The problem of load identification denotes identifying loads based on the measurement of structural responses，which is the inverse problem in structural dynamics. A load identification method based on time-delay neural network is proposed in this paper，and numerical examples based on simulation and experiments are provided to show that the method overperforms normal back-propagation neural network in accuracy of identification. Additionally，statistic pooling is introduced on the basis of the method，and it is proved that the method performs well in noisy environment compared with BP neural networks. based on the load identification methods mentioned above，a sensor placement optimization based on particle swarm optimization algorithm is proposed，and the optimal sensor placement is able to reduce the error of identification by 90% compared with the random sensor placements，meanwhile the minimum spacing of installation among sensors is also ensured during the optimization.

Jointed structures are widely used in engineering applications，and local nonlinear characteristics at the connection interface have an important influence on their dynamic modeling and characteristic prediction. Aiming at the problem that local connection parameters of nonlinear structural systems are unknown or difficult to measure，this paper proposes an identification method of local linear connection stiffness based on the FRF transformation from the perspective of inverse dynamic problems. By further combining with the time-domain nonlinear subspace identification method，the local linear and nonlinear connection stiffness of nonlinear structural systems can be finally obtained. The numerical example and experimental setup of the three degrees-of-freedom structural system are designed and further built to validate the proposed method. The results demonstrate that the proposed method can separate and identify the underlying linear FRF and nonlinear parameters of the nonlinear structural system，and subsequently realize the joint identification of the local linear and nonlinear connection stiffness.

The time-varying mesh stiffness is a core parameter of gear systems，and the mesh stiffness identification is of great significance for the dynamic analysis and condition monitoring of gear transmission systems. Since it is difficult to directly measure the mesh stiffness，it is necessary to develop a data-driven time-varying mesh stiffness identification method. To deal with this problem，an alternating state-parameter optimization method is proposed to identify the time-varying mesh stiffness of gear systems. The Fourier series with the fundamental frequency of the mesh frequency is constructed to characterize the mesh stiffness. Furthermore，a Reproducing Kernel Hilbert Space （RKHS）-based de-noise method is further proposed to estimate the system state and parameter. The system state and stiffness parameter are alternately optimized with the joint constrains of dynamic model and data to realize the time-varying mesh stiffness identification of gear transmission systems. The simulation and experimental studies validate the effectiveness of the new mesh stiffness identification method for gear systems.

The study of the influence of potential well parameters on the output of a nonlinear energy harvester system is conducive to the design of the high-performance energy harvester system. Meanwhile，the stochastic resonance phenomenon in the corresponding electromechanical coupling dynamics model of the energy harvester system can be used to enhance the characteristics of weak faults，so as to effectively identify weak faults. This paper proposes a decoupled saddle-point-degradation bistable potential function，and the electromechanical dynamic model is introduced. The bifurcation diagram under different excitation amplitudes is obtained to discuss the effect of the barrier width and the barrier height on the responses （periodic response and chaotic response）. According to the methods of the Poincaré map，the frequency spectrum analysis，and the Lyapunov exponent，the periodic response and the chaotic response are examined at a fixed excitation amplitude，which is consistent with that obtained from the bifurcation diagram. Based on the electromechanical dynamic model perturbed by the random noise，the stochastic-resonance-based method is proposed for fault diagnosis，which achieves the enhancement of the simulated and experimental bearing fault characteristics.

The dynamic method for identifying axial force is grounded in vibration theory，making the vibration equation of a bar member crucial for accurate axial force estimation. Traditionally，the Timoshenko beam is derived from the equilibrium of transverse forces and moments. In this paper，an energy-based approach is applied to derive a new vibration equation for the Timoshenko beam under axial loading. The Ressiner energy equation for a Timoshenko beam，incorporating displacement，stress and axial force，is established using a condensation hypothesis from an energy perspective. The motion equation and stress equilibrium are calculated using the extremum principle，leading to a new free vibration equation for the Timoshenko beam under axial force. Compared to classical textbooks，the proposed dynamics equation includes two additional terms related to axial forces and shear effects. The new equation is validated through numerical simulations and laboratory experiments to identify the axial force in bar members. The results demonstrate that the proposed equation significantly improves the accuracy of axial force identification，confirming its correctness and applicability.

Spinning cylindrical shells are critical components in practical engineering structures. The boundary conditions at the shell ends are diverse and significantly influence the vibration characteristics of the shell. To study these characteristics under various boundary conditions，a dynamic model of the spinning cylindrical shell is established using Lagrange equations and Novozhilov’s shell theory. The mathematical description of the boundary conditions for the cylindrical shell is combined with the discretized displacement functions，which are constructed based on a linear combination of Chebyshev polynomials. These functions satisfy the boundary conditions and are independent of the cylindrical shell's parameters. The vibration characteristics of stationary cylindrical shells are determined by solving the eigenvalue problems，revealing the influence of rotary inertia on the vibration characteristics. The applicability of different shell theories with respect to various geometrical parameters of the shell is discussed. Additionally，circumferential wave-dependent mode functions are identified and used to compute the natural frequencies of shell modes with the zero circumferential waves，as well as the travelling waves of the spinning cylindrical shell under different boundary conditions. The impact of structural parameters on the natural frequencies of the travelling waves is also analyzed.

Floating raft vibration isolation systems in the ships or submarines have the requirement of low weight and small volume. To reduce the weight of floating raft vibration isolation systems and improve its vibration suppression effect，nonlinear energy sink cell （NES cell） is applied to the structural optimization of the floating raft vibration isolation system. NES cells are placed on all the substructures of the floating raft system. The mechanical model of the floating raft system with four degrees of freedom and the vibration damping system with NES cell are established. The modal analysis of the floating raft system is carried out. The approximate analytical expression of steady-state response for nonlinear system is derived by Harmonic balance method （HBM） and verified by Runge-Kutta （RK）. The vibration suppression effect under the different total weight and NES cell number is compared by force transitivity response，and the influence of the NES cell number and total weight of the system for the 1st-order mode is analyzed. The results show that NES cell can effectively improve the vibration suppression efficiency of the floating raft system for all the modes while reducing the total weight of the system and realize the structural optimization of the floating raft system effectively.

This paper considers a quadrotor transportation system with a four-cable-suspended payload. The relative position between quadrotor and payload is introduced and used to derive the tension of cables and describe the transportation system. A cost function inspired by payload and time is built to equipoise rapid UAV positioning and payload swing elimination. Then，the pseudo-spectral method is applied to transform the optimal control problem into a nonlinear programming problem and solve the optimal trajectory. A quadrotor transportation system’s trajectory tracking is facilitated by a PID controller. The optimal trajectory is validated through the presentation of both simulation and experimental results at last.

A rate gyro adaptive weighting method is proposed for the problem that the serious coupling of elastic vibration signals and rigid-body signals in the feedback control loop of flexible launch vehicles will significantly reduce the stability of the attitude control system. The method can be applied to the cases where there are deviations in the shape slope and frequency of elastic vibration. The rate gyro observation signal is converted into a frequency domain expression，and the interpolated discrete Fourier transform method is used to identify the elastic frequency. An adaptive updating algorithm for the rate gyro weighting coefficient matrix is derived based on the frequency domain，which eliminates the elastic vibration signals of each order in a stepwise manner. A simulation calibration is carried out under different cases of deviation. Simulation results indicate that the rate gyro adaptive weighting method can realize significant suppression of elastic vibration signals in the rate gyro measurement signals and reduce the adverse effect of elastic vibration signals on the stability of the attitude control system from the source. Thus the performance of the launch vehicle attitude controller is improved and the difficulty in the controller design is reduced.

In order to solve the problem that it is difficult to fully consider the dynamic characteristics （amplitude-phase frequency characteristics） requirements in the PID parameter design of electromechanical servo system，a PID design method for dynamic characteristics is proposed. The 9-order Transfer Function （TF） model of electromechanical servo system is established based on dynamic equation. The relationship between Routh criterion and TF coefficient is used to supplement the stability constraint of the system and the compatibility constraint of TF coefficient to ensure the stability of the system and the compatibility of TF coefficient in the PID design process. On this basis，based on the idea of parameter identification，the rational fraction orthogonal polynomial method is used to identify the coefficients in the TF model，so that the PID parameters are quickly determined，which improving the design efficiency，and multiple groups of controller parameters that meet the original index can be identified by adjusting the index data. The simulation results show that the designed PID parameters not only meet the requirements of dynamic characteristics，but also take into account the compatibility of system stability and TF coefficient. The design results are in good agreement with the simulation experiments.