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Data-driven Anomaly Detection Method Based on Similarities of Multiple Wind Turbines

Journal of Modern Power Systems and Clean Energy 2024年第3期12卷 803-818页

作者： Xiangjun Zeng Ming Yang Chen Feng Mingqiang Wang Lingqin Xia the College of Electrical Engineering&New Energy China Three Gorges UniversityYichang 443002China the Key Laboratory of Power System Intelligent Dispatch and Control Shandong UniversityJinan 250061China

The operating conditions of wind turbines(WTs)in the same wind farm(WF)may share similarities due to their shared manufacturing process,control strategy,and operating ***,the similarities of WTs are seldom considered in WT anomaly detection,resulting in the disregard of useful *** paper proposes a method to improve the reliability and accuracy of WT anomaly detection using the supervisory control and data acquisition(SCADA)data of multiple WTs in the same ***,a similarity assessment method based on a comparison of different observation time series is proposed,which objectively quantifies the similarities of WT operating ***,the SCADA data of the target WT and selected WTs that are similar are used to establish several estimation models through a long short-term memory(LSTM)*** models that exhibit good estimation performance are used to construct a combined estimation model that estimates the variations in the monitored variables of the target ***,an anomaly detection method that jointly compares the effective value and information entropy of the residuals is proposed to identify *** effectiveness and accuracy of the proposed method are verified using the data of two actual WFs.

关键词： Anomaly detection information entropy long short-term memory similarity assessment wind farm wind turbines

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assessment of SoilGrids data for soil erosion estimation at watershed scale: A case study in northern Thailand

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Pedosphere 2024年第4期34卷 797-813页

作者： Chike Onyeka MADUEKE Dhruba Pikha SHRESTHA Panagiotis NYKTAS Department of Natural Resources Faculty of Geo-information Science and Earth Observation(ITC)University of TwenteEnschede 7500 AEthe Netherlands Department of Applied Earth Sciences Faculty of Geo-information Science and Earth Observation(ITC)University of TwenteEnschede 7500 AEthe Netherlands Department of Soil Science and Land Resources Management Nnamdi Azikiwe UniversityP.M.B.5025AwkaAnambra State 420110Nigeria

Soil erosion has been identified as one of the most destructive forms of land degradation,posing a threat to the sustainability of global economic,social and environmental *** underscores the need for sustainable land management that takes erosion control and prevention into *** requires the use of state-of-the-art erosion prediction *** models often require extensive input of detailed spatial and temporal data,some of which are not readily available in many developing countries,particularly detailed soil *** soil dataset Global Gridded Soil Information(SoilGrids)could potentially fill the data ***,its value and accuracy for soil erosion modelling in the humid tropics is still unknown,necessitating the need to assess its value vis-à-vis field-based *** major objective of this study was to conduct a comparative assessment of the value of SoilGrids and field-based soil data for estimating soil *** samples were collected from five physiographic positions(summit,shoulder,back slope,foot slope,and toe slope)using the soil catena *** were collected using a 5-cm steel sample ring(undisturbed)and a spade(disturbed).Data of the landform,predominant vegetation types,canopy cover,average plant height,land use,soil depth,shear strength,and soil color were recorded for each *** soil samples were subjected to laboratory analysis for saturated hydraulic conductivity,bulk density,particle size distribution,and organic matter *** functions were applied on the SoilGrids and field-based data to generate soil hydrological *** resultant field-based data were compared with the SoilGrids data for corresponding points/areas to determine the potential similarities of the two *** datasets were then used as inputs for soil erosion assessment using the revised Morgan-Morgan-Finney *** results from both datasets were again compared to determine the degree of *** r

关键词： hillslope modelling pedotransfer function similarity assessment soil erosion modelling soil loss soil survey

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