Methods of diagnostics of electrical equipment by fiber-optic sensors on the Faraday Effect

Abstract

One of the important problems in the operation and creation of a complex technical system is the provision of diagnostics of electrical equipment. This is especially important when diagnosing electrical equipment at an industrial complex belonging to the class of spark -explosive production facilities. The task of ensuring the operability of electrical equipment and preventing emergency situations due to timely detected breakage or violation of the insulation properties of the equipment includes a whole range of certain measures. In the process of operation, technical diagnostics of electrical equipment occupies a special place among complex technical devices at oil refineries. One of the most modern sensors for diagnosing electrical equipment is multiplicative sensors, which use optical fiber. Fiber-optic sensors have special proper-ties. The Faraday Effect is the basis for the construction of fiber-optic sensors for diagnostics of electrical equipment. Methods for diagnosing electrical equipment with fiber-optic sensors based on the Faraday Effect depend on the principles of the sensors themselves. This article presents the results of the study of the creation of experimental fiberoptic sensors based on the Faraday Effect. In this paper, it is proposed to carry out diagnostics of electrical equipment at an industrial complex belonging to the class of spark - explosive production facilities, such as oil refineries, using the use of fiber-optic sensors based on the Faraday Effect.

Infrared Technology-Based Sensor Data Analysis for Thermal Fault Identification of Electrical Equipment in Intelligent Substations

“…At this time, according to the subspace component of the thermal fault sample information of the electrical equipment in the intelligent substation, the frequency distributed fusion results of the thermal fault parameters of the electrical equipment in the intelligent substation are obtained [16], and the closing conditions are manually traversed and changed to obtain the frequency component of the thermal fault characteristics of the electrical equipment in the intelligent substation. e calculation formula is expressed as follows:…”