气相监测信号的处理方法研究

ABSTRACTResearch on Processing Method of Gas Phase Monitoring SignalABSTRACTGas phase monitoring has many advantages,such as high speed of data analysis,distinct separation efficiency and strong selectivity.It has important significance toimprove the efficiency of operation.Because of its advantages,it has been widely usedin many fields,such as petrochemical industry,medical treatment,environmentalprotection,food and so on.In field operation,influenced by various externalenvironments,such as design principles,detection conditions and other factors,theeffectiveness of gas chromatography signals will be affected.In addition to usefulsignals,there are noise interference signals in the signals,which will interfere with theaccuracy of the research results.In order to improve the accuracy and effectiveness ofthe research results,it is necessary to strengthen the filtering of noise in gas phasedetection signals.However,gas phase monitoring is a non-linear dynamic system withcertain complexity.Its aim is to compare and analyze the time-frequency characteristicsof gas-containing and non-gas-containing signals in the environment.Under the currentbackground,it is worth studying and exploring to adopt modern operation methods toobtain effective information.After years of analysis and research,Norden E.Huang put forward a landmarkviewpoint in the field of signal processing in 1998.He proposed a new signalprocessing method,Empirical Mode Decomposition (EMD).This signal processingmethod has a greater advantage than before.It has a strong effectiveness in processingsignals in both non-linear and non-stationary environments.The principle of empiricalmode decomposition is to simplify complex signals,decompose a series of intrinsicmode functions including the local characteristics of the original signals,and thentransform them to a certain extent to get the frequencies with physical significance.Because of its high stability and effectiveness in signal processing,it is often used inmany fields.In this paper,empirical mode decomposition (EMD)method is deeply-II-