【摘要】 针对当前复杂供水管网泄水事故频发的现象,提出以管网发生故障时的瞬态水力数据信息为样本,采用Hilbert-Huang变换将故障样本信息从水压—时间的时域信号转换为压力幅值—频率的频域信号。分析选取频域信号中的主要特征值坐标作为支持向量机(SVM)的输入数据,并采用粒子群算法(PSO)对SVM参数进行优化,建立了基于HHT和SVM的供水管网故障诊断模型。实例应用表明,该模型在供水管网泄漏诊断中效果较好,从而验证了模型的可行性。更多还原

【Abstract】 Aiming at the phenomenon of water supply network discharge accidents,a method was proposed,which considers transient hydraulic pipeline failure data as samples and uses Hilbert-Huang Transform(HHT)to transit the fault data from water pressure-time to pressure amplitude-frequency.The main eigenvalues of frequency domain signal were regarded as the input of support vector machine(SVM),and particle swarm optimization(PSO)was used to optimize the parameters of SVM.Then a model of water supply pipe network fault diagnosis was built based on the HHT and SVM.The example shows that this model can get good diagnosis effect of water supply network leakage.So,the feasibility of the model is verified.更多还原