FUZZY SENSOR VALIDATION AND FUSION Fuzzy Sensor Validation and Fusion for Gas Turbine Power Plants

نویسنده

  • Kai Goebel
چکیده

This paper introduces a fuzzy sensor validation and fusion methodology and applies it to sensor data from a gas turbine power plant. The FUSVAF (Fuzzy Sensor Validation and Fusion) algorithm tackles two problems: (1) It filters out noise from measurements provided as input to a gas turbine controller to maximize power plant performance. (2) It compensates for sensor failure to allow the power plant to operate despite temporary or permanent failure of one or more sensors. Using a combination of direct and functional redundancy the fusion algorithm determines confidence values for each sensor reading from nonlinear validation curves, which progressively discount readings with increasing distance from the predicted value. The predicted value in the FUSVAF algorithm is obtained through application of a Fuzzy Exponential Weighted Moving Average (FEWMA) time series predictor with adaptive coefficients. Simulations and a sensitivity analysis are used to validate the fuzzy rules and show the robustness of the chosen parameters. Experiments on operating data from a gas turbine in an electric power generating plant show how an increase in redundancy improves the robustness of the FUSVAF algorithm and leads to smoother controller input values. FUZZY SENSOR VALIDATION AND FUSION Fuzzy Sensor Validation and Fusion for Gas Turbine Power Plants Kai Goebel GE Global Research Information & Decision Technologies Alice Agogino Department of Mechanical Engineering University of California at Berkeley

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تاریخ انتشار 2002