激光自适应光学系统可靠性改进效果评估

贾启旺; 李新阳; 甘永东; 马瑞浩; 梅月; 斯那卓玛

doi:10.11884/HPLPB202436.230436

激光自适应光学系统可靠性改进效果评估

doi: 10.11884/HPLPB202436.230436

贾启旺^{1, 2, 3,},
李新阳^{1, 2, 3, ,},
甘永东^{1, 2, 3},
马瑞浩^{1, 2, 3},
梅月^{1, 2, 3},
斯那卓玛^{1, 2, 3}

1.
中国科学院光场调控科学技术全国重点实验室，成都 610209
2.
中国科学院自适应光学重点实验室，成都 610209
3.
中国科学院光电技术研究所，成都 610209

基金项目: 中国科学院创新基金项目（CXJJ-16S022）

详细信息

作者简介:
贾启旺，E-mail：jqw_ioe@163.com

通讯作者:
李新阳，E-mail：xyli@ioe.ac.cn。

中图分类号: TN249
计量
- 文章访问数: 30
- HTML全文浏览量: 16
- PDF下载量: 4
- 被引次数: 0
出版历程
- 收稿日期: 2023-12-14
- 修回日期: 2024-03-13
- 录用日期: 2024-02-29
- 网络出版日期: 2024-03-21

Evaluation of reliability improvement effect on laser adaptive optics systems

Jia Qiwang^{1, 2, 3
,},
Li Xinyang^{1, 2, 3
, ,},
Gan Yongdong^{1, 2, 3},
Ma Ruihao^{1, 2, 3},
Mei Yue^{1, 2, 3},
Sina Zhuoma^{1, 2, 3}

1.
National Key Laboratory of Optical Field Manipulation Science and Technology, Chinese Academy of Sciences, Chengdu 610209, China
2.
The Key Laboratory on Adaptive Optics, Chinese Academy of Sciences, Chengdu 610209, China
3.
Institute of Optics and Electronics, Chinese Academy of Sciences, Chengdu 610209, China

摘要

摘要: 随着自适应光学技术在激光领域的发展，工程上以经典自适应光学（AO）系统为基础，增加了多种基于软件监测和硬件保护的改进措施以保证激光AO系统稳定连续出光。面对结构复杂度提升带来的可靠性挑战，如何构建系统失效模型对激光AO系统可靠性进行评估，成为影响激光AO系统发展的重要一环。本文以激光光稳净化AO系统为例，提出使用动态故障树方法对激光AO系统可靠性进行评估，根据设备间动态关系建立动态故障树（DFT），结合厂家信息、疲劳寿命试验与历史数据估计得到底事件失效率，使用二元决策图和马尔可夫模型求解得到DFT的可靠性参数。使用DFT分析增加改进措施的AO系统可靠运行时间，结果相对于基本故障树获得了十倍以上的提高。实际系统调试期间，在预计的可靠运行时间内未发生自因故障，与DFT估计结果一致。验证了应用DFT方法评估增加改进措施后的激光AO系统可靠性更准确。
- 自适应光学 /
- 动态故障树 /
- 可靠性评估 /
- 马尔可夫模型
Abstract: With the development of adaptive optics (AO) technology in laser field, a variety of improvement measures based on software monitoring and hardware protection have been added to the classical AO system to ensure the stable and continuous light output of laser AO system. Facing the reliability challenge brought by the increase of structural complexity, how to build a system failure model to evaluate the reliability of laser AO system has become an important part of the development of laser AO system. In this paper, a dynamic fault tree (DFT) method is proposed to evaluate the reliability of laser AO system, and the dynamic fault tree is established according to the dynamic relationship between the equipment. The bottom event failure rate is estimated by combining the manufacturer information, fatigue life test and historical data. The reliability parameters of DFT are obtained by using binary decision graph and Markov model. Using DFT to analysis the reliable running time of the AO system increasing by the improvement measures, the result shows more than ten times improvement relative to the basic fault tree. During the actual system joint commissioning, no self-induced failure occurred during the expected reliable running time, which is consistent with the DFT estimate. It is proved that the reliability evaluation of laser AO system with improved measures is more accurate by using DFT method.
- adaptive optics /
- dynamic fault tree /
- reliability evaluation /
- Markov model

HTML全文

图 1 逻辑门图形表示

Figure 1. Logic gate graphic representation

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图 2 光稳净化系统组成结构图

Figure 2. Structure diagram of beam stabilization and clean system

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图 3 经典AO系统结构图

Figure 3. Classical AO system structure diagram

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图 4 经典AO系统故障树

Figure 4. Fault tree of classical AO system

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图 5 波前探测模块动态故障树

Figure 5. Dynamic fault tree of wavefront detection module

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图 6 波前控制模块动态故障树

Figure 6. Dynamic fault tree of wavefront control module

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图 7 检测功能依赖于波前处理模块故障树

Figure 7. The fault tree of detection function depending on the wave front processing module

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图 8 波前校正模块动态故障树

Figure 8. Dynamic fault tree of wavefront correction module

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图 9 供电模块动态故障树

Figure 9. Dynamic fault tree of power supply module

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图 10 改进AO系统动态故障树

Figure 10. Dynamic Fault Tree of Improved AO System

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图 11 改进AO系统失效概率-时间曲线

Figure 11. Failure probability time curve of improved AO control system

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图 12 改进前后AO系统失效概率-时间曲线对比

Figure 12. Comparison of failure probability-time curve of AO system before and after improvement

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表 1 AO系统基本故障树事件表

Table 1. AO system basic fault tree events table

event	failure event meaning	failure rate/h⁻¹	event	failure event meaning	failure rate/h⁻¹
T1	classical AO system failure		X4	beam clean wavefront processing failure	2×10⁻⁵
M1	failure of wavefront control subsystem		X5	beam stabilization high-voltage drive failure	1.5×10⁻⁵
M2	failure of monitoring and recording subsystem		X6	beam clean high-voltage drive failure	1.5×10⁻⁵
M3	communication subsystem failure		X7	beam stabilization tilt mirror failure	2×10⁻³
M4	power subsystem failure		X8	beam clean deformable mirror failure	2×10⁻³
M5	wavefront detection module failure		X9	monitoring control module failure	1×10⁻⁵
M6	wavefront processing module failure		X10	failure of data recording module	1×10⁻⁵
M7	wavefront control module failure		X11	main control network failure	1×10⁻⁵
M8	wavefront correction module failure		X12	electric control network failure	1×10⁻⁵
X1	beam stabilization wavefront detection failure	1×10⁻⁵	X13	program control power supply failure	1×10⁻⁵
X2	beam clean wavefront detection failure	1×10⁻⁵	X14	total power failure	1×10⁻⁵
X3	beam stabilization wavefront processing failure	2×10⁻⁵

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表 2 改进AO系统动态故障树新增事件表

Table 2. Added event table of improved AO system dynamic fault tree

event	failure event meaning	failure rate/h⁻¹	event	failure event meaning	failure rate/h⁻¹
T2	AO system failure with reliability improvement measures		M15	mirror monitoring and warning failure	1×10⁻²
M9	power supply module failure		X15	UPS failure	2×10⁻³
M10	sensor detection failure		X15	UPS spare failure	1×10⁻⁵
M11	high voltage protection failure		X16	image slope effectiveness monitoring failure	1×10⁻²
M12	high pressure drive failure		X17	voltage instability monitoring failure	1×10⁻²
M13	active mirror protection failure		X18	hardware protection network failure	1.5×10⁻⁵
M14	active mirror failure		X19	air knife failure	1.5×10⁻³

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表 3 改进AO系统动态故障树事件重要度表

Table 3. Event importance table of improved AO system DFT

event	I_s	I_p	I_c
X1	2～12	0.5797	0.0160
X2	2～12	0.5797	0.0160
X3	2～10	0.9070	0.0499
X4	2～10	0.9070	0.0499
X5	2～12	0.0014	5.9110×10⁻⁵
X6	2～12	0.0014	5.9110×10⁻⁵
X7	2～12	0.0335	0.1429
X8	2～12	0.0335	0.1429
X9	2～10	0.9046	0.0249
X10	2～10	0.9046	0.0249
X11	2～10	0.9046	0.0249
X12	2～10	0.9046	0.0249
X13	2～10	0.9046	0.0249
X14	2～11	0.0016	4.4057×10⁻⁵
X15	2～11	1.4412×10⁻⁶	6.1455×10⁻⁶
X15	2～11	0.0012	3.3525×10⁻⁵
X16	2～11	0.0072	0.0682
X17	2～12	2.2341×10⁻⁵	2.1297×10⁻⁴
X18	2～12	0.0029	1.1873×10⁻⁴
X19	2～12	0.2281	0.7762
M15	2～12	0.1511	1.4403

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表 4 改进AO系统动态故障树事件重要度表

Table 4. Test record of beam stablation and purification system

time for once experiment/s	times during experiments/times	total time/ s·times
0.5	24	184
1	22
2	1
3	6
5	5
10	3
15	1
30	2

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