Distributed Vibration Monitoring System for 10 kV-400 kVA 3D Wound Core Transformer under Progressive Short-Circuit Impulses.

As large-scale, high-proportion, and efficient distribution transformers surge into the grids, anti-short circuit capability testing of transformer windings in efficient distribution seems necessary and prominent. To deeply explore the influence of progressively short-circuit shock impulses on the core winding deformation of efficient power transformers, a finite element theoretical model was built by referring to a three-phase three-winding 3D wound core transformer with a model of S20-MRL-400/10-NX2. The distributions of internal equivalent force and total deformation of the 3D wound core transformer along different paths under progressively short-circuit shock impulses varying from 60% to 120% were investigated. Results show that the equivalent stress and total deformation change rate reach their maximum as the short-circuit current increases from 60% to 80%, and the maximum and average variation rate for the equivalent stress reach 177.75% and 177.43%, while the maximum and average variation rate for the total deformation corresponds to 178.30% and 177.45%, respectively. Meanwhile, the maximum equivalent stress and maximum total deformation reach 29.81 MPa and 38.70 µm, respectively, as the applied short-circuit current increased to 120%. In light of the above observations, the optimization and deployment of wireless sensor nodes was suggested. Therefore, a distributed monitoring system was developed for acquiring the vibration status of the windings in a 3D wound core transformer, which is a beneficial supplement to the traditional short-circuit reactance detection methods for an efficient grid access spot-check of distribution transformers.

A Novel Framework for Automation Technology Based on Machine Vision and Robotics in Electrical Power Inspection Processing.

As a well-known support, computer vision is a powerful factor to improve the application and development of the electronic system. Whether the power system can operate safely and stably can greatly influence the deduction of providence. All types of electric swinging devices are easily disturbed by various factors during the assistance operation. The ubiquitous power system that operates everywhere becomes extremely small once the electrical equipment is abandoned. For the current complexity system, if the old-fashioned hand-written visual monitoring system is still used, not only will their ability fails to meet the requirements but also the number of cumbersome, important, and financial context will be unsatisfactory. It is natural to reason about some problems. Serious problems are due to incompetent human investigation. Issues are not optimally handled during this period. The application of Coach Ken technology can fully utilize machine vision technology to analyze the salient data and identify dominant devices that support shape vision. Meanwhile, it can truly realize the supervision system of perception and machine control. In view of this, we in this work mainly expound the artifact recognition technology supported by machine vision reproduction. Besides, we disassemble the composition method of the electric power supply recognition system supported by machine vision parallel, in order to enhance the future work.