液体火箭发动机故障尾焰光谱诊断：从定性到定量

doi:10.7527/S1000-6893.2026.33069

Abstract

Abstract:

With the growing engineering demand for reusable liquid rocket engines， ensuring stable and safe operation under extreme conditions-high heat flux， high chamber pressure， and violent combustion-has become increasingly challenging. Plume spectroscopic diagnostics， featuring non-contact measurement， high sensitivity， and multi-parameter sensing capability， has emerged as an important technical route for engine health monitoring and fault identification. We first analyze the key challenges in liquid rocket engine development and the diagnostic requirements for fault monitoring. The diagnostic mechanism based on atomic emission spectroscopy is then systematically elaborated， followed by a review of domestic and international research progress and the current state of the art in plume spectroscopy. Next， the core enabling technologies are summarized， including the construction of a spectrum–material–fault-mode database， controlled metal-impurity doping combustion tests， quantitative inversion of alloy species concentrations in the plume， flight-environment spectral diagnostics， and spectral-line interference and mitigation strategies for LOX/kerosene engines. The applicability， accuracy， and engineering feasibility of three representative measurement techniques-Fabry-Pérot interferometry， Fourier-transform infrared spectroscopy， and laser-induced breakdown spectroscopy-are further evaluated and compared for plume spectral acquisition. Finally， future trends are discussed， with emphasis on multimodal data fusion， artificial-intelligence-enabled analysis， on-chip spectroscopy combined with edge computing， and extensions toward the near-/mid-/far-infrared and terahertz bands， highlighting the broad prospects of plume spectroscopy for intelligent operation and predictive maintenance of liquid rocket engines.

Key words: liquid rocket engine, exhaust plume spectroscopy, fault diagnosis, quantitative inversion, artificial intelligence

CLC Number:

V434

Song YAN, Yi LI, Hongqiang QIN, Xing CUI, Yushan GAO. Exhaust-plume spectroscopic diagnostics of liquid rocket engine faults: From qualitative to quantitative[J]. Acta Aeronautica et Astronautica Sinica, 2026, 47(16): 133069.

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元素	特征波长/nm
Al	308.22/309.27/394.40/396.15
Ca	422.67/443.50/445.48/445.58/534.95/558.88/559.45/585.75/610.27/612.22/616.22/616.95/643.91/644.98/646.26/647.17/649.38/649.97/671.77/714.81/720.22/732.62
Cr	357.87/359.35/360.53/396.37/425.44/427.48/428.97/434.45/435.18/520.45/520.60/520.84
Co	340.51/341.23/344.36/345.35/346.28/346.58/347.40/350.23/350.63/352.69/352.98/356.94/358.72/384.55/387.31/389.41/399.53
Cu	303.61/306.34/310.86/324.75/327.40/330.80/353.04/406.26/465.11/510.55/515.32/521.82/570.02/578.21/793.31/809.26
Fe	344.06/358.12/371.99/373.49/373.71/374.56/374.83/374.95/385.99/388.63/404.58/438.35
Mn	403.08/403.31/403.45/404.14
Mo	313.26/317.04/379.83/386.41/390.30/550.65
Ni	341.48/344.63/345.85/346.17/349.30/351.51/352.45/356.64/361.94
Na	330.23/330.30/449.42/449.77/568.82/589.00/589.59
Ti	319.20/319.99/334.19/335.46/337.14/363.55/364.27/365.35/374.11/375.29/394.87/395.63/ 395.82/398.18/398.98/399.86/430.11/430.59/453.32/453.47/498.17/499.11/499.95/500.72/501.42

合金	质量分数/%
合金	Ni	Fe	Cr	Mo	Ti	Al	Nb
GH4169	52.2	18.1	20.2	3.2	0.9	0.6	5.3
GH4061	57.2	14.0	17.1	3.8	0.6	1.0	4.8
GH202	66.0	2.0	18.2	4.5	2.6	1.3	/

故障描述	故障类型			材料牌号
故障描述	碰磨	掉块	烧蚀	材料牌号
涡轮盘烧蚀			√	GH4586
涡轮静子/壳体烧蚀			√	GH4061
低压壳体铸件掉块		√		S-08
诱导轮与低压壳体碰磨	√			诱导轮：GH4061 低压壳体：S-08

波长λ₀/nm	激发态能量E_n /cm^-1	统计权重g_n	爱因斯坦系数A_nm /（10⁸ s^-1）
425.43	23 499	9	0.315
427.48	23 386	7	0.307

评价指标	FPI	FTIR	LIBS
光谱范围	UV-VIS-NIR，瞬时透过带宽极窄	NIR-MIR（Mid-Infrared，中红外）宽谱覆盖（约 0.78~20.00 μm）	多在UV-VIS（取决于光谱仪），元素线丰富
光谱分辨	极高（10^-4 nm），适合线型参数反演	工程上典型1.0~4.0 cm⁻¹，优化后可达0.5~1.0 cm⁻¹	取决于光谱仪，通常优于0.1 nm
工程约束	对准直/对准、抗振、热漂移控制要求高	对可动镜位移精度与稳定性高度敏感	高能激光+精密光路+高速采集，抗振稳定与维护成本高；激光安全需评估
适用场景建议	线型/温度/流场参数反演、飞行小型化	气体组分定性与定量监测，多组分同步识别	元素识别与材料侵蚀相关金属元素，尤其低温或强背景工况

Exhaust-plume spectroscopic diagnostics of liquid rocket engine faults: From qualitative to quantitative

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