The traditional force correction iterative hybrid test method uses a fixed model to correct the restoring force, and there is a problem that the model is not accurate enough to increase the number of iterations. Aiming at this problem, a force correction iterative hybrid test method based on adaptive model is proposed. This method uses the restoring force correction value of all rounds of iteration and the real restoring force of each iteration physical substructure to build an adaptive model for iterative restoring force correction, which improves the iterative convergence speed and iterative convergence accuracy. In this paper, the influence of different weight distribution coefficients and initial model parameters on the iterative convergence speed and convergence accuracy is analyzed by taking the single-layer frame viscous damper damping structure as an example. By verifying the structures with different natural vibration periods, the influence of the natural vibration period of the structure on the method is analyzed. The results show that different weight coefficients and model parameters have great influence on the iterative convergence speed and convergence accuracy. When the weight coefficient is 0.025 and the initial model parameter is 0.8, the iterative convergence speed and convergence accuracy are much higher than the traditional force correction iterative hybrid test method. The force correction iterative hybrid test method based on the adaptive model is much better than the traditional force correction iterative hybrid test method in the iterative convergence speed and iterative convergence accuracy of different single-layer frame structures, and the advantage is more obvious in the structure with a natural vibration period of less than 1s.
The nonlinear primary resonance of electrostatically actuated micro-oscillator considering fringing effect is qualitatively studied by using the theory of nonlinear dynamics. Firstly, a single degree-of-freedom dynamic equation of the system is obtained by using the differential quadrature method. Secondly, the static bifurcation of the system is studied by using the bifurcation theory. The dimensionless critical cubic stiffness, primary and secondary pull-in voltages are derived and defined. Thirdly, the frequency response of the system is obtained by using the multi-scale method. The dimensionless critical voltage for determining the softening or hardening property with small vibration response is defined. Finally, the dynamic characteristics of the primary resonance and the interwell jumping behaviors are discussed by combining the dynamic pull-in condition and the critical governing equation of the softening-to-hardening switch condition. This study has a certain theoretical and engineering reference for qualitatively grasping the static and dynamic pull-in and primary resonance of electrostatically actuated micro-oscillators.
The wheel polygon and rail corrugation as typical wheel-rail periodic wear of high-speed railway, aggravate wheel-rail vibration and affect driving safety. In order to explore the interaction under extreme conditions when wheel polygon and rail corrugation coexist, firstly, considering wheel-rail periodic wear of high-speed railway, the finite element model of wheel-rail system is established, and the frequency-dependent wheel-rail periodic wear competition mechanism is explored. Then, from the perspective of frequency-dependent wheel-rail periodic wears, the wheel-rail friction coupling vibration characteristics of wheel-rail periodic wears in the same / different phase contact are compared. Finally, from the perspective of frequency-independent wheel-rail periodic wears, the wheel-rail friction coupling vibration characteristics of the interaction of wheel-rail periodic wear are studied. Results show that under the extreme conditions of the coexistence of frequency-dependent wheel polygon and rail corrugation, the wheel-rail system is the most unstable. The instability of the wheel-rail system will be aggravated when the frequency-dependent wheel-rail periodic wear are in the same phase, and with the increase of wave depth, the difference in wheel-rail friction coupling vibration between the same phase and different phase will be increased. the closer the frequency-independent periodic wear frequency of wheel-rail is, the more obvious the influence on the stability of wheel-rail system is.
Affected by the milling vibration, the instantaneous cutting position of the milling cutter and cutter teeth is complex and changeable, which leads to the continuous change of the instantaneous contact relationship between the milling cutter and the workpiece, which makes the formation process of the machining transition surface variable and uncertain. The instantaneous cutting position and attitude calculation model of milling cutter and cutter teeth under vibration was used to reveal the influence characteristics of instantaneous cutting attitude offset of milling cutter on the formation process of machining transition surface. Based on the mapping relationship between the instantaneous cutting position of the cutting edge and the machining transition surface, the change characteristics of the instantaneous position offset and angle offset of the milling cutter were obtained by using the surface morphology detection results. A method for identifying the characteristics of instantaneous cutting pose offset of milling cutter was proposed, and the response analysis of instantaneous cutting attitude offset of milling cutter and surface morphology solution were used for experimental verification. The results show that the above model and method can effectively identify the offset characteristics of the instantaneous cutting position of the milling cutter under vibration.
To establish the relationship between physical parameters of cohesive elements and bending strength of the sea ice, a regression model based on neural networks is proposed to determine the calculation parameters for predicting the bending strength of sea ice. Firstly, the numerical simulations of three-point bending test of sea ice are conducted applying finite element method and cohesive element method, and the effectiveness of the method is verified. Then, five influencing parameters are selected and 427 samples are generated using the Latin hypercube sampling algorithm. The corresponding bending strengths of sea ice in these samples are obtained through numerical simulations and the database of neural networks is established. On this basis, the multilayer perceptron neural network is used to train the prediction results for all samples, and a regression model for predicting the bending strength of sea ice is obtained. Consequently, a numerical model of level ice with the bending strength similar to that of the sea-ice tests is constructed. Moreover, the impacts of buoyancy and drag force by the fluid on the broken ice are considered in the numerical model as well, and the interactions between the cone and the level ice are simulated and analyzed considering the impacts by different parameters. The results indicate that the mean value, standard deviation, and peak values of the longitudinal ice force acting on the cone tend to be larger with the increase of collision velocity, cone waterplane diameter, and cone angle.
This study utilizes a high-precision Boussinesq equation to establish a numerical model, combined with experimental methods, to deeply analyze the load characteristics of shallow water sloshing motion within a rectangular tank. The research results indicate that when the dimensionless external excitation frequency approaches the natural frequency of the liquid, the sloshing motion and load time history curves exhibit similar nonlinear characteristics. As the excitation frequency increases, various different forms emerge. By performing Fourier analysis on the load time history curves, the frequency domain distribution characteristics of the load under different external excitation frequencies were obtained. Based on the similarity between the sloshing load and the high-frequency response curve of the free liquid surface wave height, as well as the analysis results of the load characteristics, an approximate method of the sloshing load was established. This approach demonstrates excellent generalization performance under different water depths and excitation amplitudes, reducing the overestimation of wall loads by linear approximations in resonance states, with errors at jump frequencies reduced by more than 50%. The proposed approximate model can quickly estimate wall loads under known wave heights, providing a theoretical basis for engineering design.
Based on the sparse decomposition matching pursuit algorithm, the ultrasonic testing signal of the protective coating of fabricated steel structures is represented in the over complete Gabor time-frequency library, and the time domain information of the coating is further extracted to obtain the thickness information of the coating. In order to solve the problem of high complexity and huge computation of the matching pursuit algorithm, the dynamic multi swarm particle swarm optimization algorithm is used to optimize the matching pursuit algorithm. The inertia weights are generated based on the chaotic strategy, and the learning factor and inertia weights are coupled together with an over trigonometric relationship, while the time factor and the influence factor of the chaotic perturbation strategy are added in the position update, balancing the local search and global search ability of the algorithm. Simulations and experiments show that the improved algorithm has greatly improved the detection accuracy, which can satisfy the practical applications, and has greatly improved the efficiency of the sparse decomposition operation, and compared with the metallographic inspection results, the relative error of the detection of the fireproof coating is -4.65%, and that of the detection of the anticorrosive coating is 1.33%.
Aiming at the problem that the negative vertical vibration effect caused by switched reluctance motor (HMDV) dead weight and motor air gap eccentricity seriously deteriorates vehicle ride comfort and operating stability, an optimal design method of HMDV controllable dynamic inertial suspension based on fractional order sliding mode control was proposed. Firstly, based on the unbalanced radial force generated by the air gap eccentricity of the hub-driven motor, the HMDV quarter-frame dynamic inertial suspension was established, and the excellent performance of the second-order hybrid-hook positive real network was proved theoretically. Then, the HMDV coordination control system based on fractional order sliding mode control theory was constructed by using the HMDV second-order hybrid-hook positive real network as the reference model, and the ride comfort simulation and analysis were carried out under random pavement. Finally, the HMDV quarter suspension bench test was carried out. The test results show that compared with HMDV traditional passive suspension, the root-mean-square value of body acceleration, root-mean value of suspension dynamic travel and root-mean value of tire dynamic load decrease by 7.72%, 30.64% and 11.54% respectively. This validates the excellent suppression performance of the proposed HMDV controllable inertial suspension against the adverse effects of vertical vibrations caused by the switched reluctance motor.
In order to suppress the vibration problem caused by reducer flexibility during the start-stop phase of industrial robot joint, a vibration suppression control method combining expectation dynamics and input shaping was presented. The dynamic equation for the robot flexible joint system was established, the calculation formula for the input shaper was deduced, and the control laws for the torque and position loops of the controller were designed according to the desired system parameters. The correspondence between the desired dynamic controller and input shaper parameters was explored, and the feasibility and effectiveness of the control method were verified. The results show that the vibration suppression control method, which effectively simplifies the design process of the input shaper, obtains a better residual vibration suppression effect, maintains a higher vibration suppression performance under different loading conditions, and can improve the operating accuracy and increase the service life of the joints.
The site information of offshore stations is usually difficult to obtain, and the engineering characteristics of marine sites are the important basis for the design, construction, operation and maintenance of major marine projects, as well as an important parameter for the study of site amplification in marine ground motion. To solve this problem, H/V spectral ratio curves of buried and unburied stations are obtained based on strong ground motion data from 150 stations of the S-net station network in the Japan Trench region and site classification is performed in this study. The results show that the offshore H/V spectral ratio curve has a large spectral ratio value. The H/V spectral ratio curves of each site category for buried and unburied stations differ dramatically in spectral ratio values and spectral ratio shapes. The magnitude and epicentral distance have a large effect on the long-periods H/V spectral ratio curves, and the focal depth has barely any effect on the H/V spectral ratio curves. The research results may provide references for the simulation of offshore ground motion, the study of site effects and the construction of marine engineering.
Using the Operating Condition Transfer Path Method (OTPA), Operational Transfer Path Analysis is used to analyze the vibration transmission characteristics of product packaging systems under different excitation spectra and vibration levels of random vibration, combined with Non Dominant Sorting Genetic Algorithm (NSGA-II), Non dominated Sorting Genetic Algorithm II for packaging system optimization design. The experimental results show that the measured vibration acceleration response curve of the key components of the product matches well with the acceleration response curve synthesized by the OTPA method, verifying the correctness of the OTPA method; Quantify the vibration contribution of each transmission path through the OTPA method, and compare and identify the main vibration transmission paths of the product packaging system; Keeping the cushioning material of the non main transmission path unchanged, the NSGA-II algorithm is applied to optimize the distribution of cushioning materials at the main vibration transmission path in the product packaging system, effectively reducing the acceleration response of key components, reducing energy accumulation during the vibration process, and promoting the vibration contribution of each transmission path to be balanced. We have achieved an optimized design of packaging systems that prioritizes buffering performance while balancing environmental performance and cost, verifying the effectiveness of the optimization method and providing reference for product packaging system design.
Aiming at the problem that the feature distribution of rolling bearing vibration data collected in variable working conditions is inconsistent and the label of the sample to be diagnosed is difficult to obtain, which leads to the difficulty of bearing fault diagnosis, this paper proposes a multi-source domain transfer diagnosis method of rolling bearing based on feature disentanglement and joint domain alignment. Firstly, in order to better extract the common features of the source domain and the target domain, the convolutional autoencoder and orthogonal constraint are used to disentangle the domain shared features and the domain private features, and the domain private features are filtered out and the domain shared features are retained for inter-domain alignment. Secondly, in order to reduce the feature distribution difference between the source domain and the target domain, the Multiple Kernel Maximum Mean Discrepancy (MK-MMD) and the Correlation Alignment method (CORAL) are used to construct the fusion metric. Finally, in order to avoid the decline of diagnostic accuracy caused by the negative impact of multi-source domain differences, the source adversarial module and the migration adversarial module are used to enhance the domain confusion between the source domain and between the source domain and the target domain, and the collaborative decision-making method is used to perform feature weighted fusion to reduce the interference of weak correlation domain features, and the final fault diagnosis recognition is realized. The proposed method is verified by experiments on rolling bearing fault data sets under two variable working conditions, and compared with the single-source domain diagnosis method and other multi-source domain diagnosis methods, which proves the effectiveness and superiority of the proposed method.
In the field of rolling bearing fault diagnosis, current unsupervised domain adaptation algorithms often face challenges due to unbalanced source domain data and domain shifts between the source and target domains, leading to low fault recognition rates. To address these issues, we propose a rolling bearing fault diagnosis method based on multi-manifold label propagation. This method aims to project the data from both the source and target domains into a common subspace, reducing intra-domain and cross-domain differences and balancing the sample distribution. Consequently, this enhances the accuracy of fault diagnosis under variable operating conditions.Firstly, we introduce a locally balanced mapping method within the domain, which maps the source and target domain data into a manifold subspace, resulting in aligned sample data. This step also balances the source domain data. Next, we propose a cross-domain manifold structure refinement alignment method, further mapping the data into a double shared subspace to obtain refined aligned sample data. Finally, we employ a dynamic weighted pseudo-label domain adaptive propagation method to achieve highly accurate pseudo-labels.Fault diagnosis experiments were conducted on both the CWRU and self-built bearing datasets. The experimental results demonstrate that the proposed method not only effectively recognizes multiple fault types, fault sizes, and composite faults but also exhibits excellent diagnostic performance even when labeled samples are scarce.
To solve the problems of low efficiency, long time consuming and complex test flow of subjective evaluation method for vehicle creep groan, the temporal features and time-frequency domain feature extraction method of creep groan signal are studied. A creep groan evaluation method based on dual-stream convolutional neural network (DSCNN) with fused features is proposed by combining the spatial processing ability of 2D-CNN with the temporal processing ability of 1D-CNN. One input is time series features extracted by variational modal decomposition, the other input is image features extracted by fast Fourier transform, the one-dimensional time series feature and the high-dimensional image feature are fused, and a training model is used for scoring. By fusing the information of different modes, the method can capture the local waveform features and spatial texture features of creep groan. The results show that the eight-classification accuracy of the scoring model is 87.13%, which verifies the effectiveness of the feature fusion method in creep groan evaluation.
The vibration signal transmission mechanism has strong coupling, strong impact, and strong interference characteristics for diesel engine. Accurate signal characteristic extraction is the key to identifying and suppressing vibration sources. To address the issues of adaptability and accuracy of the Variational Mode Extraction (VME) method in handling diesel engine vibration signals, the peak frequency of the vibration signal was taken as the initial value of the center frequency, the correlation between the decomposed signal and the original signal was considered, and the peak to peak value, root mean square value, and peak factor of the decomposed components were used as the judgment indicators, the parameter adaptive variable mode extraction (PAVME) was proposed, and the accuracy and applicability of PAVME was verified by constructing simulated signals of diesel engine vibration characteristics in low signal to noise ratio environments. the abnormal vibration source of the gearbox was identified as gear meshing excitation based on PAVME and Power Spectral Density Function (PSD). Taking into account both the source of excitation and the transmission path, a scheme for suppressing the vibration of the transmission mechanism through shaft torsional vibration control was proposed.
Aiming at the degraded performance of diagnostic models due to the uneven distribution of data under different working conditions and the imbalanced classes caused by the scarcity of fault data, a topology-aware and dual-view classifier based diagnostic method was proposed. The graph convolutional network (GCN) was taken as the framework. The non-parametric topology-aware module can adaptively update the graph topology, obtaining approximate message passing paths for cross-domain data, and extracting domain-invariant features through GCN. The dual-view classifier was constructed using binary and multiple classifiers, and the output similarities were calculated to reweight the training data, which avoids biased training with imbalanced data and poor recognition of the minority classes. Experiments were conducted using publicly available datasets (Xi'an Jiaotong University gear fault dataset, MAFAULDA machinery fault dataset) and a self-collected journal bearing fault dataset. The results show that the proposed method can improve the diagnostic performance under variable working conditions and imbalanced data.
Cable components are widely distributed in transmission lines, and their tension values and changes are the key factors affecting the intrinsic safety of transmission lines, so they are also the focus of condition monitoring during the construction and operation of transmission lines. The traditional cable tension measurement method has some problems, such as low precision, high environmental requirements, difficult to monitor live line, etc., it is not universal in transmission lines. In this paper, an image tension measurement method combining The Broad-Band Phase-Based Motion Magnification (BPMM) and deep learning semantic segmentation is proposed. By enhancing the image vibration amplitude, To achieve the amplification of microvibration images of cable components of transmission lines under environmental excitation. in order to remove the noise artifacts caused by BPMM algorithm after vibration video processing and improve the recognition accuracy, a joint segmentation method based on deep learning U-Net network and level set loss entropy is proposed to extract the centrosity of cable components and achieve the accurate pick-up of microvibration pixel changes. Then the natural vibration frequency is obtained and the cable tension is calculated by frequency domain analysis. The test and engineering application show that the strain measurement method based on microvibration amplification can effectively identify the small vibration changes of the cable under environmental excitation, and the error of the measured cable tension value is less than 6% compared with that of the sensor, which realizes the high-precision and non-contact measurement of the cable tension of the transmission line, and solves the difficult problem of the transmission line tension measurement.
Considering the threat of rockfall impacting superstructure of steel-concrete composite beam bridges in mountainous areas, both the dynamic behavior and vulnerability analysis of bridge panel under rockfall impact were performed. Firstly, based on existing impact test, the numerical simulation approach adopted to rockfall impact bridge panel was proposed and validated. Secondly, the refined finite element (FE) model of a prototype steel-concrete composite beam bridge panel subjected to rockfall impact was established, and the damage evolution process, failure mode and dynamic response of the bridge panel and shear nails were analyzed. Furthermore, the sensitivity and influence tendency of designed parameters of the bridge panel, i.e., concrete strength, yield strength, diameter and ratio of longitudinal reinforcement, transverse reinforcement ratio and stirrup reinforcement ratio, on the impact resistance performance were discussed. Finally, taking into account the randomness of geometry and material characteristics of bridge panel and impact load of rockfall, the vulnerability analysis of bridge panel was conducted based on response surface method and Monte Carlo simulation. The results indicate that improving the concrete strength and reinforcement ratio can effectively enhance the resistance of bridge panel against 400kJ energy level rockfall impact; for the considered impact scenario, in case of the impact velocity between 10~25m/s, the ratio of peak deflection to thickness at the mid span of the bridge panel is less than 0.75.
The pulley-rope system in hoisting mechanism of crane is prone to vibrate and tilt during operation process, which seriously reduces efficiency and increases safety hazard. When dealing with the real-time change of the contact state between pulley and rope, the assumption that the element node is bound to the material point leads to the fact that the element shape function hardly describes the circular curves of each section, and the element size needs to be reduced, which lowers solving efficiency. In this study, spatial description method was introduced to divide ropes in different contact states by the boundary points of the contact area on the pulley. Arc interpolation and Hermite interpolation were used to describe the shapes of the ropes in different sections, and the material velocity and material acceleration of each node were obtained. Considering the axial deformation of the rope, the dynamic equation was established according to the principle of virtual power. By comparing with ADAMS, the effectiveness of the method proposed in this paper is verified, and the pulley rope system commonly used in hoisting equipment is modeled. The influence of combination of pulleys and rope, lifting weight and distance of pulleys on the rotation degrees of pulley frame was studied. The modeling method of pulley-rope system proposed in this study provides the necessary theoretical support for engineering practice.
The Metal/CFRP hybrid materials combine low density and high strength CFRP (carbon fiber reinforced composite plastics) materials with low cost and high toughness metallic materials, which are capable to overcome the challenges of weight reduction, material cost, crash safety and bring more ideas and space for the body structure design in automotive industry. In this work, unidirectional CFRP (UD-CFRP) and woven CFRP (WF-CFRP) is combined with square aluminum alloy thin-walled tubes to prepare a series of composite thin-walled structures with different configurations. Axial quasi-static crushing tests are carried out to reveal the crashworthiness for all specimens. Based on the test results, the effects of fiber architecture, layer number and relative position of constituent parts on the crashworthiness are analyzed, and the CFRP/AL hybrid tubes shows excellent energy-absorbing characteristics. In addition, several FE models of front longitudinal beam are developed to further explore the lightweight effects of UD/AL hybrid materials in front longitudinal beam design. Finally, the aluminum tubal wall thickness and the CFRP ply orientation of UD/AL hybrid front longitudinal beam are designed by multi-objective discrete optimization method. As a result, the weight of the optimal design reduced by 34.26%, and the specific energy-absorbing (Ws) improved by 42.05%, compared with the initial design.
Aiming at the problems of end effect and poor signal noise reduction effect in empirical mode decomposition (EMD), according to the idea of extension-decomposition-clustering-noise reduction-reconstruction, a blasting vibration signal noise reduction method based on improved EMD is proposed. The method combined the characteristics of the comprehensive similarity index while taking into account the shape and amplitude similarity of the extension signal. , the clustering property of K-means algorithm and the noise reduction advantage of wavelet packet. It could not only eliminate the end effect of EMD, but also had a good noise reduction effect. The results show that compared with polynomial fitting and boundary local characteristic extension methods, the improved EMD method has the lowest energy error and mean square error (MSE) in simulation signal end effect suppression test. In the noise reduction of the measured blasting vibration signal, the improved EMD method has the highest signal to noise ratio (20.94 dB) and the lowest root mean square error (0.0031) compared with EMD and variational modal decomposition (VMD) methods. The improved EMD has the best performance in preserving low and medium frequency vibration signals at 0−200 Hz, the best filtering effect on high frequency noise above 200 Hz.
The study of meso-damage evolution in steel fiber concrete is important for the health inspection of in-service steel fiber concrete structures. A multi-channel acoustic emission system was used to collect acoustic emission signals from concrete and steel-fiber concrete specimens (steel fiber content of 15 and 45 kg/m3, respectively.) during splitting tests. Then, the damage characteristics of concrete and steel fiber concrete are analyzed by combining principal component analysis and k-means clustering algorithm. Research showed that steel fiber inhibits the propagation of cracks in concrete and effectively improve the post-peak toughness of concrete. The acoustic emission characteristics parameter of counts and energy changes reflect the meso-damage evolution process of macroscopic deformation and failure in steel fiber concrete. Finally, two damage mechanisms are identified for mortar matrix cracking and steel fiber pullout in steel fiber concrete. Compared with mortar matrix cracking, the acoustic emission signals generated by steel fiber pull-out behaviors have the characteristics of high count, high amplitude, strong energy, and long duration.
Straight-swirling mixed supercritical CO2 (SS-SC-CO2) jet is a new rock-breaking tool for oil and gas exploration and development that combines the technical advantages of SC-CO2 jet and straight-swirling mixed jet. A three-dimensional computational model of the SS-SC-CO2 jet rock-breaking was established based on the theory of fluid-solid-thermal coupling. The mechanism of SS-SC-CO2 jet rock-breaking was studied. The results show that the SS-SC-CO2 jet combines axial impact, radial tension, circumferential shear, and thermal stress; the existence of thermal stress increases the Mises stress of rock, but the increase decreases with the extension of impact time. The effects of different nozzle structural parameters on the jet flow field characteristics were analyzed by taking the erosion and diffusion effects as important references. The optimal flow field characteristics of the jet are achieved when the spiral groove opening angle is 45°, the diameter of the center hole is 2 mm, the number of spiral grooves is 4, and the impeller spiral angle is 60°. The study results provide a reference for optimizing the application of SS-SC-CO2 jets.
In order to solve the problem of optimal sensor placement in the field of wharf structure health monitoring, an optimal sensor placement algorithm based on improved multi-objective particle swarm optimization was proposed. In order to solve the problems of low optimization efficiency and single optimization objective of traditional methods, which was difficult to meet the complex health monitoring requirements such as modal identification and damage identification at the same time, a multi-objective optimization function based on damage sensitivity and redundancy, damage identification ill-posedness and modal linear independence was constructed, and the multi-objective particle swarm optimization algorithm (IMOPSO) was improved to obtain Pareto solution set, and the optimal sensor placement scheme was determined using TOPSIS entropy method. The test on a high-piled wharf shows that compared with effective independence method and effective independence-modal kinetic energy method, the distribution of measuring points using IMOPSO is more uniform, and the condition number of sensitivity matrix, the maximum non-diagonal element of MAC and the index of damage redundancy are optimized more than 45%, 90% and 5% respectively; The accuracy of damage location and degree identification under various working conditions is improved more than 5% and 7% respectively.
Seismic research shows that the damage of tunnels crossing active fault zones is extremely serious. In this paper, based on the project of Taiyuan City Urban Railway Line 1 Phase I Project, the interval tunnel crossing the Jiaocheng fault zone, the mechanical analysis model is established by Pasternak two-parameter foundation model, and the analytical solution of the longitudinal response of the underground pipeline under the positive fault is derived, and then the three-dimensional refined finite element model is established by ABAQUS software. The results of the analytical solution are in good agreement with the numerical simulation results, which proves the correctness of the analytical solution. Finally, the combination of segmental lining and flexible joints in the key protection zone is used to compare and analyse the effects of segment length, longitudinal position of joints and width of flexible joints on the overall disaster reduction effect of the tunnel structure. The results show that the results of the analytical solution of the longitudinal response of the underground pipeline under the fault movement can provide a reference for the determination of the key protection zone. The combination of segmental lining and flexible joints can effectively reduce the degree and extent of damage to the tunnel structure. The shorter the length of the tunnel section, the smaller the area of damage; increasing the width of the flexible joint will reduce the degree and extent of damage to the tunnel structure, and the damage area will be concentrated in the end part of the segmental lining structure. When the flexible joints are installed in the butt joint mode, the deformation and energy absorption of the joints can be maximised, and the disaster reduction effect is optimal. The study can provide a theoretical basis for the design and analysis of the fracture resistance design of tunnel projects crossing active fault zones using the combination of segmental + flexible joints.
Addressing concerns such as excessive displacement and inadequate self-resetting capabilities in bearings for isolated bridges employing traditional double friction pendulum bearings, a new type of iron-based shape memory alloy-double concave variable friction pendulum bearing (Fe-SMA-DVFPB) was developed utilizing both the variable friction mechanism and the superelastic characteristics of shape memory alloy. Its constitutive model is constructed and its equivalent analysis model is determined. The displacement-based seismic design method of isolated bridges employing Fe-SMA-DVFPB is proposed. Drawing from practical engineering insights, isolation bridges are individually designed with various types of bearings, facilitating a comparative and analytical examination of their seismic performance. The research findings indicate that, in comparison to isolated bridges equipped with traditional double friction pendulum bearings, those utilizing Fe-SMA-DVFPBs demonstrate a notable improvement, with a maximum reduction in the relative displacement of bearings and residual displacement by 23.79% and 93.56%, respectively. The application of Fe-SMA-DVFPB isolation bearings effectively enhances control over both relative displacement and residual displacement. The decrease in relative displacement and residual displacement of the bearings in the isolated bridge significantly exceeds the increase in bending moment and shear at the pier bottom. The implementation of Fe-SMA-DVFPB can enhance the post-earthquake resilience of bridges.
To investigate the stick-slip friction response of friction pendulum bearings (FPB) under seismic actions, a smoothing model is proposed to address the non-smooth stick-slip friction problem. Firstly, complementary equations for friction saturation and relative slip velocity are formulated based on linear complementarity theory. Secondly, the relative slip velocity is averaged over short time intervals, and the complementary variable is reconstructed using the time-averaged slip velocity instead of the time-varying slip velocity, transforming it into a set of nonlinear complementary equations, thereby smoothing the non-smooth stick-slip friction problem. Subsequently, the FPB is equivalently modeled as a 2D friction-coupling model considering the effect of restitution force. Seismic response analysis is conducted using the proposed smoothing model and compared with classical Coulomb and LuGre friction models for validation. Results demonstrate that the proposed model can effectively capture the macroscopic stick-slip transition of stick-slip friction while smoothing non-smooth problems and avoiding frequent dynamic model switching in such events. Seismic responses of the FPB are computed using different friction models, verifying the accuracy and effectiveness of the proposed model.
Lighting fixtures can alter the aerodynamic shape of stay cables and may induce galloping phenomena. In order to study the influence of different lighting fixtures on the galloping performance of stay cables, a segment model low-frequency suspension system was developed based on the stay cable of a long-span cable-stayed bridge. Wind tunnel tests were conducted on segment model vibration measurement, and the galloping performance of three types of lighting fixtures, including hoop type, laminated type, and separated type, were studied under wind attack angles of 0° to 180°. The influence of additional damping on the critical wind speed of galloping for installing lighting fixtures for stay cables was analyzed. The research results indicate that the type of lighting fixture is an important factor affecting the galloping performance of the stay cable. There is no obvious galloping phenomenon when installing the hoop lighting fixture stay cable, but both the installation of the laminated type lighting fixture stay cable and the separate type lighting fixture stay cable have galloping at low wind speeds, indicating that the laminated type lighting fixture and the separate type lighting fixture will reduce the galloping stability of the stay cable. The diameter of the stay cable is an important factor affecting the galloping performance of the stay cable. When installing laminated lighting fixtures, the adverse wind attack angle of the 200mm diameter stay cable is 160°, while the adverse wind attack angles of the 260mm diameter stay cable are 30° and 150°; When installing separated lighting fixtures, the unfavorable wind attack angle of the 200mm diameter stay cable is 20°, while the 260mm diameter stay cable does not show obvious galloping vibration. The critical wind speed of the galloping vibration of the stay cable does not show an proportional relationship with the additional damping. The relevant research results can provide important references for the study of the galloping performance and vibration reduction control of the installation of stay cables for lighting fixtures.
Existing finite element model updating (FEMU) methods for long-span bridges often fail to consider the effects of external loads on the structural dynamic properties, leading to a high degree of parameter variability in the updated model. Therefore, a hierarchical Bayesian FEMU method considering operational loads is proposed in this paper, which consists of the definition of the updating parameters considering temperature and traffic loads, response prediction considering uncertainties, and structural condition assessment. Firstly, the correlation analysis of the monitoring data is conducted to determine the loads considered in the theoretical frequency simulation. Then, a linear relationship between temperature and material elastic modulus, and a vehicle load estimation method based on Weigh-in-Motion (WIM) data are proposed to quantitatively consider the effect of operational loads on the structural natural frequencies in the FE model. Subsequently, a two-step Markov Chain Monte Carlo (MCMC) method and a response surface surrogate model are introduced to accelerate the updating process. The proposed method is validated on a long-span arch bridge with two-year-long monitoring data. The results show that the measured frequencies are generally within the 95% confidence interval of the predicted frequencies, considering the operational loads, parameter uncertainties, and modeling errors. Finally, a structural state indicator based on predicted and measured frequencies is proposed, which detects the pavement replacement process of the bridge.
Low-sidelobe broadband transducers can improve the detection accuracy and anti-jamming ability of sonar system. A low-sidelobe broadband and high frequency underwater acoustic transducer is designed,which incorporates 1-3 piezoelectric composite with non-uniform distribution piezoelectric phases technology and matched layer multimode coupling technology. Theoretical calculation model and simulation model were established. The variation laws of frequency with piezoelectric phase volume percentage and sidelobe level with ring radius were analyzed by numerical calculation and finite element simulation. According to the optimized design parameters, the transducer was fabricated and measured. The measured results are in good agreement with the simulation, providing experimental validation for the feasibility of achieving the low sidelobe broadband transducer. The measured sidelobe level is -23.9dB, exhibiting reduction 6.3dB compared to conventional piston array sidelobe level. The center frequency is 300kHz, while the transmission voltage response bandwidth (-3dB) spans across 150kHz.
An innovative acoustic metamaterial was developed by stacking multi-channel structures layer by layer. Theoretical analysis, numerical simulation and experiment were introduced to study the characteristic and generation mechanism of the sound attenuation. A genetic algorithm was utilized to find the optimal combination scheme of the chamber length to broaden the sound attenuation frequency band, and its underlying logic was discussed. Results show that the structure can be regarded as an acoustic waveguide attached multiple side-branched Helmholtz resonators, and its transmission loss curve has multiple continuous resonance peaks to achieve broadband sound attenuation. The broadband sound attenuation can be improved by adjusting the length and width of the chamber, increasing the thickness of the structure, and creating the non-uniform array. When optimizing the structure with different size parameters, the genetic algorithm consistently maximizes the sound attenuation bandwidth by creating as many Helmholtz resonators with stronger single-cell sound attenuation as possible. The broadband sound attenuation is verified by the experimental results. The obtained results can be used as a guide for reducing pipeline noise in narrow space.
In the application of noise source identification based on microphone array, the function beamforming (FB) algorithm has the performance bottleneck of spatial resolution, so a penalty function beamforming(P-FB) algorithm was proposed. The normalized FB output is used as the penalty matrix, and the Hadamard product of the normalized beamforming matrix is calculated to adjust the steering vector in the weighted matrix. The adjusted steering vector and the cross-spectral exponential function are used to calculate the output of P-FB, so as to update the penalty matrix and implement iterative operation. By penalizing iterations, the point spread function can be made close to the Dirac function, and the spatial resolution performance can be improved. Simulations and experimental results show that the proposed algorithm exhibits a narrow main lobe, low side lobes, effectively addressing the issue of suboptimal spatial resolution in FB algorithm. In the application of sound source identification of compressed gas leakage, the algorithm can effectively suppress noise interference, reduce the main lobe, indicating that it has a good engineering application prospect.
The slow time and fast-time spatial resolution of the underwater acoustic tomography model is the same, only depends on the highest frequency of the transmitted signal, and the resolution is better than that of the spotlight synthetic aperture sonar. At present, the time-domain back-projection algorithm is often used in the underwater tomography, which requires a large amount of calculation. In this paper, a wavenumber domain imaging method based on the theory of projection slicing is proposed, which integrates polar coordinate formats transformation results of each sub frequency band. The inverse Fourier transform problem of Cartesian coordinate interpolation of annulus space spectrum is transformed into the fusion problem of inverse Fourier transform of circular space spectrum of all single frequency under broadband emission, which reduces the estimation error caused by conventional wide-band wave number domain circular interpolation. The problem that the reconstructed target distribution function is a hollow ring is solved and the calculation efficiency is improved . Moreover, the effect of high side lobe on the imaging results of single frequency wave-number domain is effectively suppressed which significantly improves the imaging accuracy compared with the spotlight synthetic aperture sonar under the same conditions.
Combined with theoretical calculation, finite element simulation and experimental measurement, the optimization design method of acoustic maze structure based on acoustic black hole is studied, and a small-size and broadband sound absorption structure with 5.01 and 7.75octaves is given.First, based on the transfer matrix method, the mathematical model of acoustic black hole is established, the reflection coefficient of acoustic black hole is calculated, and the theoretical calculation results are compared with the finite element simulation results.Then, based on the admittance variation law of the acoustic black hole, the single and double side branch acoustic maze structures are designed. By optimizing the design, the matching of the maze structure and the admittance of the acoustic black hole is realized.Finally, based on the matching results of the admittance of the acoustic maze structure, the simulated annealing algorithm is used to construct the optimization model, and the small-sized acoustic maze structure with broadband sound absorption is obtained, and the 3D sample is printed for experimental verification.The results show that the double side branch pipe acoustic maze is used to replace the ring cavity in the acoustic black hole pipeline. After optimization, the admittance of the side branch pipe maze and the acoustic black hole can achieve perfect matching, and the small size design of the structure can be realized under the premise of maintaining the sound absorption performance. The effective sound absorption bandwidth of the optimized structure is 13.36 times that before optimization, and the octavesare3.94 times those before optimization.