CN118032695B - Nitrogen-sulfur in-situ measurement method and system based on differential ultraviolet spectrum technology - Google Patents
Nitrogen-sulfur in-situ measurement method and system based on differential ultraviolet spectrum technology Download PDFInfo
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- 238000000034 method Methods 0.000 title claims abstract description 67
- 238000012625 in-situ measurement Methods 0.000 title claims abstract description 31
- PFRUBEOIWWEFOL-UHFFFAOYSA-N [N].[S] Chemical compound [N].[S] PFRUBEOIWWEFOL-UHFFFAOYSA-N 0.000 title claims abstract description 26
- 238000002211 ultraviolet spectrum Methods 0.000 title claims abstract description 18
- 238000001228 spectrum Methods 0.000 claims abstract description 101
- 238000010521 absorption reaction Methods 0.000 claims abstract description 40
- 238000012216 screening Methods 0.000 claims abstract description 8
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 claims description 52
- NINIDFKCEFEMDL-UHFFFAOYSA-N Sulfur Chemical compound [S] NINIDFKCEFEMDL-UHFFFAOYSA-N 0.000 claims description 26
- 229910052757 nitrogen Inorganic materials 0.000 claims description 26
- 229910052717 sulfur Inorganic materials 0.000 claims description 26
- 239000011593 sulfur Substances 0.000 claims description 26
- 230000003595 spectral effect Effects 0.000 claims description 23
- 238000005070 sampling Methods 0.000 claims description 17
- 230000006870 function Effects 0.000 claims description 15
- 238000000870 ultraviolet spectroscopy Methods 0.000 claims description 13
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- 238000010606 normalization Methods 0.000 claims description 4
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- 230000007613 environmental effect Effects 0.000 description 2
- 238000011065 in-situ storage Methods 0.000 description 2
- 230000031700 light absorption Effects 0.000 description 2
- 238000010183 spectrum analysis Methods 0.000 description 2
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Abstract
The invention relates to the technical field of data denoising, in particular to a nitrogen-sulfur in-situ measurement method and system based on a differential ultraviolet spectrum technology. According to the change trend of the local reflection intensity between adjacent data points in each data segment of the spectrum curve, curve volatility in each data segment is obtained; screening out an absorption peak approximate region as a target data segment; obtaining the mergence in different preset neighborhood ranges according to the difference of curve volatility between the target data segment and other data segments in the corresponding different preset neighborhood ranges; judging the merging neighborhood range of the target data segment; obtaining a plurality of merged neighborhood ranges; obtaining the optimal average window size according to the fluctuation characteristics of the corresponding reflection intensity of the data points in different merging neighborhood ranges and the corresponding wavelength ranges; obtaining a denoising spectrum curve; in situ measurements were performed on nitrogen sulfur samples. The method obtains the proper average window size in the denoising process of the spectrum curve, optimizes the denoising effect and accurately measures the concentration.
Description
Technical Field
The invention relates to the technical field of data denoising, in particular to a nitrogen-sulfur in-situ measurement method and system based on a differential ultraviolet spectrum technology.
Background
The differential ultraviolet spectrum technology is a method for analyzing the absorption characteristics of ultraviolet light wave bands by using materials, and is particularly suitable for monitoring chemical substances such as nitrogen, sulfur and the like containing specific ultraviolet light absorption characteristics. The ratio of signals to noise is improved by utilizing the technical means of differential spectrum, and accurate nitrogen and sulfur concentration information is extracted by a data processing algorithm aiming at the complexity of differential ultraviolet spectrum data, so that interference and errors are avoided; therefore, denoising the nitrogen-sulfur curve is a key step for improving detection accuracy and sensitivity.
In the prior art, a moving average algorithm is adopted to remove noise in a spectrum curve; however, when the average window is too large, the peak information of the spectrum curve is lost, and the measurement of the sample concentration obtained according to the peak information is error; conversely, when the average window is too small, there is a residual of part of the noise; therefore, the poor average window size setting makes the denoising effect poor, and causes errors in the detected nitrogen-sulfur concentration.
Disclosure of Invention
In order to solve the technical problem that the error occurs in the detected sample concentration due to poor denoising effect caused by poor average window size setting, the invention aims to provide a nitrogen-sulfur in-situ measurement method and system based on a differential ultraviolet spectrum technology, and the adopted technical scheme is as follows:
the invention provides a nitrogen and sulfur in-situ measurement method based on a differential ultraviolet spectrum technology, which comprises the following steps:
acquiring a spectrum curve of a nitrogen-sulfur sample; the spectrum curve comprises reflection intensities corresponding to different wavelengths;
discretizing the spectrum curve to obtain data points on the spectrum curve; acquiring a plurality of data segments of a spectrum curve, and acquiring curve volatility in each data segment according to the change trend of local reflection intensity between adjacent data points in each data segment; screening out an absorption peak approximate region according to the curve fluctuation in each data segment;
Optionally selecting an absorption peak approximation area as a target data segment; obtaining the mergence in different preset neighborhood ranges according to the difference of curve volatility between the target data segment and other data segments in the corresponding different preset neighborhood ranges; judging a merging neighborhood range of the target data segment according to the mergence; changing the target data segment to obtain a plurality of merging neighborhood ranges;
obtaining the optimal average window size according to the fluctuation characteristics of the corresponding reflection intensity of the data points in different merging neighborhood ranges and the wavelength range of the merging neighborhood range; denoising the spectrum curve according to the optimal average window size to obtain a denoised spectrum curve;
and carrying out in-situ measurement on nitrogen and sulfur according to the denoising spectrum curve.
Further, the method for acquiring the data points comprises the following steps:
obtaining the minimum sampling frequency of a spectrum curve by adopting the Nyquist sampling theorem; calculating the reciprocal of the minimum sampling frequency and taking an integer as a sampling step length; discretizing the spectrum curve with the sampling step length as interval to obtain the data points on the spectrum curve.
Further, the method for acquiring the curve volatility comprises the following steps:
sequentially acquiring data points in a preset wavelength range on a spectrum curve to form a data segment;
Obtaining a fitting function of a spectrum curve;
Calculating, within each data segment, an integral of the fitting function between adjacent data points as the local reflection intensity between the adjacent data points;
Calculating a difference between two adjacent local reflection intensities as a first difference;
And calculating the average value of the first difference between all adjacent local reflection intensities in each data segment, and normalizing the average value to be used as the curve fluctuation of each data segment.
Further, the method for acquiring the absorption peak approximation area comprises the following steps:
and if the curve fluctuation of the data segment is within a preset fluctuation threshold range, the corresponding data segment is used as an absorption peak approximation area.
Further, the method for acquiring the mergence comprises the following steps:
calculating the ratio of the target data segment to each other data segment in the preset neighborhood range in each preset neighborhood range of the target data segment as a first ratio; calculating the difference between the first ratio and a preset constant between the target data segment and each other data segment in a preset neighborhood range as a first difference; and calculating the average value of the first difference between the target data segment and all other data segments in the preset neighborhood range, and taking the average value as the mergence in each preset neighborhood range.
Further, the method for acquiring the merged neighborhood range comprises the following steps:
If the mergence in the preset neighborhood range is not in the preset mergence threshold range, judging that the previous preset neighborhood range is the mergence neighborhood range.
Further, the method for obtaining the optimal average window size includes:
Calculating the difference between the maximum wavelength and the minimum wavelength in the merging neighborhood range as the wavelength range of the merging neighborhood range;
Obtaining the optimal average window size according to an obtaining formula of the optimal average window size, wherein the obtaining formula of the optimal average window size is as follows:
; wherein, Representing an optimal average window size; Represent the first Combining wavelength ranges of the neighborhood ranges; Represent the first Merging data points in a neighborhood range; Represent the first The data points in the combined neighborhood range correspond to the reflection intensities; Represent the first Variance of the corresponding reflection intensity of the data points in the range of the merging neighborhood; representing the number of merged neighborhood regions; Representing the normalization function.
Further, the method for acquiring the denoising spectrum curve comprises the following steps:
and denoising the spectral curve by adopting a moving average algorithm based on the optimal average window size to obtain a denoising spectral curve.
Further, the preset fluctuation threshold range is that。
The invention also provides a nitrogen and sulfur in-situ measurement system based on the differential ultraviolet spectrum technology, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes any one step of the nitrogen and sulfur in-situ measurement method based on the differential ultraviolet spectrum technology when executing the computer program.
The invention has the following beneficial effects:
In order to simplify the data processing process and retain enough information, discretizing a spectrum curve to obtain data points on the spectrum curve; acquiring a plurality of data segments of the spectrum curve, and acquiring curve volatility in each data segment according to the change trend of the local reflection intensity between adjacent data points in each data segment, so that the method is beneficial to more finely analyzing the local characteristics in each data segment and describing the structural characteristics of the spectrum curve; screening out an absorption peak approximate region according to curve fluctuation in each data segment, focusing on a region containing key characteristic information, and improving pertinence of spectrum analysis; optionally selecting an absorption peak approximation area as a target data segment; in order to make the form of the absorption peak clearer and more accurate, according to the difference of curve fluctuation between the target data segment and other data segments in corresponding different preset neighborhood ranges, the combinability in the different preset neighborhood ranges is obtained, and the similarity and the combinability between the data segments are evaluated; judging a merging neighborhood range of the target data segment according to the mergence, better reflecting the spectral characteristics of the substance, describing the complete morphological characteristics of the absorption peak, and enabling the spectral data to have better interpretation; changing the target data segment to obtain a plurality of merging neighborhood ranges; according to fluctuation characteristics of the corresponding reflection intensity of the data points in different merging neighborhood ranges and the corresponding wavelength ranges, the optimal average window size is obtained, useful information of a spectrum curve can be reserved to the maximum extent, and noise and interference are effectively removed; denoising the spectrum curve according to the optimal average window size to obtain a denoised spectrum curve, removing noise components in the spectrum curve more accurately, and improving the signal-to-noise ratio of spectrum data; in situ measurements were performed on nitrogen sulfur samples. The method obtains the proper average window size in the denoising process of the spectrum curve, optimizes the denoising effect and accurately measures the concentration.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a method for measuring nitrogen and sulfur in situ based on a differential ultraviolet spectrum technology according to an embodiment of the present invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following detailed description is given below of the nitrogen-sulfur in-situ measurement method and system based on the differential ultraviolet spectroscopy technology according to the invention, which are provided by the invention, with reference to the accompanying drawings and the preferred embodiment. In the following description, different "one embodiment" or "another embodiment" means that the embodiments are not necessarily the same. Furthermore, the particular features, structures, or characteristics of one or more embodiments may be combined in any suitable manner.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The invention provides a nitrogen and sulfur in-situ measurement method and a system based on a differential ultraviolet spectrum technology, which are concretely described below with reference to the accompanying drawings.
Referring to fig. 1, a flowchart of a method for in-situ measurement of nitrogen and sulfur based on differential ultraviolet spectroscopy according to an embodiment of the present invention is shown, and the method specifically includes:
Step S1: acquiring a spectrum curve of a nitrogen-sulfur sample; the spectral curves include reflected intensities corresponding to different wavelengths.
In the embodiment of the invention, in the process of carrying out nitrogen-sulfur analysis on a sample containing ultraviolet light absorption characteristics such as nitrogen, sulfur and the like through a differential ultraviolet spectroscopy technology, firstly, a differential ultraviolet spectroscopy technology is adopted to obtain a spectrum curve of the nitrogen-sulfur sample, wherein the spectrum curve comprises reflection intensities corresponding to different wavelengths; wherein, the abscissa is the wavelength of ultraviolet light, and the unit is nanometer (nm); the ordinate is the corresponding reflection intensity at different wavelengths, and no dimension exists.
Step S2: discretizing the spectrum curve to obtain data points on the spectrum curve; acquiring a plurality of data segments of a spectrum curve, and acquiring curve volatility in each data segment according to the change trend of local reflection intensity between adjacent data points in each data segment; and screening out an absorption peak approximate region according to curve fluctuation in each data segment.
The continuous spectrum curve comprises infinite data points, and the continuous spectrum curve can be converted into a limited number of data point sets through discretization, so that the calculated amount is reduced, and the characteristic extraction and analysis are easier to perform; proper discretization can eliminate or reduce small fluctuations due to measurement equipment or environmental noise, thereby improving the accuracy of the spectral analysis. The spectral curve is discretized to obtain data points on the spectral curve.
Preferably, in one embodiment of the present invention, the discretized acquisition method includes:
After discretizing the spectrum curve, the characteristics of the original data are still reserved; obtaining the minimum sampling frequency of a spectrum curve by adopting the Nyquist sampling theorem; calculating the reciprocal of the minimum sampling frequency and taking an integer as a sampling step length; by selecting a proper sampling step length, key features in a spectrum curve can be highlighted; discretizing the spectrum curve with the sampling step length as interval to obtain the data points on the spectrum curve. The nyquist sampling theorem is a technical means well known to those skilled in the art, and is not described herein.
Dividing the data point into a plurality of data segments, and capturing the local characteristics in each data segment more accurately; spectral curves in different data segments may have different volatility and variation trends, and the variation trend of the local reflection intensity between adjacent data points may show the trend of rising, falling, fluctuation and the like in the spectral curves, which is helpful for understanding the structure and characteristics of the spectral curves; the larger the difference between the local reflection intensities, the more the spectral curve at the data segment fluctuates, and the larger the curve fluctuation is; and acquiring a plurality of data segments of the spectrum curve, and acquiring the curve fluctuation in each data segment according to the change trend of the local reflection intensity between adjacent data points in each data segment.
Preferably, in one embodiment of the present invention, the method for acquiring curve volatility includes:
Sequentially acquiring data points in a preset wavelength range on a spectrum curve to form a data segment; obtaining a fitting function of a spectrum curve; because the spectrum curve is a continuous curve, in order to ensure the original data value of the curve to the greatest extent in the analysis process, the local reflection intensity characteristic of the spectrum curve in a specific wavelength range is reflected more accurately, an integral method is selected, and in each data segment, the integral of a fitting function between adjacent data points is calculated and used as the local reflection intensity between the adjacent data points; calculating a difference between two adjacent local reflection intensities as a first difference; the mean value of the first difference between all adjacent local reflection intensities in each data segment is calculated and normalized as the curve volatility of each data segment. In one embodiment of the invention, the formula for curve volatility is expressed as:
；
Wherein, Represent the firstCurve volatility of individual data segments; Represent the first Sequence numbers of data points within the data segments; Represent the first Data points; Represent the first Data points; a fitting function representing a spectral curve; Represent the first The number of data points within the data segment of the data segments; Representing the fitting function at the first Data point and adjacent firstAn integral function between the data points; Representing the normalization function.
In the formula of the curve volatility,The first difference between adjacent partial reflection intensities is represented, and the larger the first difference is, the larger the difference between the partial reflection intensities is, the larger the curve fluctuation is, and the more characteristic information is contained.
It should be noted that, in one embodiment of the present invention, the preset wavelength range is 30nm; in other embodiments of the present invention, the size of the preset wavelength range may be specifically set according to specific situations, which are not limited and described herein.
It should be noted that, in one embodiment of the present invention, the fitting function may be obtained by using a least square method; in other embodiments of the present invention, a fitting function may be obtained by using a fitting method such as polynomial fitting and spline interpolation, and the fitting method is a technical means well known to those skilled in the art, which is not described herein.
The nitrogen-sulfur compounds in the sample have different absorption characteristics, the positions and intensities of absorption peaks in the spectrum are different, the absorption peaks of nitrogen are usually concentrated in a region with lower wavelengths of a spectrum curve, and sulfur is mainly concentrated in a middle region of the wavelengths of the spectrum curve, so that the absorption peaks of the spectrum curve appear at a plurality of wavelengths; absorption peaks refer to regions of the spectrum in which the reflected intensity is significantly reduced in a particular wavelength range, with significantly greater volatility than other non-absorbing regions; the larger the curve volatility, the more likely it is the absorption peak approximation region; the absorption peak approximation area is screened out according to the curve fluctuation in each data segment.
Preferably, in one embodiment of the present invention, the method for acquiring the absorption peak approximation area includes:
and if the curve fluctuation of the data segment is within a preset fluctuation threshold range, the corresponding data segment is used as an absorption peak approximation area.
It should be noted that, in one embodiment of the present invention, the preset fluctuation threshold range is; In other embodiments of the present invention, the size of the preset fluctuation threshold range may be specifically set according to specific situations, which is not limited and described herein.
Step S3: optionally selecting an absorption peak approximation area as a target data segment; obtaining the mergence in different preset neighborhood ranges according to the difference of curve volatility between the target data segment and other data segments in the corresponding different preset neighborhood ranges; judging the merging neighborhood range of the target data segment according to the merging property; and changing the target data segment to obtain a plurality of merging neighborhood ranges.
Because a part of absorption peaks possibly occupy a plurality of data segments in the process of dividing the data segments, the complete absorption peak area needs to be analyzed; to get the result faster, find the key information, an absorption peak approximation area is selected as the target data segment; the difference of curve volatility reflects the similarity and the difference between the data segments, and the smaller the difference is, the more likely the data segments in the neighborhood range are the areas which can be merged; therefore, the mergence in different preset neighborhood ranges is obtained according to the difference of curve volatility between the target data segment and other data segments in the corresponding different preset neighborhood ranges.
Preferably, in one embodiment of the present invention, the method for acquiring the mergence includes:
Calculating the ratio of the target data segment to each other data segment in the preset neighborhood range in each preset neighborhood range of the target data segment as a first ratio; calculating the difference between a first ratio and a preset constant between the target data segment and each other data segment in a preset neighborhood range as a first difference; and calculating the average value of the first difference between the target data segment and all other data segments in the preset neighborhood range, and taking the average value as the mergence in each preset neighborhood range. In one embodiment of the invention, the formula for the merger is expressed as:
；
Wherein, Represent the firstSequence numbers of preset neighborhood ranges of the target data segments; Represent the first The first target data segmentMergeability of a number of preset neighborhood ranges; Represent the first Curve volatility of individual target data segments; Represent the first The data segments correspond to the first data segment in the preset neighborhood rangeCurve volatility of the other data segments; Representing the number of other data segments within the neighborhood; representing a preset constant, taking the checked value as 1.
In the formula of the mergence,Represent the firstThe target data segment is within the corresponding preset neighborhood rangeThe ratio of the curve volatility between the other data segments, if the ratio is close to 1,The closer to 0, the closer the curve volatility between data segments, the more likely the preset neighborhood range is the absorption peak region.
It should be noted that, in one embodiment of the present invention, the method for acquiring different preset neighborhood ranges includes: sequentially expanding and iterating a preset number of data segments outwards by taking the target data segment as a center, and forming a preset neighborhood range with the target data segment; the preset number is 2; an example is made: firstly, selecting 2 adjacent data segments, and forming a neighborhood range with a target data segment; expanding 2 data segments outwards for the second time, and selecting 4 adjacent data segments and target data segments to form a neighborhood range in the first iteration; thirdly, iterating, namely expanding 2 data segments outwards, and selecting target data segments of 6 adjacent data segments to form a neighborhood range with the second iteration; and sequentially acquiring different preset neighborhood ranges.
Through the mergence of the data segments in the neighborhood range, which data segments have similar characteristics can be judged, so that the merging neighborhood range is determined; more representative spectral features are extracted, and components in the sample are identified more accurately. The merge neighborhood range of the target data segment is determined based on the mergence.
Preferably, in one embodiment of the present invention, the method for acquiring the merged neighborhood range includes:
If the mergence in the preset neighborhood range is not in the preset mergence threshold range, judging the corresponding previous preset neighborhood range as a mergence neighborhood range.
It should be noted that, in one embodiment of the present invention, the preset merge threshold range is; In an embodiment of the present invention, the size of the preset merge threshold range may be specifically set according to specific situations, which is not limited and described herein.
There are a plurality of distinct characteristic regions in the spectral curve, each region possibly representing a different component or structure in the sample; by changing the target data segment, these different feature regions can be explored and identified, thereby providing a more comprehensive understanding of the spectral characteristics of the sample. The target data segment is changed to obtain a plurality of merged neighborhood regions.
Step S4: obtaining the optimal average window size according to the fluctuation characteristics of the corresponding reflection intensity of the data points in different merging neighborhood ranges and the wavelength range of the merging neighborhood range; and denoising the spectrum curve according to the optimal average window size to obtain a denoising spectrum curve.
The fluctuation characteristics of the corresponding reflection intensity of the data points in the combined neighborhood range can reflect the characteristics of the spectrum data, and the larger the fluctuation characteristics are, the more characteristic information exists in the corresponding wave band range, the more likely the characteristic information is an absorption peak area, and the more the characteristic information needs to be amplified; the original wave band range can directly reflect the real reflection or emission characteristics of the sample in the wave band ranges, so that the composition and the structural information of the sample are more accurately disclosed; comprehensively considering the characteristics of the data points on the basis of the wavelength ranges corresponding to the merging neighborhood ranges, and ensuring that useful characteristic information is fully considered and utilized; and therefore, the optimal average window size is obtained according to the fluctuation characteristics of the data points corresponding to the reflection intensity in different merging neighborhood ranges and the corresponding wavelength ranges.
Preferably, in one embodiment of the present invention, the method for obtaining the optimal average window size includes:
Calculating the difference between the maximum wavelength and the minimum wavelength in the merging neighborhood range as the wavelength range of the merging neighborhood range;
Obtaining the optimal average window size according to an obtaining formula of the optimal average window size, wherein the obtaining formula of the optimal average window size is as follows:
；
Wherein, Representing an optimal average window size; Represent the first Combining wavelength ranges of the neighborhood ranges; Represent the first Merging data points in a neighborhood range; Represent the first The data points in the combined neighborhood range correspond to the reflection intensities; Represent the first Variance of the corresponding reflection intensity of the data points in the range of the merging neighborhood; representing the number of merged neighborhood regions; Representing the normalization function.
In the acquisition formula for the optimal average window size,Represent the firstThe ratio of the variance of the reflected intensities of the individual merged neighborhood range data points to the variance of the reflected intensities of all merged neighborhood range data points is greater, the greater the ratio, the thThe larger the variance of the reflection intensities of the individual merged neighborhood range data points, the moreThe larger the difference between the reflection intensities of the data points in the merging neighborhood range, the larger the volatility in the merging neighborhood range, the more likely the absorption peak region, and the more the weight duty ratio of the wavelength range needs to be adjusted; the larger the wavelength range, the larger the weight ratio, the larger the optimal average window, and the more feature information is reserved.
Due to factors such as instrument errors, environmental noise and the like, a spectrum curve may contain noise components, and denoising processing is needed. However, due to the smaller window size, the details of the spectral curve can be better preserved, but partial noise remains; the larger window size can remove noise more effectively, but the peak information of the spectrum curve is lost, so that the measurement of the sample concentration obtained according to the peak information is error; the optimal average window size can ensure that the main characteristic information of the spectrum curve is kept as much as possible while noise is removed, so that the data is more accurate; and therefore, denoising the spectrum curve according to the optimal average window size to obtain a denoised spectrum curve.
Preferably, in one embodiment of the present invention, the method for acquiring a denoising spectral curve comprises:
and denoising the spectral curve by adopting a moving average algorithm based on the optimal average window size to obtain a denoising spectral curve.
It should be noted that, after the optimal average window size is obtained, in other embodiments of the present invention, in the process of performing the moving average algorithm on the spectrum curve, a weight may be allocated to each piece of data according to whether the data in the optimal average window is in the absorption peak area, so that the weight of the data in the absorption peak area is greater than that in other areas, more main feature information may be retained, and the denoising effect is more accurate; the specific moving average algorithm is a technical means well known to those skilled in the art, and will not be described herein.
Step S5: and carrying out in-situ measurement on the nitrogen and sulfur according to the denoising spectrum curve.
The denoising spectrum curve more accurately reflects the spectrum characteristics of nitrogen and sulfur elements in the sample, avoids measurement errors possibly caused by sample damage or pollution, and is beneficial to accurately evaluating the nitrogen and sulfur content in the sample. The in situ measurement of nitrogen sulfur is performed based on the denoising spectral curve.
In one embodiment of the present invention, the reflection intensity of the absorption peak of the spectrum curve may reflect the concentration, and the ratio of the reflection intensity to the nitrogen-sulfur concentration is calculated by using beer-lambert law for the denoising spectrum curve, so as to obtain the nitrogen-sulfur concentration. The specific beer-lambert law is a technical means well known to those skilled in the art, and will not be described herein.
In summary, the present invention discretizes the spectrum curve to obtain the data points on the spectrum curve; acquiring a plurality of data segments of a spectrum curve, and acquiring curve volatility in each data segment according to the change trend of local reflection intensity between adjacent data points in each data segment; screening out an absorption peak approximate region; optionally selecting an absorption peak approximation area as a target data segment; obtaining the mergence in different preset neighborhood ranges according to the difference of curve volatility between the target data segment and other data segments in the corresponding different preset neighborhood ranges; judging the merging neighborhood range of the target data segment; changing the target data segment to obtain a plurality of merging neighborhood ranges; obtaining the optimal average window size according to the fluctuation characteristics of the corresponding reflection intensity of the data points in different merging neighborhood ranges and the corresponding wavelength ranges; denoising the spectrum curve to obtain a denoised spectrum curve; in situ measurements were performed on nitrogen sulfur samples. The method obtains the proper average window size in the denoising process of the spectrum curve, optimizes the denoising effect and accurately measures the concentration.
The invention also provides a nitrogen and sulfur in-situ measurement system based on the differential ultraviolet spectrum technology, which comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor realizes any one of the steps of the nitrogen and sulfur in-situ measurement method based on the differential ultraviolet spectrum technology when executing the computer program.
An embodiment of a nitrogen-sulfur curve denoising method based on a differential ultraviolet spectrum technology:
In the prior art, a moving average algorithm is adopted to remove noise in a spectrum curve; however, when the average window is too large, the peak information of the spectrum curve is lost, and the measurement of the sample concentration obtained according to the peak information is error; conversely, when the average window is too small, there is a residual of part of the noise; therefore, the technical problem that the denoising effect is poor due to the poor average window size setting. In order to solve the technical problem, the embodiment provides a nitrogen-sulfur curve denoising method based on a differential ultraviolet spectrum technology, which comprises the following steps:
S1, acquiring a spectrum curve of a nitrogen-sulfur sample; the spectral curves include reflected intensities corresponding to different wavelengths.
Step S2: discretizing the spectrum curve to obtain data points on the spectrum curve; acquiring a plurality of data segments of a spectrum curve, and acquiring curve volatility in each data segment according to the change trend of local reflection intensity between adjacent data points in each data segment; and screening out an absorption peak approximate region according to curve fluctuation in each data segment.
Step S3: optionally selecting an absorption peak approximation area as a target data segment; obtaining the mergence in different preset neighborhood ranges according to the difference of curve volatility between the target data segment and other data segments in the corresponding different preset neighborhood ranges; judging the merging neighborhood range of the target data segment according to the merging property; and changing the target data segment to obtain a plurality of merging neighborhood ranges.
Step S4: obtaining the optimal average window size according to the fluctuation characteristics of the corresponding reflection intensity of the data points in different merging neighborhood ranges and the wavelength range of the merging neighborhood range; and denoising the spectrum curve according to the optimal average window size to obtain a denoising spectrum curve.
Because the specific implementation process of steps S1 to S4 is already described in detail in the above-mentioned method for measuring nitrogen and sulfur in situ based on the differential ultraviolet spectrum technology, the detailed description is omitted.
The technical effect of this embodiment is:
In the embodiment, the data points on the spectrum curve are obtained by discretizing the spectrum curve; acquiring a plurality of data segments of a spectrum curve, and acquiring curve volatility in each data segment according to the change trend of local reflection intensity between adjacent data points in each data segment; screening out an absorption peak approximate region; optionally selecting an absorption peak approximation area as a target data segment; obtaining the mergence in different preset neighborhood ranges according to the difference of curve volatility between the target data segment and other data segments in the corresponding different preset neighborhood ranges; judging the merging neighborhood range of the target data segment; changing the target data segment to obtain a plurality of merging neighborhood ranges; obtaining the optimal average window size according to the fluctuation characteristics of the corresponding reflection intensity of the data points in different merging neighborhood ranges and the corresponding wavelength ranges; denoising the spectrum curve to obtain a denoised spectrum curve; in situ measurements were performed on nitrogen sulfur samples. The invention obtains the proper average window size in the denoising process of the spectrum curve and optimizes the denoising effect.
It should be noted that: the sequence of the embodiments of the present invention is only for description, and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
Claims (9)
1. The nitrogen and sulfur in-situ measurement method based on the differential ultraviolet spectrum technology is characterized by comprising the following steps of:
acquiring a spectrum curve of a nitrogen-sulfur sample; the spectrum curve comprises reflection intensities corresponding to different wavelengths;
discretizing the spectrum curve to obtain data points on the spectrum curve; acquiring a plurality of data segments of a spectrum curve, and acquiring curve volatility in each data segment according to the change trend of local reflection intensity between adjacent data points in each data segment; screening out an absorption peak approximate region according to the curve fluctuation in each data segment;
Optionally selecting an absorption peak approximation area as a target data segment; obtaining the mergence in different preset neighborhood ranges according to the difference of curve volatility between the target data segment and other data segments in the corresponding different preset neighborhood ranges; judging a merging neighborhood range of the target data segment according to the mergence; changing the target data segment to obtain a plurality of merging neighborhood ranges;
obtaining the optimal average window size according to the fluctuation characteristics of the corresponding reflection intensity of the data points in different merging neighborhood ranges and the wavelength range of the merging neighborhood range; denoising the spectrum curve according to the optimal average window size to obtain a denoised spectrum curve;
performing in-situ measurement on nitrogen and sulfur according to the denoising spectrum curve;
the method for obtaining the optimal average window size comprises the following steps:
Calculating the difference between the maximum wavelength and the minimum wavelength in the merging neighborhood range as the wavelength range of the merging neighborhood range;
Obtaining the optimal average window size according to an obtaining formula of the optimal average window size, wherein the obtaining formula of the optimal average window size is as follows:
; wherein, Representing an optimal average window size; Represent the first Combining wavelength ranges of the neighborhood ranges; Represent the first Merging data points in a neighborhood range; Represent the first The data points in the combined neighborhood range correspond to the reflection intensities; Represent the first Variance of the corresponding reflection intensity of the data points in the range of the merging neighborhood; representing the number of merged neighborhood regions; Representing the normalization function.
2. The method for in-situ measurement of nitrogen and sulfur based on differential ultraviolet spectroscopy according to claim 1, wherein the method for acquiring data points comprises:
obtaining the minimum sampling frequency of a spectrum curve by adopting the Nyquist sampling theorem; calculating the reciprocal of the minimum sampling frequency and taking an integer as a sampling step length; discretizing the spectrum curve with the sampling step length as interval to obtain the data points on the spectrum curve.
3. The method for in-situ measurement of nitrogen and sulfur based on the differential ultraviolet spectroscopy according to claim 1, wherein the method for obtaining the curve volatility comprises the following steps:
sequentially acquiring data points in a preset wavelength range on a spectrum curve to form a data segment;
Obtaining a fitting function of a spectrum curve;
Calculating, within each data segment, an integral of the fitting function between adjacent data points as the local reflection intensity between the adjacent data points;
Calculating a difference between two adjacent local reflection intensities as a first difference;
And calculating the average value of the first difference between all adjacent local reflection intensities in each data segment, and normalizing the average value to be used as the curve fluctuation of each data segment.
4. The method for in-situ measurement of nitrogen and sulfur based on the differential ultraviolet spectroscopy according to claim 1, wherein the method for obtaining the absorption peak approximation region comprises the following steps:
and if the curve fluctuation of the data segment is within a preset fluctuation threshold range, the corresponding data segment is used as an absorption peak approximation area.
5. The method for in-situ measurement of nitrogen and sulfur based on differential ultraviolet spectroscopy according to claim 1, wherein the method for obtaining the incorporability comprises the following steps:
calculating the ratio of the target data segment to each other data segment in the preset neighborhood range in each preset neighborhood range of the target data segment as a first ratio; calculating the difference between the first ratio and a preset constant between the target data segment and each other data segment in a preset neighborhood range as a first difference; and calculating the average value of the first difference between the target data segment and all other data segments in the preset neighborhood range, and taking the average value as the mergence in each preset neighborhood range.
6. The method for in-situ measurement of nitrogen and sulfur based on differential ultraviolet spectroscopy according to claim 1, wherein the method for obtaining the combined neighborhood range comprises the following steps:
If the mergence in the preset neighborhood range is not in the preset mergence threshold range, judging that the previous preset neighborhood range is the mergence neighborhood range.
7. The method for in-situ measurement of nitrogen and sulfur based on the differential ultraviolet spectroscopy according to claim 1, wherein the method for obtaining the denoising spectrum curve comprises the following steps:
and denoising the spectral curve by adopting a moving average algorithm based on the optimal average window size to obtain a denoising spectral curve.
8. The method for in-situ measurement of nitrogen and sulfur based on differential ultraviolet spectroscopy according to claim 4, wherein the preset fluctuation threshold range is。
9. A nitrogen-sulfur in-situ measurement system based on a differential ultraviolet spectroscopy technology, the system comprising a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor implements the steps of a nitrogen-sulfur in-situ measurement method based on a differential ultraviolet spectroscopy technology as claimed in any one of claims 1 to 8 when executing the computer program.
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