基于支持向量机的可重构爬行-滚动机器人故障诊断

IF 2.5 4区 综合性期刊 Q2 CHEMISTRY, MULTIDISCIPLINARY
K. Elangovan, Y. K. Tamilselvam, R. E. Mohan, M. Iwase, Nemoto Takuma, K. Wood
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引用次数: 27

摘要

随着机器人开始在最少或没有人为干预的情况下自主执行工作,一个新的挑战出现了:机器人还需要自主检测错误并从故障中恢复。在本文中,我们提出了一个基于支持向量机(SVM)的故障诊断系统,用于一个名为Scorpio的仿生可重构机器人。当Scorpio使用爬行和滚动运动模式时,诊断系统需要检测和分类故障。具体而言,我们通过分析机载惯性测量单元(IMU)传感器数据,对故障和非故障条件进行分类。数据捕捉到了九种不同的步态,包括滚动和爬行模式,三种不同的速度。应用统计方法来提取特征并降低原始IMU传感器数据特征的维数。这些统计特征被作为训练和测试的输入。此外,还比较了支持向量机的c-SVC和nu-SVC模型及其故障分类精度。结果表明,所提出的支持向量机方法可以用于可重构机器人运行时的运动步态故障的自主诊断。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fault Diagnosis of a Reconfigurable Crawling–Rolling Robot Based on Support Vector Machines
As robots begin to perform jobs autonomously, with minimal or no human intervention, a new challenge arises: robots also need to autonomously detect errors and recover from faults. In this paper, we present a Support Vector Machine (SVM)-based fault diagnosis system for a bio-inspired reconfigurable robot named Scorpio. The diagnosis system needs to detect and classify faults while Scorpio uses its crawling and rolling locomotion modes. Specifically, we classify between faulty and non-faulty conditions by analyzing onboard Inertial Measurement Unit (IMU) sensor data. The data capture nine different locomotion gaits, which include rolling and crawling modes, at three different speeds. Statistical methods are applied to extract features and to reduce the dimensionality of original IMU sensor data features. These statistical features were given as inputs for training and testing. Additionally, the c-Support Vector Classification (c-SVC) and nu-SVC models of SVM, and their fault classification accuracies, were compared. The results show that the proposed SVM approach can be used to autonomously diagnose locomotion gait faults while the reconfigurable robot is in operation.
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来源期刊
Applied Sciences-Basel
Applied Sciences-Basel CHEMISTRY, MULTIDISCIPLINARYMATERIALS SCIE-MATERIALS SCIENCE, MULTIDISCIPLINARY
CiteScore
5.30
自引率
11.10%
发文量
10882
期刊介绍: Applied Sciences (ISSN 2076-3417) provides an advanced forum on all aspects of applied natural sciences. It publishes reviews, research papers and communications. Our aim is to encourage scientists to publish their experimental and theoretical results in as much detail as possible. There is no restriction on the length of the papers. The full experimental details must be provided so that the results can be reproduced. Electronic files and software regarding the full details of the calculation or experimental procedure, if unable to be published in a normal way, can be deposited as supplementary electronic material.
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