雙脈沖激光誘導(dǎo)擊穿光譜實(shí)驗(yàn)方法及數(shù)據(jù)處理方法研究
發(fā)布時(shí)間:2018-04-30 10:19
本文選題:激光誘導(dǎo)擊穿光譜 + 雙脈沖 ; 參考:《北京理工大學(xué)》2015年碩士論文
【摘要】:激光誘導(dǎo)擊穿光譜(Laser-induced Breakdown Spectroscopy,LIBS)是近幾十年發(fā)展起來的一種基于原子發(fā)射光譜的物質(zhì)分析新技術(shù),其基本原理是將激光束利用光學(xué)系統(tǒng)聚焦擊打材料樣品表面,燒蝕樣品產(chǎn)生等離子體,經(jīng)由光譜儀接收,通過軟件實(shí)時(shí)分析光譜中的原子和離子譜線,從而進(jìn)行定性或者定量分析。作為一種快速發(fā)展的光譜檢測(cè)手段,激光誘導(dǎo)擊穿光譜具有分析速度快、破壞性小、能進(jìn)行多種元素實(shí)時(shí)分析等顯著特點(diǎn)。本論文在實(shí)驗(yàn)室環(huán)境下建立了再加熱雙脈沖激光誘導(dǎo)擊穿光譜實(shí)驗(yàn)系統(tǒng),對(duì)比了單脈沖激光誘導(dǎo)擊穿光譜和雙脈沖激光誘導(dǎo)擊穿光譜的信號(hào)強(qiáng)度和穩(wěn)定性,并研究了雙脈沖LIBS系統(tǒng)當(dāng)中激光束之間的夾角對(duì)光譜信號(hào)強(qiáng)度的影響。此外,在LIBS光譜數(shù)據(jù)處理方面,進(jìn)行了樣品分類模型適應(yīng)性的研究。分別比較了利用偏最小二乘法和人工神經(jīng)網(wǎng)絡(luò)建立的分類模型在不同激發(fā)條件下的適應(yīng)性。
[Abstract]:Laser-induced Breakdown spectroscopy (LIBS) is a new technique for material analysis based on atomic emission spectroscopy developed in recent decades. Its basic principle is to focus the laser beam on the surface of material by optical system. Plasma is generated from the ablated sample and received by spectrometer. The atomic and ionic lines in the spectrum are analyzed in real time by software and then the qualitative or quantitative analysis is carried out. As a rapidly developing method of spectrum detection, laser induced breakdown spectroscopy has the advantages of fast analysis speed, low destructive, and can be used for real-time analysis of various elements. In this paper, the experimental system of reheating double-pulse laser induced breakdown spectrum is established in laboratory environment, and the signal intensity and stability of single-pulse laser induced breakdown spectrum and double-pulse laser induced breakdown spectrum are compared. The influence of the angle between the laser beams on the intensity of the spectral signal in the dual pulse LIBS system is studied. In addition, in the aspect of LIBS spectral data processing, the adaptability of sample classification model was studied. The adaptability of classification models based on partial least square method and artificial neural network under different excitation conditions was compared.
【學(xué)位授予單位】:北京理工大學(xué)
【學(xué)位級(jí)別】:碩士
【學(xué)位授予年份】:2015
【分類號(hào)】:TN249;TP274.2
【參考文獻(xiàn)】
相關(guān)期刊論文 前2條
1 劉凱;王茜劏;趙華;肖銀龍;;激光誘導(dǎo)擊穿光譜在塑料分類中的應(yīng)用[J];光譜學(xué)與光譜分析;2011年05期
2 伏再喜;張先q,
本文編號(hào):1824169
本文鏈接:http://sikaile.net/kejilunwen/dianzigongchenglunwen/1824169.html
最近更新
教材專著