The evolution of chaotic state of Lorenz system on the familiar parameter space orbit is analyzed.Based on the principle of chaos suppression with nonresonant parametric drive,the model of detecting weak periodic sign...The evolution of chaotic state of Lorenz system on the familiar parameter space orbit is analyzed.Based on the principle of chaos suppression with nonresonant parametric drive,the model of detecting weak periodic signals in strong noise is built.According to the parametric equivalent relationship obtained using averaging method and renormalization method,the critical values of detection parameters are determined,which lead to a sudden change of system dynamical behavior from periodic orbit to stable equilibrium point.Simulation results show that weak periodic signals in strong noise can be detected accurately with the proposed system.The method can obtain accurate range of parameter threshold through theoretical analysis,and the detection criterion is rather simple,which is more convenient for automatic detection.展开更多
为了提高呼吸信号判别驾驶疲劳的准确率,通过模拟驾驶试验探究呼吸信号与驾驶员疲劳状态的关系,提出呼吸疲劳节点的概念,并基于呼吸疲劳节点判别驾驶员的疲劳状态。首先,通过模拟驾驶试验采集驾驶员的呼吸信号,采用Karolinska嗜睡量表(K...为了提高呼吸信号判别驾驶疲劳的准确率,通过模拟驾驶试验探究呼吸信号与驾驶员疲劳状态的关系,提出呼吸疲劳节点的概念,并基于呼吸疲劳节点判别驾驶员的疲劳状态。首先,通过模拟驾驶试验采集驾驶员的呼吸信号,采用Karolinska嗜睡量表(Karolinska sleepiness scale, KSS)对疲劳程度进行主观自评量化。其次,把单位时间内眼睛闭合百分比(percentage of eyelid closure over the pupil over time, PERCLOS)作为参考,与主观自评反馈结合,对驾驶员呼吸疲劳节点进行标定。最后,基于呼吸疲劳节点利用随机树算法(random tree, RT)获得轻/重度呼吸疲劳变化节点的判别模型。结果表明:该模型能更加及时、准确地判别出驾驶员的疲劳状态;基于随机树算法获得的筛选条件对轻度呼吸疲劳变化节点识别的准确性要高于重度呼吸疲劳变化节点;轻/重度呼吸疲劳变化节点的平均识别误差分别为3.50 min和3.66 min,预测准确率分别为92.09%和92.03%。展开更多
The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and cons...The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and consequently the traffic dynamics has not been completely explored. Therefore, a new cellular automaton model, which incorporates the driving behaviors typically manifesting during the different stages when the vehicles are moving toward a traffic light, is proposed in this paper. Numerical simulations have demonstrated that the proposed model can produce the spontaneous traffic breakdown and the dissolution of the over-saturated traffic phenomena. Furthermore, the simulation results indicate that the slow-to-start behavior and the inch-forward behavior can foster the traffic breakdown. Particularly, it has been discovered that the over-saturated traffic can be revised to be an under-saturated state when the slow-down behavior is activated after the spontaneous breakdown. Finally, the contributions of the driving behaviors on the traffic breakdown have been examined.展开更多
Purpose–In this paper,the C80 special coal gondola car was taken as the subject,and the load test data of the car body at the center plate,side bearing and coupler measured on the dedicated line were broken down to g...Purpose–In this paper,the C80 special coal gondola car was taken as the subject,and the load test data of the car body at the center plate,side bearing and coupler measured on the dedicated line were broken down to generate the random load component spectrums of the car body under five working conditions,namely expansion,bouncing,rolling,torsion and pitching according to the typical motion attitude of the car body.Design/methodology/approach–On the basis of processing the measured load data,the random load component spectrums were equivalently converted into sinusoidal load component spectrums for bench test based on the principle of pseudo-damage equivalence of load.Relying on the fatigue and vibration test bench of the whole railway wagon,by taking each sinusoidal load component spectrum as the simulation target,the time waveform replication(TWR)iteration technology was adopted to create the drive signal of each loading actuator required for the fatigue test of car body on the bench,and the drive signal was corrected based on the equivalence principle of measured stress fatigue damage to obtain the fatigue test loads of car body under various typical working conditions.Findings–The fatigue test results on the test bench were substantially close to the measured test results on the line.According to the results,the relative error between the fatigue damage of the car body on the test bench and the measured damage on the line was within the range of16.03%–27.14%.Originality/value–The bench test results basically reproduced the fatigue damage of the key parts of the car body on the line.展开更多
文摘The evolution of chaotic state of Lorenz system on the familiar parameter space orbit is analyzed.Based on the principle of chaos suppression with nonresonant parametric drive,the model of detecting weak periodic signals in strong noise is built.According to the parametric equivalent relationship obtained using averaging method and renormalization method,the critical values of detection parameters are determined,which lead to a sudden change of system dynamical behavior from periodic orbit to stable equilibrium point.Simulation results show that weak periodic signals in strong noise can be detected accurately with the proposed system.The method can obtain accurate range of parameter threshold through theoretical analysis,and the detection criterion is rather simple,which is more convenient for automatic detection.
文摘为了提高呼吸信号判别驾驶疲劳的准确率,通过模拟驾驶试验探究呼吸信号与驾驶员疲劳状态的关系,提出呼吸疲劳节点的概念,并基于呼吸疲劳节点判别驾驶员的疲劳状态。首先,通过模拟驾驶试验采集驾驶员的呼吸信号,采用Karolinska嗜睡量表(Karolinska sleepiness scale, KSS)对疲劳程度进行主观自评量化。其次,把单位时间内眼睛闭合百分比(percentage of eyelid closure over the pupil over time, PERCLOS)作为参考,与主观自评反馈结合,对驾驶员呼吸疲劳节点进行标定。最后,基于呼吸疲劳节点利用随机树算法(random tree, RT)获得轻/重度呼吸疲劳变化节点的判别模型。结果表明:该模型能更加及时、准确地判别出驾驶员的疲劳状态;基于随机树算法获得的筛选条件对轻度呼吸疲劳变化节点识别的准确性要高于重度呼吸疲劳变化节点;轻/重度呼吸疲劳变化节点的平均识别误差分别为3.50 min和3.66 min,预测准确率分别为92.09%和92.03%。
基金supported by the National Basic Research Program of China(Grand No.2012CB723303)the Beijing Committee of Science and Technology,China(Grand No.Z1211000003120100)
文摘The complexity of signal controlled traffic largely stems from the various driving behaviors developed in response to the traffic signal. However, the existing models take a few driving behaviors into account and consequently the traffic dynamics has not been completely explored. Therefore, a new cellular automaton model, which incorporates the driving behaviors typically manifesting during the different stages when the vehicles are moving toward a traffic light, is proposed in this paper. Numerical simulations have demonstrated that the proposed model can produce the spontaneous traffic breakdown and the dissolution of the over-saturated traffic phenomena. Furthermore, the simulation results indicate that the slow-to-start behavior and the inch-forward behavior can foster the traffic breakdown. Particularly, it has been discovered that the over-saturated traffic can be revised to be an under-saturated state when the slow-down behavior is activated after the spontaneous breakdown. Finally, the contributions of the driving behaviors on the traffic breakdown have been examined.
基金supported by the Science and Technology Research and Development Foundation of the Ministry of Science and Technology(Grant No.2020YFB1200200ZL)the Scientific Research Program of the Department of Education of Liaoning Province(Grant No.2021LJKZ1298)the Science and Technology Research and Development Foundation of CRRC(Grant No.2021CHA014).
文摘Purpose–In this paper,the C80 special coal gondola car was taken as the subject,and the load test data of the car body at the center plate,side bearing and coupler measured on the dedicated line were broken down to generate the random load component spectrums of the car body under five working conditions,namely expansion,bouncing,rolling,torsion and pitching according to the typical motion attitude of the car body.Design/methodology/approach–On the basis of processing the measured load data,the random load component spectrums were equivalently converted into sinusoidal load component spectrums for bench test based on the principle of pseudo-damage equivalence of load.Relying on the fatigue and vibration test bench of the whole railway wagon,by taking each sinusoidal load component spectrum as the simulation target,the time waveform replication(TWR)iteration technology was adopted to create the drive signal of each loading actuator required for the fatigue test of car body on the bench,and the drive signal was corrected based on the equivalence principle of measured stress fatigue damage to obtain the fatigue test loads of car body under various typical working conditions.Findings–The fatigue test results on the test bench were substantially close to the measured test results on the line.According to the results,the relative error between the fatigue damage of the car body on the test bench and the measured damage on the line was within the range of16.03%–27.14%.Originality/value–The bench test results basically reproduced the fatigue damage of the key parts of the car body on the line.
