CN114279976B - Method for detecting content of soluble salt in wall painting based on reflection spectrum - Google Patents
Method for detecting content of soluble salt in wall painting based on reflection spectrum Download PDFInfo
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Abstract
The invention discloses a method for detecting the content of soluble salt in a wall painting based on reflection spectrum, which comprises the following steps: manufacturing a plurality of standard mural sample blocks containing soluble salts with different mass concentrations; sampling each standard wall painting sample block at least 1 time by utilizing a spectrum radiometer at intervals of preset time to obtain an original reflection spectrum of the standard wall painting sample block; performing reciprocal logarithmic transformation on the original reflection spectrum to obtain a reciprocal logarithmic spectrum; extracting a characteristic wave band; taking the mass concentration of the soluble salt of the standard mural sample block as a dependent variable, taking a parameter value of the logarithmic spectrum of the reciprocal at a characteristic wave band as an independent variable, and establishing a mural sample soluble salt content prediction model; and obtaining a punctiform spectrum curve of a specified position of the wall painting to be detected by utilizing a spectrum radiometer, and predicting the mass concentration of the soluble salt by utilizing a soluble salt content prediction model. The invention has the beneficial effects of nondestructive, high-efficiency and real-time detection of the content of the soluble salt in any area of the wall painting.
Description
Technical Field
The invention relates to the technical field of mural detection. More particularly, the invention relates to a method for detecting the content of soluble salts in wall paintings based on reflection spectrum.
Background
The mural is a colored drawing attached to ancient buildings and is also a carrier reflecting human social life, religious beliefs and historical culture. However, the wall painting is always worry about preservation of the current state due to natural erosion degradation and human improper intervention. The interaction between the wall painting and the soluble salt in the environment is obvious, the salt can be continuously dissolved, crystallized and expanded along with the temperature, and once the content product is accumulated to a certain concentration, the capillary water moves to the surface layer of the wall painting to generate enrichment and crystallization phenomena, so that various irreversible wall painting diseases such as alkali and crisp are induced. Once the mural salt damage is formed, the artistic value of the mural salt damage is seriously weakened irreversibly. Therefore, the nondestructive detection of the content of the soluble salt in the mural is performed efficiently in real time with high precision, and the method has very important and urgent practical significance.
At present, the detection of soluble salts in wall paintings mainly comprises the following two methods, wherein the first method is to analyze the types and the contents of salts in a wall painting ground layer by utilizing an ion chromatograph; the second is to use capillary electrophoresis to rapidly detect and analyze the mural salt damage; both methods need to sample the position to be detected (the position of the ground layer disease) in the full-picture wall painting in the field, so that salt content detection is difficult to be carried out on any appointed area of the full-picture wall painting, the integrity of the wall painting can be destroyed, meanwhile, the peak value limit on the concentration range of detected salt ions exists, the precision and the accuracy can be reduced along with the sampling quality, and the dynamic monitoring of the salt content can not be carried out.
Disclosure of Invention
It is an object of the present invention to solve at least the above problems and to provide at least the advantages to be described later.
The invention also aims to provide a method for detecting the content of the soluble salt in the wall painting based on the reflection spectrum, which realizes nondestructive, efficient and real-time detection of the content of the soluble salt in any area in the wall painting.
To achieve these objects and other advantages and in accordance with the purpose of the invention, there is provided a method for detecting the content of soluble salts in a wall painting based on reflectance spectrum, comprising the steps of: manufacturing a plurality of standard mural sample blocks containing soluble salts with different mass concentrations;
at least 1 sampling each standard mural sample block by utilizing a spectrum radiometer at intervals of preset time, wherein a pretreatment spectrum of the standard mural sample block in a wavelength range of 350-2500nm is obtained by pretreatment after each sampling;
performing reciprocal logarithmic transformation on the preprocessed spectrum to obtain a reciprocal logarithmic spectrum;
extracting a characteristic wave band according to the logarithmic spectrum of the reciprocal;
taking the mass concentration of the soluble salt of the standard mural sample block as a dependent variable, taking a parameter value of the logarithmic spectrum of the reciprocal at a characteristic wave band as an independent variable, carrying out linear regression to obtain a best fit line, and establishing a mural sample soluble salt content prediction model;
and (3) acquiring a punctiform spectrum curve of a specified position of the wall painting to be detected by utilizing a spectrum radiometer, preprocessing, carrying out reciprocal logarithmic transformation, acquiring characteristic spectrum parameters at a characteristic wave band, and then carrying into a soluble salt content prediction model of the wall painting sample to predict the mass concentration of the soluble salt.
Preferably, the method for manufacturing the standard mural sample block comprises the following steps:
manufacturing a coarse mud layer;
and manufacturing a fine mud layer on the surface of the coarse mud layer, and naturally drying in the shade to obtain a plurality of standard mural sample blocks, wherein soluble salt with corresponding mass concentration is uniformly mixed in the fine mud layer of each standard mural sample block.
Preferably, the mass concentration range of the soluble salt formed by the plurality of standard mural sample blocks is 0-1%, wherein the mass concentrations of the soluble salt contained in the standard mural sample blocks are arranged from small to large, and the mass concentration difference of the standard mural sample blocks with adjacent two mass concentrations is not more than 0.2%.
Preferably, the mass concentration of the soluble salt in the standard mural sample block is arranged from small to large, and the mass concentration differences of any two adjacent standard mural sample blocks with mass concentrations are equal.
Preferably, the soluble salt is one of sulfate, nitrate and chloride.
Preferably, the soluble salt is sodium sulfate.
Preferably, each sampling is specifically:
dividing each standard mural sample block into 3×3 blocks, randomly selecting a center point of each block for data acquisition in each row and each column, wherein the method for data acquisition of each center point comprises the following steps:
s1, a probe of a spectrum radiator is perpendicular to a standard mural painting sample block and aims at a central point to collect an initial reflection spectrum curve within a wavelength range of 350-2500 nm;
s2, horizontally rotating a probe of the spectrum radiometer by 90 degrees to acquire the next time;
and S3, repeating the step S2 until the probe of the spectrum radiator horizontally rotates 270 degrees.
Preferably, the post-sampling pretreatment comprises the following steps:
sa, taking the arithmetic average value of the breakpoint correction spectrum curve of the same center point as the spectrum curve of the center point;
and Sb, taking the arithmetic average value of the average spectrum curves corresponding to the same standard mural sample block.
Preferably, the preprocessing after each sampling further comprises breakpoint correction of the initial reflection spectrum curve before the step Sa is performed, so as to obtain a breakpoint correction spectrum curve;
and after the step Sb is carried out, carrying out Savitzky-Golay smoothing treatment on the spectrum curve collected by the standard mural sample block each time to obtain a reflection spectrum of the standard mural sample block in the wavelength range of 350-2500 nm.
Preferably, the method for extracting the characteristic band according to the reciprocal logarithmic spectrum includes the steps of:
selecting a wave band range in which the spectrum shows obvious peaks and valleys and the spectrum curve shows stable monotonicity change;
for a determined band range, after significant p=0.05 pearson correlation of the pre-processed spectrum with salt concentration, the characteristic band of the reciprocal logarithmic spectrum is determined.
The invention at least comprises the following beneficial effects:
the method has the advantages that the point-like reflection spectrum of different areas and salt damage degrees of the wall painting is obtained by utilizing a spectrum technology, a fitting regression equation of salt ion concentration and spectrum characteristic parameters is established through spectrum characteristic enhancement, a prediction inversion system of the soluble salt content of the wall painting is established, nondestructive, efficient and real-time detection of the soluble salt content of any area in the wall painting is realized, the detection precision is high, and the method has great economic value and practical significance in the fields of identification of the salt damage degree of the wall painting and long-term preservation of the wall painting, and is specific:
firstly, the hyperspectral technology is adopted to collect the punctiform spectrum of the wall painting, and the band response range is wider, so that the wall painting is sensitive to the superposition spectrum of surface substances, the requirement on the detection of the salt of the refined wall painting can be met, and the problems that the traditional detection mode of the soluble salt of the wall painting is single and secondary damage is caused to the wall painting are solved;
secondly, in the construction of standard mural sample blocks, the mass concentration of the soluble salt of the mural is selected as a salt content inversion index to have more practical significance, in the manufacturing process, a coarse mud layer is firstly manufactured, a fine mud layer is continuously manufactured on the surface of the coarse mud layer, and then the coarse mud layer is placed in a mould to be naturally dried in the shade indoors, wherein the soluble salt with the corresponding mass concentration is uniformly mixed in the fine mud layer of each standard mural sample block, so that the manufactured sample is more similar to an actual mural ground layer;
thirdly, in the data acquisition process, a Sudoku method is adopted for each standard mural sample block, a center point is firstly determined, the direction of each center point is changed to be measured four times, and the pretreatment is carried out in a combination mode of breakpoint elimination, spectrum average and SG smoothing in the data pretreatment process, so that noise generated by instrument elements, manual operation and the like in the acquisition process is effectively eliminated;
fifthly, the logarithmic transformation of reciprocal is used for enhancing the spectral characteristics, so that not only can the influence of illumination conditions and topography differences on the spectrum be reduced, but also the spectrum differences in the visible light range can be improved and compared, and the random factor error is reduced; the optimal characteristic wave band of the sodium sulfate salt is 1415nm, and a mural sample sodium sulfate content prediction model (the correlation coefficient R=0.858, the judgment coefficient R2=0.737 and the root mean square error RMSE=0.121) is established.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention.
Drawings
FIG. 1 is a flow chart of a method for detecting the content of soluble salts in a wall painting based on reflection spectrum according to one embodiment of the present invention;
FIG. 2 is a diagram showing a rule of point selection of a standard mural sample block Sudoku according to one embodiment of the present invention;
FIG. 3 is a general view of a pretreatment spectrum curve according to one embodiment of the present invention;
FIG. 4 is a logarithmic spectrum plot of the reciprocal of one embodiment of the invention;
FIG. 5 is a graph showing the reflectance of the reciprocal logarithmic spectrum in the range of 1000-1800nm according to one embodiment of the present invention;
FIG. 6 is a plot of the log spectrum of the reciprocal at 1415nm of one embodiment of the present invention;
FIG. 7 is a graph showing the reflectance of the pretreatment spectrum in the range of 500-1500nm according to one embodiment of the present invention;
FIG. 8 is a graph showing the best fit line of the pretreatment spectrum at 800nm according to one embodiment of the present invention;
FIG. 9 is a plot of the best fit line of the pretreatment spectra at 1413nm according to one embodiment of the present invention;
FIG. 10 is a graph showing envelope elimination spectra according to one embodiment of the present invention;
FIG. 11 is a graph showing the reflectance of the envelope elimination spectrum in the range of 350-600nm according to one embodiment of the present invention;
FIG. 12 is a plot of the envelope elimination spectrum at 420nm of a best fit line according to one embodiment of the invention;
FIG. 13 is a diagram showing a predicted result of a sodium sulfate content prediction model (LR) of a mural sample according to one embodiment of the present invention;
FIG. 14 is a diagram showing the predicted result of the sodium sulfate content prediction model (R-1) of the mural sample according to one embodiment of the present invention;
FIG. 15 is a diagram showing the predicted result of the sodium sulfate content prediction model (R-2) of the mural sample according to one embodiment of the present invention;
fig. 16 is a diagram showing a predicted result of a sodium sulfate content prediction model (CR) of a mural sample according to an embodiment of the present invention.
Detailed Description
The present invention is described in further detail below with reference to examples to enable those skilled in the art to practice the same by referring to the description.
Example 1 ]
As shown in fig. 1, the method for detecting the content of the soluble salt in the mural based on the reflection spectrum is characterized by comprising the following steps:
step one, manufacturing a standard mural sample block
Making a plurality of standard mural sample blocks containing soluble salts with different mass concentrations, which specifically comprises: standard mural sample block (1 block) with mass concentration of 0%, standard mural sample block (1 block) with mass concentration of 0.2%, standard mural sample block (1 block) with mass concentration of 0.3%, standard mural sample block (1 block) with mass concentration of 0.4%, standard mural sample block (1 block) with mass concentration of 0.5%, standard mural sample block (2 block) with mass concentration of 0.6%, standard mural sample block (1 block) with mass concentration of 0.8%, and standard mural sample block (1 block) with mass concentration of 1%;
wherein, each standard mural painting sample block is manufactured in a rectangular wooden mould (16 cm 11cm 1.8 cm), and the manufacturing method comprises the following steps
Making a coarse mud layer, uniformly mixing sand (coarse) with coarse loess, fully grinding, sieving coarse stone with a flax cloth, adding wheat straw and deionized water, uniformly mixing, wrapping with a preservative film for 24 hours, performing soil waking, and uniformly paving into a film;
manufacturing a fine mud layer on the surface of the coarse mud layer, and uniformly mixing soluble salt with corresponding mass concentration in the fine mud layer of each standard mural painting sample block, wherein the manufacturing of the fine mud layer specifically comprises the following steps: and (3) manually shredding the purchased ancient hemp knives to remove knotted hemp balls and unbinding hemp ropes. Mixing the fresh soil (fine) with the fine soil (fine) of the clarifying plate, adding deionized water and a soluble salt solution, uniformly mixing, wrapping the mixture for 24 hours by using a preservative film, and uniformly paving the mixture into the surface of a coarse mud layer in a film to form a fine mud layer after soil waking, wherein the clarifying plate is riverbed sedimentary soil with the grain size of 0.001-0.005 mm;
in the natural drying process, the soil detector is used for culturing and monitoring the temperature and humidity of the samples, so that the culture conditions of all standard mural sample blocks are ensured to be consistent;
step two, standard mural sample block spectrum data measurement
A spectral reflectometer is selected for measuring the spectral reflectivity of a standard mural sample block;
preheating the instrument for 30 minutes before using, performing experiments in a darkroom, firstly correcting a white board, and laying black flannelette under a standard mural sample block after stabilizing;
the standard mural sample blocks with the mass concentration of 0%, 0.2%, 0.4%, 0.6% (one block), 0.8% and 1% are respectively sampled for 4 times, and any two adjacent sampling times of the 4 times are separated by a preset time (24 hours);
sampling standard mural sample blocks with mass concentrations of 0.3%, 0.5% and 0.6% (the rest block) for 1 time respectively;
wherein, each sampling is specifically:
dividing the corresponding standard mural sample block into 3×3 blocks (as shown in fig. 2, dividing the standard mural sample block equally, and dividing the standard mural sample block into 3 rows and 3 columns), randomly selecting a center point of one block for data acquisition in each row and each column, namely selecting 3 center points for each standard mural sample block, wherein the rows and columns of the 3 center points are different from each other, and further, the data acquisition method for each center point comprises the following steps:
s1, a probe of a spectrum radiator is perpendicular to a standard mural sample block and aims at a center point to collect an initial reflection spectrum curve;
s2, horizontally rotating a probe of the spectrum radiometer by 90 degrees to acquire the next time, and acquiring another initial reflection spectrum curve;
and S3, repeating the step S2 until the probe of the spectrum radiator rotates 270 degrees horizontally, namely obtaining 4 corresponding initial reflection spectrum curves at each center point.
During acquisition, the spectrometer parameters were set as follows:
| parameter name | Specific numerical values |
| Spectral range | 350-2500nm |
| Number of channels | 2151 |
| Spectral width | 2.5nm |
| Spectral resolution | 50-1000nm@3nm；1001-2500nm@8nm |
In sum, 12 initial reflection spectrum curves are obtained by each collection of each standard mural sample block, 27 collection is carried out, and 324 initial reflection spectrum curves are obtained;
step three, preprocessing the spectrum data to obtain a preprocessed spectrum (R);
(1) performing breakpoint correction (Splice Correction) on the initial reflection spectrum curve by using View Spec Pro to obtain a breakpoint correction spectrum curve;
(2) after eliminating abnormal values caused by point edges and measurement jitter in each breakpoint correction spectrum curve, carrying out double average on the initial reflection spectrum curve collected by each standard mural painting sample block at each time to obtain an actual measurement reflection spectrum curve of the standard mural painting sample block with corresponding concentration, wherein the double average specifically comprises the following steps:
sa, taking the arithmetic average value of the breakpoint correction spectrum curve of the same center point as the spectrum curve of the center point;
sb, taking the arithmetic average value of the average spectrum curves corresponding to the same standard mural sample block;
(3) performing SG smoothing (Savitzky Golay Smoothing) on the actually measured reflection spectrum curve, wherein the size of a SG smoothing window is 21, and obtaining a reflection spectrum (pretreatment spectrum) of a standard mural sample block in the wavelength range of 350-2500 nm;
to sum up, preprocessing to obtain qualified 27 preprocessed spectra (as shown in fig. 3) for standard mural sample blocks;
step three, spectral feature enhancement
Performing LR transformation on the pretreated spectrum (taking the logarithm of the reflectance value after performing reciprocal operation) to obtain a reciprocal logarithmic spectrum (LR) (shown in FIG. 4, wherein for convenience of observation, only data obtained by sampling 4 th time of standard mural sample blocks with mass concentration of 0%, 0.2%, 0.4%, 0.6% (one block), 0.8% and 1% are shown in FIG. 3, FIG. 5, FIG. 7, FIG. 10 and FIG. 11 are the same;
step four, characteristic wave band extraction
The characteristic band range is determined based on the reciprocal logarithmic spectrum following two principles:
first, the spectrum changes drastically and shows distinct peaks and valleys, and according to fig. 4, two wave bands where the distinct peaks and valleys appear are respectively about 1415nm and 1941 nm;
secondly, selecting a band with a smooth monotonicity change of a spectrum curve in a band range, wherein the large change of the absorption valley reflectivity of a sample spectrum at 1941nm along with the salt concentration is due to the fact that the band is about 1950nm and is a water conventional absorption band, and the band does not show the smooth monotonicity change;
in summary, the characteristic band range is determined to be 1410nm-1420nm;
for the characteristic band range, after the p=0.05 pearson correlation of the reciprocal logarithmic spectrum and the sodium sulfate salt mass concentration is detected remarkably in the SPSS, the characteristic band of the reciprocal logarithmic spectrum is determined (as shown in fig. 5, the characteristic band is 1415nm, and a remarkable reflection peak appears in the 1415nm band and the fluctuation is smaller as seen by observation);
fifthly, establishing a mural sample sodium sulfate content prediction model
Taking the content concentration of soluble salt of a standard mural sample block as a dependent variable, taking a parameter value of a logarithmic spectrum of reciprocal at a characteristic wave band as an independent variable, performing linear regression to obtain a best fit line (shown in figure 6), and establishing a mural sample sodium sulfate content prediction model (LR);
mural sample sodium sulfate content prediction model (LR): y= -3.3906R 1415nm +2.9633
Wherein Y is the sodium sulfate content (mass concentration) of the sample, R 1415nm A post-log value of the reciprocal of the spectral reflectance at 1415nm;
step six: acquiring a punctiform spectrum curve of a specified position of the wall painting to be detected by utilizing a spectrum radiator;
and carrying out reciprocal logarithmic transformation after pretreatment, obtaining characteristic spectrum parameters at a characteristic wave band, and then carrying into a mural sample sodium sulfate content prediction model to predict the mass concentration of sodium sulfate.
Comparative example 1 ]
The method for detecting the content of the soluble salt in the mural based on the reflection spectrum is characterized by comprising the following steps of:
step one, manufacturing a standard mural sample block, which is the same as the step one of the embodiment 1;
step two, preprocessing spectrum data, and obtaining a preprocessed spectrum curve in the same way as in step two of the embodiment 2;
step three, preprocessing spectrum without spectral feature enhancement;
step four, characteristic wave band extraction
Based on the pre-processed spectrum (fig. 3), the characteristic bands are determined following two principles:
first, the spectrum changes drastically and exhibits an inflection point at a distinct peak-valley, and as can be seen from fig. 7, absorption valleys appear significantly at 367nm, 1413nm, 1941nm, 2211nm bands;
secondly, selecting a band in which a spectrum curve is in stable monotonicity change within a band range, wherein the band has larger noise influence at 367nm at an edge band, and the larger change of the absorption valley reflectivity along with the salt concentration at 1941nm is due to the fact that about 1950nm is a water conventional absorption band, the peak valley is frequently replaced at 2211nm, the signal to noise ratio is overlarge, namely, the 3 bands do not show stable monotonicity change;
in summary, the characteristic band range is determined to be 1410nm-1420nm;
further, as shown by observing the spectrum curve, in the wave band of 350nm-1400nm, the spectrum reflectivity is in an ascending trend, wherein the slope of 600-800nm is fastest in growth, the reflectivity at 800nm is good in potential increase, no obvious rate difference exists between the acceleration stability and the main of different salt concentrations, the slope growth speed is gradually decreased, and the characteristic wave band range is determined to be 795-805 nm for comparing the fitting effects of different wave bands under the same model;
for the characteristic wave band range, after the p=0.05 pearson correlation between the pretreatment spectrum and the salt concentration is obviously detected in the SPSS, the characteristic wave band of the logarithmic spectrum of the reciprocal is determined (as shown in fig. 7, the characteristic wave bands are respectively 800nm and 1413nm, as can be seen, obvious absorption valleys appear at the 1413nm wave band, the reflectivity at the 800nm has obvious increase potential and has a monotonic relation with positive correlation with the increase of the salt content, and the interval between graduation levels is relatively uniform);
fifthly, establishing a mural sample sodium sulfate content prediction model
Taking the soluble salt content concentration of a standard mural sample block as a dependent variable, taking a parameter value of a pretreatment spectrum at a characteristic wave band as an independent variable, performing linear regression to obtain a best fit line (shown in figures 8 and 9), and establishing a mural sample sodium sulfate content prediction model, wherein the mural sample sodium sulfate content prediction model (R-1) is established for the characteristic wave band 800nm, and the mural sample sodium sulfate content prediction model (R-2) is established for the characteristic wave band 1413nm;
mural sample sodium sulfate content prediction model (R-1): y= 5.4263R 800nm -1.8904
Wherein Y is the sodium sulfate content of the sample, R 800nm Spectral reflectance at 800 nm;
mural sample sodium sulfate content prediction model (R-2): y= 6.7574R 1413nm -2.7787
Wherein Y is the sodium sulfate content of the sample, R 1413nm Is 1413nm spectral reflectance.
Comparative example 2 ]
The method for detecting the content of the soluble salt in the mural based on the reflection spectrum is characterized by comprising the following steps of:
step one, manufacturing a standard mural sample block, which is the same as the step one of the embodiment 1;
step two, preprocessing spectrum data, which is the same as step two in embodiment 2;
step three, spectral feature enhancement
Envelope removal (normalization of spectral reflectance) is performed on the pre-processed spectrum to obtain an envelope removed spectrum (CR), as shown in fig. 10;
step four, characteristic wave band extraction
Based on the envelope removal spectrum, the characteristic band range is determined following two principles:
first, the spectrum changes drastically and exhibits inflection points at distinct peaks and valleys, and according to fig. 10, absorption valleys appear clearly in the wavelength bands of 420nm, 1413nm, 1941nm, 2211nm, respectively, where the distinct peaks and valleys appear;
secondly, selecting a wave band with a smooth monotonicity change of a spectrum curve in a range of wave bands, wherein the smooth monotonicity change is not shown in 1413nm, 1941nm and 2211 nm;
in summary, the characteristic band range is determined to be 415nm-425nm;
for this characteristic band range, after p=0.05 pearson correlation between the pretreated spectrum and the salt concentration is detected significantly in the SPSS, the characteristic band of the logarithmic spectrum of the reciprocal is determined (as shown in fig. 11, the characteristic bands are 420nm, and as can be seen from observation, characteristic absorption valleys with strong correlation appear at the 420nm band, which are shaped like sharp ridges);
fifthly, establishing a mural sample sodium sulfate content prediction model
Taking the content concentration of soluble salt of a standard mural sample block as a dependent variable, taking a parameter value of an envelope removal spectrum at a characteristic wave band as an independent variable, performing linear regression to obtain a best fit line (shown in figure 12), and establishing a mural sample sodium sulfate content prediction model (CR);
mural sample sodium sulfate content prediction model (CR): y= -4.521R 420nm +1.3737
Wherein Y is the sodium sulfate content of the sample, R 420nm Spectral reflectance valley depth after envelope removal at 420 nm.
1. Preparation of standard wall painting sample block
In the construction of standard mural sample blocks, the mass concentration of the soluble salt of the mural is selected as a salt content inversion index, so that the method has practical significance, in the manufacturing process, a coarse mud layer is firstly manufactured, a fine mud layer is continuously manufactured on the surface of the coarse mud layer, and then the coarse mud layer is placed in a mould to be naturally dried in the shade indoors, wherein the soluble salt with the corresponding mass concentration is uniformly mixed in the fine mud layer of each standard mural sample block, and the sample manufacturing quality is improved.
2. With respect to spectral data acquisition and preprocessing
And a Sudoku method is adopted for each standard mural sample block, a center point is firstly determined, the direction of each center point is changed for four times, and the pretreatment is carried out in a combination mode of breakpoint elimination, spectrum average and SG smoothing in the data pretreatment process, so that the obtained spectrum curve effectively eliminates noise generated by instrument elements, manual operation and other reasons in the acquisition process, and the spectrum curve changes regularly along with the salt concentration, thereby strengthening the peak-valley band characteristics.
3. Enhancement of spectral features
3.1, analysis of the pretreated spectral curve (FIG. 2):
the reflectivity of the mural sample and the salt content are in a positive correlation trend integrally, the spectral reflectivity of the mural sample is in a gradual increase trend along with the increase of the salt concentration of the sample block, wherein the reflectivity of 1% and 0.8% of the salt content is obviously higher than that of the other groups, a generation-breaking interval is transversely formed, and the preliminary analysis is caused by white frost salt spots formed on the surface of the mural sample.
Absorption valleys appear obviously at 367nm, 1413nm, 1941nm and 2211nm wave bands, reflection peaks appear obviously at 2136nm, and the maximum value of the reflection rate is 0.5821, wherein the absorption valley reflection rate of the sample spectrum at 1941nm greatly changes along with the salt concentration due to the fact that about 1950nm is a water conventional absorption wave band.
In the wave band of 350nm-1400nm, the spectral reflectivity is in an ascending trend, wherein the slope of 600-800nm is the fastest, the reflectivity at 800nm is well boosted, the speed-up stability and the main difference of different salt concentrations do not have obvious speed-up difference, and then the slope increasing speed is gradually decreased. The regular steepness ridge appears around 1400nm, and the fluctuation of the reflectivity is larger in the interval from the beginning to 2500 nm.
3.2, 3 spectral curves, i.e. pretreatment spectrum (R), envelope removal spectrum (CR), log-to-reciprocal spectrum (LR), were compared to see:
after visible light and near infrared are subjected to spectrum enhancement, reflection characteristics are amplified, hidden detail characteristics are highlighted, peaks and valleys of the spectrum are more prominent, the occurrence times of the peaks and valleys are more frequent, and the influence of different concentration salt contents on the spectral reflectivity of the surface of a wall painting sample is more finely quantized; the application of LR transformation can not only reduce the influence of illumination conditions and topography differences on the spectrum, but also improve and compare the spectrum differences in the visible light range and reduce random factor errors; envelope removal forms more absorption valleys by normalizing the spectral reflectance, thereby enhancing the correlation of spectral features with different concentrations of salt content, enabling a more visual representation.
4. Precision evaluation of predictive model
4.1, manufacturing a verification set of mural sample blocks, specifically comprising a verification mural sample block (1 block) with a mass concentration of 0.1%, a verification mural sample block (1 block) with a mass concentration of 0.2%, a verification mural sample block (1 block) with a mass concentration of 0.3%, a verification mural sample block (1 block) with a mass concentration of 0.5%, a verification mural sample block (1 block) with a mass concentration of 0.7%, and a verification mural sample block (1 block) with a mass concentration of 0.9%, wherein the manufacturing method is the same as that of example 1;
sampling the verification sample block at least 1 time, wherein the sampling method is the same as that of the embodiment 1;
preprocessing the sampled data to obtain a preprocessed spectrum for verifying that the mural sample block is in a wavelength range of 350-2500nm, wherein the preprocessing method is the same as that of the embodiment 1;
performing reciprocal logarithmic transformation on the preprocessed spectrum to obtain a reciprocal logarithmic spectrum, and performing envelope removal on the preprocessed spectrum to obtain an envelope removal spectrum;
for the pretreatment spectra of the validation set, the characteristic bands were determined to be 800nm, 1413nm;
for the log spectrum of the reciprocal of the validation set, the characteristic band was determined to be 1415nm;
determining the characteristic wave band as 420nm for the envelope removal spectrum of the verification group;
for the verification group, taking the content concentration of the soluble salt of the verification mural sample block as a dependent variable, taking a parameter value of a corresponding spectrum at a characteristic wave band as an independent variable, performing linear regression to obtain a best fit line (shown in fig. 12), and establishing a mural sample sodium sulfate content inversion verification equation;
selecting Goodness-of-fit statistics (Goodness-of-fit stat)Istic) performs accuracy analysis on the built model, and calculates and compares the decision coefficients (R) of the modeling set and the validation set, respectively 2 ) Root Mean Square Error (RMSE) and relative analysis error (RPD) to evaluate modeling quality, where R 2 For determining the model fitting effect, RMSE is used to determine the prediction capability of the model, and RPD can reduce the influence of the differences of the predicted sample attribute values in different studies to some extent, and measure the reliability of the model, and the result is shown in table 2 below:
table 2 accuracy analysis data
The four mural sample sodium sulfate content prediction models are opposite to the prediction results of the building module and the verification group, and are shown in fig. 13-16, and the comprehensive figures 13-16 and the table 2 rank the capabilities of the spectrum enhancement models at different features in the aspect of estimating the sodium sulfate content of the mural sample from strong to weak: the method comprises the steps of sequentially performing envelope removal spectrum > pretreatment spectrum (1413 nm) > pretreatment spectrum (800 nm) > envelope removal spectrum, wherein fitting effects of different wave bands under the same model are compared at the wave bands of 800nm and 1413nm, and modeling result differences of different models at the same wave band are compared at about 1414 nm.
Although embodiments of the present invention have been disclosed above, it is not limited to the details and embodiments shown and described, it is well suited to various fields of use for which the invention would be readily apparent to those skilled in the art, and accordingly, the invention is not limited to the specific details and illustrations shown and described herein, without departing from the general concepts defined in the claims and their equivalents.
Claims (6)
1. The method for detecting the content of the soluble salt in the mural based on the reflection spectrum is characterized by comprising the following steps of:
manufacturing a plurality of standard mural sample blocks containing soluble salts with different mass concentrations;
at least 1 sampling each standard mural sample block by utilizing a spectrum radiometer at intervals of preset time, wherein a pretreatment spectrum of the standard mural sample block in a wavelength range of 350-2500nm is obtained by pretreatment after each sampling;
performing reciprocal logarithmic transformation on the preprocessed spectrum to obtain a reciprocal logarithmic spectrum;
extracting a characteristic wave band according to the logarithmic spectrum of the reciprocal;
taking the mass concentration of the soluble salt of the standard mural sample block as a dependent variable, taking a parameter value of the logarithmic spectrum of the reciprocal at a characteristic wave band as an independent variable, carrying out linear regression to obtain a best fit line, and establishing a mural sample soluble salt content prediction model;
obtaining a punctiform spectrum curve of a specified position of a wall painting to be detected by utilizing a spectrum radiometer, preprocessing, carrying out reciprocal logarithmic transformation, obtaining characteristic spectrum parameters at a characteristic wave band, and then carrying into a soluble salt content prediction model of a wall painting sample to predict the mass concentration of the soluble salt;
wherein, each sampling is specifically:
dividing each standard mural sample block into 3×3 blocks, randomly selecting a center point of each block for data acquisition in each row and each column, wherein the method for data acquisition of each center point comprises the following steps:
s1, a probe of a spectrum radiator is perpendicular to a standard mural painting sample block and aims at a central point to collect an initial reflection spectrum curve within a wavelength range of 350-2500 nm;
s2, horizontally rotating a probe of the spectrum radiometer by 90 degrees to acquire the next time;
s3, repeating the step S2 until the probe of the spectrum radiator horizontally rotates 270 degrees;
the pretreatment after each sampling comprises the following steps:
sa, taking the arithmetic average value of the breakpoint correction spectrum curve of the same center point as the spectrum curve of the center point;
sb, taking the arithmetic average value of the average spectrum curves corresponding to the same standard mural sample block;
the preprocessing after each sampling further comprises breakpoint correction of the initial reflection spectrum curve before the step Sa is carried out, so that a breakpoint correction spectrum curve is obtained;
after the step Sb is carried out, carrying out Savitzky-Golay smoothing treatment on the spectrum curve collected by the standard mural sample block each time to obtain a reflection spectrum of the standard mural sample block in the wavelength range of 350-2500 nm;
the method for manufacturing the standard mural sample block comprises the following steps:
manufacturing a coarse mud layer;
and manufacturing a fine mud layer on the surface of the coarse mud layer, and naturally drying in the shade to obtain a plurality of standard mural sample blocks, wherein soluble salt with corresponding mass concentration is uniformly mixed in the fine mud layer of each standard mural sample block.
2. The method for detecting the content of soluble salts in a wall painting based on a reflection spectrum according to claim 1, wherein the mass concentration range of the soluble salts formed by a plurality of standard wall painting sample blocks is 0-1%, wherein the mass concentrations of the soluble salts contained in the standard wall painting sample blocks are arranged from small to large, and the mass concentration difference of the standard wall painting sample blocks with adjacent mass concentrations is not more than 0.2%.
3. The method for detecting the content of the soluble salt in the wall painting based on the reflection spectrum according to claim 2, wherein the mass concentration of the soluble salt in the standard wall painting sample block is arranged from small to large, and the mass concentration differences of any two adjacent standard wall painting sample blocks with mass concentrations are equal.
4. The method for detecting the content of soluble salts in wall paintings based on reflection spectrum according to claim 2, wherein the soluble salts are one of sulfate, nitrate and chloride.
5. The method for detecting the content of soluble salt in a wall painting based on reflection spectrum as claimed in claim 4, wherein the soluble salt is sodium sulfate.
6. The method for detecting the content of soluble salts in wall paintings based on reflection spectrum according to claim 1, wherein the method for extracting characteristic bands according to the logarithmic spectrum of reciprocal comprises the steps of:
selecting a wave band range in which the spectrum shows obvious peaks and valleys and the spectrum curve shows stable monotonicity change;
for a determined band range, after significant p=0.05 pearson correlation of the pre-processed spectrum with salt concentration, the characteristic band of the reciprocal logarithmic spectrum is determined.
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