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This letter demonstrates the use of modal logic for knowledge representation for condition monitoring of gas turbine start-up sequences. The potentially large amounts of data and the complex real-time processes behind on-line fault detection indicate the need for software entities that can reason and react to changing environmental conditions. These are known as intelligent software agents. As a consequence, data interpretation is achieved by converting the data into appropriate information and combining individual agents' knowledge, resulting in an automatic fault diagnosis.