In view of the adhesion performance between asphalt-aggregate， the research results on the adhesion and raveling mechanism， evaluation methods， influencing factors and improvement measures in domestic and overseas are summarized. Formation and failure of adhesion are complex processes involving physics， chemistry， thermodynamics， and micromechanics. The characteristics of the interface between asphalt and aggregate are influenced by the properties of asphalt and aggregate， the void and asphalt film thickness of the mixture， and the external environment. The different test systems are dedicated to the development of methods that that can not only simulate the process of damage occurrence in the field but also provide an assessment method through which the suitability of mixtures would be estimated in designing steps and would be guaranteed during the pavements service life. Combined with the existing research contents，the future research directions of asphalt-aggregate adhesion performance and asphalt mixture moisture sensitivity are prospected.

Based on the special working condition requirements of hybrid electric vehicles， this thesis conducted a study on the vibration and noise characteristics of the timing silent chain system （TSCS） based on the structural design of the TSCS. The dynamics characteristics of the TSCS were analyzed and the boundary conditions required for vibration analysis were obtained by establishing the dynamics model of the TSCS， and based on the finite element analysis method， the vibration of the TSCS was studied through modal analysis and frequency response analysis， at the same time， using the vibration characteristics of the TSCS as input conditions， the acoustic boundary element simulation analysis of the TSCS was carried out， and the acoustic pressure-frequency response curve and the distribution of noise were studied. The analysis results show the excellent vibration and noise characteristics of the TSCS， and the analysis method will provide a reference for the vibration and noise reduction work of hybrid electric vehicles.

In order to assess the lunar surface trafficability of YuTu-2 lunar rover， a kind of method of lunar rover drawbar pull evaluation based on slip ration information was proposed. The wheel of the Yutu-2 lunar rover and its ground prototype were used as the test objects， the YuTu-2's lunar drive was simulated by the whole vehicle test and soil trough test. With the input parameters of rutting information， slip rate and wheel load， the calibration models of sinkage-slip rate and rut spacing-slip rate were established， the slip rate was identified by Matlab image processing. The results showed that the slip rate of the YuTu-2 lunar rover traveled in the specified area of the lunar surface at locations D'， A'， and B'， respectively is 10.45%， 12.96%， and 19.70%， and the drawbar pull is 177.03 N， 181.62 N， and 194.47 N.The ground test and inversion calculation results reveal that YuTu-2 travels well in the aforementioned region and satisfies the design requirements.

To study the particulate emissions characteristics and optimization methods of the engine under transient conditions， takes a 2.8 L turbocharged diesel engine as the research object. Firstly， the effects of single factor injection parameters on the particulate emissions under transient loading conditions were studied. Then，Taguchi orthogonal experiment was designed to give the optimal control parameter combination with the number and quality of particles， and the influence weight of each control parameter was determined. The results show that during the transient loading process， the number and concentration of small-sized nuclear particles deteriorated significantly， and the mass concentration of large-sized accumulated particles deteriorated significantly； Appropriately advancing the injection timing， increasing the injection pressure and the introduction of post-injection can reduce particulate emissions； Meanwhile， the effect of control parameters on nuclear and accumulated particulates has a trade-off relationship， and the relatively large weight of particulate emissions is the effect of fuel injection timing， that is the factor of injection timing and post injection interval.

During the operation of 5-axis CNC machine tools， the angle deviation of the rotation axis greatly affects the tool path control. Therefore， a post-processing algorithm of five-axis CNC machine tool with optimized rotation angle was proposed. Firstly， the basic structure of the machine tool was analyzed， the Hausdoff distance was used to obtain the matching error between the actual machined surface and the difference surface， and the error compensation method was used to compensate the obtained error， and the rotation axis angle of the machine tool was completed according to the processing result. Based on the optimization results， the machine tool coordinate system was established， and the machine tool post-processor was developed through the coordinate transformation results and integrated into the relevant software to realize the post-processing of the machine tool. The experimental results show that the proposed method achieves better processing results when used for post processing of machine tools.

To study the constant flow mechanism of the constant flow control valve， the influence of flow area and gradient on the characteristics of constant flow control valve are analyzed based on the actual structure of a certain type of valve. Firstly， the mathematical model， the control theoretical model and the transfer function block diagram of the dynamic system are established to quantitatively analyze the influence of these factors. Then the AMESim simulation model is established， and the influence mechanism of these factors on the steady-state and dynamic characteristics of the valve is analyzed. The reliability of the simulation model is verified by the experiment. The results show that there exists negative feedback between stages in the constant flow control valve， which compensates the pressure difference between the two sides of throttle and reduces the flow adjustment deviation. Adjusting the flow area of the pressure compensator can improve the steady-state characteristics of the constant flow control valve. Adjusting the flow area gradient of the pressure compensator can significantly improve the static and dynamic characteristics of the constant flow control valve.

Exclusive lanes for connected and autonomous vehicles（CAVs） will emerge in order to ensure the safety and efficiency requirements in the process of traffic flow mixed with human-driving vehicles and CAVs. When the inner lane of the expressway is set as the exclusive lane for CAVs， it has important theoretical significance and practical value to study the strategy of guiding CAVs to merge from the ordinary lane to the exclusive lane. Firstly， the entrance area of exclusive lane was designed and vehicle control rules were proposed. Secondly， with the goal of making more CAVs change lanes to the exclusive lane， the strategy of selecting lane-changing signal actions was proposed based on deep reinforcement learning. Finally， the numerical simulation was carried out with Python language compilation. The results show that the proposed algorithm can converge very quickly under 9 scenarios constructed by different factors， such as the CAV penetration rates and the proportion of CAVs arriving at the exclusive lane； it can effectively guide CAVs to merge into exclusive lanes and ensure traffic efficiency； congestion in the second lane can be significantly reduced compared to the unsignalized control when the penetration rate changes from 20% to 40%； the proportion of CAVs changing to the exclusive lane is significantly higher under the two exclusive lane entrances scenario than that under the one entrance scenario. It shows that the proposed strategy has good applicability and can provide reference for engineering construction.

In order to prove the adaptability of the metro train-bridge （especially long-span bridge） system to resilient wheels from the perspective of dynamics， the influence of resilient wheels on the long-span cable-stayed bridge （LSCSB） on the vibration of the metro train-bridge system and its suppression characteristics was studied. Based on the vehicle-track coupling dynamics theory， a coupled dynamic model of metro train-LSCSB system considering resilient wheel was established. Adopting the model， the effect of resilient wheels on the vibration characteristics of metro train and LSCSB under the combined disturbance of long-short wave irregularities was studied， the damping effect of resilient wheel on metro train-LSCSB system is proved from time-frequency domain. The results show that when metro train running through， the resilient wheel can effectively reduce the wheel/rail force， vibration of the wheel and axle box. Compared with the traditional rigid wheel， the vibration of rim is the most intense， followed by the vibration of traditional rigid wheel， and the vibration of web is the smallest. Based on the propesd dynamic parameters of the resilient wheel， the excellent frequency of the resilient wheel vibration is concentrated in 10 Hz to 50 Hz， and there is a peak around 25 Hz. The main frequency of the bridge vertical and lateral vibration is about 1 Hz. The resilient wheels can effectively reduce the mid-low frequency vibrations of LSCSB.

For fabricated steel-concrete composite beams composed of concrete slabs with reserved post-pouring holes and steel beam with arranged discrete shear connectors， the interface slip distribution theory of fabricated steel-concrete composite beam with discrete interface shear connection is studied. Based on the beam deformation theory， fabricated composite beams with discrete shear connection are divided into shear connection area and non-shear connection area and the interface slip differential equations are established respectively based the displacement continuity and deformation coordination conditions. The interface slip distribution expression of intermittent shear connection composite beam are formulated， and the analytical expression of interface slip distribution under concentrated load and uniform load are solved. Through comparing with the existing slip distribution equation of continuous shear connection composite beam and the measured data of fabricated composite beam test， the slip distribution algorithm is verified. The influence of various parameters on slip and deformation of fabricated composite beams is analized with the parameters as the height ratio of concrete slab to steel beam， the shear connection degree and the clustering degree （an index reflecting the degree of bond clustering， defined as the ratio of the number of shear connectors in a （row） reserved hole to the number of shear connectors in the beam）. The results show that the interface slip decreases with the increase of the shear connection degree， and increases with the increase of the height ratio and the clustering degree； the larger the clustering degree， the more uneven slip distribution， and peak value appears in the non-shear connection area.

Based on the static triaxial shear test， the stress-strain characteristics， the modulus attenuation properties， and the normalized stress-strain behavior of reinforcing rubber sand mixtures were analyzed. Five kinds of rubber content （0%， 10%， 20%， 30%， and 40%）， four kinds of geogrid reinforcing patterns （lateral arrangement with no layer/one layer/two layers/three layers）， and three kinds of confining pressure（50 kPa、100 kPa、200 kPa） were taken into account in tests. Results indicate that ①The geogrid reinforcement makes stress-strain curves of rubber sand mixture raised obviously， and the hardening characteristics of the reinforced specimens are enhanced. ②The stress-strain behavior of the rubber sand mixture could be simulated well by the extended Duncan-chang hyperbola model， and the model parameters are evaluated with rubber content in the rubber sand mixture. With the increase of rubber content， the initial modulus of the rubber sand mixture decreases， and the attenuation parameters can quantitatively reflect the degree of modulus attenuation. The attenuation degree of rubber sand mixture increases for geogrid reinforcing cases lateral arrangement with three layers/no layer/two layers/one layer， but the overall difference is insignificant. ③With the use of geogrid reinforced， the reference strain of the rubber sand is increased while the index of the stress-strain model is decreased. To illustrate， the degree of nonlinearity of the normalized stress-strain curve of the modulus is weakened. With the increase of the geogrid-reinforced density and rubber content， the reinforcement effect of geogrid on the stress-strain characteristics of rubber sand is more significant.

In order to understand the mechanical properties of shear stud connectors under combined tension and shear loading， five groups of model tests were tested， including uniaxial pull-out tests， uniaxial push-out tests， and combined tension and shear loading tests. Combined with finite element models， influence of concrete strength and stud size on shear capacity were analyzed， and the load-slip relationship， the ultimate shear capacity formula of shear stud connectors under tension and shear loading were proposed. The results show that as the applied tensile force ratio increase to 0.6， the shear stiffness reduces 69%； and the ratio of ultimate elastic capacity to ultimate shear capacity reduces from 0.55 to 0.24， and the ultimate shear capacity reduces 31%. The effects of concrete strength and tensile force ratio on the shear capacity of shear stud connectors are correlated. The proposed load-slip relationship and ultimate shear capacity formula under tension and shear loading can be applied to engineering design and calculation.

In order to obtain the fatigue stiffness degradation law of in-service concrete T-beams and carry out fatigue life prediction. Based on the theory of damage mechanics， a stepped stiffness model of concrete T-beams including cracking damage was constructed. Through the full-scale model of three 10 m concrete T beams， static and fatigue failure tests were carried out to obtain the evolution law of fatigue residual stiffness with the number of loads. The fatigue damage coefficient and stiffness degradation coefficient were introduced to establish a concrete T beam in service fatigue life prediction model. The analysis results show that with the increase of load， the residual stiffness of the bridge exhibits three-stage decay， in which the initial and later stages of fatigue decay rapidly， but account for a relatively small proportion of the whole life. The result shows that more than 80% of the whole service life is the main stage of bridge service， it is about 82.7% of the initial stiffness at the time of fatigue failure. Finally， according to the working behavior of in-service concrete T-girder bridges， a life prediction method for in-service reinforced concrete girder bridges is proposed， the related research results can provide theoretical support for the study of life prediction of such bridges.

In order to reduce the damage of concrete core tube of high-rise buildings caused by vibration， the seismic performance simulation method of concrete core tube of high-rise buildings based on static pushover analysis algorithm was studied. A high-rise building concrete core tube with buckling constraint bracing was selected as the research object， and the seismic performance of high-rise building concrete core tube based on static nappe analysis algorithm was simulated with software PKPM. The test results show that the distribution of the lateral force of the static nappe has great influence on the calculation results of the apex displacement angle and the base shear force of the concrete core tube in high-rise buildings. In the X-direction， the base shear curve of concrete core tube supported by buckling constraint increases exponentially. The stiffness of concrete core tube decreases and the proportion of column shear increases under strong vibration. When ductility coefficient is constant， the ratio of energy spectrum of high-rise concrete core tube is positively correlated with stiffness reduction coefficient. The damage of concrete core tube in high-rise building caused by longer strong earthquake duration increases with the increase of strong earthquake duration. With the increasing of the characteristic stiffness value， the proportion of the energy consumption of shear wall in the total hysteretic energy consumption ratio decreases， while the proportion of the energy consumption of frame beam and column increases and the distribution pattern is roughly linear.

Aiming at the problem that the existing protective structure can not achieve multi-objective ship-type flexible protection，a flexible fender which can protect small and medium-sized ships is proposed.The fender can be used with the existing protective structure.To determine the optimal form，the quasi-static compression tests of three different flexible fenders are carried out.And the protective performance of the optimal structural fender is analyzed through full scale impact test and numerical simulation.The results indicate that the failure modes of different specimens are similar under compression test.The outer plate shear failure， matrix cracking and fiber fracture occurred in all specimens.At the end of compression， the springback rate of each specimen was as high as 85%.Specimen 3 with energy dissipation core material is the optimal structure.For the drop weight impact test， the reduction rate of impact force reaches 97%.Fender deformation recovers completely after impact， and fender dissipates energy in the form of elastic energy dissipation.Under barge impact， the fender absorbs 63% of the collision energy and greatly reduces ship damage.In this condition， the fender mainly absorbs the collision energy with the collapse of the energy dissipating core material.

Aiming at the problem that deep learning-based iris segmentation models need a large number of parameters， computation cost， and space occupation， a lightweight iris segmentation model is proposed in this paper. First， the feature extraction network of Linknet is replaced with the improved lightweight deep neural network MobileNetv3. This design significantly improves the efficiency of the model while maintaining accuracy. Then， in order to reduce the loss of iris feature information， a multiscale feature extraction module is designed in this paper. Once again， an efficient parallel attention mechanism is introduced to suppress noise interference and enhance the weight of iris region pixels. Finally， the proposed model was compared with other iris segmentation models on three iris databases， and the results showed that the model achieved a better balance between iris segmentation accuracy and efficiency.

Aiming at the problem that there exists semantic gap between visual features and high-level emotional semantics and the subjectivity and ambiguity of emotional labels in image sentiment distribution learning， this paper proposes an Emotional Semantic Dynamic Graph Convolution Network （ESDGCN）. In this framework， the Emotion Activation Module （EAM） is constructed to automatically locate the emotional semantic regions to effectively mine the content representation that fits the emotional semantics. In addition， the Semantic Dynamic Graph Convolution Network （SDGCN） is to adaptively capture the semantic relevance between labels. Finally， we adopt the parallel structure to jointly consider local semantic emotional information and label correlations. Experimental results on three open emotional datasets demonstrate the effectiveness of the proposed method.

A multi view gait cycle detection method fitting the geometric features of lower limbs is proposed to address the issue of existing gait cycle detection methods being susceptible to changes in shooting angles. Firstly， the human posture topology in the gait video sequence was extracted by the MediaPipe model， simplifying the image preprocessing process. Then， by analyzing the periodic dynamic change law between the joint points in the human posture topology map under walking state， the inclination formed by the left shin and the horizontal ground and the Euclidean distance ratio from the midpoint of the left and right hip joints to the left and right ankle are extracted as features. Finally， the feature data were fitted into sinusoidal function waves by Fourier transform， and the gait period is detected based on the fitting results. Compared with the current mainstream gait cycle detection methods， the proposed method has achieved good front and back view and strabismus angle detection results.

There are massive data in big data sets， and when the data scale expands to a certain extent， the processing efficiency of discrete point detection is limited. Therefore， a dynamic outlier detection algorithm based on CART decision tree was proposed. Firstly， the abnormal data standard of large data set was divided， the data dispersion degree by variance was measured， the abnormal data sample association rule matrix by support vector machine was established， the abnormal data range of large data set was clarified， and the amount of outlier detection calculation by dynamic meshing strategy was reduced. Then， the classification and regression trees（CART） decision tree method was used to take Boolean detection at the branch nodes， unify the data to be detected as continuous data， arrange the training data set in ascending order， calculate the maximum information gain of the data， prune the decision tree until no non leaf nodes can be replaced， and obtain the dynamic detection results of outliers. Simulation results show that the proposed algorithm has high outlier detection accuracy， short detection time， significant computational advantages， and can provide positive help for the reliable application of large data sets.

In order to improve the imaging quality of the camera and improve the image definition， a fuzzy image quality restoration algorithm based on multi-channel visual attention was proposed. Based on the multi-channel visual attention mechanism， the coding network was constructed. The blurred image is input into the coding network， and the image was restored. At the same time， the ringing detection was introduced in the restoration process to eliminate the ringing area in the restored image and improve the quality and clarity of the restored image. The experimental results show that the proposed algorithm has better effect of de ringing phenomenon， high quality after image restoration， and better application efficiency.

The point-of-interest （POI） recommendation services provided by the location-based social network （LBSN） have become an important means of mining users' preference for POIs. The sparsity of user-POI matrix is the primary problem to be solved， and a large number of unknown values in implicit feedback cannot reflect user preferences. To improve recommendation precision， this paper proposes a point of interest recommendation algorithm integrating social geographical information based on weighted matrix factorization （SGWMF）. The social information is modeled through the power-law distribution. The check-in information of the user's friends is converted into the user's visit location preference. Secondly， the power-law distribution of geographical information is used to construct the user's visit location preference matrix to alleviate the data sparsity problem. Thirdly， in order to extend the effectiveness of the model， we improve the objective function by adding implicit feedback term. Finally， the experimental results on two datasets show that it has better performance than other POI recommendation algorithms and can improve the accuracy of recommendation results.

To solve the problem of information loss in pixel-level multimodal medical image fusion, an image fusion method using pixel correlation analysis (PCA) in Non-subsampled Shearlet Transform (NSST) domain is proposed. First, NSST decomposition is performed on the source images to obtain high and low frequency sub-bands. The intensity correlation factor between neighborhood pixels and central pixel is calculated using the proposed center pixel variance, and the correlation coefficient matrix of neighborhood pixels is constructed. The proposed correlation-sum of modified laplacian (C-SML) is used as the fusion rule for high-frequency sub-bands. The energy of the central pixel and the energy gradient information of the neighboring pixels of the low-frequency sub-bands are calculated to obtain the fusion decision map for low-frequency sub-bands. Finally, the fused image is obtained by inverse NSST. The experimental results about magnetic resonance imaging (MRI) and computed tomography (CT), positron emission tomography (PET), single-photon emission computed tomography （SPECT） brain images indicate that the proposed fusion method can well retain the significant information and texture details of the source images.

To tackle the motion blur in the process of acquiring remote sensing images， an algorithm for blind deblurring of remote sensing images is designed. The algorithm is based on the geometric property of image surfaces and the algebraic property of image pixels， and it utilizes Gaussian curvature and reweighted graph total variation. First， the reweighted graph total variational prior and Gaussian curvature prior were combined to obtain the skeleton image which not only retains the gradient and sharp edge information， but also removes the harmful structural information in the latent clean image. Then， the skeleton image is used to estimate the fuzzy kernel， and then the non-blind deblurring algorithm is used to obtain the clear image. Finally, simulation validation was conducted on 8 fuzzy remote sensing images in different scenarios, and the results showed that, compared with other advanced image deblurring algorithms， the peak signal-to-noise ratio of the recovery effect of the deblurring algorithm proposed is higher than that of the comparison algorithm by 2.76， 1.84， 3.11， 2.79， 3.35， 2.76 dB， respectively. The structure similarity is higher than that of the comparison algorithm by 0.0792、0.0604、0.0873、0.0801、0.0997、0.0906， respectively. The remote sensing images recovered by our proposed algorithm have clear edge contours and local details while improving the clarity of remote sensing images.

Aiming at the problem that Big data anomaly detection process is easily interfered by edge data， which leads to poor accuracy of Big data anomaly detection， a big data anomaly detection model based on Random forest algorithm was proposed. Firstly， the improved k-means algorithm was used to cluster the big data， and the principal component analysis method was used to extract the features of the big data. Then a big data anomaly detection model based on random forest classifier was built， the extracted features was inputted into the model， a decision tree was built， and the classification accuracy of the classifier was improved by dynamically updating the weight value of the decision tree. Finally， the classification results are output to complete the anomaly detection of big data. The experimental results show that the detection time of the proposed model is about 25 s， the average big data anomaly detection accuracy is 91%， and the false alarm rate is 4.5%.

Aiming to solve the aggregation problem of traditional uniform oriented FAST and rotated BRIEF（ORB） features in visual simultaneous localization and mapping（SLAM）， a uniform FAST corner extraction method is designed， which is based on grid division and laying to determinate key points. Furthermore， a corresponding loop detection method is designed based on uniform distribution of ORB features combined with brute force matching. Experiment results compared with BoW-based loop detection algorithms show that the proposed algorithm can significantly improve the accuracy of loop detection. Furthermore， a robot operating system（ROS） based loosely coupled semi-direct SLAM system is designed， which combine the uniform ORB feature loop detection module with direct sparse odometry（DSO）. The experimental results show that the proposed system has high map construction performance.

A distributed adaptive vibration suppression control method was investigated to effectively suppress the on-orbit vibration of large flexible satellite panels. Considering the influence of actuator and sensor installation position on the control effect， a complete distributed adaptive controller was designed based on Lyapunov theory by analyzing the coupling effect of vibration and output force between adjacent sub-modules. The simulation results show that the vibration suppression time of the proposed distributed control method is reduced by 40% compared with the distributed control method based on LQR control method and 50% compared with the centralized control method under the condition of continuous external interference. Furthermore， the proposed control method has an improved on-orbit vibration suppression effect and is of great significance for the stable operation of the satellite.

To improve the mechanization harvesting level of quinoa and solve the problems of a significant loss rate， high impurity rate， and poor feeding during harvesting of ordinary rice-wheat combine harvester， according to the characteristics of quinoa plants during the harvesting period， a sizeable self-propelled quinoa combine harvester was designed. The machine used flaring type small row spacing chain teeth feeding into the header， combined longitudinal axial flow threshing cylinder， unique woven screen concave， double reciprocating vibrating screen and other devices， cooperation wide bridge， threshing cylinder CVT regulation， and excellent space design to realize the smooth quinoa feeding and efficient threshing separation. Critical components for the design were analyzed， and a field experiment was carried out. The results of the field experiment showed that when the water content of quinoa grain was 14.42%， the threshing rate was 96.83%， the impurity rate was 4.41%， the damage rate was 0.2%， the header loss rate was 1.14%， the entrainment loss rate was 1.73%， the cleaning loss rate was 1.09%， the splash loss rate was 0.16%， the total loss rate was 4.13%. During the experiment， the machine runs smoothly and meets the mechanical harvesting of quinoa. This paper can provide some reference for the design and test of quinoa combine harvester.

In order to further explore the turning performance of ratooning rice harvester in the field， the relationship between turning radius and narrow track subsidence was comprehensively analyzed. The basic principle of field turning of tracked ratooning rice harvester was analyzed， and the driving force， slip rate， track subsidence and driving resistance of narrow track were calculated. The functional relationship between turning radius and narrow track subsidence was obtained by RecurDyn analysis. The simulation results show that with the increase of the turning radius， the driving wheel torque and narrow track subsidence on both sides decrease. The driving wheel torque deceased from 5835 N·m to 672.3 N·m. The peak values of driving wheel torque and narrow track subsidence were at the turning radius of 0. The reliability of the simulation results was verified by field experiments， the results show that with the increased of turning radius， the subsidence decreased from 186.24 mm to 103.57 mm. The experimental phenomena and calculation results were consistent with the RecurDyn simulation， proving the simulation results are reliable. This study can provide a reference for the turning theory research of ratooning rice harvester in the later period.

In view of the practical problems such as large seed consumption， large variation coefficient of hole number and lack of seed in hole holes， a roller scoop type precision hole sowing seeder with scoop tongue was designed in Gansu mulch planting environment. By analyzing the operation principle of the seed rower and seed rowing process， the main parameters such as the composition of the rolling spoon assembly and the size， installation number and installation angle of the scooping spoon were determined， and the effects of the main spoon depth， the installation angle of the scooping spoon and the angular speed of the seed rowing wheel on the seed rowing performance of the seed rower were analyzed by the response surface method. The test showed that when the depth of main scoop was 6.68 mm， the installation angle of scoop was 7.62° and the angular speed of seed releasing wheel was 3.22 rad/s， the qualified rate of hole number was 92.5%， the rate of missed seeding was 2.54%， the rate of reseeding was 4.96%， and the seed releasing performance was better. This study can provide a basis for the design of precision hole-sowing seeding device for flaxes.

Aiming at the problem of high soil content of residual film by mechanical recovery， a trommel with function of separating soil from residual film was designed. Through the analysis of kinetics of the residual film material in the device， the basic structure parameters of the device were determined. The rotational speed of the trommel， the feeding speed， the inclination angle of the trommel and the pitch of the spiral blade were selected as the test factors， and the soil removal rate， the rate of the leakage of residual film and the work efficiency were selected as the evaluation indicators. A four-factor， five-level test was designed using the Central-Composite-Design experimental design principle to analyze the effects of each factor on the operational performance of membrane soil separation. The comprehensive effects of various factors on the response index were analyzed by using Design-Expert software surface response diagram， which showed that the optimal rotational speed of the trommel， the feeding speed， the inclination angle of the trommel and the pitch of the spiral blade are 24.90 r/min， 11.52 kg/min， -2° and 699.99 mm，respectively. The experimental results under this parameter combination are 94.48%， 1.90‰ and 7.61 kg/min， respectively. The errors between the experimental results and the optimization results are 2.15%， 5.79%， 2.63%， respectively. The results indicate that the constructed model has good reliability. The device designed in this study meets the design requirements， can realize the effective separation of residual film and soil impurities， and is of great significance to the mitigation of rural ecological pollution and sustainable agricultural development.

Aiming at the dynamic obstacle avoidance problem during the flying process of the Flapping-wing Micro Air Vehicle （FWMAV）， a novel obstacle avoidance scheduling strategy integrating the global path planning and the locally dynamic path planning is proposed in this paper. The static comprehensive cost model is first built by considering both the performance constraints of the FWMAV and its threat constraints during the flight environment. Based on the static cost model， a time-varying collision constraint between the FWMAV and dynamic obstacles is defined and then the dynamic comprehensive cost model for the local obstacle avoidance is established. The improved ant colony algorithm is proposed for the obstacle avoidance scheduling strategy optimization. The results show that the proposed method can effectively handle the dynamic obstacle avoidance scheduling problem of the FWMAV under the known map and improve the dynamic obstacle avoidance scheduling strategy under the dynamic obstacles； meanwhile the improved ant colony algorithm can promote the efficiency of the dynamic path optimization to ensure the real-time requirement of the obstacle avoidance control of the FWMAV.