Fault diagnosis technology can be used to detect the potential fault of the equipment by analyzing and detecting the signal, so as to ensure the operation safety and effectively improve the operation efficiency of the equipment. The bearings are widely used in rotating machinery and equipment. The fault of the bearings may seriously affect the normal operation of equipment, and inflict economic damage, even endanger the safety of staff. Therefore, it is of great theoretical and practical significance to monitor the health status of the bearing, find out the fault location and analyze its severity in time. In the actual engineering conditions, the operating environment and workspace of mechanical equipment are characterized by complexity and variability. The intelligent fault diagnosis method based on Artificial Neural Network (ANN) can effectively identify the health status of equipment, but the traditional ANN requires a large number of labeled samples for training, which greatly limits its application in equipment fault diagnosis. Also its adaptability to different working conditions is poor. In order to solve this problem, this article proposed a model of bearing fault diagnosis based on transfer learning theory. The model consists of stacked sparse AutoEncoder (SAE) and flexible maximum function (Softmax) regression. In this model, high order KL divergence (HKL) is used to train domain adaptive ability, which can transfer the working condition with a large number of known data to the similar condition with a small amount of data. Only a small amount of data is needed to train the model to adapt to the new working condition. The experimental data set of bearing from Case Western Reserve University was used to verify the effectiveness of the model.

Aiming at driver panic or other factors causing the lack of braking force and decreasing the driver's braking operating burden when driving on a long ramp, HBA and HDC control strategy is carried out by Stateflow state machine theory and Matlab/Simulink. The brake pedal displacement and speed are selected as the identification parameters to better identify the driver intention. Meanwhile, the ramp recognition is designed by Newton's second law. Considering the braking problem of high temperature failure, the temperature model is built. Based on the above, MIL and HIL are carried out, the results verify the correctness of the control strategy. In addition, road tests' results show the HBA function can meet the ECE standard and the HDC function can keep vehicle speed near the target speed, proving that the control strategy achieved good control effect.

To solve the problem of road roughness identification, a NARX neural network identification method and its applicability are studied based on vehicle responses. A four degree of freedom plane model of vehicle vibration system is established, thus, the vehicle responses and road roughness of wheel can be obtained by simulation. The application selection, input scheme optimization and evaluation index of NARX neural network are studied, and the solutions of vehicle response selection and its combination optimization are put forward. The NARX neural network is used to identify the road roughness at front wheel of a car under the common road grade B and 60 km/h driving speed, for which the correlation coefficient and root mean square error are 96.75% and 0.003 3, respectively. The influences of training sampling points, vehicle response random noise, vehicle speed, and road grade on the NARX neural network are considered, and the adaptability of NARX neural network method for road roughness identification based on vehicle responses is illustrated. The results show that the use of orthogonal test design to determine the optimal input scheme of the NARX neural network and the identification of road roughness based on vehicle responses can achieve satisfactory performance and good applicability.

On the basis of in-depth study of scroll compressor profile construction, a new method for constructing scroll profiles using Frenet moving frame was proposed, a new type of variable wall thickness scroll profile was constructed by this method. The basic geometrical theory of the profile was established and the working chamber volume was also derived. On this basis, four performance indexes including compression ratio, area utilization coefficient, axial gas force and tangential gas force were introduced to evaluate its performance. The results show that under the same geometrical parameters, the newly constructed variable wall thickness scroll profiles have better performance than traditional variable wall thickness scroll profile. Not only the compression ratio and the area utilization coefficient are increased by 7.15% and 4.84% respectively, but also the axial gas force and tangential gas force are also significantly smaller. It can be seen that the use of this variable wall thickness scroll profile helps to further improve the performance of the scroll compressor.

In order to intelligently solve the problems existing in urban road networks and improve the accuracy of short-term traffic flow prediction, a short-term traffic prediction model is established by using the least square support vector machine (LSSVM). Specifically, the immune algorithm is adopted to optimize the penalty factor and kernel parameters of the LSSVM, thus obtaining the optimal prediction model. The prediction simulation experiment takes the average speed and occupancy rate of vehicles as the input of the model to predict the traffic flow. The experimental results show that the prediction error of the optimized LSSVM model used in the simulation experiment is reduced, and the output result is closer to the real value.

For the Electronic Stability Controller(ESC) of commercial vehicle, the partial parameters such as longitudinal velocity, lateral velocity, and sideslip angle are difficult to obtain directly, and the sensor process noise of the vehicle system is generally time-varying and unknown. To solve the problems, an Adaptive Cubature Kalman Filter(ADCKF) algorithm was proposed to estimate the vehicle state parameters. First, the standard Cubature Kalman Filter(CKF) algorithm was combined with the suboptimal Sage-Husa estimation algorithm to estimate the parameters of vehicle. Then, according to the ESC control requirements and considering the modeling uncertainty and external disturbances, the commercial vehicle ESC control of Radial Basis Function(RBF) neural network Sliding Mode Control(SMC) algorithm was proposed. Finally, the disturbances were estimated by RBF neural network. The co-simulation results of MATLAB/Simulink and TruckSim show that the ADCKF algorithm is accurate in estimating vehicle state parameters, and the RBF neural network SMC based on vehicle state estimation of commercial vehicle ESC has good control effect.

To solve the issue of the single ability for robot in the nuclear power plant, an autonomous exchange mechanism of the end-effector for robot is developed. The interface of multi-torque output with the concentric and parallel mechanism with 3-Hooke joints is used to provide power input for the end-effector with related operations. Based on analysis of the passive compliance and tolerance condition for the docking process of the double Hooke joints between the end-effector exchange and the tool rack, an automatic docking control strategy of the end-effectors exchange is proposed based on the contact force threshold. The automatic replacement of different end-effectors is realized by experiments, and the feasibility of the control strategy is verified. The mechanism prototype for end-effector exchange is designed. The exchange experiments of different end-effectors are carried out by the SCHUNK 6 DOF manipulator mobile experiment platform, which demonstrate the effectiveness of the control strategy, the tolerance performance of the mechanism. The experimental results show that the mechanism has completed docking process with larger tolerance compliant and realized the power transmission of the end-effector.

The fingerprint indoor localization method based on the Received Signal Strength (RSS) is vulnerable to multipath effect and noise interference, resulting in low positioning accuracy. To solve this problem, an indoor positioning method based on location fingerprinting of imitating the mechanism of scorpion vibration source location is proposed. Firstly, the method imitates the n/1 neuron configuration of scorpion to construct the neuron structure, in order to encode the vibration signal and transform the vibration signal into pulses. Secondly, pulses are extracted as the location fingerprint feature, and then the location fingerprint feature database is established by the number of pulses. Finally, the Weighted K-Nearest Neighbours algorithm is used to estimate the position of vibration source. To verify the performance of the proposed algorithm, a vibration signal acquisition system is set up to imitate the vibration perception of scorpions. It is used to collect the user's step signals in the indoor environment. The experimental results indicate that the proposed method can improve the average positioning accuracy by 0.148 4 meters compared with the location fingerprinting based on RSS.

In order to provide reference for setting on-street parking space that occupies vehicle lane, traffic flow parameters survey was conducted under the interruption of on-street paring. The changing rules of cars’ saturated headway with the number of on-street parking cars were analyzed. The models between the saturated headway with the number of on-street parking cars on adjacent lane and interval lane were established respectively using SPSS software. Based on established models, suggested thresholds of traffic volume for adjacent lane and interval lane were given to set on-street parking lot, and case study was conducted. It shows that cars' saturated headway on adjacent lane and interval lane increases with the number of on-street parking cars and there are quadratic function relations between them. With the increase in the number of on-street paring cars the road design speed increases, and the adjustment factor decreases for possible capacity, so the setting of on-street parking lot is more improper. When the number of on-street parking car is the same, adjustment factor for possible capacity of interval lane is larger than that of adjacent lane, so the influence of on-street parking on traffic operation of interval lane is less than that of adjacent lane.

This paper proposes a new type of dynamic bus lane, which not only ensures the bus priority strategy, but also significantly improves the spatial-temporal utilization of road resources, and reduces the conflict of demand between buses and social vehicles on road resource. The paper analyzes the difference of bus arrival time and proposes the determination method of dynamic lane clear distance and lane control flow based on the dissipation process of queue at intersection. Combined with HCM2010 vehicle delay formula and BPR function, the model of vehicle average travel time and per capita travel time under different road conditions is established. Through the numerical simulation, the operational benefits of three lane organization schemes, including without bus lanes, conventional bus lanes and dynamic bus lanes, were compared and analyzed. The experimental results indicate that the time benefit of setting dynamic bus lanes is better when social flow is less than 2268 pcu/h. The study provides theoretical support for rational optimization of bus lanes.

The wake of 1/4 scale square back Ahmed body with or without boat-tail structure was investigated at ReH=9.6×104 by pressure sensor and particle image velocimetry(PIV). The statistical analysis of the instantaneous pressure on the back shows that the wake presents a bi-stable behavior in the horizontal direction, characterized by alternating occurrence of two symmetry-breaking stable states, each can maintain a relatively long-time duration. During the two stable states, a lower pressure on the back presents a high probability, while in the switch state the pressure on the back is higher. The bi-stable behavior was also observed by instantaneous and conditional average PIV results of flow field in the horizontal plane. With boat-tail structure added at the model base, the bi-stable behavior of the wake is gradually suppressed with the increase in the boat-tail length, and the wake vortex structure tends to be symmetrical, the wake width becomes narrow, the vortex shedding strength weakens, leading to higher back pressure and lower drag coefficient.

Heavy-loaded Anti-Vibration Platform (AVP) is mainly used to carry high-precision instruments and equipments to isolate vibration and impact caused by uneven complex road surface, thus, providing a stable working environment. In this paper, taking the 6 DOF series AVP as the research object, the parameters of the AVP damping system are optimized by the usage of the fast elitist multi-objective genetic algorithm (NSGA_II) and multi-objective particle swarm optimization algorithm (MOPSO) to significantly improve the anti-vibration performance of AVP. The damping and stiffness parameters of the damping system are optimized by NSGA-II and MOPSO under various road surface analog signals. The optimization results show that the anti-vibration rate of the two optimization targets of vertical acceleration and vertical displacement of upper platform under different excitation can be up to 56.21%. In addition, NSGA-II is applied to optimize the damper support angle parameters of the AVP, which increases the anti-vibration rate of the two optimization targets by 7.00%. The sine excitation is verified by experiments, and the error between experiment and simulation is as small as 8.30%, thus verifying the effectiveness of optimization parameters.

The complex interaction process between the tire and the ground determines that the inverse solution of the model does not exist adequately. It is impossible to directly solve the vehicle model, in which tire characteristics are considered, to obtain the desired control amount from the trajectory. To solve this problem, a trajectory tracking control strategy based on tire force prediction and fitting is proposed. According to the physical boundary, the trajectory tracking control is decomposed into two layers. The upper layer control uses a terminal sliding mode control algorithm. To realize the pre-judgment of the desired front wheel lateral force, the body dynamics is solved according to the target curvature. The lower layer control uses the system identification method. According to the feature point data, the desired steering angle is obtained by fitting the characteristics of the tire force through the spline function. A 12-DOF vehicle dynamics model with body and tire is established. According to the test value of sliding rate required to maintain different speeds, a semi-empirical sliding mode longitudinal control strategy is established to control the vehicle speed. A contrast algorithm is constructed with neural network algorithm. In the step curvature condition for testing stability and the multi-variable curvature condition for simulating continuous turning roads, the effectiveness and global robustness of the proposed algorithm are verified.

The change of the railway track during rail vehicles travel will affect the vertical random vibration response of the vehicle body. Based on the vertical acceleration of the vehicle, the angular velocity of the vehicle body and the attitude angle, the vertical vibration mechanics model of the rail vehicles is established. The vertical vibration response of the vehicle body during the operation of the rail vehicles is obtained by numerical solution of the differential coefficient differential equations. The rationality of the vertical vibration mechanics model is tested by comparing with the experimental test vibration acceleration signal. The variation of vertical random vibration of vehicle body with train motion parameters is analyzed. The results show that there is a certain degree of correlation between vertical random vibration of vehicle body and vertical acceleration. It lays the foundation for the safe operation of rail trains and further fault diagnosis based on motion and vibration signals.

To meet the research demand of lithium-ion batteries under high temperature, cylindrical lithium-ion battery cells with different State Of Charge (SOC) were placed at elevated temperature for rest and cycle, and then these battery cells were compressed in radial direction in this paper. The experiment results indicate that the cells with a high SOC tend to be short-circuited early under compression after resting at a temperature of 40 °C or higher. This is due to the structural softening of the cells. The higher the rest temperature, the lower the resistance of the high SOC cells to deformation. Short cycling under high temperature would increase the resistance of the cells to deformation.

Based on the rearview mirrors of sedans, the Lattice Boltzmann method is used to study the flow field characteristics of the rearview mirrors. Combining aerodynamics with multiphase flow theory, the Lagrangian method is applied on the basis of the lattice Boltzmann method to study the water phase distribution on side windows caused by the rearview mirror on rainy days, and to investigate the pollution mechanism. Then the pollution effects of the mirror column and the mirror cover on the side window are studied. The mirror column factors include the length and size, and the mirror cover factors include the windward angle, the inside diffuser angle, the leading edge chamfer angle and the rear departure angle. The Results show that these factors have significant different influences on pollution location and pollution degree of the side windows. Increasing the column length, changing the inside diffuser angle of the cover to 0°, reducing the leading edge chamfer angle of the front cover and changing the rear departure angle to 0° will reduce the pollution level. The influence of the size of the mirror column and the windward angle of the mirror cover on the side window is complicated, but a lower pollution degree can also be obtained. The influence of each factor on the side window pollution is not independent.

Based on Hybrid Particle Swarm Optimization(HPSO), a parameter optimization method is proposed for a Dual Clutch Transmission(DCT) of a multi-mode axle-split Hybrid Electric Vehicle (HEV). Combining the enhanced Particle Swarm Optimization(PSO) and chaotic local search PSO, the HPSO algorithm is proposed to optimize the minimum transmission ratio and partial geometric progression gear ratio of DCT by adopting the equivalent consumption minimization strategy. The optimization is based on a co-simulation platform, in which, the HEV is modeled in AMESim and the control/optimization algorithms are programmed in MATLAB/Simulink. The simulation results show that the optimized transmission parameters can reduce fuel consumption by 2.04%, not only ensuring the dynamic demand, but also having good fuel economic performance.

The high-power ultrasonic spot welding machine was used to successfully weld T2 pure Cu and Ti6Al4V dissimilar metals. The effects of different welding energies on the interface temperature, cross-sectional macroscopic morphology, interface formation and mechanical properties of the joints were analyzed. It is shown that with the increase in welding energy, the peak temperature and high temperature residence time increase, the indentation depth increases gradually, the joint interface is flat and no intermetallic compounds appear, There is a diffusion layer with a maximum thickness of 2 μm at the interface. The tensile shear force gradually increases with the bonded area, and the maximum shear force is 2322 N. The joint fractures along the interface of the Cu side of the base material, and the fracture mode changes from brittle fracture to ductile-brittle mixed fracture. The stress analysis of the interface under different welding energies was carried out by using ABAQUS finite element numerical simulation software. The interface forming mechanism of Cu/Ti ultrasonic welded joints was systematically expounded.

Al alloy was deposited by using variable polarity cold metal transfer technique. The welding parameter of EP/EN Balance was varied to control the ratio of positive numbers to negative numbers in a weld cycle. During welding process, a high speed camera and an electrical signal acquisition system were used for observing the dynamic droplet transfer behavior and obtaining the electrical signals, respectively. The effect of EP/EN Balance on the formation of the welded joint was analyzed by the metallographic pictures. The results show that the heat input in positive period was higher than that in negative period. The alternation of “cold” and “heat” was realized during the variable polarity cold metal transfer welding process. The numbers of positive and negative periods were adjusted by altering EP/EN Balance, which could dominate the heat input to the welded joints. The weld bead with good appearance can be fabricated using variable polarity cold metal transfer technique. Weld depth and contact angle increased and reinforcement decreased with the increase in EP/EN Balance.

To investigate the interface failure mechanism between CFRP tendon and epoxy mortar in the bond-type anchorage system, a total 9 specimens were designed for static load test. Two parameters were considered in the test, anchorage length and the internal inclination of anchorage. The failure mode of the specimens, the wear degree of CFRP tendon and load-slip curve in the loading end of specimens were obtained. The interface failure mechanism between CFRP tendon and epoxy mortar in the bond-type anchorage system was described in detail. The energy dissipation in the bonding interface was investigated. The grey relational theory was applied to investigate the sensitivity of parameters on bond strength. Based on the testing data, the regression formula of bond strength was fitted and compared with other existing formulas. The results show that the chemical bonding force only plays a limited role in the initial loading stage, and the interface bonding stress is mainly borne by the friction force and the mechanical bite force. The anchorage length and the internal inclination of anchorage have no obvious effect on the relative elastic deformation energy, but the relative local failure energy is mainly affected by the internal inclination of anchorage. The elastic bond strength, ultimate bond strength and residual bond strength all decrease with the anchorage length. With the increase in the inner inclination angle of the anchorage, the ultimate bond strength of the specimens without shear failure increases to a certain extent, but the elastic bond strength and residual bond strength change irregularly. The results of grey correlation analysis show that the correlation degree of each parameter in the order from large to small are the number of CFRP tendons, anchorage length, the internal inclination of anchorage and the spacing of CFRP tendons. A practical formula for calculating bond strength is derived and the calculated results are in good agreement with the experimental results.

2205 duplex stainless steels containing 0.07% and 0.01% Ag were respectively prepared by adding Cu-Ag alloy particles. Meanwhile, the base material 2205 and Cu-bearing 2205 were prepared for comparison with Ag-bearing 2205. The microstructure, mechanical properties, corrosion resistance and antibacterial properties of the four materials were investigated by Optical Microscope(OM), Scanning Electron Microscope(SEM), tensile test, electrochemical workstation and film mulching method. Results reveale that the increase of Ag content increases the amount of α phase and decreases the amount of γ phase in the microstructure. Ag-containing phases exist in both Ag-containing materials. Ag-phases with particle sizes ranging from 1 to 6 μm are distributed at the interface of α matrix and in α/γ phase, while Ag-phases with particle sizes ranging from 80 to 400 nm are distributed in γ phase. Compared with base material 2205, adding of Cu can improve the tensile strength of the materials, but decrease its elongation. The tensile strength and elongation of the materials both increase with the Ag content. The material containing 0.1% Ag exhibits the best comprehensive mechanical properties. In 3.5% NaCl medium, Cu-bearing 2205 exhibits the best corrosion resistance. With the increase in Ag content, the stability and corrosion resistance of passivation film first increases and then decreases. The antibacterial rate of Ag-bearing 2205 materials increases with the contact time. The high Ag-bearing materials exhibit a good antibacterial property, and the base material 2205 and Cu-bearing 2205 do not have antibacterial properties.

In wind tunnel test, sound source drifts due to jet structure when locating in outfield. The measured sound drift error is enlarged due to inaccurate locating focus distance caused by uncertainty of sound source location. Base on geometric acoustics theory, this paper proofs that the acoustic drift error is proportional to the locating focus distance error. The position function of sound source is established using the surface geometric relationship of test piece according to the spatial distribution of the target sound source. More accurate locating focus distance is obtained by approximation method, thus, the sound drift error was reduced. The effectiveness of the method is verified by wind tunnel test. This approximation method can reduce the locating focus distance error apace and eliminate the sound drift error caused by location uncertainty.

The effects of different Ti contents on the microstructure and mechanical properties of ductile cast iron were investigated by adding Ti-C-Fe pre-forms. The results show that Ti mainly exists in the form of TiC and Ti (C,N) in molten iron, and the structures of pearlite and ferrite are refined. Ti content of 0.023 wt.% can increase the spheroidization rate, graphite number and ferrite content. With the increase of Ti content, The generated TiC particles will hinder the diffusion of C atoms, resulting in distortion of the graphite spheres, a decrease in the spheroidization rate and ferrite content. The mechanical properties of the specimens were tested and found that the ductile iron specimen with Ti content of 0.023 wt.% possessed good comprehensive mechanical properties, and its yield strength and tensile strength were increased by 5.43% and 3.73% respectively, and the elongation percentage was increased by 10.64%. When the Ti content was between 0.054 wt.% and 0.072 wt.%, the tensile strength of the sample was higher. The yield strength and brinell hardness of the sample with Ti content of 0.135 wt.% reached the maximum.