Abstract:Due to the inaccuracy of potential energy method in calculation of time-varying mesh stiffness of helical gears, a stiffness correction algorithm was proposed. Considering the different expressions for the length of contact lines of single tooth on two kinds of situations in which the transverse contact ratio is greater or less than the overlap ratio, a non-uniform cantilever beam model was established when root circle and base circle misaligned, and then the mesh stiffness of helical gears was derived and calculated by using slice-integral method. By comparing with ISO standard and finite element method, the feasibility of the proposed correction algorithm was verified. Meanwhile, a parametric study was conducted to investigate the effects of various parameters, such as helix angle, normal module, tooth number, face width and normal pressure angle on the behavior of mesh stiffness. The calculation and analysis indicate that the relative time of the engaging-in section is related to the proportion values of transverse contact ratio and overlap ratio. Variation of gear parameters affects the fluctuation value of total mesh stiffness and average mesh stiffness by changing the contact ratios and single mesh stiffness. In addition, the fluctuation is little when the transverse contact ratio or overlap ratio is close to an integer, while it fluctuates more intensively when the total contact ratio is close to an integer. Compared with the traditional potential energy method, the precision of correction algorithm in calculating time-varying mesh stiffness of helical gears is obviously improved. It has relatively better practicability in the accurate calculation of stiffness excitation of helical gears.

Abstract:In view of the limitations that the tuning of shock absorber costs an engineer who depends on experience much time and strength, the thought of reverse solution was introduced, and then the forward modeling idea of shock absorber and reverse solution of key parameters were studied. Firstly, according to the thought of combining finite element analysis and least squares, a characteristic forward model based on large deflection was established. Furthermore, the obtained analysis results clearly identify some significant parameters which have a large impact on the process of the tuning of shock absorber. Based on the damping characteristic curve of shock absorber, the reverse model was established, which takes the errors between the simulation and test data as the objective function and takes the key parameters as the unknown parameters. Finally, some parameters of throttle-slices which are important to valve deflection were identified by using GA. The simulation results of parametric model after reversing agree well with the test data. This study provides a theoretical foundation for parameter optimization of shock absorber, in the case of the unknown important parameters of shock absorber. Meanwhile, this method provides a basis for the tuning of damper performance.

Abstract:In order to improve the mechanical response and fatigue life of the flexible spline (FS) during the assembly and meshing of the rigid-flexible wheel gear of the harmonic drive, an assembly and meshing analysis method of rigid-flexible gear system based on rigid-flexible coupling and transient dynamic analysis theory was proposed. Stress distribution and fatigue failure position of FS were obtained more accurately and reasonably. The sensitivity of the structure parameters of FS and material property to its fatigue life indicates that the key parameters of the fatigue design of FS, and the fatigue life size effect of FS which has sensitive range, are also noted. In addition, the fatigue life model of FS was established. The results show that the mechanical and fatigue life analysis of the rigid-flexible gear system of the harmonic drive cannot ignore the influence of the assembly and meshing process. The design of flexible wheel should avoid the sensitive range of fatigue life size effect to improve the service life of harmonic drive.

Abstract:A groove spoiler can effectively reduce vehicle sunroof buffeting noise. In order to have a better understanding of sunroof buffeting noise reduction mechanism associated with groove spoilers, a test platform of groove and uniform spoiler was built. Wind tunnel experiments were performed to investigate the surface pressure field downstream of uniform and grooved spoilers and to observe the effects of the grooves on the wall pressure. The test results show that the presence of grooves in the spoiler moves the reattachment point upstream and reduces the recirculation region length. Compared with the uniform spoiler, an initial spanwise phase difference was observed behind the spoiler in the presence of the groove, which decreased the coherence of the wall pressure, and the wall pressure had a big decay rate in the spanwise direction. Grooves in the spoiler can obviously disturb the downstream flow, and thus it can weaken the primary aerodynamic excitation for the vehicle cabin.

Abstract:Based on coupled heat transfer theory, a model of turbine box with waste gate was built, and turbine box, heat shield and bearing body was tied as an assembly to be heat transfer analyzed. Temperature and thermal stress analysis of bearing body were then obtained. The results show that temperature is gradually reduced from turbine box to bearing body, which presents an obvious temperature gradient. And the temperature of turbine box is about 71.5℃ lower than original gas temperature. Because of good insulation of heat shield and dual cooling of cooled water and oil, the temperature of bearing body is low. However, the thermal stress of bearing body is high due to its temperature difference between inside and outside surface. Compared with the test results, the maximum deviation between the simulated and experimental value is 7.2%, which verifies that this simulation method has high precision and can provide a theoretical basis for the design and optimization of turbocharger.

Abstract:Taking the ring assembly plane of cylinder part of coaxial optical system as the research object, the principle of tilt error transfer and compensation of fiducial axis in the case of multiple parts assembling was studied. Firstly, optical alignment of coaxial optical system and typical centering fiducial axis transfer paths were analyzed. And then error measurement and Least Square Method were conducted to fit the ring assembly plane of cylinder part and to get the coefficients of least-squares plane equation. By the theory of 3D geometry transformation, the transformation matrices precisely describing the tilt error of bottom face and top face in a single part, the transformation matrices of two coordinate systems of assembly joint surface in the case of two parts assembling and the function relationship between the angle between two Normal Lines of Initial Bottom Surface and End Top Surface (ANLIBSETS) and the Relative Load Angle (RLA) in the case of multiple parts assembling were established. Aiming at different types of centering fiducial axis transfer paths and applying different genetic algorithm plans, the optimization of ANLIBSETS was achieved. The method of solving the error of RLA was proposed. Finally, an optical alignment method of coaxial optical system based on global optimization alignment method was proposed. The feasibility and practicability of this method are verified by an example of a coaxial optical system.

Abstract:To develop a four-degrees-of-freedom (DOF) dynamic model for B-double vehicles based on linear tire characteristics, a modeling method was proposed where the system was studied from a whole view. B-double vehicles were made of three vehicle units, including tractor, first semitrailer and second semitrailer. This method carried out the analysis on force and moment equilibrium of three vehicle units, moment equilibrium of second and third vehicle unit, and moment equilibrium of third vehicle unit, and then four differential equations were deduced and solved further. Compared with traditional method taking the analysis on force and moment equilibrium of each vehicle unit, respectively, six differential equations were then deduced. The advantages of whole method were that it did not need to overmuch substitute and solve the constraint conditions between vehicle unit, which decreased the tedious procedures during simplification and avoided the errors in calculations effectively. With the step angle input of tractor steering wheel, simulation results of these two methods are the same asthat of MATLAB, which verifies the validity of the whole method and lays the foundation for more complex dynamic model of multi-trailers combination vehicles in the next step.The results of physical parameter simulation for B-double vehicles were analyzed under low speed and high speed working conditions, respectively. It indicates that B-double vehicles possess rearward amplification (RWA) and are prone to instability more easily at high speed, which further verifies the validity of whole method.

Abstract:According to single-motor plug-in hybrid electric vehicle with Continuous Variable Transmission (CVT), a novel design method of power and control parameters was proposed. The system efficiency model for each mode of Plug-in Hybrid Electric Vehicl (PHEV) was built, the mode switching rules based on system efficiency was then obtained, and the adjustment of the mode switching rules through multiplying the mode switching curve with control parameters was realized. Fully considering the influencing factors of fuel economy, the power source, battery number and final drive ratio were regarded as the power parameters. By using Matlab/Simulink, the vehicle economy simulation model was built, and "City-Suburban-Highway-Suburban-City" comprehensive driving conditions were constructed taking the reduction of the equivalent fuel consumption as the optimization target. The PHEV dynamic parameters and controlling parameters of mode switching rules were optimized under the comprehensive driving cycle by using Genetic Algorithm (GA). The result demonstrates that, by using the method proposed in this paper, a set of reasonable power and control system parameters can be optimized to lower the vehicle equivalent fuel consumption, where the equivalent fuel consumption per 100 km can be reduced by 7.2% when compared with that of non-optimization cases.

Abstract:Considering employing the electric vehicles to deliver parts to stations for automotive assembly lines based on in-plant milk-run delivery strategy, an electric vehicle delivery routing and battery swap station location problem was presented, and a mathematical programming model with an objective function of minimizing total cost of the system was set up. To tackle this complicated problem, the property was analyzed, and a two-phase dynamic programming method was adopted to obtain the global optimum for small scale problems. For medium and large scale problems, both the population decomposition strategy and the depth neighborhood search operator based on Lévy flight were applied to develop an improved discrete cuckoo search algorithm. Finally, through the comparison of the two-phase dynamic programming method, real genetic algorithm and modified artificial bee colony algorithm, the simulation experiments were carried out to illustrate the effectiveness and great advantages in stability, deep searching ability and convergence of the algorithm.

Abstract:The way of using optimal control theory to implement the optimal fuel control strategy of hybrid excavator is limited, because its computational complexity is large and the working conditions must be known in advance for global optimization. A real-time optimal fuel control strategy was proposed in this paper to solve the problem. An engine model of "speed-power-fuel consumption rate" was established. Under the constraint of DC bus voltage stability, the power compensation of the energy storage system was calculated as a control instruction, which can make the engine work efficiently. Finite control set model predictive control algorithm was proposed to follow the instruction speedily and flexibly. Through the simulation, the effectiveness of the proposed approach was demonstrated. Engineering practice results indicate that the fuel consumption is 82.2% and 77.6% of the prediction of the traditional model with flat light load and heavy load, respectively.

Abstract:Due to the shortcomings of traditional fault diagnosis system, such as too complicated hardware system and fault recognition algorithm, a distributed intelligent fault diagnosis system based on particle filter was proposed and studied. Real-time collection of distributed multi-variable parameters was realized by adopting ZigBee wireless sensor network, on-line processes variable data based on particle filter, and precise estimate about real system states were obtained based on simple pattern recognizing algorithm in order to realize the intelligent forecast and diagnose for system fault. The distributed fault diagnosis system includes ZigBee network, particle filter algorithm, system states model and malfunction mode recognition. Particle filter can filter data collected by sensor, suppress and eliminate the interference or significant error that affects the estimate of system states based on sequential importance sampling and Monte-Carlo method. Finding a system state model that has the minimum sum of residuals with an estimate curve about system states from a particle filter is the process of the malfunction mode recognition. Realization of the distributed intelligent fault diagnosis system and the result of the experiment show that the system can realize the remote monitor, accurate state estimation and fault diagnose, and it has the advantage of low cost, high reliability and easy to realize. The work can expand the application range of distributed sensor network and improve the diagnosis level of the fault diagnosis system.

Abstract:This paper proposed a continuous algorithm for distribution network reconfiguration (DNR) based on efficient encoding of solution space. By estimating the exchange range of switch exchange through deduced approximate formula of network loss, the solution space was compressed and the efficiency of optimization was improved. To avoid directly solving discrete variables, a double-population solution space including discrete variables and continuous variables solutions was established, which can reduce the amount of calculation and is suitable to apply continuous variable optimization method to solve DNR problem. After reducing the radius of the confidence interval variables, two kinds of non-effective solutions were avoided, and the number of times of power flow calculation was also decreased. The improved crisscross optimization algorithm improves the convergence speed and precision. Simulation results verify the correctness and effectiveness of the proposed algorithm.

Abstract:In order to enhance the security and reliability of the signal transmission in the harsh electrical noisy environment, an isolated communication chip was proposed and designed to realize the remote control of the equipment by SPI data link. The advantages and disadvantages of two current SPI isolation schemes were analyzed. Considering the isolation method, circuit complexity, cost, reliability, and other factors, the chip uses the “balanced” two-wire technology and encodes the four SPI signals into DC-free pulse that can be coupled by a transformer, which can improve the accuracy of data transmission and system reliability. The chip was designed and fabricated in GSMC 0.18 μm CMOS standard process, with a total chip area of 1.33×1.45 mm2. Test results show that the chip can reach a bit error ratio of 10-9 at 1 Mbps. The maximum cable length supported at a data rate of 0.5 Mbps can be up to 50 meters. It achieves the flexible network configuration of the remote controlled device. Compared with other similar isolation schemes, the designed chip is a low-cost, highly reliable and structural optimization solution for remote control.

Abstract:As the data imbalance of pipeline working conditions decreases the accuracy of the pipeline leakage diagnosis, a method of pipeline leak detection and location based on imbalance data was proposed. First, the imbalance data of different working conditions were processed by K-means clustering algorithm and under-sampling to achieve the balance data. Then, the Fischer-Burmeister function was introduced into the learning process of the twin support vector machine (TWSVM), in order to avoid the matrix inversion calculation, and the balance data were input into the improved TWSVM to distinguish the pipeline leakage. Leak location was obtained by the cross-correlation function method. Moreover, a flow model of pipeline was put forward based on the Flowmaster software, and the proposed method was used to identify pipeline leakage. The experimental results show that the proposed method is more effective than the classical TWSVM and the Lagrange TWSVM to identify the pipeline leakage aperture and location.

Abstract:Infrared complex background suppression is an important part of infrared dim target detection, which directly affects the target detection probability and false alarm rate of subsequent algorithms. As the isotropic bilateral filtering background suppression method can not change the background prediction direction and remain a large residual in the direction of the structured cloud edge, in this paper, an anisotropic bilateral filter which adapts the filter parameters including filter scale, mask size and filter direction by using the local characteristics of the image was designed. It separates the target from background more precisely. The test results show that the proposed method has a signal to cluter ratio gain for target and a background suppression operator for clutter, and both are up to 4 with the input signal to clutter ratio of 4.

Abstract:An improved Hidden Markov Models (HMM) was proposed to recognize the user's behavior. In order to improve the learning efficiency of Baum-Welch algorithm in HMM, and to solve the problem of initial sensitivity, the improved GA s used to optimize the initial parameters of HMM, in which the Chaos operator is utilized to avoid the problem of stagnation and premature convergence of the traditional GA in the convergence process. Finally, the experiment results based on ADLs data in UCI show the algorithm's availability and reliability for user's behavior recognition.

Abstract:Aiming at solving the representation and query efficiency in massive and dynamic dataset on storage system, a Multi-group Balance Matrix Bloom Filter (M-BMBF) and the algorithms on insertion and searching of data element were proposed. M-BMBF initiates a r×m matrix Bloom filter according to the size of dataset, and it introduces multiple located hash functions which can be used to divide the matrix Bloom filter into multi-group to achieve balanced insertion and efficient query operations. In order to slow down the bits consumption rate in Bloom filter when a new element is inserted, a longest-bit match filling algorithm was proposed, which selects a Bloom filter as the destination position for insertion from the candidate Bloom filters according to the rule that fewest bits will be changed due to this insertion operation. Experiment results show that compared with the classical Split Bloom Filter, M-BMBF can efficiently save storage space and decrease the misjudgment rate, while its time consume is constant.

Abstract:At present, with the development of the depth sensor, the on-line method of 3D reconstruction is realized. The difficulty of the online reconstruction is how to convert multiple dynamic overlapping depth maps into a three-dimensional model in real time under the premise of better reconstruction effect and reconstruction scale. To solve this problem, this paper constructed an efficient spatial voxel data structure based on the spatial index strategy, improving the hierarchical grid data structure of the traditional volume fusion method and realizing the real-time access to the hidden surface data. These surface data are only stored during the observation to achieve the sensor movement in the process of online scene reconstruction. The algorithm performs interactive real-time reconstruction of fine-grained detail and large-scale environment by completing several core stages, such as depth map preprocessing, camera pose estimation, depth map fusion and surface rendering, on the GPU (Graphics Processing Pipeline). The experimental results show that the average reconstruction time is 21.6 ms, the ICP pose estimation is 15 times, and the average frame rendering rate is increased by 13.3% when the reconstruction time is 8.0 ms and the reconstruction time is 21.6 ms, realizing the real - time 3D reconstruction of large scale scenes.

Abstract:Under the unconstrained conditions, intra-personal variation is much larger than the inter-personal variation in face images due to the affecting factors such as expression, posture, illumination and background etc. To reduce the influence of larger intra-personal on face verification, we proposed a similarity metric learning method with priori similarity and priori distance constraint by combining weighted subspace.First, the weighted intra-personal covariance matrix is learned by employing intra-personal face samples. By projecting into the intra-subspace, robust face feature representations can be obtained from face images.Second, we set up the similarity metric learning model with priori similarity and priori distance constraint, which effectively employs the similarity and discrimination information of samples that are in pairs, and the learned metric matrix can improve the robustness to intra-personal and discrimination to inter-personal.Finally, the updated metric matrix is used to compute the similarity scores of face-pairs. The experiments have been conducted on the Labeled Faces in the Wild (LFW) dataset, which shows the effectiveness of our proposed model. Compared with other metric learning methods, our learned metric matrix has higher accuracy rate for evaluating the face-pair similarity, and achieves a verification rate of 91.2% on the restricted setting.