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Aiming at the nonstationary characteristics of echo signal for a high-speed maneuvering target, a signal feature extraction method is proposed by combining the time-frequency analysis and convolution neural network, and then the automatic detection of radar moving target in a noisy environment is realized. Firstly, the echo signal is modelled as a more accurate Gaussian modulation-linear frequency modulation (GM-LFM) signal and converted into the time-frequency image by a second-order synchroextracting transform (SET2). Then, ridge extraction is applied to extract the maximum energy ridge from the time-frequency distribution, and the data set is constructed by the maximum energy ridge. Finally, the data set is input into AlexNet for training, and the deep-level features of echo signal are extracted to realize the automatic moving targets detection. Simulation results show that SET2 and RE can effectively enhance the time-frequency characteristics of echo signal under the noisy environment, and the detection accuracy and noise robustness of the proposed method are better than that of SET1 and smooth pseudo-Wigner–Ville distribution (SPWVD).

For subway connection channel projects built in coastal areas, freeze-thaw and compaction are two key factors that change the soil microstructure and affect engineering safety. Therefore, understanding the variation law of the microscopic pore structure of soft clay and freeze-thawed soft clay is crucial to the design and prediction of the serviceability of subway infrastructures. Considering this, to understand the effects of freeze-thaw and compaction coefficient on microscopic pore structures and fractal characteristics, a series of nuclear magnetic resonance (NMR) tests were performed on soft clay and freeze-thawed soft clay under different compaction coefficients. Based on the experimental data, a fractal theory was proposed to describe the fractal characteristics of the tested materials. Moreover, the effect of curing agents on the microscopic pore structure of soft clay was studied by adding two curing agents to the soft clay. The experimental results showed that compaction coefficients had a significant effect on the pore size distribution (PSD) of soft clay and freeze-thawed soft clay. As the compaction coefficient increased, the proportion of large pores decreased significantly, and the proportion of small and medium pores increased. Moreover, the compaction coefficient was found to have a significant effect on the fractal dimension (D) of soft clay and freeze-thawed soft clay whereby increases in compaction coefficients led to a trend of increased D and heterogeneity within soft clay and freeze-thawed soft clay. With the development of freezing front and the formation of ice lens, the pore structure of soft clay and the connection between soil particles are destroyed. The microscopic pore characteristics of the soil samples with an added solidifying agent were characterized by a significant increase in the number of small pores and a decrease in the number of large pores. This research can provide theoretical guidance for the construction of subway connection channel engineering projects.

Synthetic aperture radar automatic target recognition (SAR ATR) is a key technique of remote-sensing image recognition, which has many potential applications in the fields of military surveillance, national defense, civil application, and so on. With the development of science and technology, deep convolutional neural network (DCNN) has been widely applied for SAR ATR. However, it is difficult to use deep learning to train models with limited ray SAR images. To resolve this problem, we proposed an effectively lightweight attention mechanism CNN (AM-CNN) model for SAR ATR. Extensive experimental results on the Moving and Stationary Target Acquisition and Recognition (MSTAR) data set illustrate that the AM-CNN model can achieve a superior recognition performance, and the average recognition accuracy can reach 99.35% on the classification of 10 class targets. Compared with the traditional CNN and the state-of-the-art method, our model is significantly superior to improve performance and efficiency.

Transmission towers with steel tubes or so-called tubular towers are widely used for ultra-high voltage (UHV) transmission because of their overall higher strength and stability, and better wind resistant capability. However, within a specific wind velocity range, tubular members with a high slenderness ratio are susceptible to joint fatigue failure under the vortex-induced vibration (VIV). To thoroughly unveil the mechanism of VIV of tubular members in UHV transmission towers, this paper first measures the acceleration and corresponding wind velocity of a tubular member under the VIV, followed by an identification of the first-order frequency. Then, a simulation framework for the tubular members subjected to the VIV is proposed. The system considered is simplified as a mass–spring–damping system with the non-linear coupling effect between the tubular member and wind field taken into account. Based on the analysis, the lock-in region and maximum displacement amplitudes in the cross-wind direction are calculated, while the simulation accuracy is verified via comparison with the on-site measured data. Meanwhile, the influence of damping ratio on the VIV is studied. Finally, a new type of radial spoiler is proposed to suppress the VIV of the tubular members. The results of the 3D simulation show that the proposed radial spoiler can effectively suppress the vortex generation, and there is no noticeable vibration after the installation of the countermeasure. In effect, it was demonstrated that the proposed countermeasure can effectively suppress the VIV of the tubular tower. The parametric analysis reveals that the distance between two adjacent spoilers has a significant impact on the control efficiency and should be carefully designed for each project.

Accurate simulation of overhead transmission towers under extreme wind loads is complicated due to the eccentrically connected angle section members. First, a full-scale 230 kV suspension tower is manufactured, to which eight loading patterns are applied. The tower successfully passes a 100% loading step test under each pattern and is overloaded to collapse under the final pattern. Then, the framework of a uniform imperfection mode method for the transmission tower is developed to simulate the tower's ultimate performance. The calculated critical loading level and member strains agree well with the experimental results, indicating that it is feasible and reliable to simulate the tower response using the developed method. Finally, an uncertainty analysis is introduced to consider the variations in structural parameters. The tower leg, the initial failure position of the full-scale test, has a failure probability of 8.74%, and its probability of entering the plastic state reaches 92.00%. The failure positions predicted by uncertainty analysis reflect those observed experimentally, providing a feasible approach for finding all the potential failure modes.

Based on the characteristic anthrahydrazone pharmacophore, two new anthrahydrazone derivatives (9-PMAH and APMAH) were synthesized, which further afforded two corresponding cisplatin-like Pt(II) complexes (9-PMAH-Pt and APMAH-Pt). Their chemical structures were characterized by IR, ESI-MS, elemental analysis and X-ray single crystal diffraction method. Their in vitro cytotoxicity towards a series of human tumor cell lines and the normal liver cell line HL-7702 were screened and shown in IC50 values and compared with that of cisplatin. 9-PMAH-Pt showed higher cytotoxicity against MGC-803 and HepG-2 than the other tested compounds including cisplatin, while it showed lower toxicity on HL-7702 than cisplatin. The structure–activity relationship from the in vitro cytotoxicity study indicated that the substitution of –CHO on the opposite C10 of anthrahydrazone was unfavorable to higher cytotoxicity, which might be due to its steric hindrance considering the planar aromatic anthracene. Further studies demonstrated that 9-PMAH-Pt induced cell apoptosis in both MGC-803 and T-24 cells by arresting the cell cycle at the G2/M phase, which was totally different for cisplatin, suggesting the different antitumor efficacies of this platinum complex and cisplatin. On the molecular level, it was suggested that 9-PMAH-Pt could bind with DNA via an intercalative mode, likely competing with GelRed in similar intercalative binding sites. 9-PMAH-Pt also effectively inhibited the activity of TOPO I, acting as a TOPO I suppressor. The results of this work suggest a new type of platinum complex bearing anthrahydrazone ligands to form a new bifunctional antitumor candidate in comparison with the classic platinum drugs.

Wavelet transform (WT) can be viewed as a differently scaled bandpass filter in the frequency domain, so WT is not the optimal time-frequency representation method for those signals which are not band-limited in the frequency domain. A novel fractional wavelet transform (FRWT) is proposed to break the limitation of WT, it displays the time and fractional frequency information jointly in the time-fractional-frequency (TFF) plane. The definition and basic properties of FRWT are studied firstly. Furthermore, the multiresolution analysis and orthogonal fractional wavelets associated with FRWT are explored. Finally, the application of FRWT in the LFM signal TFF analysis is discussed and verified by simulations. The experimental results show that the energy concentration of LFM signal representation by proposed FRWT is better than that of some existing methods. The better energy concentration makes it can be further applied to the denoising, detection, parameter estimation and separation of LFM signal.

As important components of transmission tower-line systems, tension towers are used mainly at the corner of the line or among several suspension towers to prevent their progressive collapse under extreme loading conditions. Compared with suspension towers, tension towers exhibit more complicated stress states and different failure patterns. Under the activities of various disasters, the failure of tension towers will result in more serious consequences, but their failure mechanism is seldom investigated. In this paper, the stress and displacement distributions of a tension tower under eight different loading cases are analyzed based on a full-scale test. The test tower successfully passes a 100% loading step test under the first seven loading cases and is overloaded to collapse under Case 8. Then, the finite element model (FEM) of the test tower is established, and the buckling instability of members is simulated by applying initial imperfections. The calculated critical loading level and member strains are in good agreement with the full-scale test results, verifying the reliability of the FEM and analysis method. Finally, the pushover analysis is performed to simulate the failure pattern of the tension tower, and the results demonstrate that the failure mode is the shear failure. Plastic failure occurs firstly in the diagonal members of the cross arm under compression, after which the main members yield quickly, completely forfeiting the bearing capacity of the tower. For the tension tower employed in this test, the diagonal members under compression play a decisive role in the ultimate bearing capacity.

Quadratic phase interference fringes are often encountered in optical measurement, its parameters estimation plays an important role in the interferometry field. This paper takes Newton’s rings as a classical example of quadratic phase interference fringe, proposes a CFT-based method to estimate the parameters of Newton’s rings. The phase derivative can be estimated directly and accurately without unwrapping, which are verified by the simulated and actual Newton’s rings. Furthermore, the proposed CFT-based method is applied to measure the curvature radius of spherical surface, which makes the measurement method has the advantages of low computational complexity, high accuracy and fast speed. The experiments results confirm that the CFT-based method not only has better noise and obstacle robustness over traditional Newton’s rings measurement, but also has higher efficiency over FRFT-based method.

Aiming at the problem that the traditional M-S propagation loss estimation model is insensitive to the loss of submarine and sea surface propagation, this paper presents a method to improve the sensitivity and accuracy of the submarine absorption parameters. According to the near-field anomaly of M-S, the upper and lower limit of geometric propagation is different. This paper gives a new extended calculation method. By calculating the near-field anomaly coefficients, the new computational model is further evaluated for any negative gradient, which is further calculated for the upper and lower slope terrain. The sea trial data show that the redefined M-S model estimation has higher accuracy and more sensitive computing power under the premise of guaranteeing fast computation.

The contribution of the different covalence for t2 and e orbitals must be considered in the investigation of the optical and magnetic properties of the transition metal ion in II–VI and III–V semiconductors. In present paper, two covalent parameters Nt and Ne associated with t2 and e orbitals have been adopted to describe the covalence. The energy matrices considering the different covalence for t2 and e orbitals have been provided for d5 ions in crystal. These matrices show that the contribution from the Racah parameter A cannot be neglected in calculation of energy-level of d5 ions in covalent crystal. The calculated results using the matrix show that the energy levels of E 4 and A 1 4 states split, and the energy-level difference between E 4 and A 1 4 states increases with increase of the different covalence between t2 and e orbitals. These energy levels are always degenerate, when the different covalence for t2 and e orbitals is neglected. By using the energy matrices, the energy-level of ZnS:Mn2+ has been calculated. The calculated energy levels of ZnS:Mn2+ are in good agreement with the experiments.

In view of the non-stationary features of vibration signals of gear and the difficulty to obtain a large number of fault samples in practice, a fault diagnosis scheme based on empirical mode decomposition (EMD) entropy of singular values and support vector machine is put forward in this paper. Firstly, original acceleration vibration signals are decomposed into a finite number of stationary intrinsic mode functions (IMFs); the initial feature vector matrixes are formed by the intrinsic mode functions. Secondly, using the singular value decomposition technique to the vector matrixes, the singular values are obtained. Finally, the singular values serve as the fault characteristic vectors to be inputted to the support vector machine classifier and the work conditions and fault patterns are identified by the output of the classifier. Practical examples show that the diagnosis approach put forward in this paper can identify gear fault patterns effectively.