Thanks to the development of information technology, the health and performance of more and more machine components can be monitored during operation. The use of large amounts of data generated by such sensors requires not only sophisticated calculations but also a great deal of industry experience. The American Electric Power Research Institute (EPRI) has implemented a new demonstration project aimed at combining the two. Diagnosing potential problems in nuclear power plants requires a lot of time and resources. Although a large amount of data can now be obtained through on-line monitoring systems and other condition assessment equipment, it is not an easy task to distinguish between strengths and weaknesses and identify critical or sudden problems. EPRI is developing a forecasting and health management software tool to support nuclear power plants to achieve these goals. For example, an abnormally high temperature reading of a pump or motor bearing can be the first sign of an equipment problem, but if the problem is corrected in time, extensive damage can be avoided. The software automatically recognizes the high temperature readings and alerts the user to list potential problems that trigger the operating conditions. The software then obtains other information from the user to determine which issues need to be corrected. Comprehensive Forecasting and Health Management (FW-PHM) Tool A software tool called Omnidirectional Predictive and Health Management (FW-PHM) enhances monitoring by integrating a large number of technologies, including on-line advanced recognition modes, automatic diagnosis, and remaining life algorithms. In 2013, the software tool was pilot tested at several nuclear power plants and proved that it can shorten the time for diagnosing problems and allow system engineers to focus on solving problems. The complete software package will be used more widely in the first half of this year. Monitoring technologies, such as those used by the FW-PHM software, are at the forefront of advanced industrial management information systems. Based on the so-called big data analysis, industrial monitoring technology automatically provides information that nuclear power plant personnel can use to improve the reliability, efficiency, and productivity of nuclear power plants. The increase in industrial and economic productivity in the past three decades is based on the development and application of digital information and control technology. With the ageing of nuclear power plants, the nuclear power industry has been slow to adopt these technologies. Its current business model and hardware facilities were in the 1980s. If the industry does not adopt an efficient business model, it will be difficult to keep pace with competitors. Monitoring technology is already cost-effective, and delayed adoption may increase operating costs and limit the long-term economic viability of nuclear power plants. The FW-PHM software suite enables nuclear plant personnel to make more informed decisions about operating and maintaining equipment. It can: Reduce equipment failure Plant personnel can anticipate and avoid equipment problems that may limit the production of nuclear power plants or shorten equipment life. Improve reliability and work efficiency This tool helps the nuclear power plant develop a troubleshooting plan that can be used until the fault can be remedied. Because it helps guide the troubleshooting process, when new information comes up, the tool will continue to ask questions to help the nuclear power plant engineer decide what the next most important information to collect is. Create a more formal industry-wide diagnostic experience record When systemic reasons are determined, the nuclear power plant can change their response so that the problem does not recur. Expand knowledge The system is learning through continuous database development each time it is used. Although each nuclear power station or utility company has its own monitoring center, EPRI will collect new troubleshooting information from the experience of the nuclear power plant, compile it, and provide it to all users. Promote the health of nuclear power plants By acquiring the knowledge of experienced engineers, many of them have been operating nuclear power plants safely and reliably for decades and may be considering leaving the workforce. Tools can integrate the knowledge and experience of nuclear power plant employees to help provide continuous equipment health. management. Limitations of existing technologies In many industries, there is already a good precedent: because of the provision of timely monitoring information to correct or prevent maintenance, production losses or catastrophic accidents are avoided. For nuclear power plant applications, engineering efforts to assess anomalies and provide a useful diagnosis of real aging conditions have become an obstacle in expanding the use of technology. EPRI acknowledges that before the project enters this process, an automated diagnostic and prognostic consultant is needed to capture abnormalities and provide diagnostic information immediately. In addition, most nuclear power plants do not have an automated learning framework to capture the acquired experience while troubleshooting and then solving the problem. As a result, some industry problems have experienced the same lengthy diagnosis process again and again. Providing a risk notification and maintaining a useful life expectancy will allow nuclear power plants to prioritize maintenance activities. If properly implemented, this capability will bridge the gap between the need for timely and accurate performance analysis and the availability of nuclear power plant engineering resources. The engineering focus will shift from identifying potential problems, diagnosing asset failures, and providing maintenance guidance to accurately solving problems. Valuable operating assets can prevent premature or untimely failures or avoid life-threatening modes of operation. Container House,Container House For Workshop,Foldable Container House,Container House For Apartment HEBEI KAYI BUILDING MATERIAL TECHNOLOGY CO.,LTD , https://www.kayimesh.com