Sistema inteligente para apoio à decisão na operação de uma malha de escoamento de petróleo

The petroleum production pipeline networks are inherently complex, usually decentralized systems. Strict operational constraints are applied in order to prevent serious problems like environmental disasters or production losses. This paper describes an intelligent system to support decisions in the operation of these networks, proposing a staggering for the pumps of transfer stations that compose them. The intelligent system is formed by blocks which interconnect to process the information and generate the suggestions to the operator. The main block of the system uses fuzzy logic to provide a control based on rules, which incorporate knowledge from experts. Tests performed in the simulation environment provided good results, indicating the applicability of the system in a real oil production environment. The use of the stagger proposed by the system allows a prioritization of the transfer in the network and a flow programming

Extensões ao Projeto LVWNet: mobilidade, interação com equipamentos reais, comunicação direta, e registro dinâmico de nós

Due to the constantly increasing use of wireless networks in domestic, business and industrial environments, new challenges have emerged. The prototyping of new protocols in these environments is typically restricted to simulation environments, where there is the need of double implementation, one in the simulation environment where an initial proof of concept is performed and the other one in a real environment. Also, if real environments are used, it is not trivial to create a testbed for high density wireless networks given the need to use various real equipment as well as attenuators and power reducers to try to reduce the physical space required to create these laboratories. In this context, LVWNet (Linux Virtual Wireless Network) project was originally designed to create completely virtual testbeds for IEEE 802.11 networks on the Linux operating system. This paper aims to extend the current project LVWNet, adding to it the features like the ability to interact with real wireless hardware, provides a initial mobility ability using the positioning of the nodes in a space coordinates environment based on meters, with loss calculations due to attenuation in free space, enables some scalability increase by creating an own protocol that allows the communication between nodes without an intermediate host and dynamic registration of nodes, allowing new nodes to be inserted into in already in operation network

Modelagem do consumo de energia de redes de sensores sem fio usando SystemC-AMS e stateflow

This work aims at modeling power consumption at the nodes of a Wireless Sensor Network (WSN). For doing so, a finite state machine was implemented by means of SystemC-AMS and Stateflow modeling and simulation tools. In order to achieve this goal, communication data in a WSN were collected. Based on the collected data, a simulation environment for power consumption characterization, which aimed at describing the network operation, was developed. Other than performing power consumption simulation, this environment also takes into account a discharging model as to analyze the battery charge level at any given moment. Such analysis result in a graph illustrating the battery voltage variations as well as its state of charge (SOC). Finally, a case study of the WSN power consumption aims to analyze the acquisition mode and network data communication. With this analysis, it is possible make adjustments in node-sensors to reduce the total power consumption of the network.

Sistema inteligente para apoio à decisão na operação de uma malha de escoamento de petróleo

The petroleum production pipeline networks are inherently complex, usually decentralized systems. Strict operational constraints are applied in order to prevent serious problems like environmental disasters or production losses. This paper describes an intelligent system to support decisions in the operation of these networks, proposing a staggering for the pumps of transfer stations that compose them. The intelligent system is formed by blocks which interconnect to process the information and generate the suggestions to the operator. The main block of the system uses fuzzy logic to provide a control based on rules, which incorporate knowledge from experts. Tests performed in the simulation environment provided good results, indicating the applicability of the system in a real oil production environment. The use of the stagger proposed by the system allows a prioritization of the transfer in the network and a flow programming