An Intelligent Monitoring System for Natural Gas Odorization

In this paper, we present the design of an intelligent monitoring system consisting of physical sensors and intelligent software for the automatic identification of the concentration of natural gas odorants in the environment. An optical-based sensor array was proposed comprising the hardware module. The software module employs wavelets filters and artificial neural networks to recognize the concentration of odorant in a natural gas sample. The objective is to help the natural gas odorization process by means of end point monitoring through the recognizing of the odorant concentration. The recognizing process uses a benchmark index, which measures the degrees of human perception of gas in the environment. In this way, the proposed system tries to mimic the human perception of a natural gas leak and helps one to indicate if more or less amount of odorant should be added into the gas pipeline. Experiments were conducted comparing the performance of the system with human performance, which is normally used to deal with this problem. The proposed system demonstrated promising results and improvements are presented.