Data enhancement method and system based on static sounding curve image

Abstract

The invention relates to the technical field of geotechnical investigation data processing, and provides a data enhancement method and system based on a static sounding curve image. The method comprises the following steps: acquiring original data obtained by a static sounding test, dividing each drill hole according to different soil types to obtain a plurality of groups of data, and generating a curve image of each group of data; segmenting the curve image of the same type of soil to obtain a plurality of segmented strips; the segmentation strips belonging to the same soil class are recombined to generate a new image; and carrying out discontinuous part identification on the new image, judging the distance between two breakpoints at the discontinuous part, if the distance is smaller than a set threshold value, directly connecting the two breakpoints, otherwise, translating and adjusting the image to enable the distance between the two breakpoints to be smaller than the set threshold value, and obtaining a final image. According to the method, the quality of static sounding data can be improved to the greatest extent, so that the real condition of a soil layer can be reflected more clearly and accurately.

Description

Technical Field

[0001] The invention relates to the technical field of geotechnical exploration data processing, and in particular to a data enhancement method and system based on static penetration curve images. Background Art

[0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art.

[0003] In the field of geotechnical engineering investigation, traditional static penetration technology has always played an important role. It can help engineers obtain various parameters related to the soil layer, and then provide key data support for subsequent engineering design, construction and other links.

[0004] However, in the actual application of this technology to obtain soil parameters, many difficult problems are often encountered. Among them, the most prominent is the interference of noise. Since the on-site environment of static penetration is often more complex, there are various factors that generate noise such as the operation of mechanical equipment and human activities in the surrounding area. These noises are inevitably mixed into the data collected by static penetration, causing the data that should have been relatively pure and accurate to have different degrees of deviation. Moreover, there is also the problem of low image quality. The images generated by static penetration play a vital role in intuitively presenting the structure and characteristics of the soil layer. However, due to the accuracy limitations of the instrument itself, the imaging principle, and the influence of the external environment, the final image may have low resolution, blurred images, and key details that are difficult to clearly distinguish. These two problems are intertwined, which leads to great difficulties in the subsequent analysis of static penetration data. It becomes extremely difficult for relevant technical personnel to accurately extract key parameters such as the bearing capacity, compression modulus, porosity ratio, etc. of the soil layer from these data that are mixed with noise and have unclear and inaccurate images. As a result, the accuracy of the data finally obtained is greatly reduced and cannot meet the actual engineering needs for high-precision data. Summary of the invention

[0005] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides a data enhancement method and system based on static penetration curve image. The present invention focuses on using advanced image processing technology to carry out targeted processing of the data obtained by static penetration from multiple dimensions, aiming to improve the quality of static penetration data to the greatest extent, so that it can more clearly and accurately reflect the actual situation of the soil layer, while also improving the usability of these data in subsequent engineering applications, thereby ensuring the high-quality development of geotechnical engineering.

[0006] In order to achieve the above object, the present invention adopts the following technical solution:

[0007] A first aspect of the present invention provides a data enhancement method based on a static penetration curve image.

[0008] A data enhancement method based on a static penetration test curve image, comprising:

[0009] The original data obtained from the static penetration test is obtained, each borehole is divided according to different soil types, several groups of data are obtained, and a curve image of each group of data is generated;

[0010] Segment the curve image of the same soil type to obtain several segmentation strips;

[0011] The segmented strips belonging to the same soil type are reorganized to generate a new image;

[0012] The discontinuity of the new image is identified, and the distance between the two breakpoints at the discontinuity is determined. If the distance is less than a set threshold, the two breakpoints are directly connected. Otherwise, the image is adjusted by translation so that the distance between the two breakpoints is less than the set threshold to obtain the final image.

[0013] Furthermore, the method of segmenting the curve image of the same soil type to obtain a plurality of segmentation strips includes: segmenting the curve image of the same soil type according to equal areas so that the areas of the segmentation strips after segmentation are the same.

[0014] Furthermore, the process of identifying discontinuities in the new image includes: detecting breakpoints using an eight-neighborhood breakpoint detection method.

[0015] Furthermore, the threshold is set to Wherein W represents the width of the curve image, and the width of the curve image is the same as the width of the segmentation strip.

[0016] Furthermore, the soil types include sand, silt, and silty clay, and the curve image includes a cone tip resistance curve image and a side wall friction resistance curve image.

[0017] Furthermore, after obtaining the original data obtained from the static penetration test, the following steps are performed: completing the missing data values ​​and unifying the dimensions.

[0018] A second aspect of the present invention provides a data enhancement system based on static penetration curve images.

[0019] A data enhancement system based on static penetration test curve images, comprising:

[0020] The data acquisition and division module is configured to: acquire the original data obtained from the static penetration test, divide each borehole according to different soil types, obtain several groups of data, and generate a curve image of each group of data;

[0021] A segmentation module is configured to: segment the curve image of the same soil type to obtain a plurality of segmentation strips;

[0022] A reorganization module is configured to: reorganize the segmented strips belonging to the same soil type to generate a new image;

[0023] The breakpoint detection and connection module is configured to: identify the discontinuity of the new image, determine the distance between the two breakpoints at the discontinuity, and if the distance is less than a set threshold, directly connect the two breakpoints; otherwise, translate and adjust the image so that the distance between the two breakpoints is less than the set threshold to obtain the final image.

[0024] A third aspect of the present invention provides a computer-readable storage medium.

[0025] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps in the data enhancement method based on static penetration curve images as described in the first aspect above.

[0026] A fourth aspect of the present invention provides a computer device.

[0027] A computer device comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the steps in the data enhancement method based on static penetration curve image as described in the first aspect above are implemented.

[0028] A fifth aspect of the present invention provides a computer program product or a computer program.

[0029] The present invention provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the steps in the data enhancement method based on the static penetration curve image as described in the first aspect above.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] The present invention can effectively integrate and utilize existing static penetration test data resources by deeply analyzing the original data, revealing the internal relationship between parameters, generating curve image data, and classifying the images according to soil layer types.

[0032] The data enhancement method of the present invention improves the accuracy and efficiency of geological exploration as a whole. In terms of accuracy, since the quality of static penetration images is improved, soil layer feature identification is more accurate, and human errors are effectively controlled, the judgments and conclusions made by the present invention on geological structure, soil layer properties, etc. must be more in line with the actual situation, providing a reliable geological basis for subsequent engineering construction, etc. In terms of efficiency, the situation of spending a lot of time and energy on processing problematic data and repeatedly checking analysis results that may have errors will be greatly improved. Technicians can obtain key information from high-quality data more quickly, thereby speeding up the progress of the entire geological exploration work, improving work efficiency, and allowing geological exploration projects to be completed more efficiently and with high quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The accompanying drawings in the specification, which constitute a part of the present invention, are used to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute improper limitations on the present invention.

[0034] Figure 1 is a flow chart of a data enhancement method based on a static penetration curve image provided by an embodiment of the present invention;

[0035] Figure 2 A schematic diagram of the operation of curve image segmentation and recombination provided by an embodiment of the present invention;

[0036] Figure 3 A flow chart of the discontinuity processing of a curved image provided by an embodiment of the present invention;

[0037] Figure 4 A schematic diagram of discontinuous processing of a curved image provided by an embodiment of the present invention;

[0038] Figure 5 A schematic diagram of eight-neighborhood breakpoint detection provided by an embodiment of the present invention;

[0039] Figure 6 A comparison chart of the application effects of the method provided in the embodiment of the present invention. DETAILED DESCRIPTION

[0040] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0041] It should be noted that the following detailed descriptions are all illustrative and intended to provide further explanation of the present invention. Unless otherwise specified, all technical and scientific terms used herein have the same meanings as those commonly understood by those skilled in the art to which the present invention belongs.

[0042] It should be noted that the terms used herein are only for describing specific embodiments and are not intended to limit exemplary embodiments according to the present invention. As used herein, unless the context clearly indicates otherwise, the singular form is also intended to include the plural form. In addition, it should be understood that when the terms "comprising" and / or "including" are used in this specification, it indicates the presence of features, steps, operations, devices, components and / or combinations thereof.

[0043] It should be noted that the flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the methods and systems according to various embodiments of the present disclosure. It should be noted that each box in the flowchart or block diagram can represent a module, a program segment, or a part of a code, and the module, program segment, or a part of a code may include one or more executable instructions for implementing the logical functions specified in each embodiment. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, or they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the flowchart and / or block diagram, and the combination of boxes in the flowchart and / or block diagram can be implemented using a dedicated hardware-based system that performs a specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0044] Embodiment 1

[0045] like Figure 1 As shown, the present embodiment provides a data enhancement method based on static penetration curve images. The present embodiment uses the method applied to a server as an example for illustration. It is understandable that the method can also be applied to a terminal, and can also be applied to a terminal, a server, and a system, and is implemented through the interaction between the terminal and the server. The server can be an independent physical server, or a server cluster or a distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network servers, cloud communications, middleware services, domain name services, security services CDN, and big data and artificial intelligence platforms. The terminal can be a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart speaker, a smart watch, etc., but is not limited thereto. The terminal and the server can be directly or indirectly connected via wired or wireless communication, which is not limited in this application. In the present embodiment, the method comprises the following steps:

[0046] Step S1: Arrange the raw data obtained from the static penetration test and classify them according to seven key tags, including "region", "hole number", "depth", "cone tip resistance", "side wall friction resistance", "friction resistance ratio" and "soil type". In order to solve the problem of missing data, the average value of the data in the column is used to fill it, and the dimensions of "cone tip resistance" and "side wall friction resistance" are unified to eliminate the difficulties in comprehensive data analysis caused by different dimensions and possible problems in model training.

[0047] Step S2: Divide the data again according to the 15 soil types, group the same soil types contained in each borehole, and finally put all the same soil types in one folder.

[0048] Among them, soil types include sand, silt, silty clay, etc.; sand: the cone tip resistance curve is relatively smooth, relatively stable with depth changes, the cone tip resistance curve has no obvious mutation, and the fluctuation range is small; the side wall friction resistance curve changes with the cone tip resistance, but the fluctuation is slightly larger. Silt: The cone tip resistance curve has certain fluctuations and produces obvious fluctuations; the side wall friction resistance curve fluctuates relatively obviously and will produce mutations. Silty clay: The cone tip resistance curve fluctuates more obviously, and peaks will appear locally; the side wall friction resistance curve changes more continuously, and may produce a trend of first rising and then falling. The above description is sorted and summarized to form a soil curve feature library. This operation realizes the aggregation of the characteristics of the same soil type in a single borehole to the aggregation of the characteristics of the same soil type in different boreholes.

[0049] Step S3: Image data enhancement process is as follows Figure 1 As shown, the image segmentation diagram is as follows Figure 2 As shown, the divided data are used to generate curve images (cone tip resistance curve image and side wall friction resistance curve image). The meaning of each curve image is the relationship between the data and depth contained in a section of the same soil type in a borehole, and the dimension value range of the generated image is unified.

[0050] Step S4: Segment the images of the same soil type. Each soil type contains j images. Each image has the same width and height, that is, W and H are the same. The image is divided horizontally into i equal strips, and the strips W after segmentation remain unchanged. The image area is used as the basis for segmentation and reorganization. Each image has the same area, that is, S1 = S2 = ... S j , so the area formula of each strip after segmentation is:

[0051] S'=W×H' (1)

[0052] Step S5: Recombining the segmented images (cone tip resistance curve image and side wall friction resistance curve image) to form a new image by recombining the segmented strips of different images. The recombining of the new image follows the following formula:

[0053]

[0054] Its meaning is a new image composed of the i-th strip of the j-th image.

[0055] This operation is aimed at the segmentation of the same type of image, so the image contains relevant parameter information of the same type of soil layer, including image information of cone tip resistance, side wall friction resistance and friction resistance ratio. This operation can be used to segment the same type of soil layer information in different boreholes at different depths.

[0056] Step S6: Identify the discontinuities of the generated image using eight-neighborhood discontinuity detection. Figure 5 As shown. Eight-neighborhood breakpoint detection can identify several key points of a curve, including breakpoints and endpoints. In a two-dimensional image, each pixel has eight adjacent pixels (i.e., eight neighborhoods). For a line or contour, the pixels are normally continuous, but discontinuous at the breakpoints. By analyzing the relationship between a pixel and its eight-neighborhood pixels, it can be determined whether the pixel is a breakpoint.

[0057] Step S7: Figure 3 As shown, the distance between the two discontinuity points of the curve is judged, and the distance between the two discontinuity points of the curve is defined as x i ,like If If the discontinuity distance is too small, the feature will not have a significant impact in the smaller discontinuity, so the direct connection method is used; if the discontinuity distance is too large, the deep learning model will be affected in the image feature recognition, so the left and right translation method is used to adjust the image. The adjustment diagram is shown in the figure. Figure 4 As shown, the calculation formula for the adjusted image width is as follows:

[0058] W'=(W±x1)+(W±x2)+....+(W±x i-1 ) (3)

[0059] This operation can connect the discontinuities in the image, eliminate additional unnecessary features generated during image segmentation, and enhance the model's ability to recognize images.

[0060] In geological exploration, accurate identification of soil layer characteristics is a crucial link. Different soil layers have different physical properties, mechanical properties, etc., and these characteristics often need to be judged by identifying the characteristics presented in static penetration images or related data. With the help of the data enhancement method of the present invention, those subtle but critical features in the soil layer can be captured more keenly, allowing technicians to more accurately and quickly identify the unique characteristics of different soil layers, thereby laying a solid foundation for the subsequent in-depth understanding of the entire geological structure.

[0061] Step S8: The segmented curve image data is used for soil layer classification prediction, and compared with the image generated by the original image data enhancement method and the image generated by the innovative image data enhancement method and the original image data enhancement method. The comparison results are as follows: Figure 6 It can be seen that the recognition effect of the method of the present invention is relatively good in the deep learning image recognition model, and the prediction effect of the model is even better by adding the original image and the image generated by the original data enhancement method.

[0062] As an important carrier reflecting soil layer information, the images generated by the traditional acquisition method of the static penetration curve image often have many unsatisfactory aspects. For example, the resolution of the image is often low, making it difficult to clearly present some key data points and subtle change trends on the curve. These unclear data details may cause technicians to miss the opportunity to gain insight into some special properties of the soil layer; furthermore, the curve image may be disturbed by noise, and some irregular noise points are mixed in it, which seriously interferes with the original smooth and continuous shape of the curve. These noise points make it difficult for technicians to accurately grasp the true direction of the curve and the soil layer change law contained therein; in addition, the color contrast of the image is not enough. The curve parts corresponding to different soil layers are not distinguished enough in the image, and it is difficult to quickly distinguish the differences between the soil layers by intuitive vision. The embodiment of the present invention provides a data enhancement method based on the static penetration key parameter curve image, which not only provides a new data enhancement method for the static penetration key parameter image data, but also provides a new idea for solving the static penetration soil layer classification problem. In terms of improving the quality of the static penetration curve image, its effect is very significant. In the future, with the further development of technology, this technology will be applied in more fields and provide strong technical support for various engineering projects.

[0063] Embodiment 2

[0064] This embodiment provides a data enhancement system based on static penetration curve images.

[0065] A data enhancement system based on static penetration test curve images, comprising:

[0066] The data acquisition and division module is configured to: acquire the original data obtained from the static penetration test, divide each borehole according to different soil types, obtain several groups of data, and generate a curve image of each group of data;

[0067] A segmentation module is configured to: segment the curve image of the same soil type to obtain a plurality of segmentation strips;

[0068] A reorganization module is configured to: reorganize the segmented strips belonging to the same soil type to generate a new image;

[0069] The breakpoint detection and connection module is configured to: identify the discontinuity of the new image, determine the distance between the two breakpoints at the discontinuity, and if the distance is less than a set threshold, directly connect the two breakpoints; otherwise, translate and adjust the image so that the distance between the two breakpoints is less than the set threshold to obtain the final image.

[0070] In some embodiments, the method of segmenting the curve image of the same soil type to obtain a plurality of segmented strips includes: segmenting the curve image of the same soil type according to equal areas so that the areas of the segmented strips after segmentation are the same.

[0071] In some embodiments, the process of identifying discontinuities in a new image includes: detecting breakpoints using an eight-neighborhood breakpoint detection method.

[0072] In some embodiments, the threshold is set to Wherein W represents the width of the curve image, and the width of the curve image is the same as the width of the segmentation strip.

[0073] In some embodiments, the soil type includes sand, silt, and silty clay, and the curve image includes a cone tip resistance curve image and a side wall friction resistance curve image.

[0074] In some embodiments, after obtaining the original data obtained from the static penetration test, the following steps are performed: completing the missing data values ​​and unifying the dimensions.

[0075] In the traditional geological exploration data processing and analysis process, due to the quality problems of the static penetration data itself, technicians will inevitably introduce certain subjective judgment factors when interpreting and analyzing these data and judging the characteristics of the soil layer based on the data, and these subjective factors can easily lead to human errors. For example, when judging the thickness range of a certain soil layer, inaccurate measurements may occur due to unclear images, or when classifying the properties of the soil layer, problems such as incorrect classification may occur due to the ambiguity of the data. However, by applying the data enhancement method of the present invention, the data becomes clearer, more accurate and intuitive, and technicians can conduct objective analysis and judgment based on high-quality data, which minimizes human errors caused by subjective factors, and effectively guarantees the rigor and scientific nature of the entire geological exploration work.

[0076] Embodiment 3

[0077] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps in the data enhancement method based on static penetration curve images as described in the first embodiment above are implemented.

[0078] Embodiment 4

[0079] This embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the steps in the data enhancement method based on static penetration curve images as described in the first embodiment are implemented.

[0080] Embodiment 5

[0081] This embodiment provides a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the steps in the data enhancement method based on the static penetration curve image described in the first embodiment.

[0082] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of hardware embodiments, software embodiments, or embodiments combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage and optical storage, etc.) containing computer-usable program code.

[0083] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0084] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0085] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0086] A person skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program, and the program can be stored in a computer-readable storage medium, and when the program is executed, it can include the processes of the embodiments of the above-mentioned methods. The storage medium can be a disk, an optical disk, a read-only memory (ROM) or a random access memory (RAM), etc.

[0087] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A data enhancement method based on static penetration test curve image, characterized in that: include: The original data obtained from the static penetration test is obtained, each borehole is divided according to different soil types, several groups of data are obtained, and a curve image of each group of data is generated; Segment the curve image of the same soil type to obtain several segmentation strips; The segmented strips belonging to the same soil type are reorganized to generate a new image; The discontinuity of the new image is identified, and the distance between the two breakpoints at the discontinuity is determined. If the distance is less than a set threshold, the two breakpoints are directly connected. Otherwise, the image is adjusted by translation so that the distance between the two breakpoints is less than the set threshold to obtain the final image.

2. The data enhancement method based on static penetration curve image according to claim 1 is characterized in that: The method of segmenting the curve image of the same soil type to obtain a plurality of segmentation strips includes: segmenting the curve image of the same soil type according to equal areas so that the areas of the segmentation strips after segmentation are the same.

3. The data enhancement method based on static penetration curve image according to claim 1 is characterized in that: The process of identifying discontinuities in a new image includes: detecting breakpoints using an eight-neighborhood breakpoint detection method.

4. The data enhancement method based on static penetration curve image according to claim 1 is characterized in that: The threshold value is set to Wherein W represents the width of the curve image, and the width of the curve image is the same as the width of the segmentation strip.

5. The data enhancement method based on static penetration curve image according to claim 1 is characterized in that: The soil types include sand, silt, and silty clay, and the curve images include a cone tip resistance curve image and a side wall friction resistance curve image.

6. The data enhancement method based on static penetration curve image according to claim 1 is characterized in that: After obtaining the original data from the static penetration test, the following steps are performed: completing the missing data values ​​and unifying the dimensions.

7. A data enhancement system based on static penetration curve image, characterized in that: include: The data acquisition and division module is configured to: acquire the original data obtained from the static penetration test, divide each borehole according to different soil types, obtain several groups of data, and generate a curve image of each group of data; A segmentation module is configured to: segment the curve image of the same soil type to obtain a plurality of segmentation strips; A reorganization module is configured to: reorganize the segmented strips belonging to the same soil type to generate a new image; The breakpoint detection and connection module is configured to: identify the discontinuity of the new image, determine the distance between the two breakpoints at the discontinuity, and if the distance is less than a set threshold, directly connect the two breakpoints; otherwise, translate and adjust the image so that the distance between the two breakpoints is less than the set threshold to obtain the final image.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps in the data enhancement method based on static penetration curve images as described in any one of claims 1 to 6 are implemented.

9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the steps in the data enhancement method based on static penetration curve image according to any one of claims 1 to 6 are implemented.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by a processor, the steps in the data enhancement method based on static penetration curve images as claimed in any one of claims 1 to 6 are implemented.

Images