Volatile organic compounds (VOC) gas leak detection by using infrared sensors

Abstract

Advances in technology and industry leads to a rise in the living standards of people. However, this has also introduced a variety of serious problems, such as the undesired release of combustible and toxic gases which have become an essential part of domestic and industrial life. Therefore, detection and monitoring of VOC gases have become a major problem in recent years. In this thesis, we propose novel methods for detection and monitoring VOC gas leaks by using a Pyro-electric (or Passive) Infrared (PIR) sensor and a thermopile sensor. A continuous time analog signal is obtained for both of the sensors and sent to a PC for signal processing. While using the PIR sensor, we have Hidden Markov Models (HMM) for each type of event to be classified. Then, by using a probabilistic approach we determine which class any test signal belongs to. In the case of a thermopile sensor, in addition to Hidden Markov Modeling method, we also use a method based on the period of the sensor signal. The frequency of the output signal of the thermopile sensor increases with the presence of VOC gas leak. By using this fact, we control whether the period of a test signal is below a predefined threshold or not. If it is, our system triggers an alarm. Moreover, we present different methods to find the periods of a given signal.