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1.
《International Journal of Hydrogen Energy》2022,47(45):19821-19836
Machine learning-based fault detection methods are frequently combined with wavelet transform (WT) to detect an unintentional islanding condition. In contrast to this condition, these methods have long detection and computation time. Thus, selecting a useful signal processing-based approach is required for reliable islanding detection, especially in real-time applications. This paper presents a new modified signal processing-based islanding detection method (IDM) for real-time applications of hydrogen energy-based distributed generators. In the study, a new IDM using a modified pyramidal algorithm approach with an undecimated wavelet transform (UWT) is presented. The proposed method is performed with different grid conditions with the presence of electric noise in real-time. Experimental results show that oscillations in the acquired signal can be reduced by the UWT, and noise sensitivity is lower than other WT-based methods. The non-detection zone is zero and the maximum detection and computational time is also 75 ms at a close power match. 相似文献
2.
Erik Zipperling Benedikt Dahlmann Markus Zdrallek Christian Derksen Stefan Eicker Heiko Serafin 《化学,工程师,技术》2021,93(4):624-631
Demands on production, distribution and consumption of electrical energy change fundamentally with the energy revolution. Energy purchasing costs for inflexible consumers are rising and proceeds of inflexible producers are sinking. Companies are able to reduce costs by marketing operational flexibility options. This article sets out the need of flexibility in the energy system and the new marketing options. Flexibility potentials within infrastructure plants of a chemical park are analyzed, evaluated regarding marketing and activated in the presented research project FlexChemistry. 相似文献
3.
Investigations were performed on a group utilizing (General Purpose Unit) GPU and executions were evaluated for the utilization of the created parallel
usages to process satellite pictures from satellite Landsat7.The usage on a realistic group gives execution change from 2 to 18 times. The nature of the
considered techniques was assessed by relative dimensionless global error in synthesis (ERGAS) and Quality Without Reference (QNR) measurements. The
outcomes demonstrate execution picks ups and holding of value with the bunch of GPU contrasted with the outcomes and different analysts for a CPU and
single GPU. The errand of upgrading the view of a scene by combining data caught from various picture sensors is usually known as multisensor picture
combination. This paper displays a territory based picture combination calculation to consolidate SAR (Synthetic Aperture Radar) and optical pictures. The
co-enlistment of the two images is first led utilizing the proposed enrollment method prior to picture combination. The paper displays a parallel execution of
existing picture combination techniques on a graphical group. Parallel executions of techniques in view of discrete wavelet changes are created. Division
into dynamic and motionless regions is then executed on the SAR surface picture for particular injection of the SAR picture into panchromatic (PAN) picture.
An integrated image in view of these two pictures is produced by the novel region based combination plot, which forces diverse combination rules for each
fragmented region. At long last, this picture is melded into a multispectral(MS) picture through the half breed skillet honing technique proposed in past
research. Exploratory outcomes exhibit that the proposed strategy demonstrates preferred execution over different fusion algorithms and can possibly be
connected to the multisensory combination of SAR and optical pictures. 相似文献
4.
鄂尔多斯盆地东南部下二叠统山西组2~3亚段(以下简称山2~3亚段)为该盆地重要的天然气勘探目的层,但该亚段储层薄、厚度变化快、非均质性强,储层预测和勘探目标优选难度大。为了准确预测该亚段煤系地层致密砂岩气甜点区、提高天然气勘探成功率,针对该套储层的特征和预测难点,提出了90°相移技术识别河道外形、模型约束波阻抗反演刻画砂体厚度和子波衰减梯度属性识别含气砂体的地震逐级预测技术。研究结果表明:①山2~3亚段上覆5号煤地震强反射层,下伏储层地震反射能量弱,加之为稀疏二维地震测网、井控程度低,致使致密砂岩气甜点区预测难度大;②所提出的技术方法通过地震逐级预测约束,可以有效地刻画河道砂体分布并识别有效含气储层,提高了对勘探开发目标预测的精度;③基于该技术方法指导部署的勘探开发目标实钻效果好,地震预测结果横向分辨率高,真实地反映了河道及河道砂体的变化特征。结论认为,采用该方法可以有效地解决二维地震勘探区煤系地层强非均质性、薄储层致密砂岩气甜点区预测的地质难题。 相似文献
5.
In this work, the interdiffusion between a MCrAlY-bond coat and two different nickel-based superalloys is evaluated at three temperatures, 950 °C, 980 °C, and 1,050 °C. Of primary interest is the evolution of Kirkendall-porosity, the β-depleted zone in the bond coat and the β’- depleted zone in the superalloy. The three phenomena arise near the interface between bond coat and superalloy as a result of interdiffusion between both materials and are detrimental to the coating-substrate system. The evolution of the interdiffusion phenomena is highly dependent on the alloy composition of the materials as well as the annealing temperature. It has been found that not only the temperature dependency of the diffusion coefficient but also the temperature dependent element activities are an important factor when evaluating the interdiffusion phenomena. It has further been shown that at lower temperatures the amount of Kirkendall-porosity per volume fraction is higher than at higher temperatures, even though the overall amount of porosity is lower. Different equilibrium concentrations of main alloying elements and a correspondingly lower over-saturation of vacancies have been identified as the main explanation. 相似文献
6.
7.
8.
Zhijiang Li Yingping Zheng Liqin Cao Lei Jiao Yanfei Zhong Caiyi Zhang 《Color research and application》2020,45(4):656-670
Image color clustering is a basic technique in image processing and computer vision, which is often applied in image segmentation, color transfer, contrast enhancement, object detection, skin color capture, and so forth. Various clustering algorithms have been employed for image color clustering in recent years. However, most of the algorithms require a large amount of memory or a predetermined number of clusters. In addition, some of the existing algorithms are sensitive to the parameter configurations. In order to tackle the above problems, we propose an image color clustering method named Student's t-based density peaks clustering with superpixel segmentation (tDPCSS), which can automatically obtain clustering results, without requiring a large amount of memory, and is not dependent on the parameters of the algorithm or the number of clusters. In tDPCSS, superpixels are obtained based on automatic and constrained simple non-iterative clustering, to automatically decrease the image data volume. A Student's t kernel function and a cluster center selection method are adopted to eliminate the dependence of the density peak clustering on parameters and the number of clusters, respectively. The experiments undertaken in this study confirmed that the proposed approach outperforms k-means, fuzzy c-means, mean-shift clustering, and density peak clustering with superpixel segmentation in the accuracy of the cluster centers and the validity of the clustering results. 相似文献
9.
This study focuses on the accurate tracking control and sensorless estimation of external force disturbances on robot manipulators. The proposed approach is based on an adaptive Wavelet Neural Network (WNN), named Adaptive Force-Environment Estimator (WNN-AFEE). Unlike disturbance observers, WNN_AFEE does not require the inverse of the Jacobian transpose for computing the force, thus, it has no computational problem near singular points. In this scheme, WNN estimates the external force disturbance to attenuate its effects on the control system performance by estimating the environment model. A Lyapunov based design is presented to determine adaptive laws for tuning WNN parameters. Another advantage of the proposed approach is that it can estimate the force even when there are some parametric uncertainties in the robot model, because an additional adaptive law is designed to estimate the robot parameters. In a theorem, the stability of the closed loop system is proved and a general condition is presented for identifying the force and robot parameters. Some suggestions are provided for improving the estimation and control performance. Then, a WNN-AFEE is designed for a planar manipulator as an example, and some simulations are performed for different conditions. WNN_AFEE results are compared attentively with the results of an adaptive force estimator and a disturbance estimator. These comparisons show the efficiency of the proposed controller in dealing with different conditions. 相似文献
10.
Partial Discharge (PD) measurement is a globally accepted method for insulation diagnosis of electrical assets. The consequences of insulation breakdown are well known. The trend is to move from conventional offline testing to online monitoring for insulation life prediction, which results in the inclusion of high frequency noise in the captured signals. Therefore de-noising is of paramount importance in online monitoring to obtain useful information from the signal.In this research, a 20 kV switchgear panel has been subjected to PD faults in the laboratory and measurements have been carried out by using different non-intrusive sensors including a novel sensor, the D-dot sensor and recorded by a high frequency oscilloscope. The measured results show the effective applicability of sensors for switchgear. The Discrete Wavelet Transform (DWT) has been used to de-noise PD signals in this paper. Time domain and frequency domain comparison of original and de-noised PD signals reveals the significance of this technique for online monitoring of Medium Voltage (MV) switchgear. Finally, an adaptive online de-noising concept, based on automatic de-noising is also proposed in this paper. 相似文献