A gantry machine tool tool magazine safety detection system

Abstract

The application discloses a gantry machine tool tool magazine safety detection system and relates to the technical field of gantry machine tools.The application solves the problem that an object entering a blind area cannot be quickly identified as a human body, and the comprehensiveness of the identification needs to be improved.The application compares a change area profile with a preset human body template, analyzes a two-dimensional coordinate system, performs center point coincidence and scaling operations, calculates the proportion of the coincident area, and determines whether it is a human body area in this way.This scientific determination method improves the accuracy and reliability of the identification, reduces the false positive rate, ensures accurate transmission of early warning information, and reminds the operator to take timely measures to avoid danger once the system determines that the change area is a human body area and rapidly sends an early warning signal through an early warning end.This real-time response mechanism can effectively reduce the probability of accidents and nip potential risks in the bud.

Description

Technical Field

[0001] This invention relates to the field of gantry milling machine technology, specifically to a gantry milling machine tool magazine safety detection system. Background Technology

[0002] Gantry milling machines are a type of large, high-precision machine tool that plays a crucial role in the field of machining. They are named for their gantry-like frame structure. The iconic gantry frame is composed of components such as crossbeams and columns, and its stable structure can withstand large cutting forces, ensuring accuracy when machining large workpieces. For example, when machining large ship engine cylinder blocks, gantry milling machines can complete complex machining processes due to their stable structure. They are large in size and have a strong load-bearing capacity, allowing large workpieces to be placed stably. Some worktables can be multi-axis linked to achieve complex movements and meet diverse machining needs.

[0003] The tool magazine of the gantry milling machine is huge. When performing maintenance and tool management, relevant personnel need to enter the work area. Due to the large size of the tool magazine, there are blind spots in the field of vision during operation. In order to avoid the operational risks caused by this, safety identification is required to promote safe production in enterprises.

[0004] During the safety monitoring process of the gantry milling machine tool magazine, because it does not perform image analysis on objects entering the blind zone, it is unable to quickly and effectively determine whether the objects entering the blind zone belong to the human body. Often, an early warning is issued when an object enters, but this warning method cannot quickly identify whether the object entering the blind zone belongs to the human body, and its comprehensiveness of identification needs to be improved. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a gantry milling machine tool magazine safety detection system, which solves the problem of not being able to quickly identify objects entering the blind zone as human bodies, and the comprehensiveness of its identification needs to be improved.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a gantry milling machine tool magazine safety detection system, comprising:

[0007] The visual monitoring terminal monitors the blind spots set by the gantry milling machine and transmits the real-time video of the blind spots to the real-time video processing terminal.

[0008] The real-time video processing terminal monitors and processes the blind zone video in real time. Based on the comparison differences between adjacent frames within the blind zone video, it identifies non-overlapping areas. Then, based on the changes in these non-overlapping areas, it identifies the changed areas and the associated frames to be processed. The specific method is as follows:

[0009] Based on real-time monitoring of blind zone video, the frames of adjacent frames in the blind zone video are compared to identify whether the two sets of frames are consistent. If they are consistent, the comparison continues. If they are inconsistent, the next set of frames is marked as the initial difference frame, and the inconsistent non-overlapping areas are marked.

[0010] Based on the initial frame and the non-overlapping area marked inside, identify whether the next set of frames matches the initial frame. If they match, the non-overlapping area marked this time is recorded as the changed area. If they do not match, continue to confirm the non-overlapping area and re-record the non-overlapping area confirmed this time and the entire area of ​​the marked non-overlapping area as the non-overlapping area.

[0011] This process continues until the subsequent frames match the previous set of frames. The non-overlapping areas are locked, and the locked non-overlapping areas are marked as changed areas. The frames to which the changed areas belong are recorded as frames to be processed.

[0012] The change region confirmation end, based on the marked frame to be processed and the marked change region within it, confirms the pixel values ​​associated with the pixels within the change region, locks the gradient pixels based on the confirmed pixel values, confirms the region outline of this change region based on the continuously appearing gradient pixels, and transmits the confirmed region outline to the human body confirmation processing end. Specifically:

[0013] Based on the confirmed frames to be processed and the associated change regions, the pixel values ​​associated with different pixels within the change regions are labeled as X. i , where i represents different pixels;

[0014] Sobe was used to confirm the horizontal and vertical gradients associated with a specified pixel, and the confirmed horizontal gradient was denoted as H. i The confirmed vertical gradient is denoted as S. i ;

[0015] use: Determine the comprehensive gradient ZH associated with the corresponding pixel. i ;

[0016] The confirmed comprehensive gradient ZH i The value of Y1 is checked against the preset value Y1, where the specific value of Y1 is determined by the operator based on experience. If ZH i If ZH ≥ Y1, then this pixel is marked as a gradient pixel. i If Y < Y1, then no labeling is applied to this pixel.

[0017] The adjacent gradient pixels are confirmed in turn, the region contour associated with several groups of adjacent gradient pixels is locked, the locked region contour is marked as the region contour of this changing region, and the confirmed region contour is transmitted to the human body confirmation processing terminal.

[0018] The human body confirmation processing end, based on the confirmed region outline of the corresponding changed area, compares the region outline with the preset human body template to determine whether such a changed area belongs to the human body region. If it does, the early warning end is directly controlled to issue an early warning; if it does not, monitoring continues. The specific method is as follows:

[0019] Based on the confirmed regional outline, this regional outline is placed in a two-dimensional coordinate system. Based on the location of different outline points in the two-dimensional coordinate system, the associated two-dimensional coordinates are confirmed. Then, the average value of several sets of associated two-dimensional coordinates is processed to confirm the average value point, and the confirmed average value point is marked as the center point of this regional outline.

[0020] Based on the preset human body template, the preset center point within the human body template is confirmed. The human body template and the region outline are moved until the center point of the human body template coincides with the center point of the region outline. The human body template is then scaled according to the determined center point. During the scaling process, the region outline is kept within the human body template. The maximum overlap between the region outline and the human body template is determined. The overlap area between the region outline and the human body template is recorded, and the percentage of the overlap area within the human body template is determined. The percentage is calculated as: total area of ​​overlap area ÷ total area of ​​human body template.

[0021] The confirmed percentage value is compared with the preset value Y2: if the percentage value < Y2, it means that the outline of this area does not belong to the human body outline, and monitoring continues; if the percentage value ≥ Y2, it means that the outline of this area belongs to the human body outline, and an early warning signal is generated through the early warning terminal to alert relevant external operators.

[0022] Preferably, the blind spot is pre-set by relevant personnel to conduct safety monitoring of relevant areas of the gantry machine tool and prevent relevant personnel from entering the dangerous area of ​​the gantry machine tool.

[0023] This invention provides a safety detection system for the tool magazine of a gantry milling machine. Compared with the prior art, it has the following advantages:

[0024] This invention can accurately locate the changing area and its corresponding frame to be processed by carefully comparing adjacent frames in the blind spot video, thereby determining the position and state of a person after entering the blind spot; in the changing area confirmation stage, gradient pixel points are locked based on pixel value analysis to accurately outline the contour of the changing area, providing accurate basic data for subsequent human body confirmation.

[0025] By comparing the outline of the changed area with a preset human body template, and using two-dimensional coordinate system analysis, center point coincidence, and scaling operations, the proportion of the overlapping area is calculated to determine whether it is a human body area. This scientific determination method improves the accuracy and reliability of identification, reduces the false alarm rate, and ensures the accurate transmission of early warning information. Once the system determines that the changed area belongs to a human body area, it can quickly issue an early warning signal through the early warning terminal to remind operators to take timely measures to avoid danger. This real-time response mechanism can effectively reduce the probability of accidents and nip potential risks in the bud. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the principle framework of the present invention. Detailed Implementation

[0027] 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, and 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.

[0028] Please see Figure 1 This application provides a gantry milling machine tool magazine safety detection system, including a visual monitoring end, a real-time monitoring video processing end, a change area confirmation end, a human body confirmation processing end, and an early warning end. The visual monitoring end, the real-time monitoring video processing end, the change area confirmation end, the human body confirmation processing end, and the early warning end are all electrically connected from the output node to the input node in sequence.

[0029] Among them, the visual monitoring terminal monitors the blind spots set by the gantry machine tool and transmits the real-time monitoring video of the blind spots to the real-time monitoring video processing terminal. The blind spots are set in advance by relevant personnel to conduct safety monitoring of relevant areas of the gantry machine tool and prevent relevant personnel from entering the dangerous areas of the gantry machine tool.

[0030] The monitoring video real-time processing terminal processes the blind zone video in real time. Based on the comparison difference between adjacent frames in the blind zone video, it locks the non-overlapping area. Then, based on the changes in the non-overlapping area, it locks the changed area and the frame to be processed associated with the changed area. Specifically, it is assumed that a person walks into this blind zone. During the process of walking in, there are several different frames. Each frame contains a non-overlapping area that gradually increases in size. When the person has completely entered the blind zone, the area associated with the gradually increasing non-overlapping area will not change. Therefore, the confirmed non-overlapping area belongs to the confirmed changed area.

[0031] The specific method for locking the changing area is as follows:

[0032] Based on real-time monitoring of blind zone video, the frames of adjacent frames in the blind zone video are compared to identify whether the two sets of frames are consistent. If they are consistent, the comparison continues. If they are inconsistent, the next set of frames is marked as the initial difference frame, and the inconsistent non-overlapping areas are marked.

[0033] Based on the initial frame and the non-overlapping area marked inside, identify whether the next set of frames matches the initial frame. If they match, the non-overlapping area marked this time is recorded as the changed area. If they do not match, continue to confirm the non-overlapping area and re-record the non-overlapping area confirmed this time and the entire area of ​​the marked non-overlapping area as the non-overlapping area.

[0034] This process continues until the subsequent frames match the previous set of frames. The non-overlapping areas are locked, and the locked non-overlapping areas are marked as changed areas. The frames to which the changed areas belong are recorded as frames to be processed.

[0035] Specifically, the changed area identified here has been marked in the corresponding frame. The identified changed area is the area associated with the corresponding person fully entering this blind zone. The non-overlapping area for this type of person is locked. Based on the identified non-overlapping area, the associated coverage area of ​​the specified human body can be fully confirmed. Subsequently, the overall outline of the changed area is confirmed to ensure the accuracy of the confirmation in this frame and improve the specific confirmation effect of the frame.

[0036] The change region confirmation end confirms the pixel values ​​associated with the pixels within the marked frame to be processed and the marked change region. Based on the confirmed pixel values, it locks the gradient pixels. Based on the continuously appearing gradient pixels, it confirms the region outline of the change region and transmits the confirmed region outline to the human body confirmation processing end. Specifically, there are several different pixels in the change region, and different pixels have different pixel values. At the edge outline of the corresponding region, there are points where the pixel values ​​change more obviously. These points are gradient pixels. Based on the continuously appearing gradient pixels, the region outline of the corresponding change region can be confirmed.

[0037] Based on the confirmed frames to be processed and the associated change regions, the pixel values ​​associated with different pixels within the change regions are labeled as X. i , where i represents different pixels;

[0038] Sobe was used to confirm the horizontal and vertical gradients associated with a specified pixel, and the confirmed horizontal gradient was denoted as H. iThe confirmed vertical gradient is denoted as S. i Specifically, to confirm the horizontal and vertical gradients, it is necessary to confirm the eight adjacent groups of pixels around this pixel and assign a weight associated with the pixel value of each different pixel. Then, based on the assigned weights, the horizontal and vertical gradients associated with the corresponding pixel are locked. Since this type of processing method is common in existing technologies, it will not be elaborated on here.

[0039] use: Determine the comprehensive gradient ZH associated with the corresponding pixel. i ;

[0040] The confirmed comprehensive gradient ZH i The value of Y1 is checked against the preset value Y1, where the specific value of Y1 is determined by the operator based on experience. If ZH i If ZH < Y1, then no calibration is performed on this pixel; if ZH < Y1, then no calibration is performed on this pixel. i If Y1 ≥ 1, then this pixel is marked as a gradient pixel.

[0041] Adjacent gradient pixels are sequentially confirmed, and the region contour associated with several groups of adjacent gradient pixels is locked (lines are composed of points, so the edge contour can be determined based on several adjacent points). The locked region contour is marked as the region contour of this changing region, and the confirmed region contour is transmitted to the human body confirmation processing terminal.

[0042] The human body confirmation processing unit, based on the confirmed region outline of the corresponding changed area, compares the region outline with the preset human body template to determine whether such a changed region belongs to the human body region. If it does, the unit directly controls the early warning unit to issue an early warning; if it does not, it continues to monitor. The specific method for assessment is as follows:

[0043] Based on the confirmed regional outline, this regional outline is placed in a two-dimensional coordinate system. Based on the location of different outline points in the two-dimensional coordinate system, the associated two-dimensional coordinates are confirmed. Then, the average value of several sets of associated two-dimensional coordinates is processed to confirm the average value point, and the confirmed average value point is marked as the center point of this regional outline.

[0044] Based on the preset human body template, the preset center point within the human body template is confirmed. The human body template and the region outline are moved until the center point of the human body template coincides with the center point of the region outline. The human body template is then scaled according to the determined center point. During the scaling process, the region outline is kept within the human body template. The maximum overlap between the region outline and the human body template is determined. The overlap area between the region outline and the human body template is recorded, and the percentage of the overlap area within the human body template is determined. The percentage is calculated as: total area of ​​overlap area ÷ total area of ​​human body template.

[0045] The confirmed percentage value is compared with the preset value Y2: if the percentage value < Y2, it means that the outline of this area does not belong to the human body outline, and monitoring continues; if the percentage value ≥ Y2, it means that the outline of this area belongs to the human body outline, and an early warning signal is generated through the early warning terminal to alert relevant external operators.

[0046] Specifically, the system can monitor the blind spots of the gantry milling machine in real time, pre-set dangerous areas, prevent personnel from entering, reduce safety accidents caused by personnel accidentally entering blind spots, protect the personal safety of operators, and create a safe and reliable working environment for production.

[0047] By meticulously comparing adjacent frames in the blind zone video, the changing area and its corresponding frame to be processed can be accurately located, thereby determining the position and status of a person after entering the blind zone. In the changing area confirmation stage, gradient pixels are locked based on pixel value analysis, and the outline of the changing area is accurately delineated, providing accurate basic data for subsequent human body confirmation.

[0048] The human body confirmation processing end compares the outline of the changed area with the preset human body template. With the help of two-dimensional coordinate system analysis, center point coincidence and scaling operations, it calculates the proportion of the overlapping area to determine whether it is a human body area. This scientific determination method improves the accuracy and reliability of recognition, reduces the false alarm rate, and ensures the accurate transmission of early warning information.

[0049] Once the system determines that the changed area belongs to the human body area, it can quickly issue an early warning signal through the warning terminal to remind the operator to take timely measures to avoid danger. This real-time response mechanism can effectively reduce the probability of accidents and nip potential risks in the bud.

[0050] Some of the data in the above formulas are numerical calculations with dimensions removed, and the contents not described in detail in this specification are all prior art known to those skilled in the art.

[0051] The above embodiments are only used to illustrate the technical methods of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical methods of the present invention without departing from the spirit and scope of the technical methods of the present invention.

Claims

1. A safety detection system for a gantry milling machine tool magazine, characterized in that, include: The visual monitoring terminal monitors the blind spots set by the gantry milling machine and transmits the real-time video of the blind spots to the real-time video processing terminal. The monitoring video real-time processing terminal processes the blind zone video in real time. Based on the comparison difference between adjacent frames in the blind zone video, it locks the non-overlapping area. Then, based on the changes in the non-overlapping area, it locks the changed area and the frame to be processed associated with the changed area. The specific method for locking the changed area is as follows: Based on real-time monitoring of blind zone video, the frames of adjacent frames in the blind zone video are compared to identify whether the two sets of frames are consistent. If they are consistent, the comparison continues. If they are inconsistent, the next set of frames is marked as the initial difference frame, and the inconsistent non-overlapping areas are marked. Based on the initial frame and the non-overlapping area marked inside, identify whether the next set of frames matches the initial frame. If they match, the non-overlapping area marked this time is recorded as the changed area. If they do not match, continue to confirm the non-overlapping area and re-record the non-overlapping area confirmed this time and the entire area of ​​the marked non-overlapping area as the non-overlapping area. This process continues until the subsequent frames match the previous set of frames. The non-overlapping areas are locked, and the locked non-overlapping areas are marked as changed areas. The frames to which the changed areas belong are recorded as frames to be processed. The change region confirmation end confirms the pixel values ​​associated with the pixels within the change region based on the marked frame to be processed and the marked change region inside it, and locks the gradient pixels based on the confirmed pixel values. Based on the continuously appearing gradient pixels, it confirms the region outline of this change region and transmits the confirmed region outline to the human body confirmation processing end. The human body confirmation processing end, based on the confirmed region outline of the corresponding changed area, compares the region outline with the preset human body template to determine whether such a changed area belongs to the human body region. If it does, the early warning end is directly controlled to issue an early warning; if it does not, monitoring continues. The specific method is as follows: Based on the confirmed regional outline, this regional outline is placed in a two-dimensional coordinate system. Based on the location of different outline points in the two-dimensional coordinate system, the associated two-dimensional coordinates are confirmed. Then, the average value of several sets of associated two-dimensional coordinates is processed to confirm the average value point, and the confirmed average value point is marked as the center point of this regional outline. Based on the preset human body template, the preset center point within the human body template is confirmed. The human body template and the region outline are moved until the center point of the human body template coincides with the center point of the region outline. The human body template is then scaled according to the determined center point. During the scaling process, the region outline is kept within the human body template. The maximum overlap between the region outline and the human body template is determined. The overlap area between the region outline and the human body template is recorded, and the percentage of the overlap area within the human body template is determined. The percentage is calculated as: total area of ​​overlap area ÷ total area of ​​human body template. The confirmed percentage value is compared with the preset value Y2: if the percentage value < Y2, it means that the outline of this area does not belong to the human body outline, and monitoring continues.

2. The gantry milling machine tool magazine safety detection system according to claim 1, characterized in that, The specific method by which the change area confirmation terminal confirms the region outline of this change area is as follows: Based on the confirmed frames to be processed and the associated change regions, the pixel values ​​associated with different pixels within the change regions are labeled as X. i , where i represents different pixels; Sobel is used to confirm the horizontal and vertical gradients associated with a specified pixel, and the confirmed horizontal gradient is denoted as H. i The confirmed vertical gradient is denoted as S. i ; use: Determine the comprehensive gradient ZH associated with the corresponding pixel. i ; The confirmed comprehensive gradient ZH i The value of Y1 is checked against the preset value Y1, where the specific value of Y1 is determined by the operator based on experience. If ZH i If Y1 ≥ 1, then this pixel is marked as a gradient pixel. Adjacent gradient pixels are sequentially confirmed, and the region contours associated with several groups of adjacent gradient pixels are locked. The locked region contours are marked as the region contours of this changing region, and the confirmed region contours are transmitted to the human body confirmation processing terminal.

3. The gantry milling machine tool magazine safety detection system according to claim 2, characterized in that, If ZH i If the value is less than Y1, then no labeling is applied to this pixel.

4. The gantry milling machine tool magazine safety detection system according to claim 1, characterized in that, If the percentage value is greater than or equal to Y2, it means that the outline of this area belongs to the outline of a human body. In this case, an early warning signal will be generated and displayed through the early warning terminal to alert relevant external operators.

5. The gantry milling machine tool magazine safety detection system according to claim 1, characterized in that, The blind spots are pre-set by relevant personnel to conduct safety monitoring of relevant areas of the gantry milling machine and prevent relevant personnel from entering the dangerous areas of the gantry milling machine.

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