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Approach to Early Boiler Tube Leak Detection with Artificial Neural Networks

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Abstract

The early boiler tube leak detection is highly desirable in power plant for prevention of following utility destruction. In the paper the results of artificial neural network (ANN) models of flue gas humidity for steam leak detection are presented and discussed on example of fluid boiler data.

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References

  1. A. T. Alouani, P. Shih-Yung Chang “Artificial Neural Network and Fuzzy Logic Based Boiler Tube Leak Detection Systems” USA Patent No: 6,192,352 B1, Feb 20, 2001.

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  4. K. Olwert, „Opracowanie i analiza modelu wilgotności spalin w zadaniu wczesnej detekcji nieszczelności parowej kotła bloku energetycznego” praca dyplomowa PW D-IAR-306, 2006, praca niepublikowana.

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  5. R. J Patton, C.J Lopez-Toribio, F.J Uppa “Artificial Intelligence Approaches to Fault Diagnosis” Int. Jour. of Applied Mathematics and Computer Science. Vol.9No 3. 471–518 (1999).

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© 2007 Springer-Verlag Berlin Heidelberg

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Jankowska, A. (2007). Approach to Early Boiler Tube Leak Detection with Artificial Neural Networks. In: Jabłoński, R., Turkowski, M., Szewczyk, R. (eds) Recent Advances in Mechatronics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73956-2_12

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  • DOI: https://doi.org/10.1007/978-3-540-73956-2_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73955-5

  • Online ISBN: 978-3-540-73956-2

  • eBook Packages: EngineeringEngineering (R0)

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