A method for locking and controlling the sudden descent of the moving beam of a gantry bucket wheel excavator

Abstract

This invention provides a method for controlling the sudden descent and locking of the movable beam in a gantry bucket wheel excavator. The method includes the following steps: deploying image acquisition devices on the pulley blocks on both sides of the top of the gantry bucket wheel excavator; setting different colored marker modules on the monitored pulleys; acquiring raw images captured by the image acquisition devices; preprocessing the raw images to convert the RGB images of the marker modules into binary images; marking the connected components of the binary images to determine the position of the marker modules in the image; calculating the motion trajectory characteristics of the characteristic color regions using periodically interpolated images; calculating the vector angle based on two sets of coordinate data obtained from two consecutive frames; if the angle of any set of colored marker modules exceeds a preset value, it is determined that the pulley block is moving at overspeed, and the movable beam is suddenly descenting. At this time, the control system sends a winch locking command to stop the movable beam's movement. This invention can effectively prevent accidents from escalating and reduce economic losses for enterprises.

Description

Technical Field

[0001] This invention relates to the field of portal bucket wheel excavator technology in thermal power plants, and in particular to a method for controlling the sudden descent and locking of the movable beam of a portal bucket wheel excavator. Background Technology

[0002] The movable beam is a crucial component of a gantry bucket wheel excavator. Its lifting and lowering are controlled by a winch, pulley system, and load-bearing steel wire. The movable beam carries bucket wheels, belts, and unloading trolleys to achieve material stacking and reclaiming functions. Under normal circumstances, the movable beam's lifting and lowering are controlled by the winch. However, a malfunction in the lifting system can cause the movable beam to suddenly drop. The current method involves the excavator operator manually observing the situation on-site. Upon witnessing a sudden drop, the operator immediately triggers the emergency stop protection button, locking the winch and preventing the accident from escalating. This method demands extremely high skill and responsibility from the operator. Delayed response can often lead to irreversible damage to the gantry bucket wheel excavator, causing prolonged downtime and seriously threatening the company's safe production and economic benefits. Summary of the Invention

[0003] To address the aforementioned technical problems, a method for controlling the sudden descent and locking of the movable beam in a gantry bucket wheel excavator is provided. The technical means employed in this invention are as follows:

[0004] A method for locking and controlling the sudden descent of the movable beam of a gantry bucket wheel excavator includes the following steps:

[0005] Image acquisition devices are deployed on the pulley blocks on both sides of the top of the gantry bucket wheel excavator, and different colored marking modules are set on the monitored pulley bodies;

[0006] Acquire the raw image captured by the image acquisition device, preprocess the raw image, and convert the RGB image of the identification module into a binary image;

[0007] Connected component labeling is performed on the binarized image to determine the position of the identification module in the image;

[0008] The motion trajectory features of the characteristic color region are calculated using periodically interpolated images, and the vector angle is calculated based on two sets of coordinate data obtained from two consecutive frames.

[0009] If the included angle of any of the multiple sets of color marking modules exceeds the preset value, it is determined that the pulley block is moving at overspeed and the moving beam is suddenly dropping. At this time, the control system sends a winch locking command to stop the movement of the moving beam.

[0010] Furthermore, the identification module includes a red module and a green module, and the original image preprocessing includes the following steps:

[0011] The generated HSV image is scanned line by line. Pixels within the red color gamut are binarized as white, and pixels outside the red color gamut are binarized as black. The newly generated binarized image is named img_1. Similarly, pixels within the green color gamut are binarized as white, and pixels outside the green color gamut are binarized as black. The newly generated binarized image is named img_2. The numerical ranges in the HSV color space are as follows:

[0012] Red: H∈[0, 10]∪[156, 180]; S∈[43, 255]; V∈[46, 255]

[0013] Green: H∈[35,77]; S∈[43,255]; V∈[46,255].

[0014] Furthermore, the original image preprocessing also includes the following steps:

[0015] A closing operation is performed on img_1 and img_2 respectively to fill the holes that appear after color gamut binarization, so that the feature color region can have a stable and specific connected component.

[0016] Furthermore, calculating the motion trajectory features of the characteristic color regions using periodically interpolated images specifically includes the following steps:

[0017] Determine whether there are two connected components in the binarized image of the labeling module. If not, clear the first set of point values ​​of the center coordinates of the labeling module. If they exist, determine whether the first set of center coordinates of the connected components of the labeling module is empty.

[0018] If the coordinates of the first group of the connected components of the identifier module are empty, then the coordinates of the center point of the connected components of the identifier module at this moment are assigned to the first group of coordinate data; otherwise, the coordinates of the two center points are assigned to the second group of coordinate data.

[0019] With both the first and second sets of coordinate data assigned values, calculate the vector of the center coordinates of each set, and calculate the angle between the two vectors formed by the two sets of coordinate data obtained from two consecutive frames of images.

[0020] Furthermore, if the included angle of any group of multiple colored marking modules exceeds 10°, it is determined that the pulley group is moving at excessive speed.

[0021] Furthermore, the camera is a full-color high-definition digital camera that automatically switches to night vision mode in low light conditions. The pulley assembly is also equipped with LED lighting equipment. When the control system receives the night vision status signal transmitted by the camera, it controls the LED lighting equipment to start.

[0022] Unmanned systems for gantry bucket wheel excavators are rapidly emerging in the industry. Relying on manual methods to detect and handle sudden descents of the moving beam is no longer sufficient for actual on-site needs. This invention designs a method for interlocking and controlling sudden descents of the moving beam using digital image processing technology. This method can effectively detect the occurrence of sudden descents and, by controlling the network to interlock the stop signals of power equipment such as winches, can effectively prevent the accident from escalating and reduce economic losses for the enterprise. Attached Figure Description

[0023] 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 some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is an overall flowchart of the present invention;

[0025] Figure 2 This is an installation diagram of the movable beam pulley block testing equipment of the present invention;

[0026] Figure 3 This is a schematic diagram of image segmentation and HSV space binarization according to the present invention;

[0027] Figure 4 This is a flowchart of the feature region motion trajectory recognition algorithm in an embodiment of the present invention;

[0028] Figure 5 This is the color gamut binarization result when the red filler is obscured by the bracket in an embodiment of the present invention. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, 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 some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0030] like Figure 2The diagram shows the hardware installation required for this invention. Image acquisition devices are deployed on pulley blocks on both sides of the top of the gantry bucket wheel excavator. The pulley bodies are set on a pulley fixing foundation, and different colored identification modules are set on the monitored pulley bodies. Specifically, the camera is a full-color high-definition digital camera that automatically switches to night vision mode in low light conditions. LED lighting equipment is also provided on the pulley blocks. When the control system receives the night vision status signal transmitted by the camera, it controls the LED lighting equipment to start. Supplemental lighting allows for obtaining full-color images from the camera even in low-light conditions. The circular process holes in the diagram are hoisting holes used during installation. In this embodiment, red and green filling modules are made according to their size and placed inside the holes for filling, while also providing color areas for identification. The purpose of the red and green filling modules is to allow for judgment based on the movement trajectory characteristics of the other color area regardless of whether the filling material of any color is obstructed. In other optional embodiments, the number of color templates can be appropriately increased or decreased according to the difference in the obstruction area.

[0031] like Figure 1 As shown in the figure, an embodiment of the present invention discloses a method for controlling the sudden drop and locking of the movable beam of a gantry bucket wheel excavator, comprising the following steps:

[0032] S01. Use the camera's SDK interface to acquire on-site images.

[0033] S02, such as Figure 3 The image shown is segmented to detect the region of interest. The original image size obtained through the SDK is 1920*1080. Figure 3 The area shown is cut into a region of interest with a size of 710*780.

[0034] S03. After image segmentation, the obtained region of interest image is RGB by default. The inRange function in the OpenCV library is used to convert the RGB image into an HSV format image. Since the feature color extraction can be well expressed in the HSV color space, this operation is performed.

[0035] In this embodiment, the fill colors used are red and green, and their numerical ranges in the HSV color space are as follows:

[0036] Red: H∈[0, 10]∪[156, 180]; S∈[43, 255]; V∈[46, 255]

[0037] Green: H∈[35,77]; S∈[43,255]; V∈[46,255].

[0038] like Figure 3As shown, the generated HSV image is scanned line by line. Pixels within the red color gamut are designated as binary white (1), and pixels outside the red color gamut are designated as binary black (0). The newly generated binary image is named img_1. Pixels within the green color gamut are designated as binary white (1), and pixels outside the green color gamut are designated as binary black (0). The newly generated binary image is named img_2.

[0039] The two newly generated binary images are each subjected to a closing operation. The algorithm is as follows: the closing operation is a process of erosion followed by dilation: first, an appropriate structuring element B (in this example, a 7*7 matrix is ​​used to scan each pixel of image A); then, this structuring element is used to perform an OR operation with the value of the overlay image; when the value is 0, the pixel at the corresponding position in the output image is 0, otherwise it is 1. The resulting image A... a The area was expanded by one circumference. Image A was then scanned again using this structuring element. a Each pixel is processed; this struct element is then ANDed with the value of the overlay image; when the value is 1, the pixel at the corresponding position in the output image is 1, otherwise it is 0. The resulting image A... b This refers to the image after the closing operation needs to be performed. In this example, the purpose of using the closing operation is to fill in the small holes that appear after color gamut binarization, so that stable and specific connected components can appear in the characteristic color regions. For example... Figure 3 The image on the right is the binarized image after feature color extraction.

[0040] S04 uses the 4-neighborhood labeling method to label the connected components of the optimized binarized images img_1 and img_2 respectively, obtains the connected components of the red feature binarized image, and removes the connected components with an area less than 60, then records the coordinates of the center points A1 and A2 of the connected components; at the same time, it obtains the connected components of the green feature binarized image, removes the connected components with an area less than 60, and records the coordinates of the center points B1 and B2.

[0041] S05. Calculate the motion trajectory features of the characteristic color region using periodically interpolated images (in this embodiment, the interpolation period is 2 seconds), such as... Figure 4 The diagram shows the flowchart of the motion trajectory recognition algorithm for the feature color region.

[0042] Specifically, the steps include the following:

[0043] S501. Obtain the two binarized images described in S04 (each representing a feature region of a different color).

[0044] S502. Determine whether there are two connected components in the binarized image of the red feature. If not, ... Figure 5As shown, step S503 is executed to clear the values ​​of the first set of points at the center coordinates of the red connected domain. If they exist, step S504 is executed to determine whether the first set of center coordinates of the red feature connected domain is empty.

[0045] S504. If the result of the judgment is that the coordinates of the first group of the red connected domain are empty, then execute S505 to assign the coordinates of the center point of the red connected domain at this moment to the first group of coordinate data; otherwise, execute S506 to assign the coordinates of the two center points to the second group of coordinate data.

[0046] S507. In the algorithm, the center coordinates of the red connected domain are calculated using the following formulas 1 and 2, assuming that the first and second sets of coordinate data have been assigned values:

[0047]

[0048]

[0049] The center coordinates of the first group of red connected domains are recorded as A1(x1, y1) and A2(x2, y2); the center coordinates of the second group are recorded as A3(x3, y3) and A4(x4, y4).

[0050] The angle between two vectors formed by the two sets of coordinate data obtained from two consecutive frames of images is calculated according to Formula 3:

[0051]

[0052] S513. After the included angle is calculated, the center coordinate data of the second group of red connected domains is assigned to the first group so that the vector included angle of the next movement position can be calculated when the next frame image is executed.

[0053] Steps S508 to S513 involve simultaneously retrieving features of the motion trajectory in the green color gamut of the image, consistent with the approach for red.

[0054] S06. Compare the calculation results of the red connected domain center point vector and the green connected domain center point vector obtained above for two consecutive frames of image processing with the preset values. If they do not exceed the preset values, continue the detection. If they exceed the threshold, that is, as long as one set of angles exceeds 10°, the system considers that the pulley block is moving at an overspeed and the moving beam is suddenly dropping at this moment.

[0055] S09. When the algorithm detects fault characteristics, it sends a winch interlock command to the PLC control system via OPC communication to stop the movement of the moving beam, and at the same time sends an alarm message to the host computer operation interface to remind the operator to confirm.

[0056] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for controlling the sudden descent and interlocking of the movable beam of a gantry bucket wheel excavator, characterized in that, Includes the following steps: Image acquisition devices are deployed on the pulley blocks on both sides of the top of the gantry bucket wheel excavator, and different colored marking modules are set on the monitored pulley bodies; Acquire the raw image captured by the image acquisition device, preprocess the raw image, and convert the RGB image of the identification module into a binary image; Connected component labeling is performed on the binarized image to determine the position of the identification module in the image; The motion trajectory features of the characteristic color region are calculated using periodically interpolated images, and the vector angle is calculated based on two sets of coordinate data obtained from two consecutive frames. If the included angle of any of the multiple sets of color marking modules exceeds the preset value, it is determined that the pulley block is moving at overspeed and the moving beam is suddenly dropping. At this time, the control system sends a winch locking command to stop the movement of the moving beam.

2. The method for controlling the sudden descent and interlocking of the movable beam of a gantry bucket wheel excavator according to claim 1, characterized in that, The identification module includes a red module and a green module. The original image preprocessing includes the following steps: The generated HSV image is scanned line by line. Pixels within the red color gamut are designated as binary white, and pixels outside the red color gamut are designated as binary black. The newly generated binary image is named img_1. Pixels within the green color gamut are binarized as white, and pixels outside the green color gamut are binarized as black. The newly generated binarized image is named img_2; the numerical ranges in the HSV color space are as follows: Red: H∈[0, 10]∪[156, 180]; S∈[43, 255]; V∈[46, 255] Green: H∈[35,77]; S∈[43,255]; V∈[46,255].

3. The method for controlling the sudden descent and interlocking of the movable beam of a gantry bucket wheel excavator according to claim 2, characterized in that, The preprocessing of the original image also includes the following steps: A closing operation is performed on img_1 and img_2 respectively to fill the holes that appear after color gamut binarization, so that the feature color region can have a stable and specific connected component.

4. The method for controlling the sudden descent and interlocking of the movable beam of a gantry bucket wheel excavator according to claim 1, characterized in that, Calculating the motion trajectory features of characteristic color regions using periodically interpolated images specifically includes the following steps: Determine whether there are two connected components in the binarized image of the labeling module. If not, clear the first set of point values ​​of the center coordinates of the labeling module. If they exist, determine whether the first set of center coordinates of the connected components of the labeling module is empty. If the coordinates of the first group of the connected components of the identifier module are empty, then the coordinates of the center point of the connected components of the identifier module at this moment are assigned to the first group of coordinate data; otherwise, the coordinates of the two center points are assigned to the second group of coordinate data. With both the first and second sets of coordinate data assigned values, calculate the vector of the center coordinates of each set, and calculate the angle between the two vectors formed by the two sets of coordinate data obtained from two consecutive frames of images.

5. The method for controlling the sudden descent and interlocking of the movable beam of a gantry bucket wheel excavator according to claim 1, characterized in that, If the included angle of any group of multiple colored marking modules exceeds 10°, the pulley system is judged to be moving at excessive speed.

6. The method for controlling the sudden descent and interlocking of the movable beam of a gantry bucket wheel excavator according to claim 1, characterized in that, The camera uses a full-color high-definition digital camera, which automatically switches to night vision mode in low light conditions. The pulley group is also equipped with LED lighting equipment. When the control system receives the night vision status signal transmitted by the camera, it controls the LED lighting equipment to start.

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