CN115217084B - Method and system for detecting surface fracture rate of expansive soil in reservoir area - Google Patents
Method and system for detecting surface fracture rate of expansive soil in reservoir area Download PDFInfo
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- CN115217084B CN115217084B CN202210868911.0A CN202210868911A CN115217084B CN 115217084 B CN115217084 B CN 115217084B CN 202210868911 A CN202210868911 A CN 202210868911A CN 115217084 B CN115217084 B CN 115217084B
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- E—FIXED CONSTRUCTIONS
- E02—HYDRAULIC ENGINEERING; FOUNDATIONS; SOIL SHIFTING
- E02D—FOUNDATIONS; EXCAVATIONS; EMBANKMENTS; UNDERGROUND OR UNDERWATER STRUCTURES
- E02D1/00—Investigation of foundation soil in situ
- E02D1/02—Investigation of foundation soil in situ before construction work
- E02D1/027—Investigation of foundation soil in situ before construction work by investigating properties relating to fluids in the soil, e.g. pore-water pressure, permeability
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/90—Determination of colour characteristics
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10004—Still image; Photographic image
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A10/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE at coastal zones; at river basins
- Y02A10/40—Controlling or monitoring, e.g. of flood or hurricane; Forecasting, e.g. risk assessment or mapping
Abstract
The present disclosure provides a method and a system for detecting a surface crack rate of expansive soil in a reservoir region, wherein the method comprises determining a region to be inspected based on the expansive soil in the reservoir region; generating a plurality of inspection shooting points based on the area to be inspected so as to control the unmanned aerial vehicle device to carry out inspection shooting according to the inspection shooting points; obtaining an initial image of each inspection shooting point shot by the unmanned aerial vehicle device, and calculating a preset color pixel ratio based on the initial image so as to obtain the surface crack rate of each inspection shooting point; and obtaining the surface fracture rate of the expansive soil in the reservoir area based on the surface fracture rate of the inspection shooting point. The method can improve the accuracy and the real-time performance of the detection of the surface fracture rate of the expansive soil.
Description
Technical Field
The disclosure relates to the technical field of geotechnical engineering and special soil characteristic research, in particular to a method and a system for detecting surface crack rate of expansive soil in a reservoir area.
Background
As is well known, expansive soil is a cohesive soil containing a large amount of hydrophilic clay mineral, and is water-swellable, disintegrated or softened when meeting water, water-loss-contractible, and poor in anti-scouring performance. These characteristics make the expansive soil region prone to subsidence, slump, longitudinal crack, collapse and other accidents, and constitute a typical geological disaster.
Among the many problems of expansive soil, expansive soil slopes are one of the key problems, and an inadvertent lack of treatment can cause significant impact and loss. The instability disasters of the expansive soil slope have long plagued the safe production activities of human beings, because the expansive soil has special expansibility, crack property and strength attenuation property, the strength is obviously reduced after the cracking, the expansive soil slope is more sensitive to the climate changes such as rainfall, and the like, and the soft weathered crack layer is extremely easy to form on the soil layer surface, so that the expansive soil slope is damaged in a traction way. Especially, under the background of rapid development of engineering construction in expansive soil areas in China, excavation of various expansive soil cutting and channel slopes is unavoidable, and adverse effects caused by instability of the expansive soil slopes due to dry and wet circulation are huge.
Along with the development of a great deal of slope engineering, the corresponding expansive soil characteristic analysis and detection technology is also rapidly developed. The existing devices for analyzing and measuring the crack property and the like of the expansive soil belong to indoor tests, and are required to be subjected to on-site soil sampling and sealed transportation to laboratory tests, so that the real-time detection of the surface crack rate of the expansive soil is not high enough, the influence of soil sampling conditions is large, the laboratory tests have large difference with the stress under in-situ conditions, the characteristics of the expansive soil are obviously influenced, and the accuracy of the surface crack rate of the expansive soil is not high enough.
Disclosure of Invention
The present disclosure aims to solve, at least to some extent, one of the technical problems in the related art.
Therefore, a first object of the present disclosure is to provide a method for detecting the surface fracture rate of expansive soil in a reservoir area, so as to improve the accuracy and real-time performance of the surface fracture rate detection of expansive soil.
A second object of the present disclosure is to provide a system for detecting the surface fracture rate of expansive soil in a reservoir.
A third object of the present disclosure is to propose an electronic device.
To achieve the above object, an embodiment of a first aspect of the present disclosure provides a method for detecting a surface fracture rate of expansive soil in a reservoir, including:
determining an area to be inspected based on the reservoir area expansive soil area;
generating a plurality of inspection shooting points based on the area to be inspected so as to control the unmanned aerial vehicle device to carry out inspection shooting according to the inspection shooting points;
obtaining initial images of all inspection shooting points shot by the unmanned aerial vehicle device, and calculating a preset color pixel ratio based on the initial images so as to obtain the surface crack rate of all the inspection shooting points;
and obtaining the surface fracture rate of the expansive soil in the reservoir area based on the surface fracture rate of the inspection shooting point.
In one embodiment of the disclosure, the determining the area to be inspected based on the reservoir region expansive soil region includes: obtaining a slope range based on the reservoir region expansive soil region; planning a range to be patrolled and examined at a set distance from the outside of the slope range to the slope range, and taking an area covered in the range to be patrolled and examined as the area to be patrolled and examined.
In one embodiment of the disclosure, the generating a plurality of inspection capture points based on the area to be inspected includes: generating a zigzag broken line inspection path based on the area to be inspected; and setting a set number of inspection shooting points on each line segment of the broken line inspection path, thereby obtaining all the inspection shooting points of the area to be inspected.
In one embodiment of the disclosure, the obtaining the initial image of each inspection shooting point shot by the unmanned aerial vehicle device includes: determining at least 3 time points for each patrol shooting point, wherein the at least 3 time points comprise an initial time point and an end time point; and obtaining initial images corresponding to all time points of the inspection shooting point, and if rainfall occurs in the period from the initial time point to the ending time point, re-obtaining the initial images corresponding to all time points of the inspection shooting point after the rainfall is ended.
In one embodiment of the disclosure, the calculating the preset color pixel ratio based on the initial image to obtain the surface crack rate of each inspection shooting point includes: the preset color is black, gray processing and binarization processing are sequentially carried out on the initial image corresponding to each time point to obtain a binary image, and the black pixel duty ratio is calculated based on the binary image, so that the surface crack rate of the time point is obtained; for each inspection shot, a maximum value is selected from the surface crack rates at all time points as the surface crack rate for that inspection shot.
In one embodiment of the present disclosure, the obtaining the surface fracture rate of the expansive soil of the reservoir region based on the surface fracture rate of the inspection shooting point includes: calculating the average value of the surface crack rate of all the inspection shooting points; comparing the surface crack rate of each inspection shooting point with the average value, filtering out inspection shooting points with errors of the surface crack rate and the average value larger than a set threshold value, and obtaining a target inspection shooting point set; and calculating the average value of the surface crack rate of all the inspection shooting points in the target inspection shooting point set, and further obtaining the surface crack rate of the expansive soil in the reservoir area.
To achieve the above object, an embodiment of a second aspect of the present disclosure provides a system for detecting a surface fracture rate of expansive soil in a reservoir, including:
the control device is used for determining an area to be inspected based on the storage area expansive soil area, generating a plurality of inspection shooting points based on the area to be inspected and sending the position information of the inspection shooting points to the unmanned aerial vehicle device to obtain an initial image shot by the unmanned aerial vehicle device, calculating a preset color pixel duty ratio based on the initial image so as to obtain the surface crack rate of each inspection shooting point, and obtaining the storage area expansive soil surface crack rate based on the surface crack rate of the inspection shooting points;
The unmanned aerial vehicle device is used for carrying out inspection based on the position information of the inspection shooting point to generate an initial image, and sending the initial image to the control device.
In one embodiment of the present disclosure, the control device is further configured to: determining at least 3 time points for each patrol shooting point, wherein the at least 3 time points comprise an initial time point and an end time point; obtaining initial images corresponding to all time points of the inspection shooting point, and if rainfall occurs in the period from the initial time point to the ending time point, re-obtaining the initial images corresponding to all time points of the inspection shooting point after the rainfall is ended; the preset color is black, gray processing and binarization processing are sequentially carried out on the initial image corresponding to each time point to obtain a binary image, and the black pixel duty ratio is calculated based on the binary image, so that the surface crack rate of the time point is obtained; for each inspection shot, a maximum value is selected from the surface crack rates at all time points as the surface crack rate for that inspection shot.
In one embodiment of the present disclosure, the control device is further configured to: calculating the average value of the surface crack rate of all the inspection shooting points; comparing the surface crack rate of each inspection shooting point with the average value, filtering out inspection shooting points with errors of the surface crack rate and the average value larger than a set threshold value, and obtaining a target inspection shooting point set; and calculating the average value of the surface crack rate of all the inspection shooting points in the target inspection shooting point set, and further obtaining the surface crack rate of the expansive soil in the reservoir area.
To achieve the above object, an embodiment of a third aspect of the present disclosure provides an electronic device, including: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform a reservoir swelling soil surface fracture rate detection method of an embodiment of the first aspect of the present disclosure.
In one or more embodiments of the present disclosure, an area to be inspected is determined based on the reservoir region expansive soil region; generating a plurality of inspection shooting points based on the area to be inspected so as to control the unmanned aerial vehicle device to carry out inspection shooting according to the inspection shooting points; obtaining an initial image of each inspection shooting point shot by the unmanned aerial vehicle device, and calculating a preset color pixel ratio based on the initial image so as to obtain the surface crack rate of each inspection shooting point; and obtaining the surface fracture rate of the expansive soil in the reservoir area based on the surface fracture rate of the inspection shooting point. Under the condition, an initial image shot by the unmanned aerial vehicle device at each inspection shooting point of the area to be inspected is acquired, the image processing analysis technology is utilized for calculating the preset color pixel ratio aiming at the initial image so as to obtain the surface crack rate of the inspection shooting points, and further the surface crack rate of the expansive soil in the reservoir area is obtained, so that the accuracy of the detection of the surface crack rate of the expansive soil in the reservoir area is improved, the on-site soil sampling is not needed due to the on-site detection of the surface crack rate of the expansive soil in the reservoir area, and the real-time performance of the detection is improved.
Additional aspects and advantages of the disclosure will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the disclosure.
Drawings
In order to more clearly illustrate the embodiments of the present disclosure or the prior art, the drawings that are required in the detailed description or the prior art will be briefly described, it will be apparent that the drawings in the following description are some embodiments of the present disclosure, and other drawings may be obtained according to the drawings without inventive effort for a person of ordinary skill in the art. The foregoing and/or additional aspects and advantages of the present disclosure will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings, in which:
FIG. 1 is a schematic view of a method for detecting surface fracture rate of expansive soil in a reservoir according to an embodiment of the present disclosure;
FIG. 2 is a schematic flow chart of a method for detecting the surface fracture rate of expansive soil in a reservoir according to an embodiment of the present disclosure;
fig. 3 is a schematic diagram of a patrol shooting point according to an embodiment of the present disclosure;
FIG. 4 (a) is a schematic illustration of an initial image provided by an embodiment of the present disclosure;
FIG. 4 (b) is a schematic diagram of the binary image corresponding to FIG. 4 (a);
FIG. 5 is a block diagram of a reservoir zone expansive soil surface fracture rate detection system provided in embodiments of the present disclosure;
FIG. 6 is a block diagram of an electronic device for implementing a method for detecting a surface fracture rate of a reservoir swelling soil in accordance with an embodiment of the present disclosure.
Detailed Description
Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numbers in different drawings refer to the same or similar elements, unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the embodiments of the present disclosure. Rather, they are merely examples of apparatus and methods consistent with aspects of embodiments of the present disclosure as detailed in the accompanying claims.
In the description of the present specification, a description referring to terms "one embodiment," "some embodiments," "examples," "specific examples," or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms are not necessarily directed to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, the different embodiments or examples described in this specification and the features of the different embodiments or examples may be combined and combined by those skilled in the art without contradiction.
Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying a relative importance or implicitly indicating the number of technical features indicated. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include at least one such feature. In the description of the present disclosure, the meaning of "a plurality" is at least two, such as two, three, etc., unless explicitly specified otherwise. It should also be understood that the term "and/or" as used in this disclosure refers to and encompasses any or all possible combinations of one or more of the associated listed items.
Embodiments of the present disclosure are described in detail below, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to like or similar elements or elements having like or similar functions throughout. The embodiments described below by referring to the drawings are exemplary and intended for the purpose of explaining the present disclosure and are not to be construed as limiting the present disclosure.
The present disclosure provides a method and a system for detecting the surface fracture rate of expansive soil in a reservoir area, and aims to improve the accuracy and the real-time performance of the surface fracture rate detection of expansive soil.
In a first embodiment, fig. 1 is a schematic diagram of a scenario of a method for detecting a surface fracture rate of expansive soil in a reservoir according to an embodiment of the present disclosure. In the scene shown in fig. 1, the unmanned aerial vehicle comprises a camera module, an image storage module and a signal antenna module, wherein the camera module is used for taking high-definition photos, the image storage module is used for storing the high-definition photos, the unmanned aerial vehicle realizes information interaction with a control room computer through the signal antenna module, the control room computer obtains the high-definition photos taken by the unmanned aerial vehicle and detects the surface crack rate, specifically, the unmanned aerial vehicle receives an instruction from the control room computer to cruise in a reservoir region expansive soil area, images are taken in the cruising process and sent to the control room computer, and the control room computer detects the surface crack rate by adopting the reservoir region expansive soil surface crack rate detection method.
Fig. 2 is a schematic flow chart of a method for detecting surface fracture rate of expansive soil in a reservoir according to an embodiment of the present disclosure. As shown in FIG. 2, the method for detecting the surface fracture rate of the expansive soil in the reservoir area comprises the following steps:
and S11, determining an area to be inspected based on the expansive soil area of the reservoir area.
In step S11, determining an area to be inspected based on the reservoir region expansive soil region includes: obtaining a slope range based on the reservoir region expansive soil region; planning a range to be patrolled and examined at a set distance from the outside of the side slope range to the side slope range, and taking an area covered in the range to be patrolled and examined as an area to be patrolled and examined. Thereby, it is possible to ensure that the area to be inspected covers the area of the expansive soil of the warehouse area to be investigated.
In some embodiments, the set distance may be about 10% of the average width of the slope range. The value of the set distance in the embodiments of the present disclosure is not limited thereto.
Step S12, a plurality of inspection shooting points are generated based on the area to be inspected, so that the unmanned aerial vehicle device is controlled to carry out inspection shooting according to the inspection shooting points.
Specifically, generating a plurality of inspection shooting points based on the area to be inspected in step S12 includes: generating a zigzag broken line inspection path (referred to as an inspection path) based on the area to be inspected; and setting a set number of inspection shooting points on each line segment of the broken line inspection path, thereby obtaining all the inspection shooting points of the area to be inspected. Under the condition, the unmanned aerial vehicle is controlled to fly according to the zigzag broken line inspection path, and the initial image is obtained by shooting at the inspection shooting points, and as the two ends of the broken line inspection path exceed the range of the side slope, a set number of inspection shooting points are arranged on each line segment, so that sufficient initial images covering the range of the side slope can be obtained, comprehensive and sufficient data can be provided for the subsequent detection of the surface crack rate of the expansive soil in the storage area, and the accuracy of the detection of the surface crack rate of the expansive soil in the storage area is further improved.
In some embodiments, the set number may be, for example, 6-8.
In some embodiments, the inspection shots on each line segment may be evenly distributed. When the inspection shooting points are uniformly distributed, the interval between adjacent inspection shooting points can be predetermined based on the set number and the length of each line segment. This ensures that a large number of images are obtained for subsequent analysis.
Fig. 3 is a schematic diagram of a patrol shooting point according to an embodiment of the present disclosure. As shown in fig. 3, the closed fold line X is a side slope range of the expansive soil, the closed fold line Y is a to-be-inspected range, the area in the closed fold line Y is a to-be-inspected area, the zigzag fold line Z is an inspection path, and the five-pointed star is an inspection shooting point. In some embodiments, as shown in fig. 3, the control room computer may control the drone to fly along the inspection path Z in the direction of the arrow and take a photograph at each inspection photograph point.
Step S13, obtaining initial images of all inspection shooting points shot by the unmanned aerial vehicle device, and calculating a preset color pixel duty ratio based on the initial images so as to obtain the surface crack rate of all the inspection shooting points.
In step S13, in consideration of the repeated swelling and shrinkage of the swelling soil, the swelling soil continuously absorbs water to swell and loses water to shrink during the dry-wet cycle in the rainy season. Accordingly, the fissures in the expansive soil surface are in a condition of repeated opening and closing. For the expansive soil in the same area, the surface fracture rate obtained by taking photos at different time can be different, and although the fractured expansive soil expands after absorbing water, part of the fracture surface appears to be reclosed, the inside of the soil body is damaged to form a discontinuous damage surface due to the fact that the fracture is formed before, so that the maximum fracture rate (namely the maximum surface fracture rate) of the expansive soil in the area after the dry and wet cycles is obtained. In combination, the maximum fracture rate can better respond to the true fracture rate of the expansive soil. Therefore, in order to obtain the true fracture rate of the expansive soil at each inspection photographing point, it is first necessary to determine an initial image of each inspection photographing point. Specifically, obtaining an initial image of each inspection shooting point shot by the unmanned aerial vehicle device includes: determining at least 3 time points for each patrol shooting point, wherein the at least 3 time points comprise an initial time point and an end time point; and obtaining initial images corresponding to all time points of the inspection shooting point, and if rainfall occurs in the period from the initial time point to the ending time point, re-obtaining the initial images corresponding to all time points of the inspection shooting point after the rainfall is ended.
In some embodiments, the initial point in time is typically a first preset period of time, e.g., 48 hours, after the previous rainfall has ceased. Adjacent 2 time points typically differ by at least a second preset period of time, e.g. 24 hours.
In some embodiments, if rainfall occurs during the period from the initial time point to the end time point, all the initial images acquired by the inspection shooting point are invalid, each time point needs to be redetermined after a first preset time period when rainfall completely stops, and then the initial images corresponding to each redetermined time point are acquired.
In step S13, the surface crack rate of each inspection shooting point is obtained by calculating the preset color pixel duty ratio based on the initial image, and the initial image is resolved by using the image processing resolving technology to obtain the surface crack rate of the expansive soil at each inspection shooting point (the surface crack rate of each inspection shooting point for short). The image processing analysis technology comprises a crack imaging technology and a surface crack rate calculation method.
Specifically, calculating a preset color pixel duty ratio based on an initial image, thereby obtaining a surface crack rate of each inspection shooting point, including: the preset color is black, gray processing and binarization processing are sequentially carried out on the initial image corresponding to each time point by using a crack imaging technology to obtain a binary image, and the surface crack rate of the time point is obtained by calculating the black pixel duty ratio based on the binary image by using a surface crack rate calculation method; for each inspection shot, a maximum value is selected from the surface crack rates at all time points as the surface crack rate for that inspection shot. Therefore, more real surface fracture rate can be obtained, and the accuracy of detection of the surface fracture rate of the expansive soil in the reservoir area is improved.
In some embodiments, the initial image is a color image, and the captured initial image may be converted to a grayscale image using image processing software (e.g., photoshop). It is easy to understand that the gray image only represents the brightness information of the image without any color information, and thus each pixel of the gray image contains only one quantized gray value.
In some embodiments, the split portions in the binary image are represented in black and the remaining non-split portions are represented in white.
In some embodiments, it is desirable to select a corresponding gray threshold value to filter and remove dryness from the gray image to convert the gray image into a binary image, considering that the brightness (gray) of the image directly photographed at different time points is different.
In some embodiments, to ensure accuracy of the processing effect, the binary image may be subjected to a depuration process. The desmear process refers to a non-cracked black area that eliminates identification errors.
Fig. 4 (a) is a schematic diagram of an initial image provided by an embodiment of the disclosure, and fig. 4 (b) is a schematic diagram of a binary image corresponding to fig. 4 (a). In some embodiments, for example, the binary image shown in fig. 4 (b) is compared to the original image shown in fig. 4 (a), eliminating false non-fractured black areas in the binary image. The erroneous non-fractured black zone is identified, for example, by an uneven portion of the expansive soil surface.
In step S13, the surface crack rate at this point in time is obtained by calculating the black pixel duty ratio based on the binary image using the surface crack rate calculation method, specifically including: calculating the number of black pixels in the whole binary image; dividing the number of the black pixels by the number of the whole surface pixels to obtain a black pixel duty ratio, wherein the black pixel duty ratio is the surface crack rate of the inspection shooting point at the time point. The surface crack rate is a quantitative index of crack development degree, and can be used for judging the crack development degree of the expansive soil.
In some embodiments, the black pixel duty cycle may be obtained by an area ratio, where the black pixel duty cycle satisfies:
in delta f The corresponding surface crack rate of a certain time point of a certain inspection shooting point is represented, A represents the total area of all pixels of a binary image, A i Representing the area of a single black pixel in a binary image, n i Representing the number of black pixels in the binary image.
In some embodiments, the black pixel duty cycle of the binary image may be calculated by image processing software (e.g., photoshop and matlab, etc.).
Taking 3 time points as an example, the surface crack rate determination process of the expansive soil for a certain inspection shooting point in the step S13 is as follows:
Sequentially acquiring initial images of the inspection shooting point at 3 different time points, wherein the 3 different time points are respectively an initial time point, a middle time point and an end time point, the initial time point (namely, the time of shooting the images for the first time) is at least 24 hours after the previous rainfall stops for 48 hours, and no rainfall exists between the initial time point and the end time point;
if 3 times of shooting of the patrol shooting point cannot be completed, namely rainfall occurs, all the acquired images of the patrol shooting point are invalid, the images of the 3 time points of the patrol shooting point need to be acquired again after the rainfall is completely stopped for 48 hours, if 3 times of shooting are completed, three initial images of the patrol shooting point are obtained, and the three initial images are respectively a first image corresponding to the initial time point, a second image corresponding to the middle time point and a third image corresponding to the ending time point;
resolving the first, second and third images using image processing resolution techniquesSurface crack rate of 3 different time points to the inspection shooting point, and surface crack rate delta of 3 different time points f First crack rate delta corresponding to initial time point respectively f,1 Second crack rate delta corresponding to intermediate time point f,2 Third crack rate delta corresponding to end time point f,3 And selecting the maximum fracture rate of the three surface fracture rates as the surface fracture rate of the expansive soil of the inspection shooting point (namely the real fracture rate delta of the expansive soil of the inspection shooting point). The time points and surface crack rates of the inspection shots are shown in Table 1.
TABLE 1 time Point of inspection Point and true crack Rate
And S14, obtaining the surface fracture rate of the expansive soil in the reservoir area based on the surface fracture rate of the inspection shooting point.
In step S14, the surface fracture rate of the expansive soil in the reservoir region is obtained based on the surface fracture rate of the inspection photographing point, including: calculating the average value of the surface crack rate of all the inspection shooting points; comparing the surface crack rate and the average value of each inspection shooting point, filtering out inspection shooting points with errors of the surface crack rate and the average value larger than a set threshold value, and obtaining a target inspection shooting point set; and calculating the average value of the surface crack rates of all the inspection shooting points in the target inspection shooting point set, and further obtaining the surface crack rate of the expansive soil in the reservoir area. Wherein the set threshold may be 20%.
Taking n inspection shooting points as an example, the determination process of the surface crack rate of the expansive soil in the reservoir area in the step S14 is as follows:
calculating average value of surface crack rates of n inspection shooting points in the expansive soil area of the reservoir area Judging whether the error between the surface crack rate of each inspection shooting point and the average value is more than 20%, and if the surface crack rate of each inspection shooting point does not exceed 20% of the average value, taking the average value as the surface of the expansive soil in the reservoir regionFracture rate; if the surface crack rate of m inspection shooting points exceeds 20% of the average value, the surface crack rate of the m inspection shooting points is removed, n-m inspection shooting points are left as a target inspection shooting point set, and the average value of the surface crack rates of the n-m inspection shooting points is calculated, so that the surface crack rate of the expansive soil in the reservoir area is obtained.
In the method for detecting the surface crack rate of the expansive soil in the reservoir area, the area to be inspected is determined based on the expansive soil area in the reservoir area; generating a plurality of inspection shooting points based on the area to be inspected so as to control the unmanned aerial vehicle device to carry out inspection shooting according to the inspection shooting points; obtaining an initial image of each inspection shooting point shot by the unmanned aerial vehicle device, and calculating a preset color pixel ratio based on the initial image so as to obtain the surface crack rate of each inspection shooting point; and obtaining the surface fracture rate of the expansive soil in the reservoir area based on the surface fracture rate of the inspection shooting point. Under the condition, an initial image shot by the unmanned aerial vehicle device at each inspection shooting point of the area to be inspected is acquired, the image processing analysis technology is utilized for calculating the preset color pixel ratio aiming at the initial image so as to obtain the surface crack rate of the inspection shooting points, and further the surface crack rate of the expansive soil in the reservoir area is obtained, so that the accuracy of the detection of the surface crack rate of the expansive soil in the reservoir area is improved, the on-site soil sampling is not needed due to the on-site detection of the surface crack rate of the expansive soil in the reservoir area, and the real-time performance of the detection is improved. In addition, the method disclosed by the invention also converts the slit picture (namely the initial image) shot on site into a binary image and removes the point of the conversion error, the surface slit rate of the site expansive soil is obtained by calculating the percentage of the pixel accumulation area of the black slit area, the analysis accuracy and the rapidness are improved, the cost of manual soil taking and logistics is greatly saved, the method disclosed by the invention does not need to perform site soil taking, and particularly for some areas with larger gradient, complex topography and inconvenient transportation, the potential safety hazard, the labor cost and the logistics transportation cost caused by manual site soil taking are avoided, compared with the manual soil taking test, the efficiency is greatly improved, the soil stress environment change during the site test is avoided, the method has better economical efficiency and application prospect, and the real-time property and the accuracy of the site analysis and evaluation of the expansive soil slit characteristics are improved, and the method disclosed by the method for rapidly analyzing the expansive soil slit rate in a reservoir area is provided.
The following are system embodiments of the present disclosure that may be used to perform method embodiments of the present disclosure. For details not disclosed in the embodiments of the disclosed system, please refer to the embodiments of the disclosed method.
Referring to fig. 5, fig. 5 is a block diagram of a system for detecting a surface fracture rate of expansive soil in a reservoir according to an embodiment of the present disclosure. The reservoir region expansive soil surface fracture rate detection system 10 comprises a control device 11 and an unmanned aerial vehicle device 12, wherein:
the control device 11 is used for determining an area to be inspected based on the area of the expansive soil of the storage area, generating a plurality of inspection shooting points based on the area to be inspected and sending the position information of the inspection shooting points to the unmanned aerial vehicle device to obtain an initial image shot by the unmanned aerial vehicle device, calculating a preset color pixel duty ratio based on the initial image so as to obtain the surface crack rate of each inspection shooting point, and obtaining the surface crack rate of the expansive soil of the storage area based on the surface crack rate of the inspection shooting points;
the unmanned aerial vehicle device 12 is used for performing inspection based on the position information of the inspection shooting point to generate an initial image, and sends the initial image to the control device.
Optionally, the control device 11 is further configured to: determining at least 3 time points for each patrol shooting point, wherein the at least 3 time points comprise an initial time point and an end time point; obtaining initial images corresponding to all time points of the inspection shooting point, and if rainfall occurs in the period from the initial time point to the ending time point, re-obtaining the initial images corresponding to all time points of the inspection shooting point after the rainfall is ended; the preset color is black, gray level processing and binarization processing are sequentially carried out on the initial image corresponding to each time point to obtain a binary image, and the black pixel duty ratio is calculated based on the binary image, so that the surface crack rate of the time point is obtained; for each inspection shot, a maximum value is selected from the surface crack rates at all time points as the surface crack rate for that inspection shot.
Optionally, the control device 11 is further configured to: calculating the average value of the surface crack rate of all the inspection shooting points; comparing the surface crack rate and the average value of each inspection shooting point, filtering out inspection shooting points with errors of the surface crack rate and the average value larger than a set threshold value, and obtaining a target inspection shooting point set; and calculating the average value of the surface crack rates of all the inspection shooting points in the target inspection shooting point set, and further obtaining the surface crack rate of the expansive soil in the reservoir area.
In some embodiments, the control device 11 is, for example, a control room computer.
In some embodiments, the drone 12 may include a camera module, an image storage module, and a signal antenna module. The camera module is used for taking photos, the image storage module is used for storing the photos, the unmanned aerial vehicle device 12 achieves information interaction with the control device 11 through the signal antenna module, and the control device 11 acquires the photos (namely initial images) taken by the unmanned aerial vehicle device in real time through the signal antenna module and detects the surface crack rate.
In some embodiments, the camera module is, for example, a high-definition camera. Therefore, a high-definition photo can be obtained through the high-definition camera, and the accuracy of surface crack rate detection is improved.
In some embodiments, the drone 12 may receive the location information of the patrol shooting point from the control device 11, reach the patrol shooting point to generate an initial image, and send the initial image to the image storage module for storage and send the initial image to the control device 11 through the signal antenna module.
In some embodiments, when the drone 12 reaches a patrol shooting point, the signal antenna module sends the position information of the drone 12 to the control device 11, the control device 11 transmits the position information of the next patrol shooting point to the drone 12, and the drone 12 flies linearly to the new patrol shooting point again according to the new position information to shoot.
In some embodiments, the control device 11 may install corresponding image processing analysis software, such as Photoshop and matlab software, and implement functions of checking a field shot photo, removing error information in an image, binarizing and calculating a cumulative area (or a preset color pixel ratio) of a preset color pixel point by using an image processing analysis technology through Photoshop and matlab software.
In some embodiments, the control device 11 is in communication with the signal antenna module through a 4G module, a 5G module, a WiFi module or a ZigBee module.
In some embodiments, the control device 11 sends a re-shooting instruction to the drone device 12 if the initial image is identified as blurred. Specifically, the control device 11 determines whether the sharpness of the initial image exceeds a sharpness threshold, and if not, generates a re-shooting instruction and transmits the re-shooting instruction to the unmanned aerial vehicle device 12.
In some embodiments, the control device 11 may further determine whether the preset inspection shooting point in the initial image is blocked by the surface vegetation, if yes, the control device 11 sends an instruction to the unmanned aerial vehicle device 12, and adjusts the position to perform the supplementary shooting.
It should be noted that the foregoing explanation of the embodiment of the method for detecting the surface fracture rate of the expansive soil in the reservoir area is also applicable to the system for detecting the surface fracture rate of the expansive soil in the reservoir area in this embodiment, and is not described herein.
In the system for detecting the surface crack rate of the expansive soil in the storage area, a control device determines an area to be inspected based on the expansive soil area in the storage area, generates a plurality of inspection shooting points based on the area to be inspected, sends position information of the inspection shooting points to an unmanned aerial vehicle device, obtains an initial image shot by the unmanned aerial vehicle device, calculates a preset color pixel duty ratio based on the initial image, thereby obtaining the surface crack rate of each inspection shooting point, and obtains the surface crack rate of the expansive soil in the storage area based on the surface crack rate of the inspection shooting points; the unmanned aerial vehicle device performs inspection based on the position information of the inspection shooting point to generate an initial image, and sends the initial image to the control device. Under the condition, an initial image shot by the unmanned aerial vehicle device at each inspection shooting point of the area to be inspected is acquired, the image processing analysis technology is utilized for calculating the preset color pixel ratio aiming at the initial image so as to obtain the surface crack rate of the inspection shooting points, and further the surface crack rate of the expansive soil in the reservoir area is obtained, so that the accuracy of the detection of the surface crack rate of the expansive soil in the reservoir area is improved, the on-site soil sampling is not needed due to the on-site detection of the surface crack rate of the expansive soil in the reservoir area, and the real-time performance of the detection is improved. In addition, the system disclosed by the invention is based on an unmanned aerial vehicle high-definition picture shooting technology and a picture processing analysis technology, the unmanned aerial vehicle device flies according to a patrol path, and shoots high-definition images at patrol shooting points with a certain distance, the control device acquires the high-definition images generated by the unmanned aerial vehicle device, and also converts slit pictures shot on site (namely initial images) into binary images and removes the points with wrong conversion, the surface slit rate of the site expansive soil is obtained by calculating the percentage of the pixel accumulation area of the black slit area, so that the analysis accuracy and the rapidness are improved, the manual soil taking and logistics cost are greatly saved. The equipment related to the system has mature products, does not need a large amount of research and development investment, can use various modes such as 4g, wiFi, zigBee and the like in equipment communication, can be combined with a local existing network system, is flexible in use, can be used for local or whole, periodic or sampling, has good adaptability, and is suitable for crack analysis of an expansive soil side slope, and particularly suitable for the expansive soil side slope with large area and difficult on-site large-scale soil taking.
According to embodiments of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.
FIG. 6 is a block diagram of an electronic device for implementing a method for detecting a surface fracture rate of a reservoir swelling soil in accordance with an embodiment of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular telephones, smartphones, wearable electronic devices, and other similar computing devices. The components, connections and relationships of components, and functions of components shown in this disclosure are exemplary only, and are not meant to limit implementations of the disclosure described and/or claimed in this disclosure.
As shown in fig. 6, the electronic device 20 includes a computing unit 21 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM) 22 or a computer program loaded from a storage unit 28 into a Random Access Memory (RAM) 23. In the RAM 23, various programs and data required for the operation of the electronic device 20 may also be stored. The computing unit 21, the ROM 22 and the RAM 23 are connected to each other via a bus 24. An input/output (I/O) interface 25 is also connected to bus 24.
Various components in the electronic device 20 are connected to the I/O interface 25, including: an input unit 26 such as a keyboard, a mouse, etc.; an output unit 27 such as various types of displays, speakers, and the like; a storage unit 28, such as a magnetic disk, an optical disk, or the like, the storage unit 28 being communicatively connected to the computing unit 21; and a communication unit 29 such as a network card, modem, wireless communication transceiver, etc. The communication unit 29 allows the electronic device 20 to exchange information/data with other electronic devices via a computer network, such as the internet, and/or various telecommunication networks.
The computing unit 21 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of computing unit 21 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various specialized Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, etc. The calculation unit 21 performs the respective methods and processes described above, for example, performs a reservoir region expansive soil surface fracture rate detection method. For example, in some embodiments, the reservoir swelling soil surface fracture rate detection method may be implemented as a computer software program tangibly embodied on a machine-readable medium, such as the storage unit 28. In some embodiments, part or all of the computer program may be loaded and/or installed onto the electronic device 20 via the ROM 22 and/or the communication unit 29. When the computer program is loaded into the RAM 23 and executed by the calculation unit 21, one or more steps of the above-described method for detecting the surface fracture rate of the reservoir region expansive soil may be performed. Alternatively, in other embodiments, the computing unit 21 may be configured to perform the reservoir swelling soil surface fracture rate detection method by any other suitable means (e.g., by means of firmware).
Various implementations of the systems and techniques described above in this disclosure may be implemented in digital electronic circuitry, integrated circuit systems, field Programmable Gate Arrays (FPGAs), application Specific Integrated Circuits (ASICs), application Specific Standard Products (ASSPs), systems On Chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs, the one or more computer programs may be executed and/or interpreted on a programmable system including at least one programmable processor, which may be a special purpose or general-purpose programmable processor, that may receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for carrying out methods of the present disclosure may be written in any combination of one or more programming languages. These program code may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus such that the program code, when executed by the processor or controller, causes the functions/operations specified in the flowchart and/or block diagram to be implemented. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package, partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or electronic device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. The machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or electronic device, or any suitable combination of the preceding. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage electronic device, a magnetic storage electronic device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and pointing device (e.g., a mouse or trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic input, speech input, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a background component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such background, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), wide Area Networks (WANs), the internet, and blockchain networks.
The computer system may include a client and a server. The client and server are typically remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server can be a cloud server, also called a cloud computing server or a cloud host, and is a host product in a cloud computing service system, so that the defects of high management difficulty and weak service expansibility in the traditional physical hosts and VPS service ("Virtual Private Server" or simply "VPS") are overcome. The server may also be a server of a distributed system or a server that incorporates a blockchain.
It should be appreciated that various forms of the flows shown above may be used to reorder, add, or delete steps. For example, the steps described in the present disclosure may be performed in parallel, sequentially, or in a different order, so long as the desired result of the technical solution of the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be taken as limiting the scope of the present disclosure. It will be apparent to those skilled in the art that various modifications, combinations, sub-combinations and alternatives are possible, depending on design requirements and other factors. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present disclosure are intended to be included within the scope of the present disclosure.
Claims (5)
1. The method for detecting the surface fracture rate of the expansive soil in the reservoir area is characterized by comprising the following steps of:
determining an area to be inspected based on the reservoir area expansive soil area;
generating a plurality of inspection shooting points based on the area to be inspected so as to control the unmanned aerial vehicle device to carry out inspection shooting according to the inspection shooting points;
obtaining initial images of all inspection shooting points shot by the unmanned aerial vehicle device, and calculating a preset color pixel ratio based on the initial images so as to obtain the surface crack rate of all the inspection shooting points;
Obtaining the surface crack rate of the expansive soil in the reservoir area based on the surface crack rate of the inspection shooting point;
the obtaining the initial image of each inspection shooting point shot by the unmanned aerial vehicle device comprises the following steps:
determining at least 3 time points for each patrol shooting point, wherein the at least 3 time points comprise an initial time point and an end time point;
obtaining initial images corresponding to all time points of the inspection shooting point, and if rainfall occurs in the period from the initial time point to the ending time point, re-obtaining the initial images corresponding to all time points of the inspection shooting point after the rainfall is ended;
the calculating the preset color pixel ratio based on the initial image so as to obtain the surface crack rate of each inspection shooting point comprises the following steps:
the preset color is black, gray processing and binarization processing are sequentially carried out on the initial image corresponding to each time point to obtain a binary image, and the black pixel duty ratio is calculated based on the binary image, so that the surface crack rate of the time point is obtained;
selecting a maximum value from the surface crack rates of all time points as the surface crack rate of each inspection shooting point;
the method for obtaining the surface crack rate of the expansive soil in the reservoir area based on the surface crack rate of the inspection shooting point comprises the following steps:
Calculating the average value of the surface crack rate of all the inspection shooting points;
comparing the surface crack rate of each inspection shooting point with the average value, filtering out inspection shooting points with errors of the surface crack rate and the average value larger than a set threshold value, and obtaining a target inspection shooting point set;
and calculating the average value of the surface crack rate of all the inspection shooting points in the target inspection shooting point set, and further obtaining the surface crack rate of the expansive soil in the reservoir area.
2. The method for detecting the surface fracture rate of the expansive soil in the reservoir according to claim 1, wherein the determining the area to be inspected based on the expansive soil in the reservoir comprises:
obtaining a slope range based on the reservoir region expansive soil region;
planning a range to be patrolled and examined at a set distance from the outside of the slope range to the slope range, and taking an area covered in the range to be patrolled and examined as the area to be patrolled and examined.
3. The method for detecting the surface crack rate of the expansive soil in the reservoir area according to claim 1, wherein the generating a plurality of inspection shooting points based on the area to be inspected comprises:
generating a zigzag broken line inspection path based on the area to be inspected;
and setting a set number of inspection shooting points on each line segment of the broken line inspection path, thereby obtaining all the inspection shooting points of the area to be inspected.
4. A system for detecting the surface fracture rate of expansive soil in a reservoir region, comprising:
the control device is used for determining an area to be inspected based on the storage area expansive soil area, generating a plurality of inspection shooting points based on the area to be inspected and sending the position information of the inspection shooting points to the unmanned aerial vehicle device, obtaining an initial image shot by the unmanned aerial vehicle device, calculating a preset color pixel duty ratio based on the initial image, thereby obtaining the surface crack rate of each inspection shooting point, and obtaining the storage area expansive soil surface crack rate based on the surface crack rate of each inspection shooting point;
the unmanned aerial vehicle device is used for carrying out inspection based on the position information of the inspection shooting point to generate an initial image, and sending the initial image to the control device;
the control device is also used for:
determining at least 3 time points for each patrol shooting point, wherein the at least 3 time points comprise an initial time point and an end time point; obtaining initial images corresponding to all time points of the inspection shooting point, and if rainfall occurs in the period from the initial time point to the ending time point, re-obtaining the initial images corresponding to all time points of the inspection shooting point after the rainfall is ended;
The preset color is black, gray processing and binarization processing are sequentially carried out on the initial image corresponding to each time point to obtain a binary image, and the black pixel duty ratio is calculated based on the binary image, so that the surface crack rate of the time point is obtained; selecting a maximum value from the surface crack rates of all time points as the surface crack rate of each inspection shooting point;
the control device is also used for:
calculating the average value of the surface crack rate of all the inspection shooting points; comparing the surface crack rate of each inspection shooting point with the average value, filtering out inspection shooting points with errors of the surface crack rate and the average value larger than a set threshold value, and obtaining a target inspection shooting point set; and calculating the average value of the surface crack rate of all the inspection shooting points in the target inspection shooting point set, and further obtaining the surface crack rate of the expansive soil in the reservoir area.
5. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein, the liquid crystal display device comprises a liquid crystal display device,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the reservoir swelling soil surface fracture rate detection method of any one of claims 1-3.
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