GIS surface assessment by image processing particle detector

In this paper, we aim to study the surface effect of image processing particle detector for high voltage gas insulated switchgear. The algorithm of the particle detector was based on image processing approach. We propose the new methodology during the installation of new switchgear to prevent flashover phenomena caused by foreign metallic particle. To see the flexibility of the detector, the detector will be tested on different surface condition and lighting condition

Particle detector for gas insulated switchgear and the effect on environment

High voltage Gas Insulated Switchgear (GIS) is prone to metallic particles. The particle void can reduce the dielectric strength of the insulation material of SF6 gas. This paper discusses the developed particle detector for GIS using a new approach by using image processing to reduce flashover phenomena occurring on energized GIS. The particle detector consists of borescope, laptop and a detection program. The program was coded using MATLAB using image processing algorithm. The in-lab test was conducted on the simulated GIS to see the effectiveness of the particle detector to detect small particles inside the narrow GIS enclosure. In real world application, the borescope will be inserted through GIS access hole before filling the enclosure with SF6 gas. This new approach is proposed to be conducted during the erection and commissioning of new GIS. This new approach looks promising because it can reduce flashover phenomena caused by existence of metallic particle and also reduces Greenhouse gas emission to the air

Evaluacion metodologica del impacto ambiental de un puerto deportivo

Centro de Informacion y Documentacion Cientifica (CINDOC). C/Joaquin Costa, 22. 28002 Madrid. SPAIN / CINDOC - Centro de Informaciòn y Documentaciòn CientìficaSIGLEESSpai

Do Surges in International Capital Inflows Influence the Likelihood of Banking Crises? Cross-Country Evidence on Bonanzas in Capital Inflows and Bonanza-Boom-Bust Cycles

This paper asks whether bonanzas (surges) in net capital inflows increase the probability of banking crises and whether this is necessarily through a lending boom mechanism. A fixed effects regression analysis indicates that a baseline bonanza, identified as a surge of one standard deviation from trend, increases the odds of a banking crisis by three times, even in the absence of a lending boom. Thus, a bonanza raises the likelihood of a crisis from an unconditional probability of 4. 4 percent to 12 percent. Larger windfalls of capital (two-s. d. bonanzas) increase the odds of a crisis by eight times. The joint occurrence of a bonanza and a lending boom raises these odds even more. Decomposing flows into FDI, portfolio-equity and debt indicates that bonanzas in all flows increase the probability of crises when the windfall takes place jointly with a lending boom. Thus, windfalls in all types of flows exacerbate the deleterious effects of credit. However, surges in portfolio-equity flows seem to have an independent effect, even in the absence of a lending boom. Furthermore, emerging economies exhibit greater odds of crises after a windfall of capital