摘要
对汽轮机转子故障进行诊断是确保汽轮机安全运行的关键。振动信号的分析在汽轮机转子故障诊断中广泛应用。应用小波包分析方法提取振动信号特征值,进一步作为BP神经网络的输入量,建立信号特征与其故障类型的非线性映射关系,利用神经网络实现故障诊断。仿真结果表明,该方法可以有效地对汽轮机转子故障进行诊断。
Turbine rotor fault diagnosis is the key to ensuring the safe operation of the steam turbine. Vibration signal analysis is widely used in turbine rotor fault diagnosis. The wavelet packet analysis method was adopted to extract the vibration signal eigenvalue as the input of BP neural network, the nonlinear mapping relationship between signal features and fault type and realizing the fault diagnosis with BP neural network was established. The simulation results show that this method can effectively diagnosis turbine rotor fault.
出处
《辽宁石油化工大学学报》
CAS
2013年第3期67-69,共3页
Journal of Liaoning Petrochemical University
基金
辽宁省科技攻关项目(2011216011)
