17 April 2006 Sensor and system health management simulation
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Abstract
The health of a sensor and system is monitored by information gathered from the sensor. First, a normal mode of operation is established. Any deviation from the normal behavior indicates a change. Second, the sensor information is simulated by a main process, which is defined by a step-up, drift, and step-down. The sensor disturbances and spike are added while the system is in drift. The system runs for a period of at least three time-constants of the main process every time a process feature occurs (e.g. step change). The wavelet Transform Analysis is performed on three sets of data. The three sets of data are: the simulated data described above with Poisson distributed noise, real Manifold Pressure data, and real valve data. The simulated data with Poisson distributed noise of SNRs ranging from 10 to 500 were generated. Due to page limitations only the results of SNR of 50 is reported. The data are analyzed using continuous as well as discrete wavelet transforms. The results indicate distinct shapes corresponding to each process.
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Abolfazl M. Amini, "Sensor and system health management simulation", Proc. SPIE 6247, Independent Component Analyses, Wavelets, Unsupervised Smart Sensors, and Neural Networks IV, 624705 (17 April 2006); doi: 10.1117/12.659857; https://doi.org/10.1117/12.659857
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