Wireless Networks for Industrial Applications

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The goal of this program is to remove the barriers for using wireless networks to connect the sensors and controllers used at industrial facilities. This work falls into the area of cyber-physical systems and involves finding the best ways to control physical systems over data networks. While this research is applicable to any industrial setting, the focus will be on networks for petroleum refineries due to the importance of the energy industry to Alberta and Canada. Wireless sensor networks have yet to achieve wide commercial deployment in spite of being a popular research topic for many years. In contrast, wired sensor and control networks have been used in industrial facilities worldwide for over 30 years. There is strong economic incentive to transition these wired networks to wireless. Since explosive vapors may be present at a refinery, safety regulations require all network cables to be encased in steel shielding. This means that the cost of installing wires to connect new sensors can range from $200/foot to $2,000/foot. Using a wireless link would eliminate most of this cost. The economic case for wireless industrial networks is clear but there are still technical challenges that must be overcome before wireless can be used with confidence. The purpose of this research program is to address the most critical of these challenges. First, there is little information on how the wireless signal behaves in a refinery environment. Compared to other industrial sites, refinery environments have a much higher concentration of metal objects such as pipes and vessels. This program will be the first to conduct a wireless field measurement campaign at an operating petroleum refinery. The next challenge is to use the wireless measurement data to develop more accurate models for predicting received wireless signal power in an industrial environment. Wireless reflections cause random variations in received power which lead to uncertainty when planning how much transmit power is required to maintain reliable links. This makes it difficult to predict node power consumption and lifetime. This program will utilize theory based on random distributions of scatterers with different densities to develop more accurate wireless propagation models that will reduce uncertainty during network planning. The final challenge is to determine if it is possible to guarantee the stability of industrial process control algorithms that are running over high reliability wireless networks. A control algorithm can become unstable when sensor and controller commands traveling over a network are delayed or lost. This can place both the facility and lives at risk. This program will utilize mathematical analysis to determine the distribution of random delays that can be expected over a wireless network. That distribution will then be used in an analysis of the stability of the industrial control algorithm that is using the network.