Intelligent distributed control system and method for flexible production line based on zero-point quick change

Abstract

This invention relates to the field of intelligent manufacturing technology and discloses an intelligent distributed control method and system for flexible production lines based on zero-point quick-change. The method includes: acquiring multi-point temperature sensor data distributed across various distributed control nodes of the flexible production line to generate a set of temperature sampling points with spatial coordinate labels; performing spatial interpolation on the temperature sampling point set to generate continuous temperature field distribution data, and extracting the temperature gradient vector between the zero-point quick-change interface area and the gas path area; determining whether the amplitude of the temperature gradient vector exceeds the collaborative calibration trigger threshold; if it does, entering the collaborative calibration process; determining the execution order of thermal drift compensation and gas path pressure baseline switching based on the temperature gradient vector direction information, and outputting collaborative control commands. This invention solves the technical problem of inconsistent independent calibration timing of distributed control nodes.

Description

Technical Field

[0001] This invention relates to the field of intelligent manufacturing technology, and more specifically, to an intelligent distributed control method and system for flexible production lines based on zero-point quick change. Background Technology

[0002] The FMS flexible production line consists of multiple 5-axis machining centers, a ground-rail RGV robot, a manual loading station, a tooling and fixture library, a zero-point quick change system, and other distributed control nodes. These nodes operate collaboratively through an intelligent control platform, supporting a production mode of multi-variety, small-batch, and rapid changeover. The zero-point quick change system, which achieves second-level tooling and fixture replacement through rapid locking of the master and slave trays, is the core mechanism for flexible changeover; the pneumatic system provides the driving force for locking and unlocking the zero-point quick change module.

[0003] During 24 / 7 operation, distributed control nodes such as the machine tool processing area, the zero-point quick-change interface, and the air pipeline are located in different spatial positions. The heat generated by high-speed cutting of aluminum alloy workpieces is conducted to the tooling fixtures and the zero-point quick-change interface, causing thermal drift deviation of the zero-point quick-change positioning element due to temperature rise; while the air pipeline, being far from the heat source, maintains a relatively low temperature, and the air pipeline seals harden at low temperature, resulting in pressure response characteristics that differ from those at room temperature.

[0004] In existing distributed control methods, zero-point rapid heat exchange drift compensation and gas path pressure baseline adjustment are executed independently by each node, triggering calibration actions based on local temperature thresholds, lacking intelligent cross-node coordination. When the temperature of the zero-point rapid heat exchange node rises and triggers thermal drift compensation, the gas path node may still be in a low-temperature state. If the gas path baseline is adjusted synchronously at this time, misadjustment will occur. The independent control logic of each distributed control node cannot perceive the spatial distribution characteristics of the overall temperature field, resulting in inconsistent calibration timing and affecting the overall processing accuracy of the flexible production line. Summary of the Invention

[0005] This invention provides an intelligent distributed control method and system for flexible production lines based on zero-point quick change, solving the technical problem of inconsistent timing of independent calibration of distributed control nodes in related technologies.

[0006] This invention discloses an intelligent distributed control method for flexible production lines based on zero-point quick change, comprising the following steps: The system acquires real-time output data from multiple temperature sensors distributed across various control nodes on the flexible production line, and combines this data with the installation coordinates of each sensor to generate a set of temperature sampling points labeled with spatial coordinates. Spatial interpolation is performed on the set of temperature sampling points to generate continuous temperature field distribution data covering the zero-point quick-switch interface area and the gas path area, and the temperature gradient vector between the zero-point quick-switch interface area and the gas path area is extracted. Determine whether the magnitude of the temperature gradient vector exceeds the collaborative calibration trigger threshold. If it does, proceed with the collaborative calibration process. If it does not, each distributed node executes independently according to its local calibration logic. In the collaborative calibration process, the execution order of zero-point fast heat transfer drift compensation and gas path pressure baseline switching is determined based on the direction information of the temperature gradient vector, and collaborative control commands are output to each distributed control node in the determined order.

[0007] Further, the step of spatially interpolating the set of temperature sampling points to generate continuous temperature field distribution data and extracting the temperature gradient vector includes: The set of temperature sampling points is input into a radial basis function interpolation algorithm to generate a continuous temperature field function that can be evaluated at any spatial coordinate point. Using a gradient calculation algorithm, the rate of temperature change is calculated along the direction connecting the center point of the zero-point quick-change interface region and the center point of the gas path region, generating a temperature gradient vector containing amplitude and direction components.

[0008] Furthermore, the determination of the execution order based on the direction information of the temperature gradient vector includes: If the direction of the temperature gradient vector points to the zero-point fast-switching region, it indicates that the temperature in the zero-point fast-switching region is higher, and a coordinated control instruction sequence that prioritizes the heating drift compensation instruction under the zero-point fast-switching node is generated. If the direction of the temperature gradient vector points to the gas path region, it indicates that the temperature in the gas path region is lower, and a coordinated control command sequence is generated that prioritizes issuing baseline switching commands to the gas path nodes.

[0009] Furthermore, the cooperative control command includes a thermal drift compensation command, the generation of which includes: Based on the temperature field data of the zero-point quick-change interface area, the temperature difference between the current temperature and the initial clamping temperature is calculated. The dimensional change of the positioning element is calculated using the material thermal expansion coefficient and geometric parameters of the zero-point quick-change positioning element. The dimensional change is the product of the material thermal expansion coefficient, geometric parameters and temperature difference. The dimensional change is converted into a thermal drift offset vector of the sub-disk relative to the mother disk, generating a zero-point fast heat exchange drift compensation amount and outputting it to the tool compensation register of the CNC system.

[0010] Furthermore, the coordinated control command includes a gas path pressure baseline switching command, the generation of which includes: Based on the temperature field data of the gas path area, determine the temperature range to which the current temperature of the gas path equipment belongs; Retrieve the pressure curve characteristic parameters of normal locking records within this temperature range from the historical database. The pressure curve characteristic parameters include the mean and standard deviation. The retrieved temperature range characteristic parameters are set as the comparison baseline for the current gas path locking status diagnosis and output to the locking status diagnosis module.

[0011] Furthermore, the step of outputting cooperative control commands to each distributed control node in a predetermined order also includes: Based on the magnitude of the temperature gradient vector and the rate of temperature change in the two regions, the time interval between the two types of distributed control commands is calculated. Cooperative control commands are output sequentially at the specified time intervals.

[0012] Furthermore, the method also includes: The temperature sensor data of each distributed node is continuously acquired according to the preset temperature sampling period, and spatial interpolation is repeatedly performed to generate updated temperature field distribution data and temperature gradient vector. When the magnitude of the temperature gradient vector falls below the equilibrium threshold, the collaborative calibration process is exited, and the distributed independent control mode is restored.

[0013] Furthermore, the method also includes: When the temperature in the gas path area enters the normal temperature range, the gas path diagnostic baseline will be automatically switched from the current temperature range characteristic parameters back to the normal temperature baseline.

[0014] This invention also discloses an intelligent distributed control system for a flexible production line based on zero-point quick change, used to execute the above method, comprising: The temperature data acquisition module is used to acquire real-time output data from multiple temperature sensors distributed across various distributed control nodes, and combine this data with the installation coordinates of each sensor to generate a set of temperature sampling points with spatial coordinate labels. The temperature field gradient calculation module is used to perform spatial interpolation on the set of temperature sampling points to generate continuous temperature field distribution data, and to extract the temperature gradient vector between the zero-point quick-change interface area and the gas path area. The collaborative calibration judgment module is used to determine whether the magnitude of the temperature gradient vector exceeds the collaborative calibration trigger threshold. If it does, the collaborative calibration process is initiated. The collaborative control command generation module is used to determine the execution order of zero-point fast heat exchange drift compensation and gas path pressure baseline switching based on the direction information of the temperature gradient vector, and output collaborative control commands to each distributed control node in the determined order.

[0015] This invention integrates discrete temperature measurement points of control nodes distributed in different spatial locations into a continuous field description through temperature field gradient mapping. It uses gradient vectors to characterize the degree and direction of temperature difference between the zero-point fast-switch node and the gas path node, thus solving the technical problem of conflicting independent calibration timings caused by different temperature reference points and asynchronous rates of change among nodes in a distributed control architecture. The invention achieves the following technical effects: 1. The triggering criterion for collaborative calibration is determined based on the gradient magnitude rather than the independent threshold of each node. Collaborative calibration is only initiated when the temperature difference between the two regions is significant, thus avoiding inconsistent triggering timing caused by independent judgments of each node. 2. The execution order of collaborative calibration is determined based on the gradient direction, prioritizing the calibration of nodes with more drastic temperature changes, so that the calibration action matches the actual distribution characteristics of the temperature field; 3. By coordinating the zero-point quick-change positioning accuracy control and the air circuit locking reliability control in the temperature dimension, the overall processing accuracy and production efficiency of the flexible production line are improved. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the intelligent distributed control method for flexible production lines based on zero-point quick change, as described in this invention. Detailed Implementation

[0017] The FMS flexible production line consists of multiple 5-axis machining centers, a ground-rail RGV robot, a manual loading station, a tooling and fixture library, a zero-point quick change system, and other distributed control nodes. These nodes operate collaboratively through an intelligent control platform, supporting a production mode of multi-variety, small-batch, and rapid changeover. The zero-point quick change system, which achieves second-level tooling and fixture replacement through rapid locking of the master and slave trays, is the core mechanism for flexible changeover; the pneumatic system provides the driving force for locking and unlocking the zero-point quick change module.

[0018] During 24 / 7 operation, distributed control nodes such as the machine tool processing area, the zero-point quick-change interface, and the air pipeline are located in different spatial positions. The heat generated by high-speed cutting of aluminum alloy workpieces is conducted to the tooling fixtures and the zero-point quick-change interface, causing thermal drift deviation of the zero-point quick-change positioning element due to temperature rise; while the air pipeline, being far from the heat source, maintains a relatively low temperature, and the air pipeline seals harden at low temperature, resulting in pressure response characteristics that differ from those at room temperature.

[0019] In existing distributed control methods, zero-point rapid heat exchange drift compensation and gas path pressure baseline adjustment are executed independently by each node, triggering calibration actions based on local temperature thresholds, lacking intelligent cross-node coordination. When the temperature of the zero-point rapid heat exchange node rises and triggers thermal drift compensation, the gas path node may still be in a low-temperature state. If the gas path baseline is adjusted synchronously at this time, misadjustment will occur. The independent control logic of each distributed control node cannot perceive the spatial distribution characteristics of the overall temperature field, resulting in inconsistent calibration timing and affecting the overall processing accuracy of the flexible production line.

[0020] According to an embodiment of this invention, an intelligent distributed control method for a flexible production line based on zero-point quick-change is provided to solve the technical problem of inconsistent independent calibration timing of distributed control nodes. It should be understood that the hardware environment of this embodiment includes: multiple temperature sensors distributed across the zero-point quick-change master panel, slave panel, air manifold, and cylinder ports, and an intelligent control platform communicatively connected to each distributed control node. The intelligent distributed control method for a flexible production line based on zero-point quick-change includes the following steps: Step 100: Obtain real-time output data from multiple temperature sensors distributed across various distributed control nodes, and combine this data with the installation coordinates of each sensor to generate a set of temperature sampling points labeled with spatial coordinates.

[0021] Specifically, temperature sensors are distributed across the zero-point quick-change master plate, zero-point quick-change slave plate, air main, and cylinder ports. Each temperature sensor outputs the current temperature measurement value, along with its installation position coordinates in the flexible production line's spatial coordinate system. The temperature values ​​of each sensor Combined with location coordinates, a set of temperature sampling points is generated. ,in This represents the total number of temperature sensors.

[0022] Taking the temperature acquisition of an aluminum alloy casing part after 2 hours of continuous processing as an example, the flexible production line is equipped with 6 temperature sensors. The ambient reference temperature of the flexible production line was calibrated during the commissioning phase. ℃, allowable deviation of room temperature fluctuation ℃. The intelligent control platform at the sampling time The output data from each sensor is as follows: Table 1. Raw data from temperature sampling points; A set of temperature sampling points is generated based on the above data. The zero-point quick-change interface area includes sensors S1, S2, and S3, and the gas path area includes sensors S4, S5, and S6.

[0023] Step 200: Spatial interpolation of the temperature sampling point set is performed using the radial basis function interpolation algorithm to generate continuous temperature field distribution data, and the temperature gradient vector between the zero-point quick-change interface region and the gas path region is extracted using the gradient calculation algorithm.

[0024] Specifically, the set of temperature sampling points is input into a radial basis function interpolation algorithm to generate a continuous temperature field function covering the zero-point quick-switch interface region and the gas path region. Based on the temperature field function, a gradient calculation algorithm is used to extract the temperature gradient vector between the center point of the zero-point quick-switch interface region and the center point of the gas path region. The temperature gradient vector contains the magnitude and directional components.

[0025] The aforementioned radial basis function interpolation algorithm is a conventional spatial interpolation algorithm, whose input is a set of temperature sampling points with spatial coordinate labels. The output is a continuous temperature field function that can be evaluated at any spatial coordinate point. .

[0026] The aforementioned gradient calculation algorithm employs the finite difference method, with its input being a continuous temperature field function. and the coordinates of the center point of the zero-point quick-change interface area Coordinates of the center point of the gas path area The output is the temperature gradient vector between the center points of the two regions. .

[0027] Furthermore, the temperature gradient vector The calculation method is as follows: the gradient direction is the line connecting the center points of the two regions, and the gradient magnitude is... ,in The Euclidean distance between the centers of the two regions .

[0028] The aforementioned set of temperature sampling points is input into a radial basis function interpolation algorithm to generate a continuous temperature field function. The coordinates of the center point of the area are calculated based on the installation position coordinates of sensors S1, S2, and S3 within the zero-point quick-change interface area. mm, calculate the coordinates of the center point of the area based on the installation position coordinates of sensors S4, S5, and S6 within the gas path area. mm. Utilizing continuous temperature field functions The temperature at the center point of the zero-point quick-change interface region is obtained by calculating the value at the center point of the two regions. ℃, temperature at the center point of the gas path area ℃.

[0029] Calculate the Euclidean distance between the center points of the two regions: Calculate the magnitude of the temperature gradient vector: Step 300: Determine whether the temperature gradient vector magnitude exceeds the collaborative calibration trigger threshold. If it does, proceed to the intelligent collaborative calibration process and execute step 400. If it does not exceed the threshold, each distributed control node will execute independently according to its local calibration logic.

[0030] Specifically, the magnitude of the temperature gradient vector With preset co-calibration trigger threshold Comparison. When When this occurs, the current state is marked as a temperature field imbalance state, indicating a significant temperature difference between the zero-point quick-switch interface area and the gas path area, requiring the initiation of a cross-node collaborative calibration process. This indicates that the temperature conditions in each region are similar, and each distributed control node can execute independently according to its local calibration logic without causing timing conflicts.

[0031] Furthermore, the collaborative calibration trigger threshold The value range is determined based on the thermal expansion characteristics of the zero-point quick-change positioning element. ℃ / m indicates the maximum allowable temperature difference per unit distance.

[0032] Based on the material characteristics of the 42CrMo alloy steel positioning pins used in the zero-point quick-change module of the flexible production line, the collaborative calibration trigger threshold is set to... ℃ / m. The previously calculated temperature gradient vector magnitude... Compared with the threshold, ℃ / m, due to The system determines that the current state is an uneven temperature field and enters the intelligent collaborative calibration process.

[0033] Step 400: Determine the execution order of zero-point fast heat exchange drift compensation and gas path pressure baseline switching based on the direction information of the temperature gradient vector, generate a cooperative control command sequence, and output the cooperative control commands to each distributed control node in the determined order.

[0034] Specifically, the directional components of the temperature gradient vector are analyzed: if the gradient direction points to the zero-point quick-change interface region, indicating a higher temperature in that region, a coordinated control command sequence is generated that prioritizes issuing heat drift compensation commands to the zero-point quick-change node; if the gradient direction points to the air path region, indicating a lower temperature, a coordinated control command sequence is generated that prioritizes issuing baseline switching commands to the air path node. Zero-point quick-change heat drift compensation commands are output to the tool compensation register of the CNC system in a determined order, and air path pressure baseline switching commands are output to the locking state diagnostic module.

[0035] Furthermore, the method for determining the gradient direction is as follows: compare the temperature at the center point of the zero-point fast-switch interface region. Temperature at the center point of the gas path area The size, if If the gradient direction points to the zero-point quick-change interface area, then the gradient direction points to the gas path area; otherwise, the gradient direction points to the gas path area.

[0036] It should be noted that the generation of the aforementioned thermal drift compensation command refers to calculating the current moment based on the temperature field data of the zero-point quick-switch interface region. The temperature difference between the initial temperature and the initial clamping temperature Utilizing the thermal expansion coefficient of the positioning element material and geometric parameters Calculate the dimensional changes of the positioning element The dimensional change is converted into a thermal drift offset vector of the sub-disk relative to the parent disk, generating a zero-point fast heat exchange drift compensation.

[0037] Furthermore, the initial clamping temperature The temperature of the zero-point quick-change interface area at the moment when the tooling fixture is clamped into the zero-point quick-change module and the positioning and locking are completed is automatically recorded and stored by the intelligent control platform when the clamping and locking are completed.

[0038] Furthermore, the coefficient of thermal expansion Geometric parameters are obtained by looking up a table in a material parameter database based on the material properties of the positioning element. The effective working length of the positioning element from the positioning surface of the mother disk to the positioning surface of the daughter disk is obtained from the design drawings of the zero-point quick-change module.

[0039] Furthermore, the method for converting the thermal drift offset vector is as follows: the dimensional change of the positioning element along its own axis is converted into the thermal drift offset vector. The three coordinate axes projected onto the spatial coordinate system of the flexible production line are obtained from the decomposition of the positioning element's installation attitude angle. , , Thermal drift offset components in three directions.

[0040] It should be noted that the generation of the above-mentioned air circuit pressure baseline switching command refers to determining the temperature range to which the air circuit equipment temperature belongs based on the temperature field data of the air circuit area, retrieving the mean and standard deviation of the pressure curve characteristic parameters of the normal locking records within the temperature range from the historical database, and setting the retrieved temperature range characteristic parameters as the comparison baseline for the diagnosis of the current air circuit locking status.

[0041] Furthermore, the pressure curve characteristic parameters include the pressure change rate, pressure peak value, and pressure stability value during the pressure rise phase of the locking action. The historical database stores the statistical values ​​of the above characteristic parameters recorded during normal locking actions in each temperature range, categorized by temperature range.

[0042] Furthermore, the temperature range is divided into a low-temperature range, a normal-temperature range, and a high-temperature range based on the temperature-sensitive characteristics of the gas path seals, with the low-temperature range being... The normal temperature range is The high temperature range is .

[0043] Due to the temperature at the center point of the zero-point fast-change interface area ℃ higher than the temperature at the center point of the gas path area ℃, determine the gradient direction pointing to the zero-point fast-switch interface region, and generate a cooperative control instruction sequence that prioritizes the thermal drift compensation instruction under the zero-point fast-switch node.

[0044] Thermal drift compensation command generation process: initial clamping temperature ℃, current temperature at the center point of the zero-point quick-change interface area ℃, temperature difference value ℃. Coefficient of thermal expansion of 42CrMo alloy steel locating pins. / ℃, effective working length of the locating pin mm. Calculate the dimensional change of the positioning element: The locating pin is installed vertically (with) (Axis parallel), after thermal drift offset vector projection , The directional component is zero. Directional thermal drift compensation amount is m.

[0045] Gas path pressure baseline switching command generation process: Gas path region center point temperature ℃, ambient reference temperature ℃, allowable deviation of room temperature fluctuation ℃, the boundary of the low temperature range is ℃. Due to The temperature of the gas circuit equipment is within the normal temperature range. ℃, the characteristic parameters of the pressure curve in the normal temperature range retrieved from the historical database are as follows: Table 2. Characteristic parameters of gas pressure curves in the normal temperature range; Set the above characteristic parameters as the comparison baseline for diagnosing the current air circuit lock-up status.

[0046] In this embodiment of the application, in order to maintain a reasonable timing coordination between the two types of calibration actions, step 400 further includes: calculating the time interval between the two types of distributed control commands based on the magnitude of the temperature gradient vector and the temperature change rate of the two regions. Cooperative control commands are output sequentially at the specified time intervals.

[0047] The aforementioned time interval The calculation method is as follows: First, calculate the temperature change rate of the zero-point quick-switch interface region and the gas path region during the current sampling period. and The rate of temperature change is defined as the difference between the current temperature value and the temperature value in the previous sampling period, divided by the sampling period duration; then the absolute value of the difference between the rates of temperature change of the two regions is calculated. Finally, the magnitude of the temperature gradient vector is... Spatial distance between the center points of the two regions Multiplying the results and dividing by the absolute value of the difference in the rates of temperature change yields the time interval. This time interval represents the estimated time required for the temperature states of the two regions to converge. The spatial distance... The Euclidean distance is calculated based on the coordinates of the center point of the zero-point quick-change interface area and the center point of the gas path area.

[0048] Furthermore, the formula for calculating the rate of temperature change is: ,in At the current sampling time, This refers to the duration of the temperature sampling period. for Temperature at the center point of the zero-point quick-change interface area at any given time. Temperature at the center point of the zero-point quick-switch interface area at the previous sampling time; rate of temperature change in the gas path area. The calculation method is the same.

[0049] Furthermore, the duration of the temperature sampling period The value is determined based on the dynamic characteristics of the temperature field change, and the range is [value range missing]. Second.

[0050] Furthermore, when the absolute value of the difference between the rates of temperature change in the two regions... Less than the preset lower limit of the rate difference At that time, the time interval Set as the default time interval To avoid errors in division by zero calculations, where Values ℃ / s.

[0051] Furthermore, the default time interval The value is determined based on the execution time of the zero-point rapid heat exchange drift compensation action and the gas path pressure baseline switching action, and is taken as 1.2 to 1.5 times the longer execution time of the two types of actions.

[0052] Calculate the time interval between the two types of control commands: temperature sampling period Seconds, temperature at the center point of the fast-swapping interface area at the previous sampling time (zero point). ℃, temperature at the center point of the gas path area ℃. Calculate the rate of temperature change: The absolute value of the difference in the rate of temperature change between the two regions ℃ / s, greater than the lower limit of the rate difference ℃ / s. Calculation time interval: Intelligent control platform Output to the tool compensation register of the CNC system Directional thermal drift compensation m, in Output a command to switch the air pressure baseline to the locking status diagnostic module.

[0053] In this embodiment of the application, in order to enable the collaborative calibration process to adapt to dynamic changes in the temperature field, the following steps are included after step 400: Step 500: Continuously acquire temperature sensor data from each distributed control node according to the preset temperature sampling period, repeat step 200 to generate updated continuous temperature field distribution data and temperature gradient vector, and exit the intelligent collaborative calibration process when the amplitude of the temperature gradient vector falls below the equilibrium threshold, and restore the distributed independent control mode.

[0054] Furthermore, the equalization threshold is set as the collaborative calibration trigger threshold. The preset scaling factor is multiples of the preset scaling factor, and the range of the preset scaling factor is 10 ... This creates a hysteresis effect to avoid frequent switching of the collaborative calibration process at threshold boundaries.

[0055] The intelligent control platform continuously monitors changes in the temperature field and collaboratively calibrates trigger thresholds. ℃ / m, preset proportional coefficient is taken as The equilibrium threshold is ℃ / m. After approximately 45 minutes of intermittent cooling during processing, at the sampling time... Get the updated set of temperature sampling points: Table 3. Temperature sampling point data after cooling; Re-perform radial basis function interpolation and gradient calculation to obtain the temperature at the center point of the zero-point fast-switch interface region. ℃, temperature at the center point of the gas path area ℃, magnitude of temperature gradient vector ℃ / m. Due to Continue to maintain the collaborative calibration process.

[0056] Continue monitoring at the sampling time The temperature at the center point of the zero-point quick-change interface area dropped to ℃, the temperature at the center point of the gas path area is ℃, magnitude of temperature gradient vector ℃ / m. Due to Exit the intelligent collaborative calibration process and revert to the distributed independent control mode.

[0057] In this embodiment of the application, in order to enable the gas path diagnostic baseline to automatically adapt to normal temperature conditions, step 500 further includes: when the temperature of the gas path area enters the normal temperature range, automatically switching the gas path diagnostic baseline from the current temperature range characteristic parameters back to the normal temperature baseline.

[0058] Furthermore, the normal temperature range is defined as follows: ,in The ambient reference temperature for the initial calibration of the flexible production line clamping. The allowable deviation for room temperature fluctuations is within the range of [value range missing]. ℃.

[0059] Furthermore, the ambient reference temperature During the commissioning phase of the flexible production line, the following method was used: The clamping and positioning accuracy of the zero-point quick-change module was calibrated at room temperature, and the average temperature measurement value of each temperature sensor at the calibration moment was recorded as the data. and the ambient reference temperature The system parameter database of the intelligent control platform is stored.

[0060] According to the intelligent distributed control method for flexible production lines based on zero-point quick-change provided in this embodiment, discrete temperature measurement points of each control node distributed in different spatial locations are integrated into a continuous field description through temperature field gradient mapping, and gradient vectors are used to characterize the degree and direction of temperature difference between the zero-point quick-change node and the gas path node.

[0061] Therefore, the triggering criterion for collaborative calibration is determined based on the gradient magnitude rather than the independent threshold of each node. Collaborative calibration is only initiated when the temperature difference between the two regions is significant, thus avoiding inconsistent triggering timing caused by independent judgment of each node. The execution order of collaborative calibration is determined based on the gradient direction, prioritizing the calibration of nodes with more drastic temperature changes, so that the calibration action matches the actual distribution characteristics of the temperature field.

[0062] It is evident that this method overcomes the conflict of independent calibration timing caused by different temperature reference points and asynchronous change rates among nodes in a distributed control architecture, enabling the zero-point quick-change positioning accuracy control and the air circuit locking reliability control to coordinate and cooperate in the temperature dimension.

Claims

1. A method for intelligent distributed control of a flexible production line based on zero-point quick change, characterized in that, Includes the following steps: The system acquires real-time output data from multiple temperature sensors distributed across various control nodes on the flexible production line, and combines this data with the installation coordinates of each sensor to generate a set of temperature sampling points labeled with spatial coordinates. Spatial interpolation is performed on the set of temperature sampling points to generate continuous temperature field distribution data covering the zero-point quick-switch interface area and the gas path area, and the temperature gradient vector between the zero-point quick-switch interface area and the gas path area is extracted. Determine whether the magnitude of the temperature gradient vector exceeds the collaborative calibration trigger threshold. If it does, proceed with the collaborative calibration process. If it does not, each distributed node executes independently according to its local calibration logic. In the collaborative calibration process, the execution order of zero-point fast heat transfer drift compensation and gas path pressure baseline switching is determined based on the direction information of the temperature gradient vector, and collaborative control commands are output to each distributed control node in the determined order. The collaborative control command includes a thermal drift compensation command. The generation of the thermal drift compensation command includes: calculating the temperature difference between the current temperature and the initial clamping temperature based on the temperature field data of the zero-point quick-change interface area; calculating the dimensional change of the positioning element using the material thermal expansion coefficient and geometric parameters of the zero-point quick-change positioning element, where the dimensional change is the product of the material thermal expansion coefficient, geometric parameters, and the temperature difference; converting the dimensional change into a thermal drift offset vector of the sub-disk relative to the mother disk, generating a zero-point quick-change thermal drift compensation amount, and outputting it to the tool compensation register of the CNC system; wherein, converting the dimensional change into a thermal drift offset vector of the sub-disk relative to the mother disk includes: projecting the dimensional change of the positioning element along its own axial direction onto the three coordinate axes of the flexible production line spatial coordinate system, and obtaining the thermal drift offset components in the X, Y, and Z directions based on the positioning element's installation attitude angle decomposition. The step of outputting coordinated control commands to each distributed control node in a predetermined order further includes: calculating the time interval between the two types of distributed control commands based on the magnitude of the temperature gradient vector and the temperature change rate of the two regions; and outputting the coordinated control commands sequentially according to the time interval; wherein the temperature change rate is the difference between the current temperature value and the temperature value of the previous sampling period divided by the sampling period duration; the time interval... ,in The magnitude of the temperature gradient vector. The Euclidean distance between the center points of the two regions. The rate of temperature change in the zero-point quick-switch interface area. The rate of temperature change in the gas path region; the absolute value of the difference between the rates of temperature change in the two regions. When the rate difference is less than the preset lower limit, the time interval will be set to the preset default time interval.

2. The method according to claim 1, characterized in that, The step of spatially interpolating the set of temperature sampling points to generate continuous temperature field distribution data and extracting the temperature gradient vector includes: The set of temperature sampling points is input into a radial basis function interpolation algorithm to generate a continuous temperature field function that can be evaluated at any spatial coordinate point. Using a gradient calculation algorithm, the rate of temperature change is calculated along the direction connecting the center point of the zero-point quick-change interface region and the center point of the gas path region, generating a temperature gradient vector containing amplitude and direction components.

3. The method according to claim 1, characterized in that, The determination of the execution order based on the direction information of the temperature gradient vector includes: If the direction of the temperature gradient vector points to the zero-point fast-switching region, it indicates that the temperature in the zero-point fast-switching region is higher, and a coordinated control instruction sequence that prioritizes the heating drift compensation instruction under the zero-point fast-switching node is generated. If the direction of the temperature gradient vector points to the gas path region, it indicates that the temperature in the gas path region is lower, and a coordinated control command sequence is generated that prioritizes issuing baseline switching commands to the gas path nodes.

4. The method according to claim 1, characterized in that, The coordinated control command includes a gas path pressure baseline switching command, the generation of which includes: Based on the temperature field data of the gas path area, determine the temperature range to which the current temperature of the gas path equipment belongs; Retrieve the pressure curve characteristic parameters of normal locking records within this temperature range from the historical database. The pressure curve characteristic parameters include the mean and standard deviation. The retrieved temperature range characteristic parameters are set as the comparison baseline for the current gas path locking status diagnosis and output to the locking status diagnosis module.

5. The method according to claim 1, characterized in that, Also includes: The temperature sensor data of each distributed node is continuously acquired according to the preset temperature sampling period, and spatial interpolation is repeatedly performed to generate updated temperature field distribution data and temperature gradient vector. When the magnitude of the temperature gradient vector falls below the equilibrium threshold, the collaborative calibration process is exited, and the distributed independent control mode is restored.

6. The method according to claim 5, characterized in that, Also includes: When the temperature in the gas path area enters the normal temperature range, the gas path diagnostic baseline will be automatically switched from the current temperature range characteristic parameters back to the normal temperature baseline.

7. A smart distributed control system for a flexible production line based on zero-point quick change, used to execute the method described in any one of claims 1-6, characterized in that, include: The temperature data acquisition module is used to acquire real-time output data from multiple temperature sensors distributed across various distributed control nodes, and combine this data with the installation coordinates of each sensor to generate a set of temperature sampling points with spatial coordinate labels. The temperature field gradient calculation module is used to perform spatial interpolation on the set of temperature sampling points to generate continuous temperature field distribution data, and to extract the temperature gradient vector between the zero-point quick-change interface area and the gas path area. The collaborative calibration judgment module is used to determine whether the magnitude of the temperature gradient vector exceeds the collaborative calibration trigger threshold. If it does, the collaborative calibration process is initiated. The collaborative control command generation module is used to determine the execution order of zero-point fast heat exchange drift compensation and gas path pressure baseline switching based on the direction information of the temperature gradient vector, and output collaborative control commands to each distributed control node in the determined order.

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