白光LED燈光通量測量不確定度
發(fā)布時間：2019-02-18 10:33
【摘要】：隨著LED燈的光度測試的測量不確定度在實驗室比對的重要性越來越突出,如何正確地評估不確定度成為一大難題。其中不確定度來源與人們對不確定度知識、測試原理、樣品、設(shè)備和測試方法的理解程度和操作規(guī)范性直接相關(guān),有些潛在的較大的不確定度因素難以發(fā)現(xiàn)；測量模型不完善,非線性模型以及不確定度因素的強相關(guān)加大了不確定度合成的難度；B類不確定度的難度在于確立被測量的誤差分布范圍和概率分布。因此本論文以白光lpf燈為研究對象,從不確定度來源、數(shù)學模型和評估方法三方面探究合理地評估白光LED燈光通量測量不確定度的方法。 首先,通過文獻調(diào)研和測試實踐,盡可能地搜集影響因素。本論文主要考慮了能夠評估的影響光通量測試的18個不確定度來源。結(jié)果發(fā)現(xiàn),主要的不確定度因素只有8個,其他因素的影響是可以忽略的。 其次,建立合理的光通量數(shù)學模型。本論文結(jié)合測試原理,建立的數(shù)學模型只包含了標準燈和LED燈的光譜響應(yīng)。對于未包含在數(shù)學模型中的其它因素,要單獨考慮其影響,最后把所有的不確定度分量合成到一起。結(jié)果發(fā)現(xiàn),此模型把光譜和其它變量分離開來,非常方便不確定度的評估。 然后,在評估過程中,關(guān)于數(shù)學模型中的五個光譜,在每個波長處存在光譜能量誤差和波長誤差以及相鄰波長之間的強相關(guān)性,評估難度極大。本論文通過使用三次樣條插值法獲得整數(shù)波長點的光譜,再分別使用ISO《測量不確定度表示指南》(以下簡稱GUM)和蒙特卡羅法(以下簡稱MCM)來評估光譜能量誤差引入的不確定度分量。同時,LED燈的光譜響應(yīng)要考慮波長誤差的影響。GUM和MCM評估過程復雜,需要使用Matlab編寫所有的計算程序。結(jié)果發(fā)現(xiàn),對于非線性的光通量數(shù)學模型,MCM比GUM的不確定度要小很多,方法更簡單和精確。 對于數(shù)學模型之外的其他因素,仍然使用GUM來評估其不確定度。關(guān)于A類不確定度分量,本論文設(shè)計了一系列獨立重復實驗。關(guān)于B類不確定度分量,通過查閱證書、文獻、借鑒以前的實驗數(shù)據(jù)或者經(jīng)驗,得到誤差分布區(qū)間,并估計其概率分布。 最后,通過制定不確定度預(yù)算表,發(fā)現(xiàn)標準燈的校準光譜、LED燈的響應(yīng)、配光修正系數(shù)、LED燈響應(yīng)的波長誤差、標準燈的環(huán)境溫度和測試電流、光譜儀的非線性度和測量誤差是主要的不確定度來源。其中光譜儀的測量誤差影響最大,其次是LED燈光譜響應(yīng)的波長誤差。在實際測試中,通過合理控制以上因素,最大程度地減小測量不確定度。
[Abstract]:With the increasing importance of the uncertainty in the photometric measurement of LED lamp in laboratory comparison, how to correctly evaluate the uncertainty has become a difficult problem. The source of uncertainty is directly related to people's understanding of uncertainty, test principle, sample, equipment and test method, and some potentially large uncertainty factors are difficult to find. The imperfection of measurement model, the strong correlation of nonlinear model and uncertainty factors increase the difficulty of uncertainty synthesis, and the difficulty of class B uncertainty lies in establishing the range of error distribution and probability distribution. Therefore, this paper takes the white lpf lamp as the research object, and explores the method of reasonably evaluating the uncertainty of the white light lpf light flux measurement from three aspects: the source of uncertainty, the mathematical model and the evaluation method. First of all, through literature research and testing practice, as far as possible to collect the factors. This paper focuses on 18 sources of uncertainty that can be evaluated for the impact of luminous flux testing. The results show that there are only 8 major factors of uncertainty, while the other factors can be neglected. Secondly, a reasonable mathematical model of luminous flux is established. Based on the test principle, the mathematical model only includes the spectral response of standard lamp and LED lamp. For the other factors which are not included in the mathematical model, the influence of the factors should be considered separately, and finally all the uncertainty components should be combined together. It is found that this model separates spectrum from other variables and facilitates the evaluation of uncertainty. Then, in the evaluation process, for the five spectra in the mathematical model, there is a strong correlation between the spectral energy error and wavelength error at each wavelength, as well as the strong correlation between adjacent wavelengths, so it is very difficult to evaluate. In this paper, the spectrum of integer wavelength points is obtained by cubic spline interpolation. Then the uncertainty components introduced by spectral energy error are evaluated by ISO (GUM) and Monte Carlo method (MCM) respectively. At the same time, the spectral response of LED lamp should take into account the influence of wavelength error. The evaluation process of GUM and MCM is complicated, and all calculation programs need to be written with Matlab. The results show that the uncertainty of MCM is much smaller than that of GUM, and the method is simpler and more accurate for the nonlinear luminous flux mathematical model. For factors other than mathematical models, GUM is still used to assess its uncertainty. For class A uncertainty components, a series of independent repeated experiments are designed in this paper. For class B uncertainty components, the error distribution interval is obtained and its probability distribution is estimated by consulting certificate, literature, and previous experimental data or experience. Finally, the calibration spectrum of the standard lamp, the response of the LED lamp, the correction coefficient of the light distribution, the wavelength error of the response of the LED lamp, the ambient temperature of the standard lamp and the test current are found by making the uncertainty budget table. The nonlinearity and measurement error of spectrometer are the main sources of uncertainty. The measurement error of the spectrometer is the most important, followed by the wavelength error of the LED light spectrum response. In the actual test, the uncertainty of measurement is minimized by reasonably controlling the above factors.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM923.07
[Abstract]:With the increasing importance of the uncertainty in the photometric measurement of LED lamp in laboratory comparison, how to correctly evaluate the uncertainty has become a difficult problem. The source of uncertainty is directly related to people's understanding of uncertainty, test principle, sample, equipment and test method, and some potentially large uncertainty factors are difficult to find. The imperfection of measurement model, the strong correlation of nonlinear model and uncertainty factors increase the difficulty of uncertainty synthesis, and the difficulty of class B uncertainty lies in establishing the range of error distribution and probability distribution. Therefore, this paper takes the white lpf lamp as the research object, and explores the method of reasonably evaluating the uncertainty of the white light lpf light flux measurement from three aspects: the source of uncertainty, the mathematical model and the evaluation method. First of all, through literature research and testing practice, as far as possible to collect the factors. This paper focuses on 18 sources of uncertainty that can be evaluated for the impact of luminous flux testing. The results show that there are only 8 major factors of uncertainty, while the other factors can be neglected. Secondly, a reasonable mathematical model of luminous flux is established. Based on the test principle, the mathematical model only includes the spectral response of standard lamp and LED lamp. For the other factors which are not included in the mathematical model, the influence of the factors should be considered separately, and finally all the uncertainty components should be combined together. It is found that this model separates spectrum from other variables and facilitates the evaluation of uncertainty. Then, in the evaluation process, for the five spectra in the mathematical model, there is a strong correlation between the spectral energy error and wavelength error at each wavelength, as well as the strong correlation between adjacent wavelengths, so it is very difficult to evaluate. In this paper, the spectrum of integer wavelength points is obtained by cubic spline interpolation. Then the uncertainty components introduced by spectral energy error are evaluated by ISO (GUM) and Monte Carlo method (MCM) respectively. At the same time, the spectral response of LED lamp should take into account the influence of wavelength error. The evaluation process of GUM and MCM is complicated, and all calculation programs need to be written with Matlab. The results show that the uncertainty of MCM is much smaller than that of GUM, and the method is simpler and more accurate for the nonlinear luminous flux mathematical model. For factors other than mathematical models, GUM is still used to assess its uncertainty. For class A uncertainty components, a series of independent repeated experiments are designed in this paper. For class B uncertainty components, the error distribution interval is obtained and its probability distribution is estimated by consulting certificate, literature, and previous experimental data or experience. Finally, the calibration spectrum of the standard lamp, the response of the LED lamp, the correction coefficient of the light distribution, the wavelength error of the response of the LED lamp, the ambient temperature of the standard lamp and the test current are found by making the uncertainty budget table. The nonlinearity and measurement error of spectrometer are the main sources of uncertainty. The measurement error of the spectrometer is the most important, followed by the wavelength error of the LED light spectrum response. In the actual test, the uncertainty of measurement is minimized by reasonably controlling the above factors.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TM923.07
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