基于小波神经网络的引风机轮毂线缆故障诊断方法  

Fault Diagnosis Method for Induced Draft Fan Hub Cable Based on Wavelet Neural Network

作　　者：赵振宇 Zhenyu Zhao(Inner Mongolia Datang International Tokto Power Plant,Hohhot,Inner Mongolia 010000)

机构地区：[1]内蒙古大唐国际托克托电厂,内蒙古呼和浩特010000

出　　处：《新疆钢铁》2024年第3期185-187,共3页Xinjiang Iron and Steel

摘　　要：传统引风机轮毂线缆故障诊断方法直接对故障特征信息数据进行预处理未对引风机故障特征信息数据进行采集,造成传统方法诊断准确率相对较低。本文基于小波神经网络的引风机轮毂线缆故障诊断方法,收集引风机故障特征信息数据,在数据采集的基础上进行数据预处理,确保数值模拟精确有效,以期能够基于小波神经网络实现引风机轮毂线缆故障诊断。The traditional method for diagnosing hub and cable faults in induced draft fans directly preprocesses the fault characteristic information data without collecting the fault characteristic information data,resulting in relatively low diagnostic accuracy of the traditional method.This article is based on the fault diagnosis method of induced draft fan hub cable using wavelet neural network.The fault characteristic information data of induced draft fan is collected,and data preprocessing is carried out on the basis of data collection to ensure accurate and effective numerical simulation,in order to achieve fault diagnosis of induced draft fan hub cable based on wavelet neural network.

关 键 词：小波神经网络 引风机 轮毂线缆故障 故障诊断 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]