基于分段三次曲线和数据更新的色谱信号基线校正OA北大核心CSTPCD

In the process of using polynomial curves to piecewise fitting the baseline of measurement signals,there are frequent defects where the piecewise points affect the fitting accuracy and operational speed.A new baseline correction algorithm for chromatographic signals based on piecewise cubic curves and data updating was proposedto solve the problems.Firstly,a piecewise cubic function is constructed based on five consecutive points to fit the measured signal.This piecewise cubic function has the advantage of low order smoothness and can effectively overcome the defect of piecewisepoints affecting fitting accuracy.Then,in order to reduce the number of iterations of the baseline correction algorithm and increase computational speed,an improved data updating method is proposed.In each iteration process,the peak values of the original measured signals above the baseline are reversed in a certain proportion to update the baseline,while others remain unchanged.The calculation time ratio of the algorithm before and after improvement is approximately 7:1.Finally,the new algorithm proposed is compared with five existing related algorithms.The experimentalresults show that the baseline correction algorithm based on segmented cubic curves and data updating has high approximation to the baseline and is fast.The new baseline correction algorithm in this paper has been applied in practical applications in liquid chromatography.It proves that this algorithm can effectively remove the baseline from the source chromatographic signals.