Infrared spectrum feature extraction method for asteroid rock

Abstract

The invention discloses an asteroid rock infrared spectrum feature extraction method, and relates to the technical field of infrared spectrum feature extraction, and the method comprises the following steps: collecting light intensity data of asteroid rock at different infrared wavelengths and different temperatures to obtain initial substance light intensity data, and collecting background light intensity data; obtaining infrared spectrum characteristics of the asteroid rock at different temperatures, and carrying out first characteristic analysis to obtain normal spectrum data of the substance; performing second characteristic analysis based on the normal spectrum data of the substance to obtain representative spectrum data of the substance; performing infrared spectrum feature extraction based on the substance representative spectrum data to obtain infrared spectrum features of asteroid rocks; the method is used for solving the problem that when an existing infrared spectrum feature extraction technology is used for obtaining the infrared spectrum features of the asteroid rock, the stable temperature range of the infrared spectrum features of the asteroid rock cannot be accurately obtained, and consequently the infrared spectrum features of the asteroid rock cannot be stably and accurately extracted.

Description

Technical Field

[0001] This invention relates to the field of infrared spectral feature extraction technology, specifically a method for extracting infrared spectral features from asteroid rocks. Background Technology

[0002] Infrared spectral feature extraction technology refers to the technique used in the infrared spectral analysis process to screen, separate, and quantify key feature parameters that reflect the molecular structure, functional group composition, or content of substances from complex raw infrared spectral data through a series of processing algorithms and spectral analysis logic.

[0003] Existing infrared spectral feature extraction techniques for acquiring infrared spectral characteristics of asteroid rocks often disregard the asteroid rock's own temperature. The temperature of the asteroid rock during testing is affected by the environment, leading to inconsistent spectral characteristics of the same type of asteroid rock under different conditions. The infrared spectrum of asteroid rocks carries crucial information about their mineral composition, chemical structure, and formation environment. Infrared spectroscopy is extremely sensitive to temperature; changes in the material's own temperature can cause characteristic peak positions to shift. Without knowing the precise temperature range within which spectral characteristics are stable, random temperature fluctuations during testing can result in inconsistent spectra for the same asteroid rock, and may even lead to misinterpreting peak shifts as compositional differences. Infrared spectroscopy identifies characteristics through peak position, peak intensity, and peak shape. The existence of specific spectral characteristics and stable temperature ranges allows for the establishment of a temperature-free testing interval, ensuring the authenticity of characteristic peaks and enabling accurate identification of the main material composition and trace impurities in asteroid rocks. Furthermore, asteroid rocks undergo slight phase transitions due to temperature variations in the Earth's environment; for example, some low-temperature minerals undergo crystal transformations above room temperature. These environmentally induced changes are superimposed on the original spectrum, obscuring the information of the asteroid rocks themselves, making accurate identification of their composition and minerals impossible. Therefore, existing infrared spectral feature extraction techniques cannot accurately determine the stable temperature range of asteroid rock infrared spectral characteristics, resulting in the inability to reliably and accurately extract these characteristics. Summary of the Invention

[0004] This invention aims to at least partially solve one of the technical problems in the prior art. It obtains initial material light intensity data and background light intensity data by collecting light intensity data of asteroid rocks at different infrared wavelengths and temperatures; acquires the infrared spectral characteristics of asteroid rocks at different temperatures and performs a first feature analysis to obtain normal spectral data of the material; performs a second feature analysis based on the normal spectral data to obtain representative spectral data of the material; and extracts infrared spectral features based on the representative spectral data to obtain the infrared spectral characteristics of the asteroid rocks. This addresses the problem that existing infrared spectral feature extraction techniques cannot accurately determine the stable temperature range of the infrared spectral characteristics of asteroid rocks, leading to the inability to stably and accurately extract their infrared spectral characteristics.

[0005] To achieve the above objectives, this application provides a method for extracting infrared spectral features from asteroid rocks, comprising the following steps:

[0006] Light intensity data of asteroid rocks at different infrared wavelengths and temperatures were collected to obtain initial material light intensity data, and background light intensity data were also collected.

[0007] Infrared spectral characteristics of asteroid rocks at different temperatures were obtained based on initial material light intensity data, and first feature analysis was performed to obtain normal spectral data of the material.

[0008] Second feature analysis is performed on the normal spectral data of the substance to obtain representative spectral data of the substance.

[0009] Infrared spectral features were extracted from representative spectral data of the material to obtain the infrared spectral characteristics of asteroid rocks.

[0010] Furthermore, the light intensity data of the asteroid rocks at different infrared wavelengths and temperatures were collected to obtain initial material light intensity data, and background light intensity data was collected, including the following sub-steps:

[0011] Based on the asteroid rock to be tested, prepare a sample of the asteroid rock to be tested, and record it as the first material sample;

[0012] Set the infrared wavelength range used for infrared spectral feature extraction, denoted as the first wavelength range; set the temperature range, denoted as the first temperature range; uniformly select k1 temperatures from the first temperature range, denoted as test temperature points; denot any one of the test temperature points as the first test temperature, where k1 is the set number.

[0013] Furthermore, collecting light intensity data of asteroid rocks at different infrared wavelengths and temperatures to obtain initial material light intensity data, and collecting background light intensity data also includes the following sub-steps:

[0014] Adjust the temperature of the first material sample to the first test temperature, and record it as the first temperature sample. According to the diffuse reflectance infrared spectroscopy method, collect the diffuse reflectance light intensity of the first temperature sample when it is irradiated by infrared light of various wavelengths within the first wavelength range, and record it as the sample reflected light intensity. After completion, the sample light intensity data of the first test temperature is obtained. Repeat the acquisition of the sample light intensity data of all test temperature points and record it as the initial material light intensity data.

[0015] A reference object is set up, and its temperature is adjusted to the first test temperature. The diffuse reflection light intensity of the reference object when it is irradiated by infrared light of various wavelengths within the first wavelength range is collected and recorded as the reference reflection light intensity. After completion, the control light intensity data of the first test temperature is obtained. The control light intensity data of all test temperature points is repeatedly collected and recorded as the background light intensity data.

[0016] Furthermore, based on the initial material light intensity data, the infrared spectral characteristics of the asteroid rocks at different temperatures were obtained, and the first feature analysis was performed to obtain the normal spectral data of the material, including the following sub-steps:

[0017] Any infrared wavelength within the first wavelength range is denoted as the first wavelength. Based on the sample light intensity data and the reference light intensity data at the first test temperature, the sample reflected light intensity and the reference reflected light intensity corresponding to the first wavelength are obtained and denoted as AI and BI respectively in order. The apparent absorbance corresponding to the first wavelength is calculated as log(1 / R), where R = AI / BI.

[0018] Based on the sample light intensity data and the control light intensity data at the first test temperature, the apparent absorbance corresponding to all infrared wavelengths within the first wavelength range is repeatedly calculated; and an infrared spectral feature map is established with the apparent absorbance as the vertical axis and the corresponding wavenumber as the horizontal axis, which is recorded as the infrared feature map of the sample at the first test temperature.

[0019] Based on the infrared characteristic image of the sample at the first test temperature, the number of absorption peaks is obtained and recorded as the peak number. The peak position, peak intensity and half-width of each absorption peak are also obtained. After completion, the infrared spectral characteristics of the first test temperature are obtained.

[0020] Repeatedly acquire the infrared spectral features corresponding to all test temperature points, and sort the number of peaks corresponding to all test temperature points in ascending order, and record it as the peak number sequence.

[0021] For any two adjacent peak counts in the peak count sequence, if the two adjacent peak counts are not the same, the midpoint of the two adjacent peak counts is taken as the dividing point. All dividing points are obtained repeatedly to divide the peak count sequence into several subsequences, and the longest subsequence is denoted as the first subsequence.

[0022] The temperature range corresponding to the first subsequence is denoted as the second temperature range, and the test temperature points within the second temperature range are denoted as the basic temperature points.

[0023] Furthermore, obtaining the infrared spectral characteristics of asteroid rocks at different temperatures based on the initial material light intensity data, and performing the first feature analysis to obtain the normal spectral data of the material, also includes the following sub-steps:

[0024] Based on the infrared spectral characteristics of all basic temperature points, the absorption peaks in the infrared characteristic image of the sample at each basic temperature point are numbered sequentially according to the magnitude of the corresponding wavenumber, and are sequentially denoted as absorption peak 1 to absorption peak n. Any absorption peak is denoted as the first absorption peak, where n represents the total number of absorption peaks.

[0025] Based on the infrared spectral characteristics of all basic temperature points, the peak position, peak intensity, and half-peak width of the first absorption peak at different basic temperature points are obtained respectively, and are recorded as feature set 1, feature set 2, and feature set 3 in sequence.

[0026] Furthermore, obtaining the infrared spectral characteristics of asteroid rocks at different temperatures based on the initial material light intensity data, and performing the first feature analysis to obtain the normal spectral data of the material, also includes the following sub-steps:

[0027] Range acquisition processing is performed on feature set 1, feature set 2, and feature set 3 respectively. The range acquisition processing includes:

[0028] Sort the data of any feature set in ascending order according to the corresponding basic temperature points, and denote this as the first feature sequence; then denote the data in the first feature sequence as C1-C1. m And denote any data as C i , where i represents the position number;

[0029] Calculate C i The corresponding absolute fluctuation value AC i AC i =|C i+1 -C i |, Repeatedly calculate C1-C m-1 The corresponding absolute fluctuation value, and calculate C. i The corresponding volatility ratio BC i BC i =AC i+1 / AC i ;

[0030] Repeatedly calculate C1-C m-2 The corresponding absolute volatility values ​​are calculated, and the mean and standard deviation are denoted as AP and BP respectively, in that order; if the volatility ratio is BC i If not located in [AP-k2*BP, AP-k2*BP], then mark C. i+1For each transition point, repeat the acquisition of all transition points, where k2 is the set scaling factor;

[0031] Remove the transition points of the first feature sequence, and divide the first feature sequence into several subsequences based on the position of the transition points, denoted as the preliminary subsequences;

[0032] Calculate the correlation coefficient between the basic temperature point and the data for each preliminary subsequence; remove preliminary subsequences whose correlation coefficient is not located in [k3, k4], and denote the remaining preliminary subsequences as stable subsequences, where [k3, k4] is the set range;

[0033] Let any stable subsequence be denoted as the first stable sequence, calculate the mean of the first stable sequence and denot it as DP, and obtain the maximum and minimum values ​​of the first stable sequence and denot them as AF and BF respectively in order; calculate the dispersion LD of the first stable sequence, where LD = (AF-BF) / BF*100%.

[0034] Calculate the mean and standard deviation of the first stable sequence, denoted as AU and BU respectively; calculate the dispersion threshold YD of the first stable sequence; where YD = k5 * BU / AU * 100%, and k5 is the set scaling factor;

[0035] If the dispersion LD of the first stable sequence is not greater than the corresponding dispersion threshold YD, then the first stable sequence is marked as a qualified subsequence.

[0036] Repeatedly obtain all qualified subsequences and obtain the position of each qualified subsequence in the first feature sequence. If there is only one transition point between two qualified subsequences, merge the two qualified subsequences. After completion, obtain the temperature range of the basic temperature point corresponding to the qualified subsequence, and record it as the temperature range corresponding to the feature set.

[0037] Furthermore, obtaining the infrared spectral characteristics of asteroid rocks at different temperatures based on the initial material light intensity data, and performing the first feature analysis to obtain the normal spectral data of the material, also includes the following sub-steps:

[0038] Repeatedly obtain the temperature ranges corresponding to feature set 1, feature set 2 and feature set 3, and find their intersection to obtain the temperature range corresponding to the first absorption peak;

[0039] Repeatedly obtain the temperature range corresponding to absorption peak 1 to absorption peak n, and find the intersection. Record the intersection as the normal temperature range. Record the infrared spectral characteristics of the sample infrared feature map at the test temperature point within the normal temperature range as the normal spectral data of the substance.

[0040] Furthermore, based on the normal spectral data of the substance, a second feature analysis is performed to obtain representative spectral data of the substance, including the following sub-steps:

[0041] Based on the normal spectral data of the substance, the peak position, peak intensity and half-width of the first absorption peak at each test temperature point within the normal temperature range are obtained, and then sorted according to the test temperature points from smallest to largest, and recorded as peak position sequence, peak intensity sequence and peak width sequence respectively.

[0042] Set the sliding window size to k6 and the sliding step size to 1. Start sliding synchronously from the beginning position of the peak position sequence, peak intensity sequence and peak width sequence respectively, record the number of sliding, calculate the relative standard deviation of the data in each of the three moving windows for each sliding, and calculate the average value, which is recorded as the average deviation of this sliding.

[0043] Sort all average deviations in ascending order of their corresponding number of slides, and denote this as the average deviation sequence. Calculate the average value of the average deviation sequence, and denote this as the deviation threshold.

[0044] The average deviation in the average deviation sequence that is greater than the deviation threshold is denoted as the fluctuation deviation, and the average deviation in the average deviation sequence that is not greater than the deviation threshold is denoted as the stable deviation.

[0045] Furthermore, the second feature analysis based on the normal spectral data of the substance to obtain representative spectral data of the substance also includes the following sub-steps:

[0046] Obtain a portion of the average deviation sequence consisting of continuous stable deviations, denoted as a stable subsequence, and denote the longest stable subsequence as the first stable sequence.

[0047] Any stable deviation in the first stable sequence is denoted as the first deviation. The temperature range of the test temperature points contained in the sliding window corresponding to the first deviation is obtained and denoted as the window temperature range of the first deviation.

[0048] Repeatedly obtain the window temperature range of all stable deviations in the first stable sequence, and find the union of them, which is denoted as the stable temperature range of the first absorption peak.

[0049] Repeatedly obtain the stable temperature range of all absorption peaks, find the intersection, and record it as the representative temperature range. Record the infrared spectral characteristics of the sample infrared feature map at the test temperature point within the representative temperature range as the normal spectral data of the substance.

[0050] Furthermore, based on representative spectral data of the material, infrared spectral features are extracted to obtain the infrared spectral features of the asteroid rocks, including the following sub-steps:

[0051] Based on the representative spectral data of the substance, the peak position range, peak intensity range and half-width range of the first absorption peak in the corresponding representative temperature range are obtained, and the shape of the first absorption peak is obtained and recorded as the representative spectral characteristics of the first absorption peak.

[0052] By repeatedly acquiring representative spectral characteristics of all absorption peaks, the corresponding infrared spectral characteristics of the asteroid rocks can be obtained.

[0053] The beneficial effects of this invention are as follows: This invention obtains initial material light intensity data by collecting light intensity data of asteroid rocks at different infrared wavelengths and temperatures, and also collects background light intensity data; based on the initial material light intensity data, it acquires the infrared spectral characteristics of asteroid rocks at different temperatures, and performs a first feature analysis to obtain normal material spectral data; based on the normal material spectral data, it performs a second feature analysis to obtain representative material spectral data; based on the representative material spectral data, it extracts infrared spectral features to obtain the infrared spectral characteristics of asteroid rocks; when acquiring the infrared spectral characteristics of asteroid rocks, it can accurately determine the stable temperature range of the infrared spectral characteristics of asteroid rocks, thereby stably and accurately extracting the infrared spectral characteristics of asteroid rocks;

[0054] This invention locates the second temperature range by peak number sequence and calculates fluctuation ratio to detect jump points. Then, based on correlation coefficient and dispersion, a stable temperature range and stable characteristics are obtained. This allows for the rapid and robust identification of stable temperature ranges for the infrared characteristics of asteroid rocks, thereby eliminating temperature ranges that cause significant changes in absorption peak characteristics and improving the accuracy of asteroid rock infrared spectral feature extraction. Based on a simultaneous sliding window of peak position, peak intensity, and half-maximum width, it can capture consistent and stable temperature ranges for multiple parameters. Compared to considering only a single parameter, this avoids misjudging a stable temperature range when one parameter is stable but others are unstable, further improving the accuracy of the obtained temperature range and ensuring stable and accurate extraction of the infrared spectral characteristics of asteroid rocks. Attached Figure Description

[0055] Figure 1 This is a flowchart of the steps of the method of the present invention;

[0056] Figure 2 This is a flowchart illustrating the scope acquisition process of the present invention;

[0057] Figure 3 This is a flowchart of the second feature analysis of the present invention;

[0058] Figure 4 This is a schematic diagram of the electronic device of the present invention. Detailed Implementation

[0059] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0060] Example 1, please refer to Figure 1 As shown, this application provides a method for extracting infrared spectral features from asteroid rocks, comprising the following steps:

[0061] Step S1 involves collecting light intensity data of asteroid rocks at different infrared wavelengths and temperatures to obtain initial material light intensity data, and also collecting background light intensity data. Step S1 includes the following sub-steps:

[0062] Step S101: Based on the asteroid rock to be tested, prepare a sample of the asteroid rock to be tested, which is denoted as the first material sample; preparing the sample is to convert the irregular actual material into a standard form that can be repeatedly measured in the spectrometer, thereby ensuring the repeatability and comparability of the experiment.

[0063] Step S102: Set the infrared wavelength range used for infrared spectral feature extraction, denoted as the first wavelength range; set the temperature range, denoted as the first temperature range; uniformly select k1 temperatures from the first temperature range, denoted as test temperature points; denot any one of the test temperature points as the first test temperature, where k1 is the number of points set. In this embodiment, k1 = 100, which can be flexibly set.

[0064] The infrared wavelength range determines which chemical or structural features you can observe. Different chemical bonds and phase transitions have characteristic absorption positions in the infrared spectrum. If the wavelength range is too narrow, key information will be missed; if it is too wide, it will increase measurement time and data volume and may include noise sources. The first wavelength range can be set according to the actual application scenario. The absorption peaks of asteroid rocks may change with temperature. The first temperature range needs to cover the possible absorption peak change region and the absorption peak temperature region, which can be flexibly set according to the actual application scenario.

[0065] Step S103: Adjust the temperature of the first material sample to the first test temperature, denoted as the first temperature sample. According to the diffuse reflectance infrared spectroscopy method, collect the diffuse reflectance light intensity of the first temperature sample when it is irradiated by infrared light of various wavelengths within the first wavelength range, and record it as the sample reflected light intensity. After completion, the sample light intensity data of the first test temperature is obtained. Repeat the acquisition of sample light intensity data at all test temperature points, and record it as the initial material light intensity data. The diffuse reflectance light intensity captured by the diffuse reflectance measurement is the light of the outgoing light after the incident light is scattered multiple times inside the sample.

[0066] Step S104: Set a reference object, adjust the temperature of the reference object to the first test temperature, collect the diffuse reflection light intensity of the reference object when it is irradiated by infrared light of various wavelengths within the first wavelength range, and record it as the reference reflection light intensity. After completion, obtain the control light intensity data of the first test temperature. Repeat the acquisition of the control light intensity data of all test temperature points and record it as the background light intensity data.

[0067] Reference materials are key substances used in diffuse reflectance infrared spectroscopy to calibrate instrument signals and eliminate systematic errors. Their core function is to provide an ideal diffuse reflectance benchmark, that is, to assume that the reference material does not selectively absorb infrared light and only produces pure diffuse reflectance, so as to compare the selective absorption signal of the sample. Reference materials can be flexibly selected according to the actual application scenario.

[0068] In practical implementation, diffuse reflectance infrared spectroscopy is one of the core technologies in infrared spectroscopy analysis for opaque, powdery, or highly scattering samples. Unlike traditional transmission infrared spectroscopy, diffuse reflectance infrared spectroscopy indirectly obtains information by detecting the infrared light signal diffusely reflected from the sample surface, and is especially suitable for solid samples that cannot be made into transparent sheets.

[0069] Step S2 involves acquiring the infrared spectral characteristics of the asteroid rock at different temperatures based on the initial material light intensity data, and performing a first feature analysis to obtain the normal spectral data of the material. Step S2 includes the following sub-steps:

[0070] Step S201: Denote any infrared wavelength within the first wavelength range as the first wavelength. Based on the sample light intensity data and the control light intensity data at the first test temperature, obtain the sample reflected light intensity and the reference reflected light intensity corresponding to the first wavelength, and denote them as AI and BI respectively. Calculate the apparent absorbance log(1 / R) corresponding to the first wavelength, where R = AI / BI. The original sample reflected light intensity AI is affected by system factors such as the light source spectrum, detector response, and measurement geometry. Calculate R using the reference reflected light intensity BI, and then use log(1 / R) to separate reflection, scattering, and instrument response, obtaining spectral characteristics closer to the intrinsic properties of the material, providing a unified dimension for subsequent processing.

[0071] Step S202: Based on the sample light intensity data and the control light intensity data at the first test temperature, repeatedly calculate the apparent absorbance corresponding to all infrared wavelengths within the first wavelength range; and establish an infrared spectral feature map with the apparent absorbance as the vertical axis and the corresponding wavenumber as the horizontal axis, which is recorded as the infrared feature map of the sample at the first test temperature.

[0072] Step S203: Based on the infrared characteristic image of the sample at the first test temperature, obtain the number of absorption peaks, denoted as the peak number, and obtain the peak position, peak intensity, and half-width of each absorption peak. After completion, the infrared spectral characteristics of the first test temperature are obtained. Peak position is the most crucial parameter of the absorption peak, directly corresponding to the specific structure or functional group of the substance, and determining what substance it is. Peak intensity describes the absorption capacity of a substance for light of a specific wavelength, directly related to the content and absorption probability of the substance, and is the core parameter of the infrared spectral characteristics. Peak width reflects the degree of energy dispersion in the absorption process, and is closely related to the purity, crystal structure, and molecular motion state of the substance. It is an important basis for judging the orderliness and degree of defects of the sample.

[0073] Step S204: Repeatedly acquire the infrared spectral features corresponding to all test temperature points, and sort the number of peaks corresponding to all test temperature points in ascending order, and record it as the peak number sequence.

[0074] Step S205: For any two adjacent peak counts in the peak count sequence, if the two adjacent peak counts are not the same, take the midpoint of the two adjacent peak counts as the dividing point, repeat the acquisition of all dividing points, divide the peak count sequence into several subsequences, and denote the longest subsequence as the first subsequence.

[0075] Step S206: Record the temperature range corresponding to the first subsequence as the second temperature range, and record the test temperature points within the second temperature range as the basic temperature points.

[0076] The essence of infrared spectroscopy is the absorption of infrared light of a specific wavelength by the vibrational energy level transition of sample molecules. Temperature changes may cause thermal decomposition, phase transition, and changes in the vibrational modes of functional groups in the sample, which are ultimately manifested as the addition, disappearance, peak position shift, and peak intensity fluctuation of absorption peaks. The number of absorption peaks is the most basic macroscopic feature of the spectrum: if the number of peaks is continuous and equal, it means that within this temperature range, the sample has not undergone drastic changes that would cause the appearance of new peaks or the disappearance of old peaks. This indicates that the infrared spectral characteristics of the sample are basically stable within this temperature range, thus defining the basic range for subsequent analysis and processing.

[0077] Step S207: Based on the infrared spectral characteristics of all basic temperature points, the absorption peaks in the infrared characteristic diagram of the sample at each basic temperature point are numbered sequentially according to the magnitude of the corresponding wavenumber, and are sequentially recorded as absorption peak 1 to absorption peak n. Any absorption peak is recorded as the first absorption peak, where n represents the total number of absorption peaks.

[0078] Step S208: Based on the infrared spectral characteristics of all basic temperature points, obtain the peak position, peak intensity and half-peak width of the first absorption peak at different basic temperature points, and record them as feature set 1, feature set 2 and feature set 3 in sequence.

[0079] Step S209: Perform range acquisition processing on feature set 1, feature set 2 and feature set 3 respectively;

[0080] Step S210, the range acquisition process step S210 includes the following sub-steps:

[0081] For step S2101, please refer to... Figure 2 As shown, the data of any feature set are sorted in ascending order according to the corresponding basic temperature points, and denoted as the first feature sequence; the data in the first feature sequence are sequentially denoted as C1-C1. m And denote any data as C i, where i represents the position number;

[0082] Step S2102, calculate C i The corresponding absolute fluctuation value AC i AC i =|C i+1 -C i |, Repeatedly calculate C1-C m-1 The corresponding absolute fluctuation value, and calculate C. i The corresponding volatility ratio BC i BC i =AC i+1 / AC i ACi represents the change in a characteristic between two adjacent temperature points; BCI is used to amplify abrupt changes in the magnitude of the change. If BCI is very large or very small at a certain point, it means that the change after that point has suddenly changed, which usually corresponds to a point of abrupt change.

[0083] Step S2103, repeat the calculation of C1-C m-2 The corresponding absolute volatility values ​​are calculated, and the mean and standard deviation are denoted as AP and BP respectively, in that order; if the volatility ratio is BC i If not located in [AP-k2*BP, AP-k2*BP], then mark C. i+1 For each transition point, all transition points are repeatedly acquired, where k2 is a set scaling factor; in this embodiment, k2 = 2, which can be flexibly set according to the actual application scenario.

[0084] Step S2104: Remove the jump points of the first feature sequence and divide the first feature sequence into several subsequences based on the location of the jump points, denoted as preliminary subsequences; the jump points divide the entire sequence into several segments, each segment having relatively stable fluctuations, suitable for further statistical testing; this division isolates possible feature anomalies, facilitating local screening.

[0085] Step S2105: Calculate the correlation coefficient between the basic temperature point and the data for each preliminary subsequence; remove preliminary subsequences whose correlation coefficients are not located in [k3, k4], and denote the remaining preliminary subsequences as stable subsequences, where [k3, k4] is a set range; the correlation coefficient can be calculated using the CORREL function, and [k3, k4] can be flexibly set according to the actual application scenario. In this embodiment, [k3, k4] is [-0.6, 0.6]; outside this range, it indicates that the data shows a significant trend of change with temperature and is unstable.

[0086] Step S2106: Denote any stable subsequence as the first stable sequence, calculate the mean of the first stable sequence as DP, and obtain the maximum and minimum values ​​of the first stable sequence, which are denoted as AF and BF respectively in order; calculate the dispersion LD of the first stable sequence, where LD = (AF - BF) / BF * 100%; LD quantifies the relative range of the first stable sequence, reflecting the breadth of fluctuation of the characteristic values ​​within the segment; a small LD indicates that the segment is highly concentrated and stable;

[0087] Step S2107: Calculate the mean and standard deviation of the first stable sequence, denoted as AU and BU respectively; calculate the dispersion threshold YD of the first stable sequence; where YD = k5 * BU / AU * 100%, k5 is a set proportionality coefficient; in this embodiment, k5 = 6, because based on the statistical "3σ principle", 99.73% of the data falls within the range of mean ± 3 times the standard deviation, and is set to 6 times the standard deviation according to the size of the range; it can also be flexibly set according to the actual application scenario; YD combines the statistical standard deviation BU and the mean AU of the first stable sequence to give a relative tolerance; thereby judging whether the fluctuation of the subsequence is within the acceptable statistical range, without the need to manually set the threshold, it can be adaptively adjusted, improving the accuracy of the judgment;

[0088] Step S2108: If the dispersion LD of the first stable sequence is not greater than the corresponding dispersion threshold YD, then the first stable sequence is marked as a qualified subsequence.

[0089] Step S2109: Repeatedly obtain all qualified subsequences and obtain the position of all qualified subsequences in the first feature sequence. If there is only one transition point between two qualified subsequences, merge the two qualified subsequences. After completion, obtain the temperature range of the basic temperature point corresponding to the qualified subsequence and record it as the temperature range corresponding to the feature set.

[0090] Step S211: Repeatedly obtain the temperature ranges corresponding to feature set 1, feature set 2 and feature set 3, and find their intersection to obtain the temperature range corresponding to the first absorption peak.

[0091] Step S212: Repeatedly obtain the temperature range corresponding to absorption peak 1 to absorption peak n, and find the intersection, which is recorded as the normal temperature range. Record the infrared spectral characteristics of the sample infrared feature map at the test temperature point within the normal temperature range as the normal spectral data of the substance.

[0092] In practice, for a single peak, the peak position, peak intensity, and half-maximum width must all be stable at the same temperature range to indicate that the peak is truly stable at that temperature range. Taking the intersection of all peaks means that the entire spectrum is stable at these temperature points. Within this temperature range, the infrared spectral characteristics of asteroid rocks are basically temperature-dependent, meaning that the absorption peaks of asteroid rocks change little with their own temperature.

[0093] Step S3 involves performing a second feature analysis based on the normal spectral data of the substance to obtain representative spectral data of the substance. Step S3 includes the following sub-steps:

[0094] For step S301, please refer to... Figure 3 As shown, based on the normal spectral data of the substance, the peak position, peak intensity and half-width of the first absorption peak at each test temperature point within the normal temperature range are obtained, and sorted according to the test temperature points from smallest to largest, and recorded as peak position sequence, peak intensity sequence and peak width sequence respectively.

[0095] Step S302: Set the sliding window size k6 and the sliding step size to 1. Start sliding synchronously from the beginning position of the peak position sequence, peak intensity sequence, and peak width sequence, and record the number of sliding times. For each sliding, calculate the relative standard deviation of the data in each of the three sliding windows, which is the standard deviation of the data in the window / the average value of the data in the window * 100%. Calculate the average value and record it as the average deviation of this sliding. In this embodiment, k6 = 5, which can be set flexibly.

[0096] Step S303: Sort all average deviations in ascending order according to the corresponding number of sliding steps, and record them as the average deviation sequence. Calculate the average value of the average deviation sequence and record it as the deviation threshold. Using the average value of the average deviation sequence as the threshold is more adaptable to different samples and different noise levels than a fixed threshold.

[0097] Step S304: The average deviation in the average deviation sequence that is greater than the deviation threshold is recorded as the fluctuation deviation, and the average deviation in the average deviation sequence that is not greater than the deviation threshold is recorded as the stable deviation.

[0098] Step S305: Obtain a portion of the average deviation sequence consisting of continuous stable deviations, denoted as a stable subsequence, and denote the longest stable subsequence as the first stable sequence; the longest stable subsequence is most likely to represent the dominant and representative stable temperature range, rather than a short-lived and occasional stable window.

[0099] Step S306: Record any stable deviation in the first stable sequence as the first deviation, and obtain the temperature range of the test temperature points contained in the sliding window corresponding to the first deviation, which is recorded as the window temperature range of the first deviation.

[0100] Step S307: Repeatedly obtain the window temperature range of all stable deviations in the first stable sequence, and find the union of them, which is recorded as the stable temperature range of the first absorption peak.

[0101] Step S308: Repeatedly obtain the stable temperature range of all absorption peaks and find the intersection, which is recorded as the representative temperature range. Record the infrared spectral characteristics of the sample infrared feature map at the test temperature point within the representative temperature range as the normal spectral data of the substance. Taking the intersection of the stable temperature ranges of absorption peaks ensures that the representative temperature range is the temperature range in which all important absorption peaks are stable at the same time. Thus, the spectral characteristics of this temperature range can represent the spectral characteristics of the entire substance, rather than just a certain peak.

[0102] In practice, asteroid rocks are typically composed of olivine, pyroxene, and plagioclase, with small amounts of other minerals such as apatite, troilite, and iron-nickel alloys. The infrared spectrum of asteroid rocks carries key information about their mineral composition, chemical structure, and formation environment. Infrared spectra identify minerals through characteristic peak positions, peak intensities, and peak shapes. If the test temperature exceeds the stable range, temperature fluctuations can cause absorption peaks to shift in position, broaden in shape, or decrease in intensity. For example, increased temperature may cause the characteristic peaks of olivine and pyroxene to shift to lower wavenumbers, directly leading to misidentification as other substances. A stable temperature range ensures the authenticity of characteristic peaks, thereby accurately identifying the main minerals and trace impurities in asteroid rocks.

[0103] Step S4 involves extracting infrared spectral features based on representative spectral data of the material to obtain the infrared spectral characteristics of the asteroid rock. Step S4 includes the following sub-steps:

[0104] Step S401: Based on the representative spectral data of the substance, obtain the peak position range, peak intensity range and half-width range of the first absorption peak in the corresponding representative temperature range, and obtain the shape of the first absorption peak, which is recorded as the representative spectral characteristics of the first absorption peak.

[0105] Step S402: Repeat the acquisition of representative spectral features of all absorption peaks to obtain the corresponding infrared spectral features of the asteroid rock.

[0106] In practice, there are still finite temperature differences and measurement noise within the representative temperature range. The peak position, peak intensity, and half-peak width of the absorption peak within the representative temperature range are not fixed values. Therefore, a single value cannot reflect this uncertainty. Using an interval can simultaneously indicate the typical value and variable amplitude of the infrared spectral characteristics, and is more tolerant of small fluctuations than a fixed value.

[0107] Example 2, please refer to Figure 4 As shown, Figure 4A schematic diagram of an electronic device is provided, which may include a processor, a communication interface, a memory, and a communication bus. The processor, communication interface, and memory communicate with each other via the communication bus. The memory stores computer-readable instructions, and the processor can call these instructions. When the processor executes a computer-readable instruction, it performs steps as described in a method for extracting infrared spectral features from asteroid rocks, to achieve the following functions: acquiring light intensity data of asteroid rocks at different infrared wavelengths and temperatures to obtain initial material light intensity data, and acquiring background light intensity data; obtaining infrared spectral features of asteroid rocks at different temperatures based on the initial material light intensity data, and performing a first feature analysis to obtain normal spectral data of the material; performing a second feature analysis based on the normal spectral data of the material to obtain representative spectral data of the material; and extracting infrared spectral features based on the representative spectral data of the material to obtain the infrared spectral features of the asteroid rocks.

[0108] Furthermore, when the logical instructions in the aforementioned memory can be implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0109] Example 3: This application also provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it performs the steps described above in the method for extracting infrared spectral features of asteroid rocks to achieve the following functions: collecting light intensity data of asteroid rocks at different infrared wavelengths and temperatures to obtain initial material light intensity data, and collecting background light intensity data; obtaining infrared spectral features of asteroid rocks at different temperatures based on the initial material light intensity data, and performing a first feature analysis to obtain normal spectral data of the material; performing a second feature analysis based on the normal spectral data of the material to obtain representative spectral data of the material; and extracting infrared spectral features based on the representative spectral data of the material to obtain the infrared spectral features of the asteroid rocks.

[0110] Based on the above description of the embodiments, the embodiments of the present invention can be provided as methods, systems, or computer program products. Based on this understanding, the technical solutions described above, or the parts that contribute to the prior art, can be embodied in the form of software products. These computer software products can be stored in computer-readable storage media, such as ROM / RAM, magnetic disks, optical disks, etc., and include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or certain parts of the embodiments.

[0111] In the embodiments provided in this application, it should be understood that the disclosed system or method can be implemented in other ways. The embodiments described above are merely illustrative. For example, the division of modules or units is only a logical functional division, and there may be other division methods in actual implementation. Furthermore, multiple modules or units may be combined or integrated into another system, or some features may be ignored or not executed. Additionally, the coupling or direct coupling or communication connection shown or discussed may be through some communication interfaces. The indirect coupling or communication connection between systems, modules, and units may be electrical, mechanical, or other forms.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A method for extracting infrared spectral features from asteroid rocks, characterized in that, Includes the following steps: Light intensity data of asteroid rocks at different infrared wavelengths and temperatures were collected to obtain initial material light intensity data, and background light intensity data were also collected. Based on the initial material light intensity data, the infrared spectral characteristics of asteroid rocks at different temperatures were obtained, and the first feature analysis was performed to obtain the normal spectral data of the material. Second feature analysis is performed on the normal spectral data of the substance to obtain representative spectral data of the substance. Infrared spectral features were extracted based on representative spectral data of the material to obtain the infrared spectral characteristics of asteroid rocks.

2. The method for extracting infrared spectral features of asteroid rocks according to claim 1, characterized in that, The process of collecting light intensity data of asteroid rocks at different infrared wavelengths and temperatures to obtain initial material light intensity data, and collecting background light intensity data includes the following sub-steps: Based on the asteroid rock to be tested, prepare a sample of the asteroid rock to be tested, and record it as the first material sample; Set the infrared wavelength range used for infrared spectral feature extraction, denoted as the first wavelength range; set the temperature range, denoted as the first temperature range; uniformly select k1 temperatures from the first temperature range, denoted as test temperature points; denot any one of the test temperature points as the first test temperature, where k1 is the set number.

3. The method for extracting infrared spectral features of asteroid rocks according to claim 2, characterized in that, Collecting light intensity data of asteroid rocks at different infrared wavelengths and temperatures to obtain initial material light intensity data, and collecting background light intensity data, also includes the following sub-steps: Adjust the temperature of the first material sample to the first test temperature, and record it as the first temperature sample. According to the diffuse reflectance infrared spectroscopy method, collect the diffuse reflectance light intensity of the first temperature sample when it is irradiated by infrared light of various wavelengths within the first wavelength range, and record it as the sample reflected light intensity. After completion, the sample light intensity data of the first test temperature is obtained. Repeat the acquisition of the sample light intensity data of all test temperature points and record it as the initial material light intensity data. A reference object is set up, and its temperature is adjusted to the first test temperature. The diffuse reflection light intensity of the reference object when it is irradiated by infrared light of various wavelengths within the first wavelength range is collected and recorded as the reference reflection light intensity. After completion, the control light intensity data of the first test temperature is obtained. The control light intensity data of all test temperature points is repeatedly collected and recorded as the background light intensity data.

4. The method for extracting infrared spectral features of asteroid rocks according to claim 3, characterized in that, Based on the initial material light intensity data, the infrared spectral characteristics of asteroid rocks at different temperatures were obtained, and the first feature analysis was performed to obtain the normal spectral data of the material, including the following sub-steps: Any infrared wavelength within the first wavelength range is denoted as the first wavelength. Based on the sample light intensity data and the reference light intensity data at the first test temperature, the sample reflected light intensity and the reference reflected light intensity corresponding to the first wavelength are obtained and denoted as AI and BI respectively in order. The apparent absorbance corresponding to the first wavelength is calculated as log(1 / R), where R = AI / BI. Based on the sample light intensity data and the control light intensity data at the first test temperature, the apparent absorbance corresponding to all infrared wavelengths within the first wavelength range is repeatedly calculated; and an infrared spectral feature map is established with the apparent absorbance as the vertical axis and the corresponding wavenumber as the horizontal axis, which is recorded as the infrared feature map of the sample at the first test temperature. Based on the infrared characteristic image of the sample at the first test temperature, the number of absorption peaks is obtained and recorded as the peak number. The peak position, peak intensity and half-width of each absorption peak are also obtained. After completion, the infrared spectral characteristics of the first test temperature are obtained. Repeatedly acquire the infrared spectral features corresponding to all test temperature points, and sort the number of peaks corresponding to all test temperature points in ascending order, and record it as the peak number sequence. For any two adjacent peak counts in the peak count sequence, if the two adjacent peak counts are not the same, the midpoint of the two adjacent peak counts is taken as the dividing point. All dividing points are obtained repeatedly to divide the peak count sequence into several subsequences, and the longest subsequence is denoted as the first subsequence. The temperature range corresponding to the first subsequence is denoted as the second temperature range, and the test temperature points within the second temperature range are denoted as the basic temperature points.

5. The method for extracting infrared spectral features of asteroid rocks according to claim 4, characterized in that, Obtaining the infrared spectral characteristics of asteroid rocks at different temperatures based on initial material light intensity data, and performing first feature analysis to obtain normal spectral data of the material, also includes the following sub-steps: Based on the infrared spectral characteristics of all basic temperature points, the absorption peaks in the infrared characteristic image of the sample at each basic temperature point are numbered sequentially according to the magnitude of the corresponding wavenumber, and are sequentially denoted as absorption peak 1 to absorption peak n. Any absorption peak is denoted as the first absorption peak, where n represents the total number of absorption peaks. Based on the infrared spectral characteristics of all basic temperature points, the peak position, peak intensity, and half-peak width of the first absorption peak at different basic temperature points are obtained respectively, and are recorded as feature set 1, feature set 2, and feature set 3 in sequence.

6. The method for extracting infrared spectral features of asteroid rocks according to claim 5, characterized in that, Obtaining the infrared spectral characteristics of asteroid rocks at different temperatures based on initial material light intensity data, and performing first feature analysis to obtain normal spectral data of the material, also includes the following sub-steps: Range acquisition processing is performed on feature set 1, feature set 2, and feature set 3 respectively. The range acquisition processing includes: Sort the data of any feature set in ascending order according to the corresponding basic temperature points, and denote this as the first feature sequence; then denote the data in the first feature sequence as C1-C1. m And denote any data as C i , where i represents the position number; Calculate C i The corresponding absolute fluctuation value AC i AC i =|C i+1 -C i |, Repeatedly calculate C1-C m-1 The corresponding absolute fluctuation value, and calculate C. i The corresponding volatility ratio BC i BC i =AC i+1 / AC i ; Repeatedly calculate C1-C m-2 The corresponding absolute volatility values ​​are calculated, and the mean and standard deviation are denoted as AP and BP respectively, in that order; if the volatility ratio is BC i If not located in [AP-k2*BP, AP-k2*BP], then mark C. i+1 For each transition point, repeat the acquisition of all transition points, where k2 is the set scaling factor; Remove the transition points of the first feature sequence, and divide the first feature sequence into several subsequences based on the position of the transition points, denoted as the preliminary subsequences; Calculate the correlation coefficient between the basic temperature point and the data for each preliminary subsequence; remove preliminary subsequences whose correlation coefficient is not located in [k3, k4], and denote the remaining preliminary subsequences as stable subsequences, where [k3, k4] is the set range; Let any stable subsequence be denoted as the first stable sequence, calculate the mean of the first stable sequence and denot it as DP, and obtain the maximum and minimum values ​​of the first stable sequence and denot them as AF and BF respectively in order; calculate the dispersion LD of the first stable sequence, where LD = (AF-BF) / BF*100%. Calculate the mean and standard deviation of the first stable sequence, denoted as AU and BU respectively; calculate the dispersion threshold YD of the first stable sequence; where YD = k5 * BU / AU * 100%, and k5 is the set scaling factor; If the dispersion LD of the first stable sequence is not greater than the corresponding dispersion threshold YD, then the first stable sequence is marked as a qualified subsequence. Repeatedly obtain all qualified subsequences and obtain the position of each qualified subsequence in the first feature sequence. If there is only one transition point between two qualified subsequences, merge the two qualified subsequences. After completion, obtain the temperature range of the basic temperature point corresponding to the qualified subsequence, and record it as the temperature range corresponding to the feature set.

7. The method for extracting infrared spectral features of asteroid rocks according to claim 6, characterized in that, Obtaining the infrared spectral characteristics of asteroid rocks at different temperatures based on initial material light intensity data, and performing first feature analysis to obtain normal spectral data of the material, also includes the following sub-steps: Repeatedly obtain the temperature ranges corresponding to feature set 1, feature set 2 and feature set 3, and find their intersection to obtain the temperature range corresponding to the first absorption peak; Repeatedly obtain the temperature range corresponding to absorption peak 1 to absorption peak n, and find the intersection. Record the intersection as the normal temperature range. Record the infrared spectral characteristics of the sample infrared feature map at the test temperature point within the normal temperature range as the normal spectral data of the substance.

8. The method for extracting infrared spectral features of asteroid rocks according to claim 7, characterized in that, The second feature analysis based on the normal spectral data of a substance, to obtain representative spectral data of the substance, includes the following sub-steps: Based on the normal spectral data of the substance, the peak position, peak intensity and half-width of the first absorption peak at each test temperature point within the normal temperature range are obtained, and then sorted according to the test temperature points from smallest to largest, and recorded as peak position sequence, peak intensity sequence and peak width sequence respectively. Set the sliding window size to k6 and the sliding step size to 1. Start sliding synchronously from the beginning position of the peak position sequence, peak intensity sequence and peak width sequence respectively, record the number of sliding, calculate the relative standard deviation of the data in each of the three moving windows for each sliding, and calculate the average value, which is recorded as the average deviation of this sliding. Sort all average deviations in ascending order of their corresponding number of slides, and denote this as the average deviation sequence. Calculate the average value of the average deviation sequence, and denote this as the deviation threshold. The average deviation in the average deviation sequence that is greater than the deviation threshold is denoted as the fluctuation deviation, and the average deviation in the average deviation sequence that is not greater than the deviation threshold is denoted as the stable deviation.

9. A method for extracting infrared spectral features of asteroid rocks according to claim 8, characterized in that, The second feature analysis based on the normal spectral data of a substance to obtain representative spectral data of the substance also includes the following sub-steps: Obtain a portion of the average deviation sequence consisting of continuous stable deviations, denoted as a stable subsequence, and denote the longest stable subsequence as the first stable sequence. Any stable deviation in the first stable sequence is denoted as the first deviation. The temperature range of the test temperature points contained in the sliding window corresponding to the first deviation is obtained and denoted as the window temperature range of the first deviation. Repeatedly obtain the window temperature range of all stable deviations in the first stable sequence, and find the union of them, which is denoted as the stable temperature range of the first absorption peak. Repeatedly obtain the stable temperature range of all absorption peaks, find the intersection, and record it as the representative temperature range. Record the infrared spectral characteristics of the sample infrared feature map at the test temperature point within the representative temperature range as the normal spectral data of the substance.

10. A method for extracting infrared spectral features of asteroid rocks according to claim 9, characterized in that, Infrared spectral feature extraction based on representative spectral data of materials to obtain the infrared spectral features of asteroid rocks includes the following sub-steps: Based on the representative spectral data of the substance, the peak position range, peak intensity range and half-width range of the first absorption peak in the corresponding representative temperature range are obtained, and the shape of the first absorption peak is obtained and recorded as the representative spectral characteristics of the first absorption peak. By repeatedly acquiring representative spectral characteristics of all absorption peaks, the corresponding infrared spectral characteristics of the asteroid rocks can be obtained.

Images