DEVELOPMENT OF FAULT DETECTION MODEL FOR INSTRUMENT IN GAS TRANSPORTATION SYSTEM

The increasing demands for a better system performance and quality have led to the development of the automation of technical process. However, the system dependability and reliability to overcome the fault in the system is the issues that being addressed regarding the design of control and automation system. There are many research regarding the Fault Detection and Diagnosis (FDD) that has been conducted to enhance the reliability of the system in the plant process. Artificial intelligence such as neural network is one of the powerful tools in detecting and diagnosis the fault occurred. The ability of the neural networks to learn from the experience or past data has shown a great impact in the fault detection efficiency. Apart from that, statistical method which is based on the past data also is being proven to improve the accuracy of the fault detection in any fields. Thus, this preliminary report contains five chapters which are the introduction, literature review, methodology, result and discussion and finally conclusion. The first chapter of the report will give the overview of the project along with the problem statements. Based on the problem statements, the objectives of the project are being derived. The main objective is to develop the best fault detection model to be implemented in the gas transportation system. Next, the second chapter is to review the past research and study in this area in order to synthesize and obtaining information on how the fault detection can be done by using statistical and artificial intelligence methods. On the other hand, the third chapter will outline the project planning and activities throughout the time frame given. The methodology on how the project will be executed also being explained in this chapter. Next, in Chapter 4, the findings and results will be discussed based on the methodology outlined in the previous chapter. Finally, Chapter 5 will summarize and conclude the future planning of the project