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Search Results (9)
  • Open Access

    ARTICLE

    Comparative Analysis of ARIMA and LSTM Model-Based Anomaly Detection for Unannotated Structural Health Monitoring Data in an Immersed Tunnel

    Qing Ai1,2, Hao Tian2,3,*, Hui Wang1,*, Qing Lang1, Xingchun Huang1, Xinghong Jiang4, Qiang Jing5

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1797-1827, 2024, DOI:10.32604/cmes.2023.045251

    Abstract Structural Health Monitoring (SHM) systems have become a crucial tool for the operational management of long tunnels. For immersed tunnels exposed to both traffic loads and the effects of the marine environment, efficiently identifying abnormal conditions from the extensive unannotated SHM data presents a significant challenge. This study proposed a model-based approach for anomaly detection and conducted validation and comparative analysis of two distinct temporal predictive models using SHM data from a real immersed tunnel. Firstly, a dynamic predictive model-based anomaly detection method is proposed, which utilizes a rolling time window for modeling to achieve dynamic prediction. Leveraging the assumption… More >

  • Open Access

    ARTICLE

    Correlation Analysis of Turbidity and Total Phosphorus in Water Quality Monitoring Data

    Wenwu Tan1, Jianjun Zhang1,*, Xing Liu1, Jiang Wu1, Yifu Sheng1, Ke Xiao2, Li Wang2, Haijun Lin1, Guang Sun3, Peng Guo4

    Journal on Big Data, Vol.5, pp. 85-97, 2023, DOI:10.32604/jbd.2022.030908

    Abstract At present, water pollution has become an important factor affecting and restricting national and regional economic development. Total phosphorus is one of the main sources of water pollution and eutrophication, so the prediction of total phosphorus in water quality has good research significance. This paper selects the total phosphorus and turbidity data for analysis by crawling the data of the water quality monitoring platform. By constructing the attribute object mapping relationship, the correlation between the two indicators was analyzed and used to predict the future data. Firstly, the monthly mean and daily mean concentrations of total phosphorus and turbidity outliers… More >

  • Open Access

    ARTICLE

    Design of a Web Crawler for Water Quality Monitoring Data and Data Visualization

    Ziwen Yu1, Jianjun Zhang1,*, Wenwu Tan1, Ziyi Xiong1, Peilun Li1, Liangqing Meng2, Haijun Lin1, Guang Sun3, Peng Guo4

    Journal on Big Data, Vol.4, No.2, pp. 135-143, 2022, DOI:10.32604/jbd.2022.031024

    Abstract Many countries are paying more and more attention to the protection of water resources at present, and how to protect water resources has received extensive attention from society. Water quality monitoring is the key work to water resources protection. How to efficiently collect and analyze water quality monitoring data is an important aspect of water resources protection. In this paper, python programming tools and regular expressions were used to design a web crawler for the acquisition of water quality monitoring data from Global Freshwater Quality Database (GEMStat) sites, and the multi-thread parallelism was added to improve the efficiency in the… More >

  • Open Access

    ARTICLE

    Anomaly Detection and Pattern Differentiation in Monitoring Data from Power Transformers

    Jun Zhao1, Shuguo Gao1, Yunpeng Liu2,3, Quan Wang2,*, Ziqiang Xu2, Yuan Tian1, Lu Sun1

    Energy Engineering, Vol.119, No.5, pp. 1811-1828, 2022, DOI:10.32604/ee.2022.020490

    Abstract Aiming at the problem of abnormal data generated by a power transformer on-line monitoring system due to the influences of transformer operation state change, external environmental interference, communication interruption, and other factors, a method of anomaly recognition and differentiation for monitoring data was proposed. Firstly, the empirical wavelet transform (EWT) and the autoregressive integrated moving average (ARIMA) model were used for time series modelling of monitoring data to obtain the residual sequence reflecting the anomaly monitoring data value, and then the isolation forest algorithm was used to identify the abnormal information, and the monitoring sequence was segmented according to the… More >

  • Open Access

    ARTICLE

    Comparative Study on Deformation Prediction Models of Wuqiangxi Concrete Gravity Dam Based on Monitoring Data

    Songlin Yang1,2, Xingjin Han1,2, Chufeng Kuang1,2, Weihua Fang3, Jianfei Zhang4, Tiantang Yu4,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.131, No.1, pp. 49-72, 2022, DOI:10.32604/cmes.2022.018325

    Abstract The deformation prediction models of Wuqiangxi concrete gravity dam are developed, including two statistical models and a deep learning model. In the statistical models, the reliable monitoring data are firstly determined with Lahitte criterion; then, the stepwise regression and partial least squares regression models for deformation prediction of concrete gravity dam are constructed in terms of the reliable monitoring data, and the factors of water pressure, temperature and time effect are considered in the models; finally, according to the monitoring data from 2006 to 2020 of five typical measuring points including J23 (on dam section ), J33 (on dam section… More >

  • Open Access

    ARTICLE

    Using Grey Target Theory for Power Quality Evaluation Based on Power Quality Monitoring Data

    Qiang Yu*, Xiankai Chen, Xiaoyue Li, Chaoqun Zhou, Zhichao Li

    Energy Engineering, Vol.119, No.1, pp. 359-369, 2022, DOI:10.32604/EE.2022.015397

    Abstract Smart grid puts forward higher requirements for power quality. Power quality evaluation can provide a decision-making basis for quality improvement. Based on power quality monitoring data, a grey target method is proposed for power quality evaluation. The grey target is composed of power quality evaluation standard and power quality monitoring data to be evaluated. Combining with the characteristics of each power quality evaluation index, the target center of the whole grey target system is found. Then, the power quality monitoring data to be evaluated and the power quality standard mode are compared and analyzed to construct the power quality grey… More >

  • Open Access

    ARTICLE

    Design and Analysis of a Water Quality Monitoring Data Service Platform

    Jianjun Zhang1,*, Yifu Sheng1, Weida Chen2, Haijun Lin1, Guang Sun3, Peng Guo4

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 389-405, 2021, DOI:10.32604/cmc.2020.012384

    Abstract Water is one of the basic resources for human survival. Water pollution monitoring and protection have been becoming a major problem for many countries all over the world. Most traditional water quality monitoring systems, however, generally focus only on water quality data collection, ignoring data analysis and data mining. In addition, some dirty data and data loss may occur due to power failures or transmission failures, further affecting data analysis and its application. In order to meet these needs, by using Internet of things, cloud computing, and big data technologies, we designed and implemented a water quality monitoring data intelligent… More >

  • Open Access

    ARTICLE

    Visualization Research and Application of Water Quality Monitoring Data Based on ECharts

    Yifu Sheng1, Weida Chen, Huan Wen1, Haijun Lin1, Jianjun Zhang1, *

    Journal on Big Data, Vol.2, No.1, pp. 1-8, 2020, DOI:10.32604/jbd.2020.01001

    Abstract Water resources are one of the basic resources for human survival, and water protection has been becoming a major problem for countries around the world. However, most of the traditional water quality monitoring research work is still concerned with the collection of water quality indicators, and ignored the analysis of water quality monitoring data and its value. In this paper, by adopting Laravel and AdminTE framework, we introduced how to design and implement a water quality data visualization platform based on Baidu ECharts. Through the deployed water quality sensor, the collected water quality indicator data is transmitted to the big… More >

  • Open Access

    ABSTRACT

    Stay cable vehicle live load effects analysis based on structural health monitoring data

    C.M. Lan1, H. Li1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.12, No.3, pp. 75-82, 2009, DOI:10.3970/icces.2009.012.075

    Abstract Stay cables are some of the most critical structural components of a bridge. However, stay cables readily suffer from corrosion damage and stress corrosion damage. Thus, health monitoring of stay cables is important for ensuring the integrity and safety of a bridge. Glass Fibre Reinforced Polymer Optical Fibre Bragg Grating (GFRP-OFBG) cable, a kind of fibre Bragg grating optical sensing technology-based smart stay cables, is proposed in this study. The fabrication procedure of the smart stay cable was developed and the self-sensing property of the smart stay cable was calibrated. The application of the smart stay cables on the Tianjin… More >

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