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The Support Vector Machine (SVM) is a classical classification algorithm that has a wide range of application. With kernel function, SVM can dispose the datasets that are not linearly separable in their original feature space, making it more flexible in practical use compared with linear model. However, its complexity in training is an obstacle to large-scale dataset handling. This paper proposes...
Reliable life is defined as the average operation time of power equipment in a given reliability, and it is a significant parameter in reliability evaluation. This paper presents a reliable life calculation method for SF6 circuit breakers. The reliability evaluation model is established based on Fault Tree Analysis (FTA) method. From FTA, all the bottom events which cause top event (failure of the...
The power system reliability sensitivity analysis can recognize weak parts of the system. It is significant for system reliability assessment and enhancement. Against deficiencies in conventional reliability sensitivity analysis, this paper proposes an improved method by analyzing graphical representations of sensitivity and practical engineering requirements. This method meets real needs better and...
Ill-structured road scenarios are complicated due to inhomogeneous road surface and the lack of clear boundaries. In this paper, we propose a novel road boundary detection approach which is based on the multi-scale detection scheme and the use of patch-wise boundary cues. A characteristic scale range of road boundaries is first defined and estimated as a priori knowledge. Then, the patches with high...
With constant promotion and deepening of smart power grids, the data volume of power grid operation and equipment monitoring gain exponential growth and the environment of big data in electric system forms. Many platforms are deployed to meet different demands of equipment operation and maintenance. Since these platforms are independent and cannot be used in coordination, multi-sourced heterogeneous...
As a representative of deep learning, Boltzmann machine is being widely studied to solve some complex problems. The model of deep Boltzmann machine has been successfully applied to unsupervised learning for single modality (e.g., text, images, video or audio). In this work, we focus on the model for multiple input modalities and apply it to fault diagnosis. At present, most work on fault diagnosis...
In recent years, along with the development of industrial control equipments and electric vehicles, the control and communication communities have witnessed the growing demand of system interconnection, intercommunication, and interoperation. Therein a key issue is to connect these objects to a network through embedded control chips. In this paper, we design and implement an embedded Ethernet system...
This paper evaluates the reliability of main connections in the power plant or substation based on the Monte-Carlo simulation algorithm. The proposed simulation procedure can simulate the process of faults isolation and switching operation by means of improved topology analysis algorithm, which makes simulation more practical, to improve the calculation accuracy. Meanwhile, one kind of effective reliability...
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