Laser rust removal apparatus and laser rust removal method

Abstract

The application relates to the technical field of rust removal, in particular to a laser rust removal equipment and a laser rust removal method. The laser rust removal equipment comprises a shell with a feeding port and a discharging port, a shooting component, a controller and a laser emitter. The shooting component is arranged on the shell and is arranged close to the feeding port. A rust removal position is arranged between the feeding port and the discharging port. The controller and the laser emitter are arranged in the shell. The laser emitter is arranged towards the rust removal position. The controller is electrically connected with the shooting component and the laser emitter. Compared with the existing rust removal by mechanical brushing, the laser rust removal can avoid pipeline abrasion caused by direct contact with the pipeline surface, can avoid the problem that the mechanical brush needs to be frequently maintained due to abrasion, and can improve the rust removal efficiency.

Description

Technical Field

[0001] This invention relates to the field of rust removal technology, and in particular to a laser rust removal device and a laser rust removal method. Background Technology

[0002] Currently, the most common method for removing rust from pipelines is mechanical brushing, which involves using wire brushes, grinders, and other tools to remove rust from the pipelines.

[0003] However, rust removal by mechanical brushing is prone to wear and tear on the pipe surface, and the rust removal efficiency is low and the wear is high. When a large amount of rust removal is required, the mechanical brush will be worn out quickly, thus requiring frequent maintenance, which not only increases maintenance costs, but also seriously affects the rust removal efficiency.

[0004] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0005] The main objective of this invention is to provide a laser rust removal device and a laser rust removal method, which aims to solve the technical problem that the existing rust removal method using mechanical brushes has low rust removal efficiency.

[0006] To achieve the above objectives, the present invention provides a laser rust removal device, which includes: a housing with a feed inlet and a discharge outlet, an imaging component, a controller, and a laser emitter;

[0007] The imaging component is disposed on the housing and is located near the feed inlet. A rust removal position is provided between the feed inlet and the discharge outlet. The controller and the laser emitter are disposed inside the housing, with the laser emitter facing the rust removal position. The controller is electrically connected to the imaging component and the laser emitter respectively.

[0008] The imaging component is used to capture images of the pipe to be derusted and transmit the images to the controller.

[0009] The controller is configured to determine the rusted area based on the pipeline image and generate power parameters based on the rusted area;

[0010] The laser emitter is used to emit a corresponding laser based on the power parameters to perform laser rust removal on the pipe to be rusted.

[0011] Optionally, the laser rust removal equipment further includes: a ranging component;

[0012] The ranging component is disposed on the housing and is located near the feed inlet; the ranging component is electrically connected to the controller.

[0013] The ranging component is used to detect the pipe diameter information of the pipe to be derusted and transmit the pipe diameter information to the controller;

[0014] The controller is also configured to determine focal length information based on the pipe diameter information and transmit the focal length information to the shooting component;

[0015] The imaging component is also used to determine the imaging focal length based on the focal length information, and to take a picture of the pipe to be derusted according to the imaging focal length to obtain a pipe image of the pipe to be derusted.

[0016] Optionally, the laser rust removal equipment further includes: a conveying component;

[0017] The conveying component is located at the rust removal position and is electrically connected to the controller.

[0018] The controller is also configured to determine the rust removal start point and the rust removal end point based on the rusted area, and to determine the rust removal path based on the rust removal start point and the rust removal end point;

[0019] The conveying component is used to rotate the pipe to be derusted according to the derusting path, so that the laser emitter emits a corresponding laser based on the power parameters to perform laser derusting on the pipe to be derusted.

[0020] Furthermore, to achieve the above objectives, the present invention also proposes a laser rust removal method applied to the aforementioned laser rust removal equipment, the method comprising:

[0021] Take images of the pipes to be derusted;

[0022] The corrosion area is determined based on the pipeline image, and power parameters are generated based on the corrosion area;

[0023] Based on the power parameters, a corresponding laser is emitted to perform laser rust removal on the pipeline to be rusted.

[0024] Optionally, the step of determining the rusted area based on the pipe image includes:

[0025] Edge detection is performed on the pipe image to obtain pipe wall pixels, and Hough transform is performed on each pipe wall pixel;

[0026] The transformation results are voted on by each of the tube wall pixels, and the target parameter spatial point is determined based on the voting results;

[0027] Based on the spatial points of each target parameter, the corresponding edge segments are determined, and the pipe wall image is determined based on each edge segment;

[0028] The corroded areas were determined based on the pipe wall images.

[0029] Optionally, the step of determining the rusted area based on the pipe wall image includes:

[0030] The pipe wall image is segmented by color to obtain a first prediction region;

[0031] Feature extraction is performed on the pipe wall image to obtain the texture features corresponding to the pipe wall image;

[0032] The second prediction region is determined based on the texture features;

[0033] The rusted area is determined based on the first and second predicted areas.

[0034] Optionally, the step of generating power parameters based on the rusted area includes:

[0035] The number of pixels and the area of ​​the rusted region are determined, and the rust quantization value corresponding to the rusted region is determined based on the number of pixels and the area.

[0036] A preset scaling factor is obtained, and the power parameters corresponding to the rusted area are determined based on the rust quantification value and the preset scaling factor.

[0037] Optionally, the step of taking images of the pipe to be rusted includes:

[0038] The pipe diameter information of the pipe to be derusted is detected, and the focal length information is determined based on the pipe diameter information;

[0039] The shooting focal length is determined based on the focal length information, and the rust-removed pipe is photographed according to the shooting focal length to obtain a pipe image of the rust-removed pipe.

[0040] Optionally, the step of emitting a laser corresponding to the power parameter to perform laser rust removal on the pipe to be rusted includes:

[0041] The starting point and ending point of rust removal are determined based on the rust removal area, and the rust removal path is determined based on the starting point and ending point of rust removal.

[0042] The pipe to be rusted is rotated according to the rust removal path, and a corresponding laser is emitted based on the power parameters to perform laser rust removal on the pipe.

[0043] Optionally, the step of determining the rust removal path based on the rust removal start point and the rust removal end point includes:

[0044] Determine the extension node based on the rust removal starting point;

[0045] Determine the initial cost between each of the extended nodes and the rust removal start point, and determine the expected cost between each of the extended nodes and the rust removal end point;

[0046] Target nodes are selected from each of the extended nodes based on the initial cost and the expected cost.

[0047] A rust removal path is generated based on the rust removal starting point, the target node, and the rust removal ending point.

[0048] This invention provides a laser rust removal device and method. The laser rust removal device includes: a housing with an inlet and an outlet, an imaging component, a controller, and a laser emitter. The imaging component is disposed on the housing, near the inlet, and a rust removal area is provided between the inlet and outlet. The controller and the laser emitter are disposed inside the housing, with the laser emitter facing the rust removal area. The controller is electrically connected to both the imaging component and the laser emitter. The imaging component is used to capture an image of the pipe to be rusted and transmit the image to the controller. The controller is used to determine the rusted area based on the pipe image and generate power parameters based on the rusted area. The laser emitter is used to emit a corresponding laser based on the power parameters to perform laser rust removal on the pipe. Because this invention uses the imaging component to capture an image of the pipe to be rusted, determines the rusted area based on the obtained image, and then generates power parameters based on the rusted area, the laser emitter can emit a corresponding laser according to the power parameters to perform rust removal. Compared to existing rust removal methods using mechanical brushes, this invention uses lasers for rust removal, which not only avoids pipe wear caused by direct contact with the pipe surface, but also avoids the problem of frequent maintenance due to wear of mechanical brushes, thus improving rust removal efficiency. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0050] Figure 1 This is a front structural diagram of the first embodiment of the laser rust removal equipment proposed in this invention;

[0051] Figure 2 This is a schematic diagram of the structure of the first embodiment of the laser rust removal equipment proposed in this invention, showing the removal of the outer shell.

[0052] Figure 3This is a schematic diagram of the rear structure of the first embodiment of the laser rust removal equipment proposed in this invention;

[0053] Figure 4 This is a schematic flowchart of the first embodiment of the laser rust removal method of the present invention applied to laser rust removal equipment;

[0054] Figure 5 This is a schematic flowchart of the second embodiment of the laser rust removal method of the present invention.

[0055] Explanation of icon numbers:

[0056] 1 case 7 frame 2 feed inlet 8 Distance measuring component 3 discharge port 9 vacuum tube 4 controller 10 Filter 5 Shooting components 11 Waste hopper 6 laser emitter

[0057] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0058] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0059] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0060] Furthermore, if the embodiments of this invention involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the meaning of "and / or" throughout the text includes three parallel solutions; for example, "A and / or B" includes solution A, solution B, or a solution where both A and B are satisfied simultaneously. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed by this invention.

[0061] It should be noted that currently, the common method for removing rust from pipes is mechanical brushing, which involves using wire brushes, grinders, and other tools to remove rust from the pipes.

[0062] However, rust removal by mechanical brushing is prone to wear and tear on the pipe surface, and the rust removal efficiency is low and the wear is high. When a large amount of rust removal is required, the mechanical brush will be worn out quickly, thus requiring frequent maintenance, which not only increases maintenance costs, but also seriously affects the rust removal efficiency.

[0063] Therefore, to address the aforementioned shortcomings, this embodiment provides a laser rust removal device and method. The imaging component 5 captures images of the pipe to be rusted, identifies the rusted areas based on the obtained images, and generates power parameters based on these rusted areas. The laser emitter 6 then emits the corresponding laser beam according to these power parameters for rust removal. Compared to existing rust removal methods using mechanical brushes, this embodiment employs laser rust removal, which not only avoids pipe wear caused by direct contact with the pipe surface but also avoids the frequent maintenance required due to wear on mechanical brushes, thus improving rust removal efficiency.

[0064] For ease of understanding, the following is combined with Figures 1 to 3 The laser rust removal equipment provided in the embodiments of this application will be described in detail.

[0065] Reference Figures 1 to 3 , Figure 1 This is a front structural diagram of the first embodiment of the laser rust removal equipment proposed in this invention. Figure 2 This is a schematic diagram of the structure for removing the outer shell in the first embodiment of the laser rust removal equipment proposed in this invention. Figure 3 This is a schematic diagram of the rear structure of the first embodiment of the laser rust removal equipment proposed in this invention, as shown below. Figures 1 to 3 As shown, in this embodiment, the laser rust removal equipment includes: a housing 1 with a feed inlet 2 and a discharge outlet 3, an imaging component 5, a controller 4, and a laser emitter 6; wherein, the imaging component 5 is disposed on the housing 1 and is disposed near the feed inlet 2, a rust removal position is disposed between the feed inlet 2 and the discharge outlet 3, the controller 4 and the laser emitter 6 are disposed inside the housing 1, the laser emitter 6 is disposed facing the rust removal position, and the controller 4 is electrically connected to the imaging component 5 and the laser emitter 6 respectively.

[0066] It should be noted that, as Figure 1 and Figure 2 As shown, a feed inlet 2 and a discharge outlet 3 can be opened on the housing 1 respectively, and a frame 7 is set inside the housing 1, which can house the rust removal position, the controller 4 and the laser emitter 6.

[0067] In practical use, the pipe to be derusted can be fed into the frame 7 through the feed port 2 and pass through the derusting station. As it passes the derusting station, a laser is emitted from the laser emitter 6 onto the surface of the pipe. The rust on the surface of the pipe is heated to a vaporized or melted state by the laser irradiation, causing the rust to fall off the surface of the pipe, thus achieving the purpose of rust removal. After the rust removal is completed, the pipe can be discharged through the discharge port 3, achieving rust removal for the entire pipe.

[0068] Furthermore, in order to accurately identify the location of rust on the pipe to be rusted, the imaging component 5 is used to capture an image of the pipe to be rusted and transmit the image to the controller 4;

[0069] The controller 4 is used to determine the rusted area based on the pipeline image and generate power parameters based on the rusted area;

[0070] The laser emitter 6 is used to emit a corresponding laser based on the power parameters to perform laser rust removal on the pipe to be rusted.

[0071] It is understood that the aforementioned shooting component 5 can be a camera or other device used for shooting. In this embodiment, a camera is used for illustration, which can capture images of the pipe to be derusted and transmit the pipe images to the controller 4.

[0072] It should be emphasized that, in order to ensure the quality of the image, multiple exposure tests should be conducted in the actual environment when installing the camera to find the best exposure position, so as to ensure that a relatively clear image of the pipeline can be obtained under different lighting conditions. The specific position is not limited in this embodiment.

[0073] The controller 4 can be a device composed of a computer or other equipment with processing capabilities. The camera can transmit the captured image of the pipeline to the controller 4. Since different degrees of corrosion can be removed according to different power, the controller 4 can determine the corrosion area according to the pipeline image and generate parameters (i.e., the power parameters) for adjusting the power of the laser emitted by the laser emitter 6 according to the corrosion area, and transmit the parameters to the laser emitter 6.

[0074] After receiving the power parameters, the laser emitter 6 can emit the corresponding laser to the rusted area according to the parameters, thereby achieving laser rust removal. The laser emitter 6 can be a high-power laser source, or other laser sources used for rust removal. This embodiment does not limit this.

[0075] In this specific implementation, since laser is used for rust removal, it not only avoids pipe wear caused by direct contact with the pipe surface, but also avoids the problem of frequent maintenance due to wear of mechanical brushes, thus improving rust removal efficiency.

[0076] Furthermore, since this embodiment directly uses laser for rust removal, compared to rust removal using chemical solutions, this embodiment does not generate chemical waste, thus avoiding environmental pollution.

[0077] Furthermore, considering that different pipe diameters may require different focal lengths when photographing pipes to be derusted, in order to improve the image quality of the pipes, the following steps are taken: Figure 1 As shown, in this embodiment, the laser rust removal equipment further includes a ranging component 8; wherein the ranging component 8 is disposed on the housing 1 and is located near the feed inlet 2, and the ranging component 8 is electrically connected to the controller 4.

[0078] It should be understood that the aforementioned ranging component 8 can be a component used to measure pipe diameter, such as a laser sensor, and this embodiment does not limit this. In this embodiment, the ranging component 8 can be installed on the housing 1 near the feed inlet 2. The ranging component 8 can measure the pipe diameter of the pipe to be derusted and generate the aforementioned pipe diameter information.

[0079] It should be noted that since the center position of the pipe to be derusted is fixed when it is fed into the feed inlet 2, the pipe diameter can be calculated by measuring the distance between the distance measuring component 8 and the pipe to be derusted, based on the height of the distance measuring sensor from the ground and the height of the center position from the ground.

[0080] Furthermore, in order to enable the ranging sensor to cover the entire diameter of pipes of different specifications to be derusted, the installation height of the ranging sensor can be determined according to the following formula (1) in this embodiment. The specific formula (1) is as follows:

[0081]

[0082] Where H is the installation height of the rangefinder sensor, L is the maximum measuring distance of the rangefinder sensor, which can be determined according to the specifications of the rangefinder sensor in actual use, and D... max The maximum diameter of the pipe to be derusted can be determined based on the maximum diameter that the feed inlet 2 can support.

[0083] The installation height of the distance sensor above the ground can be calculated using the above formula (1), and then it can be installed at this height before use to facilitate the subsequent measurement of pipe diameter.

[0084] Understandably, the ranging component 8 is used to detect the pipe diameter information of the pipe to be derusted and transmit the pipe diameter information to the controller 4;

[0085] The controller 4 is also used to determine the focal length information based on the pipe diameter information and transmit the focal length information to the shooting component 5;

[0086] The imaging component 5 is also used to determine the imaging focal length based on the focal length information, and to take a picture of the pipe to be derusted according to the imaging focal length to obtain a pipe image of the pipe to be derusted.

[0087] In the specific implementation, when the controller 4 receives the pipe diameter information, it can determine the specifications of the pipe to be derusted. In order for the camera to clearly capture the entire pipe, the required shooting focal length of the camera can be determined according to the pipe diameter information. This is because a larger pipe diameter requires a shorter focal length to cover the entire pipe wall, while a smaller pipe diameter can choose a longer focal length.

[0088] Once the controller 4 determines the shooting focal length, it can transmit the generated focal length information to the camera. The camera reads the shooting focal length based on the focal length information, adjusts the focal length accordingly, and then takes the picture, thereby improving the image quality of the obtained pipeline image.

[0089] Furthermore, in order to rotate and transport the pipe to be derusted, in this embodiment, the laser derusting equipment further includes: a conveying component (not shown in the figure); wherein, the conveying component is disposed at the derusting position, and the conveying component is electrically connected to the controller 4.

[0090] It should be understood that the aforementioned conveying component can drive the pipe to be derusted to rotate around the pipe axis and move in the direction from the inlet 2 to the outlet 3. The conveying component in this embodiment can be composed of several motors, and the specific number is not limited in this embodiment.

[0091] It should be noted that the controller 4 is also used to determine the rust removal start point and the rust removal end point based on the rusted area, and to determine the rust removal path based on the rust removal start point and the rust removal end point;

[0092] The conveying component is used to rotate the pipe to be derusted according to the derusting path, so that the laser emitter 6 emits a corresponding laser based on the power parameters to perform laser derusting on the pipe to be derusted.

[0093] It is understood that the aforementioned rust removal starting point can be the starting position of the laser emitter 6 for rust removal, and the aforementioned rust removal ending point can be the ending position of the laser emitter 6 for completing rust removal. In this embodiment, the rust removal starting point and the rust removal ending point can be determined according to the rusted area. The rust removal starting point can be the point corresponding to the edge of the rusted area near the discharge port 3, and the rust removal ending point can be the point corresponding to the edge of the rusted area near the feed port 2. Of course, other methods can also be used to determine these points, and this embodiment does not limit them.

[0094] It should be understood that, in order to reduce the power consumption of the laser emitter 6, this embodiment can determine the rust removal start point and the rust removal end point according to the rust area, and determine a less energy-consuming rust removal path according to the rust removal start point and the rust removal end point. Then, the conveying component can control the movement of the pipe to be rusted according to the rust removal path, so that the laser emitter 6 can perform laser rust removal according to the rust removal path.

[0095] Furthermore, continue as Figure 1 as well as Figure 2 As shown, the laser rust removal equipment may further include: a vacuum cleaner (not shown in the figure), wherein the vacuum cleaner's suction pipe 9 is arranged relative to the rust removal position, the vacuum cleaner is arranged inside the frame 7 and close to the rust removal position, and the vacuum cleaner is electrically connected to the controller 4.

[0096] It should be noted that during the rust removal process, the laser will use high temperature to vaporize the rust material, which will inevitably produce dust-containing gas. Therefore, the vacuum cleaner can be controlled by controller 4 to remove some of the generated gas to prevent it from spreading into the environment and harming the health of technicians.

[0097] Furthermore, in this embodiment, the laser rust removal equipment also includes: a filter 10, which is connected to a vacuum cleaner. The filter 10 can be installed outside the housing 1 and electrically connected to the controller 4. It is used to filter the gas sucked in by the vacuum cleaner so that it can be discharged after meeting emission standards and thus satisfying environmental protection requirements.

[0098] Furthermore, in this embodiment, the aforementioned laser rust removal equipment also includes a waste hopper 11, with its inlet facing upwards and located below the rust removal position. The waste hopper 11 is connected to the filter 10. Since the rust on the pipe to be rusted includes both vaporized and flaked-off portions, the waste hopper 11 collects the flaked-off rust, ensuring the cleanliness of the rust removal environment and facilitating cleaning after the rust removal operation is completed.

[0099] This embodiment uses laser for rust removal, which not only avoids pipe wear caused by direct contact with the pipe surface, but also avoids the problem of frequent maintenance due to wear of mechanical brushes, thus improving rust removal efficiency.

[0100] Based on the laser rust removal equipment described above, this embodiment also provides a laser rust removal method.

[0101] refer to Figure 4 , Figure 4 This is a schematic flowchart of the first embodiment of the laser rust removal method of the present invention applied to laser rust removal equipment.

[0102] like Figure 4 As shown, in this embodiment, the laser rust removal method includes:

[0103] Step S10: Take an image of the pipe to be derusted.

[0104] It should be noted that the laser rust removal method provided in this embodiment can be applied in laser rust removal scenarios. The executing entity of the method in this embodiment can be the aforementioned laser rust removal equipment, or other equipment capable of achieving the same or similar functions. Here, the laser rust removal methods provided in this embodiment and the following embodiments are specifically described using the aforementioned laser rust removal equipment (hereinafter referred to as the equipment).

[0105] Understandably, the aforementioned equipment may be equipped with a camera, which can capture images of the pipe to be derusted.

[0106] Furthermore, considering that different pipe diameters may require different focal lengths when the camera is photographing the pipe to be rusted, and in order to improve the quality of the captured pipe image, in this embodiment, the above step S10 includes:

[0107] Step S11: Detect the pipe diameter information of the pipe to be derusted, and determine the focal length information based on the pipe diameter information.

[0108] It should be noted that the above-mentioned equipment may also be equipped with a ranging component 8 for measuring pipe diameter, such as a laser sensor, etc., and this embodiment does not impose any limitations on this. The ranging component 8 can measure the pipe diameter of the pipe to be derusted and generate the above-mentioned pipe diameter information.

[0109] In practice, once the aforementioned equipment determines the pipe diameter information, the specifications of the pipe to be derusted can be determined. To ensure the camera can clearly capture the entire pipe, the required focal length can be determined based on the pipe diameter information. This is because larger pipe diameters require shorter focal lengths to cover the entire pipe wall, while smaller pipe diameters can use longer focal lengths. Once the focal length is determined, the generated focal length information is transmitted to the camera. The camera reads the focal length information, adjusts its settings accordingly, and then takes the picture, thus improving the image quality of the obtained pipe image.

[0110] Step S20: Determine the rusted area based on the pipeline image, and generate power parameters based on the rusted area.

[0111] It should be understood that the aforementioned rusted area can be any area on the pipe to be derusted that has rust present. In this embodiment, the rusted area can be determined by taking a picture of the pipe. The specific process can be the steps described above for determining the rusted area based on the pipe image, including:

[0112] Step S21: Perform edge detection on the pipe image to obtain pipe wall pixels, and perform Hough transform on each pipe wall pixel.

[0113] Considering that the pipe images captured by the camera may contain a lot of noise, the above-mentioned device can also preprocess the pipe images before performing edge detection, that is, convert the color pipe images into grayscale pipe images, and use Gaussian filters or median filters to denoise the grayscale pipe images. Among them, Gaussian filters can remove noise through convolution operations, which can be achieved by the following formula (2):

[0114] I filtered =G σ *I Formula (2);

[0115] Among them, the above G σ The kernel is a Gaussian kernel, which can be set according to specific needs and image features. This embodiment does not impose any restrictions on it. The above I refers to the pipeline image under the above grayscale. The above formula (2) can remove noise from the pipeline image under grayscale, which is convenient for subsequent processing.

[0116] After noise removal, a preprocessed pipe image can be obtained. At this time, the above-mentioned device can perform edge detection on the preprocessed pipe image to detect the edge of the pipe in the preprocessed pipe image. The edge detection can be implemented using the Canny edge detector, or other methods can be used. This embodiment does not limit this.

[0117] After edge detection, the device can obtain a binarized image with pipe edge pixels (i.e., pipe wall pixels), wherein the pipe wall edge pixels can be converted to white and the background image can be converted to black.

[0118] After obtaining the binarized image, the above-mentioned equipment can perform Hough transform on the binarized image since the pipe to be derusted is generally a straight line. The obtained pipe wall pixels can be converted into parameter space, and polar coordinates (ρ, θ) can be used to represent the straight line corresponding to each pipe wall pixel. ρ can be the distance from the origin to the straight line, the origin can be the upper left corner of the binarized image, and θ can be the angle between the straight line and the X-axis.

[0119] Step S22: Vote on the transformation result using each of the tube wall pixels, and determine the target parameter spatial point based on the voting result.

[0120] Next, the device can vote in the parameter space for each pipe wall pixel. Each pipe wall pixel can vote for possible straight line parameters (ρ, θ). By accumulating the votes in the parameter space, a voting peak can be formed. The device can take each point in the parameter space where the voting peak is higher than a preset threshold as the target parameter space point. This point can represent the straight line with the highest confidence in the image.

[0121] Step S23: Determine the corresponding edge segments based on the spatial points of each target parameter, and determine the pipe wall image based on each edge segment.

[0122] After determining the target parameter spatial points, the above-mentioned equipment can determine the corresponding straight line parameters based on these target parameter spatial points, and connect these straight line parameters to form continuous edge lines (i.e. the aforementioned edge line segments). Then, the pipe wall image containing the pipe can be determined based on the obtained edge lines, and the background area of ​​the image can be removed.

[0123] It should be emphasized that the above method can effectively determine the pipe wall image even when the pipe image contains noise and the rust edges are not completely continuous.

[0124] Step S24: Determine the rusted area based on the pipe wall image.

[0125] Understandably, once the location of the pipe wall is determined, the rusted areas on the pipe wall can be identified. To accurately determine the rusted areas, step S24 above includes:

[0126] Step S241: Perform color segmentation on the pipe wall image to obtain the first prediction region.

[0127] It should be noted that after determining the pipe wall image, the above-mentioned device will determine the pipe wall image in the pipe image under the color image based on the position of the pipe wall image, and convert the pipe wall image into an image in the Hue-Saturation-Value (HSV) color space, which will help to separate color information in the subsequent process.

[0128] Since rust typically appears in orange, red, or brown, a corresponding color threshold range can be set to characterize the rusted area. The pipe wall image in the HSV color space can be segmented by the color threshold range, and the rusted area can then be used as the first prediction area mentioned above.

[0129] Step S242: Extract features from the pipe wall image to obtain the texture features corresponding to the pipe wall image.

[0130] Since rust usually has different texture features from normal pipe surfaces, such as spots, irregular patterns, or granular structures, the rusted areas in the pipe wall image under grayscale can be identified by texture features.

[0131] When extracting texture features, the aforementioned device can pre-construct a gray-level co-occurrence matrix (GLCM). The GLCM can be an N*N matrix, where N can be the number of gray levels in the pipe wall image. The frequency of gray-level values ​​of adjacent pixels with gray-level values ​​j when the gray-level value of each pixel in the GLCM is i is denoted as M. i,jFor each pixel in the pipe wall image, consider its relationship with pixels offset by a specified direction and distance. Whenever such a pixel pair occurs, the corresponding M... i,j It can be increased, specifically M i,j It is obtained through the following formula (3):

[0132]

[0133] Wherein, W and H can be W and H in a pipe wall image of size W*H, I(p,q) represents the gray value of the pixel at position (p,q), and Δx and Δy are offsets.

[0134] Using the aforementioned gray-level co-occurrence matrix, the device can extract texture features from the pipe wall image, wherein the texture features may include: contrast, energy, entropy, and homogeneity;

[0135] Contrast, which reflects the degree of local grayscale change in the pipe wall image, can be obtained using the following formula (4):

[0136]

[0137] The Contrast mentioned above refers to contrast.

[0138] For energy, the uniformity of the texture can be described by the following formula (5):

[0139]

[0140] The term "Energy" refers to energy.

[0141] Entropy, which measures the irregularity or complexity of a texture, can be obtained using the following formula (6):

[0142]

[0143] The above Entropy is entropy;

[0144] Homogeneity, which reflects the local similarity of textures, can be obtained through the following formula (7):

[0145]

[0146] The above-mentioned homogeneity refers to homogeneity.

[0147] Step S243: Determine the second prediction region based on the texture features.

[0148] In practical implementation, after determining the aforementioned texture features, a pre-set convolutional neural network can be used to distinguish between rusted and non-rusted areas. The device can pre-input the texture features of rusted and non-rusted areas to train the pre-set convolutional neural network, thereby enabling the trained network to determine whether a pixel is a rusted or non-rusted area, and using the rusted area as the second prediction region.

[0149] It is understood that the above-mentioned preset convolutional neural network can be set according to the actual situation, and this embodiment does not impose any restrictions on it.

[0150] Step S244: Determine the rusted area based on the first predicted area and the second predicted area.

[0151] In a specific implementation, after determining the first predicted region corresponding to the rusted area through color segmentation and the second predicted region corresponding to the rusted area through texture features, the device can merge the first predicted region and the second predicted region, and take the region that exists in both the first and second predicted regions as the rusted region, and mark the rusted region.

[0152] After determining the rusted area, in order to reduce power consumption, the laser power required for different degrees of rust may be different. Therefore, the above-mentioned equipment can determine the corresponding required power parameters according to the degree of rust in each rusted area.

[0153] Step S30: Based on the power parameters, emit the corresponding laser to perform laser rust removal on the pipe to be rusted.

[0154] It should be understood that the above-mentioned equipment may also be equipped with a laser emitter 6 for rust removal. After determining the power parameters, the above-mentioned equipment can control the laser emitter 6 to emit a laser of corresponding power to the rusted area of ​​the pipe to be removed for laser rust removal.

[0155] This embodiment uses laser for rust removal, which not only avoids pipe wear caused by direct contact with the pipe surface, but also avoids the problem of frequent maintenance due to wear of mechanical brushes, thus improving rust removal efficiency.

[0156] refer to Figure 5 , Figure 5 This is a schematic flowchart of the second embodiment of the laser rust removal method of the present invention.

[0157] Based on the first embodiment of the laser rust removal method described above, in order to accurately determine the power parameters, such as Figure 5 As shown, in this embodiment, the step of generating power parameters based on the rusted area includes:

[0158] Step S25: Determine the number of pixels and the area of ​​the rusted region, and determine the rust quantization value corresponding to the rusted region based on the number of pixels and the area.

[0159] It should be noted that after determining the rusted area, the above-mentioned equipment can determine the number of pixels in the rusted area and the area of ​​the area based on the rusted area. The number of pixels and the area can be obtained statistically from the binarized rusted area image. Of course, it can also be obtained by other methods. This embodiment does not limit this. The above-mentioned rust quantization value can be a quantization value used to characterize the degree of rust in the rusted area, which can be obtained according to the following formula (8):

[0160]

[0161] Where R is the aforementioned corrosion quantization value, N is the number of pixels in the corrosion area, and A is the area of ​​the corrosion region.

[0162] Step S26: Obtain a preset proportional coefficient, and determine the power parameters corresponding to the rusted area based on the rust quantification value and the preset proportional coefficient.

[0163] It is understood that the aforementioned preset proportional coefficient can be a coefficient used to characterize different rust quantification values ​​and corresponding laser power, and can be determined in advance based on experiments. This embodiment does not impose any restrictions on this.

[0164] In practical implementation, after the above equipment determines the rust quantification value corresponding to the rusted area, the required power parameters can be determined by the following formula (9):

[0165] P = k × R (Formula 9);

[0166] Where k is the preset proportional coefficient, R is the corrosion quantification value, and P is the power parameter.

[0167] Furthermore, in order to rotate and transport the pipe to be derusted, in this embodiment, step S30 includes:

[0168] Step S31: Determine the rust removal start point and rust removal end point based on the rust removal area, and determine the rust removal path based on the rust removal start point and rust removal end point;

[0169] Step S32: Rotate the pipe to be derusted according to the derusting path, and emit a corresponding laser based on the power parameters to perform laser derusting on the pipe.

[0170] It should be understood that the above-mentioned equipment may also be equipped with a conveying component, which can drive the pipe to be derusted to rotate around the pipe axis and move in the direction from the inlet 2 to the outlet 3. In this embodiment, the conveying component may be composed of several motors, and the specific number is not limited in this embodiment.

[0171] It is understood that the aforementioned rust removal starting point can be the starting position of the laser emitter 6 for rust removal, and the aforementioned rust removal ending point can be the ending position of the laser emitter 6 for completing rust removal. In this embodiment, the rust removal starting point and the rust removal ending point can be determined based on the rusted area.

[0172] It should be understood that, in order to reduce the power consumption of the laser emitter 6, this embodiment can determine the rust removal start point and the rust removal end point based on the rusted area, and determine a less energy-consuming rust removal path using the A* algorithm based on the rust removal start point and the rust removal end point. Then, the conveying component can control the movement of the pipe to be rusted according to the rust removal path, thereby causing the laser emitter 6 to perform laser rust removal according to the rust removal path. The specific process is as follows: The above-mentioned step of determining the rust removal path based on the rust removal start point and the rust removal end point includes:

[0173] Step S311: Determine the extension node based on the rust removal starting point.

[0174] The aforementioned extended nodes can be adjacent nodes of the current node (nodes in the upper, lower, left, right, and diagonal directions). The aforementioned device can first create an open list and a closed list, add the rust removal starting point to the open list, use the rust removal starting point in the open list as the current node, and determine the extended nodes of the current node.

[0175] Step S312: Determine the initial cost between each of the extended nodes and the rust removal start point, and determine the expected cost between each of the extended nodes and the rust removal end point.

[0176] After determining the extended nodes of the current node, the initial cost between each extended node and the current node can be determined. The initial cost can be the cost required for the laser emitter 6 to remove rust from the current node to the corresponding extended node, i.e., energy consumption. The expected cost between each extended node and the rust removal endpoint can be determined. The expected cost can be the cost required for the laser emitter 6 to remove rust from the extended node to the corresponding rust removal endpoint, i.e., energy consumption.

[0177] Step S313: Select a target node from each of the extended nodes based on each of the initial costs and each of the expected costs.

[0178] After determining the initial cost and the expected cost, the expansion node with the minimum total cost can be selected as the target node, where the total cost is the sum of the initial cost and the expected cost. This target node is then set as the next current node, and the initial cost and expected cost of the expansion nodes corresponding to this current node are calculated. At the same time, the previous target node is stored in the closed list.

[0179] Step S314: Generate a rust removal path based on the rust removal starting point, the target node, and the rust removal ending point.

[0180] When the rust removal endpoint is taken as the target node, it means that the optimal rust removal path has been found. Then, the rust removal starting point, each target node and the rust removal endpoint stored in the closed list can be connected to form a rust removal path. The movement of the pipe to be rusted is controlled according to the rust removal path, so that the laser emitter 6 performs laser rust removal according to the rust removal path, thereby reducing power consumption and cost.

[0181] Other embodiments or specific implementations of the laser rust removal equipment of the present invention can be referred to the above-described method embodiments, and will not be repeated here.

[0182] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or system. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0183] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0184] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as read-only memory / random access memory, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0185] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A laser rust removal device, characterized in that, The laser rust removal equipment includes: a housing with an inlet and an outlet, a camera, a controller, and a laser emitter; The imaging component is disposed on the housing and is located near the feed inlet. A rust removal position is provided between the feed inlet and the discharge outlet. The controller and the laser emitter are disposed inside the housing, with the laser emitter facing the rust removal position. The controller is electrically connected to the imaging component and the laser emitter respectively. The imaging component is used to capture images of the pipe to be derusted and transmit the images to the controller. The controller is configured to perform edge detection on the pipe image to obtain pipe wall pixels, and perform Hough transform on each pipe wall pixel; vote on the transform results through each pipe wall pixel, and determine target parameter spatial points based on the voting results; determine corresponding edge segments based on each target parameter spatial point, and determine the pipe wall image based on each edge segment; determine the rusted area based on the pipe wall image, and generate power parameters based on the rusted area; The laser emitter is used to emit a corresponding laser based on the power parameters to perform laser rust removal on the pipe to be rusted. The controller is further configured to perform color segmentation on the pipe wall image to obtain a first prediction region; perform feature extraction on the pipe wall image to obtain texture features corresponding to the pipe wall image; determine a second prediction region based on the texture features; and determine a rust region based on the first prediction region and the second prediction region, wherein the first prediction region is obtained by segmenting the pipe wall image in the HSV color space through a color threshold range, the second prediction region is obtained through a convolutional neural network, and the rust region is the region in which the first prediction region and the second prediction region exist. The controller is further configured to determine the number of pixels and the area of ​​the rusted region, and determine the rust quantization value corresponding to the rusted region based on the number of pixels and the area; obtain a preset scaling factor, and determine the power parameter corresponding to the rusted region based on the rust quantization value and the preset scaling factor; The corrosion quantization value is obtained by the formula R=N / A, where R is the corrosion quantization value, N is the number of pixels, and A is the area of ​​the region. The power parameter is obtained by the formula P=k×R, where P is the power parameter and k is the preset proportional coefficient. The controller is further configured to construct a gray-level co-occurrence matrix based on the pipe wall image, and use the gray-level co-occurrence matrix to extract features from the pipe wall image to obtain texture features corresponding to the pipe wall image. The texture features include the contrast, energy, entropy, and homogeneity of the pipe wall image. In the gray-level co-occurrence matrix, each pixel has a gray-level value of i, and the frequency of gray-level values ​​j of the pixels adjacent to the pixel with gray-level value i is... ; W and H represent the sizes of the pipe wall image. For position The grayscale value of the pixel, and This is the offset.

2. The laser rust removal equipment as described in claim 1, characterized in that, The laser rust removal equipment also includes: a ranging component; The ranging component is disposed on the housing and is located near the feed inlet; the ranging component is electrically connected to the controller. The ranging component is used to detect the pipe diameter information of the pipe to be derusted and transmit the pipe diameter information to the controller; The controller is also configured to determine focal length information based on the pipe diameter information and transmit the focal length information to the shooting component; The imaging component is also used to determine the imaging focal length based on the focal length information, and to take a picture of the pipe to be derusted according to the imaging focal length to obtain a pipe image of the pipe to be derusted.

3. The laser rust removal equipment as described in claim 1, characterized in that, The laser rust removal equipment also includes: a conveying component; The conveying component is located at the rust removal position and is electrically connected to the controller. The controller is also configured to determine the rust removal start point and the rust removal end point based on the rusted area, and to determine the rust removal path based on the rust removal start point and the rust removal end point; The conveying component is used to rotate the pipe to be derusted according to the derusting path, so that the laser emitter emits a corresponding laser based on the power parameters to perform laser derusting on the pipe to be derusted.

4. A laser rust removal method applied to the laser rust removal equipment according to any one of claims 1 to 3, characterized in that, The method includes: Take images of the pipes to be derusted; Edge detection is performed on the pipe image to obtain pipe wall pixels, and Hough transform is performed on each pipe wall pixel; the transformation results are voted on by each pipe wall pixel, and target parameter spatial points are determined according to the voting results; corresponding edge segments are determined based on each target parameter spatial point, and the pipe wall image is determined based on each edge segment; the rusted area is determined based on the pipe wall image, and power parameters are generated based on the rusted area; Based on the power parameters, a corresponding laser is emitted to perform laser rust removal on the pipeline to be rusted. The step of determining the rusted area based on the pipe wall image includes: The pipe wall image is segmented by color to obtain a first prediction region; the pipe wall image is extracted by feature extraction to obtain the texture features corresponding to the pipe wall image; a second prediction region is determined based on the texture features; a rust region is determined based on the first prediction region and the second prediction region, wherein the first prediction region is obtained by segmenting the pipe wall image in the HSV color space by color threshold range, the second prediction region is obtained by a convolutional neural network, and the rust region is the region where the first prediction region and the second prediction region exist. The step of generating power parameters based on the rusted area includes: The number of pixels and area of ​​the rusted region are determined, and the rust quantization value corresponding to the rusted region is determined based on the number of pixels and the area. A preset scaling factor is obtained, and the power parameter corresponding to the rusted region is determined based on the rust quantization value and the preset scaling factor. The rust quantization value is obtained by the formula R=N / A, where R is the rust quantization value, N is the number of pixels, and A is the area. The power parameter is obtained by the formula P=k×R, where P is the power parameter and k is the preset scaling factor. The step of extracting features from the pipe wall image to obtain the texture features corresponding to the pipe wall image includes: A gray-level co-occurrence matrix is ​​constructed based on the pipe wall image. The gray-level co-occurrence matrix is ​​then used to extract features from the pipe wall image to obtain the texture features corresponding to the pipe wall image. The texture features include the contrast, energy, entropy, and homogeneity of the pipe wall image. In the gray-level co-occurrence matrix, each pixel has a gray-level value of i, and the frequency of gray-level values ​​j of the pixels adjacent to the pixel with gray-level value i is... ; W and H represent the sizes of the pipe wall image. For position The grayscale value of the pixel, and This is the offset.

5. The laser rust removal method as described in claim 4, characterized in that, The step of generating power parameters based on the rusted area includes: The number of pixels and the area of ​​the rusted region are determined, and the rust quantization value corresponding to the rusted region is determined based on the number of pixels and the area. A preset scaling factor is obtained, and the power parameters corresponding to the rusted area are determined based on the rust quantification value and the preset scaling factor.

6. The laser rust removal method as described in claim 4, characterized in that, The step of taking images of the pipe to be derusted includes: The pipe diameter information of the pipe to be derusted is detected, and the focal length information is determined based on the pipe diameter information; The shooting focal length is determined based on the focal length information, and the rust-removed pipe is photographed according to the shooting focal length to obtain a pipe image of the rust-removed pipe.

7. The laser rust removal method as described in claim 4, characterized in that, The step of laser rust removal of the pipeline to be rusted by emitting a laser corresponding to the power parameters includes: The starting point and ending point of rust removal are determined based on the rusted area, and the rust removal path is determined based on the starting point and ending point of rust removal. The pipe to be rusted is rotated according to the rust removal path, and a corresponding laser is emitted based on the power parameters to perform laser rust removal on the pipe.

8. The laser rust removal method as described in claim 7, characterized in that, The step of determining the rust removal path based on the rust removal start point and the rust removal end point includes: Determine the extension node based on the rust removal starting point; Determine the initial cost between each of the extended nodes and the rust removal start point, and determine the expected cost between each of the extended nodes and the rust removal end point; Target nodes are selected from each of the extended nodes based on the initial cost and the expected cost. A rust removal path is generated based on the rust removal starting point, the target node, and the rust removal ending point.

Images