基于聚类算法的水处理机设备故障诊断方法设计  

Design of Water Treatment Equipment Fault Diagnosis Method Based on Clustering Algorithm

作　　者：陈人教 CHEN Renjiao(Sanya Environmental Water Purification Co.,Ltd.,Sanya,Hainan 572000,China)

机构地区：[1]三亚环境投资集团有限公司,海南三亚572000

出　　处：《自动化应用》2023年第9期140-142,145,共4页Automation Application

摘　　要：为提升水处理机设备故障诊断效果,缩短诊断时间,降低错诊率,本文设计了一种基于聚类算法的水处理机设备故障诊断方法。采用限幅滤波和小波变换降噪法预处理原始故障信息,去除原始数据中的噪声信号与干扰信号,利用聚类算法对数据信息进行聚类分析,提取设备故障特征,通过对故障特征进行归一化处理,以及与阈值比对,确定特征状态,诊断出水处理机设备故障状态。经实验证明,设计方法诊断时间较短,错诊率在2%以内,具有良好的水处理机设备故障诊断效果。This paper presents a fault diagnosis method of water treatment equipment based on clustering algorithm with the aim of improving the diagnostic accuracy and reducing the diagnosis time and misdiagnosis rate.Firstly,the original fault information is preprocessed using amplitude limiting filtering and wavelet transform denoising methods to remove noise and interference signals from the raw data.Next,the preprocessed data is analyzed using clustering algorithms to extract the equipment's fault characteristics.To diagnose the fault state of the water treatment equipment,the extracted characteristics are normalized and compared to a threshold value to determine the characteristic state.The experimental results demonstrate that this method provides a short diagnosis time and a low false diagnosis rate,with less than 2%of false positives encountered.Overall,this approach proves to be effective for the fault diagnosis of water treatment equipment.

关 键 词：聚类算法 水处理机设备 故障诊断 限幅滤波 小波变换降噪法 

分 类 号：TM74[电气工程—电力系统及自动化]