Development and Application of Baseline Correction Algorithm for Heavy Metal Detection Sensing Signals in Water Environment
Heavy metal pollution in water can pose threats to human health and the ecological environment.Rapid detection of heavy metal content in water is one of the key steps in eliminating heavy metal hazards.Based on the problem of baseline drift of sensing signals affecting the accuracy of analysis in heavy metal detection in water using existing detection equipment,and the limitation of the asymmetrically reweighted penalized least squares(arPLS)algorithm that cannot meet high-precision baseline estimation,a dual cycle smooth parameter adaptive selection baseline correction(DC-arPLS)algorithm is proposed.The root mean square error of DC-arPLS algorithm for simulating signal baseline fitting is 3.44×10-8,which is better than arPLS's algorithm 4.86×10-8.The application results of actual signal baseline correction show that DC-arPLS algorithm for baseline correction of real optical/electrical signals can meet the requirements of high-precision baseline correction and provide certain technical support for the protection of water environmental.
sensing signalheavy metalin situ detectionbaseline correction,penalized least squares algorithm
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