本文選題：顆粒群光散射 + 氣溶膠�。� 參考：《南京信息工程大學(xué)》2017年碩士論文

【摘要】：氣溶膠質(zhì)量濃度是評價大氣環(huán)境好壞的重要參數(shù)之一,該參數(shù)的實時監(jiān)測已迫在眉睫,而顆粒群光散射法具有快速、高精度、寬的濃度范圍且能夠在線測量的優(yōu)點。本文研究并設(shè)計了一套基于顆粒群光散射法的氣溶膠質(zhì)量濃度測量系統(tǒng)。本文主要工作包括:提出了將經(jīng)過激光束的粒子群等效為一顆凝聚體粒子,建立了采用凝聚體電壓信號幅度分布反演氣溶膠質(zhì)量濃度的分形模型,該模型充分利用了凝聚體粒子的電壓信號幅度及信號數(shù)目信息且考慮了顆粒形貌因素,能夠有效提高反演精度。基于氣溶膠質(zhì)量濃度的分形模型,設(shè)計了用于采集和處理信號的多通道電路。該電路由FPGA控制高速ADC進行信號采集,STM32負(fù)責(zé)相關(guān)數(shù)據(jù)處理和外圍器件的控制。在信號采集電路中,采用了非均勻通道劃分的方式,該方式可以有效提高系統(tǒng)的反演速度。考慮到顆粒群光散射法測量的氣溶膠質(zhì)量濃度范圍較寬,本文提出了分段標(biāo)定法標(biāo)定分形模型中的參數(shù)。實驗結(jié)果表明:對于煙塵樣品,當(dāng)相對濕度在60%以內(nèi),質(zhì)量濃度在0.5～13.0 mg/m3的范圍之間時,分形模型反演的質(zhì)量濃度值與實際測量值吻合較好,兩組實驗的平均相對誤差分別為5.6%和6.0%;而采用電壓積分量反演的質(zhì)量濃度平均相對誤差分別為11.0%和18.5%。該結(jié)果說明采用顆粒凝聚體集合的散射光信號幅度分布反演氣溶膠質(zhì)量濃度更精確。在高濕度情況下,首先利用Mie散射理論,計算了相對濕度對球形粒子散射系數(shù)的影響;然后,利用標(biāo)準(zhǔn)儀器與本文實驗裝置同時對不同相對濕度條件下的顆粒物進行測量,基于PSO算法處理得到了相對濕度與氣溶膠質(zhì)量濃度分形模型中標(biāo)定參數(shù)之間的變化關(guān)系,利用該變化關(guān)系可以對標(biāo)定參數(shù)實時修正,對比實驗結(jié)果表明PSO算法可以提高光散射法反演模型實時測量的精度。本文的研究正好符合國家當(dāng)前對大氣環(huán)境實時監(jiān)測的需求,對治理大氣污染和保護人類健康有著重大意義。
[Abstract]:Aerosol mass concentration is one of the most important parameters to evaluate the atmospheric environment. The real-time monitoring of aerosol concentration is imminent, and the particle group light scattering method has the advantages of fast, high precision, wide concentration range and can be measured online. An aerosol mass concentration measurement system based on particle group light scattering method is studied and designed in this paper. The main work of this paper is as follows: the particle swarm passing through laser beam is equivalent to a condensed particle, and a fractal model for retrieving aerosol mass concentration using the amplitude distribution of condensate voltage signal is established. The model makes full use of the information of voltage signal amplitude and signal number of condenser particles and takes into account the factors of particle morphology so that the inversion accuracy can be improved effectively. Based on the fractal model of aerosol concentration, a multichannel circuit is designed for collecting and processing signals. The circuit is controlled by FPGA and high speed ADC for signal acquisition. STM32 is responsible for data processing and peripheral device control. In the signal acquisition circuit, non-uniform channel division is adopted, which can effectively improve the inversion speed of the system. Considering the wide range of aerosol mass concentration measured by particle group light scattering method, this paper presents the parameters of fractal model calibrated by piecewise calibration method. The experimental results show that when the relative humidity is less than 60% and the mass concentration is in the range of 0.5 ~ 13.0 mg/m3, the inversion mass concentration of the fractal model is in good agreement with the actual measured value. The average relative errors of the two groups of experiments are 5.6% and 6.0%, respectively, while the average relative errors of mass concentration obtained by the voltage integral inversion are 11.0% and 18.5%, respectively. The results show that the aerosol mass concentration inversion is more accurate by using the scattering light signal amplitude distribution of the aggregate of particle condensate. In the case of high humidity, the influence of relative humidity on scattering coefficient of spherical particles is first calculated by using Mie scattering theory, and then the particles under different relative humidity conditions are measured simultaneously by using standard instrument and experimental apparatus in this paper. Based on the PSO algorithm, the relationship between the calibration parameters in the fractal model of relative humidity and aerosol concentration is obtained and the calibration parameters can be corrected in real time. The experimental results show that the PSO algorithm can improve the accuracy of real time measurement of the inversion model by light scattering method. The research in this paper is in line with the national demand for real-time monitoring of atmospheric environment, which is of great significance to the control of air pollution and the protection of human health.
【學(xué)位授予單位】：南京信息工程大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：X513;TN791

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