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  本文關鍵詞：基于二維重組和動態(tài)窗格的水質(zhì)檢測紫外-可見光譜去噪算法　出處：《光譜學與光譜分析》2016年04期 　論文類型：期刊論文

  更多相關文章： 水質(zhì)檢測 光譜去噪 二維重組 動態(tài)窗格

【摘要】：立足于成功研制的紫外-可見光譜水質(zhì)檢測多參數(shù)測量系統(tǒng),針對紫外-可見光譜水質(zhì)多參數(shù)原位實時檢測在精度、靈敏度、穩(wěn)定性等方面的實際需要,開展了基于二維重組和動態(tài)窗格的水質(zhì)檢測紫外-可見光譜去噪算法的研究,以此提高紫外-可見光譜水質(zhì)檢測的測量精度。光譜法水質(zhì)檢測系統(tǒng)通常使用工業(yè)級低成本光譜儀,其輸出光譜包含明顯的非平穩(wěn)噪聲。傳統(tǒng)去噪法難以在濾除噪聲的同時保留譜線細節(jié)。而且,原位實時水質(zhì)檢測條件下,被測水樣可能快速變化,傳統(tǒng)去噪法中常用的多次采樣求均值法將產(chǎn)生額外的測量誤差。引入的去噪算法通過對水樣光譜進行等間隙連續(xù)采樣,將光譜數(shù)據(jù)張成由光譜軸和時間軸構成的二維矩陣,經(jīng)過二維小波變換后,設置一個可變寬度的窗格在系數(shù)矩陣中水平滑動,使用窗格內(nèi)的小波系數(shù)計算得到動態(tài)去噪閾值,并隨窗格滑動構建去噪閾值向量,由此進行光譜去噪。其中,窗格寬度由相鄰區(qū)域的噪聲方差變化率決定,變化率較高的區(qū)域縮小窗格寬度,反之則擴大寬度。實驗結果表明,這種去噪算法不僅能有效去除光譜中的非平穩(wěn)噪聲,而且能保留光譜的細節(jié)信息,有助于提高儀器的測量精度。與此同時,由于該算法并未使用時域平均,樣本的快速變化對去噪性能的影響較小,適合在線或原位水質(zhì)檢測的水樣本環(huán)境。
[Abstract]:Based on the successfully developed UV-Vis spectrum water quality detection multi-parameter measurement system, aiming at the actual needs of UV-Vis spectrum water quality multi-parameter real-time detection in precision, sensitivity, stability and so on. The research of UV-Vis spectral denoising algorithm for water quality detection based on two-dimensional recombination and dynamic pane is carried out. In order to improve the measurement accuracy of UV-Vis spectral water quality detection, the industrial low cost spectrometer is usually used in the spectral water quality detection system. The output spectrum contains obvious non-stationary noise. The traditional denoising method is difficult to preserve the spectral details while filtering noise. Moreover, under the condition of in-situ real-time water quality detection, the measured water sample may change rapidly. In the traditional de-noising method, the method of calculating the mean value of multi-sampling will produce additional measurement error. The proposed de-noising algorithm carries on the equal-gap continuous sampling to the water sample spectrum. The two-dimensional matrix composed of spectral axis and time axis of Zhang Cheng spectral data is set and a variable width pane is set to slide horizontally in the coefficient matrix after 2-D wavelet transform. The dynamic denoising threshold is calculated by using wavelet coefficients in the pane, and the threshold vector is constructed by sliding with the pane, and the spectral denoising is carried out. Where, the width of the pane is determined by the variation rate of the noise variance in the adjacent region. The experimental results show that the proposed denoising algorithm can not only effectively remove the non-stationary noise in the spectrum, but also retain the detailed information of the spectrum. At the same time, because the algorithm does not use the time-domain average, the fast change of the sample has little effect on the denoising performance, so it is suitable for the water sample environment of on-line or in-situ water quality detection.
【作者單位】： 重慶大學光電技術及系統(tǒng)教育部重點實驗室;重慶工業(yè)職業(yè)技術學院;
【基金】：國家自然科學基金項目(61401049) 四川省科技支撐計劃項目(2012SZ0111) 重慶市研究生科研創(chuàng)新項目(CYS14039) 中國博士后科學基金面上項目(2014M560703) 重慶市博士后科研人員項目特別資助項目(Xm2014105)資助
【分類號】：X832;O657.3
【正文快照】： 引言水環(huán)境檢(監(jiān))測可對水的質(zhì)和量以及水體中影響生態(tài)與環(huán)境質(zhì)量的各種人為和天然因素進行統(tǒng)一的定時或隨時檢測,它是環(huán)境保護的重要組成部分,關乎國家的可持續(xù)發(fā)展和人類生存環(huán)境的維護[1]。在線(on-line)或原位(in-situ)水質(zhì)檢測系統(tǒng)[2]可對污染源進行實時監(jiān)控,及時準確的

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