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In recent years, the increasing frequency of climate change and extreme weather events has significantly elevated the risk of levee breaches, potentially triggering large-scale floods that threaten surrounding environments and public safety. Rapid and accurate measurement of river surface velocities is crucial for developing effective emergency response plans. Video image velocimetry has emerged as a powerful new approach due to its non-invasive nature, ease of operation, and low cost. This paper introduces the Dynamic Feature Point Pyramid Lucas–Kanade (DFP-P-LK) optical flow algorithm, which employs a feature point dynamic update fusion strategy. The algorithm ensures accurate feature point extraction and reliable tracking through feature point fusion detection and dynamic update mechanisms, enhancing the robustness of optical flow estimation. Based on the DFP-P-LK, we propose a river surface velocity measurement model for rapid levee breach emergency response. This model converts acquired optical flow motion to actual flow velocities using an optical flow-velocity conversion model, providing critical data support for levee breach emergency response. Experimental results show that the method achieves an average measurement error below 15% within the velocity range of 0.43 m/s to 2.06 m/s, demonstrating high practical value and reliability.

To address the challenges of sinking, imbalance, and complex control systems faced by hexapod robots walking on lunar soil, this study develops an umbrella-shaped foot lunar exploration hexapod robot. The overall structure of the robot is designed to mimic the body structure of insects. By incorporating a four-bar linkage mechanism to replace the commonly used naked joints in traditional hexapod robots, the robot reduces the number of degrees of freedom and simplifies control complexity. Additionally, an extension mechanism is added to the robot’s foot, unfolding into an umbrella shape to provide a larger support area, effectively addressing the issue of foot sinking instability during walking. This study adopts and simplifies the Central Pattern Generator (CPG) model to generate stable periodic control signals for the robot’s legs. Precise control of the extension mechanism’s unfolding period is achieved through mapping functions. A joint simulation platform using Solid Works and Matlab is established to analyze the stability of the robot’s walking. Finally, walking experiments are conducted on the prototype, confirming the smooth walking of the lunar exploration hexapod robot. The results indicate that the designed lunar exploration hexapod robot has a reasonable structure, excellent stability in motion, and the CPG control scheme is feasible.

As a typical intelligent device, magnetorheological (MR) dampers have been widely applied in vibration control and mitigation. However, the inherent hysteresis characteristics of magnetic materials can cause significant time delays and fluctuations, affecting the controllability and damping performance of MR dampers. Most existing mathematical models have not considered the adverse effects of magnetic hysteresis characteristics, and this study aims to consider such effects in MR damper models. Based on the magnetic circuit analysis of MR dampers, the Jiles–Atherton (J-A) model is adopted to characterize the magnetic hysteresis properties. Then, a weight adaptive particle swarm optimization algorithm (PSO) is introduced to the J-A model for efficient parameter identifications of this model, in which the differential evolution and the Cauchy variation are combined to improve the diversity of the population and the ability to jump out of the local optimal solution. The results obtained from the improved J-A model are compared with the experimental data under different working conditions, and it shows that the proposed J-A model can accurately predict the damping performance of MR dampers with magnetic hysteresis characteristics.

To address the challenges posed by the loose lunar surface structure, including the adhesive nature of lunar soil, strong corrosiveness and the slow walking speed of robots using traditional tripod gaits, this paper proposes the design of a small lunar exploration hexapod robot with hollow legs, employing anti-corrosive aerospace materials throughout. Additionally, an inverted gait motion mode is introduced. Simulation analysis is conducted on the displacement, angular velocity, angular acceleration and joint torque of the robot’s body under both traditional tripod gaits and the “inverted gait” motion mode. A physical prototype of the robot is developed to validate the rationality of its structure. Our research results indicate that the designed lunar exploration hexapod robot’s body structure is reasonable, enabling it to stand and walk normally on the unstructured lunar terrain. The hollow design reduces the adhesion of lunar soil. The inverted gait motion mode expands the effective swinging range of the robot’s legs and increases the effective step length during leg swing. Additionally, it improves the robot’s movement speed, eliminates vibrations at the joints during motion and improves the robot’s stability during the support phase.

Carrier phase measurements currently play a crucial role in achieving rapid and highly accurate positioning of global navigation satellite systems (GNSS). Resolving the integer ambiguity correctly is one of the key steps in this process. To address the inefficiency and slow search problem during ambiguity solving, we propose a single-frequency GNSS integer ambiguity solving based on an adaptive genetic particle swarm optimization (AGPSO) algorithm. Initially, we solve for the floating-point solution and its corresponding covariance matrix using the carrier-phase double difference equation. Subsequently, we decorrelate it using the inverse integer Cholesky algorithm. Furthermore, we introduce an improved fitness function to enhance convergence and search performance. Finally, we combine a particle swarm optimization algorithm with adaptive weights to conduct an integer ambiguity search, where each generation selectively undergoes half-random crossover and mutation operations to facilitate escaping local optima. Comparative studies against traditional algorithms and other intelligent algorithms demonstrate that the AGPSO algorithm exhibits faster convergence rates, improved stability in integer ambiguity search results, and in practical experiments the baseline accuracy of the solution is within 0.02 m, which has some application value in the practical situation of short baselines.

For the quadratic integration of seismic acceleration signal with noise and unknown initial velocity and displacement, the obtained displacement signal has serious trend error, which leads to the problem that the electrodynamic seismic simulation shaker under displacement control mode cannot accurately reproduce the seismic wave. This paper proposes the time-frequency hybrid integration algorithm based on time domain and frequency domain integration characteristics. The algorithm mainly includes two steps. The first step is to use the improved low-frequency attenuation algorithm to integrate the seismic acceleration for the first time in the frequency domain to obtain the corresponding velocity signal. The second step is to integrate the velocity signal directly in the time domain and combine it with the removal of the constant and linear terms algorithm to obtain the corresponding displacement signal. The accuracy and effectiveness of the algorithm are verified by numerical analysis and shaking table test. The results show that compared with the traditional hybrid integral algorithm, the performance improvement rates of displacement peak error and absolute error of the proposed time-frequency hybrid integral algorithm are 31.75% and 26.01%, respectively, and the accuracy of acceleration waveform reproduction is improved by 27.29%. Furthermore, when using this algorithm for the shaking table test of the seismic acceleration signal, the maximum peak error rate is only 4.92%. Therefore, this algorithm can effectively suppress the baseline drift and error accumulation caused by low-frequency noise and unknown initial state to realize the accurate reproduction of the acceleration waveform of the seismic simulation shaking table.

The low light conditions, abundant dust, and rocky terrain on the lunar surface pose challenges for scientific research. To effectively perceive the surrounding environment, lunar rovers are equipped with binocular cameras. In this paper, with the aim of accurately detect obstacles on the lunar surface under complex conditions, an Improved Semi-Global Matching (I-SGM) algorithm for the binocular cameras is proposed. The proposed method first carries out a cost calculation based on the improved Census transform and an adaptive window based on a connected component. Then, cost aggregation is performed using cross-based cost aggregation in the AD-Census algorithm and the initial disparity of the image is calculated via the Winner-Takes-All (WTA) strategy. Finally, disparity optimization is performed using left–right consistency detection and disparity padding. Utilizing standard test image pairs provided by the Middleburry website, the results of the test reveal that the algorithm can effectively improve the matching accuracy of the SGM algorithm, while reducing the running time of the program and enhancing noise immunity. Furthermore, when applying the I-SGM algorithm to the simulated lunar environment, the results show that the I-SGM algorithm is applicable in dim conditions on the lunar surface and can better help a lunar rover to detect obstacles during its travel.

Real-time hybrid testing (RTH) is a test method for dynamic loading performance evaluation of structures, which is divided into digital simulation and physical testing, but the integration of the two may lead to problems such as time lag, large errors, and slow response time. The electro-hydraulic servo displacement system, as the transmission system of the physical test structure, directly affects the operational performance of RTH. Improving the performance of the electro-hydraulic servo displacement control system has become the key to solving the problem of RTH. In this paper, the FF-PSO-PID algorithm is proposed to control the electro-hydraulic servo system in real-time hybrid testing (RTH), which uses the PSO algorithm to operate the optimized PID parameters and the feed-forward compensation algorithm to compensate the displacement. First, the mathematical model of the electro-hydraulic displacement servo system in RTH is presented and the actual parameters are determined. Then, the objective evaluation function of the PSO algorithm is proposed to optimize the PID parameters in the context of RTH operation, and a displacement feed-forward compensation algorithm is added for theoretical study. To verify the effectiveness of the method, joint simulations were performed in Matlab/Simulink to compare and test FF-PSO-PID, PSO-PID, and conventional PID (PID) under different input signals. The results show that the proposed FF-PSO-PID algorithm effectively improves the accuracy and response speed of the electro-hydraulic servo displacement system and solves the problems of RTH time lag, large error, and slow response.

Aiming at the problem of poor accuracy of acceleration waveform reproduction during the shaking table test of earthquake simulation, a hybrid integration algorithm based on seismic acceleration signal is proposed to control the trend term error. The low-frequency attenuation integral algorithm in the frequency domain is used to integrate the original seismic acceleration signal once to obtain the vibration velocity signal, then, the polynomial fitting integration algorithm is introduced to integrate of the vibration velocity signal once in the time domain to obtain the vibration displacement signal. Through these two integrals, the sensitivity of low frequency band during frequency domain integration and the accumulation of small errors in time domain are reduced. Finally, the hybrid integration algorithm is used to perform seismic wave reproduction experiments on the seismic simulation shaker and good results are obtained, which proves that the hybrid integration calculation has high practical value and practical significance in improving the accuracy of the vibration table waveform reproduction.

Viscoelastic dampers are conventional passive vibration control devices with excellent energy dissipation performance. The fractional derivative has a simple form and high accuracy in the modelling of viscoelastic materials/dampers. The internal variables reflect the internal state evolution of materials, and are often used to analyze the deformation and thermal process of materials. In the present work, the mechanical properties of a plate-shear-type viscoelastic damper at room temperature are tested under sinusoidal displacement excitations. The impacts of frequency and displacement amplitude on the dynamic properties of the viscoelastic damper in a wide frequency domain (0.1–25 Hz) are investigated. The higher-order fractional derivative model and the temperature–frequency equivalent principle are employed to characterize the frequency and temperature influence, and the internal variable theory considering the internal/microscale structure evolutions is introduced to capture the displacement affection. The higher-order fractional derivative model modified with the internal variable theory and temperature–frequency equivalent principle (ITHF) is accurate enough in describing the dynamic behaviors of viscoelastic dampers with varying frequencies and displacement amplitudes.

Aiming at the difficult problem of on-site real-time vibration responses monitoring and remote data transmission of the civil engineering structures, based on LabVIEW a remote data acquisition and transmission system is designed. In the system NI data acquisition card and DataSocket protocol of the LabVIEW software platform are used to realize data collection, remote transmission and control. That is, the civil engineering structural vibration responses can be monitored through internet at anytime and anywhere. The vibration parameters of a cantilever beam is detected and transmitted in real-time by using this system. The test parameter values are compared with the theoretical calculating value. The results show that relative to the traditional cable measurement and wireless short-range measurement, this system can effectively realize the remote real-time data acquisition, transmission, display, storage and control. Furthermore, the accuracy of data transmission is high. On the other hand, the system is easy to be built and maintained.

Eccentric structures will have torsional vibrations subjected to earthquakes, which can accelerate the damage of structures, and even become the main cause of building collapse. Semi-active control systems equipped with multiple magnetorheological (MR) dampers have been widely applied in structural vibration control. In this study, numerical models of spatial eccentric structures with multiple MR dampers were established, and time history analysis was conducted to mitigate torsional vibrations of eccentric structures. Firstly, a full-scale spatial eccentric structure model with both plan asymmetry and vertical irregularity was established in OpenSEES, and the accuracy of the structure model was verified by comparisons with model results from SAP2000. Then, the mathematical model of MR dampers was introduced to the structure model using the ‘Truss’ element and self-defined material in OpenSEES, and damping forces obtained from the MR damper model were compared with experimental data. Finally, modal analysis and nonlinear time history analysis of the eccentric structure model equipped with multiple MR dampers subjected to different seismic excitations were performed. Comparisons between the seismic responses of the uncontrolled structure and the structure with multiple MR dampers were carried out to demonstrate the effectiveness of the MR control system. Numerical results show that the control system with multiple MR dampers can significantly attenuate the torsional vibrations of eccentric structures, and thus possess significant engineering application prospects.

The identification of wildfires is a very complex task due to their different shapes, textures, and colours. Traditional image processing methods need to manually design feature extraction algorithms based on prior knowledge, and because fires at different stages have different characteristics, manually designed feature extraction algorithms often have insufficient generalization capabilities. A convolutional neural network (CNN) can automatically extract the deeper features of an image, avoiding the complexity and blindness of the feature extraction phase. Therefore, a wildfire identification method based on an improved two-channel CNN is proposed in this paper. Firstly, in order to solve the problem of the insufficient dataset, the dataset is processed by using PCA_Jittering, transfer learning is used to train the model and then the accuracy of the model is improved by using segmented training. Secondly, in order to achieve the effective coverage of the model for fire scenes of different sizes, a two-channel CNN based on feature fusion is designed, in which the fully connected layers are replaced by a support vector machine (SVM). Finally, in order to reduce the delay time of the model, Lasso_SVM is designed to replace the SVM in the original model. The results show that the method has the advantages of high accuracy and low latency. The accuracy of wildfire identification is 98.47% and the average delay time of fire identification is 0.051 s/frame. The wildfire identification method designed in this paper improves the accuracy of identifying wildfires and reduces the delay time in identifying them.

With the wide application of hydraulic servo technology in control systems, the requirement of hydraulic servo position control performance is greater and greater. In order to solve the problems of slow response, poor precision, and weak anti-interference ability in hydraulic servo position controls, a Kalman genetic optimization PID controller is designed. Firstly, aiming at the nonlinear problems such as internal leakage and oil compressibility in the hydraulic servo system, the mathematical model of the hydraulic servo system is established. By analyzing the working characteristics of the servo valve and hydraulic cylinder in the hydraulic servo system, the parameters in the mathematical model are determined. Secondly, a genetic algorithm is used to search the optimal proportional integral differential (PID) controller gain of the hydraulic servo system to realize the accurate control of valve-controlled hydraulic cylinder displacement in the hydraulic servo system. Under the positioning benchmark of step signal and sine wave signal, the PID algorithm and the genetic optimized PID algorithm are compared in the system simulation model established by Simulink. Finally, to solve the amplitude fluctuations caused by the GA optimized PID and reduce the influence of external disturbances, a Kalman filtering algorithm is added to the hydraulic servo system to reduce the amplitude fluctuations and the influence of external disturbances on the system. The simulation results show that the designed Kalman genetic optimization PID controller can be better applied to the position control of the hydraulic servo system. Compared with the traditional PID control algorithm, the PID algorithm optimized by genetic algorithm improves the system’s response speed and control accuracy; the Kalman filter is a good solution for the amplitude fluctuations caused by GA-optimized PID that reduces the influence of external disturbances on the hydraulic servo system.

The magnetorheological elastomer (MRE) is a kind of smart material, which is often processed as vibration isolation and mitigation devices to realize the vibration control of the controlled system. The key to the effective isolation of vibration and shock absorption is how to accurately and in real time determine the magnitude of the applied magnetic field according to the motion state of the controlled system. In this paper, an optimal fuzzy fractional-order PID (OFFO-PID) algorithm is proposed to realize the vibration isolation and mitigation control of the precision platform with MRE devices. In the algorithm, the particle swarm optimization algorithm is used to optimize initial values of the fractional-order PID controller, and the fuzzy algorithm is used to update parameters of the fractional-order PID controller in real time, and the fractional-order PID controller is used to produce the control currents of the MRE devices. Numerical analysis for a platform with the MRE device is carried out to validate the effectiveness of the algorithm. Results show that the OFFO-PID algorithm can effectively reduce the dynamic responses of the precision platform system. Also, compared with the fuzzy fractional-order PID algorithm and the traditional PID algorithm, the OFFO-PID algorithm is better.

The viscoelastic material is one of most popular shock absorbing materials for mitigating vibrations of building structures due to earthquake. Its dynamic performance is affected by the temperature, the excitation frequency and the excitation amplitude. Therefore, in order to study the non-linear dynamic performance of the viscoelastic materials, a hybrid test system using the electric exciter is proposed, in which the electric exciter is the actuator, MATLAB is used for the simulation of the numerical substructure and the communication between the upper computer and the lower machine, and STM32 single-chip microcomputer is used to control the work state of the electric exciter. Based on the equivalent force control method and the incremental PID control algorithm, a controller is designed to make sure the electric exciter produces accurate control forces to the non-linear test component in the physical substructure. It can be shown from the test results that the developed whole hybrid test system is feasible and effective.

The magnetorheological (MR) damping material is a kind of smart shock absorption material, and it can be made into MR dampers for reducing the vibration or dynamic response of structures. During the vibration mitigation control of structures with MR dampers, the displacement and acceleration responses are always concerned firstly because the displacement responses determine the safety of structures and, at the same time, the acceleration responses determine the comfort level of the human body staying in structures. That means, the control currents choice of MR dampers during the vibration process is a multi-objective optimization control problem. In this paper, the particle swarm optimization (PSO) algorithm is developed to control the displacement and acceleration responses simultaneously. Numerical analysis for a five-floor steel frame structure with one MR damper installed on each floor is carried out. Simulation results of the PSO control structure are compared with those of passive control (including the ON-control and the OFF-control) structures and the uncontrolled structure. Analysis results demonstrate that the PSO algorithm can reduce the displacement responses of the structure obviously and, at the same time, it can reduce the acceleration responses of the structure to a certain extent. Furthermore, the PSO algorithm reduces the seismic responses of structures more effectively than those of passive control structures.

This paper aims to develop viscoelastic dampers, which can effectively suppress vibration in a wide frequency range. First, several viscoelastic materials for damping performance were selected, and different batches of cylindrical viscoelastic dampers were fabricated by overall vulcanization. Second, the dynamic mechanical properties of the cylindrical viscoelastic dampers under different amplitudes and frequencies are tested, and the hysteretic curves under different loading conditions are obtained. Finally, by calculating the dynamic mechanical properties of the cylindrical viscoelastic dampers, the energy dissipation performance of these different batches of viscoelastic dampers is compared and analyzed. The experimental results show that the cylindrical viscoelastic damper presents a full hysteretic curve in a wide frequency range, in which the maximum loss factor can reach 0.57. Besides, the equivalent stiffness, storage modulus, loss factor, and energy consumption per cycle of the viscoelastic damper raise with the frequency increasing, while the equivalent damping decreases with the increase of frequency. When the displacement increases, the energy consumption per cycle of the viscoelastic damper rises rapidly, and the equivalent stiffness, equivalent damping, storage modulus, and loss factor change slightly.

The magnetorheological (MR) fluid is a typical smart material, whose shear yield stress can be adjusted through changing the strength of external magnetic field, and the changing process only takes a few milliseconds. The MR fluid is composed of micro/nanometer ferromagnetic particles, carrier fluids, and some additives. Among them, the performance of ferromagnetic particles will mainly affect the sedimentation stability and the magnetic saturation of the MR fluid. Therefore, the ferromagnetic particles are expected to have characteristics of both low density and high magnetism. In this paper, the multi-walled carbon nanotubes (MWNTs) were adopted to coat on the carbonyl iron (CI) particles with grafting technology using ultrasonication and mechanical stirring. The coated CI particles with perfect core-shell structure were developed and the influence of the dosages of grafting agent and MWNTs were tested. And then, MR fluids with CI particles coated with MWNTs were established and the coating effect was studied through surface topography particle density, and magnetic properties of composite magnetic particles and stability tests of the prepared MR fluids. The results showed that although the magnetic saturation of the prepared MR fluids with CI particles coated with MWNTs would reduce slightly, the particles density and the adsorption force between the particles were decreased effectively, which are both advantageous to the improvement of the sedimentation stability of MR fluids.

The slotting method is a nondestructive detection method based on the stress release principle to evaluate in-place stress in concrete. By measuring the change in strain of the slotting area using a strain gauge, the in-place stress within the concrete member can be calculated by elastic theory. This paper proposes a multi-step slotting method that combines experimental strain measurements with numerical simulation results. For concrete specimens under unidirectional stress, the effects of compressive stress, slotting spacing, slotting length, and slotting depth on the degree of stress release were analyzed using finite element analysis, and a normalized fitting equation was proposed that can be quickly and accurately applied in engineering detection. The excellent agreement between the experimental results and the numerical simulation (fitted equation) results shows that the slotting method can facilitate the accurate evaluation of the in-place stress in concrete, and the relative error can be reduced to less than 10% when it is calculated using the optimized multi-step experimental data. [ABSTRACT FROM AUTHOR]