基于动态参数测量的低压汽轮机末级叶片局部损伤识别

K. Shetkar, Jithendra Srinivas
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引用次数: 3

摘要

汽轮机叶片是电力系统中轴系的重要部件,受到高温的影响,会导致低/高周疲劳失效。在启动和关闭过程中发生的瞬态条件会产生交替应力,导致叶片根部断裂。本文研究了低压汽轮机末级叶片局部损伤对叶片振动特性和损伤识别的影响。首先,利用有限元模型对最后一排低压叶片截面进行了自由振动研究和瞬态分析。根区附近的裂纹用扭簧来模拟,其刚度用裂纹深度比来表示。详细研究了裂纹深度比和靠近根部位置对固有频率和瞬态响应幅值的影响。通过反向传播神经网络模型建立了损伤参数与叶片频率之间的关系。
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Localized damage identification in the last stage low-pressure steam turbine blade using dynamic parameter measurements
Steam turbine blades are the important components in power system shaft lines subjected to severe temperatures, leading to low/high cycle fatigue failures. The transient conditions occurring during startup and shutdown events generate alternative stresses causing the fracture at the blade roots. Present work deals with the effect of localized damage on the vibration characteristics and damage identification study in the last stage LP (low pressure) steam turbine blade. Initially, free vibration studies and transient analysis of the last row LP blade section are conducted using the finite element model. A crack near the root region is modeled by a torsional spring, whose stiffness is expressed in terms of crack depth ratio. Effects of crack depth ratio and location near the roots on the natural frequencies and transient response amplitudes are studied in detail. The relationship between the damage parameters and blade frequencies is established through the back propagation neural network model.
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来源期刊
CiteScore
3.80
自引率
9.10%
发文量
25
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