Jianfeng Li

Airborne missile health management system is a comprehensive management system which covers the whole life cycle status monitoring, diagnosis and prediction of various systems, subsystems and components of airborne missile, and then makes decision support for airborne missile maintenance and support. From the existing literature, there are few reports on the platform construction, operation mode and knowledge service of airborne missile health management. In order to effectively improve airborne missile health status cognition and knowledge management ability construction level, the operation service mode of health management platform is studied, and the resources in airborne missile health management field are integrated, and a knowledge-based service oriented airborne missile health management system architecture is constructed.

As a critical part of prognostics and health management (PHM), remaining useful life (RUL) prediction can provide manufacturers and users with system lifetime information and improve the reliability of maintainable systems. Particle filters (PFs) are powerful tools for RUL prediction because they can represent the uncertainty of results well. However, due to the lack of measurement data, the parameters of the measurement model cannot be updated during the long-term prediction process. Additionally, for complex systems, the measurement model of a system often cannot be obtained in an analytical form. In this paper, a fusion prognostic method based on an extended belief rule base (EBRB) and a PF is designed to solve these problems. In the proposed framework, a double-layer maximum mean discrepancy-extended belief rule base (DMMD-EBRB) model with time delay is adopted to estimate and predict the hidden behavior of a degrading system. The unknown parameters of the degradation model are identified by the PF using the output of the EBRB. Afterwards, the system state is further predicted by the PF. The effectiveness of the proposed method is validated with the NASA-PCoE and CALCE lithium-ion battery degradation experiment datasets. In addition, several other related fusion methods are investigated for comparison with the proposed method. The experiments show that the proposed method yields better performance than the existing methods.

Aiming at the problem of missing information and incomplete information in missile fault diagnosis, a method of acquiring missile fault diagnosis knowledge based on flow graph is proposed. Firstly, the fault feature information is extracted, and the fault diagnosis knowledge is classified by using the feature relationship to obtain a set of fault diagnosis examples under the same feature relationship. Then, the flow graph of incomplete fault diagnosis is established, and the confidence level and coverage level between each node are expressed. The knowledge acquisition framework of missile fault diagnosis is constructed. Finally, combining with the case analysis, it is verified that the fault diagnosis knowledge acquisition method has a good intuition, which provides an effective reference for missile fault diagnosis.

In this paper, the random vibration test and finite element simulation analysis of SAC305 solder joints in BGA packaged electronic chips were carried out. A failure model for BGA solder joints was established based on the life data. And Vulnerable parts in electronic chips were analyzed. Firstly, the random vibration test was conducted. Secondly a lognormal distribution model of solder joints by means of the life data was established and analyzed based on the fracture mechanics theory. Finally, the finite element simulation model of BGA packaged electronic chip was established and discussed. Failure characteristics of solder joints at different positions in electronic chips were compared and the failure mode of the solder joint was discussed using the simulation result and the observation result with scanning electron microscope(SEM). The results show that the life of each single solder joint in BGA packaged electronic chips follows a logarithmic normal distribution under the random vibration. Solder balls located at the four outermost corners of the chip are subjected to the greatest stress, which are the weakest parts in electronic chips. Cracks in solder joints are generated near the package side and emerged from the edge of the IMC layer with the largest curvature.

Carbon fibre‐reinforced polymers (CFRPs) are now widely used for high‐performance fields such as aircraft structures. On average, these structural components are subjected with more than 10⁸ cycles during their lifetime. To make full use of the mechanical performance of CFRP, the fatigue behaviour needs to be well studied. Nevertheless, at present, fatigue behaviour and failure mechanisms of CFRP under hygrothermal environment are not sufficiently investigated. To obtain comprehensive knowledge about fatigue behaviour and failure mechanisms of CFRP, hygrothermal tests and ultrasonic three‐point bending fatigue experiments are designed. Besides, a damage variable is proposed as the function of stiffness to evaluate the fatigue degradation of the composite. A nonlinear continuum damage mechanics (CDM) model is compared with three models and employed for fatigue damage evolution under cyclic loading. Compared with the other three models, the experimental results show a better consistency between the result of the CDM model and the measured damage. Meanwhile, the damage variable expresses the damage state of the composite effectively. The damage variable and the CDM model provide a reference for fatigue characterization analysis and further life prediction of CFRP.

Solenoid valves are important electromagnetic devices which are used widely in various fields. Considering the uncertainty of failure mechanisms in practical operation, a thermal-structure coupled model of a direct action solenoid valve is constructed by using the finite element method. The coupled model provides useful information such as temperature distribution and stress distribution for failure mechanism study of the solenoid valve. The model results predict that the failure of the solenoid valve is closely related to the thermal expansion inside the coil, which means the high temperature generated by thermal expansion melts the insulation layers. Under the combined action of high temperature and coupled stress, the shorting of coils occurs and the resistance decreases which may cause the eventual failure of the solenoid valve. To verify the prediction of the finite element model, a degradation experiment is designed. The results suggest that the failure of the solenoid valve is a gradual degradation process, and there are several mutations of coil temperature and resistance. The high temperature melts the insulation layers and causes the shorting of coils, which further decreases the resistance and increases the current. Later more heat is generated to rise coil temperature and melt insulation layers, which will short out the coils and drop the resistance. With such a relationship, as the temperature rises alternately, the resistance decreases alternately until the solenoid valve completely fails. The model provides a reference for failure mechanism study and life prolonging research of solenoid valves.

To achieve efficient and accurate remaining life prediction and effectively express the uncertainty of prediction results, this paper proposes a remaining life prediction method based on fuzzy evaluation-Gaussian process regression (FE-GPR). First, the prediction of the remaining useful life (RUL) is affected by unknown variables, such as the environment, and it is difficult to achieve accurate predictions. It is necessary to effectively express the uncertainty of such prediction results. In this paper, we have put forward a RUL prediction method based on GPR, which can realize the RUL prediction with a confidence interval. Second, combined with the characteristics of the GPR method, an observation data preprocessing method based on fuzzy evaluation is proposed. The initial fuzzy evaluation method is established based on expert knowledge. Then, the classification nodes are optimized by the gravitational search algorithm (GSA) and historical data. This method, which uses fuzzy logic combined with expert knowledge, can avoid over-fitting in the case of limited data, and effectively improves the prediction accuracy of the GPR model. Finally, we use NASA PCoE. lithium battery data for a case study. The results show that the FE-GPR method achieves a more accurate RUL prediction and effectively reflects the uncertainty of the prediction results.

This paper considers the sequential fault diagnosis problem with unreliable tests which exist widely in practice. This problem involves real-time inference of the most likely set of failure sources, i.e. fault state, based on unreliable test outcomes. The purpose of this paper is to optimize test set and diagnostic strategy so as to cut down the test cost while isolating the fault accurately, and a method for optimal diagnosis strategy based on partially observable Markov decision process (POMDP) is presented. The components of the POMDP tailed to optimizing the diagnostic strategy are specified, and the solution to the POMDP-based model, namely the optimal strategy is obtained to describe the optimal test sequence for fault diagnosis. The performance of the proposed method is evaluated with simulation experiments. And all the results indicate that this method performs good in diagnostic efficiency and accuracy, even compared with the strategies of traditional methods.

To solve the problem of low test efficiency and weak maneuverability of missiles, the reconfigurable instrument technology of missiles' portable test system is researched. In this paper, the realization plan based on PXI bus is proposed and key links of resource research is analyzed. Based on FPGA+DSP construction, the hardware circuit of the reconfigurable instrument is designed and the logic files are compiled. The research on the reconfigurable instrument technology can relieve the problem of low test efficiency and weak maneuverability of missiles effectively, and provide basis for further research of missiles' portable test systems.

To solve the problem that the FMECA of missiles is difficult to be quantified and the indicators are diverse, a method to describe the fault criticality of missiles based on multi-level fuzzy comprehensive evaluation theory is proposed. In this paper, a television guidance missile is taken as an example, factor sets, evaluation sets, weight sets, comprehensive evaluation based on multi-level fuzzy theory of missile is established. A comprehensive evaluation indicator C_x is proposed to quantitatively describe the fault criticality of missiles. This method is exact and effective to solve the problem of indicator diversity, and can provide basis for reliability research of missiles.