Tower crane fixed-point parking operation level assessment method and device and storage medium

Abstract

The invention discloses an assessment method and device for the fixed-point parking operation level of a tower crane and a storage medium, and the method comprises the steps: detecting the position relation between a moving target and an assessment region in real time, the assessment region comprising a parking region; detecting the hoisting weight of the moving target under the condition of determining that the moving target enters the assessment area; under the condition that the hoisting weight of the moving target is smaller than a preset hoisting weight threshold value, obtaining a monitoring image of the assessment area; determining a farthest position point from the center point of the parking area in the moving target based on the monitoring image; and checking the operation level according to the position relationship between the farthest position point and the parking area. According to the scheme, the positions of the moving target and the parking area can be accurately identified in combination with visual identification, and the position relation between the moving target and the parking area is judged, so that the operation level of fixed-point parking of the tower crane is accurately assessed.

Description

Technical Field

[0001] The present application relates to the technical field of tower crane operation level assessment, and specifically to a tower crane fixed-point parking operation level assessment method, device, storage medium and assessment system. Background Art

[0002] Operating a tower crane (or tower crane) requires a driver to hold a special operations operator certificate. This certificate is issued after the driver's theoretical knowledge and practical skills are assessed by tower crane training and testing institutions. While the theoretical knowledge assessment is now computer-automated and graded, the practical driving skills test still requires a human judge on the ground to determine whether the driver has completed the test correctly. This is not automated and is prone to human error. Furthermore, the human judges' scoring leaves no evidence, which could lead to doubts from the test takers about its accuracy, undermining its authority. Summary of the Invention

[0003] The purpose of the embodiments of the present application is to provide a method, device, storage medium and assessment system for assessing the fixed-point parking operation level of a tower crane, so as to solve the technical problem of deviation in the assessment of the tower crane operation level in the prior art.

[0004] In order to achieve the above-mentioned purpose, the first aspect of the present application provides a method for assessing the level of tower crane fixed-point parking operation, the method comprising: Real-time detection of the positional relationship between the moving target and the assessment area, wherein the assessment area includes the parking area; When the moving target is determined to have entered the assessment area, the lifting weight of the moving target is detected; When the lifting weight of the moving target is less than the preset lifting weight threshold, a monitoring image of the assessment area is obtained; Determine, based on the surveillance image, a point on the mobile object that is farthest from the center point of the parking area; The operating level is assessed based on the positional relationship between the farthest point and the parking area.

[0005] In an embodiment of the present application, determining the farthest position point in a mobile target from a center point of a parking area based on a surveillance image includes: determining a first image position of each corner point of the mobile target and a second image position of the center point of the parking area based on the surveillance image; determining a second spacing distance between each first image position and the second image position; and determining, based on all second spacing distances, the farthest corner point in the mobile target from the center point of the parking area as the farthest position point.

[0006] In an embodiment of the present application, determining the first image position of each corner point of the moving target and the second image position of the center point of the parking area based on the surveillance image includes: determining a second detection frame corresponding to the parking area in the surveillance image based on a target detection algorithm; performing median blur processing on the image information included in the second detection frame to obtain processed image information; and performing Hough circle detection on the processed image information to determine the second image position of the center point of the parking area.

[0007] In an embodiment of the present application, determining the first image position of each corner point of the moving target and the second image position of the center point of the parking area based on the surveillance image includes: determining the first detection frame corresponding to each corner point of the moving target in the surveillance image based on the target detection algorithm; and determining the center position of each first detection frame as the first image position of each corner point.

[0008] In an embodiment of the present application, the parking area includes multiple sub-areas, and assessing the operation level based on the positional relationship between the farthest position point and the parking area includes: obtaining camera parameters of an image acquisition device for acquiring monitoring images; determining the actual distance between the farthest position point and the center point of the parking area based on the camera parameters; determining the target sub-area where the farthest position point is located based on the radius and actual distance of each sub-area; and assessing the operation level based on the target sub-area.

[0009] In an embodiment of the present application, assessing the operation level according to the target sub-area includes: obtaining a preset assessment score corresponding to each sub-area, wherein multiple sub-areas are concentrically arranged with the same center point as the geometric center, and the size of each sub-area increases in the radial direction, and the larger the size of the sub-area, the smaller the corresponding preset assessment score; determining the tower crane operation level of the current operator according to the preset assessment score corresponding to the target sub-area.

[0010] In an embodiment of the present application, real-time determination of whether a mobile target has entered an assessment area includes: determining that the mobile target has entered an assessment area when a first interval distance between a center point of the mobile target and a center point of a parking area is less than or equal to a radius of the assessment area; wherein the assessment area uses the center point of the parking area as the center point of the assessment area, and uses the sum of twice the radius of the parking area and the radius of the mobile target as the radius of the assessment area.

[0011] A second aspect of the present application provides a device for assessing the level of tower crane fixed-point parking operation, comprising: a memory configured to store instructions; The processor is configured to call instructions from the memory and implement the above-mentioned assessment method for the tower crane fixed-point parking operation level when executing the instructions.

[0012] A third aspect of the present application provides an assessment system, comprising: An image acquisition device, used to obtain monitoring images of the assessment area; Based on the above-mentioned assessment device for the fixed-point parking operation level of the tower crane.

[0013] A fourth aspect of the present application provides a machine-readable storage medium having stored thereon instructions for causing a machine to execute the above-mentioned method for assessing the fixed-point parking operation level of a tower crane.

[0014] The above technical solution detects the positional relationship between the moving target and the assessment area in real time. If the moving target enters the assessment area, the target's lifting weight is detected. If the target's lifting weight is less than a preset lifting weight threshold, a monitoring image of the assessment area is acquired. Based on the monitoring image, the farthest point from the center of the parking area is determined within the moving target. The operator's operational level is assessed based on the positional relationship between the farthest point and the parking area. The above solution, combined with visual recognition, can accurately identify the position of the moving target and the parking area, and determine the positional relationship between the moving target and the parking area, thereby accurately assessing the operator's operational level for fixed-point parking of tower cranes.

[0015] Other features and advantages of the embodiments of the present application will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The accompanying drawings are used to provide a further understanding of the embodiments of the present application and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present application but do not constitute a limitation on the embodiments of the present application. In the accompanying drawings: Figure 1 A schematic diagram of an application environment of a method for assessing the level of tower crane fixed-point parking operation according to an embodiment of the present application is shown schematically; Figure 2 The following schematically shows a flow chart of a method for assessing the level of tower crane fixed-point parking operation according to an embodiment of the present application; Figure 3 Schematically shows a schematic diagram of a first detection frame and a second detection frame according to an embodiment of the present application; Figure 4 A schematic diagram of a target image according to an embodiment of the present application is schematically shown; Figure 5 A structural block diagram of an assessment of a tower crane's fixed-point parking operation level according to an embodiment of the present application is schematically shown; Figure 6 The schematic diagram shows the structure of a computer device according to an embodiment of the present application. DETAILED DESCRIPTION

[0017] To make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the specific implementation methods described herein are only used to illustrate and explain the embodiments of the present application and are not used to limit the embodiments of the present application. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0018] It should be noted that if the embodiments of the present application involve directional indications (such as up, down, left, right, front, back, etc.), such directional indications are only used to explain the relative position relationship, movement status, etc. between the various components under a certain specific posture (as shown in the accompanying drawings). If the specific posture changes, the directional indication will also change accordingly.

[0019] In addition, if there are descriptions involving "first", "second", etc. in the embodiments of the present application, the descriptions of "first", "second", etc. are only for descriptive purposes and cannot be understood as indicating or implying their relative importance or implicitly indicating the number of the indicated technical features. Therefore, the features defined as "first" and "second" may explicitly or implicitly include at least one of such features. In addition, the technical solutions between the various embodiments can be combined with each other, but they must be based on the fact that they can be implemented by ordinary technicians in this field. When the combination of technical solutions is contradictory or cannot be implemented, it should be deemed that such a combination of technical solutions does not exist and is not within the scope of protection required by this application.

[0020] Figure 1 The following schematically shows an application environment diagram of a tower crane fixed-point parking operation level assessment method according to an embodiment of the present application, such as Figure 1 As shown, the tower crane's fixed-point parking test assesses the driver's judgment of the location when dropping the hook, and places the suspended water tank at point T within the designated ground circle area A. The circle usually consists of three concentric circles, called the inner circle, middle circle, and outer circle. If the water tank is not parked in the inner circle or outside of any circle, the corresponding score will be deducted.

[0021] Figure 2 The following schematically shows a flow chart of a method for assessing the level of tower crane fixed-point parking operation according to an embodiment of the present application. Figure 2 As shown, the embodiment of the present application provides a method for assessing the fixed-point parking operation level of a tower crane, which is applied to Figure 1 In the illustrated environment, the method may include the following steps.

[0022] S202: Detecting the positional relationship between the mobile target and the assessment area in real time, wherein the assessment area includes the parking area.

[0023] S204: When it is determined that the moving target has entered the assessment area, the lifting weight of the moving target is detected.

[0024] S206: When the lifting weight of the mobile target is less than a preset lifting weight threshold, a monitoring image of the assessment area is obtained.

[0025] S208: Determine the farthest point from the center point of the parking area among the mobile objects based on the monitoring image.

[0026] S210: Assess the operating level based on the positional relationship between the farthest point and the parking area.

[0027] It can be understood that the mobile target is mounted on the tower crane and is an object that moves with the tower crane when the operator controls the tower crane. The assessment area refers to the spatial range defined in the tower crane operation test. In the operation assessment of the tower crane's fixed-point parking, the operator needs to operate the tower crane to make the mobile target enter the assessment area, so as to further park the mobile target in the parking area in the assessment area. Technicians can set the spatial range of the assessment area based on experience. The parking area is within the assessment area and is the designated parking area for the mobile target in the tower crane's fixed-point parking operation assessment. Reference Figure 1 , Figure 1 The moving target is the object carried by the hook, specifically a water tank T. The operator can control the tower crane so that the hook moves with the water tank T. The parking area can be a designated area on the ground. For example, Figure 1 The circled area A on the ground is shown.

[0028] The processor can detect the positional relationship between the mobile target and the assessment area in real time to confirm whether the mobile target is within the assessment area. When the mobile target is detected entering the assessment area, the target's lifting weight can be detected. When the operator operates the tower crane so that the mobile target contacts the ground (or other flat surface that can block objects) and is placed on the ground, the lifting weight of the mobile target will decrease. The technician can set a preset lifting weight threshold. When the lifting weight of the mobile target is detected to be less than the preset lifting weight threshold, the mobile target is considered to have completely fallen. At this time, a surveillance image of the assessment area can be obtained, and the position of the mobile target within the assessment area can be identified based on the image content of the surveillance image. To facilitate determining the positional relationship between the mobile target and the parking area, the surveillance image is a top-down image. Specifically, the fixed-point parking operation assessment requires the mobile target to be parked in a designated parking area. Furthermore, the operator's operating level can be accurately assessed based on the specific position of the mobile target within the parking area. Since the mobile target occupies a certain spatial area, in embodiments of the present application, multiple locations of the mobile target in the surveillance image and the center point of the parking area can be identified to determine the location of the mobile target farthest from the center point of the parking area. The operator's ability to determine the hook's position is assessed based on the relationship between the furthest point and the parking area. For example, the operator's ability to determine the hook's position is assessed based on the distance between the furthest point and the center of the parking area.

[0029] The above technical solution detects the positional relationship between the moving target and the assessment area in real time. When the moving target enters the assessment area, the target's lifting weight is detected. If the target's lifting weight is less than a preset lifting weight threshold, a monitoring image of the assessment area is acquired. Based on the monitoring image, the farthest point from the center of the parking area is determined within the moving target. The operator's operational level is assessed based on the positional relationship between the farthest point and the parking area. The above solution, combined with visual recognition, can accurately identify the position of the moving target and the parking area, and determine the positional relationship between the moving target and the parking area, thereby accurately assessing the operator's operational level for fixed-point parking of tower cranes.

[0030] In an embodiment of the present application, determining that a mobile target has entered an assessment area includes: determining that the mobile target has entered an assessment area when a first interval distance between a center point of the mobile target and a center point of a parking area is less than or equal to a radius of the assessment area; wherein the assessment area uses the center point of the parking area as the center point of the assessment area, and uses the sum of twice the radius of the parking area and the radius of the mobile target as the radius of the assessment area.

[0031] Specifically, the moving target can be a water tank, which can be a cube. The radius of the moving target can refer to the radius of the circumscribed circle of the square, that is, half of the diagonal of the square. The parking area can be a circular area. The radius of the test area is the sum of twice the radius of the parking area and the radius of the moving target. The processor can detect the distance between the water tank and the test tool coordinates (the center point of the parking area) in real time. Figure 1 Taking the middle scenario as an example, when the distance between point T and point A is detected to be less than 2 times the sum of the parking area radius and the water tank radius, the fixed-point parking operation level assessment and identification begins.

[0032] In an embodiment of the present application, determining the farthest position point in a mobile target from a center point of a parking area based on a surveillance image includes: determining a first image position of each corner point of the mobile target and a second image position of the center point of the parking area based on the surveillance image; determining a second spacing distance between each first image position and the second image position; and determining, based on all second spacing distances, the farthest corner point in the mobile target from the center point of the parking area as the farthest position point.

[0033] Specifically, in the case where the moving target is a cubic water tank, the water tank appears square in the monitoring image. Therefore, the target detection algorithm can be used to identify the first image position of each of the four corner points of the water tank. Furthermore, the parking area can be identified to determine the second image position of the center point of the parking area. Furthermore, the second interval distance between each first image position and the second image position can be determined, from which the corner point farthest from the center point of the parking area is selected as the farthest position point. The farthest corner point can directly reflect the accuracy with which the operator parked the moving target in the parking area. Furthermore, detecting the corner points of the water tank is simple and convenient, and the operator's level can be assessed without the need for complex algorithms.

[0034] In an embodiment of the present application, determining the first image position of each corner point of the mobile target and the second image position of the center point of the parking area based on the surveillance image includes: determining a first detection frame corresponding to each corner point of the mobile target in the surveillance image based on the target detection algorithm; and determining the center position of each first detection frame as the first image position of each corner point. Figure 3 , the four small boxes are the first detection boxes corresponding to each corner point.

[0035] In an embodiment of the present application, determining the first image position of each corner point of the mobile target and the second image position of the center point of the parking area based on the surveillance image includes: determining a second detection frame corresponding to the parking area in the surveillance image based on the target detection algorithm; performing median blur processing on the image information included in the second detection frame to obtain processed image information; and performing Hough circle detection on the processed image information to determine the second image position of the center point of the parking area. Figure 3, the large frame is the second detection frame for recognition.

[0036] Specifically, the parking area can be identified using an object detection algorithm to obtain a second detection frame corresponding to the parking area. Furthermore, median blur processing is performed on the image information contained in the second detection frame, thereby obtaining smoother image information, which facilitates subsequent image analysis. After obtaining the processed image information, Hough circle detection technology is further applied. This technology can effectively identify circular features in the image, thereby determining the second image position of the center point of the parking area.

[0037] In another embodiment, after determining the second detection frame corresponding to the parking area in the monitoring image based on the target detection algorithm, the second detection frame does not include the entire parking area. Then, when performing Hough circle detection, it may not be possible to effectively identify the circular features in the image. Then, based on the second detection frame, the preset pixels can be expanded outward and then cut out from the monitoring image to obtain the target image. Figure 4 As shown, Figure 4 The target image is schematically shown as containing image content. Further, based on the image information contained in the target image, median blur processing is performed, and Hough circle detection technology is further applied, so that the second image position of the center point of the parking area can be accurately determined.

[0038] In an embodiment of the present application, the parking area includes multiple sub-areas, and assessing the operation level based on the positional relationship between the farthest position point and the parking area includes: obtaining camera parameters of an image acquisition device for acquiring monitoring images; determining the actual distance between the farthest position point and the center point of the parking area based on the camera parameters; determining the target sub-area where the farthest position point is located based on the radius and actual distance of each sub-area; and assessing the operation level based on the target sub-area.

[0039] Specifically, camera parameters include intrinsic and extrinsic parameters, specifically the camera's focal length. After determining the image distance between the farthest point and the center of the parking area, the actual distance between them can be determined based on the camera's focal length. Furthermore, the target sub-area for the farthest point is determined based on the radius and actual distance of each sub-area, and the operator's performance is then assessed based on the target sub-area.

[0040] Specifically, in an embodiment of the present application, assessing the operation level according to the target sub-area includes: obtaining a preset assessment score corresponding to each sub-area, wherein multiple sub-areas are concentrically arranged with the same center point as the geometric center, and the size of each sub-area increases in the radial direction, and the larger the size of the sub-area, the smaller the corresponding preset assessment score; determining the tower crane operation level of the current operator according to the preset assessment score corresponding to the target sub-area.

[0041] The parking area can be a circular area, typically consisting of three concentric circles: inner, middle, and outer. Typically, the radius of the water tank's circumcircle is smaller than the radius of the inner circle. The larger the radius of the target sub-area where the farthest point is located, the greater the deduction score, or the corresponding score. Therefore, the operator's tower crane operation proficiency can be determined based on the target sub-area where the farthest point is located and its corresponding preset assessment score.

[0042] Specifically, since the camera has a fixed focus and its height from the ground does not change, the length in the surveillance image and the length in reality have a fixed proportional relationship without considering distortion. For example, Figure 2 The outer circle of the parking area in the image has a real-world diameter of 2.00m, and its length in the image is 200 pixels. This ratio is 0.01m / px. This ratio can be used to calculate the real-world distance from the farthest corner to the center of the circle. This can then be compared with the radius of each circle specified in the exam rules (typically 0.90m for the inner circle, 0.95m for the middle circle, and 1.00m for the outer circle). This will determine the score for the fixed-point parking assessment.

[0043] In an embodiment of the present application, the tower crane further includes a horizontal boom, a moving device and an image acquisition device. The moving device is installed on the horizontal boom and moves along the horizontal boom. The moving target and the image acquisition device are respectively connected to the moving device to follow the movement of the moving device.

[0044] Specifically, the mobile device can be a mobile trolley. In order to be able to observe the entire examination site through machine vision, a fixed-focus camera needs to be installed on the mobile trolley of the tower crane, at a position such as Figure 1 As shown at point E in the diagram, the camera is positioned perpendicular to the ground, following the movement of the trolley to constantly observe the suspended water tank and the test equipment on the ground. The test water tank is typically a cube with a side length of 1 meter, filled with water, and weighs approximately 1 ton.

[0045] Specifically, the crane's encoders can be used to determine its current parameters, including slewing, hoisting, luffing, and load. These parameters can be used to roughly calculate the spatial coordinates of the water tank, namely, the coordinates of point T. Before the actual test, the water tank can be hoisted onto each test fixture on the ground to determine their approximate positions. This allows the center point of the parking area and the tank's real-time position to be used to determine whether the tank has entered the test area.

[0046] Specifically, when the system detects that the lifting weight is less than 0.3t, it assumes that the water tank has completely fallen, and the camera image at that moment is used as the basis for scoring. The camera image at that moment is input into the YoloV10 target detection algorithm for identification. At this time, the targets to be detected are the four corner points and the parking circle of the water tank. Based on the parking circle detection frame identified by the Yolo algorithm, it is expanded outward by 50 pixels and intercepted to obtain the target image. After blurring the median of the intercepted image, Hough circle detection is performed to obtain the pixel coordinates of the center of point A. The distance between the center coordinates of the four corner point detection frames and the center coordinates of the circle is calculated, and the maximum value is taken. Figure 2 The outer circle of the parking area in the image has a real-world diameter of 2.00m, and its length in the image is 200 pixels. This ratio is 0.01m / px. This ratio can be used to calculate the real-world distance from the farthest corner to the center of the circle. This can then be compared with the radius of each circle specified in the exam rules (typically 0.90m for the inner circle, 0.95m for the middle circle, and 1.00m for the outer circle). This will determine the score for the fixed-point parking assessment.

[0047] Furthermore, the surveillance images captured by the image acquisition device have high clarity, ensuring accurate identification of the corners of moving targets and the center of the parking area. The image acquisition device may also include an image processing module for pre-processing the captured surveillance images, such as noise reduction and contrast enhancement, to improve the accuracy of subsequent target detection and corner identification. By combining the mobile device and image acquisition device, the tower crane can accurately locate and monitor moving targets within the parking area, providing reliable data support for operator assessment.

[0048] The above technical solution detects the positional relationship between the moving target and the assessment area in real time. When the moving target enters the assessment area, the target's lifting weight is detected. If the target's lifting weight is less than a preset lifting weight threshold, a monitoring image of the assessment area is acquired. Based on the monitoring image, the farthest point from the center of the parking area is determined within the moving target. The operator's operational level is assessed based on the positional relationship between the farthest point and the parking area. This solution, combined with a visual recognition algorithm, can accurately identify the position of the moving target and the parking area. Based on the corner points of the moving target and the positional relationship between the farthest corner point and the parking area, the operator's operational level for fixed-point parking of the tower crane can be accurately assessed.

[0049] Figure 1 FIG. 1 is a flow chart of a method for assessing the level of tower crane fixed-point parking operation in one embodiment. Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. In addition, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0050] Figure 5 The following schematically shows a structural block diagram of a tower crane fixed-point parking operation level assessment device according to an embodiment of the present application. Figure 5 As shown, the embodiment of the present application provides a device for assessing the fixed-point parking operation level of a tower crane, which may include: a memory configured to store instructions; The processor is configured to call instructions from the memory and implement the above-mentioned method for assessing the tower crane fixed-point parking operation level when executing the instructions.

[0051] Specifically, in the embodiment of the present application, the processor may be configured to: Real-time detection of the positional relationship between the moving target and the assessment area, wherein the assessment area includes the parking area; When the moving target is determined to have entered the assessment area, the lifting weight of the moving target is detected; When the lifting weight of the moving target is less than the preset lifting weight threshold, a monitoring image of the assessment area is obtained; Determine, based on the surveillance image, a point on the mobile object that is farthest from the center point of the parking area; The operating level is assessed based on the positional relationship between the farthest point and the parking area.

[0052] In an embodiment of the present application, the processor may further be configured to: Based on the monitoring image, the first image position of each corner point of the mobile target and the second image position of the center point of the parking area are determined; the second interval distance between each first image position and the second image position is determined; and based on all the second interval distances, the corner point of the mobile target farthest from the center point of the parking area is determined as the farthest position point.

[0053] In an embodiment of the present application, the processor may further be configured to: Based on the target detection algorithm, a second detection frame corresponding to the parking area in the monitoring image is determined; the image information included in the second detection frame is subjected to median blur processing to obtain processed image information; and the processed image information is subjected to Hough circle detection to determine the second image position of the center point of the parking area.

[0054] In an embodiment of the present application, the processor may further be configured to: Determine a first detection frame corresponding to each corner point of a moving target in a surveillance image based on a target detection algorithm; and determine a center position of each first detection frame as a first image position of each corner point.

[0055] In an embodiment of the present application, the parking area includes multiple sub-areas, and the processor may be further configured to: Obtain the camera parameters of the image acquisition device for acquiring monitoring images; determine the actual distance between the farthest point and the center point of the parking area based on the camera parameters; determine the target sub-area where the farthest point is located based on the radius and actual distance of each sub-area; and assess the operating level based on the target sub-area.

[0056] In an embodiment of the present application, the processor may further be configured to: Obtain the preset assessment score corresponding to each sub-area, where multiple sub-areas are concentrically arranged with the same center point as the geometric center, and the size of each sub-area increases in the radial direction. The larger the size of the sub-area, the smaller the corresponding preset assessment score; determine the tower crane operation level of the current operator based on the preset assessment score corresponding to the target sub-area.

[0057] In an embodiment of the present application, the processor may further be configured to: When the first interval distance between the center point of the mobile target and the center point of the parking area is less than or equal to the radius of the assessment area, the mobile target is determined to have entered the assessment area; wherein, the assessment area uses the center point of the parking area as the center point of the assessment area, and uses the sum of twice the radius of the parking area and the radius of the mobile target as the radius of the assessment area.

[0058] The present application also provides an assessment system, including: An image acquisition device, used to obtain monitoring images of the assessment area; Based on the above-mentioned assessment device for the fixed-point parking operation level of the tower crane.

[0059] Specifically, the tower crane further includes a horizontal boom, a moving device and an image acquisition device. The moving device is installed on the horizontal boom and moves along the horizontal boom. The moving target and the image acquisition device are respectively connected to the moving device to follow the movement of the moving device.

[0060] Specifically, the mobile device can be a mobile trolley. In order to be able to observe the entire examination site through machine vision, a fixed-focus camera needs to be installed on the mobile trolley of the tower crane, at a position such as Figure 1 As shown in point E in the figure, the camera is perpendicular to the ground and follows the movement of the trolley to observe the hanging water tank and the ground test equipment at all times.

[0061] Specifically, the crane's encoders can be used to determine its current parameters, including slewing, hoisting, luffing, and load. These parameters can be used to roughly calculate the spatial coordinates of the water tank, namely, the coordinates of point T. Before the actual test, the water tank can be hoisted onto each test fixture on the ground to determine their approximate positions. This allows the determination of whether the water tank has entered the test area based on the center point of the parking area and the tank's real-time position.

[0062] Furthermore, the surveillance images captured by the image acquisition device have high clarity, ensuring accurate identification of the corners of moving targets and the center of the parking area. The image acquisition device may also include an image processing module for pre-processing the captured surveillance images, such as noise reduction and contrast enhancement, to improve the accuracy of subsequent target detection and corner identification. By combining the mobile device and image acquisition device, the tower crane can accurately locate and monitor moving targets within the parking area, providing reliable data support for operator assessment.

[0063] An embodiment of the present application further provides a machine-readable storage medium having stored thereon instructions for causing a machine to execute the above-mentioned method for assessing the fixed-point parking operation level of a tower crane.

[0064] In one embodiment, a computer device is provided. The computer device may be a server, and its internal structure diagram may be as follows: Figure 6 As shown. The computer device includes a processor A01, a network interface A02, a memory (not shown in the figure) and a database (not shown in the figure) connected via a system bus. Among them, the processor A01 of the computer device is used to provide computing and control capabilities. The memory of the computer device includes an internal memory A03 and a non-volatile storage medium A04. The non-volatile storage medium A04 stores an operating system B01, a computer program B02 and a database (not shown in the figure). The internal memory A03 provides an environment for the operation of the operating system B01 and the computer program B02 in the non-volatile storage medium A04. The database of the computer device is used to store assessment data of the fixed-point parking operation level of the tower crane. The network interface A02 of the computer device is used to communicate with an external terminal through a network connection. When the computer program B02 is executed by the processor A01, a method for assessing the fixed-point parking operation level of the tower crane is implemented.

[0065] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than shown in the figure, or combine certain components, or have a different component arrangement.

[0066] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0067] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0068] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0069] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0070] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0071] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0072] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0073] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0074] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various modifications and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for assessing the level of tower crane fixed-point parking operation, characterized in that: The method comprises: detecting in real time the positional relationship between the mobile target and the assessment area, wherein the assessment area includes a parking area; When it is determined that the moving object enters the assessment area, detecting the lifting weight of the moving object; When the lifting weight of the mobile object is less than a preset lifting weight threshold, acquiring a monitoring image of the assessment area; Determining, based on the monitoring image, a point in the mobile object that is farthest from a center point of the parking area; The operation level is assessed based on the positional relationship between the farthest position point and the parking area.

2. The method for assessing the tower crane fixed-point parking operation level according to claim 1 is characterized in that: Determining the farthest position point from the center point of the parking area in the mobile object based on the monitoring image includes: determining a first image position of each corner point of the mobile object and a second image position of a center point of the parking area based on the monitoring image; determining a second separation distance between each first image position and the second image position; The corner point of the mobile object farthest from the center point of the parking area is determined according to all the second interval distances as the farthest position point.

3. The method for assessing the tower crane fixed-point parking operation level according to claim 2 is characterized in that: The determining, based on the monitoring image, a first image position of each corner point of the mobile target and a second image position of the center point of the parking area comprises: Determine a second detection frame corresponding to the parking area in the monitoring image based on a target detection algorithm; performing median blur processing on the image information included in the second detection frame to obtain processed image information; Hough circle detection is performed on the processed image information to determine a second image position of a center point of the parking area.

4. The method for assessing the tower crane fixed-point parking operation level according to claim 2, characterized in that: The determining, based on the monitoring image, a first image position of each corner point of the mobile target and a second image position of the center point of the parking area comprises: Determine a first detection frame corresponding to each corner point of the moving target in the monitoring image based on a target detection algorithm; The center position of each first detection frame is determined as the first image position of each corner point.

5. The method for assessing the tower crane fixed-point parking operation level according to claim 1 is characterized in that: The parking area includes a plurality of sub-areas, and the assessing of the operation level according to the positional relationship between the farthest position point and the parking area includes: Obtaining camera parameters of an image acquisition device that acquires the monitoring image; Determine the actual distance between the farthest point and the center point of the parking area according to the camera parameters; Determine the target sub-area where the farthest position point is located according to the radius of each sub-area and the actual distance; The operation level is assessed according to the target sub-area.

6. The method for assessing the tower crane fixed-point parking operation level according to claim 5, characterized in that: The assessment of the operation level according to the target sub-area includes: Obtaining a preset assessment score corresponding to each sub-region, wherein the multiple sub-regions are concentrically arranged with the same center point as the geometric center, and the size of each sub-region increases radially, and the larger the size of the sub-region, the smaller the corresponding preset assessment score; The tower crane operation level of the current operator is determined according to the preset assessment score corresponding to the target sub-area.

7. The method for assessing the tower crane fixed-point parking operation level according to claim 1 is characterized in that: Determining that the mobile target enters the assessment area includes: When a first interval distance between a center point of the mobile object and a center point of the parking area is less than or equal to a radius of the assessment area, determining that the mobile object has entered the assessment area; The assessment area takes the center point of the parking area as the center point of the assessment area, and takes the sum of twice the radius of the parking area and the radius of the moving object as the radius of the assessment area.

8. A tower crane fixed-point parking operation level assessment device, characterized in that: include: a memory configured to store instructions; The processor is configured to call the instructions from the memory and implement the method for assessing the tower crane fixed-point parking operation level according to any one of claims 1 to 7 when executing the instructions.

9. An assessment system, characterized in that: include: An image acquisition device, used to obtain monitoring images of the assessment area; The device for assessing the tower crane's fixed-point parking operation level according to claim 8.

10. A machine-readable storage medium, characterized in that The machine-readable storage medium stores instructions for causing a machine to execute the method for assessing the fixed-point parking operation level of a tower crane according to any one of claims 1 to 7.

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