Wireless Sensor Network Modeling and Deployment Challenges in Oil and Gas Refinery Plants

Abstract

Wireless sensor networks for critical industrial applications are becoming a remarkable technological paradigm. Large-scale adoption of the wireless connectivity in the field of industrial monitoring and process control is mandatorily paired with the development of tools for the prediction of the wireless link quality to mimic network planning procedures similar to conventional wired systems. In industrial sites, the radio signals are prone to blockage due to dense metallic structures. The layout of scattering objects from the existing infrastructure influences the received signal strength observed over the link and thus the quality of service (QoS). This paper surveys the most promising wireless technologies for industrial monitoring and control and proposes a novel channel model specifically tailored to predict the quality of the radio signals in environments affected by highly dense metallic building blockage. The propagation model is based on the diffraction theory, and it makes use of the 3D model of the plant to classify the links based on the number and density of the obstructions surrounding each individual radio device. Accurate link classification opens the way to the optimization of the network deployment to guarantee full end-to-end connectivity with minimal on-site redesign. The link-quality prediction method based on the classification of propagation conditions is validated by experimental measurements in two oil refinery sites using industry standard ISA SP100.11a compliant devices operating at 2.4 GHz.

Network design and planning of wireless embedded systems for industrial automation

“…Looking at the dual problem of optimal wireless node deployment, different strategies have been considered in the literature for targeting connectivity, coverage, node lifetime, and/or QoS [2]. However, the majority of published work on sensor network deployment limits its focus on simplified and analytically tractable 1D and 2D environments where connectivity can be considered as a primary/secondary objective or as a constraint in the deployment problem [6].…”

“…Although several models have been proposed in the literature, e.g., see [17] for reviewing, these cannot fully capture the unique propagation characteristics of industrial environments. In addition, most of conventional ray-tracing tools turn out not to be practical to process the high number of structures and their complexity in large industrial sites [2]. This motivates the development of accurate site-specific channel models based on a set of measurements taken in typical industrial sites.…”

“…It adopts the propagation model proposed in [2], which suggests using the 3D model of the plant to classify the links based on the number and the density of the surrounding obstructions. The paper also discusses how the coexistence of different wireless networks might affect this model.…”

Wireless Virtual Multiple Antenna Networks for Critical Process Control: Protocol Design and Experiments

“…The configuration of the primary routing path is optimized as it is based on radio planning. In complex environments like refinery or power plants, the use of the 3D model during the design phase is also crucial to maximize radio-planning accuracy in order to limit any rework to a percentage which is in line with a regular installation of a wired system [15].…”

“…Today, commercial battery-operated systems are based on the IEEE 802. 15.4 standard and enable data to be transmitted at a typical rate of 250 kbit/s (and scaling up to 2 Mbit/s by disabling direct-sequence spread spectrum functions), with up to a maximum of 10 dBm output RF power to meet the RF regulations for hazardous environments. The IEEE 802.15.4 physical layer also constitutes the basis for the wireless HART [7] and ISA100.11a [8] industry standard protocols.…”