KEYWORDS: Internet, Internet of things, Data transmission, Network security, Data storage, Computer security, Statistical analysis, Data processing, Information technology, Chemical elements
In the energy Internet integration mechanism, any abnormal data behaviour may affect the operation security of the network system. In order to accurately detect the abnormal transmission behaviour of data stream samples, this paper studies the abnormal detection method of the large data streams in energy Internet based on high-order statistical features. According to the principle of higher-order statistics, this paper defines statistical indicators. Combined with the characteristic function expression, the range of phase space parameters is determined, and the verification of abnormal large data stream information is realized. Hadoop distributed detection framework is set, and the accurate calculation result of abnormal scheduling coefficient is obtained by solving the vector of the high-dimensional large data stream, and the design of abnormal detection method for large data stream of energy Internet based on high-order statistical characteristics is completed. The experimental results show that under the high-order statistical principle, the detection accuracy of abnormal information of data stream samples by energy Internet hosts is improved, which has outstanding value in maintaining the running security of the network system.
The conventional transmission line fault location method has the problem of imperfect transient traveling wave mathematical model, resulting in large location error. A 66kV transmission line fault location method based on regional search is designed. The fault arc is divided according to the different arc power supply, the arc amplitude of 66kV transmission line is obtained, the operation data is processed synchronously, the fault information source is searched and identified in the region, the electrical quantity and its energy are redistributed, the transient traveling wave mathematical model is constructed, the signal three-phase voltage is collected, and the fault location mode is designed. Experimental results: the average location error between the 66kV transmission line fault location method and the other two 66kV transmission line fault location methods is 0.394%, 0.707% and 0.706%. It is proved that the 66kV transmission line fault location method combined with regional search is more suitable for power operation tasks.
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