Bedrock area lithology classification method suitable for engineering geological investigation

Abstract

The invention discloses a bedrock area lithology classification method suitable for engineering geological investigation. Rock has complex mineral components and contents, so that the recognition precision is influenced by directly utilizing spectral curve characteristics to recognize and classify the rock. The method comprises the following steps: testing and determining rock types and rock mechanical parameters; testing the rock sample by using an imaging spectrometer to obtain a spectral curve and typical spectral characteristics; combining the rock mechanics parameters with the typical spectral characteristics, and determining a typical rock mechanics-spectrum classification method based on the rock mechanics parameters and the typical spectral characteristics; and finally, acquiring a rock spectrum curve by using airborne hyperspectral equipment, and identifying and classifying the rocks in the bedrock area. According to the invention, the type of the rock can be rapidly positioned, and the lithology can be accurately identified and classified in the exploration process.

Description

Technical Field

[0001] The invention belongs to the technical field of engineering survey, and in particular relates to a lithology classification method for bedrock areas suitable for engineering geological survey. Background Art

[0002] In extremely complex and dangerous mountainous areas and foreign regions with weak basic geological surveys, the environment is harsh and the geological conditions are complex. Accurate identification of rock types is an urgent problem to be solved. With the development of remote sensing technology, quantitative analysis of spectral absorption characteristic parameters has become one of the important methods for rock type identification. According to the differences in spectral characteristic parameters of different rocks, various rock types can be identified and classified.

[0003] However, due to the complex mineral composition and content of rocks, rocks have similar spectral curves and absorption characteristics. Therefore, directly using spectral curve characteristics to identify and classify rocks will affect the recognition accuracy. Therefore, it is necessary to construct a lithology classification method for bedrock areas suitable for engineering geological surveys, so as to achieve rapid and accurate identification and classification of bedrock in the survey area, effectively improve the efficiency of field surveys, and save survey costs. Summary of the invention

[0004] In order to make up for the shortcomings of the prior art, the present invention provides a lithology classification method for bedrock areas suitable for engineering geological surveys. During the engineering survey stage, the method can be used to quickly and accurately identify and classify the bedrock in the survey area, thereby improving survey efficiency and saving costs.

[0005] In order to achieve the above object, the technical solution adopted by the present invention is:

[0006] A bedrock area lithology classification method suitable for engineering geological survey, characterized in that it specifically comprises the following steps:

[0007] S1: Collect typical rock samples in the field and determine the rock type and rock mechanical parameters through testing;

[0008] S2: using an imaging spectrometer to test the typical rock samples collected in step S1 to obtain a spectral curve and typical spectral characteristics;

[0009] S3: combining the rock mechanical parameters determined in step S1 and the typical spectral features determined in step S2 to determine a typical rock mechanical-spectral classification method based on the rock mechanical parameters and the typical spectral features;

[0010] S4: According to the typical rock mechanics-spectral classification method determined in step S3, the rock spectrum curve is obtained by using airborne hyperspectral equipment to identify and classify the rocks in the bedrock area.

[0011] Further, the specific method of step S1 is:

[0012] S1-1: Statistics of common rock types in railway engineering and selection of typical rock types;

[0013] S1-2: Collect fresh rock samples of typical rock types, conduct rock and mineral identification and test to obtain the uniaxial saturated compressive strength of the rock.

[0014] Further, the specific method of step S2 is:

[0015] S2-1: Use an imaging spectrometer to test the typical rock collected in step S1 to obtain a typical rock spectrum curve;

[0016] S2-2: Extract and analyze the spectral features of the spectral curve collected in step S2-1 to determine the specific spectral feature information of each rock.

[0017] Further, the specific method of step S3 is:

[0018] S3-1: Based on the uniaxial saturated compressive strength of the rock tested in step S1, the rock is classified into strength grades from an engineering perspective;

[0019] S3-2: On the basis of rock strength classification, according to the typical spectral characteristics determined in S2, based on the similarity of spectral curves and the analysis of characteristic bands of spectral curves, rocks with relatively similar spectral curves and obviously similar absorption characteristic bands are classified into one category, thereby establishing a typical rock mechanics-spectral classification method;

[0020] S3-3: According to the typical rock mechanics-spectral classification method determined in step S3-2, a typical rock spectrum sample library including rock mechanics parameters, typical rock spectrum curves and their absorption characteristics is constructed.

[0021] Further, the specific method of step S4 is:

[0022] S4-1: Use an airborne imaging spectrometer to scan the rocks in the surveyed bedrock area to obtain its imaging spectrum;

[0023] S4-2: Process and analyze the spectral data obtained by S4-1, and match the processed spectral curve with the constructed typical rock spectral sample library to achieve rapid and accurate identification and classification of the bedrock in the survey area.

[0024] Furthermore, in step S3-1, rocks are divided into the following categories according to their strength grades: high-strength rocks (uniaxial saturated compressive strength>60MPa); medium-strength rocks (uniaxial saturated compressive strength30-60MPa); low-strength rocks (uniaxial saturated compressive strength15-30MPa); and extremely low-strength rocks (uniaxial saturated compressive strength<15MPa).

[0025] Furthermore, in step S2-1, the typical rock collected in step S1 is tested using an imaging spectrometer to obtain its spectral curve from different angles and environmental conditions. Each rock sample is collected 5 times and the final typical rock spectral curve is obtained by averaging.

[0026] Further, in step S3-2, the relatively similar spectral curves are specifically:

[0027] 1) The overall change trend of the rock spectrum curve is similar. By calculating the cosine similarity of the two spectrum curves, the value range is between -1 and 1;

[0028] 2) Similar spectral features: by counting the number of obvious absorption characteristic bands in each spectral curve and calculating the standard deviation of the characteristic band positions, spectra with similar numbers of absorption bands and standard deviations of characteristic band positions less than 5nm are considered to have similar spectral features and can be classified into one category.

[0029] Beneficial effects of the present invention:

[0030] 1) The present invention establishes a classification method based on typical rock mechanics and rock spectra, and constructs a typical rock spectrum sample library including rock mechanics parameters, typical rock spectrum curves and their absorption characteristics;

[0031] 2) During the survey, the bedrock of the survey area is first scanned by hyperspectral imaging using airborne hyperspectral equipment, and the obtained rock spectrum curve is matched with the constructed typical rock spectrum sample library to quickly locate the type of rock, thereby saving a lot of manpower and material costs. At the same time, complex environments and major engineering surveys such as plateau mountainous areas, border crossings, and deep-earth development face many difficulties such as inaccessibility, inaccurate exploration, and unclear identification. The use of this classification method can better solve the problem of accurate identification and classification of lithology during the survey process. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is the operation flow chart of the present invention;

[0033] Figure 2 A schematic diagram of a typical rock mechanics-spectral classification method of the present invention;

[0034] Figure 3 It is a schematic diagram of absorption characteristic parameters of the spectrum curve of the present invention. DETAILED DESCRIPTION

[0035] The present invention is described in detail below in conjunction with specific implementation modes.

[0036] The present invention relates to a typical rock mechanics-spectral classification method, which is suitable for rapid identification and classification of lithology in bedrock areas of engineering geological surveys; Figure 1 As shown, the present invention specifically includes the following steps:

[0037] S1: Collect typical rock samples in the field and determine the rock type and rock mechanical parameters through testing; the specific method of step S1 is:

[0038] S1-1: Statistics of common rock types in railway engineering and selection of typical rock types;

[0039] S1-2: Collect fresh rock samples of typical rock types, conduct rock and mineral identification and test to obtain the uniaxial saturated compressive strength of the rock;

[0040] S2: Use an imaging spectrometer to test the typical rock samples collected in step S1 to obtain spectral curves and typical spectral features, such as Figure 3 As shown; the specific method of step S2 is:

[0041] S2-1: Use an imaging spectrometer to test the typical rock collected in step S1, and obtain its spectral curve from different angles and environmental conditions. Each rock sample is collected 5 times, and the final typical rock spectral curve is obtained by averaging;

[0042] S2-2: extracting and analyzing the spectral characteristics of the spectral curve collected in step S2-1 to determine the specific spectral characteristic information of each rock;

[0043] S3: Combining the rock mechanical parameters determined in step S1 with the typical spectral features determined in step S2, determining a typical rock mechanical-spectral classification method based on the rock mechanical parameters and the typical spectral features, such as Figure 2 As shown; the specific method of step S3 is:

[0044] S3-1: Based on the uniaxial saturated compressive strength of the rock tested in step S1, the rock is classified into strength grades from an engineering perspective; the rock is divided into the following categories according to its strength grade:

[0045] High-strength rock (uniaxial saturated compressive strength>60MPa); medium-strength rock (uniaxial saturated compressive strength 30-60MPa); low-strength rock (uniaxial saturated compressive strength 15-30MPa); extremely low-strength rock (uniaxial saturated compressive strength <15MPa);

[0046] S3-2: On the basis of rock strength classification, according to the typical spectral characteristics determined in S2, based on the similarity of spectral curves and the analysis of characteristic bands of spectral curves, rocks with relatively similar spectral curves and obviously similar absorption characteristic bands are classified into one category, thereby establishing a typical rock mechanics-spectral classification method;

[0047] Similar spectral curves are specifically manifested as follows: 1) The overall change trend of the rock spectral curve is similar. By calculating the cosine similarity of the two spectral curves, the value range is between -1 and 1. The closer the value is to 1, the more similar they are. 2) Similar spectral features. By counting the number of obvious absorption characteristic bands in each spectral curve and calculating the standard deviation of the characteristic band position, spectra with similar absorption band numbers and a standard deviation of the characteristic band position less than 5nm are considered to have similar spectral features and can be classified into one category.

[0048] S3-3: According to the typical rock mechanics-spectral classification method determined in step S3-2, a typical rock spectrum sample library including rock mechanics parameters, typical rock spectrum curves and their absorption characteristics is constructed;

[0049] S4: According to the typical rock mechanics-spectral classification method determined in step S3, the rock spectrum curve is obtained by using airborne hyperspectral equipment to identify and classify the rocks in the bedrock area;

[0050] The specific method of step S4 is:

[0051] S4-1: Use an airborne imaging spectrometer to scan the rocks in the surveyed bedrock area to obtain its imaging spectrum;

[0052] S4-2: Process and analyze the spectral data obtained by S4-1, and match the processed spectral curve with the constructed typical rock spectral sample library to achieve rapid and accurate identification and classification of the bedrock in the survey area.

[0053] The content of the present invention is not limited to the embodiments listed, and any equivalent changes made to the technical solution of the present invention by ordinary technicians in this field after reading the description of the present invention are covered by the claims of the present invention.

Claims

1. A bedrock lithology classification method suitable for engineering geological survey, characterized by: The specific steps include: S1: Collect typical rock samples in the field and determine the rock type and rock mechanical parameters through testing; S2: using an imaging spectrometer to test the typical rock samples collected in step S1 to obtain a spectral curve and typical spectral characteristics; S3: combining the rock mechanical parameters determined in step S1 and the typical spectral features determined in step S2 to determine a typical rock mechanical-spectral classification method based on the rock mechanical parameters and the typical spectral features; S4: According to the typical rock mechanics-spectral classification method determined in step S3, the rock spectrum curve is obtained by using airborne hyperspectral equipment to identify and classify the rocks in the bedrock area.

2. The method for lithology classification of bedrock areas suitable for engineering geological survey according to claim 1 is characterized by: The specific method of step S1 is: S1-1: Statistics of common rock types in railway engineering and selection of typical rock types; S1-2: Collect fresh rock samples of typical rock types, conduct rock and mineral identification and test to obtain the uniaxial saturated compressive strength of the rock.

3. The method for lithology classification of bedrock areas suitable for engineering geological survey according to claim 2 is characterized by: The specific method of step S2 is: S2-1: Use an imaging spectrometer to test the typical rock collected in step S1 to obtain a typical rock spectrum curve; S2-2: Extract and analyze the spectral features of the spectral curve collected in step S2-1 to determine the specific spectral feature information of each rock.

4. The method for lithology classification of bedrock areas suitable for engineering geological survey according to claim 3 is characterized by: The specific method of step S3 is: S3-1: Based on the uniaxial saturated compressive strength of the rock tested in step S1, the rock is classified into strength grades from an engineering perspective; S3-2: On the basis of rock strength classification, according to the typical spectral characteristics determined in S2, based on the similarity of spectral curves and the analysis of characteristic bands of spectral curves, rocks with relatively similar spectral curves and obviously similar absorption characteristic bands are classified into one category, thereby establishing a typical rock mechanics-spectral classification method; S3-3: According to the typical rock mechanics-spectral classification method determined in step S3-2, a typical rock spectrum sample library including rock mechanics parameters, typical rock spectrum curves and their absorption characteristics is constructed.

5. The method for lithology classification of bedrock areas suitable for engineering geological survey according to claim 4 is characterized by: The specific method of step S4 is: S4-1: Use an airborne imaging spectrometer to scan the rocks in the surveyed bedrock area to obtain its imaging spectrum; S4-2: Process and analyze the spectral data obtained by S4-1, and match the processed spectral curve with the constructed typical rock spectral sample library to achieve rapid and accurate identification and classification of the bedrock in the survey area.

6. A bedrock area lithology classification method suitable for engineering geological survey according to claim 5, characterized in that: In step S3-1, rocks are divided into the following categories according to their strength levels: high-strength rocks (uniaxial saturated compressive strength>60MPa); medium-strength rocks (uniaxial saturated compressive strength30-60MPa); low-strength rocks (uniaxial saturated compressive strength15-30MPa); and extremely low-strength rocks (uniaxial saturated compressive strength<15MPa).

7. A bedrock area lithology classification method suitable for engineering geological survey according to claim 6, characterized in that: In step S2-1, the typical rock collected in step S1 is tested using an imaging spectrometer to obtain its spectral curve from different angles and environmental conditions. Each rock sample is collected 5 times and the final typical rock spectral curve is obtained by averaging.

8. The method for lithology classification of bedrock areas suitable for engineering geological survey according to claim 7 is characterized by: In step S3-2, the relatively similar spectral curves are specifically: 1) The overall change trend of the rock spectrum curve is similar. By calculating the cosine similarity of the two spectrum curves, the value range is between -1 and 1; 2) Similar spectral features: by counting the number of obvious absorption characteristic bands in each spectral curve and calculating the standard deviation of the characteristic band positions, spectra with similar numbers of absorption bands and standard deviations of characteristic band positions less than 5nm are considered to have similar spectral features and can be classified into one category.

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