基于RBF的船用污水处理装置运行状态在线监测研究

Operating state monitoring of ship sewage treatment equipment based on RBF

应用径向基函数RBF神经网络对船用污水处理装置运行状态在线监测,以提高船用污水处理装置运行状态监测与管理的效率。在分析了RBF神经网络原理的基础上,研究一种监测船用污水处理装置运行状态的三层径向基神经网络。通过实际在线监测数据的RBF神经网络监测训练和实验验证,表明RBF神经网络对运行状态的分类效果较佳,能够有效地监测船用污水处理装置的状态,并为装置维修提供科学的决策支持。

A operating state monitoring method of ship sewage treatment equipment adopting radial-basis function（RBF） neural network is introduced to improve .the state monitor validity. Based on the analyzing about the structure and fundamental of RBF neural network ,a three-layer RBF neural network is designed to diagnose the state of ship sewage treatment equipment. Then ,the RBF neural network diagnosis is realized utilizing the practical monitoring data from a ship. It is proved by diagnosis results that RBF neural network is a strong classifier which can be used to state diagnosis of ship sewage treatment equipment effectively.