Chaoxuan Qin

Aiming at the problem of centroid deviation of aircraft carrying multiple fuel tanks under different fuel supply strategies, the time discretization, coordinate transformation and vector synthesis methods are used to obtain the centroid change curve, and the centroid change problem caused by the change of pitch attitude of the aircraft is studied. The Euclidean distance between the aircraft centroid and the ideal centroid is minimized as the objective function, and the optimization model is established. The fuel supply rate of each tank is obtained by particle swarm optimization algorithm, and the centroid optimization strategy is finally obtained. Simulation results show that the proposed strategy can effectively find the optimal fuel supply strategy for aircraft, which provides important reference value for aircraft design.

This paper put forward a kind of fast, high precision, high sensitivity of corrosion monitoring method and developed a portable corrosion monitoring device with 6 road crystal vibration sensor and a temperature and humidity based on QCM theory. The device can work independently for a long time in harsh outdoor environment without relying on external power supply. The quantitative relationship between quartz crystal vibration frequency and corrosion quality was determined by calibration tests in the laboratory. The device is placed in a certain environment to monitor the corrosion. The results show that the device can effectively monitor the weak corrosion phenomenon, with real-time and high sensitivity.

Outdoor haze has adverse impact on outdoor image quality, including contrast loss and poor visibility. In this paper, a novel dehazing algorithm based on the decomposition strategy is proposed. It combines the advantages of the two-dimensional variational mode decomposition (2DVMD) algorithm and dark channel prior. The original hazy image is adaptively decomposed into low-frequency and high-frequency images according to the image frequency band by using the 2DVMD algorithm. The low-frequency image is dehazed by using the improved dark channel prior, and then fused with the high-frequency image. Furthermore, we optimize the atmospheric light and transmittance estimation method to obtain a defogging effect with richer details and stronger contrast. The proposed algorithm is compared with the existing advanced algorithms. Experiment results show that the proposed algorithm has better performance in comparison with the state-of-the-art algorithms.

In this paper, an improved PSO (Particle Swarm Optimization) algorithm is proposed and applied to the infrared image enhancement. The contrast of infrared image is enhanced while the image details are preserved. A new exponential center symmetry inertia weight function is constructed and the local optimal solution jumping mechanism is introduced to make the algorithm consider both global search and local search. A new image enhancement method is proposed based on the advantages of bi-histogram equalization algorithm and dual-domain image decomposition algorithm. The fitness function is constructed by using five kinds of image quality evaluation factors, and the parameters are optimized by the proposed PSO algorithm, so that the parameters are determined to enhance the image. Experiments showed that the proposed PSO algorithm has good performance, and the proposed image enhancement method can not only improve the contrast of the image, but also preserve the details of the image, which has a good visual effect.

For compound fault detection of high-speed rail vibration signals, which presents a difficult problem, an early fault diagnosis method of an improved empirical mode decomposition (EMD) algorithm based on quartic C² Hermite interpolation is presented. First, the quartic C² Hermite interpolation improved EMD algorithm is used to decompose the original signal, and the intrinsic mode function (IMF) components are obtained. Second, singular value decomposition for the IMF components is performed to determine the principal components of the signal. Then, the signal is reconstructed and the kurtosis and approximate entropy values are calculated as the eigenvalues of fault diagnosis. Finally, fault diagnosis is executed based on the support vector machine (SVM). This method is applied for the fault diagnosis of high-speed rails, and experimental results show that the method presented in this paper is superior to the traditional EMD algorithm and greatly improves the accuracy of fault diagnosis.