Cultural relic age determination method and system

Abstract

The invention provides a cultural relic age determination method and system, and relates to the technical field of cultural relic age determination, the method comprises the following steps: collecting a sample from a to-be-tested cultural relic, and cleaning, drying and crushing the sample to obtain a treated sample; performing elemental composition analysis on the sample through an energy dispersion X-ray fluorescence spectrophotometer to obtain the types and content ratios of main elements and trace elements in the sample; collecting similar cultural relic samples of known years, performing elemental composition analysis, and establishing a standard sample ratio of the known years; comparing the ratio of the types and contents of the main elements and the trace elements in the sample with the ratio of a standard sample of a known age, and fitting a calibration curve through a least square method according to a comparison data set; and optimizing the calibration curve, and calculating an absolute age estimation value of the cultural relic according to the optimized calibration curve. According to the method, interference of single element variation is reduced through multi-element correlation analysis, and historical relic age determination is carried out.

Description

Technical Field

[0001] The present invention relates to the technical field of cultural relic dating, and particularly to a method and system for dating cultural relics. Background Art

[0002] In the field of cultural relic protection and archaeological research, accurately determining the age of cultural relics is of crucial importance. However, traditional methods for dating cultural relics often have many limitations and are difficult to meet the needs of modern scientific research.

[0003] Traditional methods for dating cultural relics mainly include carbon-14 dating, thermoluminescence dating, dendrochronology, etc. However, these methods have the following limitations: the carbon-14 method is only applicable to carbon-containing organic materials and has higher accuracy for cultural relics with relatively recent ages (<50,000 years); the thermoluminescence method requires sampling and heating, which damages the cultural relics; the dendrochronology method relies on specific wooden cultural relics and has a narrow scope of application. In addition, the above methods are difficult to directly apply to the age determination of inorganic material cultural relics. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method and system for dating cultural relics, which reduces the interference of single-element variation through multi-element correlation analysis for cultural relic dating.

[0005] To solve the above technical problem, the technical solution of the present invention is as follows:

[0006] In a first aspect, a method for dating cultural relics, the method comprising:

[0007] Collect samples from the cultural relics to be tested, and clean, dry and crush the samples to obtain processed samples;

[0008] Perform elemental composition analysis on the samples by an energy dispersive X-ray fluorescence spectrometer to obtain the types and content ratios of the main elements and trace elements in the samples;

[0009] Collect samples of the same type of cultural relics with known ages, perform elemental composition analysis, and establish a standard sample ratio for known ages;

[0010] Compare the types and content ratios of the main elements and trace elements in the samples with the standard sample ratio for known ages, and fit a calibration curve by the least squares method according to the comparison data set;

[0011] Optimize the calibration curve, and calculate the absolute age estimate value of the cultural relics according to the optimized calibration curve;

[0012] Perform outlier detection on the cultural relic age to obtain a detection value;

[0013] Fuse the detected values with the absolute age estimates and quantify the uncertainty of the fusion results to achieve the determination of the age of cultural relics.

[0014] Further, analyze the elemental composition of the sample by an energy-dispersive X-ray fluorescence spectrometer to obtain the types and content ratios of the major and trace elements in the sample, including:

[0015] Detect the elements of the sample by an energy-dispersive X-ray fluorescence spectrometer to obtain the X-ray fluorescence spectrum;

[0016] Identify the element types through the characteristic peak positions of the X-ray fluorescence spectrum and record the characteristic peak intensities of each element;

[0017] According to the element types, convert the characteristic peak intensities corresponding to the element types into element contents and calculate the ratios of the major and trace elements.

[0018] Further, collect samples of the same type of cultural relics with known ages, conduct elemental composition analysis, and establish the standard sample ratios of known ages, including:

[0019] Collect samples of the same type of cultural relics with known ages, conduct elemental composition analysis, and calculate the ratios of the major and trace elements in each sample;

[0020] Fit the elemental ratios and age data by statistical methods to establish the standard sample ratios.

[0021] Further, compare the types and content ratios of the major and trace elements in the sample with the standard sample ratios of known ages, and based on the comparison data set, fit the calibration curve by the least squares method, including:

[0022] Compare the types and content ratios of the major and trace elements in the sample with the standard sample ratios of known ages to obtain the elemental ratios in each standard sample;

[0023] According to the decay of the major and trace elements following the exponential law, construct an exponential calibration curve model;

[0024] According to the exponential calibration curve model, determine that the objective function is to calculate the sum of the squares of the differences between the actual measured values and the model predicted values of the elemental ratios of each data point, that is, each standard sample, and obtain the parameters a and b with the minimum error function through the least squares method;

[0025] With the obtained parameters a and b, obtain the calibration curve.

[0026] Further, optimize the calibration curve and calculate the absolute age estimate of the cultural relic according to the optimized calibration curve, including:

[0027] Obtain the error of the calibration curve;

[0028] Update the parameters a and b of the calibration curve by multiplying the partial derivative vector by the inverse of the approximate Hessian matrix to obtain the optimized calibration curve;

[0029] According to the optimized calibration curve, substitute the isotope ratio into the optimized calibration curve equation to obtain the absolute age estimate.

[0030] Furthermore, perform outlier detection on the ages of cultural relics to obtain the detection values, including:

[0031] Calculate the mean μ and standard deviation σ of the cultural relic age dataset. For the age value x of each cultural relic i , if ∣x i -μ∣>3σ, then mark this cultural relic as a preliminary outlier to obtain the detection value.

[0032] Furthermore, fuse the detection value with the absolute age estimate and quantify the uncertainty of the fusion result to achieve the determination of the age of cultural relics, including:

[0033] Perform weighted fusion of the detection value and the absolute age estimate to obtain the fused data;

[0034] Through Bootstrap resampling, obtain the confidence interval of the fused data, and obtain the standard deviation of the fused data through the variances and weights of each data source during the fusion process;

[0035] Quantify the uncertainty of the fusion result through the confidence interval and the standard deviation;

[0036] Adjust the age of the cultural relic according to the uncertainty of the fusion result to achieve the determination of the age of the cultural relic.

[0037] In a second aspect, a cultural relic age determination system includes:

[0038] An acquisition module for collecting samples from the cultural relics to be measured, and cleaning, drying, and pulverizing the samples to obtain the processed samples;

[0039] An optimization module analyzes the elemental composition of the samples through an energy dispersive X-ray fluorescence spectrometer to obtain the types and content ratios of the main elements and trace elements in the samples; collects samples of the same type of cultural relics with known ages, conducts elemental composition analysis, and establishes the standard sample ratios of known ages; compares the types and content ratios of the main elements and trace elements in the samples with the standard sample ratios of known ages, and based on the comparison dataset, fits the calibration curve by the least squares method; optimizes the calibration curve, and calculates the absolute age estimate of the cultural relics according to the optimized calibration curve;

[0040] A processing module for detecting outliers in the age of cultural relics to obtain detection values; fusing the detection values with the absolute age estimation values and quantifying the uncertainty of the fusion results to achieve the determination of the age of cultural relics.

[0041] In a third aspect, a computing device includes:

[0042] One or more processors;

[0043] A storage device for storing one or more programs, which when executed by the one or more processors cause the one or more processors to implement the described method.

[0044] In a fourth aspect, a computer-readable storage medium stores a program that, when executed by a processor, implements the described method.

[0045] The above solutions of the present invention have at least the following beneficial effects:

[0046] By collecting trace samples through a micro drill or laser ablation technology and combining with the non-destructive detection of EDXRF, the damage to the main body of the cultural relics is significantly reduced, especially suitable for precious cultural relics or scenarios where non-repeatable sampling is not possible. By detecting ppm-level trace elements and combining with the major element data, through multi-element comprehensive correlation analysis, the error caused by environmental or process fluctuations of a single element is reduced, and the reliability of age determination is improved. The full process from sample processing to age determination is standardized, reducing manual intervention and supporting rapid analysis of batch samples; the detection results can be repeatedly verified, providing an objective and quantitative scientific basis for cultural relic identification.

[0047] Through the elemental analysis of a large number of samples with known ages, the corresponding relationship between age and elemental ratio is established. The elemental compositions of the same type of cultural relics are similar, and the ratio of the standard sample can eliminate the influence of matrix differences on the dating results. The calibration curve establishes a mathematical relationship between the elemental ratio and the age, realizing the conversion from elemental data to age values. The least squares method optimizes the fitting parameters, reduces the deviation of data points, and improves the accuracy of age prediction. By optimizing the algorithm to adjust the curve parameters, the error caused by instrument drift or matrix effect is eliminated. By using statistical methods to detect outliers in the age estimation values, special cultural relics or analysis errors are revealed. By fusing the outlier detection results with the absolute age estimation values, the effective information in the data is fully utilized, and the comprehensiveness of age determination is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 is a schematic flowchart of a method for determining the age of cultural relics provided by an embodiment of the present invention.

[0049] Figure 2 is a schematic diagram of a system for determining the age of cultural relics provided by an embodiment of the present invention. Detailed Implementation Manner

[0050] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be completely conveyed to those skilled in the art.

[0051] As Figure 1 shown, an embodiment of the present invention provides a method for determining the age of cultural relics, and the method includes the following steps:

[0052] Step 11: Collect samples from the cultural relics to be tested, and clean, dry, and pulverize the samples to obtain processed samples;

[0053] Step 12: Analyze the elemental composition of the samples by an energy dispersive X-ray fluorescence spectrometer to obtain the types and content ratios of the main elements and trace elements in the samples;

[0054] Step 13: Collect samples of the same type of cultural relics with known ages, conduct elemental composition analysis, and establish standard sample ratios for known ages;

[0055] Step 14: Compare the types and content ratios of the main elements and trace elements in the samples with the standard sample ratios of known ages, and fit a calibration curve by the least squares method according to the comparison data set;

[0056] Step 15: Optimize the calibration curve, and calculate the absolute age estimate value of the cultural relics according to the optimized calibration curve;

[0057] Step 16: Detect outliers in the age of the cultural relics to obtain detection values;

[0058] Step 17: Integrate the detection values with the absolute age estimate values, and quantify the uncertainty of the integration result to achieve the determination of the age of cultural relics.

[0059] In the embodiments of the present invention, surface contaminants are removed through cleaning, moisture interference is avoided through drying, the sample is homogenized through pulverization, and a non-destructive sampling method is adopted to minimize damage to cultural relics, which conforms to the principle of cultural relic protection. The ED-XRF technology requires no chemical reagents, has a fast analysis speed, causes no damage to the sample, is suitable for cultural relic research, can detect multiple elements simultaneously, and provides comprehensive elemental composition information. Through the elemental analysis of a large number of samples with known ages, the corresponding relationship between age and elemental ratio is established. The elemental compositions of the same type of cultural relics are similar, and the standard sample ratio can eliminate the influence of matrix differences on the dating results. The calibration curve establishes a mathematical relationship between the elemental ratio and the age, realizing the conversion from elemental data to age values. The least squares method optimizes the fitting parameters, reduces the deviation of data points, and improves the accuracy of age prediction. The curve parameters are adjusted through an optimized algorithm to eliminate the errors caused by instrument drift or matrix effects. The abnormal points in the age estimation values are detected through statistical methods to reveal special cultural relics or analysis errors. The detection results of abnormal values are fused with the absolute age estimation values to make full use of the effective information in the data and improve the comprehensiveness of age determination.

[0060] In a preferred embodiment of the present invention, step 11 may include: collecting a trace sample through a micro drill or laser ablation technology, and cleaning, drying, and pulverizing the sample to obtain a processed sample.

[0061] In a preferred embodiment of the present invention, step 12 may include:

[0062] Step 121, detecting the elements of the sample through an energy dispersive X-ray fluorescence spectrometer to obtain an X-ray fluorescence spectrum;

[0063] Step 122, identifying the element types through the characteristic peak positions of the X-ray fluorescence spectrum and recording the characteristic peak intensities of each element;

[0064] Step 123, according to the element types, converting the characteristic peak intensities corresponding to the element types into element contents, and calculating the ratios of the major elements and trace elements.

[0065] In the embodiments of the present invention, the energy dispersive X-ray fluorescence spectrometer does not require chemical treatment of the sample and can directly analyze solid samples, avoiding the destruction of the sample by traditional chemical analysis methods. It can detect multiple elements simultaneously in one measurement, greatly improving the analysis efficiency and enabling rapid acquisition of preliminary information on various elements in the sample. The positions of the X-ray fluorescence characteristic peaks of different elements are unique. By accurately measuring the positions of the characteristic peaks, the types of elements present in the sample can be accurately identified, providing a basis for subsequent elemental quantitative analysis. Recording the intensities of the characteristic peaks of each element can intuitively reflect the relative content levels of different elements in the sample, providing data support for further content calculation. By converting the characteristic peak intensities into element contents, accurate determination of the element contents in the sample is achieved, enabling accurate understanding of the specific contents of various elements in cultural relics and calculation of the ratios of major elements and trace elements, which helps to deeply understand the chemical composition characteristics of cultural relics. For example, the proportional relationships between different elements may be closely related to the manufacturing process and raw material formula of cultural relics.

[0066] In the embodiments of the present invention, the specific steps include:

[0067] Step 121: Turn on the energy dispersive X-ray fluorescence spectrometer, place the sample in the instrument sample chamber, emit a high-energy electron beam from the X-ray tube to bombard the surface of the sample. The electrical signals output by the detector are amplified and digitally processed and then transmitted to the computer. The computer draws an X-ray fluorescence spectrum based on the relationship between the signal intensity and wavelength, with the X-ray energy on the abscissa and the signal intensity on the ordinate.

[0068] Step 122: According to the correspondence between the energy of X-ray fluorescence and the types of elements, such as characteristic lines like Kα, Kβ, Lα, etc., identify the elements corresponding to each peak in the spectrum. For example, the Lα peak of lead is located at 10.55 keV, and the Kα peak of iron is located at 6.40 keV. Through spectral analysis software, measure the intensities of each characteristic peak. The peak intensity reflects the strength of the X-ray fluorescence signal generated by the element in the sample.

[0069] Step 123: Use a series of standard samples with known element contents, measure their characteristic peak intensities through ED-XRF, establish a regression calibration curve between the element content and the characteristic peak intensity, substitute the characteristic peak intensities of the sample to be measured into the calibration curve, and calculate the contents of each element. And calculate the ratios between the contents of major elements and trace elements, such as K / Ca, Fe / Si, Pb / Cu.

[0070] In a preferred embodiment of the present invention, the above step 13 may include:

[0071] Step 131: Collect samples of the same type of cultural relics with known ages, conduct elemental composition analysis, and calculate the ratios of major elements and trace elements in each sample;

[0072] Step 132: Fit the element ratio and chronological data through statistical methods to establish a standard sample ratio.

[0073] In an embodiment of the present invention, by collecting samples of the same type of cultural relics with known ages, a reliable database of the corresponding relationship between age and element composition is established. Element composition analysis can reveal the contents and ratios of the main elements and trace elements in cultural relics. These ratios may be closely related to the production age, craftsmanship, raw material sources, etc. of cultural relics. Through statistical fitting methods, a mathematical model between the element ratio and age can be established, converting the element ratio into specific age information to achieve quantitative inference of the age of cultural relics. The establishment of the standard sample ratio can eliminate the influence of factors such as sample individual differences and measurement errors on age inference, improving the accuracy and precision of age inference.

[0074] In an embodiment of the present invention, the specific steps include:

[0075] Step 131: By collecting samples of the same type of cultural relics with known ages, a reliable database of the corresponding relationship between age and element composition is established. Element composition analysis is carried out through an energy dispersive X-ray fluorescence spectrometer to reveal the contents and ratios of the main elements and trace elements in cultural relics.

[0076] Step 132: Plot a scatter diagram of the element ratio and age, observe whether there is a trend relationship, and according to the distribution characteristics of the scatter diagram, select a time series analysis statistical model for fitting. Use the least squares method or other optimization algorithms to fit the element ratio and chronological data, and calculate the goodness-of-fit index R 2 value. The closer the R 2 value is to 1, the better the model fitting effect. For example, if R 2 = 0.85, it indicates that the model can explain 85% of the element ratio variation. Substitute the fitted model parameters into the statistical model to obtain the standard sample ratio curve of the element ratio and age.

[0077] In a preferred embodiment of the present invention, the above step 14 may include:

[0078] Step 141: Compare the types and content ratios of the main elements and trace elements in the sample with the standard sample ratios of known ages to obtain the element ratios in each standard sample;

[0079] Step 142: Construct an exponential calibration curve model according to the fact that the decay of elements follows an exponential law;

[0080] Step 143: According to the exponential calibration curve model, determine the objective function as and obtain the parameters a and b with the minimum error function through the least squares method, where y iis the ratio of the major and trace elements actually measured, is the predicted value according to the model, and a and b are model parameters;

[0081] Step 144: Obtain the calibration curve using the obtained parameters a and b.

[0082] In the embodiments of the present invention, standard samples with known exact ages are collected. These standard samples are like precise "time scales". By comparing with them, the relationship between the element ratio in the sample to be measured and the known age can be clearly understood. Comparing the isotope ratio of the sample to be measured with the ratio of the standard sample makes the data between different samples comparable. During the comparison process, the potential law of the change of the element ratio with age can be observed. As time goes by, the content of the element will gradually decrease. Through the comparison of a large number of standard samples, this change law can be understood more intuitively, which helps to understand more deeply the relationship between element decay and age. Constructing an exponential calibration curve model can scientifically describe the decay process of elements. The decay of elements is exponential, and this model can accurately reflect the change law of element content over time. Through this model, the theoretical ratio of elements in samples of different ages can be predicted. Obtaining the parameters with the minimum error function by the least squares method can improve the accuracy of the calibration curve and enhance the stability of the calibration curve model. During the data processing process, there may be some outliers or noise interferences. The least squares method can suppress these interferences to a certain extent, making the model insensitive to data fluctuations. The calibration curve can maintain good performance under different data sets and measurement conditions, improving the reliability and practicality of the model.

[0083] In the embodiments of the present invention, the specific steps include:

[0084] Step 141: Define the types, age ranges, quantities, etc. of the standard samples to be collected. For example, it is planned to collect cultural relic samples from archaeological sites of different historical periods and obtain wood samples from trees with accurate growth age records to ensure that the samples have broad age representativeness; collect samples according to the plan. During the collection process, details such as the source, collection location, collection time, and known exact age of each sample are recorded; use an accelerator mass spectrometer to accurately measure the ratio of the major and trace elements of each standard sample. After the measurement is completed, compare and analyze the measurement results of each sample with the standard ratio corresponding to the known age, calculate the actual ratio of the elements in each standard sample, and organize them into a data table.

[0085] Step 142: Analyze the decay mechanism of the element, clarify that it follows the exponential decay law, and determine the basic form of the exponential calibration curve model according to the exponential decay law. Generally speaking, the model can be expressed as an exponential function relationship between the element ratio and the age. According to the actual situation, make appropriate adjustments and deformations to the model. For example, consider the influence of environmental factors on decay, introduce a correction coefficient, and make the model more in line with the actual situation.

[0086] Step 143: According to the exponential calibration curve model, determine the objective function as the error function. The core goal is to find suitable model parameters. By continuously adjusting the values of these two parameters, make the error function E reach the minimum value. When the error function E is the smallest, it means that the difference between the model prediction value and the ratio of the main elements and trace elements measured actually is the smallest, that is, the fitting effect of the model on the actual data is the best. In this way, a set of optimal model parameters can be determined. According to the principle of the least squares method, that is, by continuously adjusting the model parameters to make the error function reach the minimum; adopt an iterative method, such as the gradient descent method, to gradually approach the optimal parameter value. In each iteration, calculate the gradient of the error function with respect to the parameter, and adjust the parameter value according to the gradient direction. For example, if the partial derivative of the error function with respect to a certain parameter is positive, it means that increasing the value of this parameter will make the error function decrease, and vice versa, decrease the value of this parameter. Continuously repeat this process until the error function converges to the minimum value to obtain the optimal parameters.

[0087] Step 144: Substitute the optimal parameters obtained in Step 143 into the exponential calibration curve model to obtain the specific calibration curve equation; according to the calibration curve equation, select a suitable age range and element ratio range, and use a drawing tool to draw the calibration curve; substitute the standard sample data collected in Step 141 into the calibration curve again to verify the accuracy of the curve.

[0088] In a preferred embodiment of the present invention, the above Step 15 may include:

[0089] Step 151: Obtain the error of the calibration curve.

[0090] Step 152: Through Update the parameters a and b of the calibration curve to obtain an optimized calibration curve, where a k and b k are the parameter values of the k-th iteration, is the approximate Hessian matrix at the k-th iteration;

[0091] Step 153: According to the optimized calibration curve, substitute the isotope ratio into the optimized calibration curve equation to obtain the absolute age estimate value.

[0092] In the embodiments of the present invention, the error function quantitatively measures the difference between the ratio of the major and trace elements measured actually and the predicted value of the calibration curve. By obtaining the error function, researchers can clearly understand the fitting degree of the current calibration curve to the actual data. The error function provides a clear goal and direction for the optimization of the calibration curve. Using an iterative method to update the parameters of the calibration curve and combining with an approximate Hessian matrix for optimization can make the calibration curve fit the actual data more accurately. Through multiple iterations, the parameters of the calibration curve gradually approach the optimal values, thereby improving the accuracy of the calibration curve. The optimized calibration curve not only performs well at the known data points, but also has strong predictive ability for the ratio data of unknown major and trace elements, and can be applied to a wider range of samples, providing accurate age estimates for samples from different sources and different ages, and enhancing the generalization ability of the model. Different geological and environmental conditions may cause changes in the distribution characteristics of the ratio of major and trace elements. By optimizing the calibration curve, it can better adapt to these changes, thereby improving the reliability of age estimation. The optimized calibration curve can accurately convert the measured ratio of major and trace elements into an absolute age estimate value, which can help scientists determine the formation ages of cultural relics, fossils, etc., reconstruct the historical and cultural development context of ancient humans, and understand the geological evolution process.

[0093] In the embodiments of the present invention, the specific steps include:

[0094] Step 151, collect a set of known ratio data of major and trace elements and their corresponding actual absolute ages, and record the relevant conditions (such as sample source, measurement environment, etc.) when measuring these isotope ratios. According to the collected data, calculate the error between the ratio of the major and trace elements measured actually and the predicted value of the calibration curve.

[0095] Step 152, initialize the parameters of the calibration curve. The initial values can be selected according to experience or prior knowledge. Select the Newton method optimization algorithm. In the Newton method, it is necessary to calculate the gradient of the error function with respect to the parameters and the approximate Hessian matrix; repeat the above iterative process until the stopping condition is met, such as the change in the error function is less than a preset threshold, or the number of iterations reaches the maximum value. The calibration curve corresponding to the finally obtained parameters is the optimized calibration curve.

[0096] Step 153, for a new sample, measure the ratio of its major and trace elements, substitute the isotope ratio into the optimized calibration curve equation, and solve the above equation to obtain the absolute age estimate value of the sample. Since the calibration curve equation may be relatively complex, numerical methods such as the Newton-Raphson method may be used in the solving process.

[0097] In a preferred embodiment of the present invention, step 16 may include:

[0098] Calculate the mean μ and standard deviation σ of the artifact age dataset. For the age value x of each artifact i , if |x i - μ| > 3σ, then mark this artifact as a preliminary outlier to obtain a detection value.

[0099] In the embodiment of the present invention, by calculating the mean and standard deviation, the central tendency and dispersion degree of the artifact age dataset can be clarified. When the age value of a certain artifact satisfies |x i - μ| > 3σ, mark it as a preliminary outlier. After marking the preliminary outliers, further verify and investigate these data. If it is confirmed as incorrect data, it can be corrected or removed, thereby improving the accuracy of the entire artifact age dataset. Accurately identifying and processing outliers helps to improve the artifact chronology system. In chronology research, establishing a reliable age framework is the key. By analyzing outliers, the accuracy and reliability of age determination are improved, thus promoting the development of the entire chronology field.

[0100] In the embodiment of the present invention, the specific steps include:

[0101] Collect data related to the artifact age, organize these data into a dataset, where each data point represents the age value of an artifact. According to the standard deviation calculation formula, calculate the square of the difference between each age value and the mean, then sum up all the squares of the differences, divide by the total number of artifacts, and finally take the square root to obtain the standard deviation of the artifact age dataset. According to the research purpose and data characteristics, select a suitable threshold coefficient. The threshold is usually determined according to historical data, and a common value is k = 3. For the age value xi of each artifact in the dataset, calculate |x i - μ| and compare it with 3σ. If |xi - μ| > 3σ, then mark this artifact as a preliminary outlier, and organize the information of all artifacts marked as preliminary outliers together to form a detection value set. The detection value set can include information such as the artifact number, age value, and the degree of difference from other artifacts.

[0102] In a preferred embodiment of the present invention, step 17 may include:

[0103] Step 171, perform weighted fusion on the detection value and the absolute age estimate value to obtain the fused data;

[0104] Step 172, obtain the confidence interval of the fused data through Bootstrap resampling, and obtain the standard deviation of the fused data by the variances and weights of each data source during the fusion process;

[0105] Step 173: Quantify the uncertainty of the fusion result through the confidence interval and the standard deviation;

[0106] Step 174: Adjust the age of the cultural relic according to the uncertainty of the fusion result to achieve the dating of the cultural relic.

[0107] In the embodiment of the present invention, the measured value is weighted and fused with the absolute age estimate value. The measured value may contain preliminary judgments based on various factors such as the characteristics of the cultural relic itself and the archaeological background, while the absolute age estimate value is usually obtained through elemental dating. Weighted fusion can comprehensively consider information from different sources, make full use of their respective advantages, obtain more accurate fused data, and make the dating of cultural relics closer to the true value. Different dating methods and detection means may have their own limitations and biases. The confidence interval of the fused data is obtained through Bootstrap resampling. The confidence interval provides a range estimate for the age of the fused cultural relic, which reflects the interval within which the age of the cultural relic may fall at a certain confidence level. The standard deviation of the fused data is obtained by combining the variances and weights of each data source in the fusion process. The standard deviation can measure the dispersion degree of the fused data. The uncertainty of the fusion result is quantified through the confidence interval and the standard deviation.

[0108] In the embodiment of the present invention, the specific steps include:

[0109] Step 171: Determine the specific values of the measured value and the absolute age estimate value, and assign weights to them respectively according to the reliability and importance of the measured value and the absolute age estimate value. For example, if the absolute age estimate value comes from a high-precision scientific dating method and the sample quality is reliable, a higher weight can be given to it, while the measured value is greatly affected by subjective factors and the weight can be relatively low, and the fused data is calculated according to the weighted fusion formula.

[0110] Step 172: Randomly draw samples from the fused data set with replacement. The number of samples drawn each time is the same as the original fused data set. Repeat the drawing multiple times, calculate the statistic for each drawn sample, sort these statistics from smallest to largest, and determine the upper and lower limits of the confidence interval according to a certain confidence level (such as 95%).

[0111] Step 173: Analyze the width of the confidence interval. The wider the confidence interval, the greater the uncertainty of the fusion result; the narrower the confidence interval, the smaller the uncertainty of the fusion result. Consider the size of the standard deviation. The larger the standard deviation, the more dispersed the fused data and the higher the uncertainty; the smaller the standard deviation, the more concentrated the fused data and the lower the uncertainty. Comprehensively consider the information of the confidence interval and the standard deviation, and conduct a quantitative evaluation of the uncertainty of the fusion result. For example, an uncertainty index U can be defined, which comprehensively considers the width of the confidence interval and the size of the standard deviation. The larger the U value, the higher the uncertainty.

[0112] Step 174: If the uncertainty of the fusion result is low, it indicates that the data after fusion is relatively reliable, and the data after fusion can be directly used as the measured value of the age of the cultural relic. If the uncertainty of the fusion result is high, it is necessary to further analyze the reasons. It may be that the reliability of the measured value or the estimated value of the absolute age has problems, or it may be that the weight allocation is unreasonable. According to the analysis results, data can be re-collected, the dating method can be improved, the weight can be adjusted, etc. During the adjustment process, steps 171-173 are continuously repeated until the uncertainty of the fusion result is reduced to an acceptable range, and finally the age of the cultural relic is determined.

[0113] As Figure 2 shown, an embodiment of the present invention also provides a cultural relic age determination system 20, including:

[0114] An acquisition module 21, configured to collect samples from the cultural relics to be measured, and clean, dry, and pulverize the samples to obtain processed samples;

[0115] An optimization module 22, which analyzes the elemental composition of the sample through an energy dispersive X-ray fluorescence spectrometer to obtain the types and content ratios of the main elements and trace elements in the sample; collects samples of the same type of cultural relics with known ages, conducts elemental composition analysis, and establishes a standard sample ratio of known ages; compares the types and content ratios of the main elements and trace elements in the sample with the standard sample ratio of known ages, and fits a calibration curve by the least squares method according to the comparison data set; optimizes the calibration curve, and calculates the estimated value of the absolute age of the cultural relic according to the optimized calibration curve;

[0116] A processing module 23, configured to detect outliers in the age of the cultural relic to obtain a detection value; fuse the detection value with the estimated value of the absolute age, and quantify the uncertainty of the fusion result to achieve the determination of the age of the cultural relic.

[0117] The above is the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present invention, several improvements and refinements can be made, and these improvements and refinements should also be regarded as the protection scope of the present invention.

Claims

1. A method for determining the age of cultural relics, characterized in that, The method includes: Collect samples from the cultural relics to be measured, and clean, dry, and crush the samples to obtain processed samples; Analyze the elemental composition of the samples by an energy-dispersive X-ray fluorescence spectrometer to obtain the types and content ratios of the major and trace elements in the samples; Collect samples of the same type of cultural relics with known ages, conduct elemental composition analysis, and establish standard sample ratios for known ages; Compare the types and content ratios of the major and trace elements in the samples with the standard sample ratios for known ages, and based on the comparison dataset, fit a calibration curve by the least squares method; Optimize the calibration curve and calculate the absolute age estimate of the cultural relics based on the optimized calibration curve; Detect outliers in the age of the cultural relics to obtain detection values; Fuse the detection values with the absolute age estimates and quantify the uncertainty of the fusion results to achieve the determination of the age of cultural relics.

2. The method for determining the age of cultural relics according to claim 1, wherein Analyze the elemental composition of the samples by an energy-dispersive X-ray fluorescence spectrometer to obtain the types and content ratios of the major and trace elements in the samples, including: Detect the elements in the samples by an energy-dispersive X-ray fluorescence spectrometer to obtain an X-ray fluorescence spectrum; Identify the element types through the characteristic peak positions of the X-ray fluorescence spectrum and record the characteristic peak intensities of each element; According to the element types, convert the characteristic peak intensities corresponding to the element types into element contents and calculate the ratios of the major and trace elements.

3. The method for determining the age of cultural relics according to claim 1, wherein Collect samples of the same type of cultural relics with known ages, conduct elemental composition analysis, and establish standard sample ratios for known ages, including: Collect samples of the same type of cultural relics with known ages, conduct elemental composition analysis, and calculate the ratios of the major and trace elements in each sample; Fit the element ratios and age data by statistical methods to establish a standard sample ratio.

4. The method for determining the age of cultural relics according to claim 1, characterized in that, Compare the types and content ratios of the major and trace elements in the samples with the standard sample ratios for known ages, and based on the comparison dataset, fit a calibration curve by the least squares method, including: Compare the types and content ratios of the major and trace elements in the samples with the standard sample ratios for known ages to obtain the element ratios in each standard sample; Construct an exponential calibration curve model according to the decay of the major and trace elements following an exponential law; According to the exponential calibration curve model, determine that the objective function is to calculate the sum of the squares of the differences between the actual measured values and the model predicted values of the element ratios of each data point, i.e., each standard sample, and obtain the parameters a and b with the minimum error function through the least squares method; With the obtained parameters a and b, obtain the calibration curve.

5. The method for determining the age of cultural relics according to claim 1, wherein Optimize the calibration curve and calculate the absolute age estimate of the cultural relics based on the optimized calibration curve, including: Obtain the error of the calibration curve; By multiplying the partial derivative vector with the inverse of the approximate Hessian matrix the parameters a and b of the calibration curve are updated to obtain an optimized calibration curve; According to the optimized calibration curve, substitute the isotope ratio into the optimized calibration curve equation to obtain the absolute age estimate.

6. The method for determining the age of cultural relics according to claim 1, wherein Detect outliers in the age of the cultural relics to obtain detection values, including: Calculate the mean μ and standard deviation σ of the dataset of the ages of cultural relics. For the age value x of each cultural relic i , if ∣x i -μ∣>3σ is satisfied, then mark this cultural relic as a preliminary outlier to obtain the detection value.

7. The method for determining the age of cultural relics according to claim 1, characterized in that, Fuse the detection values with the absolute age estimates and quantify the uncertainty of the fusion results to achieve the determination of the age of cultural relics, including: Perform weighted fusion on the detection values and the absolute age estimates to obtain the fused data; Through Bootstrap resampling, obtain the confidence interval of the fused data, and obtain the standard deviation of the fused data through the variances and weights of each data source during the fusion process; Through the confidence interval and the standard deviation, quantify the uncertainty of the fusion result; According to the uncertainty of the fusion result, adjust the age of the cultural relic to achieve the determination of the age of the cultural relic.

8. An artifact dating system that implements the method according to any one of claims 1 to 7, characterized in that, It includes: An acquisition module, configured to collect samples from the cultural relics to be measured, and clean, dry, and pulverize the samples to obtain processed samples; An optimization module, which analyzes the elemental composition of the samples through an energy dispersive X-ray fluorescence spectrometer to obtain the types and content ratios of the main elements and trace elements in the samples; collects samples of the same type of cultural relics with known ages, conducts elemental composition analysis, and establishes the standard sample ratios of known ages; compares the types and content ratios of the main elements and trace elements in the samples with the standard sample ratios of known ages, and based on the comparison data set, fits a calibration curve by the least squares method; optimizes the calibration curve, and calculates the absolute age estimate of the cultural relic according to the optimized calibration curve; A processing module, configured to perform outlier detection on the age of the cultural relic to obtain a detection value; Fuse the detection value with the absolute age estimate, and quantify the uncertainty of the fusion result to achieve the determination of the age of the cultural relic.

9. A computing device, characterized in that, It includes: One or more processors; A storage device, configured to store one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, A program is stored in the computer-readable storage medium, and when the program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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