Liquid-propellant rocket engines health-monitoring—a survey

Abstract This paper is intended to give a summary on the health-monitoring technology, which is one of the key technologies both for improving and enhancing the reliability and safety of current rocket engines and for developing new-generation high reliable reusable rocket engines. The implication of health-monitoring and the fundamental principle obeyed by the fault detection and diagnostics are elucidated. The main aspects of health-monitoring such as system frameworks, failure modes analysis, algorithms of fault detection and diagnosis, control means and advanced sensor techniques are illustrated in some detail. At last, the evolution trend of health-monitoring techniques of liquid-propellant rocket engines is set out.

[1]  Ed Nemeth,et al.  An advanced intelligent control system framework , 1992 .

[2]  Robert Babuska,et al.  Fuzzy Logic Control: Advances in Applications , 1999 .

[3]  Claudia M. Meyer,et al.  Rocket engine failure detection using system identification techniques , 1990 .

[4]  Randall C. Hopkins,et al.  SSME Condition Monitoring Using Neural Networks and Plume Spectral Signatures , 1996 .

[5]  Weidong Huang,et al.  Rocket engine diagnostics using the signed directed graph , 1995 .

[6]  Jan Lunze.  Qualitative modelling of dynamical systems motivation, methods, and prospective applications , 1998 .

[7]  June F. Zakrajsek.  The development of a post-test diagnostic system for rocket engines , 1991 .

[8]  Janos Gertler,et al.  Fault detection and diagnosis in engineering systems , 1998 .

[9]  Hudson Luce,et al.  Neural network pattern recognizer for detection of failure modes in the SSME , 1990 .

[10]  Robert B. Shanks,et al.  Infrared emission monitoring of rocket plumes , 1995 .

[11]  Charles C. Thurman,et al.  SSME exhaust plume emission spectroscopy at SSC - Recent analytical developments and test results , 1995 .

[12]  Jie Chen,et al.  Robust Model-Based Fault Diagnosis for Dynamic Systems , 1998, The International Series on Asian Studies in Computer and Information Science.

[13]  Paul M. Frank,et al.  FUZZY TECHNIQUES IN FAULT DETECTION, ISOLATION AND DIAGNOSIS , 1999 .

[14]  Gautam Biswas,et al.  Combined qualitative-quantitative steady-state diagnosis of continuous-valued systems , 1997, IEEE Trans. Syst. Man Cybern. Part A.

[15]  Paul M. Frank,et al.  New developments using AI in fault diagnosis , 1996 .

[16]  Boris Gubanov.  USSR main engines for heavy-lift launch vehicles - Status and direction , 1991 .

[17]  Yulin Zhang,et al.  Liquid-Propellant Rocket Engine Health-Monitoring Techniques , 1998 .

[18]  Brian C. Williams,et al.  Diagnosing Multiple Faults , 1987, Artif. Intell..

[19]  Timothy W. Bickmore.  A probabilistic approach to sensor data validation , 1992 .

[20]  F. Y. Kuo.  Space Shuttle Main Engine real time stability analysis , 1993 .

[21]  Gopal D. Tejwani,et al.  Approach to SSME health monitoring. III - Exhaust plume emission spectroscopy: Recent results and detailed analysis , 1993 .

[22]  Raymond Reiter,et al.  A Theory of Diagnosis from First Principles , 1986, Artif. Intell..

[23]  Michael W. Hawman.  Health monitoring system for the SSME - Program overview , 1990 .

[24]  Carl F. Lorenzo,et al.  An Intelligent Control System for Rocket Engines: Need, Vision and Issues , 1990, 1990 American Control Conference.

[25]  Eric Baumgartner,et al.  Comparison of nonlinear smoothers and nonlinear estimators for rocket engine health monitoring , 1990 .

[26]  Qiang Shen,et al.  Diagnosing continuous systems with qualitative dynamic models , 1995, Artif. Intell. Eng..

[27]  Steffen Leonhardt,et al.  Methods of fault diagnosis , 1997 .

[28]  Joseph Johnson.  Integrated health monitoring approaches and concepts for expendable and reusable space launch vehicles , 1990 .

[29]  E. Jurado,et al.  Selection of monitoring techniques for a liquid propellant rocket engine , 1990 .

[30]  Weidong Huang,et al.  Sensor failure detection and data recovery based on neural network , 1996 .

[31]  Marios M. Polycarpou,et al.  Automated fault detection and accommodation: a learning systems approach , 1995, IEEE Trans. Syst. Man Cybern..

[32]  A. Norman,et al.  Validation requirements for a rocket engine control and monitoring system , 1990 .

[33]  Rolf Isermann,et al.  On fuzzy logic applications for automatic control, supervision, and fault diagnosis , 1998, IEEE Trans. Syst. Man Cybern. Part A.

[34]  H. V. Panossian,et al.  Real time failure detection algorithm for the Space Shuttle main engine , 1997 .

[35]  Luca Chittaro,et al.  Diagnosis of multiple faults with flow-based functional models: the functional diagnosis with efforts and flows approach , 1999 .

[36]  Bruce A. Whitehead,et al.  Neural network approach to Space Shuttle Main Engine health monitoring , 1990 .

[37]  William A. Maul,et al.  Qualitative model-based diagnostics for rocket systems , 1993 .

[38]  Timothy W. Bickmore,et al.  Aerojet's Titan Health Assessment Expert System , 1992 .

[39]  William A. Maul,et al.  Rocket engine diagnostics using qualitative modeling techniques , 1992 .

[40]  Jan Lunze,et al.  An example of fault diagnosis by means of probabilistic logic reasoning , 1997 .

[41]  Atam P. Dhawan,et al.  SSME sensor modeling using radial basis function neural networks , 1994 .

[42]  P. Coleman,et al.  Development of a real-time model based safety monitoring algorithm for the SSME , 1992 .

[43]  Luca Console,et al.  Readings in Model-Based Diagnosis , 1992 .

[44]  Jianjun Wu,et al.  Real-time fault detection algorithm based on neural networks for liquid propellant rocket engine , 1996 .

[45]  Ten-Huei Guo,et al.  Integrated Health Monitoring and Controls for Rocket Engines , 1992 .

[46]  Bruce A. Whitehead,et al.  Rocket engine diagnostics using neural networks , 1990 .

[47]  Van Casdorph,et al.  Sensor failure detection, identification and accommodation in a system without sensor redundancy , 1995 .

[48]  Johan de Kleer,et al.  A Qualitative Physics Based on Confluences , 1984, Artif. Intell..

[49]  Harry A. Cikanek.  Space shuttle main engine monitoring experience and advanced monitoring systems development , 1988 .

[50]  Qiang Shen,et al.  Selecting tools and techniques for model-based diagnosis , 1998, Artif. Intell. Eng..

[51]  C. A. Ruiz,et al.  Algorithms for real-time fault detection of the Space Shuttle Main Engine , 1992 .

[52]  U. K. Gupta,et al.  Artificial intelligence techniques for ground test monitoring of rocket engines , 1990 .

[53]  Yulin Zhang,et al.  A real-time verification system on fault diagnosis methods for liquid propellant rocket engine , 1996 .

[54]  Rolf Isermann,et al.  Neuro-fuzzy systems for diagnosis , 1997, Fuzzy Sets Syst..

[55]  A. Norman,et al.  Development of a health monitoring algorithm , 1990 .

[56]  Rolf Isermann,et al.  Trends in the Application of Model Based Fault Detection and Diagnosis of Technical Processes , 1996 .

[57]  Ten-Huei Guo,et al.  Fault detection and diagnosis in propulsion systems - A fault parameter estimation approach , 1994 .

[58]  U. K. Gupta,et al.  An expert system for fault diagnosis in a Space Shuttle main engine , 1990 .

[59]  Peter Struss,et al.  Fundamentals of Model-Based Diagnosis of Dynamic Systems , 1997, IJCAI.

[60]  William A. Maul,et al.  A qualitative approach to systemic diagnosis of the SSME , 1993 .