摘要
通过对小波变换、可变模态分解(VMD)、经验模态分解(EMD)及BP神经网络等多种算法在天然气管道中应用的学习研究,提出一种基于VMD-BP神经网络的天然气管道工况判断模型。首先对管道信号进行可变模态分解,再将分解后的特征信号通过BP神经网络算法进行网络训练测试,进而对管道工况做出判断。
Abstract Through discussing the application of algorithms like the wavelet transform and variable mode decomposition （VMI））, empirical mode decomposition （EMD） and the BP neural network in gas pipelines, a VMD-BP neural network-based judgment model for working condition of natural gas pipelines was proposed, which has the VMD mode decomposition of pipeline signals carried out and then has the decomposed characteristic signals trained and tested by the BP neural network algorithm so as to determine operating conditions of gas pipelines.
作者
梁洪卫
张旭
邹岱峰
LIANG Hong-wei ZHANG Xu ZOU Dai-feng(College of Electrical Engineering and Information, Northeast Petroleum Universit)
出处
《化工自动化及仪表》
CAS
2017年第7期633-636,655,共5页
Control and Instruments in Chemical Industry
