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With the rapid development of high-speed rail in China, addressing the issue of safety assurance during the operation of the train is very important. A very important part of a train's power supply system is the pantograph and catenary system, which consists of a pantograph and a catenary. Failure of the pantograph-catenary system can cause significant damage to the normal operation of the train. The dynamic performance of the pantograph-catheter system must be detected in real time during the operation of the train. This paper is based on the study and analysis of pantograph-catheter dynamic performance parameters and developed a system for real-time detection of pantograph-catheter dynamic performance parameters based on a car visual system. The results are as follows: based on this detection method, the visual error is low and the accuracy is high. The machine-based directional height detection module developed in this paper has a good detection effect and high test accuracy; the arcing detection module designed in this paper can effectively detect the arcing and store the arcing pictures and can display the duration of single arcing and the arcing rate of the section in real-time. The practical application effect is good. The results show that the focal length of the camera lens is 16 mm, and the error of the machine vision system is low. The system designed in this paper may make a great contribution to the operation condition monitoring and fault diagnosis of the pantograph-catenary system of a high-speed train in the future. [ABSTRACT FROM AUTHOR]

Based on the data of China's ecological environment from 2006 to 2018, the paper uses the super-efficiency DEA and Malmquist index methods to evaluate China's ecological welfare performance from a static and dynamic perspective. Based on this, the Theil index is used to analyze the group's ecological welfare performance. The internal and intergroup differences show that, from the static evaluation results, China's ecological welfare performance is in a situation of "high in the east, low in the west, and average in the central region." There is not much difference between the eastern and central regions, while the ecological welfare performance in the western region is low. From the results of dynamic evaluation, the overall level of regional ecological welfare performance in China has improved in recent years, and the average Malmquist index has exceeded 1, indicating that the growth pattern of ecological welfare performance has shifted to high quality, but the degree of increase in each region is different. There is still much room for improvement in ecological welfare performance; from the perspective of intragroup and intergroup differences, the intragroup differences and intergroup differences in the three major regions have generally maintained a continuous downward trend, and the contribution of the differences in ecowelfare performance between group rate has a clear advantage. Finally, corresponding suggestions are put forward based on the empirical results of the paper. [ABSTRACT FROM AUTHOR]

With the continuous promotion of industrialization and urbanization, China's environmental pollution is becoming increasingly serious, which has caused considerable damage to the natural balance. Air pollution seriously harms people's physical and mental health, the ecological environment, and the social sustainable development of society. In this study, the backward trajectory model and multifractal methods were adopted to analyze air pollution in Zhengzhou. The backward trajectory analysis showed that most clusters of air pollution were from southern Hebei, eastern Shandong, and mid-western Henan, which were then transported to Zhengzhou. For the PSCF and CWT analyses, we selected four representative cities to explore how close the air pollution of Zhengzhou is to other areas on the basis of air polluted concentration. The results of several multifractal methods indicated that multifractality existed in the AQI time series of Zhengzhou and cross-correlations between Zhengzhou and each of the four cities. The widths of multifractal spectra showed that the air pollution in Zhengzhou was closest to that in Jinan, followed by Shijiazhuang, Zibo, and Luoyang. The CDFA analysis showed that carbon monoxide (CO), nitrogen dioxide (NO2), and inhalable particulate matter (PM10) had important influences on air pollution in Zhengzhou. These findings offer a useful reference for air pollution sources and their potential contributions in Zhengzhou, which can support policy makers in environmental governance and in achieving sustainable urban development. [ABSTRACT FROM AUTHOR]

The development of the new energy vehicle industry is necessary for its advantages of saving energy and reducing greenhouse-gas emissions. However, the industry is currently facing risks with regard to, for example, technology, market, and the policy. Most existing studies of industry risk focused on analyzing and evaluating risk factors and summarizing and interpreting risk phenomena. In this study, systematic classification and quantitative analysis for the risk of the new energy vehicle industry were investigated, in which the entropy weight method and cloud model were combined to evaluate and quantify the industry risk. The formation mechanism of the industry risk from endogenous and exogenous perspectives was analyzed to screen out risk-evaluation factors. Combining the expert-investigation and fuzzy-statistics methods, a risk-evaluation index system with six primary indicators and twenty-four secondary indicators was constructed. On the basis of the entropy weight-cloud model, the risk of the new energy automobile industry of Jiangsu province in July 2019 was evaluated. Results indicated that the impact of exogenous risk on the industry was greater than that of endogenous risk, and industry risk was higher than medium risk, which was close to a higher medium level. A series of suggestions are given for preventing industry risk, such as improving the industry's own ability to resist risk and building the industry's soft environment. [ABSTRACT FROM AUTHOR]