Joint fault diagnosis of legged robot based on acoustic processing
Joint fault diagnosis of legged robot based on acoustic processing
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DOI：
10.1109/sii.2015.7404973
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发表时间：
2015-12
期刊：
影响因子：
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通讯作者：
S. Chattunyakit;Yukinori Kobayashi;T. Emaru
中科院分区：
文献类型：
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作者：
S. Chattunyakit;Yukinori Kobayashi;T. Emaru
在步行机器人系统中，某些类型的关节故障会导致整个系统不稳定，因为预定义的控制器在损坏后无法正常工作。因此，故障诊断是防止系统发生故障的一项重要操作。本文将快速傅立叶变换和模糊逻辑分别作为特征提取和分类，提出了基于声学的腿式机器人故障诊断方法。测试结果表明，该方法能够有效地利用声学手段对接头故障进行检测，说明AFL方法在实际应用中是可行的。
In legged robot system, certain types of joint faults can lead the entire system unstable since predefined controller cannot function properly after getting damaged. Therefore, the fault diagnosis is an important operation to prevent systems from failures. In this paper, the acoustic-based fault diagnosis for legged robots (AFL) is developed by employing the FFT and fuzzy logic as a feature extraction and a classification, respectively. In the benchmark, the results indicate that the proposed method can detect and inspect the faults of joint efficiently by means of sound, meaning that AFL method is feasible to be utilized and applied in real applications.