Article(id=1239133497173013355, tenantId=1146029695717560320, journalId=1238841944844054536, issueId=1239133496480953194, articleNumber=null, orderNo=null, doi=10.12347/j.ycyk.20250411002, pmid=null, cstr=32406.14.ycyk.20250411002, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1744300800000, receivedDateStr=2025-04-11, revisedDate=1744992000000, revisedDateStr=2025-04-19, acceptedDate=null, acceptedDateStr=null, onlineDate=1773362047712, onlineDateStr=2026-03-13, pubDate=1747238400000, pubDateStr=2025-05-15, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773362047712, onlineIssueDateStr=2026-03-13, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773362047712, creator=13701087609, updateTime=1773362047712, updator=13701087609, issue=Issue{id=1239133496480953194, tenantId=1146029695717560320, journalId=1238841944844054536, year='2025', volume='46', issue='3', pageStart='1', pageEnd='152', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773362047547, creator=13701087609, updateTime=1773363045127, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1239137680697651401, tenantId=1146029695717560320, journalId=1238841944844054536, issueId=1239133496480953194, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1239137680697651402, tenantId=1146029695717560320, journalId=1238841944844054536, issueId=1239133496480953194, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=1, endPage=24, ext={EN=ArticleExt(id=1239133497466614640, articleId=1239133497173013355, tenantId=1146029695717560320, journalId=1238841944844054536, language=EN, title=Research Progress on Spacecraft Structural Health Monitoring Technology, columnId=1239133497370145646, journalTitle=Journal of Telemetry, Tracking and Command, columnName=Intelligent Sensor Technology, runingTitle=null, highlight=null, articleAbstract=

With the increasing number of space debris and the increasing complexity of spacecraft missions as well as the requirements for adaptability to extreme environments, the operational status, damage diagnosis, life prediction and reliable safety as-sessment of spacecraft structure are particularly important. Operating as an effective approach, spacecraft structural health monitoring obtains structural feature information through sensor systems deployed in the structure,analyzes and evaluates the structural status through algorithm processing, thereby ensuring the safe and stable operation of the spacecraft at all stages. This paper focuses on the key technologies of spacecraft structural health monitoring. Firstly, from the sensor end of information acquisition, the technical characteristics, application status, current problems and development directions of optical fiber sensing, acoustic emission sensing and surface acoustic wave sensing are reviewed. Then, the research progress of sensor deployment methods and diagnostic evaluation algorithms for information processing is introduced. Secondly, the development trends and main challenges of spacecraft structural health monitoring are summarized and prospected.

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随着空间碎片数量的逐年增加,以及航天器任务复杂度与极端环境适应性要求的不断提高,航天器结构的运行状况、损伤诊断、寿命预测与可靠安全性评估,显得尤为重要。航天器结构健康监测技术作为有效手段,通过布置于结构中的传感系统,获取结构特征信息并经算法处理,分析评估结构状态,从而确保航天器各阶段的安全稳定运行。本文聚焦于航天器结构健康监测的关键技术,首先从信息获取的传感端,综述了光纤传感、声发射传感、声表面波传感的技术特征、应用现状、当前问题与发展方向,随后介绍了传感系统部署方法与信息处理的诊断评估算法研究进展,最后总结展望了航天器结构健康监测技术的发展趋势与主要挑战。

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韩润奇(
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韩润奇 1991年生,博士,副教授。

刘伟松 1997年生,博士研究生。

林伯韬 1983年生,教授,博士生导师。

陈茂银 1975年生,教授,博士生导师。

马波 1984年生,教授,博士生导师。

王波 1986年生,硕士,高级工程师。

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韩润奇 1991年生,博士,副教授。

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韩润奇 1991年生,博士,副教授。

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刘伟松 1997年生,博士研究生。

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刘伟松 1997年生,博士研究生。

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林伯韬 1983年生,教授,博士生导师。

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林伯韬 1983年生,教授,博士生导师。

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陈茂银 1975年生,教授,博士生导师。

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陈茂银 1975年生,教授,博士生导师。

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马波 1984年生,教授,博士生导师。

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马波 1984年生,教授,博士生导师。

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王波 1986年生,硕士,高级工程师。

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王波 1986年生,硕士,高级工程师。

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Comparison of typical acoustic velocity, electromechanical coupling coefficient K2, maximum operating temperature and main deterioration causes of common piezoelectric materials

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压电材料典型ν(m/s)典型K2(%)最大工作温度(℃)主要恶化原因
LiNbO33 5004.5≈300分解(Li 挥发)
Li2B4O73 5001.0≈230离子电导率过高
α-Quartz3 2000.16573相变
GaPO42 4000.29≈933相变
AlN6 0000.6≈1 040(真空)900 ℃ 氧化
LGS2 7400.441 470达到熔点
), ArticleFig(id=1239263583540924631, tenantId=1146029695717560320, journalId=1238841944844054536, articleId=1239133497173013355, language=CN, label=表1, caption=

常见压电材料的典型声速、机电耦合系数K2、最大工作温度与主要恶化原因对比

, figureFileSmall=null, figureFileBig=null, tableContent=
压电材料典型ν(m/s)典型K2(%)最大工作温度(℃)主要恶化原因
LiNbO33 5004.5≈300分解(Li 挥发)
Li2B4O73 5001.0≈230离子电导率过高
α-Quartz3 2000.16573相变
GaPO42 4000.29≈933相变
AlN6 0000.6≈1 040(真空)900 ℃ 氧化
LGS2 7400.441 470达到熔点
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航天器结构健康监测技术研究进展
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韩润奇 1 , 刘伟松 1 , 林伯韬 1 , 陈茂银 1 , 马波 2 , 王波 3
遥测遥控 | 智能传感器技术 2025,46(3): 1-24
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遥测遥控 | 智能传感器技术 2025, 46(3): 1-24
航天器结构健康监测技术研究进展
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韩润奇1 , 刘伟松1, 林伯韬1, 陈茂银1, 马波2, 王波3
作者信息
  • 1中国石油大学(北京)人工智能学院 北京 102249
  • 2华中科技大学机械科学与工程学院 武汉 430074
  • 3北京空间飞行器总体设计部 北京 100094
  • 韩润奇 1991年生,博士,副教授。

    刘伟松 1997年生,博士研究生。

    林伯韬 1983年生,教授,博士生导师。

    陈茂银 1975年生,教授,博士生导师。

    马波 1984年生,教授,博士生导师。

    王波 1986年生,硕士,高级工程师。

通讯作者:

韩润奇(
Research Progress on Spacecraft Structural Health Monitoring Technology
Runqi HAN1 , Weisong LIU1, Botao LIN1, Maoyin CHEN1, Bo MA2, Bo WANG3
Affiliations
  • 1.School of Artificial Intelligence, China University of Petroleum (Beijing), Beijing 102249, China
  • 2.School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
  • 3.Institute of Spacecraft System Engineering, Beijing 100094, China
出版时间: 2025-05-15 doi: 10.12347/j.ycyk.20250411002
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随着空间碎片数量的逐年增加,以及航天器任务复杂度与极端环境适应性要求的不断提高,航天器结构的运行状况、损伤诊断、寿命预测与可靠安全性评估,显得尤为重要。航天器结构健康监测技术作为有效手段,通过布置于结构中的传感系统,获取结构特征信息并经算法处理,分析评估结构状态,从而确保航天器各阶段的安全稳定运行。本文聚焦于航天器结构健康监测的关键技术,首先从信息获取的传感端,综述了光纤传感、声发射传感、声表面波传感的技术特征、应用现状、当前问题与发展方向,随后介绍了传感系统部署方法与信息处理的诊断评估算法研究进展,最后总结展望了航天器结构健康监测技术的发展趋势与主要挑战。

航天器结构  /  健康监测  /  光纤传感  /  声发射  /  声表面波  /  系统部署  /  评估算法

With the increasing number of space debris and the increasing complexity of spacecraft missions as well as the requirements for adaptability to extreme environments, the operational status, damage diagnosis, life prediction and reliable safety as-sessment of spacecraft structure are particularly important. Operating as an effective approach, spacecraft structural health monitoring obtains structural feature information through sensor systems deployed in the structure,analyzes and evaluates the structural status through algorithm processing, thereby ensuring the safe and stable operation of the spacecraft at all stages. This paper focuses on the key technologies of spacecraft structural health monitoring. Firstly, from the sensor end of information acquisition, the technical characteristics, application status, current problems and development directions of optical fiber sensing, acoustic emission sensing and surface acoustic wave sensing are reviewed. Then, the research progress of sensor deployment methods and diagnostic evaluation algorithms for information processing is introduced. Secondly, the development trends and main challenges of spacecraft structural health monitoring are summarized and prospected.

Spacecraft structure  /  Health monitoring  /  Optical fiber sensing  /  Acoustic emission  /  Surface acoustic wave  /  System deployment  /  Evaluation algorithm
韩润奇, 刘伟松, 林伯韬, 陈茂银, 马波, 王波. 航天器结构健康监测技术研究进展. 遥测遥控, 2025 , 46 (3) : 1 -24 . DOI: 10.12347/j.ycyk.20250411002
Runqi HAN, Weisong LIU, Botao LIN, Maoyin CHEN, Bo MA, Bo WANG. Research Progress on Spacecraft Structural Health Monitoring Technology[J]. Journal of Telemetry, Tracking and Command, 2025 , 46 (3) : 1 -24 . DOI: 10.12347/j.ycyk.20250411002
自1957年人类发射第一颗卫星“斯普特尼克”以来,航天事业的蓬勃发展带来了便捷的实时通信、准确的导航定位、高清的遥感成像等服务,但数千次的发射活动产生了大量的空间碎片,直径大于10 cm的数量已超过2.5万个,直径1~10 cm区间的数量近75万个,1 cm以下的碎片更是数量上亿[1]。随着未来低轨星座的大规模建设,预计碎片数量将以年均10%以上速度增加,严重威胁了航天器的在轨运行安全。2018年,国际空间站受空间碎片撞击,对接的飞船舱体产生了直径约2 mm的空气泄漏孔。2022年,我国清华科学卫星(编号46026)与俄罗斯的宇宙1408碎片(编号49863)发生了一次极危险的交会,最近距离仅14.5 m。因此,长期在轨运行的航天器都将面临相似的风险,航天器结构的健康监测已然成为关系航天器安全的重要课题。
与此同时,伴随着人类对于浩渺宇宙的不懈探索,航天器先进技术不断应用,使得深空探测与载人航天成为大国竞争的前沿制高点。从无人月球采样返回到近地轨道有人长期值守,从载人登月探测到月球基地建设,乃至近地小天体防御与火星样品取回,航天器正面临更加恶劣的力-热-声-振-磁多场耦合服役环境,更加严酷的工况寿命与技术挑战,结构内部的隐蔽损伤不断累积,严重影响了航天器安全运行,亟须通过先进的测量手段与方法监测结构健康状态,感知环境条件与结构响应,支撑航天器设计与应用。2016年,美国猎鹰9号运载火箭由于液氧燃料箱内的压力容器破裂,引发了火箭爆炸;2023年,日本新型固体燃料运载火箭Epsilon-S号发动机金属零件熔融,导致隔热结构损伤,引起了燃烧试验爆炸。由此,航天器结构的健康监测逐渐引起国内外研究人员的关注。
结构健康监测技术(Structural Health Monitoring,SHM)最早由美国提出相应概念,在1998年由美国国家航空航天局(National Aeronautics and Space Administration,NASA)在航天飞机项目中,首次实现了低温油箱状态的监测管理,并随后迅速推广开来,在战斗机机翼与引擎结构损伤监测等多场景中得到了应用[2]。结构健康监测技术是将传感系统布置于结构中,收集整体形变、局部应力应变、刚度模态、强度载荷、温度压力等依附于或作用于结构的状态信息,并根据数据信号特征,采用信号处理与人工智能等方法,反演评估结构运行状况、损伤诊断、寿命预测、可靠安全等健康特性,从而建立合适的维护策略[3]。在航天器的研制阶段,健康监测技术可精准评估样件的损伤程度与复用可行性,降低研制成本;在总装阶段,长时间封闭储存状态下的结构健康监测,为航天器发射的科学决策提供了数据支持;在空间运行阶段,真空、辐照、热交变、微重力的轨道环境,以及月尘、冲击、宽温域的月面环境,对于难以维修的航天器所产生的损伤与寿命影响,迫切需要健康监测技术提供的可靠状态信息[4]
本文综述了近年来航天器结构健康监测领域,在光纤传感、声发射传感、声表面波传感等感知技术方面的研究进展,以及提高感知效能的传感系统部署方法和诊断评估算法的研究现状,针对各技术类型的技术特征、应用案例、当前问题与未来展望进行了详细论述,结合人工智能领域的新兴浪潮,比较了经典与智能传感系统部署优化方法,分析了物理模型和数据驱动的两类诊断评估算法,为未来航天器结构健康监测技术发展提供借鉴。
光纤传感技术自20世纪70年代中期诞生以来,以其独特的高灵敏传感方式,成为结构健康监测领域的研究热点。光纤传感的被测信号为光波,传输介质为光纤,以光纤光栅传感器为主要应用代表。与传统的电法、磁法传感相比,光纤传感技术优势特点明显,主要体现在以下几个方面:①光波传感不受电磁射频干扰,稳定性强,传输距离远;②无源驱动,对被测结构无影响,可实现原位真实传感;③灵敏度高,响应频带宽,动态范围大;④集成度高,传感与传输一体化;⑤纤芯直径仅微米量级,主材二氧化硅性能稳定,对高温腐蚀等环境适应性强;⑥分布化传感方式多,如时分复用、频分复用、波分复用等技术。根据光纤传感的工作方式和作用范围不同,可将光纤传感技术划分为局部单点式、离散多点式与连续分布式三类。
局部单点式光纤传感器是通过在光纤区段上插入敏感元件光纤光栅,监测特定位置的温度、压力、应变和振动等物理量变化,光纤光栅传感器独立布置,单独回程,适用于局部结构关键位置的重点健康监测。光纤布拉格光栅(Fiber Bragg Grating,FBG)是一种常见的点式光纤传感器,其基本原理如图1所示,基于光纤材料的光敏特性,采用紫外光干涉技术在纤芯区域制备周期性调制折射率的结构,即光纤光栅。其具有波长选择特性,只在宽带光中特定的布拉格波长处发生相干反射,其余波长保持透射传输。当外界温度应力等环境参量作用于光纤光栅区域时,会引起反射光的布拉格波长变化,通过对此解调,即可实时测量对应位置的应力应变、温度、位移、振动等参数,实现局部结构的健康监测[5]
国外较早开展了光纤光栅传感器的局部单点式光纤传感技术研究。2007年,欧洲研发(R&D)计划“HEATTOP”[7](一项高温发动机气动热测量计划)中首次开展了蓝宝石光纤传感器实验,验证了光纤高温传感器在燃气轮机高温部件的温度监测中,替代常规热电偶的可行性。
2013年,德国莱布尼茨光子技术研究所Elsmann团队[8]利用双光束干涉法成功制备出蓝宝石光纤光栅波分复用阵列。2016年,中航工业北京长城计量测试技术研究所的王文娟等[9],在复合材料制备工艺中植入12支光纤光栅传感器,通过热压罐固化工艺形成内置传感网络的层合板试件,研究了不同位置载荷冲击的传感识别特性,采用互相关时延估计算法,实现了小尺寸加筋板结构冲击的定位辨识。
2018年,深圳大学王义平团队[10]利用飞秒激光在单晶蓝宝石光纤中刻制周期性光栅,成功制备出耐高温传感器,其工作原理如图2所示,可承受高达1 612 ℃的超高温环境,实现了极端环境下航空发动机燃烧室和高速飞行器结构的高温原位监测。
2018年,北京信息科技大学研制的光纤传感监测系统,搭载于天仪研究院湘江新区号卫星进行了技术验证飞行试验。试验系统通过FBG多路复用组建了1个应变测点、10个温度测点的监测网络,并利用可调谐激光器扫描法解调传感信号,实现在轨卫星结构的应变和温度监测,如图3所示。经过两年多的飞行实测验证了所研制的光纤传感器和微型轻量解调仪的空间环境适应性。随后,北京信息科技大学与中国空间技术研究院等单位合作[12],在多种卫星上开展了光纤监测系统飞行试验,如图4所示,并针对空间站结构与环境参数,进一步开展光纤在轨监测系统的研发与试验验证。
局部单点式光纤传感技术的每个传感器独立工作,系统结构相对简单,但每个传感器都需要单独布线,增加了布线成本和复杂性,不适合长距离或大面积的监测,通常采用较短长度的部署,高精度测量特定位置的温度与应变状态。
离散多点式光纤传感器是一种半分布式光纤传感技术,测量信息在空间上并非连续分布的。它通过分复用技术,在一根光纤上实现多个光栅传感器的信号传输,每个传感器对不同的物理量或相同物理量的不同变化敏感,通过测量反射光的不同波长或时间差来区分信号,从而实现离散多点的结构健康监测[13,14]。自美国挑战者号航天飞机事故发生以来,离散多点式光纤传感技术获得快速发展,在航天器关键结构状态监测、复合材料失效分析等方面得到了大量研究测试,并已在国际空间站等多个重要型号在轨应用。
2001年,NASA将光纤传感器埋入聚合物复合材料蒙皮中,用以监控复合材料应变与温度,实现多光纤光栅传感器的复用测量。后来,研究团队[15,16]在X-33、X-34、X-37与X-38等空间飞行器中,安装了测量应变和温度的光纤传感网络,对飞行器结构可靠性进行实时在线原位监测,可实现-40 ℃~180 ℃测温范围与-1 000 με~4 000 με的应变范围。除此之外,美军将光纤传感器用于大型可展开天线等柔性结构体上,有效解决了电阻式应变片等传统传感器的测量难题。
美国海军研究实验室[17]先后开展了光纤传感技术在航空器、海军装备及其地面实验的研究,包括通过光纤传感器评估飞机的粘接接头性能,采用固定在飞机轻型天线反射器多点多位置的光纤传感器,测量纵向应变、弯曲和扭矩,以及应用光纤传感器监测舰船与潜艇结构的轻微变形等。2008年,NASA[18]将2 880个光纤光栅传感器安装在新型无人机IKHANA上,如图5图6所示,对飞行过程中的结构动态应变信号进行监测。
2016年,NASA马歇尔太空飞行中心将300个电阻与位移传感器,以及16 000个离散式多点光纤传感器,部署于大型石墨-环氧复合材料圆柱形结构,在壳体力学性能测试中评估了结构完整性,获取了无法承载的极限压缩载荷可达900 000磅(约408 233.13 kg),为返回式太空运输设备的设计与建造提供了依据。
欧洲空间局(European Space Agency,ESA)基于欧洲之星3000平台[19],如图7所示,在Inmarsat 4与Intelsat X卫星中,将多点光纤光栅传感器布置于推进器燃料箱表面,精准测量燃料箱的温度分布情况,通过热敲击法反演出剩余燃料状态,其中卫星结构面板如图8所示,同时通过监测燃料箱的应变和裂纹,提前进行风险识别与故障诊断,为航天器服役期的合理规划提供关键支撑。
2008年,北京工业大学宋永伦团队[20],为解决火箭贮箱铝合金板材焊接过程的应力应变监测问题,提出了一种基于离散多点式光纤光栅传感技术的大型焊接结构件多耦合场在线监测方法,试验测试数据表明:该系统可为揭示焊接应力与变形的演化规律,提供有效准确的测量手段。
2009年,南京航空航天大学的芦吉云等[21]针对某型飞机机翼盒段,构建试件的有限元模型,通过波分复用形式,设计与优化光纤光栅传感网络及其布置方案,分析外载荷和应变分布之间关系。结果表明:传感器的波长偏移与载荷呈线性关系,加载点位置的变化会影响线性关系的斜率,传感器的最大载荷监测灵敏度达3.09 pm/N。
2012年易金聪等人[22]利用FBG应变传感器对机翼结构的形状进行了检测。他们通过对机翼模型进行仿真,确定6个监测节点,在各节点位置粘贴光栅,如图9所示,监测各点应变的变化情况,但研究方案中没有考虑温度对监测结果的影响。
2023年,南京航空航天大学芦吉云与吴奇等[23],采用离散多点式光纤光栅阵列传感器,根据如图10所示的光谱图,监测不同载荷下的全尺寸多功能密封舱状态,通过分析诊断亚健康状态,及时预警灾难性失效,有效避免事故。2024年,北京工业大学的慕聪颖团队[24]以固体火箭发动机作为研究对象,研究了光栅传感器及其传输链路的涂覆和封装技术,将光纤传感器阵列植入发动机,并开展水压监测实验、高低温存储实验、长周期监测实验和点火实验等,实验结果表明:离散多点式光纤光栅传感网络能够准确测量发动机的应变状态,为固体火箭发动机的结构健康管理提供有效的数据支撑。
离散多点式光纤传感技术可以在同根光纤中布置多个光栅传感器,同时测量多个离散点的物理量,布线成本低、测量范围广、复杂度低,适用于中等长度的复杂结构实时监测。但受光源带宽和传感器波长范围的限制,传感器的数量和间距存在一定约束,存在传感器之间的监测盲区而无法连续监测,相比局部单点式,已能较为全面地获取测量对象状态,可以满足大部分场景需求,但仍难以实现特殊场景的分布式连续测量。
连续分布式光纤传感技术利用光纤作为信号的传输介质与传感单元,通过测量光纤中光信号的强度、相位、偏振态等参量在外部环境扰动作用下的变化,解析被调制的光信号,将单根光纤转化为数万个“虚拟传感器”,实现对外部参量的连续分布式感知。根据信号测量方式的不同,分为光频域技术和光时域技术两类,前者具有较高的空间分辨,但是测量过程复杂,传感距离有限,而光时域技术实现简单,具有长距离和高精度的特点[25]
光波在光纤中传输时,会在光纤沿线不断产生散射光,如图11所示。根据光测量原理不同,连续分布式光纤传感分为背向散射型与前向干涉型两类。背向散射型主要包括瑞利散射、布里渊散射以及拉曼散射三种。前向光干涉型最主要的三种基本结构分别是迈克耳孙型、马赫-曾德尔干涉型和萨尼亚克型。与背向散射型系统相比,前向光干涉型系统直接利用前向传输光作为信号光进行传感,传输损失较小、结构简单、动态范围大、频率响应带宽大,更容易实现长距离范围内的传感,可实现无中继放大的广域传感[26]
连续分布式光纤传感技术以其独特性能,已在航空航天关键结构的健康监测中发挥作用。2019年,美国Luna公司和NASA[27]开发了嵌入光纤传感器的智能感知管,采取连续分布式光纤传感技术监测发动机管路中温度和应变,并反算热通量和流体压力等信息。2020年,Ohanian团队与NASA等机构合作[28]将光纤传感器直接编织于柔性结构约束层织带中,如图12所示,成功实现对结构蠕变、压力变化的实时监测,并精准定位微流星体及轨道碎片超高速撞击事件的位置和损伤程度。通过实验验证了该技术在极端太空环境下的可靠性,为月球门户和火星任务中的栖息地设计提供了关键技术验证。
2023年,博洛尼亚大学的Falcetelli[29],针对分布式光纤传感器监测复合材料损伤缺乏不确定性量化方法的现实瓶颈,开发了一种生成复合材料连续分布式光纤传感方法,用于表征应变传递性能。厦门大学联合中国航天科技集团公司一院[30]完成了基于连续分布式光纤传感的复合材料贮箱低温静力试验和某飞行器复合材料尾翼力热耦合试验,获取了飞行器结构考核验证的关键载荷数据。
连续分布式光纤传感器技术通过单根光纤替代离散传感网络,能够实现高密度的传感点分布,无监测盲区,覆盖长距离和复杂环境,但系统成本较高,需要高精度的解调设备和专业的人员维护。当前,该技术已应用于新型可重复使用航天器的热防护系统监测,通过在防热瓦内嵌光纤阵列,降低航天器载荷重量,实现烧蚀厚度的分布式测量,为再入过程的结构安全提供直接判据。随着光纤解调芯片的小型化发展,连续分布式光纤正推动航天器结构监测从“故障后排查”向“损伤中预警”的智能化转型,为深空探测、载人航天等关键装备的可靠性提升提供关键技术支撑。
光纤传感技术作为航天器结构健康监测的重要手段,已在国内部分航天任务中取得阶段性成果,但在复杂环境应用中的探索尚处于初期,亟待解决多物理场耦合干扰的问题。当航天器在极端温度交变环境中,光纤传感器的温度与应变信号严重耦合,传统解耦方法难以满足高精度测量需求。同时,复杂力学载荷与空间辐射环境加剧了传感器封装结构的疲劳失效风险,长期在轨稳定性面临严峻考验。
结合当前国内光纤传感技术在航天器上的应用情况,仍需在以下方面进一步深入研究:
①多参数解耦与自适应补偿。开发新型温度自补偿光纤传感阵列,结合物理机理与人工智能算法,构建多场耦合信号的智能分离模型。通过深度学习挖掘信号本质特征,显著提升应变、温度等参数的独立测量精度。
②高可靠封装技术。发展结构-功能一体化封装方案,采用新型智能材料与纳米改性技术,增强界面结合强度。建立空间环境加速老化评估体系,完善振动、辐射、热循环等涵盖多维度封装可靠性的测试标准,确保传感器全寿命周期性能稳定。
未来通过聚焦于材料-算法-系统的协同创新,基于新型封装材料提升极端环境耐受性,依托人工智能实现多参数解耦与融合解析,构建自主适应的监测体系。随着量子传感、柔性电子等前沿技术的深度融合,光纤监测系统将向更高精度、更强韧性的方向发展,为我国深空探测、载人航天等重大工程提供全维度、全周期的结构安全保障,推动航天器健康管理进入新阶段。
声发射(Acoustic Emission, AE)传感技术通过捕捉材料受载时内部损伤释放能量所产生的弹性波,实现结构健康监测,其核心机理是材料在外界应力作用下的微裂纹扩展、摩擦或相变等物理过程[31]。声发射技术对微小裂纹敏感度高,受几何构造复杂程度影响小,远程探测范围大,适合在线监测结构损伤状态。由于采用被动监测方式,无需外部激励即可实现动态损伤监测,其信号类型可分为突发型(如脆性断裂、冲击事件)和连续型(如塑性变形、摩擦磨损)两类。
声发射波传播示意如图13所示。声发射源释放的声发射波,被结构表面的传感器接收,经分析确定声发射源的位置。目前,主要的声发射监测定位方法包括时差定位法、三角测量法、区域检测法和能量监测法等。时差定位法利用阵列传感器接收同一声发射源信号的时间差,反演计算声发射源的位置;三角测量法基于时差定位的原理,以每个传感器为圆心,根据三个传感器测量到的同一声发射源信号的时间差来确定圆弧的大小,三个圆弧的交点即为声发射源的位置;区域检测法在目标区域布置大量传感器,直接定位声发射源,适用于传播衰减大、各向异性的材料损伤定位;能量监测法基于结构损伤导致弹性导波能量的耗散原理,如图14所示,通过多路径传播的能量比,刻画传播路径中的损伤程度,从而重现整个结构的裂纹损伤情况。
国外较早开展将声发射传感技术应用于结构健康监测的研究。2001年,NASA与美国思创公司[33]合作开发的UL101超声检漏仪,在国际空间站成功识别出气闸舱连通平衡阀的泄漏路径,并随后用于检测“命运”号实验舱舷窗多层玻璃间的裂痕,以及气压排水软管的破损情况。
2002年,美国Invocon公司[34]开发了UltraWIS(超宽带智能感知)系统,用于监测太空碎片和微流星体碰撞引发的紧急泄漏事件。该系统通过捕捉气体泄漏产生的声波信号,结合三角测量技术精确定位泄漏源,并于次年通过了NASA的多项集成测试(MEIT3),应用于美国航天飞机的泄漏监测任务[35]。2005年,NASA[36]在航天飞机机翼前缘部署了44个传感器,构建了一套冲击监测系统。该系统在航天飞机发射升空阶段实时监测机翼前缘的结构状态,并于在轨期间持续跟踪微流星体和轨道碎片的撞击影响。
2016年,美国宾夕法尼亚州立大学研究人员[37],采用固定位置的传感器阵列及弹性导波技术,对E-2飞机机翼进行结构监测,基于协方差矩阵适应进化方法,提出了传感器数量和位置分布的定量优化方法,开发了一种超声导波传感器网络的损伤检测概率模型,提高飞机机翼监控的传感器网络性能。通过优化误检概率、传感器数量和参数之间的关系,得到图15所示的传感器分布网络,黑色区域为加强肋,灰色圆点代表传感器优化的位置。
美国国防部与能源部依托环境安全技术认证项目[38],开发了被动式声学泄露定位系统(The Passive Acoustic Leak-Location System,PALS),其系统原理如图16所示,主要由三个超声传感器、前置放大器及测控计算机组成,泄漏产生的超声波通过管壁传播被传感器捕获,经互相关处理解算得到漏点的具体位置。该系统在美国加利福尼亚州怀尼米港的美国海军工程营中心和肯塔基州陆军直升机场燃料管道实验中,均准确探测定位出测试管道的漏点位置。
2022年,印度杜尔加布尔国家理工学院Anupam Kumar Biswas团队[39]通过声发射技术捕获结构损伤产生的应力波,结合小波变换频谱分析精准定位损伤位置,利用随机森林分类器对裂纹、螺栓松动等损伤类型进行分类。相比传统方法,显著提升了损伤定位效率和分类准确率,解决了视觉检测无法定位内部损伤的难题。
近些年,国内在声发射技术结构健康监测方面的应用也取得了一定进展。2018年,北京卫星环境工程研究所的綦磊等人[40]针对现有航天器碎片碰撞和泄漏定位方法难以兼顾高精度和实时性的问题,提出利用二级声传感器阵列检测航天器在轨碰撞与泄漏声发射信号,地面实测1~2 m范围内的碰撞定位相对误差小于2%,直径1 mm以上漏孔的定位相对误差小于10%。两级传感阵列如图17所示,通过声达时差法对碰撞点进行定位并利用波束形成法对泄漏进行定位。研究团队以此为基础[41],在微弱声信号提取、碰撞泄漏定位、高灵敏度声阵列传感器设计等方面相继取得技术突破。
2020年5月,我国通过载人飞船试验船,首次成功开展了航天器在轨泄漏与碰撞定位试验,系统由1台主机及8个高灵敏度声发射传感器组成,其中主机实物如图18所示,可实时监测载人飞船舱壁内的微弱声信号,并提取与存储关键信号。当轨道碎片撞击或舱体泄漏事件引发特征声波时,系统通过分布式传感器阵列,捕捉声波传播的时间序列差异,运用时差定位算法解算碰撞点或泄漏源的空间坐标,同时依据声波能量幅值,量化评估碰撞等级与泄漏程度。
2018年,天津科技大学的唐玉玲等人[42]利用声发射技术,针对不同尺寸的碳纤维增强环氧树脂复合材料螺栓连接结构,研究静力载荷下的破坏行为,对结构损伤过程中的声发射信号进行全程采集、转换与特征筛选,分析得到了挤压和剪切破坏试件的损伤演化规律。2020年,北京机电工程研究所的肖登红团队[43]利用声发射技术,监测随机振动环境下声发射信号与振动载荷之间的参数关系,揭示了C/SiC复合材料在随机振动中的损伤演变过程。
航天器在轨运行环境复杂,声发射技术面临的首要难题是背景噪声的严重干扰。推进器点火、姿态调整等动作产生的高强度机械噪声与声发射信号频段存在部分重叠,导致有效信号被淹没,尤其在微裂纹萌生阶段,信号幅值微弱,漏检风险大。此外,航天器需承受深空极端低温与再入大气层时的超高温冲击,常规传感器的性能在剧烈温度交变下易发生退化,出现灵敏度下降或热致伪信号,严重影响监测可靠性。材料层面,航天器广泛采用的复合材料结构具有各向异性,声发射波在传播过程中易发生模态转换与能量衰减,并耦合多路径反射效应,使得损伤定位精度难以满足要求,制约了关键部位的精准监测。
为应对上述挑战,声发射传感需要突破噪声抑制、环境适应性与智能诊断等核心技术,需融合材料科学、人工智能与航天工程的跨学科创新。发展自适应智能信号处理算法,通过机器学习动态识别噪声模式并增强有用信号特征,结合迁移学习实现不同任务场景下的模型快速适配,增强在轨环境的实时处理能力。同时,开发新型宽温域材料与微型化封装技术,有效抑制极端温度与空间辐射对器件性能的影响。进一步地,构建自主诊断与决策平台,基于轻量化分析模块,实现在线信号处理与损伤分类,评估结构剩余寿命并自主生成维护策略,为航天器在轨维护与任务规划提供智能化支持。
未来随着耐极端环境传感器、星载边缘智能算法及多物理场融合平台的成熟,声发射技术有望成为深空探测、可重复使用运载器等任务的核心监测手段,为航天器全寿命周期安全管理提供坚实支撑。
声表面波(Surface Acoustic Wave,SAW)传感技术作为一种典型的无线无源被动感应方式,基于压电效应实现机械振动与电信号的转化,将待测物理量转化为谐振频率的变化。SAW传感器主要由SAW探头与无线问询装置组成[44],SAW探头由压电基底、叉指换能器(Interdigital Transducer,IDT)、反射栅和天线组成,如图19所示。当无线问询装置发射电磁波至SAW探头天线接收后,由压电衬底的IDT将电信号转化为表面的机械振动,即SAW的激励。随着SAW传输到反射栅后,被再次反射回IDT端,通过压电效应转化为电信号,由天线输出至无线问询装置,获取SAW探头受温度、压力、变形等影响而产生的谐振频率变化,具有体积小、重量轻、无源免维护、传输距离远、多传感节点同时问询的优点,可同时集成温度、压力、应变、扭矩等多物理参数,实现原位在线测量,对于航天器结构的健康监测具有重要意义。
随着微机电系统(Micro-electro-mechanical System, MEMS)技术的蓬勃发展,以碳化硅(Silicon Carbide, SiC)、氮化铝(Aluminum Nitride,AlN)等为代表的新型MEMS-SAW传感探头材料,具备优良的高温特性,相比于光纤传感与声发射传感系统尺度更小[45],能够原位监测传统方法不可达的特定区域,具有无线传输、微型化集成的潜力,通过多点阵列分布式测量温度、压力、应变、扭矩等多物理量,显著降低高温环境下连线不稳定性引起的传感监测失效,成为近年来的研究热点。
针对航天器特殊高温结构的健康监测,如推进器燃烧室与发动机等关键结构,传统的硅基与光纤传感系统理论工作温度在350 ℃以下,无法长期工作在1 000 ℃量级的极端温度环境[46]。目前,面向500 ℃以上的MEMS传感器材料,主要有绝缘体上硅(Silicon on Insulator, SOI)、蓝宝石上硅(Silicon on Sapphire, SOS)、碳化硅SiC、氮化铝AlN等[47,48]。因此,SAW传感器压电基底材料是高温测量的关键,需要满足高温稳定不分解不氧化、传播损耗尽可能小,以及机电耦合系数不应过小等要求[49]。目前,常见的压电材料参数如表1所示,研究人员一般选用硅酸镓镧(La3Ga5SiO14,LGS)晶体作为压电基底,新型基底材料如SiC、AlN/SiC、Pt/Al2O3等以其良好的MEMS工艺兼容性和环境适应性[50],引起了研究人员的广泛关注。
SAW技术最早可以追溯到20世纪70年代。美国Environetix公司[51]率先发布型号为EVHT-100无线无源高温SAW传感器系统,能够检测150 ℃∼900 ℃的温度,该系统的测量精度为10 ℃,能够持续工作500 h。澳大利亚Carinthian Tech Research公司[52]随后推出了一款无线无源高温SAW传感器系统,该系统工作频率为2.4 GHz,测量温度范围达到-55 ℃∼400 ℃。
2011年,美国缅因大学[53]在硅酸镓镧LGS基底材料上基于共沉积薄膜电极,制备了一种耐高温SAW传感器用于涡轮发动机健康状况监测,如图20所示,通过了发动机静态与旋转部件中53 000 g恶劣工况的测试验证,实现了200 ℃~1 000 ℃宽温域内的稳定无线无源传感响应。
2020年,Franklin Li Duan等[54]提出了量程高达1 100 ℃的无线无源SAW传感系统,通过二氧化硅保护层的41°Y切LiNbO3的压电衬底和铂Pt电极,高温下稳定性良好,测量灵敏度为-15.12 kHz/℃。同年王博文等学者采用CTGS(钽镓硅酸钙晶体)材料作为压电基体,ITO/Pt材料制成电极,在电极表面覆盖氧化铝薄膜作为保护层以提高电极的高温稳定性,如图21所示,实现了耐1 000 ℃高温SAW温度传感。
国内在SAW技术的研究主要集中在清华大学、上海交通大学、浙江大学、重庆大学、中国科学院声学所等单位。电子科技大学团队[55]在硅酸镓镧LGS晶体上通过中频磁控溅射法,沉积氮化铝薄膜制备SAW器件,如图22所示,在室温至600 ℃范围内进行了测量,揭示了SAW器件的频率温度系数随涂层厚度增加而减小,机电耦合系数随薄膜厚度增加而增大的规律,表明氮化铝涂层不仅保护SAW器件免受极端恶劣环境污染,同时提高机电耦合系数。
2021年,中北大学研究团队[56]通过脉冲激光技术,沉积氮化铝薄膜钝化层,保护铂电极与蓝宝石LGS基底,测量温度可达1 100 ℃~1 300 ℃,如图23所示,测试验证了共振频率与温度之间的线性关系,微观分析了高温暴露前后样品结构演变,实验表明:氮化铝薄膜对高温稳定性有明显改善效果,对铂电极团聚现象抑制较好。江苏声立公司长期从事声学微传感系统开发,采用SAW传感技术和特高频检测技术,自主研发了无源无线温度在线监测系统,推出了W-TSA2G型等商业化产品,接触式测温范围0 ℃~350 ℃,测温精度±2 ℃(125 ℃以上±5 ℃),工作频率433 MHz,带宽大于50 MHz。
当SAW传感器的压电基底材料受到外力作用时,IDT间距变化产生谐振频率偏移,基于此原理可在SAW温度传感器的基础上开发应变传感器。2017年美国缅因大学Anin Maskay团队[57]采用陶瓷Al2O3基环氧树脂,将SAW传感器连接到恒应力悬臂梁上,如图24所示。在20 ℃~400 ℃范围内测量了传感器的温度应变响应,在400 ℃时实测灵敏度为-41 Hz/µε,并采用温度补偿方法降低温度-应变交叉灵敏度。
2021年,李凌[58]提出基于硅酸镓镧LGS的SAW应变传感器,在同一切向基底上制备了三个应变传感器,沿三轴方向粘贴在悬臂梁上,在250 ℃以内的0~700 µε范围内温度和应变频移响应线性度良好,并基于多个SAW应变传感器,提出了温度应变解耦算法,为精确测量温度应变提供了思路。目前,高温下SAW传感器的应变测量,仍面临着重复性低、量程受限的问题,只能实现400 ℃以下最大500 με的应变测量。
同样基于SAW原理的压力传感器,能够实现压力的测量。通过在压电基底中构建封闭腔体,形成应力敏感膜,在膜表面集成SAW谐振结构,如图25所示。当外力加载于压电敏感膜时,改变了材料内部的应力分布,导致其弹性常数、密度等物理特性动态调整。这种变化将改变SAW的传播速度,同时压电敏感膜形变导致谐振器几何结构随之相应变化,从而引起谐振频率的改变。但受限于结构尺寸,当前SAW压力传感器的量程一般不超过10 MPa。2012年美国缅因大学的Scott C Moulzolf提出了一种利用(0°, 138.5°, 26.7°)切向的LGS材料制作成压力传感器,它含有一个14 mm×14 mm的方形密封腔,谐振器被放置在腔体边缘中心以提高差分灵敏度。器件通过了1.5 MPa压强和500 ℃温度测试,全温域范围内的压力灵敏度几乎保持1.4×10-6/psi(约0.203×10-6/kPa)常数。
2020年,中国科学院声学所王文团队[59]研制一种用于航天器关键部件健康监测的自温补型无线无源SAW应变传感器,如图26所示,基于压电石英晶体,通过有限元与耦合模理论,优化设计出品质因子大于12 000的谐振型器件,测试表明系统灵敏度达到598 Hz/με,温漂小于1.8%,无线信号传输距离为2 m。
2022年中北大学团队[60]开发了如图27所示的基于镓酸镧LGS的SAW压力传感器,采用LGS直接键合形成圆形密封腔,如图28所示,同时集成无密封腔的参考谐振器,压力响应由温度补偿精确获取。通过脉冲激光在两个SAW传感器铂电极上沉积氮化铝AlN保护层,测试结果表明:25 ℃~1 000 ℃温度范围内与0~300 kPa压力下传感器可正常工作,响应频率与所施加的压力呈线性变化,压力灵敏度随温度升高而降低,1 000 ℃时达到压力灵敏度最小值137 Hz/kPa。
高温MEMS-SAW传感器具有耐高温、频率量输出、电磁兼容性好、可无线化等特点,适合航天器极端高温恶劣环境的结构监测应用,可以有效解决传统硅基与光纤传感系统的高温适应性与传输方式的难题,但仍存在着测量重复性低、量程受限、微型化集成度不高的问题,涉及耐高温压电材料制备、SAW传感器结构设计与器件MEMS成型加工技术等方面。
近年来,压电多层膜结构SAW谐振器得到了广泛关注,主要由于多层膜结构材料特性的优势互补,可以提高SAW器件声速和机电耦合系数,有利于实现电路元件的系统级集成等。目前,国内外高温SAW传感器研究主要还局限在SAW谐振器的设计制作,以及谐振频率的温度、应变、压力等物理量响应方面,基于单晶SiC衬底沉积AlN薄膜继而制备MEMS-SAW谐振器的研究不足,高温敏感特性的研究尚不完善,SAW传感器的测试验证主要停留在实验室阶段,现场应用相对较少。
以MEMS-SAW传感器为基础,发挥MEMS器件微型化集成优势,构建MEMS感知微系统,是健康监测的未来重要发展方向之一。微纳集成工艺发展路线则包括系统级封装(System in Package,SIP)方案与系统级芯片(System on Chip,SOC)方案[61]。其中SIP方案利用PCB等基板,将各个器件、裸片通过引线键合、倒装焊等方式完成电连接,并统一实施封装保护,具有技术成熟、成本低良率高、系统体积小的优点。SOC方案则在晶圆级将MEMS器件与IC器件等模块,通过键合完成电连接,划片直接获得集成微系统,圆片级高集成度适合批量生产。探索融合自供能、微型天线、片上处理等多模块集成,采用多目标优化方法,依托先进的微加工与封装工艺,使得MEMS感知微系统尺寸向cm3乃至mm3量级逐步靠拢,同时兼顾环境适应性、传输距离、工作时长等实用性能。
传感器系统是航天器结构健康监测的核心基础,根据其采集的响应数据,提取损伤敏感特征,为结构状态评估与故障诊断提供关键依据。然而,航天器结构的高复杂度与特殊性,如大型桁架、密封舱体结构的多自由度与非线性力学响应,复合材料各向异性产生的多种损伤模式等,对健康监测的传感器数量、重量、功耗及部署位置有严格限制。针对上述约束,传感系统部署优化的核心目标,主要包括以下方面:①在有限的候选位置中,遴选出最大化监测效能的传感器布置方案;②捕捉关键模态响应与损伤敏感特征,提升数据完备性,为损伤识别提供高信噪比信息源;③优化模态参数的可观测性,降低参数辨识误差,增强结构状态评估的准确性;④在满足监测需求的前提下最小化传感器数量,兼顾航天器轻量化设计与系统运行成本控制[62]
经典的传感系统部署优化核心思想,是采用一定策略从所有测点出发,通过调整测点对结构性能贡献的自由度,从而筛选出关键测点,以有效独立法、最小模态置信准则法、模态矩阵求和/求积法等为主要代表。有效独立法基于模态信息矩阵,根据传感器位置的贡献排序,迭代删除贡献最小项从而保持目标模态矩阵的线性无关,是目前大型航天器结构在轨模态分析的主流常用方法[63];最小模态置信准则法正好相反,迭代过程中正向添加传感器位置项,从而最小化模态置信准则矩阵非对角元素的最大值[64,65];模态矩阵求和/求积法更为直接,从大至小排序模态矩阵中各元素绝对值的和与积,取行向量的较大值作为传感器布置点。
经典部署优化方法在低自由度结构(如小型桁架、简单舱段)中效果显著,但面对航天器复杂结构时,迭代效率骤降,难以实现全局最优[66]。近十年来,借助人工智能技术,传感系统部署优化研究领域重新引起研究人员关注,并取得了显著的研究进展。
硬件架构的革新与计算能力的指数级增长,使大型结构的传感系统部署优化算法逐步摆脱了传统迭代算法的局限。以遗传优化算法[67-74]、粒子群优化算法[75,76]、狼群优化算法[77]、K-means聚类优化[78-80]等为代表的现代智能优化算法[81-83],逐渐在大型结构传感系统部署优化中发挥了重要作用,并推动了传感系统部署优化领域向航天航空等复杂结构、大规模、海量自由度的工程应用发展。
在智能传感系统部署优化中,准确评估布置方案的优劣,设置有效的目标函数,实现监测效能的科学评价尤为重要。学术界和工程界普遍认为较有影响的5种传感器布置评价准则,包括模态置信准则、奇异值比(矩阵条件数)、模态动能、Fisher信息矩阵和待识别模态的可视化程度[84]。Cherng[85]与费庆国等[86]在卫星天线模态分析中,先后对比和应用了多种判据,但考虑到航天器结构的多样性与复杂度,各种方法存在其自身的适用范围。
2004年,西安交通大学的研究人员[87]提出了一种基于两个基因位突变改善收敛性的遗传策略算法,寻找监测传感器的最佳位置,并将改进后的遗传算法的分析结果与惩罚函数方法和强制突变方法进行比较,结果表明:改进的遗传算法的收敛速度比惩罚函数方法和强制突变方法的收敛速度快,且放置优化的结果也更好。
2010年,美国范德比尔特大学的Robert F. Guratzsch等人[88]针对不确定性下的结构健康监测系统最佳布局问题,设计开发了一种融合瞬态机械和热载荷的有限元分析以及不确定性定量分析的方法,通过结合概率有限元分析、结构损伤检测算法和基于可靠性的优化概念,实现监测传感器的最佳布置设计,如图29所示。该团队设计螺栓和压电传感器的铝板测试实验,如图30所示,验证布置优化效果。
2011年,大连理工大学伊廷华教授团队[89]提出一种基于QR(正交三角)分解、前向-后向顺序算法与双结构编码广义遗传算法的混合传感器布置策略。该方法如图31所示,通过QR分解生成初始传感器布局,结合模态置信准则矩阵非对角元素最小化策略,动态优化传感器数量,并利用广义遗传算法对传感器位置进行双结构编码优化,有效解决了复杂结构传感器布置的效率与精度矛盾。该团队基于MATLAB平台开发了混合传感器布置策略工具箱,集成命令行编译与图形用户界面,实现“黑箱”式操作,并在广州电视塔的工程实践中得到验证。该方案通过混合优化策略避免了传统有效独立法的测点冗余问题,兼顾模态可观测性与工程成本控制,为超高层建筑的健康监测提供了高可靠性、可扩展的解决方案。
2014年,河海大学的周广东等[90]提出一种基于簇中簇萤火虫算法(Cluster-in-cluster firefly algorithm, CICFA)优化传感器布置,其流程如图32所示,通过将萤火虫算法的连续优化改进为一维二进制编码及汉明距离计算,并设计簇中簇策略提升收敛速度;在无线传感器布置中引入自适应动态罚函数,将传输距离约束转化为无约束优化问题,提升算法适用性。数值实验表明:CICFA在效率和稳定性上优于遗传算法。
2020年,英国布里斯托尔大学的Cantero-Chinchilla等[91]提出一种结合参数不确定性度量(期望信息熵)与传感器-致动器成本效益的凸优化方法,优化结构健康监测中的传感器与致动器协同布置。该方法通过将离散变量松弛为连续变量实现优化问题凸化,平衡不确定性与成本,获取传感器与致动器数量及位置的全局最优配置。
2021年,中国空间技术研究院钱学森空间技术实验室的杨辰[92]提出一种基于多目标迭代优化与权重因子更新的自适应传感器布置算法,通过将六种经典传感器布置方法转化为等效形式,结合遗传算法求解并构建组合适应度函数;引入权重因子自适应迭代更新机制,最大限度降低人为设定权重对优化结果的干扰,提升算法精度与收敛速度;在弹簧质点系统、固定机翼与太阳能空间站三个工程数值案例中,如图33所示,验证了该方法的有效性,成功满足传感器分布指数及位置重复率等五项标准,为复杂结构的高效监测提供了可靠的解决方案。
2022年,美国布法罗大学的Seyedomid Sajedi等[93]提出将深度贝叶斯生成优化与条件变分自编码器及代理模型神经网络技术相结合,优化SHM系统中的传感器布置,通过将高维传感器布局问题映射至低维潜在空间,提升优化效率,借助迁移学习使振动数据评估时间减少超50%,并在九层钢筋混凝土框架案例中验证了全局最优配置能力;最终在不损失性能的前提下,损伤定位传感器数量减少52%,损伤程度预测传感器数量减少了43%,且在同等评估次数下优化效果优于遗传算法。
传感系统部署优化设计在航天器结构健康监测中虽然取得了一定的进展,但仍面临诸多亟须解决的问题,并且在技术发展和应用需求的推动下,未来的研究方向也充满潜力。
当前航天器结构健康监测传感系统部署优化设计面临的主要问题之一是工作环境变量的复杂性和多变性使得现有的优化算法在处理大规模、复杂结构时,计算效率较低、计算精度也较低。如何在有限的资源条件下实现传感器的高效布置,同时兼顾覆盖性、敏感性和冗余性,仍然是一个亟待解决的难题。
传感系统部署优化设计的实时性和适应性不足。航天器在运行过程中会面临复杂的环境变化(如温度、压力、振动等),而现有的优化设计方法往往难以动态调整传感器布置,以适应这些变化。因此,开发能够实时响应环境变化的可调控传感系统部署优化方法,是未来研究的重要方向。
传感系统部署优化设计的智能化水平有待提高。随着人工智能技术的快速发展,如何将机器学习等技术应用于传感系统部署优化设计,以实现更加智能高效的布置方案,是值得深入探索的领域。
航天器结构健康监测的核心与意义,是通过高效算法解析传感器采集的物理信号,真实准确量化表征结构损伤状态,主要分为物理模型和数据驱动两类方法。
基于物理模型的方法,通过建立结构动力学方程或导波传播模型,精准反演损伤参数。美国NASA开发了基于定性模型的诊断推理软件Livingstone[94],通过对比预期行为与实际观测差异,实现航天器部件故障的自主诊断,并先后在深空一号、对地观测卫星EO-1、X-34、X-37飞船等实际型号中进行了科学验证或应用。
2018年,南京航空航天大学杨伟博等人[95]提出了一种基于辅助粒子滤波算法的疲劳裂纹扩展预测方法,流程如图34所示,将Paris疲劳裂纹扩展规则与有限元法相结合,建立裂纹扩展的状态方程,并通过主动Lamb波健康监测方法处理Lamb波信号,拟合损伤因子函数关系,建立观测方程。进一步利用辅助粒子滤波与标准粒子滤波算法,预测了孔边裂纹扩展的寿命。实验结果表明:辅助粒子滤波算法在复杂结构的疲劳裂纹扩展预测中,有效缓解了粒子多样性匮乏现象,提高了预测精度,为复杂结构的在线寿命预测提供了有力支持。
2022年,伦敦大学的Flora Hervin等人[96]通过全3D有限元模拟和实验验证,分析准各向同性碳纤维增强聚合物板中不同损伤类型的散射特性。研究发现:各向异性对导波传播和散射有显著影响,能量主要沿着外层纤维方向聚焦。研究团队通过比较数值模拟和实验结果改进缺陷表征方法,为复合材料结构健康监测中的导波稀疏阵列成像提供了更准确的散射特性分析。
2022年,北京工业大学高翔团队[97]提出了一种基于聚类算法的Lamb波相速度精确测量方法,如图35所示,应用于板状结构的损伤定位和量化。与传统方法相比,该方法能够实现更准确可靠的测量结果,且所需测量数据更少。该方法在各向同性铝板和各向异性碳纤维增强聚合物板上进行了实验验证,相对误差小于1%,成功促进了Lamb波缺陷检测和材料参数反演。同年,该团队还提出了一种基于Lamb波和改进粒子群优化算法的非接触式测量方法[98],用于测量板状结构的厚度和弹性常数。数值模拟和验证实验表明:该方法能够准确地从零阶模态Lamb波色散曲线中获取板的杨氏模量、泊松比和厚度,为基于Lamb波的非破坏性测量提供了依据。
数据驱动方法是依托机器学习算法,实现信号特征提取与损伤模式的识别。Foss和Haugse[99]提出一种基于结构振动模态叠加的变形重构方法,通过模态分析和应变实测数据重构变形场,在板壳结构的弹性变形重构中,表现出良好的适用性。
2003年,Tessler提出反有限元法[100],通过理论剖析结构力学性质,定义待求解的问题单元,结合有限元建模思想,基于应变实测数据,实现结构变形场的重构,具有动态变形场求解速度快、实时性好、不受材料属性与复杂外界载荷限制、适应复杂型面结构等优点。
2007年,Ko和Richards[101]提出Ko位移法,一种基于应变积分原理和欧拉-伯努利梁受力模型的变形重构方法,通过分段处理梁结构并布设应变测量点,利用多项式外推法和积分运算处理得到变形位移场。NASA阿姆斯特朗飞行研究中心在2009年采用Ko位移法和光纤传感网络对Ikhana无人机机翼变形进行地面加载试验,验证了算法的精度。2012年~2016年,NASA阿姆斯特朗飞行研究中心通过飞行试验项目,验证了光纤传感网络和反有限元法重构技术在飞机结构变形实时监测中的综合性能。
2017年,Nassar等人[102]提出了一种基于投影到潜在结构判别分析的统计算法,将其应用于航天器姿态确定与控制系统的健康监测。该算法通过降维和特征提取区分正常和异常数据,如图36所示,提供关键变量的贡献分析,帮助识别分析异常事件。
2019年,田引黎等人[103]提出了一种基于半张量积压缩感知的形变数据重构方法,利用形变数据的稀疏性,采用降维的随机高斯矩阵对数据进行压缩采样,通过正交匹配追踪进行重构,应用于航天器结构健康监测中的数据传输和大容量存储。
2019年,上海卫星装备研究所李钰等人[104]针对数据传输问题,提出并证明了基于稀疏恢复技术的分式最小化模型算法和改进的分式筛选算法,并结合卫星振动试验数据与经典匹配追踪等算法进行了对比分析验证。对比结果表明:该算法在航天器所处环境条件下可以在较高压缩比的条件下保证数据恢复的精度,实现了低维数据到高维数据传输。2020年,普渡大学Chen团队[105]开发的ARF-Crack(基于主动旋转滤波器的裂缝检测)全卷积网络,实现了裂纹的像素级监测,而支持向量机在复合材料分层损伤分类中准确率达95.6%。
2022年,罗马大学的Angeletti团队[106]提出了一种基于长短期记忆网络及其双向变体的深度学习框架,应用于大型空间天线的结构健康监测,能够有效识别天线连接区域的完全断裂和部分损伤。同年,他们又提出了一种基于数据驱动技术与深度神经网络的结构损伤检测方法[107],通过堆叠多个具有不同功能的神经网络层构建的深度架构,结合有限元方法生成的多种损伤场景数据,该模型能够有效识别大型空间天线的损伤情况,提高损伤检测的精度和效率。
多源信息融合技术通过层次化架构,从数据层、特征层与决策层多个维度,提升故障诊断可靠性。数据层融合直接合成超声阵列传感器原始信号、生成复合图像,特征层融合采用模态应变聚类、分析多传感器频域特征,决策层融合则基于D-S(登普斯特-谢弗)证据理论加权多算法结果。
当前诊断与评估算法在航天器结构健康监测中已逐渐应用,其技术瓶颈在于模型泛化能力不足、星载处理器算力限制以及不确定性量化缺失,突破方向包括迁移学习框架构建与边缘计算硬件协同优化[108]。未来的研究将进一步结合深度学习与物理信息,探索更优的传感器布局策略,并开发具有更高鲁棒性和解释性的算法,以满足航天器在轨长期运行的需求。
本文综述了航天器结构健康监测的原理方法、研究进展以及应用情况,先从技术类型的角度出发,介绍了光纤传感监测技术、声发射传感监测技术、SAW传感监测技术的原理特征、应用现状、当前问题与发展方向,并细分到局部单点式、离散多点式与连续分布式光纤的不同光纤传感方式,以及基于微机电系统的MEMS-SAW多参数传感方式。随后,从传感系统部署维度,综述了智能传感系统部署优化方法研究现状、当前问题与发展方向,以实现更少数量、更精位置、更高效能、更准评价的健康监测。进一步基于传感信息,围绕物理模型与数据驱动的两类方法的原理与应用,综述了诊断与评估算法的研究进展,展望了发展趋势。
现有的航天器结构健康监测技术已经在空间站等在轨型号得到了验证应用,但仍然以实验室与地面测试应用为主。未来,随着先进材料、微机电系统与人工智能等前沿技术的不断发展,航天器结构健康监测技术将面向极端恶劣高温高压环境适应性、高功能密度微型化集成、多源多模态多物理场融合感知、智能反演与精准评估等方向,开展深入研究。建立多模态融合诊断体系,集成光纤传感、声发射传感、SAW传感等多技术手段,利用光纤传感器获取低频应变变化,通过声发射捕捉高频瞬态事件特征,建立多尺度损伤关联模型,实现多物理场信号的协同分析与交叉验证;基于神经网络算法处理时空分布数据,通过天地协同标定系统构建虚实结合的数字孪生反演平台,开发具有自主进化能力的智能诊断系统,实现对未知损伤模式的快速识别与精准定位。
本文通过详细介绍航天器结构健康监测技术的研究现状与发展展望,旨在引起工业界与学术界的重视,推动该技术从实验室原理验证样机向工程实践的转化应用,促进我国航天器结构健康监测技术的进一步发展。
  • 国家自然科学基金(62373213)
  • 中国航天科技集团钱学森青年创新基金(政字[2022]34号)
  • 中国石油科技创新基金(2024DQ02-0508)
  • 中国石油大学(北京)科研启动基金(2462024YJRC015)
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2025年第46卷第3期
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doi: 10.12347/j.ycyk.20250411002
  • 接收时间:2025-04-11
  • 首发时间:2026-03-13
  • 出版时间:2025-05-15
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  • 收稿日期:2025-04-11
  • 修回日期:2025-04-19
基金
国家自然科学基金(62373213)
中国航天科技集团钱学森青年创新基金(政字[2022]34号)
中国石油科技创新基金(2024DQ02-0508)
中国石油大学(北京)科研启动基金(2462024YJRC015)
作者信息
    1中国石油大学(北京)人工智能学院 北京 102249
    2华中科技大学机械科学与工程学院 武汉 430074
    3北京空间飞行器总体设计部 北京 100094

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韩润奇(
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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