A method of measuring a fiber optic spectrometer

Abstract

This invention provides a fiber optic spectrometer measurement method, comprising: acquiring a light to be measured; substituting the pixel number of the light to be measured into a calibrated wavelength variation curve polynomial to obtain the wavelength corresponding to the pixel number; plotting the spectral curve of the light to be measured based on the correspondence between the wavelength and the pixel number; calculating and analyzing the parameter characteristics of the light to be measured based on the spectral curve, wherein the parameter characteristics include at least one or more of reflectivity, transmittance, absorbance, and chromaticity coordinates. This invention uses standard light source spectral calibration to obtain the wavelength variation curve polynomial of the standard light source spectrum. The measured spectral curve is fitted using this wavelength variation curve polynomial, correcting the testing deviation between spectrometers of different specifications and improving testing accuracy; it also enables multiple testing functions and is highly practical.

Description

Technical Field

[0001] This invention relates to the field of optical communication equipment, and more specifically, to a method for measuring optical fiber spectrometers. Background Technology

[0002] In modern engineering applications, spectrometers play an increasingly important role in component detection. Since each substance has its own unique spectrum, spectroscopic analysis instruments can rapidly detect the composition of substances; spectrometers are such instruments. A spectrometer consists of both hardware and software. After the hardware is designed and manufactured, the software acquires and analyzes the data to provide accurate spectral data. Therefore, the software design of a spectrometer is a crucial aspect. Generally, spectrometers are calibrated before leaving the factory to determine the correspondence between characteristic wavelengths and pixels on the CCD. These calibration parameters are not disclosed to the user; therefore, spectrometers from a specific manufacturer can only use the software from that specific manufacturer. If users need to verify certain calibration methods or need to use spectrometers from different manufacturers, they need to install multiple software programs, which is inconvenient.

[0003] Traditional general-purpose spectrometers lack measurements of color temperature, chromaticity, and radioactivity; most only perform spectral wavelength detection, have limited functionality, and generally have low measurement accuracy. Summary of the Invention

[0004] This invention addresses the technical problems existing in the prior art by providing a measurement method for fiber optic spectrometers, which solves the test deviation between fiber optic spectrometers of different specifications and achieves high measurement accuracy.

[0005] According to a first aspect of the present invention, a fiber optic spectrometer measurement method is provided, comprising:

[0006] Collect the light to be measured, substitute the pixel number of the light to be measured into the calibrated wavelength change curve polynomial to obtain the wavelength corresponding to the pixel number, and plot the spectral curve of the light to be measured based on the correspondence between the wavelength and the pixel number.

[0007] The parameter characteristics of the light to be measured are calculated and analyzed based on the spectral curve of the light to be measured. The parameter characteristics include at least one or more of the following: reflectance, transmittance, absorbance, and chromaticity coordinates.

[0008] Based on the above technical solution, the present invention can also be improved as follows.

[0009] Optionally, the steps to obtain the calibrated wavelength variation curve polynomial include:

[0010] Collect the spectral curve of a standard light source and smooth the spectral curve of the standard light source;

[0011] The extreme points are found by smoothing the spectral curve, and a spectral interval of a preset range is intercepted with the extreme points as the center. The peak points of the intercepted spectral interval are obtained by the centroid algorithm.

[0012] Based on the wavelength variation pattern corresponding to each peak point, a piecewise fitting is performed to obtain the wavelength variation curve polynomial.

[0013] Optionally, the spectral curve may be smoothed, including:

[0014] The smoothness s corresponding to the spectral curve is selected using formula (1):

[0015] A n =(a n-s +a n-s+1 +……+a n +a n+1 +……+a n+s ) / (2*s+1) (1),

[0016] Where n is the pixel number on the spectral curve; s is the algebraic sum of s+1 points taken to the left and right of point n, and the average of these s+1 points is used to obtain A. n ;where a n A is the pixel value corresponding to the nth pixel on the spectral curve to be processed. n It is the pixel value corresponding to the nth pixel on the processed spectral curve;

[0017] The average k-th order spectral curve A is calculated using formula (2). n k :

[0018] A n k =(A n1 +A n2 +……A nk ) / k (2),

[0019] Where k is the average frequency, k = 1, 2, 3, ...; A nk The spectrum curve obtained by smoothing the k-th acquisition under the same conditions using formula (1) is shown.

[0020] Optionally, the step of finding the extreme point through the smoothed spectral curve, extracting a preset range of spectral intervals centered on the extreme point, and obtaining the peak point of the extracted spectral interval using a centroid algorithm includes:

[0021] Assuming the spectral curve is represented by the function f(x), let f'(x) = 0 to find all the extreme points in the spectral curve;

[0022] Taking a single extreme point x as the center, a spectral interval of range i is intercepted on both sides of the extreme point, and the mass m of the spectral interval is obtained by formula (3):

[0023]

[0024] Where L is the coordinate of a single extreme point, and i is the range of values ​​to the left and right of the single extreme point;

[0025] The centroid X of the spectral range is calculated using formula (4):

[0026] X=m / (2*i+1) (4),

[0027] The mass centroid X is the peak value to be obtained.

[0028] Optionally, the step of performing piecewise fitting based on the wavelength variation pattern corresponding to each peak point to obtain a wavelength variation curve polynomial includes:

[0029] Substituting the x-axis coordinates of the multiple peak points and the known spectral wavelength y corresponding to the standard light source at that point into formula (5), the parameter values ​​a1, a2, a3, and a4 are obtained to get the polynomial of the wavelength variation curve:

[0030] y = a1*x 3 +a2*x 2 +a3*x+a4 (5),

[0031] Where x is the pixel number and y is the wavelength.

[0032] Optionally, before calculating and analyzing the parametric characteristics of the light under test based on its spectral curve, the method further includes preprocessing the spectral curve of the light under test. The preprocessing steps include:

[0033] The current light intensity E to be measured is obtained. t With background light intensity E g Calculate the light intensity E to be measured t Subtract background light intensity E g The difference is compared with a preset threshold. When the difference is determined to be lower than the threshold, the light to be tested is denoised and frequency selected.

[0034] Optionally, the noise reduction frequency selection step includes:

[0035] The background spectrum was collected multiple times, and the intensity values ​​of the background spectrum were summed for each time to obtain the variation law of the background spectrum intensity value. Based on the variation law of the background spectrum intensity value, a weighted average was performed on each point of the background spectrum, and the background light intensity variation curve formula was fitted based on the light intensity value of each point after weighted average.

[0036] Substitute each point of the spectrum to be measured into the formula for the background light intensity variation curve to determine whether each point of the spectrum exceeds the range of background light intensity variation:

[0037] Points on the spectrum to be measured that exceed the range of background light intensity variation are identified as useful signals. All points corresponding to the useful signals are amplified by a factor and then connected sequentially to obtain the useful signal waveform.

[0038] Optionally, the reflectance of the light to be measured can be calculated and analyzed based on the spectral curve of the light to be measured, including:

[0039] Calculate the reflectance R(λ)% for any wavelength value on the spectral curve of the light to be measured according to formula (6), and calculate the transmittance T(λ)% for any wavelength value on the spectral curve of the light to be measured according to formula (7).

[0040]

[0041]

[0042] Among them, R λ S represents the reference spectrum at wavelength λ. λ D represents the sample spectrum at wavelength λ; λ This represents the dark background spectrum at wavelength λ.

[0043] Optionally, the absorbance of the light to be measured can be calculated and analyzed based on the spectral curve of the light to be measured, including:

[0044] Calculate the absorbance A(λ) corresponding to any wavelength value on the spectral curve of the light to be measured according to formula (8):

[0045]

[0046] Among them, R λ S represents the reference spectrum at wavelength λ. λ D represents the sample spectrum at wavelength λ; λ This represents the dark background spectrum at wavelength λ.

[0047] Optionally, the chromaticity coordinates of the light to be measured are calculated and analyzed based on the spectral curve of the light to be measured, including:

[0048] Calculate the chromaticity coordinate X corresponding to any wavelength value on the spectral curve of the light to be measured using formula (9). i :

[0049] X i =k*∑ψ(λ)*x i (λ)*Δλ (9),

[0050] Among them, X i =X, Y, or Z; xi (λ) represents the standard colorimetric observer color matching function, obtained through a lookup table. When calculating X, Y, or Z, x... i (λ) corresponds to x(λ), y(λ), and z(λ), respectively; k represents the normalization coefficient; Δλ represents the wavelength interval for calculation; and ψ(λ) is the color stimulus function.

[0051] According to a second aspect of the present invention, a fiber optic spectrometer measurement system is provided, comprising:

[0052] The wavelength calibration module is used to perform piecewise fitting of the wavelength variation law corresponding to the spectral curve of the standard light source to obtain the polynomial of the wavelength variation curve.

[0053] The wavelength measurement module is used to collect the light to be measured, substitute the pixel number of the light to be measured into the calibrated wavelength change curve polynomial to obtain the wavelength corresponding to the pixel number, and plot the spectral curve of the light to be measured based on the correspondence between the wavelength and the pixel number.

[0054] The parameter analysis module is used to calculate and analyze the parameter characteristics of the light under test based on the spectral curve of the light under test. The parameter characteristics include at least one or more of reflectance, transmittance, absorbance and chromaticity coordinates.

[0055] According to a third aspect of the present invention, an electronic device is provided, including a memory and a processor, wherein the processor is configured to execute a computer management program stored in the memory to implement the steps of the above-described fiber optic spectrometer measurement method.

[0056] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which a computer management program is stored, which, when executed by a processor, implements the steps of the above-described fiber optic spectrometer measurement method.

[0057] This invention provides a fiber optic spectrometer measurement method, system, electronic device, and storage medium. It employs standard light source spectral calibration to obtain a polynomial of the wavelength variation curve of the standard light source spectrum. This calibrated polynomial is stored. Later, when using the spectrometer for testing, the pixel values ​​of each point of the light under test collected by the spectrometer can be substituted into the aforementioned wavelength variation curve polynomial to retrieve the corresponding wavelength value. Based on the correspondence between each pixel point and wavelength, the spectral curve of the light under test is plotted, improving the accuracy of the spectral curve plotting, correcting test deviations between different spectrometer specifications, and enhancing the measurement accuracy of the fiber optic spectrometer. Based on the plotted spectral curve of the light under test, the parameter characteristics of the light under test, such as reflectance, transmittance, absorbance, and chromaticity coordinates, can be calculated and analyzed. This method unifies the testing standards for spectrometers of different specifications, reduces test deviations between different spectrometer specifications, and improves measurement accuracy. It also allows for the analysis of parameters such as reflectance, transmittance, absorbance, and chromaticity coordinates of the measured spectrum. With comprehensive measurement functions and multi-functionality, it reduces the space occupied by multiple testing instruments used in traditional testing methods, making it highly practical. Attached Figure Description

[0058] Figure 1 A flowchart of a fiber optic spectrometer measurement method provided by the present invention;

[0059] Figure 2 A flowchart for wavelength calibration provided by this invention;

[0060] Figure 3 This is a schematic diagram of a test operation page in a specific embodiment of the present invention;

[0061] Figure 4 A block diagram of a fiber optic spectrometer measurement system provided by the present invention;

[0062] Figure 5 A schematic diagram of the hardware structure of a possible electronic device provided by the present invention;

[0063] Figure 6 This is a schematic diagram of the hardware structure of a possible computer-readable storage medium provided by the present invention. Detailed Implementation

[0064] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0065] Figure 1 A flowchart of a fiber optic spectrometer measurement method provided by the present invention is shown below. Figure 1 As shown, the method includes:

[0066] The light to be measured is collected, and the pixel value of the light to be measured is substituted into the calibrated wavelength change curve polynomial to obtain the wavelength corresponding to the pixel value. The spectral curve of the light to be measured is plotted according to the correspondence between the wavelength and the pixel value.

[0067] The parameter characteristics of the light to be measured are calculated and analyzed based on the spectral curve of the light to be measured. The parameter characteristics include at least one or more of the following: reflectance, transmittance, absorbance, and chromaticity coordinates.

[0068] It is understandable that, based on the deficiencies in the background technology, this embodiment of the invention proposes a fiber optic spectrometer measurement method.

[0069] The method of this invention uses standard light source spectral calibration to obtain a wavelength variation curve polynomial of the standard light source spectrum. This calibrated wavelength variation curve polynomial is stored. Later, when using a spectrometer for testing, the pixel values ​​of each point of the light under test collected by the spectrometer can be substituted into the aforementioned wavelength variation curve polynomial to retrieve the wavelength value corresponding to that pixel value. Based on the correspondence between each pixel point and wavelength, the spectral curve of the light under test is plotted, improving the accuracy of the spectral curve plotting and thus enhancing the measurement accuracy of the fiber optic spectrometer. Based on the plotted spectral curve of the light under test, the parameter characteristics of the light under test, such as reflectance, transmittance, absorbance, and chromaticity coordinates, can be calculated and analyzed. This method of the present invention can unify the testing standards of spectrometers of different specifications, reduce testing deviations between spectrometers of different specifications, and improve measurement accuracy. It can also analyze parameters such as reflectance, transmittance, absorbance, and chromaticity coordinates of the spectrum under test, providing comprehensive measurement functions and multi-purpose functionality, reducing the space occupied by multiple testing instruments required by traditional testing methods.

[0070] Based on the above technical solution, the following improvements can be made to this embodiment.

[0071] In one possible embodiment, such as Figure 2 As shown in the flowchart, the steps to obtain the calibrated wavelength variation curve polynomial include:

[0072] Collect the spectral curve of a standard light source and smooth the spectral curve of the standard light source;

[0073] The extreme points are found by smoothing the spectral curve, and a spectral interval of a preset range is intercepted with the extreme points as the center. The peak points of the intercepted spectral interval are obtained by the centroid algorithm.

[0074] Based on the wavelength variation pattern corresponding to each peak point, a piecewise fitting is performed to obtain the wavelength variation curve polynomial.

[0075] Understandably, smoothing the acquired spectral curves can remove noise signals and reduce errors. Finding extreme points reveals the approximate variation of the spectral curve. Since the peaks of the spectral curve are not symmetrical within a narrow range due to various interferences, finding extreme points in such waveforms often results in inaccuracies. Therefore, the centroid algorithm is used to obtain accurate peak points. The centroid algorithm finds the centroid by integrating the area of ​​the region enclosed by the spectral curve and the coordinate axes. The coordinates corresponding to the centroid are then used to determine the peak point of a certain segment of the curve. This method is relatively stable. Finally, the obtained peak variation pattern is piecewise fitted to obtain the calibrated wavelength variation curve polynomial. The calibration method in this embodiment combines the advantages of various algorithms, improving measurement accuracy.

[0076] In one possible embodiment, during calibration, the spectral curve is smoothed, including:

[0077] The smoothness s corresponding to the spectral curve is selected using formula (1):

[0078] A n =(a n-s +a n-s+1 +……+a n +a n+1 +……+a n+s ) / (2*s+1) (1),

[0079] In formula (1), n ​​is the pixel number on the spectral curve; s is the algebraic sum of s+1 points taken to the left and right of point n, and the average of the sums is used to obtain A. n ;where a n A is the pixel value corresponding to the nth pixel on the spectral curve to be processed. n It is the pixel value corresponding to the nth pixel on the processed spectral curve;

[0080] The average k-th order spectral curve A is calculated using formula (2). n k :

[0081] A n k =(A n1 +A n2 +……A nk ) / k (2),

[0082] In formula (2), k is the average frequency, k = 1, 2, 3, ...; A nk The spectrum curve obtained by smoothing the k-th acquisition under the same conditions using formula (1) is shown.

[0083] It is understood that by smoothing the spectral curve using the algorithm in this embodiment, a good denoising effect can be achieved, thus improving the accuracy of the spectral curve.

[0084] In one possible embodiment, during the calibration process, the step of finding extreme points using the smoothed spectral curve, intercepting a preset range of spectral intervals centered on these extreme points, and then using a centroid algorithm to determine the peak points of the intercepted spectral intervals includes:

[0085] Assuming the spectral curve is represented by the function f(x), let f'(x) = 0 to find all the extreme points in the spectral curve;

[0086] Taking a single extreme point x as the center, a spectral interval of range i is intercepted on both sides of the extreme point, and the mass m of the spectral interval is obtained by formula (3):

[0087]

[0088] In formula (3), L is the coordinate of a single extreme point, and i is the range of values ​​to the left and right of the single extreme point;

[0089] The centroid X of the spectral range is calculated using formula (4):

[0090] X=m / (2*i+1) (4),

[0091] The mass centroid X is the peak value to be obtained.

[0092] It is understandable that in this embodiment, the extreme points are obtained by differentiating the function of the spectral curve. Since the peak of the spectral waveform is not a symmetrical figure due to various interferences within a relatively narrow range, there is often a deviation in finding the extreme points in such a waveform. Therefore, the extreme points obtained by differentiating the spectral curve are not accurate peak points. The centroid method finds the centroid by integrating the area of ​​the region enclosed by the spectral curve and the X-axis. The abscissa (X-axis) of the centroid is used to determine the peak point of a certain segment of the curve. Therefore, the peak points obtained by further calculation using formulas (3) to (4) are more accurate.

[0093] After obtaining each peak point, piecewise curve fitting can be performed based on the peak variation pattern. In one possible embodiment, the piecewise fitting based on the wavelength variation pattern corresponding to each peak point to obtain a wavelength variation curve polynomial includes:

[0094] Substituting the x-axis coordinates of the multiple peak points and the known spectral wavelength y corresponding to the standard light source at that point into formula (5), the parameter values ​​a1, a2, a3, and a4 are obtained to get the polynomial of the wavelength variation curve:

[0095] y = a1*x 3+a2*x 2 +a3*x+a4 (5),

[0096] Where x is the pixel number and y is the wavelength. By solving formula (5), the light to be tested collected by the fiber optic spectrometer can be tested using formula (5). By solving formula (5), the correspondence between the wavelength and pixel value of each pixel can be found.

[0097] In one possible embodiment, before calculating and analyzing the parametric characteristics of the light under test based on its spectral curve, the method further includes preprocessing the spectral curve of the light under test. The preprocessing steps include:

[0098] The current light intensity E to be measured is obtained. t With background light intensity E g Calculate the light intensity E to be measured t Subtract background light intensity E g The difference is compared with a preset threshold. When the difference is determined to be lower than the threshold, the light to be tested is denoised and frequency selected.

[0099] Understandably, in spectral measurements, the first step is to determine whether the acquired spectral features are significant using a threshold method. If the spectral features are significant, meaning the useful signal in the spectral curve is obvious, then the next step of calculation continues; if they are not significant, then the acquired spectrum needs to be denoised and frequency-selected to extract its useful signal. Specifically, a threshold is set, such as a percentage value, if the light intensity E to be measured... t Subtract background light intensity E g If the difference fluctuation exceeds the set percentage, then noise reduction frequency selection is not required; if the calculated difference is lower than the set percentage, then noise reduction frequency selection is required.

[0100] In one possible embodiment, the noise reduction and frequency selection step includes:

[0101] Background spectra were collected multiple times, and the intensity values ​​of each background spectrum were summed to determine the variation pattern of the background spectral intensity values. For example, the sum of the intensity values ​​of each collected background spectrum can be calculated using the following summation formula:

[0102] In this formula, E b It is the sum of the background spectral intensity values ​​collected in the b-th acquisition, u is the number of pixel units collected in each acquisition, and f(u) is the light intensity value of the u-th pixel;

[0103] Based on the variation law of background spectral intensity value, a weighted average is calculated for each point of the background spectrum, and the background light intensity variation curve formula is fitted based on the light intensity value of each point after weighted average.

[0104] Substitute each point of the spectrum to be measured into the formula for the background light intensity variation curve to determine whether each point of the spectrum exceeds the range of background light intensity variation:

[0105] Points on the spectrum to be measured that exceed the range of background light intensity variation are identified as useful signals. All points corresponding to the useful signals are amplified by a factor and then connected sequentially to obtain the useful signal waveform.

[0106] Understandably, in order to effectively remove background noise and improve the strength of useful signals, this embodiment employs a noise reduction and frequency selection method, which can effectively improve the strength of useful signals and find and display the useful signal waveform completely, thereby achieving the purpose of identifying weak signals.

[0107] Once the spectral curve of the light to be measured is obtained, parameter analysis can be performed on the spectral curve of the light to be measured.

[0108] In one possible embodiment, calculating and analyzing the reflectance and transmittance of the light to be measured based on its spectral curve includes:

[0109] Calculate the reflectance R(λ)% for any wavelength value on the spectral curve of the light to be measured according to formula (6), and calculate the transmittance T(λ)% for any wavelength value on the spectral curve of the light to be measured according to formula (7).

[0110]

[0111]

[0112] In formula (7), R λ S represents the reference spectrum at wavelength λ, measured under normal conditions with the light source on and no sample placed on it; λ This represents the sample spectrum at wavelength λ, i.e., the spectrum measured with the light source normally turned on and the sample in its correct position; D λ This represents the dark background spectrum at wavelength λ, i.e., the spectrum measured when the light source is off.

[0113] It is worth noting that the optical paths used for measuring reflectance and transmittance differ when measuring the sample spectrum. When measuring reflectance, the light source and the CCD used to collect the light signal are on the same side of the sample; when measuring transmittance, the sample is positioned between the light source and the CCD. Therefore, even with the same S... λ Different measurement results will yield different values.

[0114] In one possible embodiment, calculating and analyzing the absorbance of the light to be measured based on its spectral curve includes:

[0115] Calculate the absorbance A(λ) corresponding to any wavelength value on the spectral curve of the light to be measured according to formula (8):

[0116]

[0117] In formula (8), similar to the previous embodiment, R λ S represents the reference spectrum at wavelength λ, measured under normal conditions with the light source on and no sample placed on it; λ This represents the sample spectrum at wavelength λ, i.e., the spectrum measured with the light source normally turned on and the sample in its correct position; D λ This represents the dark background spectrum at wavelength λ, i.e., the spectrum measured when the light source is off.

[0118] In one possible embodiment, calculating and analyzing the chromaticity coordinates of the light to be measured based on its spectral curve includes:

[0119] Calculate the chromaticity coordinate X corresponding to any wavelength value on the spectral curve of the light to be measured using formula (9). i :

[0120] X i =k*∑ψ(λ)*x i (λ)*Δλ (9),

[0121] In formula (9), X i =X, Y, or Z, i.e., chromaticity coordinates X i For XYZ coordinates; x i (λ) represents the standard colorimetric observer color matching function, obtained through a lookup table, which is stored in a fixed location in the software using a data structure; when calculating the coordinate values ​​of the X, Y, or Z axes, x i (λ) corresponds to x(λ), y(λ), and z(λ) respectively; k in formula (9) represents the normalization coefficient, which is obtained according to the nationally prescribed calculation method based on different spectral properties (illuminant or light source, reflective object, and transmissive object); Δλ represents the calculation wavelength interval, which is usually taken as 5nm; ψ(λ) is the color stimulus function.

[0122] Furthermore, the methods for calculating the color stimulus function ψ(λ) for the light source or illuminator, reflector, and transmissor are as follows:

[0123] The color stimulus function of the light source or illuminator is ψ(λ) = S(λ), where S(λ) is the relative spectral power distribution of the light source or illuminator;

[0124] The color stimulus function of the reflector is ψ(λ)=R(λ)S(λ), where R(λ) is the spectral reflectance, spectral reflectance factor or spectral radiance factor of the object, and S(λ) is the relative spectral power distribution of the illuminator.

[0125] The color stimulus function of the illuminator is ψ(λ) = τ(λ)S(λ), where τ(λ) is the spectral transmittance or spectral transmittance factor of the object, and S(λ) is the relative spectral power distribution of the illuminator.

[0126] like Figure 3 The image shows an operation page for testing using the method provided by this invention in a specific embodiment. The method provided by this invention can perform tests for various functions, such as calibrating the spectrometer, plotting the spectral curve of the light to be tested in real time, and performing various parameter analyses on the measured spectral curve, such as reflectance analysis, transmittance analysis, absorbance analysis, and chromaticity coordinate analysis.

[0127] Figure 4 A structural diagram of a fiber optic spectrometer measurement system provided in an embodiment of the present invention is shown below. Figure 4 As shown, a fiber optic spectrometer measurement system includes a wavelength calibration module, a wavelength measurement module, and a parameter analysis module, wherein:

[0128] The wavelength calibration module is used to perform piecewise fitting of the wavelength variation law corresponding to the spectral curve of the standard light source to obtain the polynomial of the wavelength variation curve.

[0129] The wavelength measurement module is used to collect the light to be measured, substitute the pixel number of the light to be measured into the calibrated wavelength change curve polynomial to obtain the wavelength corresponding to the pixel number, and plot the spectral curve of the light to be measured based on the correspondence between the wavelength and the pixel number.

[0130] The parameter analysis module is used to calculate and analyze the parameter characteristics of the light under test based on the spectral curve of the light under test. The parameter characteristics include at least one or more of reflectance, transmittance, absorbance and chromaticity coordinates.

[0131] It is understood that the fiber optic spectrometer measurement system provided by the present invention corresponds to the fiber optic spectrometer measurement methods provided in the foregoing embodiments. The relevant technical features of the fiber optic spectrometer measurement system can be referred to the relevant technical features of the fiber optic spectrometer measurement methods, and will not be repeated here.

[0132] Please see Figure 5 , Figure 5 A schematic diagram illustrating an embodiment of the electronic device provided in this invention. For example... Figure 5 As shown, this embodiment of the invention provides an electronic device 500, including a memory 1310, a processor 520, and a computer program 511 stored in the memory 510 and executable on the processor 520. When the processor 520 executes the computer program 511, it performs the following steps:

[0133] Collect the light to be measured, substitute the pixel number of the light to be measured into the calibrated wavelength change curve polynomial to obtain the wavelength corresponding to the pixel number, and plot the spectral curve of the light to be measured based on the correspondence between the wavelength and the pixel number.

[0134] The parameter characteristics of the light to be measured are calculated and analyzed based on the spectral curve of the light to be measured. The parameter characteristics include at least one or more of the following: reflectance, transmittance, absorbance, and chromaticity coordinates.

[0135] Please see Figure 6 , Figure 6 This is a schematic diagram illustrating an embodiment of a computer-readable storage medium provided by the present invention. (See diagram below.) Figure 6 As shown, this embodiment provides a computer-readable storage medium 600, on which a computer program 611 is stored. When the computer program 611 is executed by a processor, it performs the following steps:

[0136] Collect the light to be measured, substitute the pixel number of the light to be measured into the calibrated wavelength change curve polynomial to obtain the wavelength corresponding to the pixel number, and plot the spectral curve of the light to be measured based on the correspondence between the wavelength and the pixel number.

[0137] The parameter characteristics of the light to be measured are calculated and analyzed based on the spectral curve of the light to be measured. The parameter characteristics include at least one or more of the following: reflectance, transmittance, absorbance, and chromaticity coordinates.

[0138] This invention provides a fiber optic spectrometer measurement method, system, and storage medium. It employs standard light source spectral calibration to obtain a wavelength variation curve polynomial for the standard light source spectrum. This calibrated polynomial is stored. Later, when using the spectrometer for testing, the pixel values ​​of each point of the light under test collected by the spectrometer are substituted into the aforementioned wavelength variation curve polynomial to retrieve the corresponding wavelength value. Based on the correspondence between each pixel and wavelength, the spectral curve of the light under test is plotted, improving the accuracy of the spectral curve plotting and thus enhancing the measurement accuracy of the fiber optic spectrometer. Based on the plotted spectral curve of the light under test, the parameter characteristics of the light under test, such as reflectance, transmittance, absorbance, and chromaticity coordinates, can be calculated and analyzed. This method unifies the testing standards for spectrometers of different specifications, reduces testing deviations between different spectrometer specifications, and improves measurement accuracy. It also allows for the analysis of parameters such as reflectance, transmittance, absorbance, and chromaticity coordinates of the measured spectrum. With comprehensive measurement functions and multi-purpose functionality, it reduces the space occupied by multiple testing instruments used in traditional testing methods.

[0139] This invention is applicable to different spectrometer products, employing a unified calibration method to reduce deviations in test data between spectrometers of different specifications. It can calibrate spectrometers that have not undergone wavelength calibration and perform secondary calibration on spectrometers with inaccurate wavelength calibration, ensuring the accuracy of spectral data. It can also be used to verify the advantages and disadvantages of different calibration methods under different usage environments, helping users select a more suitable calibration method. This invention has high value and is worthy of promotion.

[0140] It should be noted that the descriptions of each embodiment in the above embodiments have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0141] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0142] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0143] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0144] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0145] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0146] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An optical fiber spectrometer measurement method, characterized by, The application relates to a method for calculating and analyzing parameter characteristics of a light spectrum, and belongs to the technical field of light spectrum analysis. The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: m= （3）， The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps:

2. The method of claim 1, wherein, The method comprises the following steps: The method comprises the following steps: A n = (a n-s + a n-s+1 + … + a n + a n+1 + … + a n+s ) / (2 * s + 1) (1), Wherein, n is the pixel number on the spectrum curve; s is to take s points on the left and right of the point n as the center, and the average value of the algebraic sum of s+1 points is A n ; wherein a n is the pixel value corresponding to the nth pixel on the spectrum curve to be processed, A n is the pixel value corresponding to the nth pixel point on the spectrum curve after processing; The average kth order spectrum curve A is calculated by formula (2) n k : A n k =(A n1 +A n2 +……A nk ) / k(2), wherein k is the average number of times, k = 1, 2, 3, …; A nk is the spectrum curve after smoothing processing by formula (1) for the kth collection under the same environment.

3. The method of claim 1, wherein, The method comprises the following steps: The method comprises the following steps: y = a1 * x 3 + a2 * x 2 + a3 * x + a4 (5), The method comprises the following steps:

4. The method of claim 1, wherein, The method comprises the following steps: measuring a current to-be-measured light intensity E t subtracts the background light intensity E g , calculates a difference value between the to-be-measured light intensity E t and the background light intensity E g , compares the obtained difference value with a preset threshold value, and when determining that the difference value is lower than the threshold value, carries out denoising and frequency selection on the to-be-measured light.

5. The method of claim 4, wherein, The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps:

6. The method of claim 1, wherein, The method comprises the following steps: According to formula (6), the reflectivity corresponding to any wavelength value on the spectral curve of the light to be measured is calculated According to formula (7), the transmittance corresponding to any wavelength value on the spectral curve of the light to be measured is calculated : （6）， （7）， wherein R λ represents a reference spectrum at wavelength λ, S λ represents a sample spectrum at wavelength λ; D λ represents a dark background spectrum at wavelength λ.

7. The method of claim 1, wherein, The method comprises the following steps: According to formula (8), the absorbance corresponding to any wavelength value on the spectral curve of the to-be-tested light is calculated : （8）， wherein R λ represents a reference spectrum at wavelength λ, S λ represents a sample spectrum at wavelength λ; D λ represents a dark background spectrum at wavelength λ.

8. The method of claim 1, wherein, The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the following steps: The method comprises the According to formula (9), the color quality coordinate X corresponding to any wavelength value on the spectral curve of the to-be-tested light is calculated i : X i = k * ∑ψ(λ) * x i (λ) * Δλ (9), wherein X i = X, Y or Z; x i (λ) represents the standard colorimetric observer color matching function, obtained by table lookup, when calculating X, Y or Z, x i (λ) respectively correspond to x(λ), y(λ), z(λ); k represents a normalization coefficient; Δλ represents a calculation wavelength interval; and ψ(λ) is a color stimulus function.

Images