Research on fault diagnosis of hydropower generating unit vibration based on neural network and d - s evidence theory 基于神经网络和证据理论融合的水电机组振动故障诊断研究
Vibration and other fault of hydroelectric set is the main factor that affect the power set to run safely and stably 水电机组的振动以及其它故障是影响机组安全、稳定运行的主要因素。
Research on vibrant fault diagnosis of hydro - turbine generating unit based on wavelet packet analysis and support vector machine 基于小波包分析和支持向量机的水电机组振动故障诊断研究
It shows that the wavelet analysis has the predominance and potentials in the monitoring and fault system 说明了小波分析在水电机组的在线监测与故障诊断系统的应用中具有很大的优势和潜力。
So the study of faults diagnose system and test technology of large - scale hydropower units is very impendency and important 所以，对大型水电机组故障诊断系统及测试技术的研究是十分迫切而又极为重要。
The vibration fault diagnosis of hydro - turbine generating unit is investigated by the method of spectrum analysis and wavelet neural network classifier 摘要提出应用频谱法和小波神经网络对水电机组的振动故障进行诊断。
Wireless sensor network , which is a new way for collecting data , provides an excellent choice for hydrogenerator condition monitoring 无线传感器网络作为一种新的数据采集技术为水电机组状态监测提供了一种极佳的选择。
With matlab and its fuzzy logic toolbox , fuzzy inference system ( fis ) of hydro - generator unit fuzzy gpss is founded and so the fuzzy gpss is attained with the aid of computer 利用matlab的模糊逻辑工具箱建立水电机组模糊gpss的模糊推理系统，实现了模糊gpss的计算机辅助设计。
The system uses signal processing , monitoring technology and network , so it can monitor the unit on - line and real - time to help operation and servicing worker 本文对实际并网运行的机组实施全面的在线实时监测,将信号处理技术,水电机组测量技术,以及网络技术结合起来应用于工业现场,为运行
Enhancement of the operation stability of hydroelectric unit , development of the fault diagnose technology , and actualization of condition monitoring are the requirement of the reform of power system 提高水电机组运行稳定性,发展故障诊断相关的研究技术和实测手段,实施状态检修,是电力改革的必然要求
