摘要
Industrial robots commonly perform cyclic reciprocating motions during operation. The dynamic loads caused by frequent acceleration and deceleration make the RV reducers of the robots prone to failure and generate abnormal vibration during operation. However, the variable speed condition makes it difficult to analyze the frequency of the vibration signal. This paper proposes a frequency-adaptive method to analyze the vibration signals to identify the frequency range of vibration energy distribution. A filter bank is designed based on this frequency range, enhancing the target frequency while lowering other unnecessary frequency components of the Short-Time Fourier Transform (STFT) spectrogram. Features extracted from the enhanced spectrograms were employed to identify and classify various failure types. In experimental trials involving a six-joint serial industrial robot, the frequency-adaptive approach achieved a classification accuracy of 93.06% across 108 trials. These results suggest that the proposed method is highly effective for monitoring variable speed conditions and diagnosing faults in RV reducers.
| 源语言 | 英语 |
|---|---|
| 主期刊名 | 15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024 |
| 编辑 | Huimin Wang, Steven Li |
| 出版商 | Institute of Electrical and Electronics Engineers Inc. |
| ISBN(电子版) | 9798350354010 |
| DOI | |
| 出版状态 | 已出版 - 2024 |
| 活动 | 15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024 - Beijing, 中国 期限: 11 10月 2024 → 13 10月 2024 |
出版系列
| 姓名 | 15th Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024 |
|---|
会议
| 会议 | 15th IEEE Global Reliability and Prognostics and Health Management Conference, PHM-Beijing 2024 |
|---|---|
| 国家/地区 | 中国 |
| 市 | Beijing |
| 时期 | 11/10/24 → 13/10/24 |
联合国可持续发展目标
此成果有助于实现下列可持续发展目标:
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可持续发展目标 3 良好健康与福祉
学术指纹
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