Comprehensive Detection System and Method for Bored Pile Hole Formation Quality

Abstract

The present invention provides a comprehensive detection system and method for the hole-forming quality of dug piles. The system includes a first acquisition module for acquiring a first image thereof towards the surface to be detected; a second acquisition module for acquiring a second image thereof towards the surface to be detected; a data processing module for receiving the first image and the second image; a comparison module for obtaining first precision data in the first direction or the second direction of the same surface to be detected in a continuous sampling image set and generating a marked image area; obtaining second precision data of different surfaces to be detected; a third acquisition module configured to acquire first ranging data and second ranging data from the center of the marked image area to its respective boundaries, and calculate to obtain third precision data; a processor for obtaining a detection data set. The present invention realizes the comprehensive detection of the hole-forming quality in dug piles.

Description

Technical Field

[0001] The present invention belongs to the field of in - hole quality detection, and particularly relates to a comprehensive detection system and method for the in - hole quality of dug piles. Background Art

[0002] In foundation treatment, it is a common foundation treatment method to perform concrete pouring after forming a hole using a dug pile. Whether the quality of the formed hole meets the design and specification requirements is directly related to the quality of the concrete - poured pile, and plays a decisive role in the stability of the upper structure.

[0003] Currently, in the specifications, the detection methods for various indicators in the in - hole quality detection process before pouring concrete after hole formation basically rely on manual inspection. There are great limitations and deficiencies in the accuracy of the acceptance control of the in - hole quality of pile foundations, and there is still a large gap from the accuracy index control.

[0004] How to conveniently, quickly, and accurately measure various indicators to overcome the limitations and deficiencies of the above problems, and display various indicator parameters through computer image and vision detection has become the key to the problem. In view of this, it is urgent to propose a comprehensive detection system and method for dug piles. Summary of the Invention

[0005] Therefore, the present invention provides a comprehensive detection system and method for the in - hole quality of dug piles to provide comprehensive detection of the in - hole quality.

[0006] In the first aspect of the present invention, a comprehensive detection system for the in - hole quality of dug piles is provided, including:

[0007] A first acquisition module configured to acquire a first image of its target detection surface;

[0008] A second acquisition module configured to acquire a second image of its target detection surface, and the first acquisition module is set to have an imaging signal source different from that of the first acquisition module;

[0009] A data processing module configured to receive the first image and the second image, and obtain a continuous sampling image set of the first direction and / or the second direction of the target detection surface after the first pre - processing;

[0010] A comparison module having a first configuration and a second configuration. The first configuration is to obtain first accuracy data of the same target detection surface in the first direction or the second direction in the continuous sampling image set and generate a marked image area;

[0011] The second configuration is to obtain second accuracy data of different target detection surfaces in a preset spatial angle interval in the two continuous sampling image sets and generate a marked image area;

[0012] A third acquisition module, configured to acquire first ranging data and second ranging data from the center of the marked image area to its respective boundaries, and calculate third precision data;

[0013] A processor, configured to receive marked image data from a comparison module, send a ranging signal to the third acquisition module and then acquire the ranging data, and obtain a detection data set based on the marked image area, the first, second, and third precision data.

[0014] Further, it further includes a communication module, which receives the detection data set from the processor and transmits the data to the server after establishing a communication connection.

[0015] Further, it further includes a display module, which receives the detection data set from the communication module or the processor and is configured to display the first image, the second image, and the detection data set according to a preset display area.

[0016] Further, it further includes a fourth acquisition module, which is configured to detect the atmosphere inside the hole.

[0017] Further, it further includes an alarm module, which is configured to initiate an alarm when the first precision data, the second precision data, the third precision data, and the atmosphere composition exceed a preset threshold.

[0018] In a second aspect of the present invention, there is provided a comprehensive detection method for the hole forming quality of dug piles, including the following steps:

[0019] S1. Determine a first image sampled from the surface to be detected, and determine a plurality of first boundaries in the first image determined by a first gray threshold;

[0020] Within a preset pixel interval of the first boundary, obtain the average gray change rate of different gradients, and determine a plurality of marked pixel blocks in each of the first boundaries;

[0021] S2. Determine a second image sampled from the surface to be detected, obtain a marked image corresponding to the marked pixel block in the second image, and obtain the marked image from a plurality of sampling surfaces in the second image;

[0022] S3. Repeat the execution of S1 - S2 in a specified first direction and / or second direction to obtain each of the marked images, merge the marked images to obtain a marked image area,

[0023] Obtain the pixel area ratio at each of the gradients from the entire marked image area;

[0024] Obtain first precision data obtained from the single-gradient area ratio and the overall-gradient area ratio;

[0025] S4. Obtain the laser data sampled from the marked image area, and obtain the first ranging data and the second ranging data of two sets of planes from the center of the marked image area towards the first boundary;

[0026] The first ranging data is the distance from the center point to the plane where the average gray area is located;

[0027] The second ranging data is the distance from the center point to the preset sampling point of the first boundary after being fitted to the plane where the average gray area is located;

[0028] S5. Traverse and execute S1 - S4 to obtain whether the total area ratio of the marked image areas of each detection surface is within the preset threshold. If not, initiate an alarm;

[0029] If so, execute the next step;

[0030] S6. Taking the first direction or the second direction as the reference plane, obtain the sliced image of the reference plane from the first image or the second image sampled from the surface to be detected, obtain the pixel band with the minimum average gray change rate of the sliced image, and fill the sliced image with the average gray of the pixel band to generate a reference image including laser depth data;

[0031] S7. Taking the other direction outside the reference plane as the calibration plane, obtain the sliced image of the calibration plane from the first image or the second image sampled from the surface to be detected, obtain the pixel band with the minimum average gray change rate of the sliced image, and fill the sliced image with the average gray of the pixel band to generate a calibration image including laser depth data, and different calibration images are set with adjacent sides coinciding;

[0032] S8. Traverse to obtain the spatial angles between the calibration image and each of the reference images;

[0033] S9. Obtain the second precision data including the single - reference spatial angle dispersion rate and the overall spatial angle dispersion rate. If the spatial angle dispersion rate between any calibration image and any reference image is greater than the preset value, or the statistic of the overall spatial angle dispersion rate is greater than the preset ratio, initiate an alarm.

[0034] Further, after executing S8, it also includes:

[0035] If different surfaces to be detected are detected, traverse to obtain the second precision data of each surface to be detected;

[0036] Taking each of the two surfaces to be detected as the reference plane and the calibration plane respectively, execute S6 - S7 to obtain the second precision data between different surfaces to be detected.

[0037] In a third aspect of the present invention, there is provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, it is used to implement the method of the first aspect of the present invention.

[0038] In a fourth aspect of the present invention, there is provided a storage medium for implementing the method provided in the first aspect of the present invention.

[0039] The above technical solution of the present invention has the following advantages compared with the prior art:

[0040] In the present invention, through the image sampling methods of two different signal sources of the first acquisition module and the second acquisition module, the single-image sampling data is calibrated. In this application, the continuously changing gray level in the sampled image is used as a reference to obtain an area with significantly inconsistent gray level changes. After marking this area, two sets of ranging data within the laser ranging calibration area are calibrated to determine whether this area is a qualified hole-forming area, and then the surface depression is judged.

[0041] Furthermore, by obtaining the spatial angles between the calibrated image and each of the reference images, it is judged whether the images obtained only by the image sampling method are qualified hole-forming areas in terms of the spatial angles of the hole-forming straightness, angle, etc. of the detected surface, thereby realizing the comprehensive quality detection of the hole-forming of dug piles including diameter, width, surface depression, and the atmosphere inside the hole. And a display module and an alarm module are configured to update the detection status in real time. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 is a schematic diagram of the module connection of the system provided in the first embodiment of the present invention;

[0043] Figure 2 is a schematic diagram of the module connection of the electronic device provided in the embodiment of the present invention.

[0044] Among them, 30, processor; 31, memory; 32, communication interface; 33, bus. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0045] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0046] Embodiment 1

[0047] In the first aspect of the embodiments of the present disclosure, there is provided a comprehensive detection system for the quality of dug pile hole-forming, asFigure 1 As shown in the figure, it includes:

[0048] A first acquisition module, configured to acquire a first image of it towards the detected surface;

[0049] A second acquisition module, configured to acquire a second image of it towards the detected surface, and the first acquisition module is set to have an imaging signal source different from that of the first acquisition module;

[0050] A data processing module, configured to receive the first image and the second image, and obtain a continuous sampling image set of the first direction and / or the second direction of the detected surface after the first preprocessing;

[0051] A comparison module, which has a first configuration and a second configuration. The first configuration is to obtain first precision data of the same detected surface in the first direction or the second direction in the continuous sampling image set and generate a marked image area;

[0052] The second configuration is to obtain second precision data of different detected surfaces in the continuous sampling image sets of both in a preset spatial angle interval and generate a marked image area;

[0053] A third acquisition module, configured to acquire first ranging data and second ranging data from the center of the marked image area to its respective boundaries, and calculate to obtain third precision data;

[0054] A processor, configured to receive the marked image data from the comparison module, send a ranging signal to the third acquisition module and then acquire the ranging data, and obtain a detection data set according to the marked image area, the first, second, and third precision data.

[0055] Furthermore, it further includes a communication module, which receives the detection data set from the processor, and transmits the data to the server after communication connection.

[0056] Furthermore, it further includes a display module. The display module receives the detection data set from the communication module or the processor, and is configured to display the first image, the second image, and the detection data set according to a preset display area.

[0057] Furthermore, it further includes a fourth acquisition module, which is configured to detect the atmosphere inside the hole.

[0058] Furthermore, it further includes an alarm module, which is configured to initiate an alarm when the first precision data, the second precision data, the third precision data, and the atmosphere composition exceed a preset threshold.

[0059] In the second aspect of the embodiments of the present disclosure, a comprehensive detection method for the hole-forming quality of dug piles is provided, including the following steps:

[0060] S1. Determine the first image sampled from the surface to be detected, and determine multiple first boundaries in the first image determined by the first gray threshold;

[0061] Within the preset pixel interval of the first boundary, obtain the average gray change rate of different gradients, and determine multiple marked pixel blocks in each of the first boundaries;

[0062] S2. Determine the second image sampled from the surface to be detected, obtain the marked image corresponding to the marked pixel block in the second image, and obtain the marked image from multiple sampled surfaces in the second image;

[0063] S3. Repeat steps S1 - S2 in the specified first direction and / or second direction to obtain each of the marked images, and merge the marked images to obtain a marked image area.

[0064] Obtain the pixel area ratio at each of the gradients from the overall marked image area;

[0065] Obtain the first precision data obtained from the single - gradient area ratio and the overall - gradient area ratio;

[0066] S4. Obtain the laser data sampled from the marked image area, and obtain the first ranging data and the second ranging data of two sets of planes from the center of the marked image area towards the first boundary;

[0067] The first ranging data is the distance from the center point to the plane where the average gray area is located;

[0068] The second ranging data is the distance from the center point after being fitted to the plane where the average gray area is located to the preset sampling point of the first boundary;

[0069] S5. Traverse and execute steps S1 - S4 to obtain whether the total area ratio of the marked image areas of each detected surface is within the preset threshold. If not, initiate an alarm;

[0070] If so, execute the next step;

[0071] S6. Taking the first direction or the second direction as the reference plane, obtain the slice image of the reference plane from the first image or the second image sampled from the surface to be detected, obtain the pixel band with the minimum average gray change rate of the slice image, and fill the slice image with the average gray of the pixel band to generate a reference image including laser depth data;

[0072] S7. Taking another direction outside the reference plane as the calibration plane, obtaining a sliced image of the calibration plane from the first image or the second image sampled from the surface to be detected, obtaining the pixel band with the minimum average gray level change rate of the sliced image, and filling the sliced image with the average gray level of the pixel band to generate a calibration image including laser depth data, and different calibration images are set with adjacent sides coinciding;

[0073] S8. Traversing to obtain the spatial angles between the calibration image and each of the reference images;

[0074] S9. Obtaining second precision data including the discrete rate of a single reference spatial angle and the discrete rate of all spatial angles. If the spatial angle discrete rate between any calibration image and any reference image is greater than a preset value, or the statistic of the discrete rate of all spatial angles is greater than a preset ratio, an alarm is initiated.

[0075] In the embodiments of the present disclosure, through the image sampling methods of two different signal sources of the first acquisition module and the second acquisition module, the single image sampling data is calibrated. In this application, the continuously changing gray level in the sampled image is used as a reference to obtain regions with significantly inconsistent gray level changes. After marking this region, two sets of ranging data within the region are calibrated by laser ranging to determine whether this region is a qualified hole-forming region, and then the surface depression is judged.

[0076] The embodiments of the present disclosure also judge, by obtaining the spatial angles between the calibration image and each of the reference images, whether the spatial angles including the straightness and angle of the hole of the surface to be detected in the image obtained only by the image sampling method are qualified hole-forming regions.

[0077] Further, after executing S8, it further includes:

[0078] If different surfaces to be detected are detected, traversing to obtain the second precision data of each surface to be detected;

[0079] Taking each of the two surfaces to be detected as the reference plane and the calibration plane respectively, executing S6 - S7 to obtain the second precision data between different surfaces to be detected, and further obtaining the positional relationship between different surfaces during the hole-forming process.

[0080] The present invention realizes the comprehensive quality detection of the hole formation of dug piles including diameter, width, surface depression and the atmosphere inside the hole by setting the first acquisition module, the second acquisition module, the third acquisition module and the fourth acquisition module, and configures a display module and an alarm module to update the detection status in real time.

[0081] Embodiment 2

[0082] Combined with Figure 2As shown in the figure, the electronic device for comprehensively detecting the hole forming quality of dug piles provided by the embodiments of the present disclosure includes a processor 30 and a memory 31. Optionally, the electronic device may further include a communication interface 32 and a bus 33. Among them, the processor 30, the communication interface 32, and the memory 31 can complete mutual communication through the bus 33. The communication interface 32 can be used for information transmission. The processor 30 can call the logical instructions in the memory 31 to execute the method of the first embodiment above.

[0083] The embodiments of the present disclosure provide a storage medium storing computer-executable instructions, and the computer-executable instructions are set to execute the method as in the first embodiment.

[0084] The above storage medium may be a transient computer-readable storage medium or a non-transient computer-readable storage medium. The non-transient storage medium includes: various media that can store program codes such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs, and may also be a transient storage medium.

[0085] The above description and the accompanying drawings fully illustrate the embodiments of the present disclosure, enabling those skilled in the art to practice them. Other embodiments may include structural, logical, electrical, process, and other changes. The embodiments merely represent possible variations. Unless explicitly required, the individual components and functions are optional, and the order of operations may vary. Parts and features of some embodiments may be included in or replace parts and features of other embodiments. Moreover, the terms used in this application are only for describing the embodiments and do not limit the claims. As used in the description of the embodiments and the claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to also include the plural forms. Similarly, as used in this application, the term "and / or" refers to any and all possible combinations of one or more of the associated listed items. Additionally, when used in this application, the term "comprise" and its variants "comprises" and / or "comprising" etc. mean the presence of the stated features, wholes, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or groups thereof. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, or apparatus comprising the element. Herein, what each embodiment focuses on may be the differences from other embodiments, and the same or similar parts among the embodiments may be referred to each other. For the methods, products, etc. disclosed in the embodiments, if they correspond to the method parts disclosed in the embodiments, the relevant parts may refer to the description of the method parts.

[0086] Those skilled in the art can realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in a hardware or software manner may depend on the specific application and design constraints of the technical solution. The skilled person may use different methods for each specific application to achieve the described functions, but such implementation should not be considered to exceed the scope of the embodiments of the present disclosure. The skilled person can clearly understand that for the convenience and brevity of description, the specific working processes of the above-described devices, apparatuses, and units can refer to the corresponding processes in the foregoing method embodiments, and will not be described herein again.

[0087] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of code, or a portion thereof that contains one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures. For example, two consecutive blocks may in fact be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending upon the functionality involved. In the description corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur out of the order disclosed in the description, and sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may in fact be executed substantially in parallel, or they may sometimes be executed in the reverse order, depending upon the functionality involved. Each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented by dedicated hardware-based devices that perform the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

Claims

1. A comprehensive inspection method for the hole forming quality of dug piles, characterized in that, The steps are as follows: S1. Determine a first image sampled from the surface to be detected, and determine a plurality of first boundaries in the first image determined by a first gray-scale threshold; Within a preset pixel interval of the first boundary, obtain the average gray-scale change rate of different gradients, and determine a plurality of marked pixel blocks in each of the first boundaries; S2. Determine a second image sampled from the surface to be detected, obtain a marked image corresponding to the marked pixel block in the second image, and obtain the marked image from a plurality of sampled surfaces in the second image; S3. Repeat the execution of S1-S2 in a specified first direction and / or second direction to obtain each of the marked images, merge the marked images to obtain a marked image area, Obtain the pixel area ratio at each of the gradients from the overall marked image area; Obtain first accuracy data obtained from the single-gradient area ratio and the overall gradient area ratio; S4. Obtain laser data sampled from the marked image area, and obtain first ranging data and second ranging data of two sets of planes from the center of the marked image area towards the first boundary; The first ranging data is the distance from the center point to the plane where the average gray-scale area is located; The second ranging data is the distance from the center point after being fitted to the plane where the average gray-scale area is located to a preset sampling point of the first boundary; S5. Traverse and execute S1-S4 to obtain whether the total area ratio of the marked image areas of each detection surface is within a preset threshold. If not, initiate an alarm; If so, execute the next step; S6. Taking the first direction or the second direction as a reference plane, obtain a sliced image of the reference plane from the first image or the second image sampled from the surface to be detected, obtain a pixel band with the minimum average gray-scale change rate of the sliced image, and fill the sliced image with the average gray-scale of the pixel band to generate a reference image including laser depth data; S7. Taking the other direction outside the reference plane as a calibration plane, obtain a sliced image of the calibration plane from the first image or the second image sampled from the surface to be detected, obtain a pixel band with the minimum average gray-scale change rate of the sliced image, and fill the sliced image with the average gray-scale of the pixel band to generate a calibration image including laser depth data, and different calibration images are set with adjacent sides coinciding; S8. Traverse and obtain the spatial angles between the calibration image and each of the reference images; S9. Obtain second accuracy data including the single-reference spatial angle dispersion rate and the overall spatial angle dispersion rate. If the spatial angle dispersion rate between any calibration image and any reference image is greater than a preset value, or the statistic of the overall spatial angle dispersion rate is greater than a preset ratio, then initiate an alarm.

2. The comprehensive inspection method for the hole forming quality of dug piles according to claim 1, wherein After executing S8, it further includes: If different surfaces to be detected are detected, traverse and obtain the second accuracy data of each of the surfaces to be detected; Taking each of the two surfaces to be detected as a reference plane and a calibration plane respectively, execute S6-S7 to obtain the second accuracy data between different surfaces to be detected.

3. An electronic device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the method according to any one of claims 1-2.

4. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by a processor, it implements the method described in any one of claims 1-2.

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