和健康运行具有非常重要的现实意义。本文取得的主要研究成果如下：(1)从微观角度对颗粒物在压气机内部的输送过程和沉积过程进行理论和数值仿真分析,建立了颗粒物输送机理与叶片不同位置之间的对应关系,所得到的结论是压力面积垢是由于较大颗粒物的惯性作用的结果,而吸力面积垢的主要原因是因为小颗粒物的湍流扩散造成的。然后,分别研究了颗粒物大小、颗粒物浓度、入口温度、初始速度、旋转速度、表面粗糙度和湿度等因素对积垢形成的影响。(2)对单级轴流式压气机积垢行为建模方法进行分析,对过去采用表面粗糙度以及厚度等参数的设定表征积垢行为存在的缺陷进行讨论,提出利用压气机叶片型面参数的变化,将逆向工程中的测量技术与传统的CFD分析方法相结合,获取积垢叶片的准确几何模型,真实反映叶片积垢的实际状态,提高性能仿真的精度。(3)提出了多级轴流式压气机性能预测的新方法,改变原有方法只能针对某一指定时刻积垢状态进行分析的缺点,将积垢的多级轴流式压气机划分为两部分,分别选择合理的计算方法。对于积垢部分的性能计算,采用级堆叠方法、相似理论和线性退化模型相结合,充分考虑级间积垢分布的差异及其它影响因素。对于无积垢级的性能计算,采用平均微元级计算其性能。(4)提出了压气机积垢状态监测的优化方案,改变过去仅仅依靠某一性能参数进行监测所存在的缺陷。在运行的初期,主要基于热力学性能参数的变化进行判断,当性能参数下降到一定程度的时候,再结合对叶片型面参数的监测,对压气机积垢的状态进行准确评估。(5)对压气机清洗时间间隔进行分析,获得优化数学模型,为压气机积垢的控制提供支持。更多还原

【Abstract】 Axial flow compressor is one of the important parts of gas turbine units. Because50%-60%power of unit is consumed by the axial flow compressor, the compressor performance directly affects the efficiency of the whole unit. In many failure modes in the compressor,70%-85%compressor performance degradation is caused by fouling. Therefore, it is very important to study the fouling mechanism. The effect of fouling on the performance of an axial compressor and the monitoring and control strategies of compressor fouling can not be ignored. It has very important practical significance for the safe, efficient and healthy operation of gas turbine. The main achievements in this paper are as follows:(1) Theoretical analysis and numerical simulation of particle transport mechanism and deposition process in compressor are implemented from the microscopic point of view. And then, the relation between the particle deposition mechanism and blade position is established. The fouling in pressure side is due to the inetia effect of larger particles, and the fouling in suction side is due to the turbulent diffusion caused by small particles. Then, the influence of particle size, particle volume concentration, temperature, the initial speed of entrance, rotation speed, surface roughness and humidity on deposit formation were studied.(2) The modelling methods of fouling behavior for a single stage axial flow compressor are analyzed. And then, the shortcoming in the last modelling methods is discussed. In this paper, a new method is presented by using the combining measuring technology applied in reverse engineering with a traditional CFD analysis method to obtain accurate geometrical model of fouled blade. The real state of fouled blade can be effectively characterized by this method. Therefore, it can accurately simulate the effect of fouling on compressor performance.(3) A new performance prediction method of multistage axial flow compressor is put forward which overcome the disadvantages of tradional method. The fouled multistage axial flow compressor is divided into two parts for which a reasonable computing method is respectively chosed. For the fouled stages, the performance is calculated by combining stage stacking method, similarity theory with linear progression model. On the other hand, the performance of non-fouled stages is computed by averaged infinitesimal stage method.(4) The optimizational scheme of compressor fouling monitoring is put forward which deal with the problems existed in monitoring method relyed on single parameter. In the intial operation, the judgement is based on the performance parameters. When they reduced to a certain extent of the performance, the blade profile parameters are monitored so as to accurately evaluate the fouling severity.(5) The compressor cleaning interval is analyzed in order to obtain the optimized mathematical model.更多还原