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For optimal performance a modern intralogistic system needs to monitor its maintenance state to avoid unnecessary down-times. This paper proposes the Smart Drive concept of a distribution of static and mobile sensors and presents an approach to localize mobile measurement units on conveyor tracks and to map disturbances and areas of potential future failure. The localization is performed using stochastically robust methods to allow applicability under real-world conditions including imperfect sensor calibration or imprecise information about the tracks. The proposed algorithm is evaluated using real sensor data gathered in an experimental scenario.