Image processing-based sewing machine plate punching depth detection method and system

Abstract

The embodiment of the present application relates to the sewing machine plate processing technical field, and specifically discloses a sewing machine plate punching depth detection method and system based on image processing.The embodiment of the present application plans a punching detection path, determines a current punching position, carries out punching detection shooting, obtains a detection shooting image, processes the detection shooting image, identifies an enhanced detection image, calculates a current punching depth, carries out punching processing adjustment control according to the current punching parameter and the current punching depth, and carries out processing visual display on the current punching depth.The present application deeply couples the plate mechanical properties and the biological optimization mechanism through the dynamic path decision of bionic stress release, actively identifies the high stress area and preferentially punches in the processing, inhibits the cumulative deformation and micro-crack generation of the thin-walled part from the root, and realizes the breakthrough improvement of the sewing machine plate structure integrity and assembly precision.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of sewing machine plate processing, and particularly relates to a sewing machine plate punching depth detection method and system based on image processing. BACKGROUND

[0002] Sewing machine plate processing is a process of processing metal (such as cast iron, aluminum alloy, steel plate, etc.) or non-metallic material (such as engineering plastic) into a part (i.e., a sewing machine plate) meeting the structure design and functional requirements of a sewing machine through a series of machining, forming and surface treatment processes.

[0003] Sewing machine plate punching is one of the most common sewing machine plate processing technologies.

[0004] In the prior art, for the punching processing of a sewing machine plate, only direct punching processing is usually performed according to a pre-set processing depth parameter, and there is a lack of a dynamic detection and adjustment mechanism for an actual processing state, and in an actual production scene, the actual punching depth may have an error due to deformation or uneven placement of the sewing machine plate, thereby affecting the processing quality of the sewing machine plate. SUMMARY

[0005] The purpose of the embodiments of the application is to provide a sewing machine plate punching depth detection method and system based on image processing, and to solve the problems proposed in the background.

[0006] To achieve the above-mentioned purpose, the embodiments of the application provide the following technical solutions:

[0007] The sewing machine plate punching depth detection method based on image processing comprises the following steps:

[0008] Receiving a punching processing requirement of a sewing machine plate, planning a plurality of punching processing positions, matching corresponding punching processing parameters, and planning a punching detection path;

[0009] According to the punching detection path, determining a current punching position, performing punching detection shooting, obtaining a detection shooting image, processing the detection shooting image, and generating an enhanced detection image;

[0010] According to the current punching position, matching a current punching parameter, identifying the enhanced detection image, determining a drill depth on the plate, and calculating a current punching depth;

[0011] According to the current punching parameter and the current punching depth, performing punching processing adjustment control;

[0012] Obtaining a plate material three-dimensional model of the sewing machine plate, and based on the plate material three-dimensional model, performing processing visual display of the current punching depth.

[0013] The image processing-based sewing machine plate drilling depth detection system comprises a detection path planning unit, a detection shooting processing unit, a drilling depth calculation unit, a processing adjustment control unit and a processing visualization display unit, wherein:

[0014] The detection path planning unit is used for receiving the drilling processing requirement of the sewing machine plate, planning a plurality of drilling processing positions, matching corresponding drilling processing parameters, and planning a drilling detection path.

[0015] The detection shooting processing unit is used for determining a current drilling position according to the drilling detection path, performing drilling detection shooting, obtaining a detection shooting image, and processing the detection shooting image to generate an enhanced detection image.

[0016] The drilling depth calculation unit is used for matching a current drilling parameter according to the current drilling position, identifying the enhanced detection image, determining the drill depth on the plate, and calculating the current drilling depth.

[0017] The processing adjustment control unit is used for performing drilling processing adjustment control according to the current drilling parameter and the current drilling depth.

[0018] The processing visualization display unit is used for obtaining a plate material three-dimensional model of the sewing machine plate, and performing processing visualization display on the current drilling depth based on the plate material three-dimensional model.

[0019] Compared with the prior art, the present application has the following advantages:

[0020] 1. The present application deeply couples the plate mechanical properties and biological optimization mechanism by dynamic path decision based on bionic stress release, actively identifies the high stress area and preferentially drills in the processing, and from the root, inhibits the cumulative deformation and micro-crack generation of the thin-walled part, and realizes the breakthrough improvement of the sewing machine plate structure integrity and assembly precision.

[0021] 2. The present application uses a multi-source anti-interference depth calculation model, creatively integrates drill posture optical compensation, orifice state restoration and tool wear dynamic calibration, completely overcomes the measurement failure problem of the traditional image method in the industrial scene such as inclined drilling and burr shielding, and achieves the qualitative leap of hole depth precision in all working conditions.

[0022] 3. The present application is based on a cross-module data cooperation engine, breaks through the data barriers of three-dimensional design model, real-time processing record and historical process knowledge, forms a "detection-decision-optimization" closed-loop self-learning mechanism, and significantly improves the self-adaptive ability of the system to material fluctuation and tool aging. BRIEF DESCRIPTION OF DRAWINGS

[0023] In order to make the technical solutions in the embodiments of the present application clearer, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application.

[0024] Figure 1 A flow chart of the method provided by the embodiments of the present application is shown.

[0025] Figure 2 An application architecture diagram of the system provided by the embodiments of the present application is shown.

[0026] Figure 3 A structural block diagram of the detection path planning unit in the system provided by the embodiments of the present application is shown.

[0027] Figure 4 A structural block diagram of the detection photographing processing unit in the system provided by the embodiments of the present application is shown.

[0028] Figure 5 A structural block diagram of the punching depth calculation unit in the system provided by the embodiments of the present application is shown. DETAILED DESCRIPTION

[0029] In order to make the technical solutions in the embodiments of the present application clearer, the drawings needed to be used in the embodiments or prior art description will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present application.

[0030] It can be understood that, in the prior art, for the punching processing of the sewing machine plate, direct punching processing is usually performed according to the pre-set processing depth parameter, and there is a lack of dynamic detection and adjustment mechanism for the actual processing state. However, in the actual production scene, the actual punching depth may have errors due to the deformation or uneven placement of the sewing machine plate, thereby affecting the processing quality of the sewing machine plate.

[0031] To solve the above problems, the embodiment of the present application receives the punching processing requirement of the sewing machine plate, plans multiple punching processing positions, matches corresponding punching processing parameters, and plans a punching detection path; according to the punching detection path, the current punching position is determined, punching detection shooting is performed, a detection shooting image is obtained, and the detection shooting image is processed to generate an enhanced detection image; according to the current punching position, the current punching parameter is matched, the enhanced detection image is identified, the drill bit depth on the plate is determined, and the current punching depth is calculated; according to the current punching parameter and the current punching depth, punching processing adjustment control is performed; the plate material three-dimensional model of the sewing machine plate is obtained, and based on the plate material three-dimensional model, the current punching depth is processed and visualized. According to the punching detection path, the current punching position can be determined, punching detection shooting, processing and identification can be performed, the drill bit depth on the plate can be determined, the current punching depth can be calculated, and then according to the current punching depth, punching processing adjustment control can be performed and visualized, the actual processing state can be dynamically detected and adjusted, the error of the actual punching depth can be effectively avoided, and the processing quality of the sewing machine plate can be improved.

[0032] Figure 1 A flowchart of the method provided by the embodiment of the present application is shown.

[0033] Specifically, the image processing-based sewing machine plate punching depth detection method comprises the following steps:

[0034] Step S101, receiving the punching processing requirement of the sewing machine plate, planning multiple punching processing positions, matching corresponding punching processing parameters, and planning a punching detection path.

[0035] In the embodiment of the present application, the punching processing requirement of the sewing machine plate input by the worker is received, the punching processing requirement is identified, multiple punching processing positions are planned on the sewing machine plate, processing parameter data is extracted from the punching processing requirement, and punching processing parameters corresponding to the multiple punching processing positions are matched from the processing parameter data, and then the movement planning of punching detection is performed according to the multiple punching processing positions and the multiple punching processing parameters to generate a punching detection path.

[0036] In the preferred embodiment provided by the present application, the receiving of the punching processing requirement of the sewing machine plate, the planning of multiple punching processing positions, the matching of corresponding punching processing parameters, and the planning of a punching detection path specifically comprise the following steps:

[0037] Step S1011, receiving the punching processing requirement of the sewing machine plate;

[0038] Step S1012, identifying the punching processing requirement and planning multiple punching processing positions;

[0039] Step S1013, extracting processing parameter data from the punching processing requirement;

[0040] Step S1014, matching punching processing parameters corresponding to multiple punching processing positions from the processing parameter data;

[0041] Step S1015, planning a punching detection path according to multiple punching processing positions and multiple punching processing parameters.

[0042] In the preferred embodiments provided by the present application, planning a punching detection path according to multiple punching processing positions and multiple punching processing parameters specifically includes the following steps:

[0043] Step S10151, calculating a detection priority coefficient of each punching processing position based on a current requirement depth in the multiple punching processing parameters and a preset depth tolerance threshold, to obtain a priority coefficient corresponding to the punching processing position;

[0044] Step S10152, dividing punching processing positions with the same drill bit type and aperture specification into a processing parameter group based on a drill bit type and an aperture specification in the multiple punching processing parameters;

[0045] Step S10153, sorting the processing parameter group according to the priority coefficient corresponding to the punching processing position from high to low to obtain a sorting result;

[0046] Step S10154, planning a detection path within the processing parameter group based on a spatial proximity principle and the sorting result;

[0047] Step S10155, planning a detection path between processing parameter groups according to a principle of minimizing switching times between processing parameter groups;

[0048] Step S10156, finally generating a punching detection path based on the detection path within the processing parameter group and the detection path between the processing parameter groups.

[0049] Further, the image processing-based sewing machine plate punching depth detection method further includes the following steps:

[0050] Step S102, determining a current punching position according to the punching detection path, performing punching detection shooting, obtaining a detection shooting image, and processing the detection shooting image to generate an enhanced detection image.

[0051] In the embodiment of the present application, in the punching processing of the sewing machine plate, the current punching position is determined from the plurality of punching processing positions according to the punching detection path, and the punching detection position at this time in the punching detection path is determined, the punching detection direction is determined according to the current punching position and the punching detection position, and then the punching detection shooting is performed according to the punching detection direction to obtain the detection shooting image, and then the detection shooting image is subjected to gray processing, and the image noise is filtered by using Gaussian filtering, and the image contrast is enhanced by using histogram equalization, so as to realize the automatic image processing of the detection shooting image and generate the enhanced detection image.

[0052] In the preferred embodiment provided by the present application, the determination of the current punching position according to the punching detection path, the punching detection shooting, the acquisition of the detection shooting image, and the processing of the detection shooting image to generate the enhanced detection image specifically include the following steps:

[0053] In step S1021, the plate three-dimensional model of the sewing machine plate and the current all processed hole positions are obtained.

[0054] In step S1022, the unprocessed hole positions are regarded as growth points, the local stress value of each growth point is calculated under the preset load, the highest stress value is taken as the stress concentration coefficient, and the target growth point is obtained.

[0055] In step S1023, the distance from the target hole position point position to the nearest neighbor unprocessed hole position and the distance from the target hole position point position to the second nearest neighbor unprocessed hole position are taken, and the two distances are multiplied and then taken as the reciprocal to obtain the hole group density factor of the target growth point.

[0056] In step S1024, the stress concentration coefficient and the hole group density factor of the target growth point are multiplied to generate the dynamic priority value of the target growth point.

[0057] In step S1025, the unprocessed hole position corresponding to the highest dynamic priority value of the target growth point is selected as the current punching position to obtain the priority processing hole position.

[0058] In step S1026, the priority processing hole position is marked at the corresponding position of the three-dimensional model to obtain an updated three-dimensional model.

[0059] In step S1027, the current punching position is determined according to the updated three-dimensional model.

[0060] In step S1028, the punching detection direction is determined for the current punching position.

[0061] In step S1029, the punching detection shooting is performed according to the punching detection direction to obtain the detection shooting image.

[0062] In step S10210, the detected image is subjected to grayscale processing, Gaussian filtering to filter image noise, and histogram equalization to enhance image contrast, to generate an enhanced detection image.

[0063] Further, the image processing-based sewing machine plate punching depth detection method further includes the following steps.

[0064] In step S103, the enhanced detection image is identified according to the current punching position and the current punching parameter to determine the plate drill depth and calculate the current punching depth.

[0065] In the embodiment of the present application, the current punching parameter corresponding to the current punching position is matched from a plurality of punching processing parameters, the target drill image is extracted from the enhanced detection image according to the target drill region after target drill region is determined by target recognition of the enhanced detection image, the plate drill depth is determined by size recognition of the target drill image, the current drill length is determined according to the current punching parameter, and the current punching depth is obtained by subtracting the plate drill depth from the current drill length.

[0066] In the preferred embodiment provided by the present application, the step of identifying the enhanced detection image according to the current punching position and the current punching parameter to determine the plate drill depth and calculate the current punching depth specifically includes the following steps:

[0067] In step S1031, the current punching parameter corresponding to the current punching position is matched from a plurality of punching processing parameters.

[0068] In step S1032, the target drill image is extracted by target recognition of the enhanced detection image.

[0069] In step S1033, the plate drill depth is determined by size recognition of the target drill image.

[0070] In step S1034, the current drill length is determined according to the current punching parameter.

[0071] In step S1035, the current punching depth is calculated according to the current drill length and the plate drill depth.

[0072] In the preferred embodiment provided by the present application, the step of calculating the current punching depth according to the current drill length and the plate drill depth specifically includes the following steps:

[0073] In step S10351, the current drill length and the plate drill depth are subjected to basic punching depth calculation to obtain a calculated basic punching depth.

[0074] Step S10352, drill posture analysis is performed on the enhanced detection image, an angle between a drill axis and a normal line of a preset reference surface is identified, and a posture correction amount is calculated by using a preset angle-depth correction model, so as to obtain a calculated posture correction amount;

[0075] Step S10353, orifice state analysis is performed on the enhanced detection image, an occlusion degree of an orifice burr on a drill depth measurement on the board is identified, and an orifice state correction amount is calculated by using the angle-depth correction model, so as to obtain a calculated orifice state correction amount;

[0076] Step S10354, historical drilling depth data of completed hole positions in a preset range of a current drilling position are obtained, and a spatial depth trend compensation amount is calculated by using the angle-depth correction model, so as to obtain a calculated spatial depth trend compensation amount;

[0077] Step S10355, according to a drill type in the current drilling parameter and a current processing hole sequence, in combination with a wear compensation coefficient of a historical same type drill, a drill wear dynamic compensation amount is calculated by using the angle-depth correction model, so as to obtain a calculated drill wear dynamic compensation amount;

[0078] Step S10356, the calculated basic drilling depth, the calculated posture correction amount, the calculated orifice state correction amount, the calculated spatial depth trend compensation amount and the calculated drill wear dynamic compensation amount are comprehensively calculated, and a current drilling depth is finally calculated by using the angle-depth correction model.

[0079] Further, the sewing machine board drilling depth detection method based on image processing further includes the following steps:

[0080] Step S104, drilling processing adjustment control is performed according to the current drilling parameter and the current drilling depth.

[0081] In the embodiment of the application, according to the current drilling parameter, a current required depth is determined, by comparing the current required depth with the current drilling depth, it is judged whether the processing requirement is met, and when the processing requirement is not met, a processing adjustment depth is calculated, a processing adjustment instruction is generated according to the processing adjustment depth, and drilling processing adjustment control is performed according to the processing adjustment instruction.

[0082] In the preferred embodiment provided by the application, the drilling processing adjustment control according to the current drilling parameter and the current drilling depth specifically includes the following steps:

[0083] Step S1041, according to the current drilling parameter, a current required depth is determined;

[0084] Step S1042, comparing the current demand depth with the current drilling depth, calculating a machining adjustment depth;

[0085] Step S1043, generating a machining adjustment instruction according to the machining adjustment depth;

[0086] Step S1044, performing drilling machining adjustment control according to the machining adjustment instruction.

[0087] Further, the image processing-based sewing machine plate drilling depth detection method further includes the following steps:

[0088] Step S105, obtaining a plate material three-dimensional model of the sewing machine plate, and performing machining visual display on the current drilling depth based on the plate material three-dimensional model.

[0089] In the embodiment of the present application, the internal machining code of the sewing machine plate is obtained, and then the plate material three-dimensional model is matched from the preset model database according to the internal machining code, and the plate material three-dimensional model is exported and processed, and a drilling display image is generated according to the current drilling position, the current drilling depth and the current drilling parameter, and then the display area of the drilling display image is determined based on the plate material three-dimensional model, and the visual display of the drilling display image is performed in the display area.

[0090] In the preferred embodiment provided by the present application, the current demand depth is compared with the current drilling depth to calculate the machining adjustment depth, which specifically includes the following steps:

[0091] Step S10421, calculating the basic depth deviation of the current demand depth and the current drilling depth to obtain the calculated basic depth deviation;

[0092] Step S10422, determining and obtaining a feature-error correlation model, performing feature analysis on the enhanced detection image, identifying the hole burr feature and the drill bit side wear feature, and calculating the feature compensation amount of the hole burr feature and the drill bit side wear feature using the feature-error correlation model to obtain the calculated feature compensation amount;

[0093] Step S10423, obtaining the machining adjustment depth record of the completed hole position in the preset range of the current drilling position, and calculating the spatial prediction compensation amount using the feature-error correlation model to obtain the calculated spatial prediction compensation amount;

[0094] Step S10424, according to the drill bit type, the current speed parameter and the feed rate parameter in the current drilling parameter, combining the drill bit type, the historical speed parameter and the historical feed rate parameter in the historical drilling parameter, and calculating the drill bit characteristic compensation amount using the feature-error correlation model to obtain the calculated drill bit characteristic compensation amount;

[0095] Step S10425, based on the calculated basic depth deviation, the calculated feature compensation amount, the calculated spatial prediction compensation amount and the calculated drill bit characteristic compensation amount, to calculate the machining adjustment depth.

[0096] In the preferred embodiment provided by the present application, the step of obtaining the three-dimensional model of the sewing machine plate and visually displaying the machining of the current drilling depth based on the three-dimensional model of the plate material specifically includes the following steps:

[0097] Step S1051, obtaining internal machining code of the sewing machine plate;

[0098] Step S1052, according to the internal machining code, matching and exporting the three-dimensional model of the plate material of the sewing machine plate from the preset model database;

[0099] Step S1053, generating a drilling display image according to the current drilling position, the current drilling depth and the current drilling parameter;

[0100] Step S1054, based on the three-dimensional model of the plate material, performing positioning visual display of the drilling machining on the drilling display image.

[0101] Further, Figure 2 The application architecture diagram of the system provided by the embodiment of the present application is shown.

[0102] In another preferred embodiment provided by the present application, the image processing-based sewing machine plate drilling depth detection system includes:

[0103] The detection path planning unit 101 is configured to receive the drilling machining requirement of the sewing machine plate, plan a plurality of drilling machining positions, match corresponding drilling machining parameters, and plan a drilling detection path.

[0104] In the embodiment of the present application, the detection path planning unit 101 receives the drilling machining requirement of the sewing machine plate input by the worker, identifies the drilling machining requirement, plans a plurality of drilling machining positions on the sewing machine plate, extracts machining parameter data from the drilling machining requirement, matches drilling machining parameters corresponding to the plurality of drilling machining positions from the machining parameter data, and then plans a drilling detection movement according to the plurality of drilling machining positions and the plurality of drilling machining parameters to generate a drilling detection path.

[0105] Specifically, Figure 3 The structure block diagram of the detection path planning unit 101 in the system provided by the embodiment of the present application is shown.

[0106] In the preferred embodiment provided by the present application, the detection path planning unit 101 specifically includes:

[0107] The requirement receiving module 1011 is configured to receive a punching processing requirement of the sewing machine plate.

[0108] The position planning module 1012 is configured to identify the punching processing requirement and plan a plurality of punching processing positions.

[0109] The parameter extraction module 1013 is configured to extract processing parameter data from the punching processing requirement.

[0110] The processing parameter matching module 1014 is configured to match punching processing parameters corresponding to the plurality of punching processing positions from the processing parameter data.

[0111] The path planning module 1015 is configured to plan a punching detection path according to the plurality of punching processing positions and the plurality of punching processing parameters.

[0112] Further, the sewing machine plate punching depth detection system based on image processing further comprises:

[0113] The detection photographing processing unit 102 is configured to determine a current punching position according to the punching detection path, perform punching detection photographing, obtain a detection photographing image, process the detection photographing image, and generate an enhanced detection image.

[0114] In the embodiment of the present application, during the punching processing of the sewing machine plate, the detection photographing processing unit 102 determines a current punching position from the plurality of punching processing positions according to the punching detection path, determines a punching detection position in the punching detection path at this time, determines a punching detection direction according to the current punching position and the punching detection position, performs punching detection photographing according to the punching detection direction, obtains a detection photographing image, then performs grayscale processing on the detection photographing image, filters image noise by using Gaussian filtering, and enhances image contrast by using histogram equalization, thereby realizing automatic image processing of the detection photographing image and generating an enhanced detection image.

[0115] Specifically, Figure 4 The structure block diagram of the detection photographing processing unit 102 in the system provided by the embodiment of the present application is shown.

[0116] In the preferred embodiment provided by the present application, the detection photographing processing unit 102 specifically comprises:

[0117] The position determination module 1021 is configured to determine a current punching position from the plurality of punching processing positions according to the punching detection path.

[0118] The direction determination module 1022 is configured to determine a punching detection direction for the current punching position.

[0119] The detection shooting module 1023 is configured to shoot a detection image in the punching detection direction.

[0120] The image processing module 1024 is configured to perform grayscale processing on the detection image, filter image noise by using a Gaussian filter, and enhance the contrast of the image by using histogram equalization to generate an enhanced detection image.

[0121] Further, the punching depth detection system based on image processing further comprises:

[0122] The punching depth calculation unit 103 is configured to match a current punching parameter corresponding to the current punching position according to the current punching position, identify the enhanced detection image, determine the drill depth on the plate, and calculate the current punching depth.

[0123] In the embodiment of the present application, the punching depth calculation unit 103 matches the current punching parameter corresponding to the current punching position from a plurality of punching processing parameters, identifies the target drill region in the enhanced detection image, extracts the target drill image from the enhanced detection image according to the target drill region, identifies the size of the target drill image to determine the drill depth on the plate, determines the current drill length according to the current punching parameter, subtracts the current drill length from the drill depth on the plate to obtain the current punching depth.

[0124] Specifically, Figure 5 The structure block diagram of the punching depth calculation unit 103 in the system provided by the embodiment of the present application is shown.

[0125] In the preferred embodiment provided by the present application, the punching depth calculation unit 103 specifically comprises:

[0126] The current parameter matching module 1031 is configured to match the current punching parameter corresponding to the current punching position from a plurality of punching processing parameters.

[0127] The target identification module 1032 is configured to identify the target drill image from the enhanced detection image.

[0128] The size identification module 1033 is configured to identify the size of the target drill image to determine the drill depth on the plate.

[0129] The length determination module 1034 is configured to determine the current drill length according to the current punching parameter.

[0130] The depth calculation module 1035 is configured to calculate the current punching depth according to the current drill length and the drill depth on the plate.

[0131] Further, the image processing-based sewing machine plate punching depth detection system further comprises:

[0132] The processing adjustment control unit 104 is configured to perform punching processing adjustment control according to the current punching parameter and the current punching depth.

[0133] In the embodiment of the present application, the processing adjustment control unit 104 determines the current required depth according to the current punching parameter, compares the current required depth with the current punching depth to determine whether the processing requirement is met, calculates a processing adjustment depth when the processing requirement is not met, generates a processing adjustment instruction according to the processing adjustment depth, and performs punching processing adjustment control according to the processing adjustment instruction.

[0134] The processing visualization display unit 105 is configured to acquire a plate material three-dimensional model of the sewing machine plate, and perform processing visualization display on the current punching depth based on the plate material three-dimensional model.

[0135] In the embodiment of the present application, the processing visualization display unit 105 acquires internal processing codes of the sewing machine plate, matches the plate material three-dimensional model of the sewing machine plate from a preset model database according to the internal processing codes, and performs export processing on the plate material three-dimensional model, generates a punching display image according to the current punching position, the current punching depth and the current punching parameter, and determines a display area of the punching display image based on the plate material three-dimensional model, and performs visualization display of the punching display image in the display area.

[0136] It should be understood that, although each step in the flowchart of each embodiment of the present application is displayed in sequence according to the arrow, these steps are not necessarily executed in sequence according to the arrow. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other sequences. Moreover, at least part of the steps in each embodiment can include multiple sub-steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution sequence of these sub-steps or stages is not necessarily sequential, but can be executed in rotation or alternation with other steps or sub-steps or stages of other steps.

[0137] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program. The program can be stored in a non-volatile computer readable storage medium, and when the program is executed, the processes of the above-mentioned embodiments of the methods can be included. Any reference to memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration but not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0138] Any combination of the technical features of the above-mentioned embodiments can be combined. In order to make the description simple, all possible combinations of the technical features in the above-mentioned embodiments are not described, however, as long as the combination of the technical features does not exist contradictory, it should be considered as the scope of the present application.

[0139] The above-mentioned embodiments only express several embodiments of the present application, and the description is more specific and detailed, but it should not be understood as limiting the scope of the present application. It should be noted that for ordinary skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are within the scope of the present application. Therefore, the protection scope of the present application should be subject to the appended claims.

[0140] The above-mentioned is only the preferred embodiment of the present application, and does not limit the present application. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A sewing machine plate perforation depth detection method based on image processing, characterized in that, The method includes the following steps: Receive the drilling requirements of the sewing machine board, plan multiple drilling locations, match the corresponding drilling parameters, and plan the drilling detection path; According to the drilling detection path, determine the current drilling position, perform drilling detection and capture, acquire the captured image, and process the captured image to generate an enhanced detection image; Based on the current drilling position, the current drilling parameters are matched, the enhanced detection image is identified, the drill bit depth on the board is determined, and the current drilling depth is calculated. Based on the current drilling parameters and the current drilling depth, the drilling process is adjusted and controlled. Obtain a 3D model of the sewing machine board, and based on the 3D model of the board, visualize the current drilling depth. The process of determining the current punching position according to the punching detection path, performing punching detection and capturing images, and processing the captured images to generate enhanced detection images specifically includes the following steps: Obtain the 3D model of the sewing machine board and all currently processed holes; The unprocessed holes are regarded as growth points. The local stress value of each growth point is calculated under a preset load, and the highest stress value is taken as the stress concentration factor to obtain the target growth point. For the target pore location, take the distance from the target pore location to the nearest neighbor unprocessed pore location, and the distance from the target pore location to the second nearest neighbor unprocessed pore location. Multiply the two distances and take the reciprocal to obtain the pore group density factor of the target growth point. The stress concentration factor is multiplied by the pore group density factor of the target growth point to generate the dynamic priority value of the target growth point. Select the unprocessed hole position corresponding to the highest dynamic priority value of the target growth point as the current drilling position to obtain the priority of the processed hole position; Mark the priority machining holes at their corresponding positions on the 3D model to obtain an updated 3D model; The current drilling position is determined based on the updated 3D model; For the current drilling position, determine the drilling detection direction; Perform a hole detection image capture according to the hole detection direction to obtain the detection image; The detected image is converted to grayscale, Gaussian filtering is used to filter image noise, and histogram equalization is used to enhance image contrast, thereby generating an enhanced detection image.

2. The sewing machine plate punching depth detection method based on image processing according to claim 1, characterized in that, The process of receiving the punching requirements of the sewing machine plate, planning multiple punching locations, matching corresponding punching parameters, and planning the punching detection path specifically includes the following steps: Receive requests for drilling processing on sewing machine plates; The drilling requirements are identified, and multiple drilling locations are planned. Extract processing parameter data from the drilling requirements; From the processing parameter data, match the drilling processing parameters corresponding to multiple drilling positions; Plan the drilling inspection path based on multiple drilling locations and multiple drilling parameters.

3. The sewing machine plate punching depth detection method based on image processing according to claim 2, characterized in that, Based on multiple drilling locations and multiple drilling parameters, a drilling inspection path is planned, which includes the following steps: Based on the current required depth and preset depth tolerance threshold among the multiple drilling processing parameters, the detection priority coefficient of each drilling processing position is calculated to obtain the priority coefficient corresponding to the drilling processing position. Based on the drill bit type and hole diameter specifications among the multiple drilling processing parameters, drilling positions with the same drill bit type and hole diameter specifications are divided into processing parameter groups. Within the processing parameter group, the parameters are sorted in descending order of priority coefficients corresponding to the drilling positions to obtain the sorting result. Based on the principle of spatial proximity and the sorting results, the detection path within the processing parameter group is planned; Based on the principle of minimizing the number of times processing parameter groups are switched, the detection paths between processing parameter groups are planned; Based on the detection paths within the planned processing parameter group and the detection paths between the planned processing parameter groups, the final drilling detection path is generated.

4. The sewing machine plate punching depth detection method based on image processing according to claim 1, characterized in that, The steps of matching the current drilling parameters with the current drilling position, identifying the enhanced detection image, determining the drill bit depth on the board, and calculating the current drilling depth specifically include the following steps: From multiple drilling processing parameters, match the current drilling parameter corresponding to the current drilling position; Target recognition is performed on the enhanced detection image to extract the target drill bit image; The target drill bit image is used for size recognition to determine the drill bit depth on the board; Determine the current drill bit length based on the current drilling parameters; The current drilling depth is calculated based on the current drill bit length and the drill bit depth on the board.

5. The sewing machine plate punching depth detection method based on image processing according to claim 4, characterized in that, The current drilling depth is calculated based on the current drill bit length and the drill bit depth on the board, specifically including the following steps: The basic drilling depth is calculated by using the current drill bit length and the drill bit depth on the plate; The drill bit attitude is analyzed on the enhanced detection image to identify the angle between the drill bit axis and the normal of the preset reference plane, and the attitude correction amount is calculated using the preset angle-depth correction model to obtain the calculated attitude correction amount. The enhanced detection image is analyzed for orifice status to identify the degree of obstruction of the drill bit depth measurement on the board by orifice burrs, and the orifice status correction amount is calculated using the included angle-depth correction model to obtain the calculated orifice status correction amount. Obtain historical drilling depth data of completed holes within a preset range of the current drilling position, and use the included angle-depth correction model to calculate the spatial depth trend compensation amount, thus obtaining the calculated spatial depth trend compensation amount; Based on the drill bit type and current hole sequence in the current drilling parameters, and combined with the wear compensation coefficient of similar drill bits in history, the dynamic compensation amount of drill bit wear is calculated using the included angle-depth correction model, and the calculated dynamic compensation amount of drill bit wear is obtained. The current drilling depth is finally calculated by comprehensively considering the basic drilling depth, the calculated attitude correction amount, the calculated borehole state correction amount, the calculated spatial depth trend compensation amount, and the calculated drill bit wear dynamic compensation amount, using the included angle-depth correction model.

6. The sewing machine plate punching depth detection method based on image processing according to claim 5, characterized in that, The step of adjusting and controlling the drilling process based on the current drilling parameters and the current drilling depth specifically includes the following steps: Determine the current required depth based on the current drilling parameters; Compare the current required depth with the current drilling depth to calculate the processing adjustment depth; Based on the stated processing adjustment depth, a processing adjustment instruction is generated; Perform drilling adjustment control according to the processing adjustment instructions.

7. The sewing machine plate punching depth detection method based on image processing according to claim 6, characterized in that, The current required depth is compared with the current drilling depth to calculate the processing adjustment depth, which specifically includes the following steps: The base depth deviation between the current required depth and the current drilling depth is calculated to obtain the calculated base depth deviation. The feature-error correlation model was determined and obtained. Feature analysis was performed on the enhanced detection image to identify the burr features at the orifice and the wear features on the drill bit side. The feature-error correlation model was used to calculate the feature compensation amount for the burr features at the orifice and the wear features on the drill bit side, and the calculated feature compensation amount was obtained. Obtain the historical records of the processing and adjustment depth of completed holes within the preset range of the current drilling position, and use the feature-error correlation model to calculate the spatial prediction compensation amount to obtain the calculated spatial prediction compensation amount. Based on the drill bit type, current rotation speed, and feed rate parameters in the current drilling parameters, and combined with the drill bit type, historical rotation speed, and historical feed rate parameters in the historical drilling parameters, the drill bit characteristic compensation amount is calculated using the feature-error correlation model to obtain the calculated drill bit characteristic compensation amount. The processing adjustment depth is calculated based on the calculated basic depth deviation, the calculated characteristic compensation amount, the calculated spatial prediction compensation amount, and the calculated drill bit characteristic compensation amount.

8. The sewing machine plate punching depth detection method based on image processing according to claim 7, characterized in that, The process of obtaining a 3D model of the sewing machine board and visually displaying the current punching depth based on the 3D model includes the following steps: Obtain the internal machining code of the sewing machine plate; Based on the internal processing code, the three-dimensional model of the sewing machine board is matched and exported from the preset model database; A punching display image is generated based on the current punching position, the current punching depth, and the current punching parameters; Based on the three-dimensional model of the board material, the positioning and visualization of the drilling process are displayed in the drilling display image.

9. A sewing machine plate punching depth detection system based on image processing, characterized in that, The system employs the image processing-based sewing machine plate punching depth detection method as described in any one of claims 1 to 8 above. The system comprises: The detection path planning unit is used to receive the punching processing requirements of the sewing machine plate, plan multiple punching processing positions, match the corresponding punching processing parameters, and plan the punching detection path. The detection and imaging processing unit is used to determine the current drilling position according to the drilling detection path, perform drilling detection imaging, acquire the detection and imaging image, and process the detection and imaging image to generate an enhanced detection image; The drilling depth calculation unit is used to match the current drilling parameters with the current drilling position, identify the enhanced detection image, determine the drill bit depth on the board, and calculate the current drilling depth. The processing adjustment control unit is used to perform drilling processing adjustment control based on the current drilling parameters and the current drilling depth; The processing visualization display unit is used to acquire a three-dimensional model of the sewing machine board and, based on the three-dimensional model of the board, to visualize the current drilling depth.

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