Abstract

This paper conducts sensitivity analysis and sensitivity-based design for linear filter alarm monitoring systems. Based on a derivative-based local sensitivity measure, models are proposed to assess the sensitivity of the system detection errors to changes in the trip point and to uncertainties in the collected data. Then, analytical expressions are derived to quantitatively evaluate the sensitivity of a general linear alarm filter with unknown data distributions. Subsequently, a new sensitivity-based linear filter design method is formulated to minimize a weighted sum of the detection errors subject to upper bounds on the system sensitivities. Extensive simulations with both Gaussian and industrial data are conducted to verify the analytical results and to show trade-offs between the detection errors and sensitivities of linear filter alarm system.

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