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Multiple Sensors Soft-Failure Diagnosis Based on Kalman Filter

Author(s): Xiuling XU | Xiaodong WANG

Journal: Signal & Image Processing
ISSN 2229-3922

Volume: 1;
Issue: 2;
Start page: 126;
Date: 2011;
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Keywords: soft-failure | residual | Kalman filter | multiple-failure-hypothesis based testing | fault detection and isolation

Sensor is the necessary components of the engine control system. Therefore, more and more work must dofor improving sensors reliability. Soft failures are small bias errors or drift errors that accumulaterelatively slowly with time in the sensed values that it must be detected because of it can be very easy tobe mistaken for the results of noise. Simultaneous multiple sensors failures are rare events and must beconsidered. In order to solve this problem, a revised multiple-failure-hypothesis based testing isinvestigated. This approach uses multiple Kalman filters, and each of Kalman filter is designed based ona specific hypothesis for detecting specific sensors fault, and then uses Weighted Sum of SquaredResidual (WSSR) to deal with Kalman filter residuals, and residual signals are compared with thresholdin order to make fault detection decisions. The simulation results show that the proposed method can beused to detect multiple sensors soft failures fast and accurately.
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