Abstract:To improve suspension regenerative power with reasonable vehicle ride comfort,sensitivity analysis and optimization of hydraulic parameters to a hydraulic-electrical regenerative suspension were carried out. The regenerative suspension consists of a spring and a hydra-electrical regenerative unit. Based on the suspension structure and principle,a simulation model of the hydra-electrical regenerative unit was established by AMESim software. And the model was verified by a prototype testing of the hydraulic-electrical regenerative unit. Taking ISIGHT software as a platform,sensitivities of hydraulic system parameters affecting car-body vertical acceleration and suspension regenerative power were analyzed by a quarter car vehicle mode in AMESim. The results show that,compared with recharging pressures and volumes of two accumulators,hydraulic motor displacement has a significant effect on both the vehicle vertical acceleration and suspension regenerative power. Moreover,taking the vehicle vertical acceleration RMS value of a traditional suspension as a constraint,the hydraulic system parameters were optimized to maximize the suspension average regenerative power. The results show that the average regenerative power is improved by 12.7% after optimization when the vehicle ride comfort is acceptable.

Abstract:By adding a hydraulic variable pump,two hub motors and an accumulator to a traditional rear-drive heavy vehicle,a new hydraulic hub-motor hybrid system was built,and the auxiliary drive and regenerative braking can be realized based on accumulator. Firstly,the flow controller of accumulator bleeder valve was designed based on the vehicle optimum slip efficiency to achieve coordinating control of vehicle driving force. And then,according to synthetic judgment of the feedback signals for the opening of the accelerator pedal,the opening of the brake pedal and the accumulator pressure,the driving and braking mode switching rules were divided. Moreover,the auxiliary driving and regenerative braking control strategy was developed. Finally,the control algorithm was simulated at the test driving cycle of prototype vehicle by co-simulation platform of MATLAB/Simulink and AMESim. According to the simulation results at the test driving cycle of prototype vehicle,the coordinated switch of operation mode was realized,and the vehicle power performance and fuel economy were obviously improved. Compared with the traditional trucks,the ratio of oil saving is up to 10.5%,and the maximum grade ability is increased by 10%~40% at different adhesion coefficient road.

Abstract:Most of the regenerative braking strategies only considered the stability on the braking direction and ignored the braking efficiency constancy,thus these researches may have defect under the ideal braking condition. A front driving electric vehicle was studied with the object to obtaining good braking and maximizing energy recovery rate. A regenerative braking strategy based on the multi-factor input fuzzy control was also proposed. Using the passage vehicle model,the front and rear axle braking force distribution was first set up according to the braking stability and ECE regulations. The front axle braking force was tried to be kept at the maximum at the same time. Second,the dynamic friction coefficient was used to predict the mechanical braking performance factor. Third,the battery state of charge,the braking strength and the estimated mechanical brake efficiency factor were introduced to the fuzzy controller. Finally,the distribution of regenerative braking force was obtained,and thus energy recovery was finished. The results show that with the new method,the braking performance constancy is improved in the frequent and constant intensity braking conditions. The braking energy recovery rate is increased by 18.5%. In the urban road condition with battery full power to zero,the energy recovery rate is increased by 5.3%.

Abstract:In order to improve the vehicle handling stability, an active rear independent pulse steering system(ARIPS)which integrates independent steering and active pulse steering was proposed, and theoretical analysis and experiment study were carried out. The simulation dynamics model equipped with ARIPS system was established to analyze the effects of installation and operation of pulse actuator on the suspension performance. The optimal pulse parameters were determined according to the simulation analysis and frequency analysis method. A control structure and algorithm were designed and a full vehicle model equipped with the steering actuator was built in Carsim and co-simulated with Simulink to verify the proposed system. A hydraulic steering system was designed and assembled for a Lexus to carry out road experiments to assess the applicability of the ARIPS system. Simulation and test results obtained have shown that the proposed system has better performance in terms of improving vehicle handling stability compared with ARS and ARPS system. Meanwhile, the proposed system is economical and feasible,providing a new research space and experimental basis to improve the performance of 4WS system.

Abstract:Variable joints are the crucial structures for changing topological characteristics of variable topology mechanisms. Design of variable joints is a challenge for the type synthesis of variable topology mechanism. Based on the concept and method of design catalogue,the design catalogues of variable joints were proposed to design the structures of variable joints. Adopting the arithmetic operation of constraint functions,the constraint variation features of variable joints were described in the three processes of topological variations (including changing the axis azimuth,changing the numbers and changing the types),respectively. Based on summarizing and designing the corresponding variable structures of general joints,the design catalogues of variable joints were established through classifying and compiling the design information,including the ways of topological variations,constraint variation features,and structures of variable joints. Meanwhile,the example shows that the design catalogues of variable joints are applicable to design the structures of variable joints for variable topology mechanisms effectively. This method provides convenience for type synthesis of variable topology mechanisms with variable joints.

Abstract:A theoretical calculation model was established to study the static characteristics of porous graphite aerostatic thrust bearings. Based on the proposed model,the effect of the related factors,such as porous density,surface-restricted layer,external gas pressure and mass flow rate on the static characteristics of porous aerostatic thrust bearings was analyzed. Theoretical calculation results show that the load-carrying capacity of the bearing is negatively correlated with the graphite density and positively correlated with the gas supply pressure,but it is smaller than that of the surface-restricted layer. Gas mass flow rate is negatively correlated with the graphite density and positively correlated with the gas supply pressure,but it is also smaller than that of the surface-restricted layer. Bearing stiffness is positively correlated with the gas supply pressure and graphite density,but it is smaller than that of the surface-restricted layer. According to the results,corresponding function diagrams were plotted. The test rig was then designed to plot the static characteristic curve of porous aerostatic thrust bearings,including the load-carrying capacity and gas film thickness. The numerical method was eventually verified by the experimental results.

Abstract:In order to solve the calibration problem of the application of REVO 5-axis system,which was designed to be applied in the orthogonal coordinate measuring machines (CMMs) and non-orthogonal CMM,some techniques based on symmetrical and reversal principle for calibrating the parameters and error items of REVO probe head were proposed and discussed in detail. The calibration of the parameters and error items of REVO probe head in the non-orthogonal CMM was realized only by measuring some gauge blocks with one CMM axis moving in a short distance,which avoided the introduced error due to the motion errors of the CMM axes moving in a large scale. The accuracy and effectiveness of the calibration techniques was proved by experiments and practice. After the calibration and error compensation,the average measurement error was reduced to 0.8 μm from 18.1 μm. The results show that the proposed methods are easy to operate and be traced to the source,and with high accuracy.

Abstract:The vibrating griddle system is a kind of nonlinear multi-parameter dynamical system with high non-smoothness,and traditional bifurcation criterion can’t be applied directly. Therefore,a new explicit bifurcation criterion independent on eigenvalue calculation was adopted to achieve the anti-control of double Hopf bifurcation for vibrating griddle system. Firstly,the Poincaré mapping at the fixed point was obtained according to the motion equation of the system. Then,a linear feedback controller was applied to the system to obtain the controlled Poincaré mapping,and the explicit critical condition of double Hopf bifurcation was obtained according to the bifurcation critical criterion. Finally,numerical simulation of the two types of systems was carried out by the modal superposition method. The results show that the linear feedback controller can effectively achieve the anti-control of double Hopf bifurcation by adjusting the control parameters under the same system parameters. Double Hopf bifurcation can improve the working efficiency of some vibration machinery,so it has certain practical significance.

Abstract:Actual engineering structures are often designed using deterministic parameters，which may lead to high failure probability. This paper proposed a reliability-based structural dynamic topology method，in which structural reliability analysis was incorporated into the topology optimization procedure. The geometry dimensions and material volume were considered as uncertain parameters，and it was assumed that they obey a Gaussian distribution. It is a two-nested optimization problem when the structural reliability analysis is considered as constraints into the topology optimization，which results in low efficiency and cannot be used in practice. To this end，a new decouple strategy was proposed to decouple the reliability analysis from the topology optimization procedure. In this case，structure reliability analysis and dynamic topology optimization become two independent optimization cycles，and the computational efficiency is improved enormously. The design problem was then constructed so as to maximize the first eigenfrequency and to meet the volume and reliability requirement. SIMP and MMA were combined to successfully solve the design problem. The proposed method can produce various topologies that satisfy different reliability requirement，and its validity is demonstrated by one benchmark example.

Abstract:Transformer vibration and noise are mainly caused by the magnetostriction of silicon steel sheets. Since the magnetostriction of silicon steel sheets can be aggravated by the harmonic,the vibration and noise of transformer will be more excited if harmonic flux is flowed within transformer. In this paper,the vibration mode of the core of a four-column single-phase converter transformer prototype was built,and the influence of harmonic flux on the magnetostriction of silicon steel sheets were discussed. From the view point of acoustics,the relevance of harmonic flux and noise of transformer was verified. Second,based on the basic principle of inductive filtering method,the noise reduction feasibility of this method was theoretically analyzed. Finally,one 12 pulses rectifier system was built. The experimental data shows that the converter transformer noise can be effectively suppressed by using the inductive filtering method,and noise reduction performance of this filtering method is more preferable,compared with other traditional filtering methods.

Abstract:In order to improve the intelligent diagnosis level of an on-load tap-changer (OLTC) mechanical condition,a feature extraction method was proposed based on improved variational mode decomposition (IVMD) and weight divergence. The harmony search (HS) algorithm was used to optimize the parameter selection of the relevance vector machine (RVM). The mechanical vibration signals of OLTC under different conditions were measured by simulation experiments. The OLTC vibration signals were then decomposed into a series of finite-bandwidth intrinsic mode function (IMF) by IVMD. Next,Kullback–Leibler divergence (K-L divergence) of the IMF and original vibration signal was calculated. The K-L divergence was multiplied by the weight coefficient to obtain the weight divergence,which represented the time-frequency domain complexity of the OLTC mechanical vibration signals. Simultaneously,the multi-classification model of RVM was constructed. The selections of kernel function parameters were optimized by HS,and the classification of weight divergence was realized effectively. The experimental and data analysis results show that the proposed integrated model exhibits high fault diagnosis accuracy. This model can accurately extract the characteristics of mechanical condition,and provide reference for the practical OLTC intelligent fault diagnosis.

Abstract:This paper focused on the dual PWM converter and battery of the direct drive permanent magnet wind power generation system. In order to obtain the maximum benefit of wind power system，a capacity optimization model of converter and battery was established. The overall capacity optimization strategy of dual PWM converter and battery was proposed based on nonlinear programming genetic algorithm. The strategy analyzes the benefits of wind power system，the loss energy efficiency，and the costs of dual PWM converters and batteries. An objective function considering national restrictions on the fluctuation of output power of wind field was then established and solved by a nonlinear programming genetic algorithm，which aims at the maximum annual income of wind power system. To verify this strategy，a wind power system was emulated. The results show that，compared with the traditional capacity allocation method，the annual costs of wind power system can be reduced by 10.3%.

Abstract:A quantile regression model was established based on spline estimation. Based on the output data of photovoltaic panel,the curve of power was fitted,which was compared with ordinary least squares regression model and simple quantile regression model. The results show that the quantile regression model can give much more accurate and effective analysis on the influence of relative factors on the output power of photovoltaic panels,improve the efficiency of solar energy,provide the complete distribution of output power,and reduce the negative impact of photovoltaic panel when connected to the grid.

Abstract:Considering the situation that photovoltaicpower generation is affected by a variety of weather factors,a hybrid model was proposed based on warped Gaussian process to predict the power generation,where probability of photovoltaic power generation at any time in one day can be realized and prediction point and prediction interval can be obtained. Firstly,multivariate adaptive regression splines model was used to reduce multidimensional input variables,and to obtain the prior data of test. According to the type of weather,fuzzy C-means algorithm was then used to divide the training data and prior data of test,and to obtain the similar samples. The warped Gaussian process was also used to estimate the test data. Finally,bagging algorithm was used to realize the integrated study,and to obtain the prediction interval and prediction point. By the simulation and experimental results,the validity and reliability of this hybrid model was verified. The results show that the hybrid model improves both accuracy and practicability,compared with Gaussian process predictions and BP quantile regression neural network predictions.

Abstract:Traditional synchronous demodulation of MEMS (Micro-Electro-Mechanical System) gyroscope is based on phase relationship of drive and sense positions. This relationship depends on the work mode of gyro. Moreover,the phase jitter of drive displacement is large,which makes the phase alignment of demodulator hard. To solve these problems,a new demodulation method based on quadrature error alignment was proposed,which is independent on work mode of gyro. Demodulator reference was extracted from PLL (Phase-locked loop) output,which has low jitter. Phase shifter of sense channel was used to delay quadrature error by 90°,compared with the reference signal. Therefore,Coriolis signal and the reference were automatically in-phase,and successful demodulation was achieved. To demonstrate this method,drive-mode and sense-mode circuits were elaborately implemented,and several critical blocks were care fully de signed. The demodulation of MEMS gyro shows that the vibration oscillation is stable and the operation of sense channel is correct. The scale factor is 1.415 mV/(°·s),and the bias instability is 108°/h. Moreover,the measurement results verify the validity of the demodulation method,providing solid foundation for further research. The method is also applicable to other vibratory MEMS gyroscopes.

Abstract:A novel low-voltage and low-dissipation pseudo ring voltage-controlled oscillator (VCO) was proposed,based on cross coupling technology. The schematic includes the pseudo-differential ring VCO core and output shaping buffer. An inverter controlled by tail current source was used as the delay cell,which composed the novel low-voltage and low-dissipation pseudo-differential ring VCO. Moreover,linear technology was applied to improve the tuning linearity. Utilizing the output buffer circuit to trim the ring VCO’s wave form,the proposed circuits eliminate the limitation of output swing which cannot reach the rail-to-rail output swing. The circuit was designed by 0.13 μm standard CMOS process,and simulated by the spectre in cadence under the supply voltage of 1.2V. The pre-simulation results show that the VCO’s phase noise is only -100.58 dBc/Hz@1MHz,the power dissipation is 0.92 mW,the design shows a good tuning linearity between the voltage range from 0.45 to 1V,the frequency tuning range is from 0.303 to 1.63 GHz,and it can also work at 1V supply voltage.

Abstract:For electromagnetic environment complex evaluation,a novel evaluation method was proposed based on S-transform and probabilistic neural network (PNN). S-transform was applied to perform time-frequency analysis on the electromagnetic environment disturbance samples,the evaluation parameters such as time occupation,frequency occupation and energy occupation of the samples were extracted synchronously,physical interpretation of each parameter was analyzed,and the calculation formulas of them were shown. At the same time,frequency coincidence,modulation similarity and background noise intensity were selected as important evaluation indicators. These parameters were then used to train a PNN which was adopted to evaluate environmental complexity. The simulation results show that the proposed method has integrity of parameter extraction and relatively high evaluation accuracy,and it can also give excellent evaluation for high level noises background and small training set.

Abstract:Most existing methods of abnormal behavior detection merely use hand-crafted features to represent behavior,which may be costly. Moreover,choice and design of hand-crafted features can be difficult in the complex scene without prior knowledge. In order to solve this problem,combining the stacked denoising autoencoders (SDAE) and improved dense trajectories,a new approach for abnormal behavior detection was proposed by using deep-learned features. To effectively represent the object behavior,two SDAE were utilized to automatically learn appearance feature and motion feature,respectively,which were constrained in the space-time volume of dense trajectories to reduce the computational complexity. The vision words were also exploited to describe the behavior using the method of bag of words. In order to enhance the discriminating power of these features,a novel method was adopted for feature fusing by using weighted correlation similarity measurement. The sparse representation was applied to detect abnormal behaviors via sparse reconstruction costs. Experiments results show the effectiveness of the proposed method in comparison with other state-of-the-art methods on the public databases CAVIAR and BOSS for abnormal behavior detection.

Abstract:Video multi-target tracking is an important problem in the field of computer vision. In order to solve the problem where the target is easy to lose due to target scaling,rotation,distortion and occlusion,this paper proposed a multi-target tracking algorithm based on ORB feature point . First,the "moving edge growth" algorithm was used to obtain target blocks. Next,targets were associated by matching the ORB features of target blocks with feature templates. The matching process enables target templates to be updated in the real time by eliminating the old feature information from the noise and adding new feature information. In this way,effectiveness of feature template is guaranteed in the real time,resulting in greater reliability of matching during the tracking process. Experimental results demonstrate the ability of the proposed algorithm to robustly track targets even if the targets are deformed or partially occluded.

Abstract:An approach to segment ocular optical coherence tomography images with age-related macular degeneration was developed. The main advantage is to decrease computational loads while maintaining high accuracy through the following techniques: Fisher’s discriminant analysis for initial location of layer interfaces,curvature calculation for drusen detection,and refining interfaces using Kalman filters. Validation on 220 images of 20 volumes shows that three layer interfaces in each image can be segmented within 42 milliseconds with an average absolute error of layer interface below 3.29 μm. Compared with a state-of-the-art method,the proposed method is 40 times faster and maintains similar or significantly better accuracy,which is better suited for clinical usage.

Abstract:In order to enhance the temporal relevance of retrieval result,the text feature extraction and algorithm of multi-label classification were applied to potential temporal intention classification of literature retrieval. From the perspective of retrieving the classification of potential temporal intentions,an algorithm was proposed to automatically classifiy potential temporal intentions of literature,based on text temporal information extraction and labeled LDA. Firstly,by use of such temporal information,the potential temporal intention of literature retrieval was mapped onto specific temporal categories based on temporal information gained from literature. Secondly,the distribution features of temporal phrases across disciplines were used to optimize the process of label selection of the classification model of labeled LDA in order to reduce the impact of sparsity of temporal information on the learning process of classification features. Finally,the proposed algorithm was compared with other multi-label classification algorithms in specific experiments,and the accuracy of automated classification of potential temporal intentions of literature retrieval was analyzed and evaluated. The result shows that the AUC value of the proposed algorithm reaches 94.3%,which increases approximately 4.3%,compared with the algorithm of ECC (Ensembles of Classifler Chains). In addition,the present algorithm has produced favorable classifying effects in different disciplines. Thus,it is an effective learning method for potential temporal intention of literature retrieval.