A fault diagnosis method for optical elements based on infrared and visible light videos
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摘要: 光学元件的健康状态是激光系统稳定运行的关键，如何在激光系统工作状态下实现光学元件的实时监测和故障诊断定位是该专业领域亟需解决的问题。针对该问题，提出了一种基于红外和可见光视频信息的光学元件故障诊断方法。首先，使用长波红外相机和可见光相机采集光学元件工作过程中的视频信息；然后，对采集的视频信息使用异常点检测算法进行处理；最后，结合光学元件温升特性对光学元件进行故障诊断及定位。试验结果表明：相同算法情况下，该方法相较于单独使用红外视频进行故障诊断的方法在故障诊断准确率、虚警率和漏警率3个指标上分别提升9.70%、3.60%和6.10%；该方法相较于单独使用可见光视频进行故障诊断的方法在故障诊断准确率、虚警率和漏警率3个指标上分别提升18.00%、16.00%和2.00%。Abstract: Optical elements are the core components of laser systems, and their health status is the key to the stable operation of laser systems. How to realize real-time monitoring and fault diagnosis of optical elements in the working status of laser systems is a problem that urgently needs to be solved in this professional field. To solve this problem, this paper proposes a fault diagnosis method for optical elements based on infrared and visible light videos. Firstly, a long-wave infrared camera and a visible light camera are used to collect video information during the working process of the optical element. Then, the collected video information is processed using anomaly point detection algorithms. Finally, the fault diagnosis and localization of the optical element are carried out in combination with the thermal rise characteristics of the optical element. The experimental results show that, under the same algorithm, the method proposed in this paper has improved the fault diagnosis precision rate, false alarm rate and missed alarm rate by 9.70%, 3.60% and 6.10%, respectively, compared with the method of fault diagnosis using infrared videos alone; the method proposed in this paper has improved the fault diagnosis precision rate, false alarm rate and missed alarm rate by 18.00%, 16.00% and 2.00%, respectively, compared with the method of fault diagnosis using visible light videos alone.
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Key words:
- optical element /
- health status /
- infrared video /
- visible light video /
- fault diagnosis
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图 5 不同二值化阈值下可见光故障定位时间
Figure 5. Visible light FLT under different binarization threshold
图 6 不同二值化阈值下可见光FDPR、FAR、MAR
Figure 6. Visible light FDPR, FAR and MAR under different binarization threshold
表 1 两种视频异常点检测情况说明表
Table 1. Description of two videos’ anomaly detection
infrared video visible light video process flow case1 normal normal normal process flow case2 abnormal normal next step, analyze temperature information case3 abnormal abnormal position matching，output fault information directly case4 normal abnormal impossible case5 abnormal abnormal position mismatching，impossible 
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表 2 三种方法的指标对比结果表
Table 2. Experimental results of indicators of three methods
No. FDPR /% FLT/ms FAR /% MAR /% method 1 88.80 228 4.60 6.60 method 2 80.50 97 17.00 2.50 method 3 98.50 135 1.00 0.50
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[1] Conder A, Alger T, Azevedo S, et al. Final optics damage inspection (FODI) for the National Ignition Facility[C]//Proceedings of SPIE 6720. 2008: 672010. [2] Deng Hongxiang, Guo Wenli, Gao Huanhuan, et al. A numerical approach for femtosecond laser-induced photoionization in solids and its application[J]. Journal of Optics, 2019, 21: 075501. doi: 10.1088/2040-8986/ab2357 [3] Jing Xufeng, Tian Ying, Zhang Junchao, et al. Modeling validity of femtosecond laser breakdown in wide bandgap dielectrics[J]. Applied Surface Science, 2012, 258(10): 4741-4749. doi: 10.1016/j.apsusc.2012.01.070 [4] 邓燕, 许乔, 柴立群, 等. 光学元件亚表面缺陷的全内反射显微检测[J]. 强激光与粒子束, 2009, 21(6):835-840Deng Yan, Xu Qiao, Chai Liqun, et al. Total internal reflection microscopy: a subsurface defects identification technique in optically transparent components[J]. High Power Laser and Particle Beams, 2009, 21(6): 835-840 [5] 赵文川, 钟显云, 刘彬. 基于条纹反射的光学表面疵病检测法[J]. 光子学报, 2014, 43:0912007 doi: 10.3788/gzxb20144309.0912007Zhao Wenchuan, Zhong Xianyun, Liu Bin. The surface flaws inspection of optical components based on the fringe reflection[J]. Acta Photonica Sinica, 2014, 43: 0912007 doi: 10.3788/gzxb20144309.0912007 [6] 任冰强, 黄惠杰, 张维新, 等. 光学元件损伤在线检测装置及实验研究[J]. 强激光与粒子束, 2004, 16(4):465-468Ren Bingqiang, Huang Huijie, Zhang Weixin, et al. Online inspection apparatus and experiments on optics damage[J]. High Power Laser and Particle Beams, 2004, 16(4): 465-468 [7] 解亚平. 高功率固体激光光学元件损伤在线检测装置的研究[D]. 武汉: 华中科技大学, 2006: 35-40Xie Yaping. Research of online inspection equipment for optic damage of high power solid laser[D]. Wuhan: Huazhong University of Science and Technology, 2006: 35-40 [8] 范哲源, 曹剑中, 屈恩世, 等. 一种8倍可见光变焦光学系统设计[J]. 光子学报, 2010, 39(s1):101-104 doi: 10.3788/gzxb201039s1.0101Fan Zheyuan, Cao Jianzhong, Qu Enshi, et al. Design of an 8 times ratio visible zoom optical system[J]. Acta Photonica Sinica, 2010, 39(s1): 101-104 doi: 10.3788/gzxb201039s1.0101 [9] 彭志涛. 强激光复杂光机组件光学元件激光损伤在线检测技术研究[D]. 绵阳: 中国工程物理研究院, 2011: 41-48Peng Zhitao. On-line laser damage detection technology for optical components of high-power complex optical-mechanical components[D]. Mianyang: China Academy of Engineering Physics, 2011: 41-48 [10] 张文学, 王继红, 任戈. 基于相机阵列的光学组件缺陷在线检测方法[J]. 强激光与粒子束, 2020, 32:051001 doi: 10.11884/HPLPB202032.190444Zhang Wenxue, Wang Jihong, Ren Ge. Optical elements defect online detection method based on camera array[J]. High Power Laser and Particle Beams, 2020, 32: 051001 doi: 10.11884/HPLPB202032.190444 [11] 黄柏, 杨帆, 邓剑平, 等. 基于累积帧间差分法和掩膜的SF6红外检漏视频定位算法研究[J]. 电气技术, 2022, 23(7):104-108Huang Bo, Yang Fan, Deng Jianping, et al. Study of an accumulated interframe difference and mask based SF6 leakage infrared video location method[J]. Electrical Engineering, 2022, 23(7): 104-108 [12] 赵高鹏, 薄煜明, 尹明锋. 一种红外和可见光双通道视频目标跟踪方法[J]. 电子与信息学报, 2012, 34(3):529-534Zhao Gaopeng, Bo Yuming, Yin Mingfeng. An object tracking method based on infrared and visible dual-channel video[J]. Journal of Electronics & Information Technology, 2012, 34(3): 529-534 [13] 尹丽华, 杭娟, 康亮, 等. 基于联合相机路径的红外视频稳像算法[J]. 红外与激光工程, 2021, 50:20200405 doi: 10.3788/IRLA20200405Yin Lihua, Hang Juan, Kang Liang, et al. Infrared video image stabilization algorithm based on joint camera path[J]. Infrared and Laser Engineering, 2021, 50: 20200405 doi: 10.3788/IRLA20200405 [14] 李向燕, 王肖霞, 杨风暴. 一种基于差异特征驱动的红外与可见光视频拟态融合方法[J]. 电子测量技术, 2021, 44(22):114-120Li Xiangyan, Wang Xiaoxia, Yang Fengbao. Fusion method of infrared and visible video mimicry based on difference feature driving[J]. Electronic Measurement Technology, 2021, 44(22): 114-120 [15] 赵元安, 邵建达, 刘晓凤, 等. 光学元件的激光损伤问题[J]. 强激光与粒子束, 2022, 34:011004 doi: 10.11884/HPLPB202234.210331Zhao Yuanan, Shao Jianda, Liu Xiaofeng, et al. Tracking and understanding laser damage events in optics[J]. High Power Laser and Particle Beams, 2022, 34: 011004 doi: 10.11884/HPLPB202234.210331 -
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