| 1. |
- Xin, Tao, et al.
(author)
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Time Series Recovery Using Adjacent Channel Data Based on LSTM: A Case Study of Subway Vibrations
- 2022
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In: Applied Sciences. - : MDPI. - 2076-3417. ; 12:22
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Journal article (peer-reviewed)abstract
- Multi-sensor technology has been widely applied in the condition monitoring of rail transit. In practice, the data of some channels in the high channel counts are often abnormal or lost due to the abnormality and damage of the sensors, thus resulting in a large amount of data waste. A method for the data recovery of lost channels by using adjacent channel data is proposed to solve this problem. Based on the LSTM network algorithm, a data recovery model is established based on the “sequence-to-sequence” regression analysis of adjacent channel data. Taking the measured vibration data of a subway as an example, the network is trained with multi-channel measured data to recover the lost channel data of time-series characteristics. The results show that this multi-channel data recovery model is feasible, and the accuracy is up to 98%. This method can also further reduce the number of channels that need to be collected.
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| 2. |
- Li, Bojia, et al.
(author)
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Evaluating the role of clean heating technologies in rural areas in improving the air quality
- 2021
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In: Applied Energy. - : ELSEVIER SCI LTD. - 0306-2619 .- 1872-9118. ; 289
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Journal article (peer-reviewed)abstract
- The Air Pollution Prevention and Control Action Plan proposed in 2013 has contributed to the fossil fuel reduction in central heating, but the consumption of scattered coal in rural areas should not be overlooked as it accounts for nearly 50% pollutant emissions during the heating season. Air Pollution Prevention and Control Action Plan for Beijing-Tianjin-Hebei and Surrounding Areas was issued to solve the problem of scattered coal consumption and improve the heating energy structure in 2017. In this paper, an air quality-heating model is established to evaluate the air quality improvement potential and far-reaching influence of scattered coal consumption reduction in rural areas. Distinct from other air quality evaluation models, the proposed model is to evaluate the regional air quality related to the heating factors. The results indicate that the coal substitution policy can reduce PM2.5 concentrations in the heating season by about 20 mu g/m(3) in Beijing-Tianjin-Hebei and surrounding areas. Furthermore, predictions about the variation of PM2.5 concentration in the heating season are conducted, which indicate that the PM2.5 concentration of Beijing, Tianjin, Hebei and surrounding areas in 2030 will drop by 48%, 35%, 29% and 23% respectively compared to that in 2016. The reduction could be further enhanced to be 55%, 40%, 32% and 27% with the consideration of clean power development. This study is conducive to evaluate the clean heating technologies role in improving the environment and air quality.
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| 3. |
- Wang, F., et al.
(author)
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Do ‘green’ data centres really have zero CO2 emissions?
- 2022
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In: Sustainable Energy Technologies and Assessments. - : Elsevier Ltd. - 2213-1388 .- 2213-1396. ; 53
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Journal article (peer-reviewed)abstract
- The claim of a green data centre is generally made based on a net-zero CO2 emission through a ‘balance-sheet’ approach, which considers renewable electricity through on-site installation or purchase agreement as abatement measures against the use of fossil electricity from the electric grid on an annual basis. However, when the hourly dynamic fuel mix is accounted for in the assessment, the annual net-zero energy approach does not lead to a true carbon neutral data centre. In response, two approaches based on net-zero energy and net-zero CO2 emission respectively are proposed and investigated regarding the goal of net-zero CO2 emission. A data centre in Singapore with typical load profiles is used as a case study, different scenarios considering climate change and projected future energy are defined to examine the impacts of dynamic energy mix on the net CO2 emission of the data centre. The net-zero energy approach is found to result in significant amount of annual CO2 emissions. In comparison, the net-zero CO2 emission approach can assure a true net-zero CO2 emission, but this approach will require an increase of PV capacity by 20% and 60% as compared to the net-zero energy approach based on assessment for the year 2030 and 2050, respectively.
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