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In terms of optimization, a methodology to assist the decision for the sequence of visits to be made by maintenance technicians on the various wind generators is proposed. This methodology takes into account the on-condition maintenance plan previously defined. The proposed optimization method uses genetic algorithms and a specific solution to solve the sequence of visits problem.The organization of the maintenance management of wind farms is structured, integrating a set of developed hardware and software modules, as well as a set of updates and new modules, developed for the SMIT software. The proposed structure including the new modules, allows implementations based on corrective maintenance, planned maintenance and on condition maintenance. A client/server maintenance management system was developed, using open-source software whenever possible. It includes the Linux operating system, the PostgreSQL database engine, and the development tools Octave, R, Apache and PHP. The SMIT client was programmed using Delphi and interacts with the user through the Windows platform.
In terms of hardware, the followed methodology relies on the use of low cost components and devices, to create a data acquisition system over IP networks. The basic idea consists on distributing a master clock to the different field equipments, to ensure the synchronous acquisition at the different data collection points. The SNTP and PTP protocols were used to implement a set of control techniques in order to achieve clock synchronization. The basic structure of the system uses data collecting devices connected through a CAN network. One of the devices, which has CAN and Ethernet connectivity, coveys the acquired information and relays it to the SMIT server. Simultaneously, this master node controls the data acquisition sequence, as well as the clock synchronization with the SMIT server. The integration of the developed hardware and software modules implies the flow of data from the acquisition nodes to the server, which sends time references to the master device, including the reference clock signal. The SMIT server, using algorithms based on Time Series, analyzes the acquired data using the Octave or R platforms, to predict possible failures or dysfunctional states. Based on these predictions, the server can anticipate the generation of the respective alerts, with the emission of the corresponding Working Orders.",
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FEUP oai:digitool.fe.up.pt:227412
Supervisor: Fernando Maciel Barbosa",
Genetic Programming entries for Inacio de Sousa Adelino da Fonseca