Autonomous underwater vehicles (AUVs) are widely used in various fields such as hydrological monitoring, underwater exploration, and patrol reconnaissance, due to their mobility, robustness, and extensive operational range. To ensure the safe and efficient completion of various tasks, the research on motion control technology for AUVs is of paramount importance. This paper provides a chronological overview of the development of AUVs, focusing on typical products both domestically and internationally, with an emphasis on motion control technologies. Additionally, it presents the "Sheng Whale I" AUV developed by the team, along with its motion control technology. Based on the current state of AUV motion control research, strategies can be classified into path tracking, trajectory tracking, and stabilization control. Research in this field primarily focuses on the design of guidance schemes and the optimization of controllers. The main challenges affecting AUV motion control systems include model uncertainties, external disturbances, and actuator saturation. To address these challenges, intelligent control techniques such as deep reinforcement learning, sliding mode control, active disturbance rejection control, neural networks, adaptive control, S-plane control, and fuzzy control have been widely applied. These methods effectively mitigate the impact of changes in the AUV's dynamic model, as well as environmental disturbances like waves and ocean currents, on tracking accuracy. For actuator saturation issues, model predictive control, deep reinforcement learning, and sliding mode control have shown particularly promising results. Existing research indicates that information-based AUVs are numerous, and the motion control systems of AUVs demonstrate significant advantages in terms of accuracy and robustness. Future developments in AUVs will focus on long-range vehicles powered by renewable energy and multi-mode AUVs equipped with autonomous maneuvering capabilities. Additionally, the trend in AUV motion control will shift towards low-power motion control and swarm motion control.

As a flexible bridge, the deflection control of the main girder is particularly important during the operation of a suspension bridge. To predict the vertical deflection of the main girder of an existing suspension bridge under the combined effects of random traffic flow and environmental temperature, this paper establishes an integrated deflection interval prediction method based on Convolutional Neural Networks (CNN), Long Short-Term Memory (LSTM) networks, probability density estimation layer, and bridge monitoring data. Using health monitoring data from the Nanxi Yangtze River Bridge, a time series training set of environmental temperature, vehicle load, and deflection monitoring data was established. The combined CNN-LSTM layers captured local features and long-term memory in the time series. A Gaussian distribution was used as the probability density function, and the parameters of the Gaussian distribution were evaluated using the maximum likelihood method, resulting in optimal deflection prediction values and probability intervals. Based on this, a method for identifying abnormal deflection and warning thresholds for the main girder of existing suspension bridges was proposed. The study shows that compared to LSTM and CNN-LSTM models, the CNN-LSTM-GD model has better predictive capabilities for small deflection fluctuations and extreme deflections, with deflection prediction values closely matching the monitoring data. Over a 24-hour time scale, compared to the traditional LSTM model, the CNN-LSTM-GD model improved the Root Mean Square Error (RMSE) and the coefficient of determination (R2) by 54.40% and 10.22%, respectively. Compared to the CNN-LSTM model, the improvements in RMSE and R2 were 38.43% and 5.31%, respectively.

Precision optical instruments in aircraft and ships face increasingly stringent requirements for the vibration environment, and active control methods via the Stewart platform have attracted extensive attention. Firstly, the development of Stewart active vibration isolation platform at home and abroad was investigated, and the main performance indicators such as payload (Kg), active bandwidth (Hz) and maximum amplitude attenuation (dB) were summarized. Secondly, the key technologies on Stewart active vibration isolation platform, including Stewart platform configuration, isotropic and dynamic stability, coupling factors and decoupling methods, dynamic modeling methods, nonlinear and hysteresis phenomena of smart material actuators, and active control algorithms, were summarized in detail. The study discussed how the main performance indicators were enhanced by these key technologies and identified unresolved issues； then, the advantages of multi-channel coupled adaptive algorithm using Stewart isolation platform in complex and time-varying vibration environment were summarized. Finally, the further development of Stewart active vibration isolation platforms in precision optical instruments was prospected. 

In order to solve the problem of low fault diagnosis accuracy, this paper proposes a bearing fault diagnosis method based on feature cross-attention mechanism fusion and develops the CNN-BiTCN-CATTM model. The original signal is reconstructed using variational mode decomposition and fast fourier transform, while bidirectional temporal convolutional networks (BiTCN) and convolutional neural networks (CNN) are used to extract time-frequency features. The cross-attention mechanism (CATTM) is applied to fuse these features, fully capturing fault characteristics from the original signal. Experiments show that in an environment with Gaussian white noise (SNR = 9.32, standard deviation = 2.98), the CNN-BiTCN-CATTM model achieves a bearing fault classification accuracy of 99.88%, which is about 22.79%, 4.85%, and 4.19% higher than using CNN, BiTCN, and CNN-SATTM, respectively. Even with Gaussian white noise (SNR = 3.31, standard deviation = 5.96), the model still achieves a diagnostic accuracy of 96.12%. The CNN-BiTCN-CATTM model effectively extracts deep fault features and significantly improves fault classification accuracy.

Nonlinear energy sink (NES) has broad application prospects in passive control.However, studies in this filed mainly focus on unidirectional vibration absorbers to limit its applicability to multi-directional vibrations in practical applications.Here, a multi-directional NES was designed using 2 sets of mutually orthogonal steel wire structures to realize adaptive vibration absorption in any direction of a single vibrator space.Multi-directional vibration governing equations of the system were established based on Lagrange equation, and the harmonic balance method was used for approximate analytical analysis of the system’s steady-state response.The fourth-order Runge-Kutta method was used for numerical verification, and then the vibration reduction effect of the multi-directional NES was studied.The results showed that the multi-directional single vibrator NES can effectively suppress multi-directional vibrations and it is equally effective for any unidirectional excitation. This study can provide a reference for application and design of NES in multi-directional vibration control.

Given the issues of imbalanced attention mechanisms, conservative pooling strategies, and the loss function's inability to comprehensively consider information from all classes leads to the learned features being relatively scattered in the FasterVit network, a rolling bearing fault diagnosis method based on the CFasterVit-TFAM and COS-UMAP models is proposed. The model consists of the FasterVit-TFAM network, the COS-UMAP dimensionality reduction algorithm, and the activation function CMSD-Softmax. Firstly, a new attention mechanism TFAM is proposed and combined with the FasterVit network to improve the balance and representation ability of information attention in the FasterVit network. Secondly, the COS-UMAP dimensionality reduction algorithm is used to replace the last pooling operation before the fully connected layer of the FasterVit network, effectively filtering and retaining important features in multidimensional data. Finally, replacing the cross-entropy loss function in the Softmax activation function with the mean standard deviation loss function allows for a more comprehensive learning of features and improves the model's generalization. The XJTU rolling bearing mixed fault experiment results show that the diagnostic accuracy of the TFAM attention mechanism is increased by 8% compared to other attention mechanisms, and the diagnostic accuracy of the COS-UMAP is increased by 15.8% compared to other dimensionality reduction algorithms. The diagnostic accuracy of the CMSD is increased by 0.5% compared to the cross entropy loss function. The proposed model achieves a recognition accuracy of 99.6% for fault samples, which is 1.4% higher than that of FasterVit and 7.8% higher than that of other network models. The simulation results of the rolling bearing dataset from Southeast University show that the proposed model achieves a recognition rate of 98.6% for fault samples, which is 2.2% higher than that of FasterVit. The average training time per round is reduced by 16.92 seconds, which is a maximum improvement of 12.2% compared to other network models, effectively improving the accuracy and generalization performance of the rolling bearing fault diagnosis model.

The transfer learning method has made great progress in solving the problem of unsupervised fault diagnosis of gearbox. However, due to the differences in the distribution of gearbox data, noise and interference, and the limitations of the model, most of the methods are not effective in migrating complex gearbox datasets, and there are still few studies on the interpretability of network inputs. In this paper, we propose an improved domain-adversarial neural network (IDANN). The improved time-frequency network is used as a feature extractor to provide interpretability and noise reduction when the signal is fed into the network, and then the class-level alignment method of the target domain is added to the domain adversarial network, and two classifiers are used to detect the target samples close to the decision boundary to enhance the migration performance. The effectiveness and reliability of IDANN are verified on the Southeast University gearbox dataset and straddle-type monorail gearbox, and the performance of IDANN under noise conditions is tested on the Case Western Reserve University bearing dataset, and the experimental results show that IDANN has excellent diagnostic performance and robustness. 

As the core component of active vibration control, a novel Ampere force electromagnetic actuator based on the Halbach magnetic pole array was designed, featuring high force density and low output force fluctuation rate. The multi-physical field coupling relationship of the electromagnetic actuator was analyzed, and a coupled model of the electromagnetic field and energy consumption field was established. In this model, the energy consumption field was modeled by the neural network surrogate model method to enhance the computational efficiency. The NSGA-II optimization algorithm was employed to conduct multi-objective optimization design, and the improved entropy weight decision-making theory was combined to obtain the optimal combination of design parameters. A prototype of the electromagnetic actuator was fabricated and experimental analysis was carried out. The results show that: In the 30-250Hz frequency band, the force constant of the actuator can reach 20 N/A, and the nonlinearity is less than 10%. When the peak current is 8 A at 250 Hz, the energy consumption of the actuator is 105.20 W, presenting the advantages of low force attenuation rate, good linearity, and low power consumption.

To address the issues with complex and variable vibration signals in gearboxes, which led to low diagnostic accuracy of existing gearbox fault diagnosis methods and the risk of weak fault features being overwhelmed by noise, a new fault diagnosis method was proposed. Firstly, entropy weight fusion algorithm was used to fusion vibration sensor signals at different locations, and vector weighted mean value algorithm (INFO) was used to optimize parameters in the variational mode decomposition (VMD) algorithm. A composite evaluation index was designed as the evaluation standard for parameter optimization. The Singular Kurtosis Differential Spectrum (SKD) method was employed to reconstruct the sensitive components. What’s more, the time domain and frequency domain features were extracted from the reconstructed signals and fed into the CNN model for classification. Finally, Shapley Additive Explanations (Shap) value method was used to rank the importance of input features. The impact of different feature combinations on model classification and specific fault identification was analyzed. The proposed method was validated on the Planetary Gearbox Dataset from Southeast University. It was shown that using the proposed feature combination for fault diagnosis, the CNN model achieves an accuracy of 98.24%, which is higher than other combinations. This provides an effective set of feature indicators for planetary gearbox fault diagnosis.

Accurately identifying and locating internal defects is crucial for ensuring safety and durability of concrete structures. The impact echo (IE) method has unique advantages for concrete structures with only a single inspection surface. When using IE method for testing internal defects in concrete structures, the difficulty lies in analyzing features of IE signals and classifying and identifying defects. Here, a method for identifying internal defects in concrete was proposed based on deep learning of time-frequency maps of IE signals. Firstly, IE tests were conducted for concrete slabs containing different types of defects including holes, honeycombs and cracks. Then, the original IE signals were converted into time-frequency maps with short-time Fourier transform and continuous wavelet transform, respectively. Finally, 2 types of time-frequency maps were combined for data expansion to construct datasets containing defect types, hole sizes and crack depth time-frequency maps. 3 types of deep learning models of Swin Transformer, Vision Transformer and ResNet18 were used for training. Based on the relevant evaluation indexes of deep learning models, performances of different deep learning models under different datasets were analyzed, and the classification and recognition effects of models on defects were compared. The results showed that Swin Transformer performs the best among 3 models, its correctness rate is over 95.00% in defect type classification, and it has good recognition performance.

The crashworthiness of an aircraft is not only affected by its own structural design, but also closely related to the crash speed, the landing attitude, and the runway environment.The full-scale structure of a typical civil aircraft was taken as the study object, and a full-scale aircraft crash dynamics model, was established, which was then validated by the experimental data from the literature.Numerical simulations of crashes under different impact speeds, pitch angles, roll angles, and runway environment factors were further conducted to explore the influences of different factors on the aircraft crash response.The results show that as the impact speed increases, the initial peak of the crash load on the lower part of the fuselage and the platform load gradually increase, and the area of deformation of the fuselage gradually increases.With the increase of the pitch angle, the waveform of the crash load changes significantly, the load peak decreases significantly, the peak acceleration of the floor gradually decreases, the acceleration of the mid-fuselage structure is more sensitive to the change of the pitch angle, and the impact speed of the local fuselage structure of the aircraft is significantly affected by the aircraft pitch angle.Under the condition that the overall vertical impact speed of the aircraft remains unchanged, the greater the pitch angle, the greater the impact speed of the front fuselage section, and the overall non-linear increase trend from the nose to the rear fuselage is presented.The roll angle has little effect on the aircraft’s crash load and the acceleration peak of the wing, but has a significant effect on the acceleration peak of the fuselage floor.The deformation on the side of the fuselage bottom at the near roll direction increases, and a new plastic hinge is produced.Compared with the rigid runway, when crashing on the clay runway, the vertical impact load peak of the aircraft decreases, and the heading impact load peak increases significantly.The aircraft crashes on the clay runway and produces a gully-like deformation.The shape of the gully and the deformation expansion process under different pitch angles are significantly different.The deformation of the fuselage and the peak acceleration of the floor are smaller when crashing on the clay runway, and the risk to the safety of the passengers is smaller than that on the rigid runway.

Because of the large scale of the project, high efficiency, and to a certain extent can save the production cost of mining and stripping, cast blasting has been favored by the open pit mining industry in the United States, Australia and other developed countries. By combing and analyzing the development history of cast blasting technology in open-pit mines at home and abroad, the production characteristics of cast blasting technology are defined. The factors influencing the blasting quality in open-pit coal mine are analyzed from the aspects of strong controllable, weak controllable and uncontrollable, and the applicability conditions of the cast blasting technology in open-pit mining are also analyzed. Based on the theory of plane charge method and blasting seismic effect, the rock blasting mechanism of blasting technology is deeply analyzed, the four stages of rock throwing after explosive initiation and the evolution characteristics of rock strata are defined, and the seismic response characteristics of blasting technology are analyzed and summarized. Taking Heidaigou open-pit mine as an example, the application status of cast blasting technology is described in detail, the operation flow of cast blasting technology application is systematically analyzed, the internal structure and operation mechanism of cast blasting and dragline stripping technology is analyzed, and the bottleneck problems existing in the application of cast blasting technology are analyzed and summarized. Aiming at the intelligent transformation and upgrading of projectile blasting technology, the whole system process of cast blasting engineering, such as transparent geological information, intelligent blasting design, fine blasting construction, informatization of safety management, and precision blasting effect, is analyzed and refined respectively, from the aspects of disciplinary support, technical support and problems to be solved. The knowledge system and intelligent system architecture of cast blasting technology are constructed, the research trend of cast blasting technology in the future is proposed, and the applicability of cast blasting technology in other open-pit coal mines in china is analyzed. The research results can provide reference and basis for the upgrading and transformation of blasting engineering technology in other industries.

The impact vibration test is widely used in modal analysis, because of its convenience, low cost, and efficiency in identifying multiple modes with a single impact.To achieve efficient and accurate estimation and uncertainty quantification of modal parameters in the impact test, a fast Bayesian fast Fourier transform method was proposed.The likelihood function was first developed based on the equation of motion and the complex normal assumption of measurement error, and the Laplace approximation was then adopted to obtain the posterior distribution of modal parameters, i.e., fitting the posterior distribution with a Gaussian distribution, whose mean was computed by minimizing the negative log likelihood function (NLLF) while the covariance matrix was obtained by taking the inverse of the Hessian matrix of NLLF at the posterior mean.A coordinate descent algorithm was proposed to minimize the NLLF taking advantage of the analytical gradient of NLLF.The Hessian matrix was obtained via the calculus of complex matrix, allowing an efficient implementation.Finally, the performance of the proposed method was validated through synthetic and laboratory data.A comparison with the methods based on free and ambient vibration tests was also provided, respectively.

多体动力学；刚柔耦合；假设模态法；机电耦合；振动控制

Clunk noise caused by torque ripple under transient operating conditions is one of the main vibration and noise problems of IWM (in-wheel motor) drive systems. Large torque ripple may cause torsional vibration in the drive transmission system, seriously affecting ride comfort and safety. Therefore, conducting research on Clunk noise of IWM drive systems is of great engineering significance for improving the NVH performance of the system. The driving system of the inner rotor permanent magnet synchronous IWM is taken as the research object, and the mechanism of Clunk noise generation during vehicle testing is analyzed. Through bench testing, it was found that the impact vibration between teeth caused by the cogging torque of the motor is the main cause of Clunk noise. A multi-body dynamics analysis model of the IWM drive system was established based on Masta software, and the effectiveness of the model was verified through experimental data conclusions. The influence of various parameters on Clunk noise was analyzed using the control variable method. Through the analysis of key parameter influencing factors, it was found that motor speed and cogging torque have a significant impact on Clunk noise. A control scheme was proposed to suppress Clunk noise by reducing torque ripple caused by cogging torque. By optimizing the rotor skewed pole and injecting harmonic current, the torque fluctuation can be reduced from 3.8Nm to 0.24Nm, achieving the effect of improving the sound quality of Clunk noise. After optimizing the NVH test of the sample, the Clunk noise level was significantly reduced, and the subjective evaluation was acceptable. Solved practical engineering problems and improved the NVH performance of the wheel hub motor-driven transmission system.

Based on the research background of twin rotor actuator, a single drive twin rotor actuator active control device is proposed in this paper, which is mainly composed of mass block, space transmission gear group, motor and controller. The centrifugal force generated when the rotor is driven by the gear is used as the active control force to reduce the structural vibration. Compared with the traditional active mass damper, this design not only does not need to consider the linear travel limit of the guide rail, but also solves the problem that the motor in the dual drive twin rotor actuator is difficult to synchronize through structural optimization, and realizes more efficient and stable vibration control. In order to study the vibration damping performance of the single drive twin rotor actuator, firstly, the mechanical model of the single drive twin rotor actuator system, the single degree of freedom structure and the state equation of the single driven twin rotor actuator are established based on the mechanical analysis of Lagrange equation. Secondly, a controller combining pole assignment method and Super-Twisting Sliding mode control algorithm is designed for vibration reduction of single drive twin rotor actuator system, and the control parameters contained in the controller are optimized based on the improved Dung beetle optimization algorithm. Compared with other control algorithms, the proposed method not only enables easier acquisition of controller parameters but also eliminates tedious trial-and-error tuning, thereby streamlining practical engineering im-plementation. Finally, the stability of the system is proved by the Lyapunov function, and the feasibility and effec-tiveness of the Super-Twisting sliding mode control algorithm based on the single drive twin rotor actuator system are verified by the simulation experiments.

Damage to transformer windings caused by external short circuits is usually not only related to a single short-circuit process, but also to gradual deformation of windings caused by successive short-circuit impacts to generate irreversible cumulative deformation and reduce their anti-short-circuit ability. Here, firstly, a 110.0 kV transformer was remade to conduct multiple short-circuit impulse tests. Cumulative effect of short-circuit impacts on mechanical state damage of windings was verified by measuring changes of reactance and axial pressure of windings. Then, effects of cumulative effect on vibration characteristics of windings were revealed through time domain and frequency domain analyses of vibration signals on surface of fuel tank and axial impact force of windings. Wigner-Ville distribution method was used to process vibration signals, construct time-frequency matrix for realizing feature extraction, and calculate the membership degree of winding mechanical state based on fuzzy C-means clustering algorithm, a method for quantifying the cumulative effect of winding deformation was proposed, and the criterion for severe winding deformation was determined. According to the experimental results, it can be seen that the variation law of vibration characteristic parameters is highly consistent with the change rate of reactance and axial pressure. The study results can be applied in mechanical state assessment and early fault warning of windings, and provide important engineering reference value for safe and stable operation of transformers.

The MS 6.2 Jishishan earthquake, which occurred near Qinghai Province, caused significant seismic damage to buildings in many counties, affecting rural buildings in particular. The results indicate that rural buildings with wooden and brick (or earth)-wood structures experienced greater damage compare with those with masonry and reinforced concrete (RC) frame structures. In wooden structures, the cooperative deformation between wooden frames and rammed earth walls or brick walls is poor. The pressure from the walls can easily cause splitting, pull-out-tenoning, and even complete de-tenoning at the mortise and tenon joints of the wooden frames. In some brick (or earth)-wood structures, the connection between the wooden roofs and the load-bearing walls is inadequate, posing the risk of roof displacement and collapse. A small number of brick-concrete and RC frame structures also suffered significant earthquake damage due to inadequate design and poor construction quality. Additionally, the site selection for rural buildings requires careful consideration to avoid the impact of potential secondary disasters. Based on this investigation and historical seismic data, several recommendations were put forward regarding standard formulation, structural system optimization, construction quality improvement, non-structural element enhancement, and location selection. These suggestions aim to guide the seismic design and repair of rural buildings in the Qinghai earthquake region and beyond. 

As a key space structure in geostationary orbit, large ring-column antenna satellite is tasked with providing high-speed information transmission and stable communication service in this orbit. This requires satellites having precise orbit maintenance and attitude control capabilities. Due to such satellites typically having larger masses and special structural designs, here, the high-precision orbit prediction algorithm was used to finely model and analyze effects of key space environmental factors of non-spherical perturbations, solar pressure and 3-body perturbation on space operation of such satellites. Furthermore, referring to the design concept of formation-flying gravity field measurement satellites, a distributed full thrust control strategy based on thruster layout optimization for such satellites was proposed. Then, an improved explicit model predictive control algorithm was proposed based on Laguerre function to convert device capability limitations and performance requirements into input-output constraints, combine multi-parameter quadratic programming, and realize attitude-orbit integrated control of large ring-column antenna satellites. The simulation results showed that during stable operation, position maintenance errors of such satellites can be controlled within a meter-level range, and attitude angle errors are better than 0.03°; the computational efficiency of the proposed control algorithm is significantly higher than that of the standard model predictive control algorithm and Laguerre function-based model predictive control algorithm; the hardware memory occupied is much lower than that of the explicit model predictive control algorithm. Through theoretical analysis and numerical verification, it was shown that this study can provide an effective solving scheme for full thruster integrated control of large ring-column antenna satellites in complex space environment using onboard computers with limited computing power.

In construction process of power grid, it is inevitable to pass through heavy icing areas. Surveys of icing in high-altitude areas showed that icing thickness on transmission lines varies with altitude to cause non-uniform icing along transmission lines. Moreover, de-icing of transmission lines under changes of external forces or environment is usually uneven. Here, non-uniform icing coefficient was defined according to non-uniform icing characteristics of high-altitude and high-altitude difference transmission lines. A finite element software was used to build a transmission line de-icing jump analysis model, dynamic characteristics of non-uniform and uniform icing conductors under different uneven de-icing modes were calculated to explore effects of icing mode, de-icing mode, conductor span and altitude difference on ice jumping height, conductor tension, tower unbalanced tension and ice jumping position of continuous transmission lines, and the simulation model was verified with real tests. The results showed that de-icing dynamic response of conductor under non-uniform icing condition is slightly elevated compared to that under uniform icing condition, effects of different de-icing modes on conductor’s maximum jump height positions are significant, which are generally located at 049-069 times conductor span; however, one entire span conductor de-icing is still the de-icing mode with the maximum ice jumping height, and the maximum ice jump height position is mainly concentrated at midpoint of de-icing span conductor; maximum tension of conductor under all operating conditions does not exceed its initial static tension; impact coefficient of tension during entire span conductor de-icing is 070, tension in chain type conductor de-icing process exhibits a monotonic decay with impact coefficient of 1.03; longitudinal unbalanced tension in deicing process is much higher than that in static state with impact coefficient of 146-175. The study results can provide important reference for designing transmission lines and formulating de-icing schemes.

Explosive stress wave propagating in the rock cavity will occur scattering and dynamic stress concentration, which will affect the blasting effect. In order to investigate the dynamic response of the rock cavity surface under the effect of blast load, based on the explosion dynamics theory, the theoretical solution of the dynamic stress field on the surface of the rock cavity is obtained, and the effects of the radius of the cavity, the spacing between the blast source and the cavity, and the frequency of the incident wave on the distribution of the dynamic stress around the rock cavity are investigated. The results show that the dynamic stress factor δθθ and δϕϕ are symmetric about the XOY plane at the boundary of the cavity in the explosion stress field, and their maximum values are biased toward the explosion source. The dynamic stress factor δθθ curve is “petal-like”, and δθθ reaches the maximum value of 2.62 at θ=±72.19°, while the dynamic stress factor δϕϕ curve is “gourd-like”, and its maximum value occurs at θ=180°. The dynamic stress factor peak 2, peak 5 and peak 3 increase with the increase of the radius of the cavity, and the peak 1 and peak 4 gradually decrease. With the increase of R0, the peak 2, peak 5 and peak 3 show a gradual decrease trend, and gradually tend to be stabilized after R0>12m. The dynamic stress factor peak 1 and peak 3 show a gradual decrease trend, and gradually tend to be stabilized after R0>12m. The dynamic stress factor peak 1 and peak 4 increase first and then decrease with the increase in incident wave frequency, while the peak values 2, 3 and 5 continue to increase. The research results can provide a theoretical basis for the optimal design of engineering blasting parameters.

The dominant flutter mode of long-span suspension bridges varies with the erection stage of the main girder.This study investigates the mode transition during construction and its impact on aeroelastic stability.A 2 300 m-span suspension bridge with a closed-box girder was analyzed through free and forced vibration wind tunnel tests on segmental models at different erection stages.Critical flutter wind speeds and flutter derivatives were obtained.A double-mode coupled analytical method was employed to evaluate flutter performance throughout the erection process.The results indicate that before 58% of the main girder is erected, flutter is governed by symmetric mode combinations.During the transition stage from 58% to 66% erection, the dominant flutter modes gradually shift from symmetric to antisymmetric combinations.After 66% erection, flutter is controlled by antisymmetric mode combinations.The transition is caused by a rapid decline in aerodynamic damping of the antisymmetric mode.At the transition, the phase difference of antisymmetric motion drops sharply, vertical motion lags behind torsion, torsional energy contribution decreases, mode coupling intensifies, and aerodynamic energy dissipation increases.

In structural strength design of ships, water entry slamming load receives great attention. Here, using computational fluid dynamics-finite element method (CFD-FEM) bidirectional coupling numerical method, the fluid-structure interaction problem of an elastic wedge  under gravity entering water in different flow field environments was studied. Firstly, taking wedge slamming in still water as an example, simulation results were compared with experimental ones to verify the correctness of CFD-FEM. Then, slamming loads, structural responses and flow field changes of elastic wedges with different water entry velocities and bottom oblique angles were analyzed when entering water in different flow field environments of still water, flow and waves. The results showed that water entry slamming of wedge  in still water is consistent with experimental results of model, so the numerical simulation has the reliability and feasibility;under action of uniform flow, when a wedge  enters water, due to wall reflection of structure to incoming flow, the flow velocity near wedge  is different from that far away from incoming flow to generate a pressure difference,  bottom of wedge  shifts to direction of incoming flow;when entering water at different wave positions, model equilibrium position is in direction of wave velocity, as the relative slamming velocity between wave and wedge  increases, the generated slamming load is larger than that in still water, high stress zone is mainly concentrated at wedge  bottom and weld position;the study results can provide a guidance for ship structure design and water entry slamming study.

The stiffened plate structures are widely used in engineering applications, and the rational layout of the stiffeners can effectively enhance the stiffness and load-bearing capacity of these structures. In order to achieve optimal stiffener layout design for thin plate structures, a new dynamic topology optimization method tailored for multi-phase material stiffened structures is proposed. Firstly, the stiffeners and thin plate are respectively considered as strong and weak materials and characterized by different bending stiffness, with use of equivalent stiffness method; Next, the Hilber-Hughes-Taylor-α (HHT-α) method is employed to solve the dynamic finite element model, and dynamic sensitivity analysis is conducted using the adjoint variable method with the discretize-then-differentiate approach; Furthermore, the effectiveness of the dynamic topology optimization method for stiffened plate structures is validated through a comparison of stiffener distribution topology optimization examples of a corner simply supported square plate with traditional methods. Finally, the stiffener topology optimization design is carried out for several typical thin plate structures using both single-phase and bi-phase materials under various loading and boundary conditions. The results show that the proposed dynamic topology optimization method for stiffened plate structures demonstrates flexible and effective optimization capabilities under dynamic conditions. By introducing bi-phase materials, the issues related to continuity distribution in single-phase materials are successfully overcome through reasonable material distribution and refined structural design. The optimized stiffener structure is continuous with complete force transmission paths, and significantly outperforms traditional methods.

Fault diagnosis models optimized through deep transfer learning have proven effective in addressing civil aircraft fault diagnosis tasks under variable working conditions, ensuring component reliability in in complex operational environments. However, the scarcity of high-confidence fault samples, particularly under varying conditions, due to the stringent safety requirements in civil aviation hinders the model's inference capabilities and increases the risk of overfitting. To overcome these challenges, we propose a Condition Diffusion-based Fault Diagnosis (CDFD) algorithm. The algorithm integrates a denoising diffusion model to conditionally generate high-confidence fault samples, thereby alleviating overfitting caused by sample scarcity. Unlike traditional diffusion methods that focus solely on sample distribution inference, the CDFD algorithm couples fault sample generation with decision-making optimization,  ensuring the quality of generated samples and significantly enhancing the diagnostic model’s generalization. Experimental validation on both simulated and real-world fault data demonstrates the efficiency of the proposed algorithm in handling real civil aircraft fault diagnosis tasks.

In the dynamic load test of bridges, environmental noise interference leads to the distortion of bridge vibration signals, which affects the accuracy of bridge structural condition assessment. To address this issue, this paper proposes a hybrid denoising method that combines hippopotamus optimization algorithm (HOA), variational mode decomposition (VMD) and singular spectrum analysis (SSA). The HOA is used to optimize the key parameters of the VMD, and then the VMD decomposes the original signal into multiple intrinsic modal functions (IMFs). By calculating the correlation coefficient between each IMF and the original signal, the IMFs below the threshold are removed. Finally, SSA is introduced for secondary denoising, and the principal components are screened by the cumulative contribution rate of singular values after the singular value decomposition to eliminate the low-frequency oscillating noise components in the signal. The simulation results show that compared with other methods, the root mean square error (RMSE) and signal-to-noise ratio (SNR) of the signal processed by this paper's method are improved by 16.22% and 2.51%, respectively, at different noise levels. The engineering application results show that compared with other methods, the normalized Shannon entropy ratio (NSER) and noise suppression ratio (NSR) of the denoised signals of this paper's method are improved by 12.81% and 8.44%, respectively, which is of practical significance for denoising of signals of the bridge dynamic loading test.

The health monitoring of bridge structures is crucial in ensuring traffic safety, extending service life, and improving operational and maintenance efficiency. However, the existing bridge monitoring methods still require improvements in measurement performance, cost, and efficiency. To address this, research is conducted on the application of a novel non-contact microwave full-field vibration measurement method for lightweight bridge monitoring. The hardware architecture of the microwave full-field vibration measurement system is outlined, along with the sensing principles of full-field multi-target recognition and vibration displacement extraction. Leveraging the advantages of microwave full-field vibration measurement, a lightweight bridge monitoring method is established from three aspects: equipment, sensing, and data. A microwave-based measurement technique for multi-span deflection and multi-cable tension in the full field of the bridge is proposed. A linear slide vibration measurement experiment was conducted under different conditions to verify the effectiveness of microwave full-field vibration measurement in suppressing multi-target coupling interference compared to traditional microwave vibration measurement technology. An outdoor dynamic response test was carried out on a tied-arch bridge, where multi-point deflection changes and cable force distribution of the bridge were measured and analyzed. The results demonstrate that the proposed method can efficiently and accurately measure bridge deflections and cable forces, providing a new technical approach and perspective for lightweight bridge health monitoring. A comparative experiment was conducted between the microwave vibrometer and traditional accelerometer for measuring cable fundamental frequencies, further validating the accuracy of the proposed method.

The micro-vibration induced by the rotating components on the satellite is one of the key aspects that affect the working precision of the optical payload.The vibration isolation mechanism installed between the satellite platform and the optical payload can effectively suppress the transmission of micro-vibration to the payload.Based on the stable spherical pair-prismatic pair-revolute pair(3-SPR)parallel mechanism, along with diaphragm springs, eddy current dampers and piezoelectric actuators, an active vibration isolation platform for optical payload were explored and analysed.The dynamic modeling and analysis of the 3-SPR parallel mechanism were conducted and the kinematic features of its corresponding degrees of freedom were discussed in detail.The closed-loop control algorithm based on the acceleration and angular displacement measurements was further introduced.The rigid-flexible coupling dynamic model of this mechanism was established to provide the transmission function and to evaluate the passive and active vibration isolation performances of this parallel platform.The ground experiment verifies that the platform possesses desirable vibration isolation abilities, which achieves over 42% disturbance isolation, and paves the way for the future on-orbit applications.

The variable gap magnetorheological variable energy absorber, which adopts a flow channel structure with a gradually decreasing gap, is a structural compensation idea that relies on the decrease in the velocity of the magnetic fluid gel due to the attenuation of the buffering force. However, the compensation effect of the variable gap flow channel structure is limited by the accuracy of the mechanical model in predicting the dynamic behaviour of the buffer. Therefore, constructing an accurate dynamic model is a key factor in compensating for the attenuation of the buffering force in the variable gap flow channel structure. To this end, the differential thinking is used to analyse the damping force of the variable gap flow channel, and a dynamic model that considers local losses, inertial effects, and their combined action is constructed. This model is used to compare and analyse the accuracy of various model predictions. By using differential thinking, the variable gap flow channel is divided into several microelements, and the Herschel-Bulkley (HB) model is used to obtain the flow channel damping force. Considering local losses, the HB-Minor Losses (HBM) dynamic model is constructed. By considering the inertial effect, the differential thinking is used to convert the damping force produced by the inertial effect into the sum of the damping forces of N microelements along the axial direction, and the HB-Inertia Losses (HBI) model is established. By comprehensively considering the effects of both inertial effect and local loss, a model that contains both inertial effect and local loss, called HB-Minor-Inertia Losses (HBMI), is constructed. To verify the accuracy of the theoretical model, a prototype of the variable gap magnetic fluid buffer was produced, and dynamic performance tests of the buffer under different impact conditions were carried out. The results showed that the buffer has good controllability. When compared with the experimental results, the peak force maximum relative error of the HB, HBM, HBI and HBMI models are 17.7%,11.1%,15.8% and 1.2% respectively, and the dynamic range relative error are 7.4%, 1.7%, 7.2%, and 1.0% respectively, indicating that the HBMI model predicts the dynamic behaviour of the variable gap magnetic fluid buffer with the highest accuracy.

Aeroengine data exhibits complex characteristics such as multivariate, nonlinear, and dynamic variations, with significant spatiotemporal correlations. The majority of research, when analyzing data, often limits itself to a single multi-sensor scale or temporal scale, and frequently neglects the long-term dependencies among the data, thereby constraining its application in the task of predicting the remaining useful life (RUL) of aircraft engines.. To address this, a spatio-temporal fusion Transformer network model is proposed. This model retains the advantages of the multi-head attention mechanism and positional encoding in the Transformer architecture to accurately capture long-term dependency features. Firstly, an efficient fully connected network is adopted to replace the original decoding module, matching the attributes of the nonlinear regression problem in aeroengine RUL prediction while simplifying the model structure. Secondly, a spatial attention mechanism module is introduced to deeply explore the spatial features among different variables. Finally, the improved AIC criterion is applied to identify critical hyperparameters of the Transformer, addressing the challenge of selecting its hyperparameters. Multiple sets of experiments conducted on the C-MAPSS and PHM08 Prognostics Data Challenge have confirmed the effectiveness of the proposed model and its superior performance in prediction accuracy.

In this study, large eddy simulation and FW-H acoustic analogy method were used to study the characteristics associated with cavitation flow field and sound field of organ pipe nozzles, focusing on evaluating the cavitation effect and the impact of cleaning noise on the cultivation of large yellow croaker.It is found that the turbulent boundary layer at the throat of the organ pipe nozzle is more obvious owing to the influence of the natural vibration effect which is conducive to the formation of cavitation groups, the average volume of cavitation produced by its work can reach 1.8 times when compared with that related to traditional convergent-divergent nozzles. In the external flow field, the narrower the jet trajectory outside the nozzle is, the more concentrated the cavitation cloud distribution will be. Its cavitation performance is better than that of the convergent-divergent nozzle in the near flow field area of 10 times the diameter of the pipe. The research results of cavitation sound field show.The self-oscillating organ pipe nozzle has no obvious peak noise in the sound sensitive band of large yellow croaker.Its working noise is mainly high frequency noise above 2000Hz.and presents a "maple leaf"-like directional distribution in the downstream plane. Considering the hearing curve of large yellow croakers, the total sound pressure level of the far-field monitoring point of the weighted organ pipe nozzle is more than 10 dB lower than that of the convergent-divergent nozzle, and its influence range on large yellow croakers remains within a radius of less than 0.7 m, suitable for the low-noise cleaning operations of cages for large yellow croakers in deep water culture.

The Fast Iterative Shrinkage Threshold algorithm based on Fast Fourier transform (FFT-FISTA) has high computational efficiency, as it ignores the spatial variation of the point spread function and the winding error, resulting in the loss of sound source recognition performance. The improved algorithm takes the output of function beamforming as the iterative input of FFT-FISTA algorithm, establishes a linear equation system of function beamforming, sound source distribution and rising power spatial transfer invariant point spread function, and solves it iteratively based on the fast Fourier transform under the periodic boundary condition. The calculated non-periodic function is changed into a periodic function, which solves the problem of wavenumber leakage caused by the zero-filling boundary, which can improve the accuracy of the operation and further improve the imaging performance. The main lobe of the point spread function is sharpened by exponential operation, and the applicability of the assumption of spatial transfer invariance of the point spread function is expanded. The simulation and experimental results show that, compared with the conventional FFT-FISTA algorithm, the improved algorithm can improve the spatial resolution and dynamic range of the imaging, and expand the effective imaging area of the FFT-FISTA algorithm, and the experimental results of compressed gas leakage verify the effectiveness of the improved algorithm. 

Near-fault ground motions often exhibit distinct velocity pulse characteristics, which pose significant threats to arch bridges, particularly due to their pronounced spatial vibration response under seismic loading. To better understand the impact of near-fault ground motions on the seismic response of arch bridges, this study proposes a novel analytical approach called Seismic Meta-analysis (SMa). SMa is a secondary quantitative analysis method based on existing research data, offering a new pathway for seismic studies.This paper comprehensively outlines the SMa methodology, covering key aspects such as defining the analysis theme, collecting and classifying research data, constructing the analytical framework, applying quantitative theories, selecting metrics, and interpreting results. Using SMa, a comparative study is conducted to evaluate the effects of near-fault and non-near-fault ground motions on the seismic response of arch bridges. This analysis focuses on three dimensions: response differences, the extent of these differences, and the influence of specific factors. A total of 2,137 valid data sets from 98 studies were collected and analyzed to validate the feasibility of the SMa method, highlighting the distinctive effects of the two types of ground motions on the seismic response of arch bridges.The study reveals the following key findings: 1) SMa provides a fresh perspective for secondary analysis, free from the limitations of existing conclusions. It allows for the formulation of new research themes and offers supplementary insights to address gaps in current studies; 2) In the range of ground motion intensities between 0 and 0.6g, the differences in the seismic response of the main arch under near-fault and non-near-fault ground motions increase with intensity. However, these differences significantly decrease when the intensity exceeds 0.8g; 3) Near-fault ground motions have a more pronounced adverse effect on the displacement response and transverse seismic behavior of arch bridges; 4) Forward-directivity near-fault ground motions pose the greatest threat to arch bridges. Moreover, the impact of near-fault ground motions on transverse displacement shows a significant positive correlation with span length. Additionally, the study highlights the need for further investigation into the influence of factors such as bridge type, service life, and initial bridge conditions. Research on targeted seismic isolation and mitigation strategies for near-fault ground motions remains insufficient. This work represents the first application of Meta-analysis in the field of bridge seismic design and civil engineering, demonstrating broad practical value. 

In order to realize the intelligent multi-component fault diagnosis of bearings, rotors and gears in a mechanical transmission system under low speed, weak faults and few measurement points, a fault diagnosis method based on improved vibration-mapped gray texture images (GTIs) and multi-scale lightweight convolutional neural network is proposed. An improved gray texture image with enhanced features is obtained by robust local binary pattern (RLBP) on the traditional gray image. Based on the standard convolutional neural network (CNN), a multi-scale lightweight CNN (MSLCNN) model is constructed by adding batch normalization, multi-scale convolution and simplified full connection layer. The fault diagnosis experiment under 700r/min and a single measurement point is designed, and seven typical faults of bearings, rotors and gears are simulated. The investigation shows that the model parameters of the proposed fault diagnosis method are 0.30M, the floating point operations (FLOPs) are 127.22M, the model size is 1.17MB, and the average diagnostic accuracy is 98.42%. It provides a new feasible path for the data-driven multi-component fault diagnosis of the mechanical transmission system based on the deep learning.

Killing and detonation warhead has been widely used in many kinds of air defense and anti-missile weapon systems. This kind of warhead mainly realizes efficient destruction of incoming missile target through explosion shock wave and fragments. To investigate the coupled destruction capability of the explosive shock wave and fragments damage on the target under different explosion scenarios, cylindrical shell is selected as the effect target, a computational method that can classify the different explosion action fields is proposed based on the velocity change equations of the explosive shock wave and fragments, the LBE (LOAD_BLAST_ENHANCED) method is introduced to realize the effective simulation of the coupled damage condition on the cylindrical target under the synergistic effect of the explosive shock wave and fragments. The results show that: the material strength of the target is the main factor affecting the damage effectiveness, increase the strength of the target is a key factor in enhancing the ability of their own protection. In the premise of the initial explosion parameters are the same, the damage efficiency of explosion-related action is the highest, about 1.06~5.26 times that of shock wave alone, and the damage efficiency of combined action is about 1.06~1.44 times that of shock wave alone. 

To investigate the impact of underfilled grouting defects on the seismic performance of prefabricated bridge piers, produced three groups of grouting sleeve connectors specimens and carry out pull-out tests. According to the tests results, cast-in-place single-column pier, fully grouted assembled single-column pier and assembled single-column pier with grouting defect were designed as specimens and the pseudo-static tests were carried out. In addition, verified finite element pier models were established, and an extended parametric analysis was conducted regarding the length, location and quantity of the grouting defects. The results showed that: when the length of grouting defects in grouted sleeve connections exceeds 2.5 times the diameter of the reinforcement, the damage mode will change; the use of grouted sleeve connections will reduce the ultimate bearing capacity of the abutment specimens by 6.8%, and grouting defects will reduce the unloaded stiffness of the structure. In order to make the existence of grouting defects of the bridge pier still have sufficient seismic performance, should ensure that the grouting defects of the length of less than 2 times the diameter of the rebar, grouting defects in the number of sockets accounted for less than 40% of the defects do not appear in the middle of the assembly end and the end of the defects, this time, assembly of a single-column pier of cumulative hysteresis dissipation of the reduction in the amount of energy can be less than 10%.

Multi-objective Crashworthiness Optimization of Novel Functionally-graded Variable Section Double-hexagonal Crash Box
Abstract: In order to synergistically improve the crashworthiness safety and lightweight level of the car body, a novel functionally-graded variable section double-hexagonal crash box was designed and proposed. The substructure at its lower end with regular shape, namely functionally-graded variable section double-hexagonal tube (FS-DHT), was extracted as research subject, on which parametric geometric modeling was conducted. The finite element model of FS-DHT under axial crushing was established and verified by experiments. A comparative study concerning crashworthiness and energy absorption characteristics under axial crushing was conducted among FS-DHT, traditional straight DHT (S-DHT) and conical DHT (C-DHT). The influence of the tube wall thickness, the circumcircle radius differences at upper and lower end face of inner and outer hexagonal tubes, and the gradient exponent on the crashworthiness and energy absorption characteristics of FS-DHT under axial crushing was explored. A multi-objective optimization was carried out on FS-DHT by combining the Optimal Latin Hypercube Sampling, response surface surrogate model and NSGA-II algorithm, then verified. The finite element model of “bumper-crash box” assembly under axial crushingwas further established to verify the improvement effect of FS-DHT optimization on the crashworthiness of functionally-graded variable section double-hexagonal crash box. The results show that after optimization of FS-DHT, its specific energy absorption (SEA) increases by 17.69% while its initial peak crushing force (IPCF) decreases by 10%, which meanwhile promotes the energy absorption (EA) of functionally-graded variable section double-hexagonal crash box to increase by 22.25% and the corresponding IPCF at the bumper to decrease by 9.14%, indicating a good multi-objective collaborative crashworthiness optimization is obtained.An effective novel structure and new approach are provided for synergistically improving the crashworthiness and lightweight level of the vehicle body

This paper establishes a simplified model of the bladeless wind turbine and derives the formula for its power generation efficiency. Numerical simulations were conducted using computational fluid dynamics software Fluent and user-defined functions (UDF), studying the vortex-induced vibration characteristics and power generation efficiency of single and dual degree-of-freedom bladeless wind turbines under different reduced wind speeds. The study shows that the difference in the degrees of freedom of the wind turbine significantly affects its vibration response, aerodynamic characteristics, and power generation efficiency. The vibration amplitude initially increases and then decreases as the reduced wind speed increases, remaining stable in certain wind speed ranges. The vibration trajectory of the dual degree-of-freedom wind turbine at reduced wind speeds primarily forms a figure-eight pattern, exhibiting multi-frequency vibrations when the wind speed approaches the natural frequency, with the trajectory becoming chaotic. The power generation efficiency follows a trend of increasing first and then decreasing with the reduced wind speed, with the efficiency of the dual degree-of-freedom wind turbine being higher than that of the single degree-of-freedom wind turbine. At a reduced wind speed of Ur = 2.4, the maximum power generation efficiency of the single degree-of-freedom wind turbine is 25.19%; at Ur = 3.4, the maximum power generation efficiency of the dual degree-of-freedom wind turbine is 57.14%. Power generation efficiency is influenced by the combined effects of incoming wind speed, vibration velocity, and lift-drag coefficients. With changes in degrees of freedom and reduced wind speeds, the wake vortex shedding patterns of the wind turbine also vary. The vortex shedding patterns of the three-dimensional bladeless wind turbine at different heights in the span direction are similar to those of the two-dimensional wind turbine, but due to smaller vortices in the surrounding flow field, the energy loss is higher, leading to a slightly lower power generation efficiency compared to the two-dimensional bladeless wind turbine.

To investigate the vibration mechanism of the swash plate axial piston pump, a finite element model of the piston pump distributor oil film iwas established, and the model is was verified to be highly accurate through by the test. The influence of working condition parameters such as load pressure at the discharge port, cylinder rotational speed, and swash plate inclination angle on the pressure, temperature, positive pressure, and cavitation characteristics of the distributor oil film is was analyzed by using the equidistant test method. The results show that: with the increase of load pressure at the discharge port, cylinder rotational speed, and swashplate inclination angle, thearea of the local high-pressure and high-temperature areas of the flow-distributing sub-film increases, the positive pressure of the film increases, the degree of cavitation increases, and the peak gas-phase volume fraction of the oil film increases from 5.61% to 6.32% and from 2.24% to 3.94%, respectively, at the stage of the transition between suction area and discharge area, 5.61% to 6.37%, respectively, all of which will exacerbate the vibration phenomenon of swash plate axial piston pumps; With the increase of suction port pressure, the degree of oil film cavitation decreases, and the peak oil film gas-phase volume fraction decreases from 2.99% to 1.51%, and there is an optimal interval for the values of each operating condition parameter in the actual design of the piston pump.

Under the action of complex environmental loads, performance degradation of space grid structures is severe to cause sharp increase in risks of their safe service life.Here, mechanical response laws of grid structures under different design parameters were explored to perform probabilistic safety assessment of structures based on reliability.A 2D orthogonal flat plate space grid structure model was established using the software ABAQUS, and its stress and displacement changes under different height-span ratios, column spacings and corrosion rates were studied.Through simulation, it was shown that with increase in height-span ratio, the maximum tensile stress and displacement gradually decrease but their drop rates are gradually smaller, while the maximum compressive stress firstly decreases and then slightly increases; if height of space grid structure increases from 3.5 m to 6.3 m, the maximum displacement decreases by 53.66%; increase in column spacing causes the maximum stress and displacement increase, but their growth rates are gradually smaller; under grid space structure height of 3.5 m, column spacing increases from 4.5 m to 13.5 m, the maximum displacement increases by 22.63%; increase in corrosion rate causes slow increase in maximum stress and displacement, and effects of corrosion on structural stress is a gradual accumulation process, which does not suddenly cause a sharp drop of structural performance.Furthermore, Latin hypercube sampling method was used to evaluate the probability of structural failure under effects of multidimensional uncertain parameters, taking the allowable deflection specified in “Technical Specifications for Space Grid Structures” as the evaluation criterion.The results showed that under H1L2 working condition of 3.5 m structure height and 9.0 m column spacing, the failure probability without corrosion is 0.27%; when corrosion rate is 40.00%, the failure probability increases to 22.76%.