Remodeling method and device of tool clamp, storage medium and electronic equipment

Abstract

The invention discloses a tool clamp model changing method and device, a storage medium and electronic equipment, and relates to the field of industrial equipment management.The method comprises the steps that a module identifier of a target module is recognized, a first interface specification corresponding to the target module is determined through the module identifier, and the target module is used for clamping a workpiece in a tool clamp system; under the condition that a first deviation between the first interface specification and a second interface specification of a basic mounting base in the tool clamp system conforms to a preset deviation interval, target parameters of a target module and a target workpiece are obtained, and parameter loading is conducted on the target module according to the target parameters; under the condition that the target module completes loading of the target parameters, it is determined that remodeling of the target module is completed, and the target workpiece is clamped; and positioning the target workpiece, and fixing the target workpiece according to the target parameters. The problem that the production efficiency of multi-variety products is low in a production scene in the prior art is solved.

Description

Technical Field

[0001] This application relates to the field of industrial equipment management, and more particularly to a tooling fixture change method and apparatus, storage medium and electronic equipment. Background Technology

[0002] In a multi-variety, small-batch production model, production lines need to frequently switch production tasks, placing extremely high demands on the adaptability and rapid changeover capabilities of equipment. As an indispensable component of precision machining, tooling and fixtures directly affect machining accuracy, efficiency, and production costs. Traditional tooling and fixture designs often focus on mass production of single products, meaning that frequent product changes require tedious manual adjustments and prolonged equipment downtime. This undoubtedly becomes a major obstacle to the transformation of modern manufacturing towards flexibility and intelligence.

[0003] In specific scenarios, such as automobile manufacturing and aerospace parts processing, production lines often need to process parts of various shapes and sizes. Whenever the type of workpiece changes, technicians on the production line must manually adjust the fixtures and replace components such as locating pins and clamping devices suitable for the new workpiece. This process is not only time-consuming (usually taking 15-30 minutes) but also prone to introducing human error, affecting processing accuracy. In other words, the production scenarios in related technologies suffer from the problem of low production efficiency for multiple product varieties. Summary of the Invention

[0004] This application provides a tooling fixture change method and apparatus, storage medium and electronic device, to at least solve the problem of low production efficiency for multiple product types in related production scenarios.

[0005] This application provides a method for changing the type of a tooling fixture, comprising: identifying a module identifier of a target module and determining a first interface specification corresponding to the target module through the module identifier, wherein the target module is used to clamp a workpiece in a tooling fixture system; when a first deviation between the first interface specification and the second interface specification of the base mounting seat in the tooling fixture system conforms to a preset deviation range, obtaining target parameters of the target module and the target workpiece, and loading parameters onto the target module according to the target parameters; when the target module has completed loading the target parameters, determining that the change of the target module is completed, and clamping the target workpiece; positioning the target workpiece, and fixing the target workpiece according to the target parameters.

[0006] Optionally, positioning the target workpiece includes: acquiring multiple reference coordinates, wherein the reference coordinates are used to indicate the coordinate data of sampling points on the target workpiece; performing edge detection on the target workpiece based on the multiple reference coordinates to obtain a set of edge coordinates corresponding to the target workpiece; fitting the set of edge coordinates according to the shape of the target workpiece to obtain the current reference coordinates of the target workpiece; and controlling the movement and positioning of the target workpiece based on the deviation between the current reference coordinates and the target coordinates.

[0007] Optionally, edge detection is performed on the target workpiece based on multiple reference coordinates to obtain a set of edge coordinates corresponding to the target workpiece, including: smoothing the multiple reference coordinates to obtain multiple first reference coordinates; calculating the gradient intensity of the multiple first reference coordinates, and determining the first reference coordinates corresponding to gradient intensities greater than a first preset threshold as edge coordinates and placing them into the set of edge coordinates; determining the first reference coordinates whose gradient intensity is less than the first preset threshold but greater than a second preset threshold as second reference coordinates, and if the second reference coordinates are connected to the edge coordinates, determining the second reference coordinates as edge coordinates and placing them into the set of edge coordinates.

[0008] Optionally, fitting the edge coordinate set according to the shape of the target workpiece to obtain the current reference coordinates of the target workpiece includes: if the shape of the target workpiece is a first shape, obtaining the first dimension of the target workpiece; calculating the first distance between the edge coordinates and the preset reference coordinates, and calculating the first error between the first distance and the first dimension; adding the first errors corresponding to each of the multiple edge coordinates in the edge coordinate set, and determining the preset reference coordinate as the current reference coordinate when the first error value is the smallest; if the shape of the target workpiece is a second shape, determining the maximum abscissa value as a first reference value, the minimum abscissa value as a second reference value, the maximum ordinate value as a third reference value, and the minimum ordinate value as a fourth reference value among the multiple edge coordinates in the edge coordinate set; determining the average of the first reference value and the second reference value as the abscissa value of the current reference coordinate, and determining the average of the third reference value and the fourth reference value as the ordinate value of the current reference coordinate.

[0009] Optionally, controlling the movement and positioning of the target workpiece based on the deviation between the current reference coordinates and the target coordinates includes: after moving the target workpiece, calculating the reference deviation between the current reference coordinates and the target coordinates; determining that the positioning of the target workpiece is complete when the reference deviation is continuously less than a first preset deviation value for a preset number of times; and sending a first instruction when the reference deviation is continuously greater than a second preset deviation value for a warning number of times, wherein the first instruction is used to instruct the tooling fixture to be repaired.

[0010] Optionally, determining the first interface specification corresponding to the target module through the module identifier includes: searching in the module database for the first interface specification matching the module identifier and the module type of the target module, wherein the first interface specification is used to indicate the matching size and locking method of the target module; if the first deviation between the first interface specification and the second interface specification of the base mounting seat in the tooling fixture system conforms to a preset deviation range, obtaining the target parameters of the target module and the target workpiece includes: searching in the fixture database for the second interface specification of the base mounting seat, wherein the second interface specification is used to indicate the matching size of the base mounting seat; comparing the size, position, shape, and interface type of the locating pin hole and the locating pin of the target module and the base mounting seat to determine the first deviation.

[0011] Optionally, before identifying the module identifier of the target module, the process includes: obtaining maintenance data matching the tooling fixture and the target module from a maintenance database, wherein the maintenance data is used to indicate the failure time, failure type, and repair time; determining the continuous operating time and reliability of the tooling fixture and the target module, wherein the reliability is used to indicate the time during which the tooling fixture and the target module will not fail; determining the maintenance cycle of the tooling fixture and the target module based on the maintenance data, continuous operating time, and reliability; and sending a second instruction if the maintenance conditions are met during the current time and maintenance cycle, wherein the second instruction is used to indicate that the tooling fixture and the target module require maintenance.

[0012] This application also provides a tooling fixture changeover device, comprising: a first identification module for identifying a module identifier of a target module and determining a first interface specification corresponding to the target module through the module identifier, wherein the target module is used to clamp a workpiece in the tooling fixture system; a first acquisition module for acquiring target parameters of the target module and the target workpiece when a first deviation between the first interface specification and the second interface specification of the base mounting seat in the tooling fixture system conforms to a preset deviation range, and loading parameters onto the target module according to the target parameters; a first loading module for determining that the changeover of the target module is complete when the target module has completed loading the target parameters, and clamping the target workpiece; and a workpiece fixing module for positioning the target workpiece and fixing the target workpiece according to the target parameters.

[0013] This application also provides an electronic device, including: a memory for storing a computer program; and a processor for executing the computer program to implement the steps of the tooling fixture transformation method described above.

[0014] This application also provides a computer-readable storage medium storing a computer program, wherein when the computer program is executed by a processor, it implements the steps of any of the above-described tooling fixture transformation methods.

[0015] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of any of the above-described tooling fixture transformation methods.

[0016] This application identifies the module identifier of the target module and determines the corresponding first interface specification of the target module based on the module identifier. The target module is used to clamp a workpiece in a tooling fixture system. If the first deviation between the first interface specification and the second interface specification of the base mounting in the tooling fixture system conforms to a preset deviation range, target parameters for the target module and the target workpiece are obtained, and parameters are loaded onto the target module according to these parameters. Once the target module has completed loading the target parameters, the module's transformation is considered complete, and the target workpiece is clamped. The target workpiece is positioned and fixed according to the target parameters. The first interface specification of the target module is compared with the second interface specification of the base mounting in the tooling fixture system, and the first deviation between them is calculated. Only when this deviation is within a preset allowable range is the system determined that the module is compatible with the fixture, allowing subsequent parameter loading and locking control. This verification mechanism ensures precise docking between the module and the base mounting, avoiding clamping failures or equipment damage caused by interface mismatch. Once the module is confirmed to be compatible with the system, the software system will automatically acquire the target parameters (such as clamping force threshold and positioning reference coordinates) of the target module and the target workpiece, and automatically load parameters onto the target module based on these parameters. This eliminates the uncertainty of manual settings and improves the standardization and reliability of the clamping process. By automatically configuring parameters, changeover efficiency is improved while ensuring safety and reliability, thereby solving the problem of low production efficiency for multiple product varieties in related production scenarios. Attached Figure Description

[0017] To more clearly illustrate the embodiments of this application, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 This is a flowchart of an optional tooling fixture change method according to an embodiment of this application;

[0019] Figure 2 This is a schematic diagram of an optional workpiece positioning process according to an embodiment of this application;

[0020] Figure 3 This is a schematic diagram of an optional tooling fixture replacement method according to an embodiment of this application;

[0021] Figure 4This is a structural block diagram of an optional tooling fixture changing device according to an embodiment of this application. Detailed Implementation

[0022] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the protection scope of this application.

[0023] It should be noted that, in the description of this application, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. The terms "first," "second," etc., in this application are used to distinguish similar objects and are not used to describe a specific order or sequence.

[0024] To enable those skilled in the art to better understand the present application, the present application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0025] The embodiments of this application provide a method for changing tooling fixtures. Figure 1 This is a flowchart of an optional tooling fixture changeover method according to an embodiment of this application; as follows: Figure 1 As shown, the tooling fixture changeover method includes:

[0026] Step S102: Identify the module identifier of the target module and determine the first interface specification corresponding to the target module through the module identifier, wherein the target module is used to clamp the workpiece in the tooling fixture system;

[0027] It should be noted that the target module refers to the specific module that needs to be identified and used in the tooling and fixture system. These modules can be specialized fixtures for different machining processes (such as milling, welding, etc.), each with a unique design to adapt to specific types of workpieces or machining requirements. Module identification typically refers to RFID (Radio Frequency Identification) tags, barcodes, QR codes, or other encoding methods used to uniquely identify the target module. This helps the software system quickly identify the module's identity and specifications, forming the basis for modular quick-change and automated management. The first interface specification refers to the physical specifications and standards that the target module must follow when connecting to the base mounting base in the tooling and fixture system, including but not limited to the location, size, and shape of the mounting holes, as well as the type and specifications of electrical and pneumatic interfaces. Accurate identification of the first interface specification is crucial to ensuring a correct and safe connection between the module and the base mounting base.

[0028] In an optional implementation, the tooling fixture software system first reads the module identifier on the target module using an automatic identification device (such as an RFID reader). This identifier contains information such as the module type and number. The software system then uses the read module identifier to search the database for a matching first interface specification, i.e., the physical specification required for the target module to connect to the base mounting. This process emphasizes the importance of the module identifier, which acts as a bridge between the software and hardware, enabling the software system to quickly and accurately identify different modules and obtain their detailed specifications, laying the foundation for subsequent compatibility checks, parameter loading, and other steps. Simultaneously, the identification of the target module and the determination of the first interface specification ensure that the module can be correctly and safely installed on the base mounting, providing the necessary conditions for workpiece clamping and subsequent processing. This is crucial for realizing the modular quick-change function of the tooling fixture system and is fundamental to improving production efficiency and reducing human error.

[0029] In an optional implementation, an RFID reader is installed on the base mounting of the tooling fixture system. This reader automatically reads the RFID tags on the target modules placed on it, each tag containing the module's unique identification information. When the target module is placed on the base mounting, the RFID reader immediately reads its RFID tag, and the software system parses the tag information to extract the module identifier. The software system retrieves a first interface specification matching the module identifier from a database. This database stores detailed information about all modules, including their identifier, type, and first interface specification. The system parses the database query results to determine the first interface specification of the target module, preparing for the next step of compatibility verification.

[0030] Step S104: If the first deviation between the first interface specification and the second interface specification of the base mounting seat in the tooling fixture system meets the preset deviation range, obtain the target parameters of the target module and the target workpiece, and load the parameters of the target module according to the target parameters.

[0031] It should be noted that the second interface specification refers to the standard interface specification of the base mounting seat in the tooling fixture system, such as the diameter, length, and arrangement of the locating pins. The base mounting seat is the fixed part in the tooling fixture system used to support and position different modules. The first deviation represents the difference between the first interface specification of the target module and the second interface specification of the base mounting seat. It is an important parameter for measuring the degree of matching between the module and the mounting seat. The preset deviation range is an allowable first deviation range set according to the accuracy requirements of the tooling fixture system and the feasibility of modular quick-change. Exceeding this range indicates that the module and the mounting seat are incompatible. The target parameters specifically refer to the specific parameters required during workpiece machining and clamping, such as the magnitude of the clamping force and the positioning reference coordinates. It also includes relevant parameters for module identification, loading, and locking during modular quick-change. Parameter loading refers to transmitting the target parameters stored in the software system, such as clamping force and positioning coordinates, to the control system of the target module to guide the clamping and positioning actions of subsequent modules.

[0032] In an optional implementation, the software system obtains the first interface specification of the target module by reading the RFID tag and compares it with a preset second interface specification to calculate a first deviation. If this deviation falls within a preset allowable range, it indicates that the module and the mounting base are physically compatible, and subsequent operations can proceed. The software system then retrieves parameter information of the target module and the target workpiece from the database, including clamping force settings and positioning reference coordinates. These parameters are preset based on historical data and workpiece characteristics, aiming to optimize the clamping process to meet machining accuracy and safety requirements. The software system transmits the acquired target parameters to the control system of the target module, guiding the servo motor, cylinder, and other actuators to adjust to specified states, such as setting the clamping force to a preset threshold and adjusting the slide to the positioning reference coordinates, thereby achieving automatic clamping of the module and precise positioning of the workpiece.

[0033] It should be noted that a mapping library between module identifiers and interface specifications is established in the software system to ensure that each module identifier can be quickly linked to the corresponding first interface specification data. The software system's built-in calculation module calculates the first deviation in real time and compares it with a preset deviation range. If the deviation is within the acceptable range, the system continues execution; if the deviation is too large, an alarm is triggered, prompting the operator to replace or adjust the module. The software system includes a parameter management module that can automatically retrieve and load target parameters based on the module identifier. This includes clamping force thresholds, positioning coordinates, and the module's own operating parameters. All parameters are transmitted to the control execution interface module via a standardized communication protocol (such as Modbus-RTU), which then converts them into hardware-recognizable signals, such as pulse + direction signals, to control actuators such as servo motors. During parameter loading, the software system monitors the module status in real time through sensors, such as clamping force and slide position, to ensure accurate parameter loading. If a deviation between the actual state and the target parameters is detected, the system will automatically adjust until the expected state is reached, forming a closed-loop control.

[0034] Step S106: After the target module has completed loading the target parameters, determine that the target module has completed the transformation and clamp the target workpiece.

[0035] It should be noted that when the target module completes its configuration according to the received target parameters and is correctly connected to the base mounting, the software system determines that the module's changeover operation is complete. At this point, the module is ready to clamp and process the workpiece. Specifically, after the module changeover is complete, the software system controls the module's clamping mechanism to fix the workpiece according to the preset target parameters, preparing it for the processing flow.

[0036] In an optional implementation, after receiving the target parameters, the control system of the target module performs internal configuration, such as setting the servo motor speed to achieve the specified slide movement distance and adjusting the hydraulic or pneumatic system pressure to achieve the predetermined clamping force. The software system monitors the parameter loading process of the target module. Once it is confirmed that the module has completed all necessary adjustments according to the target parameters and that the connection status between the module and the base mounting meets the requirements, the conversion is considered complete. After confirming the conversion is complete, the software system issues instructions to the target module to control the clamping mechanism to accurately clamp the target workpiece according to the target parameters.

[0037] It should be noted that the software system monitors the parameter loading progress of the target module in real time to ensure that the parameters are executed accurately. This may involve communication with the module control system to confirm that all settings have been correctly applied. Through sensors (such as position sensors and force sensors) installed on the module and tooling system, the software system collects real-time data such as module position and clamping status to determine whether the module is in the correct working position and whether the clamping force meets the target parameters. The software system employs state machine control logic to ensure that the entire process, from parameter loading to changeover completion and workpiece clamping, is orderly and controllable. Each state of the state machine, such as "parameter loading," "changeover confirmation," and "workpiece clamping," has corresponding judgment conditions and execution actions to ensure a smooth transition. To cope with possible hardware failures or parameter loading errors, the software system is designed with safety redundancy mechanisms and fault handling procedures. For example, when an abnormal clamping force is detected, operation is immediately paused and fault investigation is conducted to prevent workpiece damage or production accidents.

[0038] Step S108: Position the target workpiece and fix it according to the target parameters.

[0039] It should be noted that positioning refers to determining the precise position of the workpiece in the fixture, ensuring that the workpiece remains stable throughout the machining process and avoiding machining errors caused by positional changes. Target parameters refer to the specific parameters required to fix the target workpiece, including but not limited to positioning reference coordinates and clamping force thresholds. These parameters are preset according to the workpiece characteristics and machining requirements to guide the fixture in correctly fixing the workpiece.

[0040] In an optional example, suppose a complex curved surface part needs to be machined on an automobile manufacturing assembly line. The following is an example of the entire process of replacing the target module with a fixture module suitable for machining curved surfaces, and then positioning and securing the target workpiece:

[0041] Step S102: Module Identification and Specification Confirmation:

[0042] By using RFID to read the tag on the target module, the software system identified it as a module specifically designed for clamping curved parts. The system then queried the database and determined that the module's first interface specification was ISO 9409-1, suitable for high-speed changeovers.

[0043] Step S104: Compatibility verification and parameter acquisition:

[0044] The software system automatically compares the first interface specifications of the target module with the second interface specifications of the base mounting, confirming that the first deviation (0.003mm) between the two is within the preset allowable range (±0.02mm), and that the module and mounting are compatible. The system loads the parameters of the target module and the curved workpiece, including setting the clamping force threshold to 250N and the positioning coordinates to (100.000mm, 200.000mm).

[0045] Step S106: Automatic module switching and loading:

[0046] The software system schedules a modular quick-change management module, automatically unloading the old module and installing the target module. After the target module is installed correctly and the parameters are automatically loaded into the module control system, it is ready for workpiece positioning and clamping.

[0047] Step S108: Workpiece positioning and fixing:

[0048] When the curved workpiece is placed on the target module, the system activates an adaptive positioning algorithm, acquiring coordinate data of the workpiece surface via a laser displacement sensor. After data preprocessing, the Canny edge detection algorithm is used to extract the workpiece's outer contour, the least squares method is used to calculate the reference point, and a PID algorithm dynamically adjusts the slide and clamping mechanism. Finally, the workpiece is precisely positioned (100.000mm, 200.000mm) with an error of less than ±0.01mm, and firmly fixed under a clamping force of 250N, ready for subsequent processing.

[0049] This application identifies the module identifier of the target module and determines the corresponding first interface specification of the target module based on the module identifier. The target module is used to clamp a workpiece in a tooling fixture system. If the first deviation between the first interface specification and the second interface specification of the base mounting in the tooling fixture system conforms to a preset deviation range, target parameters for the target module and the target workpiece are obtained, and parameters are loaded onto the target module according to these parameters. Once the target module has completed loading the target parameters, the module's transformation is considered complete, and the target workpiece is clamped. The target workpiece is positioned and fixed according to the target parameters. The first interface specification of the target module is compared with the second interface specification of the base mounting in the tooling fixture system, and the first deviation between them is calculated. Only when this deviation is within a preset allowable range is the system determined that the module is compatible with the fixture, allowing subsequent parameter loading and locking control. This verification mechanism ensures precise docking between the module and the base mounting, avoiding clamping failures or equipment damage caused by interface mismatch. Once the module is confirmed to be compatible with the system, the software system will automatically acquire the target parameters (such as clamping force threshold and positioning reference coordinates) of the target module and the target workpiece, and automatically load parameters onto the target module based on these parameters. This eliminates the uncertainty of manual settings and improves the standardization and reliability of the clamping process. By automatically configuring parameters, changeover efficiency is improved while ensuring safety and reliability, thereby solving the problem of low production efficiency for multiple product varieties in related production scenarios.

[0050] In an optional implementation, positioning the target workpiece includes: acquiring multiple reference coordinates, wherein the reference coordinates are used to indicate the coordinate data of sampling points on the target workpiece; performing edge detection on the target workpiece based on the multiple reference coordinates to obtain a set of edge coordinates corresponding to the target workpiece; fitting the set of edge coordinates according to the shape of the target workpiece to obtain the current reference coordinates of the target workpiece; and controlling the movement and positioning of the target workpiece based on the deviation between the current reference coordinates and the target coordinates.

[0051] It should be noted that reference coordinates are coordinate data collected by sensors during the positioning process to describe specific sampling points on the surface of the target workpiece. These coordinate points are typically sampling points on the outer contour of the workpiece, used for subsequent edge detection and reference coordinate calculation. The edge coordinate set is the coordinate information of all edge points collected by the software system after edge detection; this information is used for subsequent reference coordinate fitting. The current reference coordinates can be the coordinates of the actual positioning point of the workpiece calculated based on the edge coordinate set using a fitting algorithm (such as the least squares method). This is the basis used by the software system to guide workpiece movement and positioning. Deviation refers to the distance difference between the current reference coordinates and the preset target coordinates, used to measure the degree of deviation between the actual position and the ideal position of the workpiece. The target coordinates are the preset ideal positioning point coordinates of the workpiece, which are predefined according to the workpiece's machining requirements and the working reference of the fixture, used to guide the precise movement and positioning of the workpiece.

[0052] In an optional implementation, a dynamically updated window is used, with a window size set to 5-10 sampling points. When new data points arrive, the algorithm calculates the average of all points within the window as the output, effectively removing random fluctuations and short-term anomalies, ensuring the stability of the positioning data. In addition to noise filtering, the system performs two critical checks on the data: ensuring that the laser displacement sensor readings are within a reasonable range, i.e., between 0-100mm. If the sensor readings exceed this range, the data is considered invalid, and the system ignores the value or triggers resampling to prevent erroneous data from affecting positioning accuracy. The system also checks whether the deviation between adjacent sampling points is less than or equal to 0.02mm to avoid abrupt, abnormal readings. If the deviation between sampling points exceeds a set threshold, the system considers the data abnormal and takes appropriate measures, such as resampling or issuing an alarm, to ensure data consistency and positioning accuracy.

[0053] The laser displacement sensor collects not only planar positioning information but also height data of the workpiece surface. Therefore, the transmitted data includes the three-dimensional coordinates (x_i, y_i, z_i) of each sampling point. Here, x_i and y_i are coordinate values ​​in the planar positioning dimension, used to calculate the workpiece's positioning reference in the XY plane. z_i is the coordinate value in the height dimension, which is not currently directly involved in the positioning reference calculation but can be used for subsequent workpiece height adjustment or other applications.

[0054] The data sampling frequency is set to 100Hz, meaning the sensor captures the workpiece surface coordinates 100 times per second. This high sampling frequency ensures real-time data, enabling the system to respond quickly to changes in workpiece position, and also facilitates more effective noise removal through sliding window filtering. The high sampling frequency is particularly important for capturing fast-moving workpieces or maintaining positioning accuracy in vibrating environments, as it provides sufficiently dense time-series data for accurate analysis and positioning.

[0055] In an optional implementation, high-precision sensors such as laser displacement sensors are used to collect coordinate data from multiple sampling points on the workpiece surface. This data is used for subsequent edge detection and reference coordinate calculation, ensuring the accuracy of workpiece positioning. An edge detection algorithm is used to process the reference coordinate data, identify and extract workpiece edge information, forming an edge coordinate set. Noise is removed using Gaussian filtering, and strong edge pixels are extracted and linked using a dual-threshold method, ensuring the stability and accuracy of edge detection. Based on the workpiece's preset shape information (e.g., circular, rectangular), the edge coordinate set is fitted using the least squares method. For circular workpieces, the center coordinates are calculated as the reference coordinates; for rectangular workpieces, the center of the rectangle is calculated as the reference coordinates. This step ensures the accuracy of workpiece positioning, with an error not exceeding ±0.005mm. The software system calculates the deviation between the current reference coordinates and the target coordinates, then activates a PID control algorithm to dynamically adjust the control parameters of the servo motor based on the deviation, driving the X / Y axis slide to move the workpiece to the target position. The entire process provides real-time feedback on the workpiece position until the deviation converges to within ±0.01mm, achieving precise workpiece positioning.

[0056] The above-described embodiments of this application effectively achieve high-precision positioning of the target workpiece, ensuring the stability of the processing process and the quality of the workpiece. They also provide data support for subsequent equipment maintenance and workpiece processing parameter optimization, making them an important technical means for modern manufacturing to improve production efficiency and reduce defect rates.

[0057] In an optional implementation, edge detection of the target workpiece is performed based on multiple reference coordinates to obtain a set of edge coordinates corresponding to the target workpiece. This includes: smoothing the multiple reference coordinates to obtain multiple first reference coordinates; calculating the gradient intensity of the multiple first reference coordinates, and determining the first reference coordinates corresponding to gradient intensities greater than a first preset threshold as edge coordinates and placing them into the set of edge coordinates; determining the first reference coordinates whose gradient intensities are less than the first preset threshold and greater than a second preset threshold as second reference coordinates, and if the second reference coordinates are connected to the edge coordinates, determining the second reference coordinates as edge coordinates and placing them into the set of edge coordinates.

[0058] It should be noted that the first reference coordinates refer to the coordinate data after Gaussian filtering and smoothing, used to reduce noise and ensure more accurate edge detection. In image processing, gradient intensity reflects the rate of gray-level change of a coordinate point on the workpiece surface and is a key indicator for edge detection. Points with large gradient intensities are more likely to be located at workpiece edges. The first preset threshold is used to distinguish between high and low intensity thresholds for strong edge points; points with gradient intensities exceeding this threshold are considered strong edge points and are directly retained. The second preset threshold is used to filter weak edge points; points with gradient intensities between this threshold and the first preset threshold are only retained if they are connected to strong edge points, avoiding interference from isolated noise points.

[0059] In an optional implementation, the software system smooths the original coordinate data using Gaussian filtering, setting the Gaussian kernel standard deviation σ=1.2 to balance noise reduction and edge sharpness, thus obtaining the first reference coordinates. The Sobel operator is applied to the first reference coordinates to calculate the gradient strength and direction of each point, initially filtering out potential edge points. A high threshold (e.g., 80) and a low threshold (e.g., 40) are set to classify and filter the calculated gradient strengths. Points with gradient strengths greater than the high threshold are directly identified as strong edge points; points with gradient strengths less than the high threshold but greater than the low threshold are considered weak edge points and retained if they are connected to strong edge points after connectivity checks, thus preventing isolated noise points from being misidentified as valid edges. All determined edge coordinates (including strong edge points and eligible weak edge points) are collected into an edge coordinate set, providing a precise data foundation for subsequent baseline coordinate calculations.

[0060] In an optional example, assuming an irregular curved surface workpiece needs to be machined, the following are the specific implementation steps of the edge detection algorithm: A laser displacement sensor acquires workpiece surface coordinate data at a frequency of 100Hz. The software system smooths this raw data using a Gaussian filter (σ=1.2) to obtain the first reference coordinates. The Sobel operator is applied to process the first reference coordinates to calculate the gradient intensity of each point. For example, the gradient intensity of a point on the workpiece surface might be 85, indicating that it is located in the edge region of the workpiece. A high threshold is set to 80, and a low threshold to 40. Points with a gradient intensity of 85 (greater than the high threshold) are directly identified as edge coordinates and added to the edge coordinate set. For points with a gradient intensity of 45 (between the low and high thresholds), their connectivity with surrounding points is checked. If it is connected to a point with a gradient intensity of 85, it is also determined to be an edge coordinate, thus avoiding misjudgment of isolated noise points and ensuring the accuracy of edge recognition. Through the above processing, the software system collects all points identified as edge coordinates and constructs an edge coordinate set. For irregular curved workpieces, this set will accurately depict the workpiece outline with an edge recognition accuracy of over 99%, providing reliable data support for subsequent reference coordinate calculations.

[0061] The above-described embodiments of this application effectively realize high-precision edge detection of complex-shaped workpieces, providing crucial information for precise workpiece positioning and automated processing, and are an important means to improve production quality and efficiency.

[0062] In an optional implementation, fitting the edge coordinate set according to the shape of the target workpiece to obtain the current reference coordinates of the target workpiece includes: when the shape of the target workpiece is a first shape, obtaining the first dimension of the target workpiece; calculating the first distance between the edge coordinates and the preset reference coordinates, and calculating the first error between the first distance and the first dimension; adding the first errors corresponding to each of the multiple edge coordinates in the edge coordinate set, and determining the preset reference coordinate as the current reference coordinate when the first error value is the smallest; when the shape of the target workpiece is a second shape, determining the maximum abscissa value as a first reference value, the minimum abscissa value as a second reference value, the maximum ordinate value as a third reference value, and the minimum ordinate value as a fourth reference value among the multiple edge coordinates in the edge coordinate set; determining the average of the first reference value and the second reference value as the abscissa value of the current reference coordinate, and determining the average of the third reference value and the fourth reference value as the ordinate value of the current reference coordinate.

[0063] It should be noted that the first shape and second shape represent the preset workpiece shape categories in the software system, such as circle and rectangle. These shape categories are classified based on the geometric features of the workpiece and are used to guide the selection of subsequent fitting algorithms. The first dimension refers to the radius of the circular workpiece, which is one of the key parameters required when executing the circle fitting model. The first distance refers to the distance between the edge coordinate point and the preset reference coordinates, which is the basis for calculating the first error.

[0064] In an optional implementation, the software system reads the workpiece shape parameters from the human-computer interaction module and selects the appropriate fitting model based on whether the workpiece is circular or rectangular.

[0065] Circular workpiece fitting: Obtain the preset first dimension (i.e., radius). For each coordinate point (x_) in the edge coordinate set. edge y_ edge The distance between the edge coordinates and the preset reference coordinates is calculated, and then the first error is calculated. The first error values ​​corresponding to all edge coordinates are added together, and the center coordinates (x0, y0) that minimize the total error are solved by the least squares method. The center coordinates are the current reference coordinates of the circular workpiece, ensuring that the fitting error does not exceed ±0.005mm.

[0066] In an optional implementation, an error function E=Σ[(x_ edge -x0)²+(y_ edge -y0)²-r²]², which quantizes the actual edge point (x_ edge y_edge The goal is to find a center point (x0, y0) that minimizes the sum of squared distances from all points to the fitted model (i.e., a circle or rectangle centered at (x0, y0)). Let the set of points after workpiece edge detection be {(x1, y1), (x2, y2), ..., (xn, yn)}. The objective is to find a center point (x0, y0) such that the sum of squared distances from all points to the center is minimized. In other words, to find the minimum of the error function E, we need to take the partial derivatives of E with respect to the unknown variables x0 and y0 and set them to zero. This is because the derivative of any function at its extreme points is zero; here we are looking for the global minimum. For a circular workpiece, the objective is to minimize E(x0, y0, r). Therefore, we need to take the partial derivatives of x0, y0, and r respectively and set them to zero to form three equations. We then combine these partial derivative equations to form a system of linear equations with respect to x0 and y0. Solving this system of equations yields the center coordinates (x0, y0) that minimize the error function E.

[0067] Rectangular workpiece fitting: Determine the first to fourth reference values ​​in the edge coordinate set, which represent the four boundaries of the rectangular workpiece. Calculate the mean of the first and second reference values ​​as the x-coordinate value, and the mean of the third and fourth reference values ​​as the y-coordinate value, finally obtaining the current reference coordinates of the rectangular workpiece, i.e., the center point of the rectangle, i.e., the reference coordinates (x0, y0) = ((a+b) / 2, (c+d) / 2).

[0068] In an optional implementation, the system obtains the coordinates of a series of edge points through the edge detection algorithm in the previous step. These points are distributed on the four sides of the rectangular workpiece, but may contain some extreme values ​​due to noise or anomalies. To determine the approximate range of the edge points, the maximum and minimum values ​​in the x and y directions are calculated. These values ​​initially define the boundary of the rectangle. Although an approximate boundary can be given, outliers (extreme values) that may exist in the edge points can seriously affect the calculation of the reference points. Therefore, the values ​​of a, b, c, and d need to be further corrected using the least squares method to eliminate the influence of these outliers. Substituting all edge points into the equations x=a, x=b, y=c, y=d of the rectangle, an error function E is constructed. The error function E quantifies the sum of squares of the deviations of the point set from the rectangle with (a, b, c, d) as its boundary. The partial derivatives of the error function E with respect to a, b, c, and d are calculated and set to 0. The resulting system of equations can be corrected by solving for the mean value. Specifically, for edge points in the x-direction, points that deviate excessively from a and b are removed, and the average x-coordinate of the remaining points is calculated as the average of the corrected a and b. For edge points in the y-direction, points that deviate excessively from c and d are removed, and the average y-coordinate of the remaining points is calculated as the average of the corrected c and d.

[0069] The software system outputs the calculated current reference coordinates to guide subsequent operations such as workpiece positioning and slide adjustment, ensuring that the workpiece is accurately positioned at the preset processing position.

[0070] The above-described embodiments of this application effectively achieve precise calculation of the reference coordinates of circular workpieces, ensuring accurate workpiece positioning and machining precision. For rectangular workpieces, the center of the rectangle is calculated based on the maximum and minimum coordinate values ​​in the edge coordinate set, serving as the reference coordinates. This process also ensures high positioning accuracy and efficiency. These technical implementation methods are key links in achieving automated and intelligent processing in modern manufacturing, providing a solid technical foundation for improving production quality and efficiency.

[0071] It should be noted that, based on the deviation between the current reference coordinates and the target coordinates, the movement and positioning of the target workpiece can be controlled using a PID algorithm. The PID adjustment algorithm is a closed-loop control algorithm that automatically adjusts the system output through a combination of proportional (P), integral (I), and derivative (D) control terms to eliminate deviations and achieve stable control. Positioning deviation refers to the difference between the actual position of the workpiece and the preset target position, represented by Δx and Δy, corresponding to the deviations along the x-axis and y-axis, respectively. Slide adjustment amount refers to the value calculated by the software system used to adjust the slide position to eliminate positioning deviations. The adjustment amount is usually measured in millimeters (mm) and reflects the distance and direction the slide needs to move. A servo motor is an electric motor capable of precisely controlling position, speed, and torque, widely used in automated equipment such as robots and machine tools for precision motion control. Pulse + direction signal is a common control signal form for servo motors; the number of pulses determines the motor's movement distance, and the direction signal determines the direction of movement (forward or reverse). Sampling frequency refers to the frequency at which the sensor collects data, the number of samples collected per unit time, which is crucial for real-time control and feedback. The sampling frequency is 100Hz, which ensures the real-time nature of the data and the accuracy of the control.

[0072] In an optional implementation, the software system reads preset PID coefficients, namely, proportional coefficient Kp=0.8, integral coefficient Ki=0.1, and derivative coefficient Kd=0.05. These coefficients correspond to the three functions of PID control: Kp is used for rapid response to positioning deviations, Ki is used to eliminate static deviations during the positioning process, and Kd is used to suppress overshoot during the adjustment process, ensuring that the slide movement is both rapid and smooth. Based on the workpiece position fed back by the sensor in real time, the positioning deviations Δx and Δy between the workpiece and the preset target position are calculated. The software system substitutes the deviation values ​​into the PID formula for calculation, obtaining the adjustment amounts u(x) and u(y) of the slide in the x-axis and y-axis directions, in millimeters. The software system converts the calculated adjustment amounts into control signals that the servo motor can understand, namely, "pulse + direction" signals. Signals are sent to the servo motor through the control execution interface module to drive the X / Y axis slide to move a specific distance, thereby correcting the deviation. After the slide table moves, the laser displacement sensor immediately re-acquires position data at a sampling frequency of 100Hz. The software system recalculates the deviation based on the new data, repeating the PID calculation and slide table adjustment process until the positioning deviation stabilizes within ±0.01mm. During the slide table position adjustment process, the software system monitors the adjustment amount and adjustment time to ensure that the overshoot is less than 5%, avoiding excessive slide table movement that could generate new deviations. Simultaneously, the adjustment time is controlled within 0.5 seconds to ensure positioning efficiency while achieving precise slide table positioning.

[0073] In an optional implementation, for the positioning deviation Δ(t), the software system continuously calculates u(t) and adjusts the slide position in real time. Δ(τ) in the formula represents the historical deviation value, calculated through the integral term Ki× Δ(τ)dτ calculates the cumulative deviation, while dΔ(t) / dt represents the rate of change of deviation, used in the differential term Kd×dΔ(t) / dt to suppress overshoot. The software system converts the calculated adjustment amounts Δx' and Δy' into control signals for the servo motor. Each pulse represents a movement of 0.001mm, and the direction signal indicates forward or reverse movement, ensuring that the slide table executes the adjustment commands accurately. The software system constructs a closed-loop control logic, which continuously approaches the target position through a cycle of real-time deviation feedback, PID calculation, slide table adjustment, and further deviation measurement until the deviation meets the accuracy requirements.

[0074] Figure 2 This is a schematic diagram of an optional workpiece positioning process according to an embodiment of this application; as shown. Figure 2 As shown, the laser displacement sensor collects the surface coordinate data of the workpiece, which serves as the initial input to the algorithm. Step 1 performs edge detection and outputs a set of edge coordinates; Step 2 performs benchmark fitting and outputs the current benchmark coordinates; Step 3 calculates the positioning deviation and outputs the positioning deviation; Step 4 executes the PID adjustment algorithm; and Step 5 performs precision verification.

[0075] In step 1, the workpiece surface coordinate data is first smoothed using a Gaussian filter to remove high-frequency noise. The Sobel operator is then used to calculate the gradient of the smoothed data, obtaining the gradient intensity at each point. High and low thresholds are set to filter the gradient intensities, retaining strong edge points and some weak edge points connected to them. The thresholded edge points are then connected to form a continuous edge contour, and edge refinement is achieved using techniques such as non-maximum suppression. Finally, the edge image of the workpiece is output, providing clear contour information for subsequent positioning reference calculations.

[0076] In step 2, the coordinates (x_) of the edge points are read from the edge image output by the edge detection. edge y_ edge For a circular workpiece, the equation (x-x0)²+(y-y0)²=r² is set; for a rectangular workpiece, the equations x=a, x=b, y=c, y=d are set, where (x0, y0) is the center of the circular workpiece, and (a, b, c, d) are the coordinates of the four sides of the rectangular workpiece. Based on the model, an error function E is constructed, representing the sum of squared deviations between the model's predicted values ​​and the actual data points. The partial derivatives of the error function E with respect to x0 and y0 (or a, b, c, d) are calculated and set to 0 to solve for the optimal positioning reference parameters. The actual positioning reference coordinates (x0, y0) or center point coordinates of the circular or rectangular workpiece are obtained, preparing for the next step of PID adjustment.

[0077] In step 3, the reference coordinates output by the least squares method are read and compared with the preset target reference coordinates to calculate the deviations Δx and Δy.

[0078] In step 4, based on the deviations Δx and Δy, the output control quantity u(t) is calculated using a PID algorithm. This control quantity u(t) is converted into a control signal for the servo motor, adjusting the position of the slide table until the deviation is controlled within the allowable range. Position information during the adjustment process is returned to the system in real time, forming a closed-loop control to ensure positioning accuracy and the stability of the adjustment process.

[0079] In step 5, a precise verification is performed. When the positioning deviations Δx and Δy are less than ±0.01mm three times consecutively, the positioning process ends, a positioning qualified signal is output, and preparation is made to enter the clamping control stage.

[0080] In an optional implementation, controlling the movement and positioning of the target workpiece based on the deviation between the current reference coordinates and the target coordinates includes: after moving the target workpiece, calculating the reference deviation between the current reference coordinates and the target coordinates of the target workpiece; determining that the positioning of the target workpiece is completed when the reference deviation is continuously less than a first preset deviation value for a preset number of times; and sending a first instruction when the reference deviation is continuously greater than a second preset deviation value for a warning number of times, wherein the first instruction is used to instruct the tooling fixture to be repaired.

[0081] It should be noted that the reference deviation refers to the deviation between the actual reference coordinates and the target coordinates of the workpiece after movement and positioning attempts. It is a key indicator for evaluating whether the workpiece has been correctly positioned to the required processing location. The first preset deviation value can be the maximum allowable deviation threshold during the workpiece positioning process, used to determine whether the workpiece positioning is complete. Once the reference deviation is continuously less than this value multiple times, the positioning task can be considered accomplished. The second preset deviation value can be a threshold larger than the first preset deviation value, used to monitor for significant deviations that may occur during the positioning process. Once the reference deviation continuously exceeds this value multiple times, the system will activate an early warning or maintenance mechanism. The preset number of times / warning number of times can be the number of consecutive deviation samples used by the software system to determine whether positioning is complete or to initiate a maintenance command. The preset number of times is usually smaller to confirm the immediate accuracy of positioning; the warning number of times is larger to avoid short-term fluctuations misleading the system's decision-making.

[0082] In an optional implementation, after each workpiece movement and adjustment, the software system immediately calculates the reference deviation between the workpiece's current reference coordinates and the target coordinates. This calculation is based on the latest position data to ensure real-time performance. The software system continuously monitors changes in the reference deviation. Once it detects that the deviation is less than the first preset deviation value (e.g., ±0.01mm) for N consecutive times (a preset number of times), the workpiece positioning is considered successful, and the subsequent processing flow begins. During the positioning process, if the reference deviation is greater than the second preset deviation value (e.g., ±0.1mm) for M consecutive times (a warning number of times, e.g., 5 times), this may indicate wear or other malfunctions in the tooling fixture. The software system will then initiate an emergency procedure, sending a first instruction to the control execution interface module to prompt inspection and repair of the tooling fixture to avoid potential production accidents.

[0083] In an optional example, suppose a circular workpiece needs to be positioned at a target location of (100mm, 100mm). The positioning process of the software system is as follows: The initial position of the workpiece is measured as (100.05mm, 99.95mm), and the deviations Δx = 0.05mm and Δy = -0.05mm are calculated. The software system initiates slide adjustment to move the workpiece towards the target position. After the workpiece moves, the software system calculates the new deviations Δx and Δy in real time. For example, after the first movement, the deviations decrease to Δx = 0.02mm and Δy = -0.02mm. The system continuously monitors the deviation changes, assuming the first preset deviation value is ±0.01mm and the preset number of times is 3. In the next three samplings, if the deviations Δx and Δy remain within ±0.01mm, the system determines that the positioning is complete and the workpiece can begin processing. Suppose that during the positioning process, due to some unknown factors (such as fixture wear), the deviations suddenly increase to Δx = 0.12mm and Δy = -0.13mm. At this point, if the deviation measurement exceeds the second preset deviation value (e.g., ±0.1mm) for five consecutive times, the software system determines that there is a problem with the positioning process and immediately sends the first instruction to the control execution interface module, instructing to suspend processing and arrange for inspection and necessary maintenance of the tooling fixture.

[0084] The above-described embodiments of this application not only ensure the precise positioning of the workpiece, but also effectively prevent production interruptions and quality losses that may be caused by tooling fixture failures. It is an important component for realizing automated and intelligent processing on modern production lines.

[0085] In an optional implementation, determining the first interface specification corresponding to the target module through the module identifier includes: searching the module database for the first interface specification matching the module identifier and the module type of the target module, wherein the first interface specification is used to indicate the matching size and locking method of the target module; if the first deviation between the first interface specification and the second interface specification of the base mounting seat in the tooling fixture system conforms to a preset deviation range, obtaining the target parameters of the target module and the target workpiece includes: searching the fixture database for the second interface specification of the base mounting seat, wherein the second interface specification is used to indicate the matching size of the base mounting seat; comparing the size, position, shape, and interface type of the positioning pin hole and the positioning pin of the target module and the base mounting seat to determine the first deviation.

[0086] It should be noted that the locating pin hole and locating pin are key components for achieving precise positioning between tooling fixtures and modules. The matching of their size, position and shape is crucial to the accuracy and stability of module changeover.

[0087] In an optional implementation, the software system reads the target module's identifier via RFID, then searches the module database for matching records to obtain the target module's first interface specifications (including dimensions, locking method, etc.) and module type. The software system compares the target module's first interface specifications with the base mounting's second interface specifications, calculating a first deviation between them. If the first deviation is within a preset deviation range (e.g., ±0.02mm), it indicates compatibility. The software system further compares the detailed specifications (dimensions, positions, shapes) of the locating pin holes and locating pins of the target module and the base mounting to ensure the matching of these key components, thereby guaranteeing the accuracy of module changeover. After confirming the compatibility between the module and the mounting, the software system, based on the target module's type, searches the fixture database and loads preset target parameters for the target workpiece, such as clamping force and positioning coordinates, to prepare for subsequent workpiece clamping and processing.

[0088] In an optional implementation, each tooling module is equipped with an RFID tag storing a unique identifier (ID) and some basic attributes, such as module type. When a module is placed within the coverage area of ​​an RFID reader, the reader sends a radio frequency signal to activate the tag. The tag then transmits the ID and other stored information back to the reader. This process is typically very fast, with an identification response time of no more than 0.3 seconds. Upon receiving the module ID, the RFID reader first parses the ID to ensure data integrity and accuracy. The ID is usually a combination of numbers or letters used to uniquely identify a module. This parsing process may include data verification and error correction to ensure that the module ID can be accurately read and understood even in complex production environments. After parsing the module ID, the system immediately queries the "Module Ledger" in the local database, a table specifically used to store tooling module information. The purpose of the query is to find the detailed information corresponding to this module based on the ID, including but not limited to:

[0089] Module type: such as milling module, welding module, etc. This is crucial for subsequent model changeover operations, because different module types may correspond to different working parameters and interface specifications.

[0090] Interface specifications: These include T-slot dimensions, locking methods, and other information. This information helps the system determine the compatibility between the module and the base mounting, ensuring that the module can be installed correctly.

[0091] Maintenance history: Although not the primary query item in this step, checking a module's maintenance history can help determine the module's status and avoid using potentially problematic modules in some cases.

[0092] After a successful database query, the system will obtain the corresponding module type and interface specification information. This information is then passed to subsequent logical processing units for module compatibility verification and type conversion scheduling.

[0093] In optional implementations, the interface specifications of the base mounting base must also conform to certain industry standards, such as ISO 9409-1. This standard defines a series of dimensional parameters to ensure that tooling fixtures of different brands and types can be installed compatiblely on the same base. These standard parameters are predefined in the software system for reference during the verification process. Next, the algorithm compares the module interface specifications with the interface specifications of the base mounting base item by item, especially the two key parameters: T-slot dimensions and locking method. The core of the comparison is to detect whether the dimensional differences between the two are within the allowable tolerance range, i.e., a deviation limit of no more than 0.02mm. The selection of this tolerance range takes into account factors such as dimensional variations, wear, and minor assembly errors during the manufacturing process. If any specification parameter deviation is found to exceed the 0.02mm limit during the comparison process, the system will immediately trigger an "incompatibility alarm." This alarm mechanism notifies the on-site operators through visual or audible signals to prevent the module from being installed incorrectly. The timeliness of the alarm helps to avoid potential production interruptions or equipment damage, ensuring the safety and continuity of production. The design of the compatibility verification algorithm follows strict logical and mathematical comparison principles to ensure that the accuracy of the judgment results can reach 100%. This means that as long as the module specifications and mounting bracket specifications are entered accurately, the algorithm can correctly determine whether the two are compatible, without any false alarms or omissions.

[0094] In optional implementations, state machine scheduling logic is one of the core mechanisms for automating modular quick-change tooling fixtures. By defining a set of ordered states and triggering transitions between states based on sensor signals, it ensures the automated execution of the changeover process without manual intervention, improving changeover efficiency and accuracy. A state machine is a mathematical model of finite states used to describe the behavior patterns of an entity under different inputs. In modular quick-change applications, state machine logic is used to manage and control the changeover process of tooling fixture modules, ensuring correct execution and efficient transitions at each stage from module identification to final changeover completion. State List:

[0095] Module awaiting identification: This is the initial state of the replacement process. When a module needs to be replaced, the system is in a waiting state for the new module to be placed. At this time, the RFID reader begins scanning the module ID.

[0096] Successful identification: Once the RFID reader reads the module ID, the system will enter the "successful identification" state, and the module ledger will be queried to obtain information such as module type and interface specifications.

[0097] Compatibility Check: Upon successful identification, the system immediately performs a compatibility check, comparing the module's interface specifications with the specifications of the base mounting bracket. If the check passes, the system proceeds to the next step; if it fails, an "incompatibility alarm" is triggered, and the system remains in that state until the problem is resolved.

[0098] Parameter Loading: After passing compatibility verification, the system automatically loads preset operating parameters according to the module type, such as a clamping force of 300N for the milling module and 200N for the welding module. After parameter loading is complete, the system enters the next state.

[0099] Locking control: After the parameters are loaded, the system begins to control the slide or clamping mechanism to fix the new module in the preset position. During the locking process, Hall sensors monitor whether the module is in place. Once the module is confirmed to be locked, the system will proceed to the next state.

[0100] Changeover complete: The module is locked in place, and the Hall sensor sends a position signal to the control system, confirming the completion of the "locking control" state. The system then announces the end of the changeover process and enters normal production or standby mode, awaiting the next changeover instruction or workpiece placement.

[0101] Each state transition of the state machine is automatically triggered by sensor signals (such as the position signal from a Hall sensor or the module ID signal read by RFID). This ensures that the system can react to real-time changes in the physical environment without manual intervention, enhancing the level of automation. The automation characteristic of the state machine scheduling logic is reflected in the fact that the entire changeover process can be completed without manual intervention. From the placement of the module to the completion of the changeover, the entire process is automatically executed driven by sensor signals. The state machine ensures the correct sequence and execution of all necessary steps, thereby achieving 100% automation.

[0102] The automated changeover process, implemented through state machine scheduling logic, significantly reduces changeover time from the traditional 15 minutes to less than 30 seconds, dramatically improving production line flexibility and responsiveness. Furthermore, the orderly state transitions of the state machine and the sensor signal triggering mechanism ensure the safety of the changeover process, preventing production accidents or equipment damage that could result from human error, thereby improving overall production efficiency and economic benefits. The implementation of automated processes not only reduces the workload of operators but also enhances the stability and reliability of the production line by minimizing human factors.

[0103] In an optional implementation, once the module type is determined, the system immediately retrieves the preset parameters for that module type from the "Module Ledger." These parameters include, but are not limited to, clamping force, locking method, and operating torque. Each module type has its specific optimal parameter settings to ensure that the module can immediately reach its best working state after the changeover. For example, the clamping force of the milling module is preset to 300N, while the clamping force of the welding module is set to 200N. After obtaining the preset parameters of the module, the software system quickly loads these parameters into the corresponding control execution unit. The control execution unit includes servo motors, cylinders, hydraulic cylinders, etc., which are responsible for converting parameters such as clamping force into physical actions. The parameter loading logic ensures that during the changeover process, the system automatically adjusts the clamping device to adapt to the needs of the new module without manual intervention. The loading time is strictly controlled within 0.1 seconds to reduce changeover waiting time and improve production efficiency.

[0104] Once the parameters are loaded, the system immediately verifies whether the loaded parameters have been executed correctly. This is typically done using integrated sensors (such as force sensors or position encoders), which provide real-time feedback on the clamping force and fixture position. If the parameters are executed correctly, the system proceeds to the next state (e.g., locking control). If parameter loading fails or the parameters are executed incorrectly, the system triggers an error warning, which may include reloading the parameters or halting the changeover process until the problem is resolved.

[0105] In an optional example, suppose the software system needs to identify and replace a milling module with a base mounting bracket. The specific steps are as follows: The RFID reader reads the identifier on the module, determining the module ID to be M001. The software system queries the module database and finds that the module type corresponding to M001 is "milling module," with the first interface specification conforming to the ISO 9409-1 standard, a T-slot size of 10mm, and bolt locking. By comparing the first interface specification of the M001 milling module with the second interface specification of the base mounting bracket in the tooling fixture system (also conforming to the ISO 9409-1 standard), the software system determines that the first deviation is less than 0.02mm, confirming the module's compatibility with the mounting bracket. The software system then compares the dimensions, positions, and shapes of the locating pin holes and locating pins of the milling module and the base mounting bracket in detail, finding a perfect match, further confirming the feasibility of module replacement. After confirming the module's compatibility with the mounting bracket, the software system loads the milling module's clamping force parameter of 300N from the fixture database and prepares to send this parameter to the control execution interface module to ensure stable clamping of the workpiece during subsequent machining.

[0106] Through the above-described embodiments of this application, the milling module was successfully identified and replaced, providing the necessary preparation and parameter settings for workpiece machining, ensuring the efficiency and accuracy of the production process. This process fully demonstrates the importance of modular quick-change management modules in modern manufacturing environments and is a key technology for improving production flexibility and reducing changeover time.

[0107] In an optional implementation, before identifying the module identifier of the target module, the process includes: obtaining maintenance data matching the tooling fixture and the target module from a maintenance database, wherein the maintenance data is used to indicate the failure time, failure type, and repair time; determining the continuous operating time and reliability of the tooling fixture and the target module, wherein the reliability is used to indicate the time during which the tooling fixture and the target module will not fail; determining the maintenance cycle of the tooling fixture and the target module based on the maintenance data, continuous operating time, and reliability; and sending a second instruction if the maintenance conditions are met during the current time and maintenance cycle, wherein the second instruction is used to indicate that the tooling fixture and the target module require maintenance.

[0108] It should be noted that the maintenance database can be a database storing historical maintenance information for tooling fixtures, including key data such as failure time, failure type, and repair time, used to analyze maintenance cycles and predict maintenance needs. Maintenance data specifically refers to the time of failure, the type of failure (e.g., excessive positioning deviation, abnormal clamping force), and the time spent repairing the failure. This data forms the basis for calculating maintenance cycles and assessing the health status of tooling fixtures. Continuous uptime is the cumulative uptime of the tooling fixture or module from its activation to the present time, usually measured in hours, and is an important parameter for assessing fixture health and calculating maintenance cycles. Reliability refers to the probability that the tooling fixture or module will not fail within a specific timeframe, usually derived from historical maintenance data and uptime analysis, and is a key indicator for developing maintenance strategies. The maintenance cycle is calculated based on the Weibull distribution model and maintenance data, representing the recommended maintenance interval for the tooling fixture or module. Determining the maintenance cycle helps with preventative maintenance, reducing production interruptions and failure losses. The software system sets a series of conditions to trigger the second instruction, i.e., a maintenance reminder. These conditions may include the current time being less than a certain time away from the next maintenance cycle, or the reliability being lower than a preset threshold, to ensure the timeliness and effectiveness of maintenance reminders.

[0109] In an optional implementation, the software system extracts maintenance data related to tooling fixtures and target modules from the maintenance database, analyzes key indicators such as failure modes and failure intervals, and provides a data foundation for subsequent calculations. The software system continuously monitors the uptime of the tooling fixtures and modules, and estimates their reliability—the probability of no failures within a specific uptime—based on historical failure data. Combining maintenance data, uptime, and reliability, the recommended maintenance cycle for the tooling fixtures and target modules is calculated. The software system determines whether maintenance conditions (e.g., 72 hours in advance) are met based on the time difference between the current time and the next maintenance cycle. When the conditions are met, the system sends a second instruction to the operator or maintenance department, reminding them to perform preventative maintenance to avoid unplanned downtime and production delays.

[0110] In an optional implementation, a Weibull distribution model can be constructed. The distribution model is determined by two parameters: a scale parameter (λ) and a shape parameter (k). The scale parameter λ relates to the average lifespan of the equipment, while the shape parameter k reflects the equipment's failure mode (early failure, random failure, or wear failure). The values ​​of λ and k are estimated from historical failure data using maximum likelihood estimation (MLE). This requires analyzing the number of operating hours before each failure to find the parameter estimates that best fit the Weibull distribution. The effectiveness of the constructed model is validated by the goodness of fit with historical failure data. A good Weibull model should accurately reflect the trend of equipment failure rate over time. The maintenance cycle for a specific fixture type is calculated. The maintenance cycle refers to the time that the equipment is expected to operate without failure at a specific reliability level. For example, if the reliability level is set at 90%, the maintenance cycle is the cumulative operating time required for the equipment to reach that reliability level. Typically, the maintenance cycle is calculated based on the expected reliability level, such as 90%. This means that the probability of the equipment failing within the maintenance cycle will not exceed 10%. Using the cumulative distribution function (CDF) of the Weibull model, the cumulative operating hours required to achieve a 90% reliability level are calculated as the maintenance cycle. For example, the calculation shows that the maintenance cycle for a milling fixture at a 90% reliability level is 300 hours.

[0111] After the maintenance cycle is calculated, the system monitors the running time of each fixture and compares it with the calculated maintenance cycle. When the cumulative running hours of a fixture approach the preset time point of the maintenance cycle (e.g., 72 hours in advance), the system will automatically push a maintenance reminder to the operator or maintenance team. The warning threshold is calculated by subtracting the advance warning time (e.g., the number of working hours corresponding to 72 hours) from the maintenance cycle. Once the fixture's running time reaches or exceeds this threshold, the system automatically sends a warning. Maintenance reminders can be pushed via software interface, email, or mobile application to ensure that relevant personnel receive the information in a timely manner, prepare for maintenance, and avoid unplanned downtime.

[0112] Through the above-described embodiments of this application, the software system can not only intelligently calculate and adjust the maintenance cycle of tooling fixtures, but also proactively send maintenance reminders based on the current running time and historical data, which greatly improves the maintenance efficiency of equipment and the controllability of production plans. This is an important manifestation of the intelligent maintenance management of modern manufacturing.

[0113] Figure 3 This is a schematic diagram of an optional tooling fixture change method according to an embodiment of this application; as shown. Figure 3 As shown, the human-computer interaction module (user operation layer) provides an intuitive user interface, allowing operators to set parameters, monitor status, query data, and handle alarms.

[0114] The purpose of the human-computer interaction module is to provide users with an intuitive and efficient visual operating interface, allowing them to easily set workpiece parameters, monitor system status in real time, query historical data, and handle alarm events. Through this module, even personnel without specialized skills can effectively operate and maintain the system, greatly improving the software's usability and real-time responsiveness.

[0115] The parameter preset interface allows users to preset and recall parameters for over 100 different workpieces, including center coordinates and clamping force thresholds. The preset parameter setting accuracy reaches ±0.001mm, ensuring high precision and repeatability of workpiece clamping. The user interface includes a workpiece parameter input area, allowing users to select specific workpiece types via drop-down menus or a search function. The input area allows users to precisely set the workpiece's center coordinates and clamping force thresholds; the system automatically verifies the validity and format of the parameters. The system supports parameter saving, allowing users to create a parameter file for each workpiece for quick future retrieval. The recall function allows users to quickly load the corresponding parameter settings from a saved parameter file based on the current workpiece's ID or type.

[0116] The status monitoring interface displays the real-time status of key system components, including the position of the slide, the magnitude of the clamping force, and the status of the modules (e.g., whether they are locked or need replacement). The data refresh rate is 1Hz, meaning it updates once per second. The interface includes a real-time status display area, using charts or indicator lights to visually represent the status of each component. Real-time data acquisition: The system acquires slide position, clamping force, and module status data in real time through the control execution interface module and the perception layer interface module. The 1Hz data refresh rate ensures the real-time performance and accuracy of the system status. For states exceeding preset ranges (e.g., excessive clamping force or abnormal module status), the interface will highlight them with a prominent color or icon to immediately alert the operator.

[0117] The data query interface allows users to search historical positioning data and maintenance records by time or workpiece ID, and supports exporting to Excel reports for easy data analysis and archiving. Query options are provided, allowing users to select data retrieval by time range or workpiece ID. The system backend integrates a data management module, enabling rapid retrieval of relevant information from positioning data and maintenance record tables. Query results are displayed in tabular form on the interface, allowing users to select specific data rows for detailed viewing or editing. The export function supports saving query results as Excel files for further processing and visualization in other data analysis software.

[0118] When the system detects any abnormal state (such as module incompatibility or excessive positioning deviation), this interface will display the alarm type, cause analysis, and suggested handling steps. Alarm response time is controlled within 0.1 seconds to ensure rapid identification and response to potential problems. The interface includes an alarm list area, displaying all unprocessed alarm events in chronological order. Each alarm entry includes the alarm type, occurrence time, possible cause analysis, and handling suggestions. The alarm mechanism is linked with the perception layer interface module and data management module; when an abnormal situation is detected, the alarm is immediately displayed on the interface, and relevant data is recorded in the background database. Users can click on alarm entries to view detailed information and confirm the alarm status or take appropriate handling measures. The system is designed with alarm confirmation and deactivation functions to ensure users can respond to and handle abnormal events promptly, avoiding production interruptions or equipment damage.

[0119] The perception layer interface module (data input layer) realizes real-time data acquisition and preprocessing, and connects to external sensors, such as laser displacement sensors, force sensors, position encoders, and RFID modules. As a communication bridge between the software system and the hardware (i.e., various sensors), it is responsible for collecting raw data from laser displacement sensors, force sensors, position encoders, and RFID modules in real time, and performing necessary preprocessing to facilitate subsequent analysis and control.

[0120] Data acquisition (via Modbus-RTU protocol, acquiring sensor data at a frequency of 100Hz): The sensing layer interface module communicates with external sensors and acquires data through this protocol. The advantages of the Modbus-RTU protocol lie in its reliability and support for real-time data transmission, making it very suitable for applications in industrial environments. The sensor data acquisition frequency directly affects the system's real-time performance and response speed. A frequency of 100Hz means that 100 data acquisitions can be performed per second. This high frequency enables the system to track changes in workpiece position, clamping force, and other key parameters in real time, which is crucial for achieving precise control and rapid response.

[0121] In this module, a sliding window filtering algorithm is applied to the output signals of the laser displacement sensor and force sensor. It smooths the data by calculating the average or median value within the sliding window, reducing measurement errors caused by sensor jitter, electromagnetic interference, etc. The window size is typically 5-10 sampling points, effectively filtering out noise without excessively sacrificing the real-time characteristics of the data. After data acquisition, the system verifies the data to ensure its validity and continuity. This includes checking whether the sensor data is within a preset reasonable range (e.g., the laser displacement sensor measurement should be between 0-100mm), and whether the changes between consecutive sampling points conform to physical laws (e.g., the displacement change between adjacent sampling points should not be too large). Data verification helps to promptly detect and correct abnormal data caused by sensor malfunctions or external interference, ensuring the stable operation of the system.

[0122] The physical connection between the perception layer interface module and the sensor must use a standard interface, such as an RS-485 interface, to support Modbus-RTU protocol communication. These interface designs must consider electrical isolation, signal interference immunity, and data transmission reliability. The specific implementation of the sliding window filtering algorithm needs to consider the selection of the window length and the optimization of the filtering method. Data verification requires establishing an effective set of rules to quickly identify and process abnormal data while avoiding misinterpretation of normal data fluctuations. This module is at the lowest level of the software architecture and interacts directly with the hardware; therefore, its software stability and efficiency must be ensured. A modular programming approach is typically adopted to make data acquisition and preprocessing functions easy to expand and maintain, while optimizing code logic to improve the speed and accuracy of data processing.

[0123] The adaptive positioning algorithm module (core algorithm layer) processes the preprocessed data transmitted from the perception layer interface module, automatically calculates the workpiece positioning reference, and corrects positioning deviations. It is responsible for processing the preprocessed data from the perception layer interface module, automatically identifying and calculating the workpiece's positioning reference, and correcting positioning deviations when necessary to ensure the workpiece can be accurately positioned at the preset location. This process encompasses three key steps: edge detection, reference calculation, and dynamic adjustment, aiming to improve positioning accuracy and automation while reducing the need for manual calibration.

[0124] The modular quick-change management module (collaborative scheduling layer) automates the identification, compatibility verification, and changeover of fixture modules through software scheduling. This module aims to reduce manual intervention, accelerate changeover time, and ensure the efficiency and accuracy of the changeover process.

[0125] The specific implementation methods of the adaptive positioning algorithm module and the modular quick-change management module are as described above, and will not be repeated here.

[0126] The data management module (data support layer) integrates and manages the entire lifecycle data of tooling fixtures, supporting data analysis and maintenance alerts. It is responsible for integrating, analyzing, and issuing alerts on the entire lifecycle data of tooling fixtures to support efficient and intelligent equipment management and maintenance decisions. Its key features and functions are as follows:

[0127] This module is responsible for collecting and storing various data during the use of tooling fixtures, including positioning data, clamping force data, maintenance records, and module ledger information. This data is automatically transmitted from the perception layer, core algorithm layer, and control execution layer via standardized interfaces, ensuring data real-time performance and integrity. Data analysis methods, such as moving averages and Weibull distribution models, are used to perform trend analysis on the large amount of historical data stored, predicting the future condition of the fixtures, including wear levels, maintenance needs, and potential failures. Based on the results of trend analysis, the data management module can automatically identify upcoming or potential maintenance needs, issuing early warnings to operators, reducing the occurrence of emergency failures, minimizing maintenance costs and downtime, and improving equipment availability and production efficiency.

[0128] Record detailed data for each positioning operation, including timestamp, workpiece ID, and positioning deviation, to provide a basis for subsequent accuracy analysis and troubleshooting. Store clamping force information during fixture use, which can be used to monitor the fixture's usage intensity and wear condition, as well as adjust clamping strategies. Include information such as the date of each maintenance, maintenance content, and responding operator, which helps track maintenance history and evaluate maintenance efficiency. Detailed information on maintenance modules, such as module ID, type, status, and compatible workpieces, ensures the accuracy of module management. The specific data tables included are shown in Table 1.

[0129] Table 1

[0130]

[0131] The control execution interface module (instruction output layer) serves as a bridge between the tooling and fixture software system and the hardware execution layer. It is responsible for converting the instructions generated by the software algorithm module into signals that the hardware can recognize and execute. These signals are used to precisely control the position of the slide, the clamping force of the grippers, and the locking status of the module, ensuring accurate workpiece clamping and rapid module replacement. Furthermore, the module has emergency stop logic, enabling it to respond quickly to detected abnormalities and prevent equipment damage or production accidents.

[0132] The adaptive positioning algorithm module calculates the slide adjustment amount and converts it into a "pulse + direction" signal for the servo motor. The pulse equivalent is set to 0.001mm / pulse, and the direction signal indicates whether the servo motor rotates in the forward or reverse direction. This signal format ensures precise slide movement, meeting the positioning accuracy requirement of ±0.01mm. For example, if the algorithm indicates that the slide needs to move 0.03mm in the forward direction, it outputs 3 pulses and a forward direction signal. The clamping force command output by the modular quick-change management module is transmitted to the electric or pneumatic gripper via a 0-10V analog signal. This signal format allows for precise adjustment of the clamping force, covering a range of 0-500N, ensuring stable workpiece clamping while avoiding damage caused by excessive clamping force.

[0133] The control execution interface module works closely with the data management module and the perception layer interface module to monitor sensor data in real time, such as feedback from the clamping force sensor and laser displacement sensor. When the clamping force exceeds the threshold of 500N or the positioning deviation exceeds ±0.1mm, the emergency stop logic responds immediately. Upon detecting an anomaly, the module immediately outputs an emergency stop signal. The response time of the emergency stop signal is ≤0.05s, ensuring rapid interruption of equipment operation in the event of an anomaly, preventing further damage or safety accidents. The emergency stop signal is transmitted to the emergency stop control unit of the entire control system via a hardware cascade circuit or safety loop. This unit immediately cuts off the power to all actuators, stopping the slide movement, gripper clamping, and locking mechanisms.

[0134] In an optional example, suppose we are in a high-precision manufacturing industry producing complex, high-precision parts such as curved skin. Traditional positioning algorithms have low accuracy when dealing with extremely complex irregular-shaped parts and cannot meet the high-precision requirements for curved skin positioning (requiring an accuracy rate > 99.5%).

[0135] In an optional implementation, 1000 sets of workpiece data covering different specifications and shapes can be collected, including edge contours, positioning references, and other information, ensuring that the dataset covers typical complex shapes of curved skin surfaces. A convolutional neural network (CNN) model is trained using the prepared 1000 sets of data as the training set through a deep learning framework (such as TensorFlow), enabling it to directly identify workpiece edges and reference coordinates from the original images. The trained CNN model is integrated into the software system, replacing the original Canny edge detection algorithm module, allowing it to handle workpiece positioning with more complex shapes. In actual production, the workpiece is placed on a positioning platform, and the system captures workpiece images through a camera. The CNN model directly identifies the workpiece edges from the images and calculates the reference coordinates, outputting the results to the control execution interface module for positioning correction.

[0136] For complex, irregularly shaped parts, such as aerospace curved skins, the recognition accuracy is significantly improved, exceeding 99.5%, which can meet the requirements of high-precision positioning. However, it requires a large amount of labeled data to train the model, which is costly, and the response time may be greater than 1 second, slower than PID-based positioning algorithms, limiting its applicability to small-batch production scenarios.

[0137] In one optional example, for a production facility with multiple plants distributed globally, the complexity of managing fixture data across geographical regions arises. The tooling and fixture data from each plant is isolated, hindering unified management and rapid sharing, thus impacting production coordination and maintenance efficiency at the group level.

[0138] In an optional implementation, a data management module is deployed in the cloud (e.g., an IoT platform) to replace the local databases of each factory. The tooling and fixture systems of each factory are configured to upload positioning data, clamping force data, maintenance records, and other information to the cloud database in real time. In the cloud, data integration tools are used to manage data from different factories uniformly, and analysis tools are used for trend analysis and fault warnings, supporting cross-regional data collaboration. Each factory can access the cloud database according to its permissions, enabling the sharing and unified scheduling of fixture data, improving the efficiency of production planning and maintenance management at the group level. SSL protocol is used for data encryption to ensure data transmission security; simultaneously, network configuration is optimized to ensure a bandwidth of at least 10Mbps to reduce network latency and guarantee data real-time performance.

[0139] It enables unified management of fixture data across multiple factories in a group enterprise, supports cross-regional data sharing, and improves the efficiency of production coordination and maintenance management.

[0140] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method.

[0141] Embodiments of this application also provide a tooling fixture changing device. Figure 4 This is a structural block diagram of an optional tooling fixture changing device according to an embodiment of this application, such as... Figure 4 As shown, the device includes:

[0142] The first identification module 402 is used to identify the module identifier of the target module and determine the first interface specification corresponding to the target module through the module identifier, wherein the target module is used to clamp the workpiece in the tooling fixture system;

[0143] The first acquisition module 404 is used to acquire the target parameters of the target module and the target workpiece when the first deviation between the first interface specification and the second interface specification of the base mounting seat in the tooling fixture system meets the preset deviation range, and to load the target parameters into the target module according to the target parameters.

[0144] The first loading module 406 is used to determine that the target module has completed the transformation and to clamp the target workpiece after the target module has completed loading the target parameters.

[0145] The workpiece fixing module 408 is used to position the target workpiece and fix it according to the target parameters.

[0146] Optionally, the workpiece fixing module 408 is further configured to acquire multiple reference coordinates, wherein the reference coordinates are used to indicate the coordinate data of sampling points on the target workpiece; perform edge detection on the target workpiece based on the multiple reference coordinates to obtain the edge coordinate set corresponding to the target workpiece; fit the edge coordinate set according to the shape of the target workpiece to obtain the current reference coordinates of the target workpiece; and control the movement and positioning of the target workpiece based on the deviation between the current reference coordinates and the target coordinates.

[0147] Optionally, the workpiece fixing module 408 is further configured to smooth multiple reference coordinates to obtain multiple first reference coordinates; calculate the gradient intensity of the multiple first reference coordinates, and determine the first reference coordinates corresponding to gradient intensities greater than a first preset threshold as edge coordinates and put them into the edge coordinate set; determine the first reference coordinates whose gradient intensities are less than the first preset threshold and greater than the second preset threshold as second reference coordinates, and if the second reference coordinates are connected to the edge coordinates, determine the second reference coordinates as edge coordinates and put them into the edge coordinate set.

[0148] Optionally, the workpiece fixing module 408 is further configured to: obtain a first dimension of the target workpiece when the target workpiece has a first shape; calculate a first distance between the edge coordinates and the preset reference coordinates, and calculate a first error between the first distance and the first dimension; add the first errors corresponding to each of the multiple edge coordinates in the edge coordinate set, and determine the preset reference coordinate as the current reference coordinate when the first error value is the smallest; when the target workpiece has a second shape, determine the maximum horizontal coordinate value as a first reference value, the minimum horizontal coordinate value as a second reference value, the maximum vertical coordinate value as a third reference value, and the minimum vertical coordinate value as a fourth reference value among the multiple edge coordinates in the edge coordinate set; determine the average of the first reference value and the second reference value as the horizontal coordinate value of the current reference coordinate, and determine the average of the third reference value and the fourth reference value as the vertical coordinate value of the current reference coordinate.

[0149] Optionally, the workpiece fixing module 408 is further configured to calculate the reference deviation between the current reference coordinates and the target coordinates of the target workpiece after the target workpiece is moved; determine that the target workpiece positioning is completed when the number of times the reference deviation is continuously less than the first preset deviation value meets the preset number; and send a first instruction when the number of times the reference deviation is continuously greater than the second preset deviation value meets the warning number, wherein the first instruction is used to instruct the tooling fixture to be repaired.

[0150] Optionally, the first identification module 402 is further configured to search in the module database for a first interface specification and a module type of the target module that match the module identifier, wherein the first interface specification is used to indicate the size and locking method of the target module; and, if the first deviation between the first interface specification and the second interface specification of the base mounting seat in the tooling fixture system conforms to a preset deviation range, to obtain the target parameters of the target module and the target workpiece, including: searching in the fixture database for the second interface specification of the base mounting seat, wherein the second interface specification is used to indicate the size of the base mounting seat; and comparing the size, position, shape, and interface type of the positioning pin hole and the positioning pin of the target module and the base mounting seat to determine the first deviation.

[0151] Optionally, the first identification module 402 is further configured to: obtain maintenance data matching the tooling fixture and the target module from the maintenance database, wherein the maintenance data is used to indicate the fault time, fault type, and repair time; determine the continuous operating time and reliability of the tooling fixture and the target module, wherein the reliability is used to indicate the time during which the tooling fixture and the target module will not fail; determine the maintenance cycle of the tooling fixture and the target module based on the maintenance data, continuous operating time, and reliability; and send a second instruction if the maintenance conditions are met during the current time and maintenance cycle, wherein the second instruction is used to indicate that the tooling fixture and the target module need maintenance.

[0152] For a description of the features in the embodiment corresponding to the tooling fixture changing device, please refer to the relevant description in the embodiment corresponding to the tooling fixture changing method, which will not be repeated here.

[0153] Embodiments of this application also provide an electronic device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the tooling fixture transformation method embodiments described above.

[0154] Embodiments of this application also provide a computer-readable storage medium storing a computer program, wherein the computer program is configured to execute the steps in any of the above-described tooling fixture change method embodiments when running.

[0155] In one exemplary embodiment, the aforementioned computer-readable storage medium may include, but is not limited to, various media capable of storing computer programs, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard disk, magnetic disk, or optical disk.

[0156] The embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the tooling fixture transformation method embodiments described above.

[0157] Embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above-described tooling fixture replacement method embodiments.

[0158] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0159] The foregoing has provided a detailed description of a tooling fixture changeover method and apparatus, storage medium, and electronic device provided in this application. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are merely for the purpose of helping to understand the method and core ideas of this application. It should be noted that those skilled in the art can make various improvements and modifications to this application without departing from its principles, and these improvements and modifications also fall within the protection scope of the claims of this application.

Claims

1. A method for changing tooling fixtures, characterized in that, include: Identify the module identifier of the target module and determine the first interface specification corresponding to the target module through the module identifier, wherein the target module is used to clamp the workpiece in the tooling fixture system; If the first deviation between the first interface specification and the second interface specification of the base mounting seat in the tooling fixture system conforms to a preset deviation range, the target parameters of the target module and the target workpiece are obtained, and the target module is loaded with parameters according to the target parameters. Once the target module has completed loading the target parameters, the module is determined to have completed its transformation, and the target workpiece is clamped. The target workpiece is positioned and fixed according to the target parameters.

2. The method according to claim 1, characterized in that, The positioning of the target workpiece includes: Multiple reference coordinates are acquired, wherein the reference coordinates are used to indicate the coordinate data of sampling points on the target workpiece; Based on the multiple reference coordinates, edge detection is performed on the target workpiece to obtain the set of edge coordinates corresponding to the target workpiece; The current reference coordinates of the target workpiece are obtained by fitting the edge coordinate set according to the shape of the target workpiece; The target workpiece is moved and positioned based on the deviation between the current reference coordinates and the target coordinates.

3. The method according to claim 2, characterized in that, The step of performing edge detection on the target workpiece based on the multiple reference coordinates to obtain the edge coordinate set corresponding to the target workpiece includes: The multiple reference coordinates are smoothed to obtain multiple first reference coordinates; Calculate the gradient intensity of the plurality of first reference coordinates, and determine the first reference coordinates corresponding to gradient intensities greater than a first preset threshold as edge coordinates and put them into the edge coordinate set; The first reference coordinate with a gradient intensity less than the first preset threshold and greater than the second preset threshold is determined as the second reference coordinate. When the second reference coordinate is connected to the edge coordinate, the second reference coordinate is determined as the edge coordinate and placed into the edge coordinate set.

4. The method according to claim 2, characterized in that, The step of fitting the edge coordinate set according to the shape of the target workpiece to obtain the current reference coordinates of the target workpiece includes: When the target workpiece has a first shape, obtain the first dimension of the target workpiece; Calculate the first distance between the edge coordinates and the preset reference coordinates, and calculate the first error between the first distance and the first size; The first errors corresponding to each of the multiple edge coordinates in the edge coordinate set are added together, and the preset reference coordinate is determined as the current reference coordinate when the first error value is the smallest. When the shape of the target workpiece is the second shape, the maximum abscissa value is determined to be a first reference value, the minimum abscissa value is determined to be a second reference value, the maximum ordinate value is determined to be a third reference value, and the minimum ordinate value is determined to be a fourth reference value among the multiple edge coordinates in the edge coordinate set; The average of the first and second reference values ​​is determined as the horizontal coordinate of the current reference coordinate, and the average of the third and fourth reference values ​​is determined as the vertical coordinate of the current reference coordinate.

5. The method according to claim 2, characterized in that, The step of controlling the movement and positioning of the target workpiece based on the deviation between the current reference coordinates and the target coordinates includes: After moving the target workpiece, calculate the reference deviation between the current reference coordinates and the target coordinates of the target workpiece; If the number of times the reference deviation is continuously less than the first preset deviation value meets the preset number, the positioning of the target workpiece is determined to be complete. If the number of times the reference deviation is greater than the second preset deviation value meets the number of warnings, a first instruction is sent, wherein the first instruction is used to instruct the tooling fixture to be repaired.

6. The method according to any one of claims 1 to 5, characterized in that, The step of determining the first interface specification corresponding to the target module through the module identifier includes: The module database is searched for a first interface specification that matches the module identifier and the module type of the target module, wherein the first interface specification is used to indicate the size and locking method that the target module matches; When the first deviation between the first interface specification and the second interface specification of the base mounting seat in the tooling fixture system conforms to a preset deviation range, the target parameters of the target module and the target workpiece are obtained, including: The second interface specification of the base mount is searched in the fixture database, wherein the second interface specification is used to indicate the size of the base mount. The first deviation is determined by comparing the size, position, shape, and interface type of the positioning pin holes and positioning pins of the target module and the base mounting base.

7. The method according to any one of claims 1 to 5, characterized in that, Before identifying the module identifier of the target module, the following is included: Retrieve maintenance data matching the tooling fixture and the target module from the maintenance database, wherein the maintenance data is used to indicate the fault time, fault type, and repair time; Determine the continuous operating time and reliability of the tooling fixture and the target module, wherein the reliability is used to indicate the time during which the tooling fixture and the target module will not fail; The maintenance cycle of the tooling fixture and the target module is determined based on the maintenance data, the continuous operating time, and the reliability. If the maintenance conditions are met at the current time and during the maintenance week, a second instruction is sent, wherein the second instruction is used to indicate that the tooling fixture and the target module require maintenance.

8. A tooling fixture changing device, characterized in that, include: The first identification module is used to identify the module identifier of the target module and determine the first interface specification corresponding to the target module through the module identifier, wherein the target module is used to clamp the workpiece in the tooling fixture system; The first acquisition module is used to acquire the target parameters of the target module and the target workpiece when the first deviation between the first interface specification and the second interface specification of the base mounting seat in the tooling fixture system meets the preset deviation range, and to load parameters of the target module according to the target parameters. The first loading module is used to determine that the target module has completed its transformation and to clamp the target workpiece after the target module has completed loading the target parameters. The workpiece fixing module is used to position the target workpiece and fix the target workpiece according to the target parameters.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method described in any one of claims 1 to 7.

10. An electronic device, characterized in that, include: Memory, used to store computer programs; A processor for executing the computer program to implement the method as described in any one of claims 1 to 7.

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