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A New Method For Multisensor Data Fusion Based on Wavelet Transform in A Chemical Plant
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نویسنده
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Salahshoor Karim ,Ghesmat Mohammad ,Shishesaz Mohammad Reza
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منبع
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Iranian Journal Of Oil And Gas Science And Technology - 2014 - دوره : 3 - شماره : 3 - صفحه:62 -74
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چکیده
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This paper presents a new multi-sensor data fusion method based on the combination of wavelettransform (wt) and extended kalman filter (ekf). input data are first filtered by a wavelettransform via daubechies wavelet “db4” functions and the filtered data are then fused based onvariance weights in terms of minimum mean square error. the fused data are finally treated byextended kalman filter for the final state estimation. the recent data are recursively utilized toapply wavelet transform and extract the variance of the updated data, which makes it suitable to beapplied to both static and dynamic systems corrupted by noisy environments. the method hassuitable performance in state estimation in comparison with the other alternative algorithms. athree-tank benchmark system has been adopted to comparatively demonstrate the performancemerits of the method compared to a known algorithm in terms of efficiently satisfying signal-tonoise(snr) and minimum square error (mse) criteria.
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کلیدواژه
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Multisensor ,Data Fusion ,Wavelet Transform ,Extended Kalman Filter ,Minimum Mean Square Error (Mmse)
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آدرس
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Petroleum University Of Technology, Department Of Automation And Instrumentation, Petroleum University Of Technology, Ahwaz, Iran, ایران, Petroleum University Of Technology, Department Of Automation And Instrumentation, Petroleum University Of Technology, Ahwaz, Iran, ایران, Petroleum University Of Technology, Department Of Technical Inspection Engineering, Petroleum University Of Technology, Abadan, Iran, ایران
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Authors
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