阅读说明：本技术 一种基于近红外反射光谱的绿泥石矿物种类鉴定方法 (Chlorite mineral species identification method based on near-infrared reflectance spectrum ) 是由 杨敏 徐友宁 周宁超 陈华清 柯海玲 叶美芳 董会 刘三 于 2019-08-12 设计创作，主要内容包括：本发明属于绿泥石矿物鉴定技术领域,公开了一种基于近红外反射光谱的绿泥石矿物种类鉴定方法,通过无损表面测量获取野外绿泥石矿物的近红外反射光谱；对光谱数据的平滑去噪处理,采用高斯-洛伦兹函数拟合进行特征吸收峰位置的确定；近红外反射光谱数据在数据处理终端中进行光谱曲线平滑数据预处理,经过光谱数据平滑环节的曲线进行特征吸收峰的分峰拟合与定位；依据特征吸收峰位置与绿泥石铁含量的线性统计关系,按照特征吸收峰位置快速鉴定绿泥石矿物的亚种类别。本发明可使野外工作人员实时得到蚀变带中绿泥石矿物的亚种信息,缩短了实验室岩矿鉴定所需的时间,节省了样品制备的步骤,省时省力,同时节省了经费。(The invention belongs to the technical field of chlorite mineral identification, and discloses a chlorite mineral type identification method based on near-infrared reflectance spectrum, which obtains the near-infrared reflectance spectrum of field chlorite mineral through nondestructive surface measurement; smooth denoising processing is carried out on the spectral data, and the position of a characteristic absorption peak is determined by adopting Gaussian-Lorentz function fitting; performing spectral curve smoothing data preprocessing on the near-infrared reflection spectral data in a data processing terminal, and performing peak-splitting fitting and positioning on a characteristic absorption peak through a curve of a spectral data smoothing link; and rapidly identifying the subspecies of the chlorite mineral according to the linear statistical relationship between the characteristic absorption peak position and the chlorite iron content and the characteristic absorption peak position. The method can enable field workers to obtain subspecies information of the chlorite mineral in the altered zone in real time, shorten the time required by laboratory rock and ore identification, save the steps of sample preparation, save time and labor, and save cost at the same time.)

1. The chlorite mineral species identification method based on the near-infrared reflectance spectrum is characterized in that the chlorite mineral species identification method based on the near-infrared reflectance spectrum obtains the near-infrared reflectance spectrum of a field chlorite mineral through nondestructive surface measurement; in the near-infrared reflection spectrum measurement link, a spectrometer probe directly contacts the surface of a sample to measure data and inputs the data into a connected data processing terminal, a self-adaptive filter is adopted to carry out smooth denoising processing on spectrum data, and Gaussian-Lorentz function fitting is adopted to determine the position of a characteristic absorption peak; performing spectral curve smoothing data preprocessing on the near-infrared reflection spectral data in a data processing terminal, and performing peak-splitting fitting and positioning on a characteristic absorption peak through a curve of a spectral data smoothing link; and rapidly identifying the subspecies of the chlorite mineral according to the linear statistical relationship between the characteristic absorption peak position and the chlorite iron content and the characteristic absorption peak position.

2. The method of identifying chlorite mineral species based on near infrared reflectance spectrum according to claim 1, wherein said method of identifying chlorite mineral species based on near infrared reflectance spectrum comprises certain aids:

firstly, cleaning the surface of a rock sample containing chlorite minerals, and performing spectral measurement on the surface of the chlorite sample without sample preparation by using a portable near-infrared reflection spectrum measuring instrument;

secondly, smoothing the spectral data based on a Savitzky-Golay convolution smoothing method after spectral measurement;

thirdly, fitting and peak searching by using a Lorentzian-Gaussian peak-splitting fitting method, and fitting the obtained curve and the actually measured curve correlation coefficient r²Not less than 0.95, two characteristic absorption peaks of chlorite;

fourthly, distinguishing iron-rich chlorite and magnesium-rich subspecies according to the positions of the characteristic peaks.

3. The method for identifying mineral species in chlorite according to claim 2, wherein in the first step, an artificial light source is used, and a spectrometer probe is contacted with the surface of an unformulated chlorite sample to perform spectral measurement.

4. The method for identifying the mineral species of the chlorite based on the near-infrared reflectance spectrum as claimed in claim 2, wherein in the second step, the spectral data smoothing is performed based on a Savitzky-Golay convolution smoothing method, and a smoothing window is selected from 10 to 50.

5. The method for identifying a mineral species in chlorite according to claim 2, wherein chlorite has two characteristic absorption peaks at 2253nm and 2345nm in chlorite in the third step.

6. The method for identifying a mineral type of chlorite as claimed in claim 2, wherein the MgFe-rich chlorite in the fourth step is a method for mineralogically distinguishing Fe-MgCl by measuring Fe-Mg content of a MgFe-rich series sample using an electronic probe, calculating Fe/Fe + Mg values, i.e., Fe/Fe + Mg >0.75 as a Ferro-rich subspecies, Fe/Fe + Mg <0.75 as an intermediate subspecies, and Fe/Fe + Mg <0.25 as a Mgo subspecies.

7. The method of identifying chlorite mineral species based on near infrared reflectance spectroscopy as claimed in claim 6, further comprising:

(1) classification was done with a characteristic absorption peak position around 2253 nm: when the characteristic absorption peak position is less than 2248.45nm, the chlorite is rich in magnesium and poor in iron, when the characteristic absorption peak position is between 2248.45nm and 2259.63nm, the chlorite is intermediate, and when the characteristic absorption peak position is more than 2259.63nm, the chlorite is rich in iron and poor in magnesium;

(2) the classification was made with a characteristic absorption peak position around 2345 nm: when the characteristic absorption peak position is less than 2333.72nm, the chlorite is rich in magnesium and poor in iron, when the characteristic absorption peak position is between 2333.72nm and 2357.38nm, the chlorite is intermediate, and when the characteristic absorption peak position is more than 2357.38nm, the chlorite is rich in iron and poor in magnesium.

8. A chlorite mineral species identification device to which the near-infrared reflectance spectrum-based chlorite mineral species identification method according to any one of claims 1 to 7 is applied.

Technical Field

The invention belongs to the technical field of chlorite mineral identification, and particularly relates to a chlorite mineral type identification method based on near-infrared reflectance spectrum.

Background

At present, the identification of chlorite mineral iron-rich magnesium-poor and magnesium-rich iron-poor subspecies mainly depends on electron probe micro-area analysis: the electron probe apparatus irradiates the surface of a sample with a finely focused electron beam, thereby exciting X-rays of sample elements, and then detects the wavelength, intensity, etc. of the rays using a wavelength dispersion spectrum detection device and a counting system, thereby obtaining the element types and proportions of the respective samples. Analysis of the wavelength, or characteristic energy, of the radiation gives rise to the specific elements of the sample, which is typical of qualitative analysis, while in combination with the intensity of the radiation, the proportion of the corresponding elements is obtained, which is typical of quantitative analysis. The lens barrel component of the detection device has a structure substantially consistent with that of an electron microscope. Only in the detection device link, an X-ray spectrum device is used, and by means of the X-ray spectrum device, the characteristic wavelength and energy of the ray are detected, so that the chemical components of the micro-area can be developed and analyzed. Therefore, besides the special electronic probe device, the probe device can be used as an accessory and arranged on a lens cone of a scanning or transmission electron microscope, thereby better meeting the comprehensive analysis requirements of the microstructure morphology, the chemical composition and the crystal structure of the micro-area. Moreover, the analysis mode does not need to break the sample, and the analysis diameter and the analysis depth of the sample are all more than 1 micron, and the atomic coefficient is more than 4. However, if the ordinal number of the element is lower than 12, the detecting device lacks a corresponding sensitivity. In conventional detection, the relative sensitivity of the device can reach one ten thousandth, and a part of environment is one hundred thousandth higher. The absolute sensitivity of detection will vary from element to element, typically between 10-14 and 10-16 g. By means of the method, the elements can be analyzed from three visual angles of points, surfaces and lines, and if the atomic number exceeds 10 and the proportion exceeds 10.0 percent, the accuracy of quantitative analysis can exceed plus or minus 2.0 percent.

The existing electronic probe equipment is firstly applied to the metal field. The method mainly carries out qualitative and quantitative analysis on a plurality of elements such as composition phases, impurities and the like in the alloy, and can solve the problems of diffusion, segregation and the like of the elements. In addition, the device is widely applied to the field of metal material oxidation and corrosion problems, can correspondingly measure the thickness and components of a plating layer and a film, and is also a common mode for selecting a process, analyzing a special material, analyzing the failure of a mechanical part and the like. With this analysis, the chemical composition of the sample, as well as the weight percentages of the various elements, can be obtained. Before specific analysis, the corresponding samples are prepared according to the purpose of experiment, and meanwhile, the surfaces of the samples are required to have certain cleanliness. When analyzing a sample with the aid of a spectrometer, it is necessary to ensure that the sample has a flatness, which otherwise affects the intensity of the X-rays.

The problems of the current electronic probe device are as follows:

(1) the existing electronic probe equipment belongs to a large-scale laboratory instrument, has high accuracy, but can not carry out field test, and can not carry out miniaturized design.

(2) The sample of the existing electronic probe test needs to grind a probe sheet and can not be directly tested.

(3) In the prior art, a method for subdividing mineral subclasses by using near-infrared reflection spectrum is not available; the subspecies information of the chlorite mineral in the altered zone can not be obtained by field workers in real time, the laboratory rock and ore identification consumes time and labor, the step of sample preparation can not be saved, and the cost is high.

(4) Mineral subclasses can not be identified in the existing field.

The difficulty of solving the technical problems is as follows: the electron probe instrument has precise and complex structure, and comprises an electron gun, a focusing and accelerating element, an X-ray detection device, a vacuum sample chamber and the like. Therefore, direct attempts to miniaturize the electronic probe instrument are not feasible. The portable near-infrared spectrometer is a field spectrum testing instrument newly developed in nearly 10 years, can meet the requirements of field testing and analysis, and has sensitive reflection on the types and contents of the phyllosilicate mineral class homomorphic replacement ions. Therefore, the method for identifying the chlorite mineral rich in magnesium and poor in iron and rich in iron and poor in magnesium is feasible by utilizing the portable near infrared spectrum equipment.

The significance of solving the technical problems is as follows: the near-infrared reflection spectrum analysis technology has the advantages and characteristics of rapidness, convenience, greenness and environmental protection. The formed chlorite identifying method for the subspecies rich in iron and magnesium and rich in magnesium and iron fully utilizes the characteristics of near-infrared reflection spectrum, can meet the working requirement of identifying and identifying in the field, greatly reduces the cost of traditional experimental tests, saves manpower and material resources, and has remarkable economic benefit and environmental benefit.

Disclosure of Invention

Aiming at the problems in the prior art, the invention provides a chlorite mineral species identification method based on near-infrared reflectance spectrum.

The invention is realized by the method for identifying the chlorite mineral type based on the near-infrared reflectance spectrum, which obtains the near-infrared reflectance spectrum of the field chlorite mineral through nondestructive surface measurement; in the near-infrared reflectance spectrum measurement link, a spectrometer probe directly contacts the surface of a sample to measure data, the data is input into a connected data processing terminal, the smooth de-noising processing of the spectral data is carried out by adopting a Savitzky-Golay convolution smoothing method, and the determination of the position of a characteristic absorption peak is carried out by adopting Gaussian-Lorentz function fitting; performing spectral curve smoothing data preprocessing on the near-infrared reflection spectral data in a data processing terminal, and performing peak-splitting fitting and positioning on a characteristic absorption peak through a curve of a spectral data smoothing link; and rapidly identifying the subspecies of the chlorite mineral according to the linear statistical relationship between the characteristic absorption peak position and the chlorite iron content and the characteristic absorption peak position.

Further, the method for identifying chlorite mineral species based on near-infrared reflection spectrum comprises some aids:

firstly, cleaning the surface of a rock sample containing chlorite minerals, and performing spectral measurement on the surface of the chlorite sample without sample preparation by using a portable near-infrared reflection spectrum measuring instrument;

secondly, after the spectrum measurement, performing spectrum data smoothing treatment based on a Savitzky-Golay convolution smoothing method, wherein the Savizky-Golay convolution smoothing is a weighted average algorithm of a moving window, and a weighting coefficient of the Savizky-Golay convolution smoothing is not simply a constant window but is obtained by least square fitting of a given high-order polynomial in the window;

and thirdly, fitting and searching peaks by using a Lorentzian-Gaussian peak-splitting fitting method, wherein two-dimensional spectrums such as spectrograms have definite physical meanings and can be described by using Lorentzian-Gaussian functions, so that parameters with physical meanings such as peak shapes, peak positions, peak heights, peak areas and the like of the spectrums can be expressed by using parameters of the Lorentzian-Gaussian functions. Correlation coefficient r of curve obtained by fitting and actually measured curve²Not less than 0.95, two characteristic absorption peaks of chlorite;

fourthly, distinguishing iron-rich chlorite and magnesium-rich subspecies according to the positions of the characteristic peaks.

Further, in the first step, an artificial light source is adopted, and a spectrometer probe is contacted with the surface of the chlorite sample which is not subjected to sample preparation to carry out spectral measurement.

Further, in the second step, the spectral data smoothing is carried out based on a Savitzky-Golay convolution smoothing method, and a smoothing window is selected to be 10-50.

Further, the chlorite in the third step has two characteristic absorption peaks, which are near 2253nm and 2345nm, respectively.

Further, the Mg-rich iron-rich chlorite in the fourth step is a method for testing the Fe-Mg content of the Mg-rich iron series samples by using an electronic probe, calculating the Fe/Fe + Mg value and distinguishing the Fe-Mg chlorite according to the mineralogy, namely Fe/Fe + Mg >0.75 is an Fe-rich subspecies, Fe/Fe + Mg <0.25 <0.75 is an intermediate subspecies, and Fe/Fe + Mg <0.25 is an Mg-rich subspecies.

Further comprising:

(1) classification was done with a characteristic absorption peak position around 2253 nm: when the characteristic absorption peak position is less than 2248.45nm, the chlorite is rich in magnesium and poor in iron, when the characteristic absorption peak position is between 2248.45nm and 2259.63nm, the chlorite is intermediate, and when the characteristic absorption peak position is more than 2259.63nm, the chlorite is rich in iron and poor in magnesium;

(2) the classification was made with a characteristic absorption peak position around 2345 nm: when the characteristic absorption peak position is less than 2333.72nm, the chlorite is rich in magnesium and poor in iron, when the characteristic absorption peak position is between 2333.72nm and 2357.38nm, the chlorite is intermediate, and when the characteristic absorption peak position is more than 2357.38nm, the chlorite is rich in iron and poor in magnesium.

Another object of the present invention is to provide a chlorite mineral species identification apparatus to which the near-infrared reflection spectrum-based chlorite mineral species identification method is applied.

In summary, the advantages and positive effects of the invention are: the method utilizes the characteristics of the relationship between the positions of two characteristic absorption peaks of the chlorite mineral near-infrared reflection spectrum and the iron-magnesium content in the range of 2100-2400nm, and meets the requirement of rapidly identifying the chlorite mineral subspecies in the field through field near-infrared reflection spectrum measurement, spectrum data preprocessing, chlorite characteristic absorption peak positioning identification, chlorite subspecies attribution judgment and the like.

The invention utilizes the characteristics that the near-infrared reflectance spectrum does not need sample preparation, the field rapid measurement and the real-time near-infrared spectrum analysis of the minerals are carried out; the method can enable field workers to obtain subspecies information of the chlorite mineral in the altered zone in real time, shortens the time required by laboratory rock and ore identification (the single-point test time of the traditional electronic probe is 30 seconds, and the single-point test time of the near infrared test is 0.1 second), saves the steps of sample preparation of the traditional electronic probe, saves time and labor, and saves the expenditure (the single sample can save the sample preparation cost by 80 yuan).

The method mainly uses a near-infrared reflection spectrum analysis technology to identify the chlorite iron-rich magnesium-lean iron subspecies by taking the chlorite iron-rich magnesium-lean iron subspecies as an identification object and identifying the chlorite iron-rich magnesium-lean iron subspecies according to the linear relation between the iron-magnesium content in the chlorite mineral and the characteristic absorption peak position of the near-infrared reflection spectrum. The set of experimental test method mainly aims at the condition limitations that the traditional chlorite subspecies identification method needs sample grinding and preparation, can only carry out identification in a laboratory and the like, and adopts the portable near-infrared reflection spectrum technology to realize the real-time chlorite mineral subspecies identification in the field. The method has the advantages of shorter time (30 seconds for testing the electronic probe by a single sample and 0.1 second for near infrared testing) than the conventional electronic probe test, reduced sample preparation procedures, and saved labor cost and test expenditure (80 yuan for sample preparation cost for a single sample).

Drawings

Fig. 1 is a flowchart of a method for identifying a mineral type of chlorite based on a near infrared reflectance spectrum according to an embodiment of the present invention.

Fig. 2 is a schematic flow chart of a method for identifying a mineral type of chlorite based on a near-infrared reflection spectrum according to an embodiment of the invention.

Fig. 3 is a schematic diagram illustrating the determination of iron-rich and magnesium-rich subspecies of chlorite according to an embodiment of the present invention.

FIG. 4 is a graph of the spectrum of the Eugonite copper ore obtained by the specific application of the embodiment of the present invention.

FIG. 5 is a graph of the spectrum of the Eugonite copper ore obtained by the specific application of the embodiment of the present invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Aiming at the problems in the prior art, the invention provides a method for identifying the mineral species of chlorite based on near-infrared reflection spectrum, which is described in detail below with reference to the accompanying drawings.

As shown in fig. 1, the method for identifying a chlorite mineral type based on a near-infrared reflectance spectrum provided by an embodiment of the invention comprises the following steps:

s101: cleaning the surface of a rock sample containing chlorite minerals, and performing spectral measurement on the surface of the chlorite sample without sample preparation by using a portable near-infrared reflection spectrum measuring instrument;

s102: after the spectrum measurement, performing spectrum data smoothing treatment based on a Savitzky-Golay convolution smoothing method;

s103: fitting and peak searching by using a Lorentzian-Gaussian peak-splitting fitting method, and fitting the obtained curve and the actually measured curve correlation coefficient r²Not less than 0.95, two characteristic absorption peaks of chlorite;

s104: and distinguishing iron-rich and magnesium-rich subspecies of chlorite according to the positions of the characteristic peaks.

The technical solution of the present invention is further described below with reference to the accompanying drawings.

As shown in fig. 2, the method for identifying a chlorite mineral type based on a near-infrared reflectance spectrum provided by the embodiment of the invention specifically includes the following steps:

the method comprises the steps of firstly, collecting a rock sample containing chlorite minerals in the field, cleaning the surface, and carrying out spectral measurement by contacting a spectrometer probe with the surface of the chlorite sample which is not subjected to sample preparation by using a portable near-infrared reflection spectral measurement instrument and an artificial light source.

And secondly, after the spectral measurement is finished, smoothing the spectral data based on a Savitzky-Golay convolution smoothing method, wherein a smoothing window is selected to be 10-50. If the window selection is too small, the smoothing effect cannot be achieved, and if the window selection is too large, the data will be distorted.

Thirdly, fitting and peak searching are carried out on the near-infrared reflection spectrum characteristic absorption peak position of the chlorite mineral by using a Lorentzian-Gaussian peak-splitting fitting method, and the correlation coefficient r between the curve obtained by fitting and the actually measured curve²Not less than 0.95, the chlorite has two characteristic absorption peaks which are respectively positioned near 2253nm and 2345 nm; the other absorption peaks obtained by fitting are not characteristic absorption peaks.

Fourthly, distinguishing iron-rich chlorite and magnesium-rich subspecies according to the positions of the characteristic peaks.

In a preferred embodiment of the present invention, the Mg-rich siderite in step four is a method for mineralogically differentiating Fe-Mg chlorite by measuring the Fe-Mg content of a Mg-rich series of samples by using an electronic probe, calculating the Fe/(Fe + Mg) value, i.e., Fe/(Fe + Mg) >0.75 is a siderite, 0.25< Fe/(Fe + Mg) <0.75 is an intermediate siderite, and Fe/(Fe + Mg) <0.25 is a siderite. Referring to the relationship between the Fe/(Fe + Mg) value and the projection diagram (figure 3) of the position of the chlorite characteristic band, the step of distinguishing the chlorite iron-rich and magnesium-rich subspecies according to the position of the characteristic peak comprises the following steps:

(1) classification was done with a characteristic absorption peak position around 2253 nm: when the characteristic absorption peak position is less than 2248.45nm, the chlorite is rich in magnesium and poor in iron, when the characteristic absorption peak position is between 2248.45nm and 2259.63nm, the chlorite is intermediate, and when the characteristic absorption peak position is more than 2259.63nm, the chlorite is rich in iron and poor in magnesium;

(2) the classification was made with a characteristic absorption peak position around 2345 nm: when the characteristic absorption peak position is less than 2333.72nm, the chlorite is rich in magnesium and poor in iron, when the characteristic absorption peak position is between 2333.72nm and 2357.38nm, the chlorite is intermediate, and when the characteristic absorption peak position is more than 2357.38nm, the chlorite is rich in iron and poor in magnesium.

In the preferred embodiment of the invention, the near-infrared reflection spectrum of the rock sample containing chlorite minerals is measured in real time in the field by a portable near-infrared reflection spectrometer, the peaks are found by data preprocessing and characteristic absorption peak fitting, and finally, the chlorite is identified as being rich in iron and magnesium or rich in magnesium and iron subspecies according to the position of the characteristic peaks. Because the near-infrared reflection spectrometer can carry out field measurement and analysis, the workload of indoor rock and ore identification can be greatly reduced, and the efficiency of field geological investigation work is improved.

The method provided by the invention has good effect after being verified by practical application. The following examples are given for specific analyses.

1. Fifty-eight ditch iron-rich chlorite verification point

The verification point is located at the south 7 kilometers of the scenic spot of the Xiwang Muyao pool on the G219 highway of the national road, and is a tough shear band in geology. The lithology of the investigation point mainly comprises mylonite, marble, slate and phyllite, which are mainly located in the grayish green color-changed sandstone.

Spectral measurements of point grayish green sandstone showed 7 absorption peaks: 600-1200nm has 3 absorption peaks which are the absorption peaks of iron ions, and the peak shape is mild; an absorption peak of water is near 1400nm and 1890-2020 nm; 2260nm is an obvious absorption peak at the center, namely an (AlAl) O-OH absorption peak; the band centered at 2357nm is the (SiAl) O-OH absorption peak, with a deeper peak shape than the previous one (FIG. 4). According to the invention, iron-rich chlorite can be classified. The results are consistent with the high iron content shown by the simple analysis of the sample. Table 1 shows the simple analysis results of fifty-eight grooves and west beach north ductile shear band.

TABLE 1 simple analysis results of fifty-eight channels and west Dai North tough shear band

2. Zhongyangshan lean iron chlorite verification point

The inspection points are located 15 km east of the Yuzhu peak glacier sightseeing spot on the national G219 road, and the Kunlun mountain main ridge is located on the north side of the northern east great beach.

The point rock spectra were confirmed to have mainly 5 spectral absorption peaks (fig. 5): two iron ion absorption peaks are arranged near 800nm at 600-; two water absorption peaks are near 1400nm and 1880-1975 nm; a small (AlAl) O-OH absorption peak is arranged near 2248 nm; near 2333nm is the (SiAl) O-OH absorption peak (FIG. 5), which can be scribed into Mg-rich lean iron chlorite according to the present invention.

Meanwhile, simple analysis of collected samples shows that the iron content is not high, and the iron content is expressed as an iron-poor environment and is the same as a near-infrared discrimination result. As shown in table 2:

TABLE 2 SANYANGSHAN CHECK POINT AND SIMPLE ITEM ANALYSIS RESULT TABLE

The above description is only for the purpose of illustrating the preferred embodiments of the present invention and is not to be construed as limiting the invention, and any modifications, equivalents and improvements made within the spirit and principle of the present invention are intended to be included within the scope of the present invention.