Crystallization early warning method, device, equipment and medium based on tunnel drainage pipe

Abstract

The present invention discloses a crystallization warning method, device, equipment and medium based on tunnel drainage pipes, which relates to the field of automated energy-saving control technology. The method includes: extracting a feature area image of a drainage pipe image, and generating feature point image depth data corresponding to the feature area image; extracting crystallization feature information in the feature point image depth data, and tracking the crystallization feature information respectively; obtaining the position of the stacked crystallization feature point according to the tracked crystallization feature information; calculating the crystallization stacking distance between the initial crystallization feature point position and the stacked crystallization feature point position; generating a warning message when the crystallization stacking distance is greater than a preset stacking threshold. This solves the problem in the prior art that when descaling the drainage pipe, crystals adhere to the inner wall of the pipe, making it impossible to observe the internal situation of the drainage pipe, and thus it is impossible to effectively judge the scaling situation of the inner wall of the drainage pipe.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a crystallization early warning method, device, equipment and medium based on a tunnel drainage pipe. Background Art

[0002] As the scale of transportation infrastructure continues to expand, the progress of tunnel construction has moved forward, bringing great convenience to travel. However, various diseases will occur in the subsequent operation of the tunnel, and water leakage is one of the main types of tunnel diseases. Tunnel water leakage not only affects the appearance of the tunnel, but also greatly threatens the operational safety of the tunnel. During the use of the tunnel drainage system, calcium, magnesium ions and other ions in the tunnel concrete and surrounding rock will react with carbon dioxide in the air after dissolving in water to form crystalline precipitates. After long-term accumulation, it will cause blockage of the horizontal drainage pipes and cause tunnel water leakage. The existing drainage pipes are fixed to the inner wall of the tunnel. After long-term use, the inner wall of the drainage pipes will scale, which requires manual cleaning on a regular basis. However, the crystals adhere to the inner wall of the pipe, and the internal situation of the drainage pipe cannot be observed, making it impossible to effectively judge the scaling condition of the inner wall of the drainage pipe. Therefore, it is necessary to propose a more reasonable technical solution to solve the problems existing in the existing technology. Summary of the Invention

[0003] In order to solve the problem in the prior art that when descaling the drain pipe, crystals adhere to the inner wall of the pipe, the internal situation of the drain pipe cannot be observed, and thus the scaling situation of the inner wall of the drain pipe cannot be effectively judged.

[0004] In a first aspect, an embodiment of the present invention provides a crystallization early warning method based on a tunnel drainage pipe, the method comprising:

[0005] When the drain pipe image is acquired, a feature area image of the drain pipe image is extracted, and feature point image depth data corresponding to the feature area image is generated, wherein the feature point image depth data includes the number of bits of the corresponding pixel;

[0006] Scanning pixels of the feature point image depth data one by one, extracting crystallization feature information in the feature point image depth data, and tracking the crystallization feature information respectively;

[0007] When it is detected that the crystallization feature point positions corresponding to the tracked crystallization feature information are stacked from the initial crystallization feature point positions, obtaining the stacked crystallization feature point positions according to the tracked crystallization feature information;

[0008] Calculating the crystal stacking distance between the initial crystallization feature point position and the crystallization feature point position after stacking;

[0009] When the crystal stacking distance is greater than a preset stacking threshold, an early warning message is generated.

[0010] Preferably, the steps of extracting crystallization feature information from the feature point image depth data and tracking the crystallization feature information respectively include:

[0011] Extracting crystallization feature information from the feature point image depth data, and detecting whether the crystallization feature information contains preset pipeline initial feature information;

[0012] If it is detected that the crystallization characteristic information includes the preset pipeline initial characteristic information, the crystallization characteristic information is tracked; if it is detected that the crystallization characteristic information does not include the preset pipeline initial characteristic information, an operation prompt message is sent.

[0013] Preferably, the step of extracting the characteristic region image of the drain pipe image further includes:

[0014] Decompose the acquired drainage pipe image into multiple monitoring areas;

[0015] Feature area images are extracted in each monitoring area.

[0016] Preferably, before the step of acquiring the drain pipe image, the method further includes:

[0017] The drainage pipe environmental data is obtained at a preset interval, and it is determined whether the environmental data meets the preset image acquisition conditions. When the environmental data does not meet the preset image acquisition conditions, the drainage pipe shooting area is supplemented with light according to the current environmental data and the preset image acquisition conditions.

[0018] In a second aspect, an embodiment of the present invention provides a crystallization warning device based on a tunnel drainage pipe, the device comprising:

[0019] An image depth data module is used to extract a feature area image of the drain pipe image when acquiring the drain pipe image, and generate feature point image depth data corresponding to the feature area image, wherein the feature point image depth data includes the number of bits of the corresponding pixel;

[0020] A crystallization feature information tracking module is used to scan pixels of the feature point image depth data one by one, extract crystallization feature information from the feature point image depth data, and track the crystallization feature information respectively;

[0021] a stacking data acquisition module for acquiring the positions of the crystallization feature points after stacking according to the tracked crystallization feature information when it is detected that the crystallization feature point positions corresponding to the tracked crystallization feature information are stacked from the initial crystallization feature point positions;

[0022] A stacking distance processing module is used to calculate the crystal stacking distance between the initial crystallization feature point position and the crystallization feature point position after stacking;

[0023] The early warning module is used to generate early warning information when the crystal stacking distance is greater than a preset stacking threshold.

[0024] Preferably, the crystallization characteristic information tracking module includes:

[0025] An initial feature information detection unit is used to extract crystallization feature information from the feature point image depth data and detect whether the crystallization feature information contains preset pipeline initial feature information;

[0026] The prompt unit is used to track the crystallization characteristic information if it is detected that the crystallization characteristic information includes the preset pipeline initial characteristic information; if it is detected that the crystallization characteristic information does not include the preset pipeline initial characteristic information, send an operation prompt information.

[0027] Preferably, the image depth data module includes:

[0028] A monitoring area decomposition unit, used for decomposing the acquired drainage pipe image into multiple monitoring areas;

[0029] The regional data extraction unit extracts characteristic regional images in each monitoring area.

[0030] Preferably, it also includes an environmental correction module, which is used to obtain the drainage pipe environmental data according to a preset interval time, determine whether the environmental data meets the preset image acquisition conditions, and when the environmental data does not meet the preset image acquisition conditions, fill in the light of the drainage pipe shooting area according to the current environmental data and the preset image acquisition conditions.

[0031] In a third aspect, an embodiment of the present invention proposes a computer device comprising a memory and a processor that are communicatively connected, wherein the memory is used to store a computer program, and the processor is used to read the computer program and execute the crystallization warning method based on the tunnel drainage pipe proposed in the above embodiment.

[0032] In a fourth aspect, an embodiment of the present invention proposes a computer-readable storage medium having instructions stored thereon. When the instructions are run on a computer, the crystallization warning method based on the tunnel drainage pipe proposed in the above embodiment is executed.

[0033] Beneficial Effects: A camera device installed inside a drain pipe captures images of the drain pipe with a time delay. The time interval for capturing the images can be set based on the rock formation properties, the length and inclination of the drain pipe, or the pipe diameter. After acquiring the drain pipe image, a feature region image is extracted from the drain pipe image, and feature point image depth data corresponding to the feature region image is generated. The feature point image depth data includes the number of bits corresponding to the pixel and can also be used to measure the image's color resolution. After generating the feature point image depth data, edge detection and noise thresholding are performed on the feature point image depth data, and the pixels of the feature point image depth data are scanned one by one to extract crystallization feature information from the feature point image depth data. The crystallization feature information can include scale contour information and feature information of each major protrusion within the scale. After extracting the crystallization feature information, the position of the scale relative to the camera device and the position of each major protrusion within the scale relative to the camera device can be analyzed based on the crystallization feature information to initiate time-delay tracking of the scale location corresponding to the crystallization feature information. During the time-lapse tracking of the scale location corresponding to the crystallization characteristic information, if the scale contour information and the major protrusions within the scale are stacked in a certain direction, the server connected to the camera device can identify the scale stacking direction based on the scale location corresponding to the tracked crystallization characteristic information. The specific process for identifying the scale stacking direction can include: using image subtraction to compare the pixel differences between two adjacent frames, the scale location within each frame can be found. Based on the scale location within each frame, the entire stacking process of the scale movement can be identified, and the scale stacking direction can be further identified based on this stacking process. Because the camera device captures images within the drain pipe in a time-lapse manner, the scale location corresponding to the time-lapse tracked crystallization characteristic information is also constantly changing, meaning that the camera device can track the scale location in a time-lapse manner. After obtaining the current stacking position, the crystal stacking distance can be determined based on the initial stacking position. A stacking threshold can be set based on the properties of the rock formation in which the drain pipe is located, the length and inclination of the drain pipe, or the diameter of the drain pipe. When the crystal stacking distance exceeds the preset stacking threshold, an alert is generated to notify staff to clean the scale within the drain pipe. This solves the problem in the prior art that when descaling the drain pipe, crystals adhere to the inner wall of the pipe, making it impossible to observe the internal situation of the drain pipe and thus unable to effectively judge the scaling condition of the inner wall of the drain pipe. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference numerals are used throughout the accompanying drawings to denote the same components. In the accompanying drawings:

[0035] Figure 1This is a flow chart of a crystallization early warning method based on tunnel drainage pipes;

[0036] Figure 2 This is a functional module diagram of a crystallization warning device based on tunnel drainage pipes;

[0037] Figure 3 This is a functional module diagram of another crystallization warning device based on tunnel drainage pipes;

[0038] Figure 4 It is a structural diagram of a computer device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0039] In order to more clearly illustrate the embodiments of the invention or the technical solutions in the prior art, the invention will be briefly introduced below in conjunction with the drawings and the description of the embodiments or the prior art. Obviously, the following description of the structures of the drawings is only some embodiments of the invention. For those skilled in the art, other drawings can be obtained based on these drawings without inventive work. It should be noted that the description of these embodiments is used to help understand the invention, but does not constitute a limitation of the invention.

[0040] For the first aspect, see Figure 1, a crystallization early warning method based on a tunnel drainage pipe proposed in an embodiment of the present invention is applied to a server connected to a camera device; wherein the server can be executed by, but is not limited to, a computer device with certain computing resources, such as a personal computer (Personal Computer, PC, refers to a multi-purpose computer with a size, price and performance suitable for personal use; desktops, laptops, small laptops, tablets and ultrabooks are all personal computers), smart phones, personal digital assistants (Personal digital assistants) An electronic device such as a computer assistant (PAD) or a platform server is used to extract a feature area image of the drain pipe image when a drain pipe image is acquired, and generate feature point image depth data corresponding to the feature area image, wherein the feature point image depth data includes the number of bits of the corresponding pixel; scan the pixels of the feature point image depth data one by one, extract the crystallization feature information in the feature point image depth data, and track the crystallization feature information respectively; when it is detected that the crystallization feature point position corresponding to the tracked crystallization feature information starts to stack from the initial crystallization feature point position, obtain the stacked crystallization feature point position according to the tracked crystallization feature information; calculate the crystallization stacking distance between the initial crystallization feature point position and the stacked crystallization feature point position; when the crystallization stacking distance is greater than a preset stacking threshold, generate an early warning message. This solves the problem in the prior art that when descaling the drain pipe, crystals adhere to the inner wall of the pipe, making it impossible to observe the internal situation of the drain pipe, and thus it is impossible to effectively judge the scaling situation of the inner wall of the drain pipe.

[0041] It can be understood that the aforementioned execution entities do not constitute a limitation on the embodiments of the present application. Accordingly, the operation steps of the present method may be, but are not limited to, the following steps S11 to S14.

[0042] Step S11: when the drain pipe image is acquired, extract the characteristic region image of the drain pipe image and generate characteristic point image depth data corresponding to the characteristic region image, wherein the characteristic point image depth data includes the number of bits of the corresponding pixel;

[0043] A camera device installed inside the drain pipe captures images of the drain pipe with a time delay. The time interval for capturing the images of the drain pipe can be set based on the rock formation properties, the length and inclination of the drain pipe, or the diameter of the drain pipe. After acquiring the drain pipe image, a feature region image of the drain pipe image is extracted, and feature point image depth data corresponding to the feature region image is generated. The feature point image depth data includes the number of bits corresponding to the pixel and can also be used to measure the color resolution of the image. The method for generating the feature point image depth data can be a monocular depth estimation method, a binocular depth estimation method, or other existing depth estimation algorithms.

[0044] Step S12, scanning pixels of the feature point image depth data one by one, extracting crystallization feature information in the feature point image depth data, and performing time-delay tracking on the crystallization feature information respectively;

[0045] After generating the feature point image depth data, edge detection and noise threshold processing are performed on the feature point image depth data, and the pixels of the feature point image depth data are scanned one by one to extract the crystallization feature information in the feature point image depth data. The crystallization feature information may include scale contour information and feature information of each major protrusion in the scale. After extracting the crystallization feature information, the position of the scale relative to the camera device and the position of each major protrusion in the scale relative to the camera device can be analyzed based on the crystallization feature information to initiate time-lapse tracking of the scale position corresponding to the crystallization feature information.

[0046] Step S13, when it is detected that the crystallization feature point positions corresponding to the tracked crystallization feature information are stacked from the initial crystallization feature point positions, obtaining the stacked crystallization feature point positions according to the tracked crystallization feature information;

[0047] During the delayed tracking of the scaling position corresponding to the crystallization characteristic information, if the scaling contour information and the main protrusions in the scaling are stacked in a certain direction, the server connected to the camera device can identify the scaling stacking direction based on the scaling position corresponding to the tracked crystallization characteristic information. The specific identification process of the scaling stacking direction can be: by comparing the pixel differences between two adjacent frames through image subtraction, the scaling position in each frame can be found, and then the entire stacking process of the scaling movement can be identified based on the scaling position in each frame, so that the scaling stacking direction can be further identified based on the stacking process.

[0048] Step S14, calculating the crystal stacking distance between the initial crystallization feature point position and the crystallization feature point position after stacking;

[0049] Since the camera captures images inside the drain pipe with a time delay, the scaling position corresponding to the crystallization characteristic information tracked with a time delay is also constantly changing, that is, the camera can track the scaling position with a time delay. After obtaining the current stacking position, the crystal stacking distance can be obtained based on the initial stacking position. It is clear that in order to facilitate the identification of the degree of scaling in the drain pipe, the initial stacking position can be set to the stacking position when scaling has not yet appeared in the drain pipe; or, the initial stacking position when scaling has not been completely removed after cleaning.

[0050] Step S15: When the crystal stacking distance is greater than a preset stacking threshold, a warning message is generated.

[0051] A stacking threshold can be set based on the rock formation properties, pipe length, inclination, or pipe diameter. When the distance between crystals stacking exceeds the preset stacking threshold, an alert is generated, notifying staff to clean the scale in the pipe. This solves the existing problem of crystals adhering to the pipe's inner wall during descaling, making it impossible to observe the interior of the pipe and effectively determine the scale condition.

[0052] Preferably, the steps of extracting crystallization feature information from the feature point image depth data and performing time-delay tracking on the crystallization feature information respectively include:

[0053] Extracting crystallization feature information from the feature point image depth data, and detecting whether the crystallization feature information contains preset pipeline initial feature information;

[0054] Specifically, after extracting the crystallization feature information from the feature point image depth data, it is necessary to monitor whether the crystallization feature information contains the preset pipeline initial feature information; wherein, the pipeline initial feature information is the initial scaling stacking data of scaling contour information and each main protrusion in the scaling stacking in a certain direction during the delayed tracking of the scaling position corresponding to the crystallization feature information. In order to facilitate the identification of the degree of scaling in the drain pipe, the initial stacking position corresponding to the pipeline initial feature information can be set to the stacking position when scaling has not yet appeared in the drain pipe; or, the initial stacking position after the scaling has not been completely removed after the scaling is cleaned. Alternatively, the starting position for identifying the scaling stacking direction is always the initial scaling position corresponding to the pipeline initial feature information, and the initial scaling position is the scaling position in the drain pipe when the drain pipe is facing the camera device.

[0055] If it is detected that the crystallization characteristic information includes the preset pipeline initial characteristic information, the crystallization characteristic information is delayed and tracked; if it is detected that the crystallization characteristic information does not include the preset pipeline initial characteristic information, an operation prompt message is sent.

[0056] Specifically, when it is detected that the crystallization characteristic information contains the preset initial pipeline characteristic information, the crystallization characteristic information is tracked with a delay; in the process of delaying the scale position corresponding to the crystallization characteristic information, the initial stacking position corresponding to the initial pipeline characteristic information is used as a reference. If the scale contour information and the main protrusions in the scale are stacked in a certain direction, the server connected to the camera device can identify the scale stacking direction based on the scale position corresponding to the tracked crystallization characteristic information. If it is detected that the crystallization characteristic information does not contain the preset initial pipeline characteristic information, an operation prompt message needs to be sent to allow the administrator to set the stacking threshold between the initial crystallization characteristic point position and the stacked crystallization characteristic point position, so as to facilitate the subsequent monitoring of scale in the drainage pipe.

[0057] Preferably, the step of extracting the characteristic region image of the drain pipe image further includes:

[0058] Decompose the acquired drainage pipe image into multiple monitoring areas;

[0059] After obtaining the drain pipe image, it is necessary to decompose the drain pipe image into multiple monitoring areas and monitor different monitoring areas separately. Specifically, after obtaining the drain pipe image, the image is segmented to obtain a feature area image. The segmentation can be performed according to the connection or bend of the drain pipe, and the time interval for delayed shooting or the stacking threshold can be set at different detection positions.

[0060] Feature area images are extracted in each monitoring area.

[0061] The monitoring area can be set according to the shape, inclination or connection point of the drainage pipe, and the method of extracting the feature area image corresponding to each monitoring area can be set according to the monitoring area.

[0062] Preferably, before the step of acquiring the drain pipe image, the method further includes:

[0063] The drainage pipe environmental data is obtained at a preset interval, and it is determined whether the environmental data meets the preset image acquisition conditions. When the environmental data does not meet the preset image acquisition conditions, the drainage pipe shooting area is supplemented with light according to the current environmental data and the preset image acquisition conditions.

[0064] Specifically, because the drainage pipe is fixed to the inner wall of the tunnel, the camera needs to be protected when not in use. Therefore, time-lapse photography is required, and the time-lapse photography period is adjusted when the shooting conditions are not met. Furthermore, because the drainage pipe is located below ground level, the internal lighting conditions are easily controlled, requiring only fill lighting during photography. This is accomplished by acquiring the current environmental data of the drainage pipe and applying fill lighting to the captured area based on this data and pre-set image acquisition conditions.

[0065] For the second aspect, please see Figures 2 to 3 The embodiment of the present invention provides a crystallization warning device 100 based on a tunnel drainage pipe, the device comprising:

[0066] The image depth data module 110 is used to extract a feature area image of the drain pipe image when acquiring the drain pipe image, and generate feature point image depth data corresponding to the feature area image, wherein the feature point image depth data includes the number of bits of the corresponding pixel;

[0067] A camera device installed inside the drain pipe captures images of the drain pipe with a time delay. The time interval for capturing the images of the drain pipe can be set based on the rock formation properties, the length and inclination of the drain pipe, or the diameter of the drain pipe. After acquiring the drain pipe image, a feature region image of the drain pipe image is extracted, and feature point image depth data corresponding to the feature region image is generated. The feature point image depth data includes the number of bits corresponding to the pixel and can also be used to measure the color resolution of the image. The method for generating the feature point image depth data can be a monocular depth estimation method, a binocular depth estimation method, or other existing depth estimation algorithms.

[0068] The crystallization feature information tracking module 120 is used to scan the pixels of the feature point image depth data one by one, extract the crystallization feature information in the feature point image depth data, and perform time-delay tracking on the crystallization feature information respectively;

[0069] After generating the feature point image depth data, edge detection and noise threshold processing are performed on the feature point image depth data, and the pixels of the feature point image depth data are scanned one by one to extract the crystallization feature information in the feature point image depth data. The crystallization feature information may include scale contour information and feature information of each major protrusion in the scale. After extracting the crystallization feature information, the position of the scale relative to the camera device and the position of each major protrusion in the scale relative to the camera device can be analyzed based on the crystallization feature information to initiate time-lapse tracking of the scale position corresponding to the crystallization feature information.

[0070] The stacking data acquisition module 130 is configured to acquire the positions of the crystallization feature points after stacking according to the tracked crystallization feature information when it is detected that the crystallization feature point positions corresponding to the tracked crystallization feature information are stacked from the initial crystallization feature point positions;

[0071] During the delayed tracking of the scaling position corresponding to the crystallization characteristic information, if the scaling contour information and the main protrusions in the scaling are stacked in a certain direction, the server connected to the camera device can identify the scaling stacking direction based on the scaling position corresponding to the tracked crystallization characteristic information. The specific identification process of the scaling stacking direction can be: by comparing the pixel differences between two adjacent frames through image subtraction, the scaling position in each frame can be found, and then the entire stacking process of the scaling movement can be identified based on the scaling position in each frame, so that the scaling stacking direction can be further identified based on the stacking process.

[0072] The stacking distance processing module 140 is used to calculate the crystal stacking distance between the initial crystallization feature point position and the crystallization feature point position after stacking;

[0073] Since the camera captures images inside the drain pipe with a time delay, the scaling position corresponding to the crystallization characteristic information tracked with a time delay is also constantly changing, that is, the camera can track the scaling position with a time delay. After obtaining the current stacking position, the crystal stacking distance can be obtained based on the initial stacking position. It is clear that in order to facilitate the identification of the degree of scaling in the drain pipe, the initial stacking position can be set to the stacking position when scaling has not yet appeared in the drain pipe; or, the initial stacking position when scaling has not been completely removed after cleaning.

[0074] The warning module 150 is configured to generate a warning message when the crystal stacking distance is greater than a preset stacking threshold.

[0075] A stacking threshold can be set based on the rock formation properties, pipe length, inclination, or pipe diameter. When the distance between crystals stacking exceeds the preset stacking threshold, an alert is generated, notifying staff to clean the scale in the pipe. This solves the existing problem of crystals adhering to the pipe's inner wall during descaling, making it impossible to observe the interior of the pipe and effectively determine the scale condition.

[0076] Preferably, the crystallization characteristic information tracking module 120 includes:

[0077] The initial feature information detection unit 121 is used to extract crystallization feature information from the feature point image depth data and detect whether the crystallization feature information contains preset pipeline initial feature information;

[0078] Specifically, after extracting the crystallization feature information from the feature point image depth data, it is necessary to monitor whether the crystallization feature information contains the preset pipeline initial feature information; wherein, the pipeline initial feature information is the initial scaling stacking data of scaling contour information and each main protrusion in the scaling stacking in a certain direction during the delayed tracking of the scaling position corresponding to the crystallization feature information. In order to facilitate the identification of the degree of scaling in the drain pipe, the initial stacking position corresponding to the pipeline initial feature information can be set to the stacking position when scaling has not yet appeared in the drain pipe; or, the initial stacking position after the scaling has not been completely removed after the scaling is cleaned. Alternatively, the starting position for identifying the scaling stacking direction is always the initial scaling position corresponding to the pipeline initial feature information, and the initial scaling position is the scaling position in the drain pipe when the drain pipe is facing the camera device.

[0079] The prompt unit 122 is configured to perform delayed tracking of the crystallization characteristic information if it is detected that the crystallization characteristic information includes the preset initial pipeline characteristic information; and to send operation prompt information if it is detected that the crystallization characteristic information does not include the preset initial pipeline characteristic information.

[0080] Specifically, when it is detected that the crystallization characteristic information contains the preset initial pipeline characteristic information, the crystallization characteristic information is tracked with a delay; in the process of delaying the scale position corresponding to the crystallization characteristic information, the initial stacking position corresponding to the initial pipeline characteristic information is used as a reference. If the scale contour information and the main protrusions in the scale are stacked in a certain direction, the server connected to the camera device can identify the scale stacking direction based on the scale position corresponding to the tracked crystallization characteristic information. If it is detected that the crystallization characteristic information does not contain the preset initial pipeline characteristic information, an operation prompt message needs to be sent to allow the administrator to set the stacking threshold between the initial crystallization characteristic point position and the stacked crystallization characteristic point position, so as to facilitate the subsequent monitoring of scale in the drainage pipe.

[0081] Preferably, the image depth data module 110 includes:

[0082] A monitoring area decomposition unit 111 is used to decompose the acquired drainage pipe image into multiple monitoring areas;

[0083] After obtaining the drain pipe image, it is necessary to decompose the drain pipe image into multiple monitoring areas and monitor different monitoring areas separately. Specifically, after obtaining the drain pipe image, the image is segmented to obtain a feature area image. The segmentation can be performed according to the connection or bend of the drain pipe, and the time interval for delayed shooting or the stacking threshold can be set at different detection positions.

[0084] The area data extraction unit 112 extracts characteristic area images in each monitoring area.

[0085] The monitoring area can be set according to the shape, inclination or connection point of the drainage pipe, and the method of extracting the feature area image corresponding to each monitoring area can be set according to the monitoring area.

[0086] Preferably, it also includes an environmental correction module 160, which is used to obtain the drainage pipe environmental data according to a preset interval time, determine whether the environmental data meets the preset image acquisition conditions, and when the environmental data does not meet the preset image acquisition conditions, fill in the light of the drainage pipe shooting area according to the current environmental data and the preset image acquisition conditions.

[0087] Specifically, because the drainage pipe is fixed to the inner wall of the tunnel, the camera needs to be protected when not in use. Therefore, time-lapse photography is required, and the time-lapse photography period is adjusted when the shooting conditions are not met. Furthermore, because the drainage pipe is located below ground level, the internal lighting conditions are easily controlled, requiring only fill lighting during photography. This is accomplished by acquiring the current environmental data of the drainage pipe and applying fill lighting to the captured area based on this data and pre-set image acquisition conditions.

[0088] See also Figure 4 In a third aspect, an embodiment of the present application provides a crystallization warning device based on a tunnel drainage pipe, comprising a memory and a processor that are sequentially connected in communication, wherein the memory is used to store a computer program, and the processor is used to read the computer program and execute the crystallization warning method based on a tunnel drainage pipe as in the first aspect of the embodiment. For example, the memory may include, but is not limited to, a random access memory (RAM), a read-only memory (ROM), a flash memory, a first-in-first-out memory (FIFO), and / or a first-in-last-out memory (FILO), etc.; the processor may be, but is not limited to, a microprocessor of the STM32F105 series, an ARM (Advanced RISC Machines), an X86 architecture processor, or a processor with an integrated NPU (neural-network processing unit).

[0089] The working process, working details and technical effects of the device provided in the third aspect of this embodiment can be found in the first aspect of the embodiment and will not be described in detail here.

[0090] A fourth aspect of this embodiment provides a computer-readable storage medium storing instructions for the crystallization early warning method for tunnel drainage pipes according to the first aspect of the embodiment. Specifically, the computer-readable storage medium stores instructions that, when executed on a computer, execute the crystallization early warning method for tunnel drainage pipes according to the first aspect. The computer-readable storage medium refers to a medium for storing data and may include, but is not limited to, a floppy disk, an optical disk, a hard disk, a flash memory, a USB flash drive, and / or a memory stick. The computer may be a general-purpose computer, a dedicated computer, a computer network, or other programmable device.

[0091] The working process, working details and technical effects of the computer-readable storage medium provided in the fourth aspect of this embodiment can be found in the first aspect of the embodiment and will not be repeated here.

[0092] A fifth aspect of this embodiment provides a computer program product comprising instructions, which, when executed on a computer, causes the computer to execute the crystallization warning method based on a tunnel drainage pipe as described in the first aspect of the embodiment, wherein the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device.

[0093] The various embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units. That is, they may be located in one place or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the embodiments. Persons of ordinary skill in the art will be able to understand and implement the embodiments without inventive effort.

[0094] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course by hardware. Based on this understanding, the above technical solution, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a warehouse code merging device to execute the methods of each embodiment or certain parts of the embodiment.

[0095] Finally, it should be noted that the above are only preferred embodiments of the invention and are not intended to limit the scope of protection of the invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the invention shall be included in the scope of protection of the invention.

Claims

1. A crystallization early warning method based on tunnel drainage pipes, characterized in that: Methods include: When a drain pipe image is acquired, a feature area image of the drain pipe image is extracted, and feature point image depth data corresponding to the feature area image is generated, wherein the feature point image depth data includes the number of bits of the corresponding pixel; Scanning pixels of the feature point image depth data one by one, extracting crystallization feature information in the feature point image depth data, and tracking the crystallization feature information respectively; When it is detected that the crystallization feature point positions corresponding to the tracked crystallization feature information are stacked from the initial crystallization feature point positions, obtaining the stacked crystallization feature point positions according to the tracked crystallization feature information; Calculating a crystal stacking distance between the initial crystallization feature point position and the stacked crystallization feature point position; When the crystal stacking distance is greater than a preset stacking threshold, a warning message is generated.

2. The crystallization early warning method based on tunnel drainage pipe according to claim 1 is characterized in that: The steps of extracting crystallization feature information from the feature point image depth data and tracking the crystallization feature information respectively include: Extracting crystallization feature information from the feature point image depth data, and detecting whether the crystallization feature information includes preset pipeline initial feature information; If it is detected that the crystallization characteristic information includes the preset pipeline initial characteristic information, the crystallization characteristic information is tracked; if it is detected that the crystallization characteristic information does not include the preset pipeline initial characteristic information, an operation prompt message is sent.

3. The crystallization early warning method based on tunnel drainage pipe according to claim 1 is characterized in that: The step of extracting the characteristic region image of the drain pipe image further includes: Decompose the acquired drainage pipe image into multiple monitoring areas; Feature area images are extracted in each monitoring area.

4. The crystallization early warning method based on tunnel drainage pipe according to claim 1 is characterized in that: Before obtaining the drain pipe image, the following steps are also included: The drainage pipe environmental data is obtained at a preset interval, and it is determined whether the environmental data meets the preset image acquisition conditions. When the environmental data does not meet the preset image acquisition conditions, the drainage pipe shooting area is supplemented with light according to the current environmental data and the preset image acquisition conditions.

5. A crystallization warning device based on a tunnel drainage pipe, characterized in that: The device comprises: An image depth data module is used to extract a feature area image of the drain pipe image when acquiring the drain pipe image, and generate feature point image depth data corresponding to the feature area image, wherein the feature point image depth data includes the number of bits of the corresponding pixel; a crystallization feature information tracking module, configured to scan pixels of the feature point image depth data one by one, extract crystallization feature information from the feature point image depth data, and track the crystallization feature information respectively; a stacking data acquisition module, configured to, when detecting that the crystallization feature point positions corresponding to the tracked crystallization feature information start to stack from the initial crystallization feature point positions, acquire the crystallization feature point positions after stacking according to the tracked crystallization feature information; a stacking distance processing module, configured to calculate a crystal stacking distance between the initial crystallization feature point position and the crystallization feature point position after stacking; The early warning module is used to generate early warning information when the crystal stacking distance is greater than a preset stacking threshold.

6. The crystallization warning device based on tunnel drainage pipe according to claim 5 is characterized in that: The crystallization characteristic information tracking module includes: an initial feature information detection unit, configured to extract crystallization feature information from the feature point image depth data, and detect whether the crystallization feature information includes preset pipeline initial feature information; The prompt unit is configured to track the crystallization characteristic information if it is detected that the crystallization characteristic information includes the preset pipeline initial characteristic information; and send operation prompt information if it is detected that the crystallization characteristic information does not include the preset pipeline initial characteristic information.

7. The crystallization warning device based on tunnel drainage pipe according to claim 5 is characterized in that: The image depth data module includes: A monitoring area decomposition unit, used for decomposing the acquired drainage pipe image into multiple monitoring areas; The regional data extraction unit extracts characteristic regional images in each monitoring area.

8. The crystallization warning device based on tunnel drainage pipe according to claim 5 is characterized in that: It also includes an environmental correction module; the environmental correction module is used to obtain drainage pipe environmental data according to a preset interval time, determine whether the environmental data meets the preset image acquisition conditions, and when the environmental data does not meet the preset image acquisition conditions, fill in the light of the drainage pipe shooting area according to the current environmental data and the preset image acquisition conditions.

9. A computer device, characterized in that: The invention comprises a memory and a processor which are communicatively connected, wherein the memory is used to store a computer program, and the processor is used to read the computer program and execute the crystallization early warning method based on the tunnel drainage pipe as described in any one of claims 1 to 4.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed on a computer, the crystallization early warning method based on a tunnel drainage pipe as claimed in any one of claims 1 to 4 is executed.

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