Health monitoring of liquid-propellant rocket engines (LRE) is one of the key technologies for improving the safety of existing engines and developing reliable next-generation engines. Extensive research has been done on the health monitoring of the Space Shuttle Main Engine and next-generation reusable LRE. A brief overview of these research projects is presented. Research advances on the health monitoring of the Long March Main Engine YF-20B are described in detail. The failure mode simulation and analysis of the YF-20B engine are introduced. A component module-based diagnosis method is developed, and a fuzzy hypersphere neural network is demonstrated for the fault detection and isolation of the engine. A real-time veri cation system for the health-monitoring algorithms and system was constructed and applied in the research.

No abstract

Based on a fuzzy match method of fuzzy rule sets which are a series of fuzzy neural networks, a system framework used for the engine fault diagnosis is proposed in this paper. This fault diagnosis system consists of five parts, including the extraction of fuzzy rules, fuzzy reference rule sets, a fuzzy rule set to be detected, the fuzzy match module of fuzzy rule sets and the diagnosis logic module. The extraction of fuzzy rules involves two steps: step 1 adaptively divides the whole space of the trained data into the subspaces in the form of hypersphere, which is expected efficiently to work out the recognition questions in the high dimension space; step 2 generates a fuzzy rule in each sample subspace and calculates the membership degree of each fuzzy rule. This paper specially makes extension of the conception of the fuzzy rule for resolving the contradictions among the generated fuzzy rules. The fuzzy rule is divided into the fuzzy reference rule set and the fuzzy rule set to be detected. Many fuzzy reference rule sets are obtained by the extraction module of fuzzy rules for the offline learning, and a fuzzy rule set to be detected is online formed while the monitoring process is going on. With the beliefs estimated from the fuzzy match process of fuzzy rule sets, which indicate the existence of working classes in the plant, the diagnosis logic module can export fault detection time, fault isolation time, fault type and fault degree. The simulation researches of the fault diagnosis in a 2000N space propulsion system demonstrate the superior qualities of the fault diagnosis method on the basis of the fuzzy match of the fuzzy rule sets.

No abstract

This paper designed a platelet heat exchanger in the solar thermal thruster and analyzed the unsteady-state conjugate heat transfer characteristics between heat exchanger and propellant. The conjugate heat transfer (CHT) computational fluid dynamics (CFD) simulation of the 3D model of the platelet under steady-state conditions was carried out with different mass flow rates to find the empirical correlation between the average Nusselt number and the average Reynolds number. The unsteady-state 1D simplified model of the heat exchanger was established using a loose coupling algorithm based on quasi-steady flow domain and finally verified by experiments. The results show that the platelet structure could heat the working medium to more than 2380 K with the heat transfer efficiency of 87% and produce a peak thrust of 0.57 N and specific impulse of 2200 m/s; in steady state, the outlet temperature and heat transfer efficiency of the heat exchanger were stable at 1950 K and 69%. Moreover, 1D model could accurately reflect the real heat exchange situation to a certain extent, the simulation error was less than 5% compared with the 3D model, and the calculation time was greatly shortened, making it more convenient to adjust the heat exchange strategy. The experimental results were consistent with the simulation results at the initial stage of heat exchange, and the difference was mainly reflected in the steady-state stage, which might be caused by the lack of precision of the experimental equipment.