High-dimensional uncertainty propagation currently faced the curse of dimensionality, which made it difficult to utilize the limited sampling resources to obtain high-precision uncertainty analysis results. To address this problem, a high-dimensional uncertainty propagation method was proposed based on supervised dimension reduction and adaptive Kriging modeling. The high-dimensional inputs were projected into the low-dimensional space using the improved sufficient dimension reduction method, and the dimensionality of the low-dimensional space was determined by using the Ladle estimator. The projection matrix was embedded into the Kriging kernel function to reduce the number of hyperparameters to be estimated and improve the modeling accuracy and efficiency. Finally, the leave-one-out cross-validation error of the projection matrix was innovatively defined and the corresponding Kriging adaptive sampling strategy was proposed, which might effectively avoid large fluctuations of model accuracy in the adaptive sampling processes. The results of numerical and engineering examples show that, compared with the existing methods, the proposed method may obtain high-precision uncertainty propagation results with fewer sample points, which may provide references for the uncertainty analysis and design of complex structures. 

For the dynamic problem of rigid-flexible coupling systems under dynamic uncertain excitations, an interval process model-based sequential simulation method was proposed for uncertainty analysis, which aimed to obtain the upper and lower bounds of the system dynamic responses such as structural vibrations and mechanism kinematics, by sequential sampling of the interval process and the rigid-flexible coupling dynamics simulations. The construction and numerical solution of the dynamic equation of the rigid-flexible coupling systems with central rigid body and flexible beam were introduced. Aiming at the dynamic analysis of rigid-flexible coupling systems under uncertain dynamic excitations, the interval process model and the interval K-L expansion were introduced to quantify and represent the dynamic uncertainty efficiently, and a sequential simulation method was proposed to solve the upper and lower bounds of the dynamic responses of the system mechanism motions and structural vibrations. The method used a sequential simulation strategy to identify the interval process parameter sample sets that contributed to the upper or lower bounds of dynamic responses in the cur rent simulation sequence, and served as the local encrypted sampling center in the next simulation sequence, which might effectively avoid the inefficient convergence problem caused by excessive invalid sampling simulations when calculating the upper and lower bounds of dynamic response in direct Monte Carlo simulation. Finally, three examples were given to verify the effectiveness of the proposed method. The results show that the sequential simulation method has better computational efficiency and accuracy than that of the direct Monte Carlo simulation method for solving the upper and lower bounds of the rigid-flexible coupling systems large overall motions and vibration responses.

An efficient method for solving the failure probability function was proposed to address the difficulties of solving the failure probability function in reliability optimization design, such as complexity and large amount of computation. The basic idea of the proposed method was to utilize the adaptive Kriging method to construct a local surrogate model of the full space of input variables at the failure boundary. The local surrogate model was then combined with the Monte Carlo simulation method to calculate the failure probability of the structures under the specified distribution parameter samples. The functional relationship between the sample points of the distribution parameters and the structural failure probability was then fitted by the Kriging method. Finalization of the implicit function of the failure probability function expressed in terms of the Kriging model. In order to test the accuracy and efficiency of the proposed method, two examples were given to compare the computational results of the proposed method with those of the existing methods for solving failure probability functions. The results of examples show that the proposed method is suitable for solving complicated functional function problems and significantly reduces the amount of computation while satisfying the accuracy requirements.

An uncertainty propagation method was proposed based on active learning and BDNN for solving the high dimensional multioutput problems existed in practical engineering. Since the multiple output responses corresponded to the same input variables, the efficient one-step sampling was implemented and the initial training dataset was established. BDNN was utilized for initially establishing the surrogate model for high dimensional multioutput problem. Because BDNN might provide the uncertainty estimation for multiple predictive output responses simultaneously, an active sampling strategy was proposed for high dimensional multioutput problem. Then, Monte Carlo sampling(MCS) method and Gaussian mixture model were combined for computing the joint probability density function of multiple output responses. The results show that proposed method may avoid the repeated computing processes for different output responses individually, and make full use of the internal relationship among multiple output responses for implementing active learning. Therefore, the efficiency for solving high-dimensional multioutput problems may be improved to some extent. Finally, several numerical examples were utilized to validate the efficiency of the proposed method. 

A reliability allocation method that considered both cognitive uncertainty and random uncertainty was proposed to address the problems of uncertainty in expert evaluation in meta-action reliability allocation. The mechanical products were reasonably decomposed by using the hierarchical method of function-motion-action(FMA) to obtain the basic motion type(meta-action) of the products. The experts were grouped and evaluated by probabilistic linguistic term set(PLTS) to reduce the random uncertainty of the experts evaluations. The combined evaluation results of the experts in each group were used as the evidences for the inference. And according to the evidence fusion theory to synthesize all experts information and reduce the influences of experts cognitive uncertainty. The weight value of each meta-action was calculated, and then the product reliability index was assigned to the meta-action. The effectiveness and practicality of the method were demonstrated through application examples.

 Since the failure of mechanical components was affected by the coupling effects of multiple degradation processes and external shocks and other factors, the current studies mostly considered a single factor and thought that the failure threshold was a fixed value, ignoring the facts that the equipment might reduce the shock resistance due to the degradation. Therefore, the influences of shocks on the degradation processes and the random uncertainty of the degradation processes on the shock failure threshold, as well as the correlation among different degradation processes were considered. A multi-correlation degradation reliability model was proposed considering a random variable threshold. In addition, the Copula function was used to describe the correlation among different degradation processes, and the parameter estimation method of the correlation model was given. According to the measured wheel wear data of a certain electric multiple unit(EMU), the accuracy of the model was verified by the Monte Carlo method. The influences of the correlation in the degradation processes on the reliability were discussed, and the sensitivity analysis of the random variable failure threshold was carried out to further illustrate the practicability of the proposed model.

 Considering performance stability, a reliability allocation method was proposed for mechanical system reliability allocation. The meta-action theory was introduced to decompose the structures of mechanical system and the meta-action unit was used as allocation object, a two-level comprehensive evaluation index model for meta-action reliability was established. Combining with the MCDM method, the reliability allocation coefficients of meta-action were obtained. Then, a stability model for the mechanical transmission system was established and the influence coefficient of each meta-action on the system performance stability was calculated. Finally, the reliability allocation coefficients were modified by using the influence coefficient of performance stability and a reasonable allocation of mechanical system reliability was achieved. By comparing with the traditional methods, the effectiveness of the proposed method was verified. 

The welded joints were susceptible to defects and stress concentration, rendering them vulnerable areas for fatigue crack initiation and propagation under fatigue loads. In comparison to homogeneous materials, the microstructure and stress localization in each of regions for the joints further complicated the fatigue issue in welded structures. Unlike ideal experimental conditions, the actual service environments of welded structures were intricate, it was necessity to consider the coupling characteristics between environmental factors and welded structures when predicting welded structure fatigue life. Therefore, the internal factors influencing welded structures were summarized and analyzed while reviewing existing life prediction models from perspectives encompassing complex loads and extreme service environment. Combining the latest research progresses, the recommendations were proposed to enhance fatigue life assessment methods for the welded structures.

Aiming at the problems that were difficult to capture the damage feature information and the identification results were inaccurate when there were different types of damages in truss rod elements, a damage identification method was proposed using JMRAE. Firstly, JMRAE was applied to intercept the signals according to different scale numbers, and the Sigmoid function and ReLU function were combined to extract the features. ZCA was introduced to reduce the features dimension to retain important information and reduce data redundancy. Then, SoftMax classifier was applied to solve the local features of different segments in the hidden layers, and feature fusion was performed to determine the structural states. Finally, the numerical three-dimensional truss structure model and the laboratory-built truss were used for validation and comparative study with the refined composite multiscale dispersion entropy(RCMDE), kurtosis, and back-propagation(BP) neural network methods. The results show that the proposed method has higher damage identification accuracy.

In order to accurately predict the remaining useful life of lithium-ion batteries and reduce the risk of battery operations, a novel model was proposed for online remaining useful life prediction of lithium-ion batteries. On the basis of historical operation data of lithium-ion batteries, six types of health indicators were extracted to characterize the degradation of batteries. The random forest(RF) algorithm was adopted to evaluate and screen the health indicators. The generalized regression neural network(GA-GRNN), which was optimized by genetic algorithm, was used to estimate the residual capacity of the battery. Then, a hybrid model combining bidirectional long short-term memory（Bi-LSTM）network model and nonlinear autoregressive（NAR） neural network（hybrid Bi-LSTM-NAR model）was used to predict the remaining useful life for lithium-ion batteries. A case study was conducted with the NASA open data. The results show that by way of screening the indicators, the accuracy of capacity estimation and remaining useful life prediction of lithium-ion batteries are ensured. Compared with the prediction results of existing methods, the prediction accuracy of the proposed hybrid prediction model is improved effectively.

A reliability estimation model for micro-electro-mechanical system(MEMS) micro accelerometer was proposed based on the total probability theory under a multi-load environment, addressing issues related to sensitive structural fractures and material fatigue degradation. The model combined homogeneous Poisson processes and Wiener degradation processes to characterize the number of impact loads acting on the micro accelerometers within a unit time and the fatigue degradation process of the device under vibrational loads. The model accomplished reliability modeling for the micro accelerometers under generalized extreme impacts, generalized δ- impacts and generalized mixed impact conditions. The reliabilities of the three models were compared and analyzed with time, and the results of reliability calculations from the generalized mixed impact model offer more valuable insights. Furthermore, a parameter sensitivity analysis of generalized mixed impact model shows that impact intensity and impact times have significant influences on the reliability of micro accelerometers.

For the problem of heat exchange micro-tube vibration reliability of diaphragm micro-channel pre-coolers which was one of the key components of pre-cooled air breathing combined cycle engines, the method and mathmatical model for calculating the natural vibration characteristics of heat exchange micro-tubes were developed, and the vibration modes and their mechanism of heat exchange micro-tube with the action of high speed air flow were studied. Then, the vibration modes including the vortex shedding excitation vibration, the turbulent buffeting vibration and the elastic excitation vibration were taken into account, and the reliability evalutating model of pre-coolers with heat exchange micro-tube vibration failure mode was derived. The pre-cooler heat exchange micro-tube vibration reliability of change rules were revealed. The results show that the natural vibration frequency of heat exchange micro-tube is affected by the parameters including outside diameter, pipe wall thickness, adjacent support plate spacing, material properties and so on, and the vibration modes of heat exchange micro-tube have the characteristics of sine function. Three important vibration modes including the vortex shedding excitation vibration, the turbulent buffeting vibration and the elastic excitation vibration those may happen in the heat exchange micro tubes of pre-cooler with the action of high speed air flow. And with the increasing of flow velocity of cooled working fluid, the heat exchange micro-tube vibration reliability of pre-coolers decreases firstly, and then increases and approaches a certain value. In order to avoid the resonance of heat exchange micro tubes, the structural parameters may be designed rationally with the operating profile and the flow and heat transfer characteristics may be also taken into account.

In order to improve the coordination engagement efficiency while maintaining the high reliability of the coordination engagement action, a reliability optimization design of ammunition coordinators was carried out. Considering the main geometric dimensions, manufacturing errors, elastic deformation of important components and other factors, a parametric rigid-flexible coupled dynamic model of ammunition coordinators was established, the failures of the coordination engagement action for coordinators were reproduced through the parametric dynamics analysis, then the performance function corresponding to the coordination failure mode and the reliability optimization design model of the coordinators were built. In order to improve the efficiency and accuracy of solving the coordinator reliability optimization design model, a new Kriging model adaptive update strategy was constructed and combined with SQP method and performance measure approach(PMA)/ reliability index approach(RIA), and the coordinator mechanism reliability optimization design method was proposed. The results show that the coordination efficiency of the coordinators is greatly improved under the conditions that the coordination engagement reliability meets the requirements, and the validity and engineering value of the proposed reliability optimization design method are also verified.

 In order to address the issues of life evaluation for polyurethane sealing elements used in electrical connectors during prolonged storage conditions, the underlying mechanism behind cohesion failure and boundary failure that contributed to performance degradation of these seals was analyzed. The reliability statistical model of polyurethane sealing elements for electrical connectors, established at the mechanism level, was validated at a statistical level by comprehensively applying particle swarm optimization algorithm and regression analysis, AD test and goodness of fit test methods to the comprehensive stress accelerated degradation data of temperature and humidity on polyurethane sealing elements. The validity of the failure mechanism analysis was confirmed through SEM and EDS techniques. Ultimately, the developed model was employed to assess the reliable lifespan of polyurethane adhesive seals for electrical connectors under the  storage environment.

 In order to study the adaptability of CFRP adhesive joints to the high temperature and high humidity environments in the automobile painting processes, the experiments of baking and accelerated moisture absorption of single lap CFRP adhesive joints were carried out. The shear tensile and normal tensile tests of bonded joints undergoing different environmental tests were performed. The strength changes and failure mode evolution of CFRP adhesive joints were discussed under different environments. The adaptability of the joints bonded by epoxy resin and polyurethane adhesives to baking was compared, and the effects of adding spew fillet at the edge of the lap area on improving the joint strength were studied. The results show that the shear tensile strength of single lap CFRP adhesive joints is much higher than the normal tensile strength. After baking treatment, the strength of CFRP laminates and CFRP adhesive joints are increased instead of decreasing. DP420 epoxy resin adhesive has better baking resistance than that of DP6330 polyurethane adhesive. After moisture absorption, the strength, stiffness and maximum fracture displacement of CFRP adhesive joints are decreased. The failure modes of the joints are gradually evolved from the cohesive failure of the adhesive layers to the inter-laminar failure of the CFRP laminate. For single lap CFRP adhesive joints, adding a spew fillet at the edge of the lap area may effectively enhance the tensile shear strength.

Aiming at the problems of high computational cost of large-scale structure topology optimization and low solving accuracy of solid isotropic material with penalization(SIMP) at the optimized structure boundary, an adaptive design domain(ADD) topology optimization method was proposed based on SIMP. The improved quadtree method was applied in the processes of topology optimization to reduce the computational burden and improve the solution accuracy at the boundaries through different levels of grid cell. The SBFEM was used to calculate the finite element information of the partitioned structures in real-time, solving the problem of hanging nodes between different level cells. The proposed method might obtain more accurate results with fewer initial grids and significantly reduce the computational cost. Numerical example results demonstrate that, with the same final structural boundary accuracy, the proposed method may reduce the computation time to 1/100 of the original at most, offering a reference for reducing the computational cost of large-scale structural topology optimization in subsequent processes.

A ultrasonic guided wave detection method was proposed to address the difficulty in detecting the interface quality of adhesive structures. Based on the spring model and wave equation, the mathematical model of ultrasonic guided wave propagation in the double-layer bonding structure was established, and the dispersion equations of different bonding interfaces were obtained. The dispersion characteristics of different bonding interfaces were obtained by solving the equations. The propagation processes of sound waves at different adhesive interfaces were simulated using COMSOL software. The simulation results show that under the condition of 1 MHz frequency rigid bonding, the group velocity numerically solved is as 4.632 km/s, and the simulated mean group velocity is as 4.505 km/s, with error of 2.74%. Under the condition of slip bonding, the numerical solution group velocity is as 4.855 km/s, and the simulation mean group velocity is as 5.045 km/s, with error of 3.91%. Under the condition of complete debonding, the dispersion curve of the double-layer adhesive structure is the superposition of the single-layer dispersion curve. Through the analysis of the experimental detection results of ultrasonic guided waves in double-layer media, it is found that the experimental results are in good agreement with the numerical solution and finite element simulation ones, which verifies the correctness of the theoretical model.

The active suspension might adjust the suspension parameters according to the real-time status of the vehicles, which greatly improved the rescue efficiency of emergency rescue vehicles. Electro-hydraulic servo actuator was the core component of active control of electro-hydraulic servo active suspension system, the control strategy of electro-hydraulic servo actuator was studied. The active suspension hydraulic servo actuator model was established. Then, based on the model, an adaptive position tracking control strategy was proposed based on a strict feedback model, and the stability of the proposed strategy in the Lyapunov sense was proved. The simulation and single-cylinder experiments show that the position tracking algorithm proposed may effectively improve the position tracking performance of electro-hydraulic servo actuators compared with the traditional control methods.

In view of the problems of frequent replacement of belt conveyor rollers, heavy manual replacement tools, high labor intensity and low shutdown replacement efficiency, taking the belt conveyor in the main adit of Wangjialing Coal Mine as the research object, the roller replacement robots with non-stopping were studied according to roadway parameters and roller replacement processes, and the overall research plan of the robots was formulated. Based on the functional analysis method and the theory of roller replacement with non-stopping, the 3D solid model of the robots was established by using SolidWorks software, and the parameters of the walking mechanism, attitude adjustment platform, telescopic support platform and disassembling manipulator were optimized. The finite element analysis of the support platforms and belt lifting mechanisms was carried out by ANSYS Workbench software. The telescopic support platform adopted a sliding rail structure, and the stresses of the sliding rail under the cantilever and lifting rated load are as 15.647 MPa and 66.395 MPa respectively. The maximum deformation and displacement occur under the rated load. The displacement is as 1.0742 mm. Belt lifting mechanism adopted shear fork structure, the rated lifting maximum stress is as 152.82 MPa, the maximum displacement is as 0.7331 mm. According to the design parameters, the robot prototype was processed with the power of 64 kW diesel engine as the power, and the crawler was driven by the hydraulic motor. The speed range is as 3~8 km/h. The attitude adjustment platform may realize the lifting height 0~357 mm, the pitch angle ±15°, the roll angle -4°~7°, the rotation angle -10°~20°, the transverse movement range 0~400 mm, the longitudinal movement range 0~ 350 mm, the multi-stage telescopic mechanism adopted the combined slide to achieve the platform 0~2.1 m telescopic. Using a five-degree-of-freedom manipulator may disassemble and assemble rollers in different positions. Through the ground and underground tests, the robot prototype walking, attitude adjustment, lifting belt, disassemble roller functions were verified experimentally. The results show that the robots may pass well in the narrow tunnel of the main tunnel, and the maximum height of the lifting belt of the telescopic support platform is as 241 mm when the conveyor is not stopped, which provides enough operating space for the robots to disassemble and assemble the rollers under different positions to meet the design performance requirements. The study of roller replacement robots with non-stopping for belt conveyor provides a new way for the maintenance of coal mine belt conveyor.