中国科学院沈阳自动化研究所机构知识库
Advanced  
SIA OpenIR  > 自动化系统研究室  > 学位论文
题名: 汽车变速器故障诊断数据采集及特征提取算法研究
其他题名: Study on Data Acquisition and Feature Extraction Algorithms of Automobile Transmission Fault Diagnosis
作者: 姚秀琴
导师: 彭威
分类号: TP206.3
关键词: 故障诊断 ; 数据采集 ; 特征提取 ; 测点位置 ; 故障分类
索取号: TP206.3/Y35/2011
学位专业: 控制理论与控制工程
学位类别: 硕士
答辩日期: 2011-05-27
授予单位: 中国科学院沈阳自动化研究所
学位授予地点: 中国科学院沈阳自动化研究所
作者部门: 自动化系统研究室
中文摘要: 本课题是国家863高技术研究发展计划资助项目“汽车变速器装配过程综合质量问题诊断、评估与度量技术”及国家自然科学基金项目“基于解释/归纳策略的汽车变速箱新产品故障诊断机器学习方法研究”的主要研究内容之一,同时以沈阳上汽金杯汽车变速器新产品为应用背景,以阶次分析和特征提取为理论依据,设计开发了数据采集、时频分析、学习训练、在线检测、数据存储等五个主要功能模块,其目的在于实现工业现场汽车变速器的在线故障诊断,识别故障类别,为变速器的检测和维修提供依据,从而有助于提高生产效率。 在变速器故障诊断过程中,首先以LabVIEW为开发平台,利用NI公司的PCI-4474和PCI-6601数据采集卡完成了变速器的振动信号和转速信号采集。在程序设置中,主要解决了数据同步的问题,同时对采集板卡之间的程序主控实现进行了较为系统的研究,成功配置了变速器故障诊断软硬件平台及应用系统。 其次,本文讲述了时域分析、频域分析、包络谱分析、倒频谱分析等信号处理方法,详细研究了基于时频域的特征提取在设备诊断学中的应用。采用阶次分析的方法进行旋转机械的故障判别,并介绍了其与传统频域分析的不同。由于在不同测点位置处通过振动传感器获取的振动信号包含的故障特征是不同的,所以从变速器不同位置处采集的信号中提取特征值进行分析评价,选取更能表征各种故障特征的最佳安装位置,为变速器故障诊断奠定基础。 最后,根据变速器的故障类别,建立BP神经网络模型进行故障分类研究,将阶次分析得到的128阶阶次谱作为神经网络训练的输入参数,进行仿真分析。由于BP网络存在收敛慢、不稳定性等缺点,利用遗传算法(GA)优化BP神经网络,结果表明GA-BP网络能够加快网络的收敛速度,并且具有较好的性能及相对较高的预测精度,从而保证了故障分类的准确性和可靠性。 本文设计实现的变速器故障诊断系统,目前已在上汽金杯变速器生产线上应用,满足装配过程中的现场控制及功能要求,可有效提高汽车变速器的故障检测效率,具有较高的推广应用性。
英文摘要: This subject is one of main research of the project of “the diagnosis, evaluation and measurement technology of integrated quality problem in the process of automobile transmission assembly” supported by the National 863 High Technology Research and Development Program and the National Natural Science Foundation “research on the learning method of fault diagnosis of new product of automobile transmission based on explanation/induction strategy ”, Meanwhile automobile transmission in SAIC-JinBei is researched as application background for system development, based on the theory of order analysis and feature extraction, five main function modules which contain data acquisition, time-frequency domain analysis, training, online testing and data storage are designed and developed, it aims to realize on-line fault diagnosis of the automobile transmission in industrial site, identify fault category and provide the basis for detection and maintenance of the transmission, thereby helping to improve production efficiency. In the process of transmission fault diagnosis, firstly, based on the development platform of LabVIEW, the acquisitions of vibration signal and speed signal of transmission are completed by using the PCI-4474 and PCI-6601 data acquisition card of NI company. In program settings, data synchronization is one of the key technologies to solve , meanwhile the procedure master realization of acquisition cards is studied systematically, software and hardware platform of fault diagnosis and application system of transmission are configured successfully. Secondly, the signal processing methods of time-domain analysis, frequency –domain analysis, envelope spectrum analysis and inverse spectrum analysis are  described in this paper, the application of the feature extraction based on time-frequency domain is studied detailly. order analysis is used to distinguish the fault of rotating machinery ,and the differences between order analysis and traditional frequency domain analysis are introduced. Because fault characteristics which vibration signals contain are different by getting from vibration sensor in different measure locations, eigenvalues are extracted from signals which is collected from different locations to analyze and evaluate, the best installation location of characterizing fault feature morely is selected, and it lay the foundation for transmission fault diagnosis. Finally, according to fault categories of transmission, a BP neural network model is established for fault classification research, 128 orders which obtained from order analysis are used as input parameters of neural network to train and analyze. Due to such shortcomings of the BP network as slowness in convergence, instability .Genetic algorithm (GA) is used to optimize BP neural network, the simulation results show that GA-BP network can accelerate the speed of convergence, has good performance and relatively high precision of prediction, so as to ensure fault classification accuracy and dependability. The transmission fault diagnosis system which is designed and implemented in the paper has been running on the SAIC-JinBei automobile transmission assembly line and can meet field control and functional requirements, which can effectively improve the efficiency of the automobile transmission fault detection and has higher promotion application.
语种: 中文
产权排序: 1
内容类型: 学位论文
URI标识: http://ir.sia.cn/handle/173321/9324
Appears in Collections:自动化系统研究室_学位论文

Files in This Item:
File Name/ File Size Content Type Version Access License
汽车变速器故障诊断数据采集及特征提取算法研究.pdf(1659KB)----限制开放 联系获取全文

Recommended Citation:
姚秀琴.汽车变速器故障诊断数据采集及特征提取算法研究.[硕士学位论文].中国科学院沈阳自动化研究所.2011
Service
Recommend this item
Sava as my favorate item
Show this item's statistics
Export Endnote File
Google Scholar
Similar articles in Google Scholar
[姚秀琴]'s Articles
CSDL cross search
Similar articles in CSDL Cross Search
[姚秀琴]‘s Articles
Related Copyright Policies
Null
Social Bookmarking
Add to CiteULike Add to Connotea Add to Del.icio.us Add to Digg Add to Reddit
所有评论 (0)
暂无评论
 
评注功能仅针对注册用户开放,请您登录
您对该条目有什么异议,请填写以下表单,管理员会尽快联系您。
内 容:
Email:  *
单位:
验证码:   刷新
您在IR的使用过程中有什么好的想法或者建议可以反馈给我们。
标 题:
 *
内 容:
Email:  *
验证码:   刷新

Items in IR are protected by copyright, with all rights reserved, unless otherwise indicated.

 

 

Valid XHTML 1.0!
Copyright © 2007-2016  中国科学院沈阳自动化研究所 - Feedback
Powered by CSpace