The failure of board level solder joint is a critical reason to electronic equipment faults in service.In this paper,a non-empirical fatigue life model of solder joint was developed based on the single time factor transfer entropy theory under vibration and temperature coupling loadings.First,the mean energy measure index was constructed by analysing the energy change before and after the crack initiation,and it was used to represent the damage degree of the solder joint.Then,a fatigue life formula was established to calculate the remaining useful life of solder joint,according to the monotonic characteristic of the index.Finally,the vibration and temperature coupling accelerated life tests were conducted to obatain the real-time dynamic response signal,in order to verify the accuracy and applicability of the model.The results showed that the damage status of solder joint can be identified effectively,and the fatigue life prediction error was less than 15％.

Thermal fatigue is a maj or source of failure of solder j oints in surface mount electronic compo-nents.Through analyzing and summarizing the lead?free solder j oint thermal reliability at home and a-broad,this paper emphatically expounds the influence of the solder Ag content,thermal cycle parameters and solder j oint microstructure on the thermal reliability of lead?free solder j oints.Finally,the paper analy-zes the challenges and the developing trend of the lead?free solder j oint thermal reliability.The hotspot and challenges in the future research by microstructure analysis and modeling,the influence of thermal load a-nalysis and the construction of physical failure model of solder joint,etc.are going to be researched fur-ther.

Anand’s visco-plasticity model was used to describe mechanical property of lead-free solders SAC305 under temperature cycle load. Finite element method was employed in the analysis of the stress and strain response of lead-free solders (SAC305) in plastic ball grid array package, especially the strain energy of key solders was discussed. The results show that the critical region appears on the surface edge of the most critical solder joints, where fatigue damage often initiates and propagates, which is verified by experiment. Plastic strain rate in temperature rising is much higher than that in high temperature lingering in temperature cycle, which affects the fatigue life of solder joints vastly.

The high uncertainty and randomness are the characteristics of the sensor data in the Cyber-Physical Systems (CPS), which make the data unreliable. A creditability analysis framework is proposed to solve those problems. Abandoning the idea that the sensor is the center in modeling, the theory takes monitoring targets into consideration and constructs the sensor-target relationship diagram, which is the base of the creditability reasoning algorithm. Meanwhile, in order to reduce the space and time of searching the relationship diagram, an improving reasoning method basing on filtering the incredible targets is designed. The examples demonstrate that the proposed algorithm can filter out the false message in the sensor data and enhances the creditability of the data in CPS.

The fault sample size which is required in existing testability demonstration test schemes may be reduced by using data in the development phase.However,the growth test data are“small samples”with“varying population”.A new testability verification method based on the Bayes theory is proposed.Firstly,the proposed method establishes a dynamic growth model of the test parameters based on multiple phases’samples,which is used to describe the changing rule of equipment’s testability and predict the fault detection rate (FDR)and the fault isolation rate (FIR).Then,the prior distribution of the system’s FDR/FIR is calculated based on the maximum entropy principle.Finally,a new testability determination scheme is defined to verify FDR/FIR,ac-cording to Bayes maximum posterior risk rules with a small size of field trial data.The practical comparison shows that this method,in which the growth test data and field trial data can be fused effectively,can reach an evaluation conclusion with a high confidence level under small sample circumstance,and reduce the risk of evaluation.

随着故障预测与健康管理(prognostics and health management,PHM)技术的快速发展和实际应用的不断深入,PHM相关标准的建立就显得非常重要.首先给出了PHM的概念和技术内涵,指明PHM标准应该规范的内容,并介绍了国内外的研究现状;其次综述了现有国外标准化组织和机构中与相关的标准,并按照视情维修(CBM),故障预测与健康管理(PHM),综合航天器健康管理(IVHM)和状态使用和管理系统(HUMS)对PHM相关标准进行了深入分析;最后对我国PHM标准开发提出了几点建议,并指明了下一步工作的重点和研究方向.

Based on the in-depth study of empirical mode decomposition (EMD) and support vector machine (SVM) algorithm, a model for aviation synchronous generator dynamic performance was presented. The EMD method was firstly used to denoise the input signal of the model. The SVM method was used to establish the model of synchronous generator's dynamic performance under the condition of instant load and unload. The results showed that the dynamic transient process of aviation synchronous generator's voltage regulation was successfully described by the model, so this method was proven to be correct and reliable.

Based on the in-depth study of fuzzy and neural network,a new prediction model for storage battery's residual capacity was presented.The clustering method of k-means was introduced to preprocess the inputs of the model,in order to improve the reasoning layer,and simplify the system output as well.Compared with the basic fuzzy and neural network,the improved fuzzy and neural network had high accuracy and needed less time,thus the method realized the real-time and precise forecast of aviation battery's residual capacity.