A stability controller based on layered structure is proposed for the rear in-wheel motor drive vehicle. In the upper controller， the reference vehicle is first used to calculate the ideal vehicle state， the linear quadratic regulator （LQR） controller is used to calculate the additional yaw moment required by the vehicle， and the variable weight is designed according to the stability state of the vehicle. Secondly， in order to obtain as much ground adhesion， a fuzzy controller is proposed to control the slip ratio of rear wheels. In the lower controller， the driving torque of the rear in-wheel motor is distributed according to the stability state of the vehicle. Finally， the effectiveness of the controller is verified by the hardware-in-the-loop test. The results show that， when the vehicle is in the stable domain， the stability controller proposed in this paper can control the yaw rate of the vehicle to quickly follow the ideal value and suppress the increase in the sideslip angle. When the vehicle is in an unstable state， it can control the vehicle to quickly return to the stable domain and suppress the side slip of the vehicle. Throughout the control process， the slip ratio of rear wheels is always controlled below the optimal slip ratio to ensure great adhesion.

In order to give the driver better braking experience on the basis of ensuring safety， the driver’s braking intention is identified according to the pressure of the brake master cylinder and the rate of pressure change. First， the braking intention is divided into conventional deceleration and emergency braking. Then， two control strategies， current closed-loop control and active pressure control， are designed respectively. The two control strategies were verified by real car experiments. The experimental results show that： under active pressure control mode， the brake master cylinder pressure can quickly follow the target pressure. In the current closed-loop control mode， the booster current can follow the target current well. Compared with the ordinary control strategy， the control strategies designed in this paper can complete the process of building the brake master cylinder faster.

High-frequency nanosecond pulsed discharge is an effective way to generate non-equilibrium plasma for plasma assisted ignition and combustion research. In this paper， a compact high-frequency nanosecond-pulsed ignition system is designed based on resonant charging and magnetic pulse compression. Details of the electrical architecture and working principles of the ignition system are presented. The system can produce high voltage pulses over 10 kV， with a rising time of 20 ns， and a full width at half maximum of 50 ns， at repetition rate up to 16 kHz. Test results show that 10 pulses at repetition rate of 16 kHz have larger discharge volume and higher brightness than single pulse， and the utilization of coaxial electrode enlarges the discharge volume compared with pin-to-pin electrode. The experiment results show that the ignition delay time of multi-pulse discharge is much shorter than that of single-pulse discharge， and coaxial electrode discharge can significantly shorten the ignition delay time compared to pin-to-pin electrode with the same pulse number.

Gasoline direct injection （GDI） engine cars are widely welcomed by the market due to their outstanding fuel economy and engine power density. However， compared to traditional port injection engines and diesel engines equipped with diesel particulate filter （DPF）， GDI engines have higher particulate emissions. Therefore， countries around the world have enacted laws to limit particulate emissions. Gasoline particulate filter （GPF） is an effective solution to the problem of particulate matter emission. Aiming at the dynamic filtration process， filtration efficiency and pressure drop performance of the gasoline particulate filter， the probability density function （PDF） of the pore size distribution and the piecewise function of the porosity distribution are used to characterize the heterogeneity of the microstructure of the porous medium. The log-normal distribution is introduced to describe the particle size distribution of incident particles， and the influence of the filter wall microstructure on the GPF deep bed filtration process under the condition of multi-particle size incident is studied. The results show that the porous medium is saturated from the upper 1/6 area， and most of the particles are deposited in the upper 1/3 area of the porous wall. The increase of the pore size will lead to the downward expansion of the deposition position， the decrease of the first saturated layer and the improvement of the uniformity of the porosity distribution， while the change of the porosity will have a small effect on the particle deposition position. The filtration performance and pressure drop performance of porous media show a trade-off relationship. Compared with porosity changes， the filtration efficiency and pressure drop performance of porous media are more sensitive to changes in pore size， and the porosity has little effect on the initial filtration efficiency. The porous media with large porosity and small pore size has higher filtration efficiency and the best pressure drop performance.

In order to diagnose the fault of the input current sensor of the lithium-ion （Li-ion） battery， a linear first-order Thevenin equivalent circuit model of the Li-ion battery， coupled with lumped thermodynamics model， is adopted. Based on this model， a sliding mode observer is designed for fault diagnosis strategy research. First， the nonlinear varying parameters Li-ion battery model is linearized to establish a linear varying parameters Li-ion battery model that satisfies the operating accuracy of the entire operating condition. Then， the linearized Li-ion battery model with varying parameter is recombined and transformed， so that the current in the original system as the input is transformed into the output of the new system. Third， based on the new system of transformation， a sliding mode observer based on temperature estimation error correction is designed to estimate the output current in the new system. Finally， a residual evaluation function based on norm is designed. Simulation results show that the linearized model is feasible； the fault diagnosis strategy designed based on the model can quickly detect the occurrence of input current sensor faults， thus verifying the effectiveness of the proposed fault diagnosis method.

Under the requirement of precise control， the servo electric cylinder needs to ensure a high positioning accuracy. However， under heavy load， the servo electric cylinder will have a large elastic deformation， which seriously affects its positioning accuracy. To solve this problem， first， the mechanical stiffness model of the servo electric cylinder transmission system is established， which is verified through experiments. Then， a feedforward control algorithm based on the stiffness model is added. The research results show that the established mechanical stiffness model of the established servo electric cylinder transmission system is effective.. The addition of the feedforward control algorithm can significantly improve the positioning accuracy of the servo electric cylinder.

For large size hydrostatic bearings in heavy equipment manufacturing， it is easy to cause lubrication failure when running at high speed. In this paper， the lubrication performance of wedge oil film for hydrostatic bearing is studied under variable viscosity and high speed operation. Based on lubrication theory of bearings， the flow rate equation， the hydrostatic bearing capacity equation and the dynamic pressure bearing capacity equation of micro-beveled rectangular cavity affected by different speed and angle are deduced. CFD and FLUENT are used to simulate the oil film lubrication performance of bearings at higher speeds of 100 r/min， 120 r/min， 140 r/min， 160 r/min， 180 r/min and 200 r/min， respectively. The comprehensive influence law of oil cavity pressure， fluid velocity， vorticity and flow rate is revealed under the influence of higher speed changes. Finally， the oil film pressure field affected by higher speeds is tested under certain wedge height and higher speed， which verifies the theoretical analysis and simulation. It is found that hydrostatic failure of flat oil pad is very obvious at high speed. The micro-bevel oil pad can compensate the hydrostatic loss by the high-speed operation of the hydrostatic bearing. The dynamic pressure compensation range of the bearing is 16%~30%. The experimental and numerical simulation results of bearing operation have a good consistency at higher speeds.

In order to quickly and systematically identify the position dependent geometric error terms of CNC machine tool turntable， a rapid measurement and identification method of the geometric error of the turntable based on a double ballbar is proposed. Firstly， based on the homogeneous coordinate transformation theory， the position dependent geometric error model of the machine tool turntable is established， and the relationship between the change in ballbar length and the geometric error during the movement of the ballbar is obtained. Then， a six-time tapered installation method of the ballbar is designed， the error identification matrix expression is direved， the change in the length of the ballbar during the movement of the ballbar is record， and the position dependent geometric error terms of the turntable can be quickly identified. Then， a method for eliminating the installation error of the double ballbar is proposed， which can effectively eliminate the influence of the installation error in the raw data of the ballbar measurement. Finally， based on the identification results of the position dependent geometric errors of the turntable， the change in the length of the ballbar in the additional experiment is predicted， and compared with the experimental results， the prediction accuracy is high. On this basis， the position dependent geometric error of the turntable is compensated. It is show that after compensation， the accuracy is significantly improved compared with that before compensation. The experimental results show that the method can accurately and quickly identify the position dependent geometric error terms of the turntable， which has important significance for improving the accuracy of the machine tool.

A linear actuator driven by dual piezoelectric oscillators in inverse mode is proposed in order to improve the positioning ability. Two groups of independent controlled piezoelectric oscillators in inverse mode are used as the main and auxiliary piezoelectric oscillators. The oscillators generate the pulling force and thrust force， under which the actuator moves stably in the inclined plane. The bi-directional motion condition of the actuator is obtained. The prototype of the actuator was designed and developed， and the performance test was carried out. The linear actuator driven by dual piezoelectric oscillators in inverse mode outputs large speed and power， and realizes directional and stable motion in a inclined plane with an angle of 10°. The minimum step distance of the actuator is 5 μm， the maximum average speed is 22 mm/s.

Based on Epsilon algorithm and improved Neumann series， an approximate method for calculating the first and second order sensitivity of structural static displacement is proposed. First， the Epsilon algorithm is combined with the improved Neumann series to form a new fast approximate calculation method of static displacement， and a fast approximate calculation method of the first-order sensitivity of static displacement is derived. Then， the second-order sensitivity approximate calculation method of static displacement is further derived by combining the difference method with the first-order sensitivity method. The sensitivity calculation results of truss model and beam model show the engineering application value of the two sensitivity methods.

The flexible support structure of lens is designed by CAE， and the geometric position parameters are optimized in order to make the surface accuracy of lens meet the requirements of optical system in complex working environment. Firstly， by comparing the commonly used materials and processing technology of the lens support structure， the lens support material is selected， and according to the optical design results， the centering machining technology is used to ensure the straightness of the optical axis. Secondly the suitable flexible structure is chosen and the flexible support according to its central symmetry is designed. Finally， the geometric position of the flexible structure is parameterized， and the structural form of the flexible support is optimized by the integrated optimization method. The experimental results show that the surface shape error （RMS value） of the single lens module is better than λ/50 under three directions of self-weight deformation with temperature ranging from -10 ℃ to 50 ℃， and the first-order resonance frequency of the lens module and the single lens module is no less than 120 Hz. It is verified that the lens can meet the requirements of lens design in the environment of large temperature difference and high frequency vibration.

Aiming at the problem of rapid and accurate positioning of assembly reference points of rail vehicles， a multi-dimensional reference point positioning method is designed. Through IFR analysis， P&B product design and other methods， the scheme combines hardware and software. The instrument carries multiple ranging modules and communication modules， and transmits the measured car body data to the platform for analysis and calculation. Then， according to the calculation results， accurate reference points are obtained and positioned. In the practical work， comparing the new scheme with the traditional manual measurement method， the accuracy and efficiency of the new scheme are significantly improved compared with the original scheme.

Cu nanoparticles with different contents were added into Ultra-high-molecular-weight polyethylene （UHMWPE） and polyphenyl ester （POB）reinforced with carbon fibre（CF）.The effect of Cu nanoparticles content on the mechanical properties and heat conduction performance of the composites was studied. The wear surface of Cu nanoparticles modified composite material at temperature were examined by scanning electron microscope （SEM）. The transfer films topographical were studied by atomic force microscopy（AFM）. The research shows： The coefficient of friction and wear rate of composites at low temperature was lower than the coefficient of friction and wear rate of composites at room temperature. The wear mechanism of Chafing fatigue and abrasive wear is mainly for composite materials in low temperature environment. A compact and coherent transfer film is formed after adding copper nanoparticles to significantly reduce the wear rate of the modified composite material.

In order to investigate the effect of different spot diameters on the electrochemical corrosion resistance of 6061-T6 aluminum alloy subjected to laser shock peening， the surface roughness and residual stress of the alloy were measured. The cross-sectional metallographic and electrochemical corrosion experiments were carried out. Corroded specimens were observed and analyzed by scanning electron microscope （SEM） and energy dispersive spectroscopy （EDS）. Results show that laser shock peening refines the surface grains of 6061-T6 alloy， increases the surface roughness and generates a compressive residual stress. The corrosion current densities of the untreated specimen， treated specimens with 2 mm and 3 mm spot diameters were 154.5 μA/cm²， 14.70 μA/cm² and 11.17 μA/cm²， respectively， indicating that laser shock peening effectively improves the corrosion resistance. The treated specimen with 2 mm spot diameter had worse surface topographies than that of the treated specimen with 3 mm spot diameter， resulting in the lower corrosion resistance.

Based on arrival-departure pattern， a unit delay model of coordinated control was proposed with the offset as the independent variable. The offset was optimized with the goal of minimizing unit delay. A numerical case was used to illustratd the application process of the offset optimization algorithm. Based on microscopic simulation， the influencing factors of the optimal offset value were analyzed. The results indicate that initial queuing has no effect on the optimal offset value. If there exists is a stranded queue， the optimal offset is postponed a few seconds after the head car arrives. When the distance between two intersections increases， the postponed time increases， and when the coordinated flow or the flow-in increases， the optimal offset increases.

Aiming at the problems of fluctuations and low accuracy rate of traditional D-S evidence theory map matching algorithm in dealing with the urban dense road network， this paper proposes an improved dynamic matching algorithm based on D-S evidence theory. Using this algorithm， the candidate segment probability formula in the traditional D-S evidence theory is improved， and its weight parameters are adaptively adjusted for different road types. Simulation experiments show that the matching accuracy and matching time of the proposed algorithm are improved. The matching accuracy can be improved by about 2% compared with other algorithms， and the single-point matching time can be reduced by about 0.5 ms， which can efficiently and quickly realize the accurate matching of the positioning points of complex urban road networks.

Accurately understanding the relationship between land use and public bicycle traffic demand is essential for adjusting control measures and station operation management. Taking public bicycle stations in Xi'an as an example， first， the public bicycle stations are divided into daytime destination stations， nighttime destination stations， daytime origin stations and combined origin/destination stations through K-means clustering while treating multi-factor indicators as variables. Then the non-linear regression models of land use， bus lines， subway entrances and exits， and station centrality as explanatory variables for each station attribute separately are established. The results show that station locations， external environment variables， and land use will lead to discrepancy in passenger flow generation rates for stations with different attributes. This study can provide theoretical reference for the operation and management of urban public bicycle systems.

The paper proposed a double-ring adaptive signal control method for intersection in intelligent and connected environment. First， Connected and Automated Vehicles （CAV） are modeled by Intelligent Driver Model （IDM） while human-driven vehicles are calibrated by the Wiedemann model. Then， running delay and vehicle stops are chosen as optimization targets considering the minimal constraint of green time. The signal timing optimization utilizes the double ring structure NEMA phases group as the variant. A micro-scope traffic simulation platform based on VISSIM was implemented. Simulation experimental results indicate that compared with single-ring fixed control method， double-ring adaptive control method reduces delay by 7.9%~17.7% and vehicle stops by 7.3%~17.0%. In the networked environment, the optimization effect of double-ring adaptive control method increases with the increase of saturation and the penetration rate of networked vehicles.

The dynamic model of articulated vehicle is of great significance for understanding the complex relationship within the vehicle system， predicting the change of vehicle performance and improving the development of new vehicle models. A dynamic model of three-axis semi-trailer with eleven degrees of freedom including vertical and lateral motions is presented. Compared with the vertical ride model， the validity of the coupled model is verified. The wheel bounce and body rolling motion are studied with the changes of road uneven excitation， vehicle velocity， suspension stiffness and tire stiffness of the semitrailer. The research results can provide reference value for the design control and parameter matching of articulated vehicles.

Driver fatigue caused by long-term driving is usually accompanied by a decline in driving performance. Therefore， driver fatigue threatens the safety of the drivers and passengers seriously. The development of driver fatigue detection technology can help remind the drivers and take relevant measures against driver fatigue， thereby improving traffic safety to a certain degree. The purpose of this paper is to improve the classification accuracy of the driver fatigue detection model. To achieve this goal， this paper introduces multi-fractal features of the driver behavior data. Six male subjects participated in the driving simulation experiment and UC-win/Road driving simulation software was used to collect driver behavior data such as driving speed， acceleration， steering wheel angle and steering wheel angular velocity. Indicators of the mean， the standard deviation and several different multi-fractal features of each kind of data were calculated. The changes of the drivers' subjective fatigue were also measured with a time interval of 600 s. And the relationship between the indicators and driver fatigue were measured. Additionally， the accuracies of driver fatigue detection models based on support vector machine （SVM） considering different features and different time window were compared. The research shows： The correlation between the singularity strength of acceleration （A₀） and driver fatigue is significant； Compared with the correlation between other indicators and driver fatigue， that between A₀ and driver fatigue is less affected by the time window width； The singularity strength of acceleration can help improve the accuracy of SVM； Compared with the time window of 15 s， a wider time window of 30 s can make the improvement more obvious. Therefore， it has certain application value in driver fatigue detection technology.

Based on the characteristics of traffic flow between adjacent intersections， this paper first considers the influence of queuing and departure of side vehicles on the offset and analyzes the arrival， queuing and departure of six kinds of arterial traffic flow at the downstream intersection. Then， the range of offset corresponding to each situation is determined respectively. Third， the delay analysis of arterial vehicles is carried out. Finally， an optimization model of offset with the minimum delay of arterial vehicles is established. Five adjacent intersections of Ganjiang North Avenue in Nanchang city are selected as examples to verify the proposed model. The quantitative relationship between offset of intersections and the delay of arterial vehicles is clarified， and the minimum delay of arterial system as the aim of offset is determined. The results show that the optimization model can significantly reduce the delay of arterial vehicles， and the total delay of arterial vehicles is reduced by 89.136%. The optimization model proposed can be used as a reference for the follow-up study of the influence of vehicles on side road on the arterial signal coordination.

In order to explore the running speed mesoscopic change of vehicles in the long line segment of desert steppe， the lines’ alignment elements data and the running speed of the vehicles under free-flow are collected in Wuhai-Maqing expressway and national trunk highway 110 in Ningxia. First， in order to reduce the interference of redundant factors in the analysis process， it is assumed that the vehicles’ running speed model in the straight segment is divided into acceleration， constant speed and deceleration. Second， and the parameters related to the max driving speed are regressed and analyzed respectively. Third， the mesoscopic model of the running speed is established in the straight segment of the desert grassland. Furthermore， considering the changes of the longitudinal section and downhill of the long straight section within the slope ［2%， 3%］， the velocity models of the uphill and downhill sections are modified， respectively. Finally， the effectiveness and reliability of the running speed models are determined by comparing the measured running speed with the model speed of the road. The conclusions of this study provide theoretical basis for the highway alignment design and speed control of long line segment of desert steppe highway.

At present， the research on commercial bridge weigh-in-motion （BWIM） system was mainly focused on the one-dimensional BWIM system. Most of them only consider the situation of a single vehicle crossing the bridge， and the phenomenon of multiple vehicles crossing the bridge in actual traffic was common. Aiming at this situation， a multi-vehicle dynamic weighing algorithm was proposed. Based on the Moses axle weight recognition algorithm， based on the transverse bridge's dynamic response line and bridge bending moment influence surface， the vehicle information such as the lateral position and axle weight of the single and multiple vehicles crossing the bridge were identified， and the finite element was finally weighed by the bridge dynamics Simulation analysis is performed to study the reliability of the algorithm under different working conditions such as single vehicle crossing the bridge， two vehicles crossing the bridge and three vehicles crossing the bridge. The results shows that： under the conditions of single vehicle crossing the bridge， two vehicles crossing the bridge， and three vehicles crossing the bridge， with the increase of the number of vehicles， the recognition accuracy slightly decreases， the maximum error of the total vehicle weight recognition is about 13%， and the lateral position recognition The error is about 9%， and the recognition accuracy meets the actual needs of the project. The algorithm can identify the lateral position and axle weight of the vehicle when multiple vehicles cross the bridge， and has the potential to develop into a commercial BWIM system.

In view of the existing failure mode search method， the global critical strength branch and bound method， the failure element is directly deleted in the effective strength calculation without considering the dead load and internal force redistribution. The failure mode searched by this method is not consistent with the actual failure path of the structure. Therefore， a more comprehensive method to reflect the failure mode of bridge is proposed. The dead load effect of the structural failure element was applied to the adjacent structures as part of the external load. Considering the redistribution of the internal force of the structure， the internal force and effective strength of the remaining structural system element was optimized. The improved branch and bound method was established. A continuous rigid frame bridge was used to verify the improved method. The results show that the main failure mode of the continuous rigid frame bridge is obtained by the improved method， and the failure path is consistent with the actual damage situation of the bridge， and the failure mode of the bridge structure system is not missed.

The current DSR test and BBR test have limitations in evaluating the fracture performance of warm mix asphalt. In order to accurately predict the effect of warming agent on the fracture properties of asphalt materials， two different types of warming agents （Sasobit and ET-3100） were added to the matrix asphalt， then the rotating thin film oven（RTFO） and pressure aging vessel（PAV） tests were carried out to study the fracture properties of the warm mix asphalt. The extended bending beam rheometer（Ex-BBR） test and double edge notched tension（DENT） test were conducted to characterize the low strain rheological and high strain ductile fracture properties of the warm mix asphalt. In addition， Fourier transform infrared spectroscopy（FTIR） test was conducted to compare the molecular structure of asphalt before and after the addition of warming agent. The test results show that addition of 3% Sasobit and above can significantly reduce the low strain rheological properties and high strain ductile fracture properties of asphalt. ET-3100 can slightly reduce the ductile fracture resistance of asphalt， and this the effect has nothing to do with the amount of ET-300. The FTIR test results show that warming agent ET-3100 slows down the aging degree of asphalt， which is manifested by the reduction of hydroxyl C=O and sulfoxide S=O.

In order to research the transverse force of hollow slab bridge when the hinge joint and the slab are damaged， first， an analytical model of the damaged hollow slab bridge is established based on the articulated slab girder theory. Then， the influence of the damage of hinge joint and slab on the transverse force of the bridge is investigated. The results show that the damaged hinge joint can reduce the capacity of the transverse loading transferring. Moreover， the severe is the damage， the greater the maximum load is distributed to each slab， and the closer to the damaged hinge joint， the greater the impact on the slab. The load on the surrounding intact slabs will increase when the hinge joints and the slabs are damaged at the same time， and new damages are easy to occur to the intact slabs.

Through the shear failure test of five reinforced concrete beams with different shear span ratio and different hoop ratio， the damage evolution process of concrete beams was studied by using acoustic emission detection technology and fractal theory. Based on the parameters of acoustic emission signal energy， ringing count and crack fractal characteristics， the evolution of shear damage of concrete beams is quantitatively analyzed. Test results show that the acoustic emission ringing counts and energy with the damage degree are divided into three stages. The accumulate ringing count， energy and the fractal dimension of crack increase with load level. The growth rate of the crack increases with the shear span ratio， while decreases with increasing stirrup ratio， proving that the acoustic emission parameters can be used as a damage degree evaluation index. By establishing the correlation between the cumulative acoustic emission events and the load level， the damage evolution model of the shear beam is derived， and the correlation between the damage degree and the fractal dimension of the beam surface crack is established.

Two types of Geosynthetic-reinforced Walls （GRWs） are considered here to assess their emission reduction performance based on stability design. Comparing with the gravity retaining walls， the influences of various design parameters are further investigated on the carbon emission reduction performance. Using GRWs can reduce carbon emission by at least 50%. Due to the excellent anti-seismic property of GRWs， the carbon emission reduction performance increases as the horizontal seismic acceleration increases， but it is insignificant. The carbon emission reduction performance of photosynthesis increases linearly with the carbon fixation years. Vegetated rap-around GRWs uses plants rather than panels to make its emission reduction rate exceed 90%. When the constructions of GRWs is completed， about 3~10 years later， the carbon emission mitigation rate can reach 100%， thus acheiving green ecological support.

In order to study the viscoelastic damage characteristics of sandstone， the Hopkinson test under multiple impact compression was carried out. Based on the dynamic stress-strain curve of sandstone， two definitions of dynamic deformation modulus in the range of middle strain rate are analyzed. It is shown that the equivalent dynamic deformation modulus can reflect the damage characteristics of sandstone under dynamic impact compression. Microscopically， the statistical damage variable of sandstone can be defined by the ratio of the number of damaged microelements to the total number of microelements； and macroscopically it can also be defined by the dynamic deformation modulus before and after the microelement failure. It is verified that the dynamic deformation modulus obeys the Weibull statistical distribution. The force model of the microelement is composed of a viscous body and a damaged body in parallel. The mechanical mechanism of the viscoelastic body is reasonably explained by the highly linear correlation between the dynamic stress， the dynamic strain and the strain rate of sandstone. The stress-strain relation of the damaged body is derived based on the Drucker-Prager strength criterion and the strain equivalent principle proposed by Lemaitre. Through the verification of the introduced viscoelastic constitutive relation curve and the test curve of sandstone， the trend of change between them is consistent， which has good representativeness， indicating that the established viscoelastic damage constitutive relation is reasonable. The deviation between them can be solved by increasing the number of sandstone samples， optimizing the test scheme and applying probability statistics. After obtaining the viscoelastic constitutive relationship parameters with a certain guarantee rate of probability， the viscoelastic damage constitutive relation can be used to analyze and evaluate the stability of the rock slope in the coal mining area， and provide the necessary theoretical analysis basis for the related geological engineering evaluation of safety.

To improve the iris recognition rate by suppressing the noise and extracting the feature of local texture effectively in iris image， an iris recognition algorithm based on multi-direction local binary mode and stable feature is proposed. First， applying a variety of filtering processing algorithms， sufficient iris internal features are extracted from the iris image in unstable state with illumination and noise interference， which are as effective iris information to form a stable iris feature image. Then， based on the local binary pattern， a multi-directional local binary pattern is proposed to extract the feature vectors. This method not only can describe the overall spatial information of the iris image， but also reduce the dimension of the feature image. Finally， the Hamming distance is used for iris recognition. This method is used to identify CASIA， JLU-6.0 database， and the results show that this method not only can guarantee the effectiveness of the stable feature， but also extract the local texture feature effectively with higher recognition rate and robustness.

In order to achieve secure and efficient authentication between legitimate users and servers， and to ensure the security of communication between the two parties， the design of authentication protocols has become an important research hotspot. The three-factor authentication key agreement protocol proposed by Lwamo et al can not defend against offline password guessing attacks， and can not achieve perfect forward secrecy and user untraceability. To remedy these flaws， we propose an improved authentication protocol for single-server architectures by the use of traditional Diffie-Hellman key exchange algorithm and fuzzy verification technology. Security analysis and performance analysis show that the proposed protocol can effectively solve the above security vulnerabilities， and can achieve secure and efficient identity authentication.

The potential of accelerating CALYPSO structure prediction by replacing DFT methods with machine learning was studied. The performance in predicting the potential energy of boron clusters was evaluated with five machine learning methods. Firstly， the original data was represented as structural information metrics with Coulomb matrix. Then the eigenvalue vector pair of the matrix was extracted and used as the input of machine learning algorithms to training model， five algorithms were trained and tested using the same dataset. Also， factors affecting the performance were explored. Finally， a method of comparing the similarity of predicted values and ground truth was proposed based on the characters of potential energy surface （PES）， and a confidence model was constructed to validate the best kernel ridge regression （KRR） method. It is suggested that PES fitted by KRR is similar with the PES by DFT， and the confidence of the algorithm is closed to 90% while permissible error is 1 kcal/mol. The result of time test to KRR shows that the method’s time complexity is O（n）， which is improved by 1 to 2 orders of magnitude compared with DFT methods.

The estimated accuracy of the depth maps of underwater images affects the quality of the restored images. In order to obtain more precise depth maps， an algorithm was proposed to calculate the depth map based on attenuated channels and luminance map， and then the depth map was used to recover underwater images. First， the depth map of underwater image is estimated according to the relationship between image pixel and scene depth. Then the depth map is further rectified and refined by using the luminance map. Third， the atmospheric light value and the transmission map of the image is calculated using the refined depth map. Finally， the degraded underwater image is restored by inversely solving the underwater imaging model. The experimental results show that compared with the existing algorithms， the model parameters calculated using the rectified depth map are more accurate， and the restored image has better contrast and can maintain more natural color.

In practical engineering problems， due to the influence of external factors such as artificial or environmental disturbance， there will inevitably be outliers in the measurement data obtained by instruments. The outliers will deviate from the measurement data in some way， resulting in the instability of the accuracy of data reconstruction. For the measurement data with outliers， a robust reconstruction method based on Moving Least Squares （MLS） is proposed. This method fits the nodes with the least square method in the influence domain. The abnormal degree of generated fitting point is quantified according to the geometric characteristic parameter α， and the outliers is eliminated. The local fitting coefficients are determined with the weight least square by using the remaining nodes in the influence domain， and the curve and surface reconstruction is completed by moving the influence domain. By trimming only one point in each influence domain， the multiple outliers of measurement data can be effectively handled， and it is unnecessary to set threshold values subjectively or assign weights， which avoids the negative influence of manual operations. The numerical simulation and experimental results show that the proposed method can effectively eliminate the outliers in the measurement data. Compared with the MLS method， the accuracy of the numerical case can be improved by more than 60%.

In view of the huge memory consumption of traditional discrete data mining methods， this paper proposes a local outlier data mining method based on artificial intelligence technology. The feature of the discrete data is extracted and the local outlier data is detected by the algorithm based on information entropy. Through standardized processing of the detected data， the mining of local outlier data in neural network is realized， and the research on local outlier data mining method based on artificial intelligence technology is completed. Experimental results show that， compared with the traditional data mining method， the proposed method consumes less memory in the process of data mining and has obvious advantages， which fully verifies the applicability and effectiveness of this method.

This paper discusses a multi-state repairable and degraded wind power generation system with multiple maintenance strategies. According to the operating environment and the principle of wind power generation system， the reliability model of this system is established by using Markov process and reliability theory. This wind power generation system can be degraded into several discrete states over time， and the system can be converted into more intermediate states between the good state and complete failure. Then the system can be transformed into an abstract Cauchy problem， and the existence and uniqueness of the state probabilities of the repairable degenerate system are discussed. Finally， the simulation of the state probability， availability and other indexes of the degradation system was carried out under the determined energy efficiency grade. The study shows that the wind power system can be described by Markov process， and this model can effectively make quantitative analysis of the system reliability index.

In order to quickly and accurately obtain the driver's head status during the driving schedule to identify drivers' status， an improved ResNeSt classification algorithm is proposed in this paper. Yolov4 is used as an algorithm to detect the drivers' head to obtain head images. To solve the problem of imbalance classification of the dataset， the method named PULSE is applied to recover the focus failed image to complete the dataset. Experimental results show that the classification accuracy can reach to 80.51%， indicating that the proposed algorithm has certain validity and accuracy.

As a classic multi-level optimization algorithm， the Canny algorithm is widely used in MRI edge detection. MRI has the limitations of uneven gray density and low contrast. This paper uses lumbar disc MRI as an example to propose an improved Canny algorithm for optimization in edge detection. First， the image contrast is enhanced， and on this basis， the median filtering is introduced to effectively process impulse noise for preprocessing. Then， for the problem of insufficient edge extraction accuracy， the gradient direction template is increased to obtain the gradient amplitude and direction. For the excessive number of false edges and edge discontinuities， the gradient intensity information calculation method is used to achieve threshold adaptation. Finally， the image enhancement is performed again through the histogram normalization. This paper uses four evaluation criteria of PSNR， SSIM， MSE and algorithm running time to verify the traditional algorithm， the existing algorithm and the improved algorithm in this paper. The results show that the improved Canny algorithm significantly improves the accuracy of MRI detection， effectively reduces the false edges， and it is adaptive. The results of this article have certain reference significance for MRI in medical image processing.

In order to improve the operation efficiency and the energy efficiency of the assembly line， the energy consumptions during task performing， changeover， stand-by and transportation were considered when balancing the robotic assembly lines. The objective was to minimize the number of workstations and the total energy consumption simultaneously. A mathematical model was first established， and then an improved Multi-objective Evolutionary Algorithm was proposed and a special coding scheme was designed. A constraint-handling technique， an adaptive penalty factor and a problem-based local search strategy were introduced to enhance the performance of the algorithm. Finally， the problems of different scales were optimized and the results were compared with other algorithms. The results show that the proposed algorithm is effective and feasible， and the energy efficiency of robotic assembly lines is improved.

The traditional hierarchical sliding mode control method applied directly to the spherical robot speed control will cause a long adjustment time and a large overshoot， which is hard to meet the requirements in practical application. In this paper， a new sliding surface with fractional order PI^λD^μstructure is proposed by introducing a derivative element and fractional order calculus. The asymptotic stability condition of the sliding surface is given. Based on the new fractional PI^λD^μ sliding surface， a velocity controller for the linear motion of the spherical robot is designed. Furthermore， an adaptive law is used to estimate the unknown rolling friction. The simulation results show that the new adaptive fractional sliding mode controller designed in this paper presents a better control performance and stronger robustness compared to the conventional one. Besides， the new controller can accurately estimate the unknown rolling friction.

In order to reduce the increasing traffic safety problems， the development of vehicle collision early warning and collision avoidance control system is essential. This paper presents a compound control and collision avoidance method based on the longitudinal and lateral dynamics of vehicles to reduce traffic accidents. First， the vehicle inverse longitudinal and lateral dynamics models are established respectively. The longitudinal controller judges whether the vehicle is in a dangerous state and gives collision warning through the safety distance model. Then， the upper model prediction controller and the bottom single neuron PID controller are designed by using the layered control method. Finally， the model predictive controller is designed by combining the parameters constraint at different speeds. Simulation experiments under different working conditions were performed， and results show that the control system designed in this paper can avoid collision successfully and improve the safety， stability and comfort of the vehicle.

Aiming at the problem that the parameters such as the height， relative distance and termination impedance of the transmission line show uncertainty in the practice， a calculation method for the uncertainty of crosstalk in multi-conductor transmission line is proposed. Firstly， the multi-conductor transmission line model with uncertain parameters is established. Then， according to the multi-conductor transmission line theory， considering that the model has a safety threshold， the random response surface method based on the most likely failure point is used to calculate the failure probability of the multi-conductor transmission line model. By comparison， the failure probability of the model obtained by this method is basically consistent with the calculation result of Monte Carlo method， but its calculation efficiency is greatly improved， and the statistical moment of model crosstalk can be conveniently obtained， so as to realize efficient and accurate prediction of electromagnetic compatibility performance of transmission lines， such as wire harness or circuit board microstrip line in complex systems， such as automobiles.

In order to solve the problems of low testing efficiency， high labor intensity and danger during the tractor hydraulic suspension system text， a hitching testing device for tractor hydraulic suspension system was designed based on virtual simulation. The mechanism was composed of a hitching part and a loading part. In the hitching system， the hydraulic automatic control method was used to complete the positioning and connection of the tractor's lower pull rod. In the loading system， the lower pull rod of the tractor was loaded by adopting the hydraulic loading cylinder and lever mechanism. Meanwhile， using the lever loading method can reduce the movement displacement of the loading cylinder and avoid the excavation of the trench in the experiment site. The virtual simulation software， Adams and Workbench， was used to simulate the kinematics and mechanics of the tractor hydraulic hitch detection device. The results show that the designed hitch test device meets the mechanical requirements and the kinematic requirements without interference jamming. The tractor hydraulic hitch test device was manufactured and assembled， and the hitch and loading experiments were carried out. A loading force of 5 kN was applied to the end of the device during the loading test， and the lower pull rod of the tractor was lifted 650 mm. The results of the verification test show that the device can be used to connect the lower pull rod of the tractor accurately and quickly， and can complete the loading experiment of tractor hydraulic suspension， which meets the expected requirements. This research can provide reference for intelligent and high efficiency testing of tractor hydraulic suspension， and designing the corresponding device for testing.

Sieve is one of the important parts of corn grain harvester. However， it is often blocked by corn cobs in working process， which leads to high loss rate and high percentage of dirt corn kernels. The sieve with chaffer opening angle of 37.5°， 45°， 52.5° and 60° were selected as research objects. The stripping force test of blocking corn cob was carried out by using self-made device. The results show that the hole-blocking ratio of sieve gradually increases with the work quantity of corn grain harvester， and the dirt percentage in granary and the loss rate at the tail sieve varied slowly first and then increased sharply. The influence of sieve blocking on the quality of cleaning operation was significantly enhanced when work quantity of corn grain harvester exceeded 1.5 hm2. The hole-blocking ratio of upper sieve was 7.89%， 7.59%， 7.14% and 6.91%， respectively. The hole-blocking ratio of tail sieve was 8.07%， 7.81%， 7.49% and 6.78%， respectively. The dirt percentage of corn kernels in granary was 1.15%， 1.29%， 1.34% and 1.45%， respectively. The loss rate of corn kernels at the tail sieve was 1.13%， 1.07%， 0.93% and 0.87%， respectively. The stripping force of blocking corn cob in upper and tail sieve were all between 0.5~ 3.5 N. The average stripping force of blocking cob in upper sieve was 2.07 N， 1.76 N， 1.56 N and 1.47 N， respectively. The average stripping force of blocking cob in tail sieve was 2 N， 1.73 N， 1.59 N and 1.48 N， respectively.

In order to improve the cutting efficiency and conveyor rate of hemp harvester， the central composite design experiments were conducted to optimize the working parameters. Firstly， the physical and mechanical properties of hemp stem were studied. Based on composite experiment methods of quadratic orthogonal rotation， the effects of key components' main working parameters， including cutting speed， chain conveyor speed， horizontal distance between cutting and clamping point， on cutting efficiency and convey rate were analyzed. The data were analyzed based on the Design-Expert software. The regression models of cutting efficiency and convey rate were built， and corresponding variance analysis was conducted. The response surface method was utilized to analyze the effects of factors' interaction on the cutting efficiency and conveyor rate， and the multi-objective optimizations were conducted to determine the working parameters for the best cutting efficiency and conveyor rate. The optimal combination of the working parameters of the hemp harvester are the cutting speed of 1.33 m/s， the chain conveyor speed of 1.35 m/s， and the horizontal distance between cutting and clamping point of 63.9 mm. Under this optimal combination， the cutting efficiency and conveyor rate are 44.35 stalks/s and 93.93%， respectively. The field verification test was conducted. With the optimal parameters， and the cutting efficiency and conveyor rate are 44.7 stalks/s and 92.21%， respectively， closing to the model predicted results and greatly improving the harvester performance. The study provides the scientific basis for key components' working parameters optimization of hemp harvester.