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基于神经网络观测器的机器人故障诊断方法研究
Alternative TitleNeural Network Observer-based Robot Fault Diagnosis Scheme
张会彬1,2; 蒋强1; 张伟2; 高升2; 季毅巍3
Department空间自动化技术研究室
Source Publication自动化与仪表
ISSN1001-9944
2018
Volume33Issue:8Pages:49-53
Contribution Rank1
Keyword径向基函数 神经网络观测器 机器人系统 故障诊断
Abstract径向基函数神经网络对非线性映射具有强大的逼近能力和良好的泛化能力。该文针对机器人系统的故障诊断问题,提出了基于径向基函数神经网络的故障诊断方法,依靠径向基神经网络的结构优势,设计了一种机器人系统的人工神经网络观测器,通过比较运行过程中实际系统与观测器的输出差异,获得各关节运行参数的残差,实现对故障的识别。仿真采用二连杆机器人系统为研究对象来验证该文提出的方法,仿真结果表明了故障诊断方法的有效性。
Other AbstractThe radial basis function neural network has ability of approximation and generalization ability for nonlinear mapping. For fault diagnosis problem of robot system,a fault diagnosis method based on radial basis function neural network is proposed. Relying on the structural advantages of radial basis neural networks,an artificial neural network observer for robot systems is designed. By comparing the difference between the output of the actual system and the observer in the operation process,the residuals of the various joint operating parameters are obtained and analyzed to realize the identification of the fault. A two-link robot system is simulated based on the method proposed in this paper, and the effectiveness is verified.
Language中文
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/22717
Collection空间自动化技术研究室
Corresponding Author张会彬
Affiliation1.沈阳理工大学自动化与电气工程学院
2.中国科学院沈阳自动化研究所机器人国家重点实验室
3.上海微小卫星工程中心
Recommended Citation
GB/T 7714
张会彬,蒋强,张伟,等. 基于神经网络观测器的机器人故障诊断方法研究[J]. 自动化与仪表,2018,33(8):49-53.
APA 张会彬,蒋强,张伟,高升,&季毅巍.(2018).基于神经网络观测器的机器人故障诊断方法研究.自动化与仪表,33(8),49-53.
MLA 张会彬,et al."基于神经网络观测器的机器人故障诊断方法研究".自动化与仪表 33.8(2018):49-53.
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