Optics and Precision Engineering, Volume. 30, Issue 16, 1905(2022)
Infrared intelligent condition monitoring and fault diagnosis of rotating machinery
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Fig. 4. Infrared intelligent fault diagnosis process of rotating machinery
Fig. 8. Infrared intelligent fault diagnosis of rotating machinery
Table 1. Target detection results
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Random Group mAP mIoU 1 97.80% 83.30% 2 99.35% 82.33% 3 96.93% 81.30% 4 96.08% 78.29% 5 97.37% 80.23% 6 94.83% 80.01% 7 92.22% 80.63% 8 99.65% 80.02% 9 99.51% 84.89% 10 95.78% 80.15%
Table 2. State classification accuracy
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Random Group Rotor system Motor 1 100% 98.81% 2 99.40% 98.81% 3 100% 98.81% 4 100% 98.21% 5 99.40% 98.21% 6 100% 98.81% 7 100% 100% 8 100% 98.21% 9 100% 98.21% 10 100% 98.81%
Table 3. Intelligent fault diagnosis accuracy
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Item Motor Rotor system Both 1 97.62% 95.24% 93.45% 2 90.48% 95.83% 86.90% 3 94.05% 97.62% 91.67% 4 95.24% 93.45% 88.69% 5 94.64% 92.86% 88.10% 6 93.45% 95.24% 89.29% 7 97.02% 89.29% 86.90% 8 94.05% 97.02% 91.67% 9 94.64% 98.81% 93.45% 10 95.83% 94.64% 90.48% Mean 94.70% 95.00% 90.06%
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Yang WANG, Li YANG. Infrared intelligent condition monitoring and fault diagnosis of rotating machinery[J]. Optics and Precision Engineering, 2022, 30(16): 1905
Paper Information
Category: Modern Applied Optics
Received: Jun. 10, 2021
Accepted: --
Published Online: Sep. 22, 2022
The Author Email: WANG Yang (373647411@qq.com)
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