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In this paper, taking typical porcelain insulators for research objects, the deteriorated diagnosis model of single insulator infrared image is studied. By infrared imaging, layered cutting, homomorphic filtering de-noising, a set of single insulator to be processed is obtained. Based on the sparse characteristics of single insulator infrared image, building an over-complete dictionary with the single image as the constituent atom. The sparse representation coefficient of the identified image in the dictionary is calculated, diagnosing identified single insulator according to the nonzero term in the coefficient. Through test and analysis, the designed diagnostic model of single insulator has high classification accuracy. Furthermore, it also has stronger noise immunity to the background and a better recognition ability for the initial heating of the deteriorated insulator.

Deteriorated insulators may lead to flashover or power failure in transmission lines, because of degradation in insulators strings' mechanism and insulation level after long periods of performing. By utilizing finite element method, E-field intensity and potential distribution of insulators strings with different resistance in different positions under the same pollution level have been researched. Simulation results indicate that: 1, E-field line distorts most seriously on the joint of deteriorated insulators' porcelain and steel-foot, spreading along the outline of deteriorated insulators, making the insulator looks like equipotential. 2, E-field intensity distorts most gravely on the joint of porcelain and steel-foot as well, the distortion will aggravate as the deteriorated position approaching the high-voltage side. 3, Comparing with normal insulator strings, except the deteriorated position, the voltage of the every one of the rest insulators bears in the deteriorated strings rise, which can rise up to 26.77%, causing normal insulators accelerated aging. The statics above provide some theoretical support for the deteriorated insulators detection according to characteristics.

In this paper, a new detection method of high voltage bushing is proposed using Hu invariant moments and Support Vector Machine (SVM), which is designed in regard to both complex environments of transformer substation and the characteristics of pictures obtained by inspection robots. The Niblack algorithm is first used as a binarization method to decrease the influence of changing of lighting. The morphology method is then used to remove messy interference while maintaining the morphological characters of the target, and a few potential regions of high voltage bushing can be found. Hu invariant moments is used to extract the features of the potential positions, and a SVM is trained to classify and recognize the positions of high voltage bushing. The experimental results show that the proposed detection method is effective and it can remove the complex background of the substation and reduces the influence of changed lighting, shooting position and shooting angle.

With the unceasing improvement of the on-site comprehensive automation level of substation and increasing number of unattended substation, the work efficiency of substation tour-inspection should be higher and higher. It is crucially important to detect equipment failure and hidden dangers timely and effectively. The paper disposed the acquired equipment image with the purpose to quickly and accurately detect equipment abnormity for forewarning of equipment fault and hidden dangers. It is of important and practical application significance for the safe and reliable operation of the power grid.

Transformation equipment on-line monitoring device aims at monitoring substation equipment operation parameters. Through internal network, the data will be transported to the on-line monitoring platform of electric power internal network to provide maintenance basis for maintenance department. While the existing calibration method needs professional personnel carrying relevant calibrators and conducting contrast calibration on site. In order to make up for deficiency of existing substation on-line monitoring device calibration, such as instruments isolated with each other, instrument control and data management low automation, data contrast, retrieval and archiving is inconvenient, personnel requirement large and so on. This paper presents a new method for intelligent check of transformation equipment condition monitoring device based on wireless communication technology and computer control technology. It can promote the accuracy of calibration greatly and provide a powerful guarantee to grid reliable operation.

The calibration of SF6 gas density on-line monitoring device needs to simulate different pressure environment to calibrate the data accuracy of the on-line monitoring device. At present, the simulation of different pressure environment is conducted by artificial cranking bar to change the stroke of cylinder piston to realize the aim of change the gas pressure. Generally, technical personnel take calibration device to the field, select a suitable pressure, connect the checked device to test button and conduct the contrast calibration. Based on above operation, multi-group data of the checked on-line monitoring device can be obtained. While this method depends on artificial manual operation, squander time and vigour and can not set pressure value exactly. In order to make up for deficiency of existing problems, the paper presents a calibration device on SF_6 gas density monitoring equipment. The calibration device can make the calibration procession conducted automatically through controlling the pressure and its lasting time automatically. The use of the device can effectively complete calibration and improve the quality of work.Facts show that it can provide a powerful guarantee to grid equipment reliable operation.

Aiming at the existing problems such as heavy workload and low efficiency of intelligent substation state monitoring device calibration, combined with the current information technology and intelligent technology, his paper presents a vehicle-borne intelligent verification system. The system adopts vehicle as the platform and transport data through GPRS/3G and MIWAVE wireless network. From the point of function optimization, information interaction and intelligent monitoring, the system realizes the integrated, information and intelligent transformation of kinds of standard signal source device and monitoring equipment for calibration. The use of the system can effectively complete calibration and improve the quality of work. The system has completed the calibration of many 500kV, 220kV substations monitoring devices successfully. Facts show that it can provide a powerful guarantee to grid equipment reliable operation.