摘要
提出了一种恒误差修正率控制的网络学习率和动量系数自适应调整方法,克服了网络训练收敛时间长和陷入局部最优的缺点;并根据大型汽轮发电机组振动故障的特点,建立了改进的BP网络故障诊断模型.对一实际汽轮机发电机组振动故障事例的诊断结果表明,该方法有效地提高了故障诊断的精度和可靠度.
A new network training rate controlled by a constant error correction rate and a selfadaptive momentum coefficient adjustment method were put forward to shorten the convergence time and overcome the local optimization. A fault diagnosis model based on the improved BP network was established for the vibration faults of steam turbinegenerator sets. The application of the model to diagnosis of a practical generator set shows that the method is effective.
出处
《河海大学学报（自然科学版）》
CAS
CSCD
北大核心
2003年第2期233-236,共4页
Journal of Hohai University(Natural Sciences)
