A Study on Developing IGAS for Analyzing the Status of Gas Facility

Abstract

Gas facilities such as LPG station have showed frequently diverse accidents, because they are seemed to satisfy only institutional requirements. In Gas accidents, human is damaged directly because most cause is careless handling and inadequate safety equipment, most type is explosion, fire and rupture. Therefore, an advanced safety process is required for enforcing gas safety management. Although correct progress direction in advances safety process is necessary for many devices, methods and system, it is to require analysis method that many different data are analyzed in parallel but each measuring data is analyzed in individual. This paper preferentially aims to check the feasibility of machine learning analysis in order to apply a safety of gas facility, and devise method using artificial intelligent algorithm in order to manage total safety analysis that can analyze simultaneously many different data. At First, the feasibility study must be generally selected target gas facility, collected what kinds of risk factor, and then considered the appropriated machine learning method. Next, our research develops total risk analysis algorithm with a combination method between classification and clustering algorithm. Finally, we developed IGAS (Intelligent Gas Analysis System) for small gas facility version. This method and system are to mark the beginning of analysis method for detecting cause and increasing safety about gas facilities.