Research Of Solution Cathode Glow Discharge Atomic Emission Spectrometry System

In recent years,Solution Cathode Glow Discharge-Atomic Emission Spectrometry has been widely used in water testing industry and academia due to its fast analysis speed,high accuracy and low energy consumption.However,it was concentrated on hardware optimization methods such as equipment optimization and environmental improvement,when the technology was used by researchers.Software optimization methods(pretreatment method)of SCGD-AES detection technology were overlooked.In this thesis,in order to improve the accuracy of the SCGD-AES technology,the atomic emission spectrometry pretreatment method was mainly investigated and combined with a large number of experiments for quantitative analysis.In order to eliminate the influence of baseline drift on SCGD-AES,an automatic background estimation point screening method based on B-spline curve and adaptive iterative weighted penalty least squares method were used for baseline correction and comparison.The experiments proved that the former had a relatively high signal-to-back ratio after baseline correction.After the method was processed,the six metal elements(Zn,Pb,Sr,Na,Li and K)were analyzed by the standard curve method.Experiments had shown that the baseline fit results were good and the detection limits and relative standard deviations were improved to varying degrees.Then,when the collected spectral data was automatically peak-searched,the ant colony algorithm was compared with the traditional quadratic polynomial algorithm.The ant colony algorithm can find all peaks without error,which had obvious advantages for peak searching.The standard addition method was used in the experiments to further reduce the influence of the sample matrix effect in SCGD-AES,but the standard addition method is easily interfered by the background signal,which causing errors in the measurement results.Therefore,the improved wavelet transform method was used to eliminate the background interference of the spectral data before the standard addition method,and the result was compared with the off-peak correction method.It was found that the wavelet transform method combined with the standard addition method was not bound by the background correction occasion.And the improved wavelet transform method was not necessary to select an appropriate background correction point,and the prediction accuracy was higher,which was more obvious than the off-peak correction method.In this thesis,LabVIEW was used to integrate the SCGD-AES spectral analysis system,which made the SCGD-AES technology more convenient.The algorithm was added to the self-developed software,combining the advantages of LabVIEW and MATLAB development platforms to complete the spectral preprocessing work.The data acquisition card was uesd as an intermediary tool by calling the hardware interface,and the voltage was displayed on the computer.The high-voltage power supply was monitored in real time,and the mode of observing the voltage through the voltmeter was inconvenient.The spectrometer was connected to the computer to realize the collection and processing of the spectrometer data,which greatly improved the experimental efficiency.The interface of the system was clear and easy to observe the experimental process which can improve the efficiency of the experimental analysis.In summary,in this SCGD-AES analysis system,the hardware part improved the experimental efficiency,the software part improved the detection accuracy.The combination of software and hardware made the system more portable,which can improve the detection performance,application and development in SCGD-AES.