Wenjun Wang

Dr. Wenjun Wang


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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3 July 2024 in Sensors
Verified
Journal Article
Open access
PDF file
CZChao Zeng
Chao Zeng
继张继亮 张
继亮 张
YSYizi Su
Yizi Su
LLli ll
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ZWZhenyuan Wang
Zhenyuan Wang
WWWenjun Wang
Wenjun Wang
Traffic accidents due to fatigue account for a large proportion of road fatalities. Based on simulated driving experiments with drivers recruited from college students, this paper investigates the use of heart rate variability (HRV) features to detect driver fatigue while considering sex differences. Sex-independent and sex-specific differences in HRV features between alert and fatigued states derived from 2 min electrocardiogram (ECG) signals were determined. Then, decision trees were used for driver fatigue detection using the HRV features of either all subjects or those of only males or females. Nineteen, eighteen, and thirteen HRV features were significantly different (Mann–Whitney U test, p < 0.01) between the two mental states for all subjects, males, and females, respectively. The fatigue detection models for all subjects, males, and females achieved classification accuracies of 86.3%, 94.8%, and 92.0%, respectively. In conclusion, sex differences in HRV features between drivers’ mental states were found according to both the statistical analysis and classification results. By considering sex differences, precise HRV feature-based driver fatigue detection systems can be developed. Moreover, in contrast to conventional methods using HRV features from 5 min ECG signals, our method uses HRV features from 2 min ECG signals, thus enabling more rapid driver fatigue detection.

15 February 2024 in Applied Sciences
Verified
Journal Article
Open access
PDF file
XJXingheng Jia
Xingheng Jia
YYYuming Yin
Yuming Yin
WWWenjun Wang
Wenjun Wang
For better small-radius curve negotiation performance, the independently rotating wheelset has the potential to be equipped in urban rail transit. As a crucial part of the running gear, its dynamic characteristics directly affect the railway vehicle’s stability and curve negotiation ability. This study follows a model–simulation–experiment method to delve into the dynamic process and steady convergent process of the independently rotating wheelset. An improved mathematical dynamic model of the independently rotating wheelset is established, considering the gravitational restoring forces of the wheelset and different creepages between the left and right wheels. In addition, the gyroscopic effects on the independently rotating wheelset with positive wheel tread conicity and at high speeds are introduced and analyzed. With variations in the longitudinal speed and yaw suspension coefficients, three kinds of motions, derailment, hunting, and offset running, occur on the independently rotating wheelset. We find that the gyroscopic effects contribute to the slight self-guidance ability of the independently rotating wheelset, causing a hunting motion at high speeds. Through sufficient simulations, the improved mathematical dynamic model is verified to be closer to the dynamic model built in the general multibody system simulation software SIMPACK 2018 than the classical mathematical dynamic model. Further, we perform experiments on a scaled independently rotating wheelset experiment system. The dynamic characteristics derived from theoretical analysis, especially the slight self-guidance ability at high speeds, are verified.