Research on CART Model of Mass Concrete Temperature Prediction Based on Big Data Processing Technology

Li, Baoyu; Li, Guoxing; Wang, Guiyu; Yang, Man

doi:10.1109/access.2022.3161556

Cited by 4 publications

(1 citation statement)

References 46 publications

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“…Traditional approaches have significantly contributed to the advancement of temperature forecasting. For example, Li and coworkers [15] introduced a data processing technique that involves outlier identification, missing value imputation, and random error reduction. This method was employed to enhance the accuracy of temperature prediction in large-scale concrete applications.…”

Section: Introductionmentioning

confidence: 99%

Pre-trained 1DCNN-BiLSTM Hybrid Network for Temperature Prediction of Wind Turbine Gearboxes

Zhuang,

Ma,

Lam

et al. 2023

Processes

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The safety and stability of a wind turbine is determined by the health condition of its gearbox. The temperature variation, compared with other characteristics of the gearbox, can directly and sensitively reflect its health conditions. However, the existing deep learning models (including the single model and the hybrid model) have their limitations in dealing with nonlinear and complex temperature data, making it challenging to achieve high-precision prediction results. In order to tackle this issue, this paper introduces a novel two-phase deep learning network for predicting the temperature of wind turbine gearboxes. In the first phase, a one-dimensional convolutional neural network (1DCNN) and a bidirectional long short-term memory (BiLSTM) network are separately trained using the same dataset. The two pre-trained networks are combined and fine-tuned to form the 1DCNN-BiLSTM model for the accurate prediction of gearbox temperatures in the second phase. The proposed model was trained and validated by measured datasets from gearboxes from an existing wind farm. The effectiveness of the model presented was showcased through a comparative analysis with five traditional models, and the result has clearly shown that the proposed model has a great improvement in its prediction accuracy.

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Section: Introductionmentioning

confidence: 99%

Pre-trained 1DCNN-BiLSTM Hybrid Network for Temperature Prediction of Wind Turbine Gearboxes

Zhuang,

Ma,

Lam

et al. 2023

Processes

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Prediction of uniform temperature effect on rectangular hollow concrete pier based on measured temperature data

Chen,

Wu,

Yun

et al. 2024

Sci Rep

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In order to accurately and easily predict the variation of the average temperature of the concrete rectangular hollow pier. Firstly, the temperature distribution of the concrete rectangular hollow pier of Changjiahe Special Bridge was observed for 212 days. Then, based on the observation data, the functional relationship between the average concrete hollow pier temperature and the outside air temperature, and the air temperature inside the hollow pier was studied. Finally, based on this functional relationship, a prediction model for the range of variation of the mean temperature of the hollow pier was given and verified. The results of the study show that: the change of external shade temperature can be regarded as the superposition of different cyclic changes and random changes; the change rule of the average temperature of the concrete hollow pier is the same as that of the air temperature, both presenting day-by-day cyclic and step changes; the linear correlation coefficients between the daily maximum and daily minimum average hollow pier temperature and the daily average air temperature are R = 0.980 and R = 0.973, respectively; the daily average air temperature, the daily average air temperature inside the pier and daily average hollow pier temperature are R = 0.980, R = 0.998; the daily variation of the average hollow pier temperature and the daily variation of the air temperature are approximately linear, with a correlation coefficient of R = 0.899; assuming that the average temperature of the concrete hollow pier is a folding change, based on the above relationship, a method of predicting the time-by-time average temperature of the concrete hollow piers is proposed, as well as two methods of predicting the average temperature of the test piers. Average temperature change range method. Comparing the predicted values with the measured values, it is found that the predicted values are in good agreement with the measured values.

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Prediction of uniform temperature of rectangular hollow concrete pier based on measured temperature data

Chen,

Wu,

Yun

et al. 2023

Preprint

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The standard value of uniform temperature action for bridges is more loosely defined in local bridge design codes. Currently, there is an increasing tendency to determine the range of variation of uniform temperature of bridges based on air temperature information from various locations. In this study, in order to accurately and conveniently predict the range of temperature change of concrete during the design reference period. The temperature distribution of concrete rectangular hollow piers of Changjiahe Special Bridge was observed for 212 days. According to the observation data, the average temperature of the concrete hollow pier was studied as a function of the outside air temperature and the air temperature inside the hollow pier. The method of predicting the range of variation of the average concrete temperature according to the local air temperature material is proposed; the method of predicting the time-by-time uniform temperature of the concrete hollow pier based on the same temperature data inside and outside the hollow pier is proposed. The research results show that: the average temperature change rule of concrete hollow piers and air temperature, are presented day by day cycle and step change, and the hollow pier average temperature extremes appear time lagging behind the air temperature; day maximum, day minimum hollow pier average temperature and the average daily air temperature is linearly correlated between the average daily air temperature, the average daily air temperature, average daily air temperature inside the pier and the average daily hollow pier temperature is linearly correlated between the average daily air temperature and the average daily hollow pier temperature; the average temperature of the hollow pier The magnitude of change is less than the air temperature, hollow pier average temperature daily variation and air temperature daily difference is approximately linear; concrete hollow pier average temperature prediction and measured values, the maximum difference between − 1.1 ~ 0.8 ºC; in the design reference period, in the day of the highest, lowest daily average air temperature on the basis of an increase of 2 degrees Celsius, can be obtained from the range of uniform temperature changes in the bridge abutment.

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Research on CART Model of Mass Concrete Temperature Prediction Based on Big Data Processing Technology

Cited by 4 publications

References 46 publications

Pre-trained 1DCNN-BiLSTM Hybrid Network for Temperature Prediction of Wind Turbine Gearboxes

Pre-trained 1DCNN-BiLSTM Hybrid Network for Temperature Prediction of Wind Turbine Gearboxes

Prediction of uniform temperature effect on rectangular hollow concrete pier based on measured temperature data

Prediction of uniform temperature of rectangular hollow concrete pier based on measured temperature data

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