[1]张海霞,徐 娟.基于自适应模糊神经网络推理系统的齿轮箱故障诊断方法[J].机械与电子,2015,(02):51-54.
　ZHANG Haixia,XU Juan.Gearbox Fault Detection Method Based on Adaptive Neuro-Fuzzy Inference System[J].Machinery & Electronics,2015,(02):51-54.
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基于自适应模糊神经网络推理系统的齿轮箱故障诊断方法
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《机械与电子》[ISSN:1001-2257/CN:52-1052/TH]

卷:
期数:
2015年02期
页码:
51-54
栏目:
自动控制与检测
出版日期:
2015-02-25

文章信息/Info

Title:
Gearbox Fault Detection Method Based on Adaptive Neuro-Fuzzy Inference System
文章编号:
1001-2257(2015)02-0051-04
作者:
张海霞; 徐 娟
(秦皇岛供电公司,河北 秦皇岛 066004)
Author(s):
ZHANG Haixia; XU Juan
(Qinhuangdao Power Supply Company,Qinhuangdao 066004,China)
关键词:
状态监测;  自适应模糊神经推理系统;  齿轮箱故障;  故障检测;  运行参数
Keywords:
condition monitoring;  adaptive neuro-fuzzy inference system;  gearbox fault;  fault detection;  operating parameters
分类号:
TM93
文献标志码:
A
摘要:
研究利用从机械控制过程中获得的运行参数开发一种齿轮箱监测方法,而非振动与声音的传统测量方法。为了检测齿轮箱状态,采用一种自适应模糊神经推理系统来获取电机电流和控制参数之间的非线性相关性。比较自适应模糊神经推理系统模型产生的预测值和实测值来预测齿轮箱异常状态。试验结果表明,自适应模糊神经推理系统模型能够作为齿轮箱状态监测与故障检测的一种有效工具。
Abstract:
This study force to develop the gearbox monitoring methods using the operating parameters obtained from machine control processes rather than the traditional measurements such as vibration and acoustics.To monitor the gearbox conditions,an adaptive neuro-fuzzy inference system(ANFIS)is used to capture the nonlinear connections between the electrical motor current and control parameters such as load settings and temperature. The experimental results show that ANFIS model is able to serve as an efficient tool for gearbox condition monitoring and fault detection.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2014-10-22
作者简介:张海霞(1977-),女,河南驻马店人,工程师,硕士研究生,研究方向为电力系统运行、分析、控制和规划。
更新日期/Last Update: 2015-02-25