YANG Wei , ZHAO Huyi , SHU Hong
2019, 42(2):1-10. DOI: 10.11835/j.issn.1000-582X.2019.02.001
Abstract:In order to improve the safety of AEB (autonomous emergency braking) pedestrian protection, a hierarchical pedestrian collision avoidance strategy based on upper fuzzy control and lower PID control was proposed. Taking an E-class SUV vehicle as the research object, its dynamic model was established. Based on the real pedestrian test scenarios at home and abroad, the TTC (time to collision) risk assessment model was established. Then the control strategies were simulated and verified through the joint simulation of Matlab and CarSim. The simulation results show that the strategies of the pedestrian collision avoidance system can satisfy the domestic pedestrian test condition standards, and the minimum safe distance from vehicle to pedestrians is 0.9 m. The fuzzy control can automatically adjust the braking strength, the output deceleration range is controlled within 4.8 m/s2 to 6.1 m/s2 for better comfort on the premise of ensuring safety. The risk assessment model can correctly send out pedestrian collision warning signals without missed alarm and false alarm.
JIA Changwang , LU Yongjie , YANG Shaopu , ZHANG Guangfeng
2019, 42(2):11-19. DOI: 10.11835/j.issn.1000-582X.2019.02.002
Abstract:A three-axle heavy-duty vehicle model was built based on the TruckSim vehicle simulation software in order to improve the safety performance of the vehicle under the steering braking condition.The mechanical properties of three-axle vehicles under steering braking conditions were analyzed.Based on the analysis results, a three-axis vehicle steering brake cooperative controller was designed by reducing braking force.A fuzzy controller for slip ratio distribution was designed for the case that the vehicle was understeering.The control effect of ABS control and coordinated control under steering braking conditions were examined by using co-simulation with TruckSim and Simulink.The simulation results show that the coordinated controller improves the steering stability and braking safety of the three-axle heavy-duty vehicle compared with the ABS controller under steering braking conditions.
LI Zhe , ZHENG Ling , HU Yiming , LI Yinong
2019, 42(2):20-29. DOI: 10.11835/j.issn.1000-582X.2019.02.003
Abstract:The four-wheel electric vehicles drive the vehicle independently through the in-wheel motor, which causes the electromagnetic force output fluctuation directly acts on the wheels and the suspension, resulting in deterioration of the vehicle's dynamic performance. The Fourier series method was adopted in this research to develop an in-wheel motor-electric vehicle (IWM-EV) co-model with active suspension.And then, a co-operative parameter optimization via (multi-objective particle swarm optimization) MOPSO was proposed to weaken the negative vibration effects caused by electromechanical coupling in in-wheel motor system. The simulation results has testified its effectiveness.
LIN Xiao , LIU Yang , XU Lixiong , MA Chenxiao , ZHU Jiayuan
2019, 42(2):30-40. DOI: 10.11835/j.issn.1000-582X.2019.02.004
Abstract:Identifying backbone grid is of great significance to the differential planning of power grid in that it can improve the resistance to natural disasters effectively. The stepwise graded backbone grid based on the evaluation of both equipment importance and the benefit of disaster resistance can balance disaster resistance and economy of power grid construction. This paper presents an approach to construct graded backbone according to the classification of power sources, loads and branches. Based on the life cycle cost theory, the cost calculation model of the differential construction is established with the grade of equipment, service life and depreciation value taken into account. The model of customer outage cost is set up with typical users as representatives, which, together with the benefits of power-generation-side and transmission-side and the cost calculation model, constitutes a set of economic assessment system. The feasibility of the method to search for graded backbone grid and the validity of the proposed assessment system are verified by simulation results of the IEEE 118-bus power system.
LIU Jia , YUAN Yiping , WAN Lingyun , ZHAO Yuan , LIAO Qinglong , YANG Qunying
2019, 42(2):41-50. DOI: 10.11835/j.issn.1000-582X.2019.02.005
Abstract:A modified load curtailment model based on dynamic correction area and static Ward equivalent method is proposed to improve the calculation efficiency of power system reliability assessment. Firstly, an analytical expression of cross-weight for node was deduced using Wood Bury matrix transformation, on the basis of which the dynamic correction area that reflected the effective adjustment area for overload lines was determined. Secondly, a static Ward equivalent method of considering equivalent slack node was developed, thus realizing the flexible equivalence of external network of dynamic correction area. Furthermore, a modified load curtailment model for dynamic correction area was presented. The proposed model transforms traditional load curtailment method which is a global optimization, to a series of consecutive sub-optimizations in the dynamic correction areas, reducing the optimization scale and improving the calculation efficiency greatly. The effectiveness of the proposed method is verified by the simulation results of RBTS, IEEE-RTS79 and IEEE-RTS96 systems.
FENG Xinyang , ZHANG Qiaorong , LI Qingyong
2019, 42(2):51-61. DOI: 10.11835/j.issn.1000-582X.2019.02.006
Abstract:Traditional intelligent diagnosis methods rely too much on the experience of signal processing and fault diagnosis to extract fault features, and generalization ability of models is poor. Based on the theory of deep learning, a convolutional neural network algorithm combined with the softmax classifier is proposed to introduce weighting to the solution of data set imbalance problem. Model optimization techniques such as weighted loss function, regularization, and batch normalization are applied to the construction of an improved deep convolutional neural network model for rolling bearing fault diagnosis. The model learns from the original measured bearing vibration signal by layer-by-layer learning to achieve feature extraction and target classification. Experimental results show that the optimized deep learning model can achieve accurate recognition of early weak faults and different levels of faults, and its recognition accuracy on unbalanced data sets can reach 95%. Furthermore the model has faster convergence speed and strong generalization ability.
DENG Shiyuan , XIN Jianqiang , ZHANG Kun , WANG Linlin , YAO Jianyao , HONG Wenhu
2019, 42(2):62-70. DOI: 10.11835/j.issn.1000-582X.2019.02.007
Abstract:Safety and structural integrity of hypersonic vehicles are directly influenced by the reliability of their thermal protection system (TPS). To improve the efficiency of reliability analysis of TPS, a new method based on importance sampling was proposed in this paper. The detailed calculation procedure and thermal reliability assessment methods were also introduced. The thermal reliability analysis of a typical non-ablative TPS with uncertainties about material properties and geometries was used as numerical example to verify the effectiveness of the proposed method. The results indicate that to achieve reliability result with the same confidence level, importance sampling method needs only 10% simulation iterations of the conventional Monte Carlo method, which dramatically improves the efficiency of reliability analysis.
YANG Jishi , LI Na , SUN Dongyang , DUAN Yingtao , HU Ning , NING Huiming , YE Wei , WU Jian
2019, 42(2):71-80. DOI: 10.11835/j.issn.1000-582X.2019.02.008
Abstract:A stiffness prediction model was built for carbon/glass fiber-reinforced & 2D triaxial braided composites (2DTBC) in accordance with the feature of spatial geometry of carbon fiber and glass fiber, and a strength prediction model was established based on Tsai-Wu failure criterion, thus a general process of progressive failure analysis of braided composites being created. The corresponding material testing was designed and the engineering constants and strength parameters obtained from it verified the reliability of theoretical models. Furthermore, a strength analysis of three-point bending for middle crossbeam-roof made of carbon/glass fiber-reinforced 2DTBC was conducted. The results show that failure-prone positions are concentrated in the contact positions and edges of crossbeam-roof.
WANG Jintao , HAN Xiaoyu , LIU Shouping , HOU Wei
2019, 42(2):81-92. DOI: 10.11835/j.issn.1000-582X.2019.02.009
Abstract:In this paper, the high-temperature oxidation resistance of Fe-Al-Cr high-aluminium steel with different alloying elements (Si, V) was tested by high-temperature oxidation test at 900℃ for 10 h. The high-temperature oxidation resistance of Fe-Al-Cr-Si was better than that of Fe-Al-Cr and Fe-Al-Cr-V alloys. Experiments revealed that the dynamic process of oxide formation, shedding and matrix oxidation occurs in Fe-Al-Cr alloy in a high-temperature environment. The high-temperature oxidation resistance of Fe-Al-Cr alloy mainly depends on the bonding strength of Fe/Al2O3 interface, rather than the positive correlation with the content of Al. The effect of alloying elements on interfacial bonding energy of metal/oxide was calculated by density functional theory. The mechanism of the effect of Si and V on high-temperature oxidation resistance of Fe-Al-Cr alloys was explained. The interfacial bonding force of Fe/Al2O3 comes from the covalent effect of Fe-O, and Si can reduce the interfacial bonding energy from-7.16 eV to -7.41 eV, which makes the bonding between Al2O3 and matrix more closely. V can increase the interfacial bonding energy to -6.06 eV, which will make the interface easy to fail, lead to the fall off of Al2O3, and destroy the high temperature oxidation resistance of the alloy.
LYU Yuxiang , JIANG Jing , YANG Pingheng , XIE Bin , HU Wei
2019, 42(2):93-103. DOI: 10.11835/j.issn.1000-582X.2019.02.010
Abstract:Groundwater simulation and application of karst water-bearing medium are hot spots and difficulties in hydrogeological work. In this research,Jingguan area in the east wing of the Guanyinxia anticline was selected as the research object, and the multiple pumping test data of 3 geothermal wells were obtained. Based on Visual Modflow software platform, the numerical simulation model was established,and interwell interference degree of the geothermal well with the exexisting UK1in different conditions was calculated. The results show that:when the distance between a new drill and ZK1 and its mining amount is 1 km and 500 m3/d, 2 km and 1 000 m3/d, 5 km and 1 500 m3/d, 2 000 m3/d and 2 500 m3/d, respectively, there is no effect on the flow field near the ZK1;when the distance between a new drill and ZK1 and its mining amount is 1 km and 1 000 m3/d, 2 km and 1 500 m3/d, 5 km and 3 000 m3/d,the water head of ZK1 well decreases by 19 m, 13 m and 8 m respectively, illustrating that the smaller the spacing of geothermal wells and the larger the mining volume, the greater the probability of interference with adjacent wells. It proves feasible to simulate the characteristics of geothermal flow field using the Visual Modflow model.
PENG Shoujian , WU Shankang , XU Jiang , LIU Yixin
2019, 42(2):104-111. DOI: 10.11835/j.issn.1000-582X.2019.02.011
Abstract:Soil erosion is a complex phenomenon involving the detachment and transport of soil particles, storage and runoff of rainwater, and infiltration. The relative magnitude and importance of these processes depends on a host of factors, including rainfall intensity, surface roughness, subsurface soil water pressure, and so on. Thus, in our study, the soil erosion results of a series of experiments were reported in the form of a volume index. Different rainfall intensity in relation to the erosion rate was investigated for the chronological phenomenon and more insight and detail were got to improve estimation of eroded volume of the slope surface. The results show the surface runoff by rainfall is the key factor in producing the soil sediment. And a sequence of rainstorms of increasing intensity on an initially smooth surface cause high soil loss rate,but which will be slowed down with the aggravation of surface roughness and the formation of rills. The highlight is the use of 3D fitting model by which the interaction and function among rainfall intensity, duration, and soil yield sediment is investigated.
BAI Runcai , CHAI Senlin , LIU Guangwei , FU Ensan , ZHAO Jingchang , CAO Bo
2019, 42(2):112-122. DOI: 10.11835/j.issn.1000-582X.2019.02.012
Abstract:In order to effectively improve the accuracyof transportationfunction consumption models, open-pit designer can establish a more detailed material transportation planning model for theproblems that cannot be solved for lack ofestimation method of strip-by-strip transport distance in the annual plan. In this paper a prediction model of multivariate nonlinear haul distance curve trained by extreme learning machine was proposed. The dump strip on transport line designed for year-end dump project location was taken as the training samplesto train prediction model to learn the time varying trait of hual distance and influence factor. Finally, the nonlinear estimation of haul distance expression was used to predict block variable distance. In order to enhance the prediction accuracy of the ELM algorithm,the modified particle swarm optimization algorithm was adopted to build the model of parameters optimization aimed at structural risk minimization and realized the structural risk correction to improve the accuracy of prediction algorithm. The results show that the method of ELM model ultimately determine the number of hidden layer nodes to be 27 through the test of simulation by trial and graphic test.The evaluation indexesof algorithm prediction accuracy (mean square error, goodness of fit, relative error expectation, absolute error expectation, misestimation coefficient, execution efficiency) are 0.006 8, 0.995 3, 0.027%, 0.62,0.03 and 1.49 srespectively.Compared with other prediction model of intelligent algorithm,their absolute error are 0.116 2, 0.094 7, 0.139 1 and the coefficient of miscalculation are 0.230, 0.200, 0.266. In conclusion, the algorithm has better prediction effect obviously.