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To solve the problems of low accuracy, difficult diagnosis and long time consuming of the current fan bearing fault diagnosis, an improved grey wolf optimization (IGWO) algorithm and a support vector machine (SVM) fault diagnosis method are proposed. In order to accurately extract the fault features, the wavelet packet decomposition method in the time-frequency domain analysis is used to extract the fault vibration signal. Take the wavelet packet decomposition energy of the eight frequency bands as the fault feature， the eigenvectors are constructed. Then, the fault model of SVM is established and the parameters of the SVM model are optimized by the IGWO algorithm, which avoids the defects of local optimum and slow convergence. According to the experimental analysis result, the average fault recognition rate of the IGWO algorithm is up to 99.3%, and it can identify fault types more quickly, more efficiently and more accurately, which provides a good support for the development of fault diagnosis.

DC-DC converter is the core component of power conversion module of integrated modular avionics. Condition monitoring and fault diagnosis of DC-DC converter can effectively improve the reliability of avionics equipment, reduce the maintenance cost and greatly improve the use efficiency of aircraft. In this paper, firstly, a typical DC-DC converter model based on SEPIC topology is designed in PSPICE environment, and the failure modes of DC-DC converter are analyzed. Secondly, the typical fault types of DC-DC converter are simulated, and the corresponding original data are obtained through simulation. Finally, the processing framework including data preprocessing, feature extraction and selection, and multi model fusion is used to do fault classification of the DC-DC converter. The fault diagnosis of the converter is simulated. Simulation results show the effectiveness of the proposed method.

Aviation control software has become the core control decision-making unit of the aviation system. The Boolean conditional expressions are the main parts of the branch and loop control logic of aviation control software. This paper studies the fault classification and repair method of conditional expression of aviation control software. 1) a two-level Boolean conditional expression fault classification method is proposed; 2) based on the design of mutation operator, repair solution and stop condition of mutation repair, an automatic repair method of conditional expression is proposed; 3) a repair assistant tool for conditional expression is designed and implemented, and 155 fault expressions are repaired. The results show that 55.5% of fault expressions can achieve accurate repair, 44.5% of fault expressions can generate multiple correct versions after a repair, and some versions have operation redundancy, so it is necessary to select the optimal version manually.

Different faults of oil-immersed power transformers were classified with three-layer structure of 'parts-fault causes-temperature rising phenomeno' and the fault causes were summarized, impacts of the different faults on outer surface temperature of transformer were briefly analyzed. The results show that fault will lead to outer surface temperature rising which including iron core and clamping pieces, winding and leading wires, tapping switch, insulation system, tank and base of the transformer; the faults of cooling system inevitably lead to outer surface temperature rising; part of bushing failures of outlet and inlet line will cause outer surface temperature rising of the transformer; most of failures of protection and measurement device will cause temperature rising of the transformer. Thus the preliminary relations between faults and its outer surface temperatures of the oil-immersed power transformer were obtained, namely most faults of the transformer will lead to outer surface temperature rising.