Multi-point synchronous intelligent control forming method for core pulling mechanism of plastic tray injection mold

Abstract

The invention provides a multi-point synchronous intelligent control forming method for a core pulling mechanism of a plastic tray injection mold, and relates to the technical field of intelligent manufacturing. Establishing a cross influence mapping relation, and determining an interference sensitive position and a synchronous control reference point; dividing a stroke and generating a segmented motion trail; calculating a delay pressure response amplitude, and constructing a speed coupling transfer matrix; therefore, the core-pulling mechanisms are controlled to execute synchronously. According to the method, the interference influence is intelligently compensated, the mold stress concentration is reduced, and the plastic tray forming quality and production efficiency are improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent manufacturing technology, and in particular to a multi-point synchronous intelligent control molding method for a core-pulling mechanism of a plastic pallet injection mold. Background Technology

[0002] Plastic pallets, as essential tools in logistics transportation and warehousing, are widely used across various industries due to their advantages such as light weight, corrosion resistance, and recyclability. Injection molding is the main process for producing plastic pallets, and the core-pulling mechanism is a key component for achieving the molding of special pallet structures. Traditional plastic pallet injection molds typically employ multi-point core-pulling mechanisms to achieve complex structures. These mechanisms need to work collaboratively during demolding to ensure product quality and production efficiency.

[0003] Currently, the control methods for core-pulling mechanisms in plastic pallet injection molds mainly rely on simple position synchronization or timing control. However, in actual production, due to the complex mold structure, mutual interference between different core-pulling mechanisms, and uneven pressure distribution generated during the flow and cooling of the molten plastic, existing technologies still have shortcomings and deficiencies. Traditional control methods cannot effectively identify and address cross-interference between multiple core-pulling mechanisms. When one core-pulling mechanism moves, it causes pressure changes in other cavities. This cross-influence is particularly pronounced at critical locations, leading to product deformation or damage. Existing technologies lack differentiated control strategies for different core-pulling stages and cannot perform segmented optimization based on the characteristics of resistance changes during the core-pulling process. This is especially true at nodes where demolding resistance changes significantly, easily causing localized stress concentration or disrupted core-pulling movements. Existing synchronous control systems cannot perceive and respond to the spatial gradient characteristics of pressure changes within the cavity in real time and lack the ability to dynamically adjust the movement speed of each core-pulling mechanism based on pressure distribution. They are ill-suited to adapting to the dynamic pressure environment of complex-shaped plastic trays during demolding, affecting product quality stability and mold lifespan. Summary of the Invention

[0004] This invention provides a multi-point synchronous intelligent control molding method for a core-pulling mechanism in a plastic pallet injection mold, which can solve the problems in the prior art.

[0005] A first aspect of the present invention provides a multi-point synchronous intelligent control molding method for a core-pulling mechanism of a plastic pallet injection mold, comprising: Obtain the position information of multiple core-pulling mechanisms and the pressure information of the corresponding cavities; When each core-pulling mechanism performs the test stroke, a cross-influence mapping relationship between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity is established. The extreme value position of the cross-influence coefficient is extracted from the cross-influence mapping relationship to determine the interference-sensitive position. A cross section passing through the interference-sensitive position is constructed, and the motion trajectory of each core-pulling mechanism is projected onto the cross section and an envelope is constructed to determine the synchronous control reference point. Using the synchronous control reference point as the dividing node, the motion stroke of each core-pulling mechanism is divided into the front stroke and the back stroke; based on the distribution of resistance response characteristic points in the front stroke and the back stroke, the lead amount of the front trajectory or the lag amount of the back trajectory is determined, and the segmented motion trajectory of each core-pulling mechanism is generated. Collect the spatial gradient vector of the pressure distribution in each cavity, calculate the delayed pressure response amplitude based on the spatial gradient vector and the spatial adjacency relationship of the cavity, construct the velocity coupling transfer matrix with the delayed pressure response amplitude, and perform matrix operations on the current velocity to obtain the target velocity vector; Based on the segmented motion trajectory and the target velocity vector, each core-pulling mechanism is driven to synchronously perform the core-pulling action, thereby completing the demolding and forming of the plastic tray.

[0006] In one optional embodiment, when each core-pulling mechanism performs its test stroke, a cross-influence mapping relationship is established between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity. The extreme value positions of the cross-influence coefficient are extracted from the cross-influence mapping relationship, and the interference-sensitive positions are determined, including: When each core-pulling mechanism performs the test stroke, the first core-pulling mechanism is driven to move independently in sequence, while the other core-pulling mechanisms remain stationary. The pressure change data of non-corresponding cavities during the movement of the first core-pulling mechanism is monitored in real time. The position coordinates of the first core-pulling mechanism are correlated with the pressure change data of the non-corresponding cavities. The ratio of the pressure change data to the position change of the first core-pulling mechanism is extracted to determine the cross-influence coefficient. The correspondence between the cross-influence coefficient and the position coordinates constitutes the cross-influence mapping relationship between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity. Extract the location coordinates where the cross-influence coefficient reaches its maximum value from the cross-influence mapping relationship. Then, perform spatial integration on the cross-influence coefficients of all core-pulling mechanisms within a preset spatial range around the location coordinates to obtain the spatial location corresponding to the maximum value of the spatial integration, which is then identified as the interference-sensitive location.

[0007] In one optional embodiment, a cross section passing through the interference-sensitive location is constructed, the motion trajectories of each core-pulling mechanism are projected onto the cross section and an envelope is constructed, and the synchronization control reference point is determined by: Extract the complete motion trajectory of each core-pulling mechanism from the starting position to the ending position, calculate the tangent direction vector of each complete motion trajectory at the interference-sensitive position, and perform vector weighted average of all tangent direction vectors to obtain the composite motion direction vector. Construct a plane perpendicular to the composite motion direction vector with the interference-sensitive position as the origin, and determine the plane as the cross section passing through the interference-sensitive position. Discrete spatial points on each complete motion trajectory are projected onto the cross section along a direction parallel to the direction vector of the composite motion to obtain a set of discrete projection points of each core-pulling mechanism on the cross section. The sets of discrete projection points are sequentially connected to form a projection trajectory. The outermost boundary points of all projection trajectories are extracted and sequentially connected in circumferential order to form a closed curve, and the envelope of the projection trajectory is determined. A two-dimensional plane coordinate system is established on the cross section. The average coordinate value of all points within the area enclosed by the envelope of the projected trajectory is calculated. The plane position point corresponding to the average coordinate value is mapped back to the three-dimensional space along the opposite direction of the composite motion direction vector to obtain the three-dimensional space coordinate point and determine the synchronous control reference point.

[0008] In one optional embodiment, using the synchronous control reference point as the dividing node, the motion stroke of each core-pulling mechanism is divided into a front stroke and a rear stroke; based on the distribution of resistance response characteristic points in the front and rear strokes, the lead amount of the front trajectory or the lag amount of the rear trajectory is determined, and the segmented motion trajectory of each core-pulling mechanism is generated, including: Using the synchronous control reference point as the central node, the initial trajectory of each core-pulling mechanism from the starting position to the synchronous control reference point, and the subsequent trajectory from the synchronous control reference point to the ending position are planned respectively. Collect the normal pressure distribution data of the core surface in the cavity corresponding to each core pulling mechanism, identify the local maximum points in the normal pressure distribution data, screen out the local maximum points where the cavity cross-sectional shrinkage rate exceeds the preset shrinkage threshold, and determine the resistance response characteristic points. The number of resistance response characteristic points of each core-pulling mechanism in the first and second strokes is counted, and the ratio of the number of resistance response characteristic points in the first stroke to the number of resistance response characteristic points in the second stroke is calculated to obtain the resistance stroke distribution ratio of each core-pulling mechanism. When the resistance stroke distribution ratio is greater than 1, measure the time it takes for the core-pulling mechanism to move from the starting position to the last resistance response characteristic point of the first stroke to determine the lead amount of the first trajectory. When the resistance stroke distribution ratio is less than 1, measure the time it takes for the core-pulling mechanism to move from the first resistance response characteristic point in the latter part of the stroke to the termination position to determine the hysteresis of the latter part of the trajectory. The leading and trailing trajectories are adjusted based on the lead and lag amounts, and then connected at the synchronous control reference point to generate the segmented motion trajectories of each core-pulling mechanism.

[0009] In one optional embodiment, counting the number of resistance response characteristic points of each core-pulling mechanism in the first and second stages of the stroke includes: For each resistance response feature point identified by each core-pulling mechanism during the core-pulling stroke, the resistance response feature points are sorted and numbered in the order from the starting position to the ending position in the core-pulling direction. Extract the cavity region between two adjacent resistance response feature points as a transfer segment. In this transfer segment, collect the distribution gradient of melt pressure along the core pulling direction. When the pressure distribution gradient is monotonically decreasing and the gradient value exceeds the preset gradient threshold, mark the latter resistance response feature point as the pressure transfer derivative point of the former resistance response feature point. Identify resistance response feature points that are not marked as pressure transmission derivative points, determine independent resistance source points, and when counting the number of resistance response feature points of each core-pulling mechanism in the front and rear trajectories, only count the number of independent resistance source points.

[0010] In one optional embodiment, the spatial gradient vector of the pressure distribution in each cavity is collected. The delayed pressure response amplitude is calculated based on the spatial gradient vector and the spatial adjacency relationship of the cavities. A velocity coupling transfer matrix is ​​constructed using the delayed pressure response amplitude. The target velocity vector is obtained by performing matrix operations on the current velocity, including: During the movement of each core-pulling mechanism, pressure distribution data along the core-pulling direction in each cavity is collected, and spatial differentiation is performed on the pressure distribution data to obtain the pressure spatial gradient vector. Extract the projection component of the pressure spatial gradient vector in the motion direction of each core-pulling mechanism, multiply the projection component with the current motion speed of the corresponding core-pulling mechanism to obtain the pressure fluctuation propagation rate generated by the core-pulling mechanism, and calculate the propagation delay of the pressure fluctuation generated by each core-pulling mechanism to reach the adjacent cavity based on the spatial adjacency relationship between each cavity and the pressure fluctuation propagation rate. The propagation rate and propagation delay of the pressure fluctuation generated by each core-pulling mechanism are convolved to obtain the delayed pressure response amplitude of each core-pulling mechanism to the adjacent cavity. The velocity coupling weight factor is determined, and the velocity coupling transfer matrix between each core-pulling mechanism is constructed. Obtain the motion speed of each core-pulling mechanism at the current moment, form a current speed column vector, and perform matrix multiplication operation between the current speed column vector and the speed coupling transfer matrix to obtain the speed compensation amount of each core-pulling mechanism affected by the delayed pressure response of the adjacent core-pulling mechanism. The current speed of each core-pulling mechanism is superimposed with the corresponding speed compensation amount to obtain the target speed vector of each core-pulling mechanism.

[0011] In one optional embodiment, the propagation delay of pressure fluctuations generated by each core-pulling mechanism reaching adjacent cavities is calculated based on the spatial adjacency relationship between cavities and the pressure fluctuation propagation rate, including: Construct a topological graph of spatial adjacency relationships between cavities, with each cavity as a node and the melt connection channels between cavities as edges, and identify all melt connection paths between the corresponding cavity of each core-pulling mechanism and adjacent cavities; For each melt connection path, the spatial length of the melt connection path is measured, and the melt flow resistance on the melt connection path is calculated. The basic propagation delay is calculated based on the spatial length and the pressure fluctuation propagation rate. The basic propagation delay is corrected according to the melt flow resistance to obtain the pressure fluctuation propagation delay of the melt connection path. The propagation delay of pressure fluctuations in each melt connection path is sorted, and the main path with the shortest propagation delay and the second shortest secondary path are extracted. The difference in propagation delay between the main path and the secondary path is calculated. When the propagation delay difference is less than the preset delay threshold, the pressure fluctuation propagation delay of the main path and the pressure fluctuation propagation delay of the secondary path are weighted and averaged according to their respective pressure fluctuation propagation rates to obtain the equivalent propagation delay of the multi-path superposition effect, and the propagation delay of the pressure fluctuation generated by each core pulling mechanism to the adjacent cavity is determined.

[0012] A second aspect of the present invention provides a multi-point synchronous intelligent control molding system for a core-pulling mechanism of a plastic pallet injection mold, comprising: The data acquisition module is used to acquire the position information of multiple core-pulling mechanisms and the pressure information of the corresponding cavities; The interference identification module is used to establish a cross-influence mapping relationship between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity when each core-pulling mechanism performs the test stroke, extract the extreme value position of the cross-influence coefficient from the cross-influence mapping relationship, determine the interference-sensitive position, construct a cross section passing through the interference-sensitive position, project the motion trajectory of each core-pulling mechanism onto the cross section and construct the envelope, and determine the synchronization control reference point. The trajectory planning module is used to divide the motion stroke of each core-pulling mechanism into a front stroke and a rear stroke, with the synchronous control reference point as the dividing node; based on the distribution of resistance response characteristic points in the front stroke and the rear stroke, the lead amount of the front trajectory or the lag amount of the rear trajectory is determined, and the segmented motion trajectory of each core-pulling mechanism is generated. The velocity coupling module is used to collect the spatial gradient vector of the pressure distribution in each cavity, calculate the delayed pressure response amplitude based on the spatial gradient vector and the spatial adjacency relationship of the cavity, construct the velocity coupling transfer matrix based on the delayed pressure response amplitude, and perform matrix operations on the current velocity to obtain the target velocity vector. The synchronous execution module is used to drive each core-pulling mechanism to perform core-pulling actions synchronously according to the segmented motion trajectory and the target velocity vector, so as to complete the demolding and forming of the plastic tray.

[0013] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0014] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0015] In this embodiment of the invention, by establishing a cross-influence mapping relationship between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity, the interference-sensitive position is effectively identified, solving the technical problem that traditional core-pulling control methods cannot accurately consider the mutual influence between the core-pulling mechanisms. Based on the interference-sensitive position, a cross section is constructed and a synchronous control reference point is determined, realizing the precise positioning of key nodes in the core-pulling process and providing a scientific basis for the segmented control strategy. By adopting a segmented motion trajectory control method, the coordination of each mechanism in the core-pulling process is optimized by adjusting the advance amount of the front trajectory or the lag amount of the rear trajectory, effectively reducing the stress concentration phenomenon in the demolding process. By introducing spatial gradient vector and cavity spatial adjacency relationship to calculate the delayed pressure response, a velocity coupling transfer matrix is ​​constructed for real-time velocity adjustment, realizing dynamic synchronous control of the multi-point core-pulling process, significantly improving the accuracy and efficiency of plastic tray injection molding. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the multi-point synchronous intelligent control molding method for the core-pulling mechanism of a plastic pallet injection mold according to an embodiment of the present invention. Figure 2 The flowchart shows the three-stage calculation process for the synchronous control reference point of the core-pulling mechanism. Detailed Implementation

[0017] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] The technical solution of the present invention will be described in detail below with reference to specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0019] Figure 1 This is a flowchart illustrating the multi-point synchronous intelligent control molding method for the core-pulling mechanism of a plastic pallet injection mold according to an embodiment of the present invention. Figure 1 As shown, the method includes: Obtain the position information of multiple core-pulling mechanisms and the pressure information of the corresponding cavities; When each core-pulling mechanism performs the test stroke, a cross-influence mapping relationship between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity is established. The extreme value position of the cross-influence coefficient is extracted from the cross-influence mapping relationship to determine the interference-sensitive position. A cross section passing through the interference-sensitive position is constructed, and the motion trajectory of each core-pulling mechanism is projected onto the cross section and an envelope is constructed to determine the synchronous control reference point. Using the synchronous control reference point as the dividing node, the motion stroke of each core-pulling mechanism is divided into the front stroke and the back stroke; based on the distribution of resistance response characteristic points in the front stroke and the back stroke, the lead amount of the front trajectory or the lag amount of the back trajectory is determined, and the segmented motion trajectory of each core-pulling mechanism is generated. Collect the spatial gradient vector of the pressure distribution in each cavity, calculate the delayed pressure response amplitude based on the spatial gradient vector and the spatial adjacency relationship of the cavity, construct the velocity coupling transfer matrix with the delayed pressure response amplitude, and perform matrix operations on the current velocity to obtain the target velocity vector; Based on the segmented motion trajectory and the target velocity vector, each core-pulling mechanism is driven to synchronously perform the core-pulling action, thereby completing the demolding and forming of the plastic tray.

[0020] In one optional implementation, when each core-pulling mechanism performs its test stroke, a cross-influence mapping relationship is established between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity. The extreme value positions of the cross-influence coefficient are extracted from the cross-influence mapping relationship, and the interference-sensitive positions are determined, including: When each core-pulling mechanism performs the test stroke, the first core-pulling mechanism is driven to move independently in sequence, while the other core-pulling mechanisms remain stationary. The pressure change data of non-corresponding cavities during the movement of the first core-pulling mechanism is monitored in real time. The position coordinates of the first core-pulling mechanism are correlated with the pressure change data of the non-corresponding cavities. The ratio of the pressure change data to the position change of the first core-pulling mechanism is extracted to determine the cross-influence coefficient. The correspondence between the cross-influence coefficient and the position coordinates constitutes the cross-influence mapping relationship between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity. Extract the location coordinates where the cross-influence coefficient reaches its maximum value from the cross-influence mapping relationship. Then, perform spatial integration on the cross-influence coefficients of all core-pulling mechanisms within a preset spatial range around the location coordinates to obtain the spatial location corresponding to the maximum value of the spatial integration, which is then identified as the interference-sensitive location.

[0021] In one specific embodiment, the testing apparatus includes multiple core-pulling mechanisms, pressure sensors, position encoders, and a data acquisition system. Taking four core-pulling mechanisms as an example, named Core-pulling Mechanism 1, Core-pulling Mechanism 2, Core-pulling Mechanism 3, and Core-pulling Mechanism 4 respectively, each core-pulling mechanism controls the molding of a cavity area. A high-precision pressure sensor is installed in each cavity, with a sampling frequency of not less than 1000Hz and an accuracy of 0.01MPa. Each core-pulling mechanism is equipped with a position encoder with a resolution of 0.001mm for real-time recording of the position coordinates of the core-pulling mechanism.

[0022] Before the test, install the injection mold on the injection molding machine, set the mold temperature to 80℃, the injection machine barrel temperature to 220℃, the injection pressure to 15MPa, the holding pressure to 12MPa, the holding time to 15 seconds, and the cooling time to 30 seconds. Ensure that the temperature of all parts of the mold is uniform and that there are no residual impurities in the cavity.

[0023] During the test, core-pulling mechanism 1 was driven to move independently at a speed of 10 mm / s, with a stroke range from 0 mm to a maximum stroke of 100 mm. Meanwhile, core-pulling mechanisms 2, 3, and 4 remained stationary. The data acquisition system simultaneously recorded the position coordinates of core-pulling mechanism 1 and the pressure changes within non-corresponding cavities (i.e., cavities 2, 3, and 4).

[0024] In actual measurements, when the core-pulling mechanism 1 moves from the initial position of 0mm to the position of 20mm, the pressure in cavity 2 changes from the initial value of 8.5MPa to 8.7MPa, a pressure change of 0.2MPa, while the position change is 20mm. Therefore, the cross-influence coefficient of the core-pulling mechanism 1 on cavity 2 at this position is calculated to be 0.01MPa / mm. Continuing to record data at different positions, when the core-pulling mechanism 1 moves to the position of 45mm, the pressure in cavity 2 increases to 9.2MPa, at which point the cross-influence coefficient increases to 0.0156MPa / mm. When the core-pulling mechanism 1 moves to the position of 65mm, the pressure in cavity 2 reaches its highest value of 9.5MPa, and the cross-influence coefficient at this position reaches its maximum value of 0.0169MPa / mm.

[0025] Similarly, by measuring the pressure effect of the core-pulling mechanism 1 on cavities 3 and 4, the cross-influence coefficients at the corresponding positions are obtained. For example, at a position of 65mm on the core-pulling mechanism 1, the cross-influence coefficient for cavity 3 is 0.0142MPa / mm, and the cross-influence coefficient for cavity 4 is 0.0108MPa / mm.

[0026] After completing the test of core-pulling mechanism 1, the pressure effects of core-pulling mechanisms 2, 3, and 4 on non-corresponding cavities were tested using the same method. For example, when core-pulling mechanism 2 was driven to move alone, the pressure change data of cavities 1, 3, and 4 were recorded; when core-pulling mechanism 3 was driven to move alone, the pressure change data of cavities 1, 2, and 4 were recorded; when core-pulling mechanism 4 was driven to move alone, the pressure change data of cavities 1, 2, and 3 were recorded.

[0027] Through these tests, a complete cross-influence mapping table was established, which includes the pressure influence coefficient of each core-pulling mechanism on non-corresponding cavities at different positions. For example, the cross-influence coefficient of core-pulling mechanism 1 on cavity 2 at position coordinates (65mm, 0mm, 0mm) is 0.0169MPa / mm, and the cross-influence coefficient of core-pulling mechanism 2 on cavity 1 at position coordinates (0mm, 58mm, 0mm) is 0.0185MPa / mm, etc.

[0028] The coordinates of the location where the cross-influence coefficient of each core-pulling mechanism reaches its maximum value on non-corresponding cavities are extracted from the test data. Taking core-pulling mechanism 1 as an example, the location where the cross-influence coefficient reaches its maximum value is 65mm. A preset spatial range with a radius of 5mm is set around this location, and the spatial integration calculation is performed on the cross-influence coefficients of all core-pulling mechanisms within this spatial range.

[0029] The spatial integral calculation method involves dividing a preset spatial range into several tiny cubes, each with a side length of 0.1 mm. The weighted average of the cross-influence coefficients of each core-pulling mechanism on non-corresponding cavities within each tiny cube is calculated. The weighting coefficients are set according to actual process requirements; for example, the weight for cavity 1 is 0.3, for cavity 2 it is 0.25, for cavity 3 it is 0.25, and for cavity 4 it is 0.2. The weighted average values ​​within all tiny cubes are then summed to obtain the spatial integral value for the entire preset spatial range.

[0030] Calculations revealed that when core-pulling mechanism 1 is located at 63mm, the spatial integral value reaches its maximum of 15.75 MPa·mm, which is higher than the spatial integral values ​​at adjacent locations. Therefore, the interference-sensitive position of core-pulling mechanism 1 is determined to be 63mm. Similarly, the interference-sensitive positions of core-pulling mechanism 2, 3, and 4 are determined to be 55mm, 68mm, and 59mm, respectively.

[0031] In practical applications, when multiple core-pulling mechanisms move simultaneously, the control system adjusts the speed and acceleration of each mechanism based on the measured cross-influence mapping relationship and interference-sensitive location information. This prevents multiple mechanisms from being simultaneously located at interference-sensitive positions, reducing pressure fluctuations caused by cross-influence. For example, when core-pulling mechanism 1 approaches the interference-sensitive position by 63mm, the control system reduces its speed and accelerates the speeds of other core-pulling mechanisms, causing them to stagger their interference-sensitive positions and thus reducing the overall degree of cross-interference.

[0032] In one optional implementation, a cross-section passing through the interference-sensitive location is constructed, the motion trajectories of each core-pulling mechanism are projected onto the cross-section and an envelope is constructed, and the synchronization control reference point is determined by: Extract the complete motion trajectory of each core-pulling mechanism from the starting position to the ending position, calculate the tangent direction vector of each complete motion trajectory at the interference-sensitive position, and perform vector weighted average of all tangent direction vectors to obtain the composite motion direction vector. Construct a plane perpendicular to the composite motion direction vector with the interference-sensitive position as the origin, and determine the plane as the cross section passing through the interference-sensitive position. Discrete spatial points on each complete motion trajectory are projected onto the cross section along a direction parallel to the direction vector of the composite motion to obtain a set of discrete projection points of each core-pulling mechanism on the cross section. The sets of discrete projection points are sequentially connected to form a projection trajectory. The outermost boundary points of all projection trajectories are extracted and sequentially connected in circumferential order to form a closed curve, and the envelope of the projection trajectory is determined. A two-dimensional plane coordinate system is established on the cross section. The average coordinate value of all points within the area enclosed by the envelope of the projected trajectory is calculated. The plane position point corresponding to the average coordinate value is mapped back to the three-dimensional space along the opposite direction of the composite motion direction vector to obtain the three-dimensional space coordinate point and determine the synchronous control reference point.

[0033] In one specific implementation, for multiple core-pulling mechanisms in the mold, the complete motion trajectory of each core-pulling mechanism is extracted. Here, the complete motion trajectory refers to the spatial path of the core-pulling mechanism from its starting position to its ending position. This path can be obtained through motion simulation in mold design software or calculated from the geometric parameters and motion equations of the core-pulling mechanism. Each trajectory consists of a series of three-dimensional spatial coordinate points, arranged in chronological order to form a sequence of spatial positions of the core-pulling mechanism during its motion.

[0034] Identifying interference-sensitive locations in the mold is crucial. These locations typically refer to spatial areas where multiple core-pulling mechanisms might collide or interfere with each other, making them particularly important in mold design. They can be identified by analyzing the intersection areas of the core-pulling mechanism's motion trajectories or by pre-defining them based on design experience. In practical applications, multiple interference-sensitive locations may exist; in such cases, subsequent steps can be performed separately for each sensitive location.

[0035] For the identified interference-sensitive locations, the tangent direction vector of the motion trajectory of each core-pulling mechanism at that location is calculated. Specifically, for the motion trajectory of each core-pulling mechanism, the trajectory point closest to the interference-sensitive location is found, and then the tangent direction at that point is calculated. The tangent direction can be approximated by the difference between adjacent trajectory points; that is, if the sequence of trajectory points is P1, P2, ..., P... n And P i If the point is the closest to the interference-sensitive location, then the tangent direction vector can be expressed as the normalized (P) 1+1 -P i-1 ).

[0036] After obtaining the tangent direction vectors of the motion trajectories of each core-pulling mechanism, a weighted average is performed to obtain the composite motion direction vector. The weighting coefficients can be determined based on the importance of each core-pulling mechanism, its motion frequency, or other design considerations. For example, if there are three core-pulling mechanisms with tangent direction vectors v1, v2, and v3, and corresponding weights w1, w2, and w3, then the composite motion direction vector v... m =(w1×v1+w2×v2+w3×v3) / |w1×v1+w2×v2+w3×v3|, where |·| represents the magnitude of the vector, ensuring that the synthesized vector is a unit vector.

[0037] Using the disturbance-sensitive location as the origin, a plane perpendicular to the resultant motion direction vector is constructed as the cross section for subsequent analysis. This plane can be determined by the point-normal form equation, i.e., the vector (PO) between any point P on the plane and the disturbance-sensitive location O, and the resultant motion direction vector v. m The dot product is zero.

[0038] The complete motion trajectory of each core-pulling mechanism is projected onto the aforementioned defined cross-section. Specifically, for each discrete point on the motion trajectory of each core-pulling mechanism, a straight line is drawn along a direction parallel to the composite motion direction vector; the intersection of this line and the cross-section is the projection point of that point onto the cross-section. In this way, the motion trajectory in three-dimensional space can be mapped to a two-dimensional trajectory on the cross-section.

[0039] For each core-pulling mechanism, the projection points of its motion trajectory on the cross section are connected in chronological order of the original trajectory points to form a projected trajectory. These projected trajectories reflect the motion characteristics of the core-pulling mechanism on a plane perpendicular to the direction of the composite motion.

[0040] Extract the outermost boundary points of all projected trajectories; these boundary points are crucial for defining the motion space boundaries of the core-pulling mechanism. Convex hull or Alpha shape algorithms can be used to identify these boundary points from the set of projection points. Connect these boundary points sequentially in circumferential order to form a closed curve, i.e., the envelope of the projected trajectory.

[0041] Establish a two-dimensional plane coordinate system on the cross-section, with the origin chosen as the projection point of the disturbance-sensitive location onto the cross-section. Calculate the average coordinates of all points within the envelope region, i.e., the geometric center. This geometric center represents the equilibrium point of the core-pulling mechanism's motion space on the cross-section, which is of great significance for synchronous control.

[0042] The geometric center point determined on the cross section is mapped back to three-dimensional space along the opposite direction of the resultant motion direction vector. This can be achieved by starting from the geometric center point on the cross section and finding the intersection or closest point with the original core-pulling mechanism's motion trajectory along the opposite direction of the resultant motion direction vector. This mapped three-dimensional space point is the required synchronization control reference point, located near the spatial geometric center of each core-pulling mechanism's motion trajectory, and can serve as a reference point for coordinating the motion of multiple core-pulling mechanisms.

[0043] The synchronization control reference point determined by the above method can effectively coordinate the movement of multiple core-pulling mechanisms, avoiding collisions or interference at sensitive locations and improving the stability and safety of mold operation. This method is particularly suitable for complex mold designs where multiple core-pulling mechanisms need to work collaboratively.

[0044] like Figure 2 As shown, the flowchart illustrates the three-stage calculation process for the synchronous control reference point of the core-pulling mechanism.

[0045] In one optional implementation, using the synchronous control reference point as the dividing node, the motion stroke of each core-pulling mechanism is divided into a front stroke and a rear stroke; based on the distribution of resistance response characteristic points in the front and rear strokes, the lead amount of the front trajectory or the lag amount of the rear trajectory is determined, and the segmented motion trajectory of each core-pulling mechanism is generated, including: Using the synchronous control reference point as the central node, the initial trajectory of each core-pulling mechanism from the starting position to the synchronous control reference point, and the subsequent trajectory from the synchronous control reference point to the ending position are planned respectively. Collect the normal pressure distribution data of the core surface in the cavity corresponding to each core pulling mechanism, identify the local maximum points in the normal pressure distribution data, screen out the local maximum points where the cavity cross-sectional shrinkage rate exceeds the preset shrinkage threshold, and determine the resistance response characteristic points. The number of resistance response characteristic points of each core-pulling mechanism in the first and second strokes is counted, and the ratio of the number of resistance response characteristic points in the first stroke to the number of resistance response characteristic points in the second stroke is calculated to obtain the resistance stroke distribution ratio of each core-pulling mechanism. When the resistance stroke distribution ratio is greater than 1, measure the time it takes for the core-pulling mechanism to move from the starting position to the last resistance response characteristic point of the first stroke to determine the lead amount of the first trajectory. When the resistance stroke distribution ratio is less than 1, measure the time it takes for the core-pulling mechanism to move from the first resistance response characteristic point in the latter part of the stroke to the termination position to determine the hysteresis of the latter part of the trajectory. The leading and trailing trajectories are adjusted based on the lead and lag amounts, and then connected at the synchronous control reference point to generate the segmented motion trajectories of each core-pulling mechanism.

[0046] In one specific implementation, after obtaining the synchronization control reference point, the initial trajectory of each core-pulling mechanism from the starting position to the synchronization control reference point, and the subsequent trajectory from the synchronization control reference point to the ending position are planned respectively. The initial trajectory typically adopts a motion mode with constant acceleration, while the subsequent trajectory selects a uniform speed or deceleration mode according to the cavity characteristics to ensure that the change in resistance within the cavity is controllable.

[0047] To accurately identify resistance response characteristic points, it is necessary to collect normal pressure distribution data on the surface of the core within the corresponding cavity of each core-pulling mechanism. This data can be collected by installing an array of pressure sensors on the core surface to record pressure changes in real time during the core-pulling process. The sampling frequency is typically set to over 100 times per second to ensure data continuity and integrity.

[0048] The collected pressure distribution data is processed to identify local maxima. Local maxima can be identified using a sliding window method: within a fixed-width data window, the point with the highest pressure value is searched; if the pressure value at that point is greater than the pressure value at the window boundary, it is considered a local maximum. The window width is typically set to 5% to 10% of the core diameter to ensure accurate capture of local pressure changes.

[0049] Among the identified local maxima, points where the cavity cross-sectional shrinkage rate exceeds a preset shrinkage threshold are further selected and identified as resistance response characteristic points. The preset shrinkage threshold is typically set to 5% to 15%, and the specific value can be adjusted according to the flow characteristics of the molding material and the complexity of the product structure. The cavity cross-sectional shrinkage rate is calculated based on the cavity geometric model by comparing the rate of change of the cavity cross-sectional area at adjacent locations.

[0050] After obtaining the resistance response characteristic points, the distribution of these points in the initial and subsequent strokes of each core-pulling mechanism is statistically analyzed. The ratio of the number of resistance response characteristic points in the initial stroke to the number in the subsequent stroke is calculated to obtain the resistance stroke distribution ratio for each core-pulling mechanism. The resistance stroke distribution ratio reflects the unevenness of resistance distribution during core pulling and is an important basis for adjusting the motion trajectory.

[0051] When the resistance-stroke distribution ratio is greater than 1, it indicates that there are many resistance response characteristic points in the initial stroke, and the core-pulling mechanism experiences more frequent resistance changes in the initial stroke. In this case, it is necessary to measure the time it takes for the core-pulling mechanism to move from the starting position to the last resistance response characteristic point in the initial stroke; this time value is used as the lead time for the initial trajectory. The lead time is usually measured in milliseconds and is used to adjust the timing of the initial trajectory, enabling the core-pulling mechanism to complete its movement earlier in the section where resistance changes frequently.

[0052] When the resistance stroke distribution ratio is less than 1, it indicates that there are more resistance response characteristic points in the latter part of the stroke, and the resistance change of the core-pulling mechanism is more significant in the latter part of the stroke. In this case, the time it takes for the core-pulling mechanism to move from the first resistance response characteristic point in the latter part of the stroke to the termination position is measured. This time value is used as the hysteresis of the latter part of the trajectory. The hysteresis is also measured in milliseconds and is used to adjust the motion timing of the latter part of the trajectory, enabling the core-pulling mechanism to start the motion of the latter part of the stroke at the appropriate time and avoiding excessive motion impact in the resistance peak section.

[0053] Based on the aforementioned lead and lag amounts, the front and rear trajectories of each core-pulling mechanism are adjusted. The adjusted end time of the front trajectory is equal to the original end time minus the lead amount; the adjusted start time of the rear trajectory is equal to the original start time plus the lag amount. During the adjustment process, the connectivity between the front and rear trajectories at the synchronous control reference point is maintained to ensure the continuity and smoothness of the trajectory.

[0054] The adjusted front and rear trajectories are connected at the synchronous control reference point to generate the complete segmented motion trajectory of each core-pulling mechanism. The smooth connection of the segmented motion trajectories can be achieved through cubic spline interpolation to ensure the continuity of velocity and acceleration at the connection point and avoid abrupt changes during the motion process.

[0055] In practical applications, a certain injection mold contains three core-pulling mechanisms, responsible for molding the sidewalls, bottom, and top structures of the product, respectively. Using the method described above, the resistance-stroke distribution ratio of the first core-pulling mechanism was identified as 1.8, with a calculated lead time of 120 milliseconds; the resistance-stroke distribution ratio of the second core-pulling mechanism was 0.6, with a calculated lag time of 80 milliseconds; and the resistance-stroke distribution ratio of the third core-pulling mechanism was 1.2, with a calculated lead time of 50 milliseconds. Based on this, the motion trajectories of the three core-pulling mechanisms were adjusted to achieve synchronization at the synchronous control reference point, effectively avoiding mold wear and product defects caused by uneven resistance distribution in traditional isochronous synchronous control methods.

[0056] Through the technical solutions described above, the motion trajectory of the multi-core-pulling mechanism can be precisely controlled according to the resistance distribution characteristics within the cavity during the injection molding process, thereby achieving synchronous control based on resistance response and improving product quality and production efficiency.

[0057] In one optional implementation, counting the number of resistance response characteristic points of each core-pulling mechanism in the first and second stages of the stroke includes: For each resistance response feature point identified by each core-pulling mechanism during the core-pulling stroke, the resistance response feature points are sorted and numbered in the order from the starting position to the ending position in the core-pulling direction. Extract the cavity region between two adjacent resistance response feature points as a transfer segment. In this transfer segment, collect the distribution gradient of melt pressure along the core pulling direction. When the pressure distribution gradient is monotonically decreasing and the gradient value exceeds the preset gradient threshold, mark the latter resistance response feature point as the pressure transfer derivative point of the former resistance response feature point. Identify resistance response feature points that are not marked as pressure transmission derivative points, determine independent resistance source points, and when counting the number of resistance response feature points of each core-pulling mechanism in the front and rear trajectories, only count the number of independent resistance source points.

[0058] In one specific implementation, a force sensor mounted on the core-pulling mechanism collects core-pulling resistance data in real time during the core-pulling process. The sampling frequency can be set to 100 times per second to ensure that subtle resistance changes during the core-pulling process can be captured. Simultaneously, a displacement sensor records the real-time position information of the core-pulling mechanism, establishing a correspondence between resistance and position.

[0059] After data acquisition, the raw resistance data undergoes preprocessing, including noise reduction and smoothing. A moving average filtering method can be used, selecting a window width of 5 sampling points to eliminate random noise interference with subsequent feature point identification.

[0060] Based on the processed resistance-position curve, characteristic points of the resistance response are identified. Characteristic point identification employs a differential method, specifically calculating the first and second derivatives of the resistance with respect to position. A point is considered a resistance extremum when the first derivative is zero and the second derivative is not zero; a point is considered a resistance abrupt change point when the rate of change of resistance exceeds a preset threshold (e.g., 10 N / mm). Both extrema and abrupt change points are used as characteristic points of the resistance response.

[0061] The identified resistance response feature points are sorted and numbered in order from the starting position to the ending position according to the core-pulling direction. For example, for a core-pulling mechanism with five feature points, the feature points are labeled P1, P2, P3, P4, and P5 sequentially from the starting position to the ending position.

[0062] The cavity region between two adjacent resistance response feature points is extracted as a transfer segment. For example, the region between P1 and P2 is defined as transfer segment T1-2, the region between P2 and P3 is defined as transfer segment T2-3, and so on. Within each transfer segment, melt pressure data points are collected at 0.5 mm intervals to form a pressure distribution curve.

[0063] Analyze the pressure distribution curve within each transmission section and calculate the pressure distribution gradient along the core-pulling direction. The pressure gradient can be calculated by dividing the pressure difference between two adjacent points by their position difference. Determine whether the pressure distribution gradient is monotonically decreasing and whether the gradient value exceeds a preset gradient threshold (e.g., 5 MPa / mm).

[0064] When the pressure distribution gradient within a certain transmission segment satisfies the condition of monotonically decreasing and exceeding a preset gradient threshold, the resistance response characteristic point at the latter end of the transmission segment is marked as the "pressure transmission derivative point" of the previous resistance response characteristic point. For example, if the pressure gradient within the T1-2 transmission segment satisfies the condition, then P2 is marked as the pressure transmission derivative point of P1.

[0065] Identify all resistance response feature points that are not marked as "pressure transmission derivative points" and define them as "independent resistance source points". These independent resistance source points represent the true source of resistance during core pulling, rather than derivative effects caused by pressure transmission from other resistance sources.

[0066] Based on the stroke characteristics of the core-pulling mechanism, the entire core-pulling stroke is divided into a front stroke and a rear stroke. The front stroke typically corresponds to the initial stage of core pulling, while the rear stroke corresponds to the stage nearing completion. This division can be based on a percentage of the total core-pulling stroke, such as the first 50% being the front stroke and the last 50% being the rear stroke.

[0067] Count the number of independent resistance sources in the first and second strokes of each core-pulling mechanism. For example, for core-pulling mechanism A, if there are 3 independent resistance sources in the first stroke and 2 independent resistance sources in the second stroke, then record it as 3 in the first stroke and 2 in the second stroke.

[0068] For the statistical results of multiple core-pulling mechanisms, a comparison matrix can be established. The horizontal axis represents the number of each core-pulling mechanism, and the vertical axis is divided into the first stroke and the second stroke. The matrix elements represent the number of independent resistance sources for the corresponding core-pulling mechanism in the corresponding stroke segment.

[0069] This statistical method based on independent resistance sources eliminates interference caused by pressure transmission effects, and can more accurately reflect the actual resistance faced by each core-pulling mechanism in different stroke segments, providing a strong basis for the design optimization of core-pulling mechanisms and the formulation of core-pulling strategies.

[0070] By analyzing the statistical results, the resistance concentration of a specific core-pulling mechanism in a specific stroke segment can be identified. For example, if a core-pulling mechanism has significantly more independent resistance sources in the initial stroke than other mechanisms, it may be necessary to focus on optimizing the initial motion trajectory or related structures of that mechanism.

[0071] The method in this embodiment can also be used for anomaly detection in core-pulling mechanisms. By establishing a baseline for the distribution of independent resistance sources under normal operating conditions, potential problems can be detected in a timely manner when the number or distribution of independent resistance sources deviates significantly from the baseline during a core-pulling process, thus preventing mold damage or product quality degradation.

[0072] In one optional implementation, the spatial gradient vector of the pressure distribution in each cavity is collected. The delayed pressure response amplitude is calculated based on the spatial gradient vector and the spatial adjacency relationship of the cavities. A velocity coupling transfer matrix is ​​constructed using the delayed pressure response amplitude. The target velocity vector is obtained by performing matrix operations on the current velocity, including: During the movement of each core-pulling mechanism, pressure distribution data along the core-pulling direction in each cavity is collected, and spatial differentiation is performed on the pressure distribution data to obtain the pressure spatial gradient vector. Extract the projection component of the pressure spatial gradient vector in the motion direction of each core-pulling mechanism, multiply the projection component with the current motion speed of the corresponding core-pulling mechanism to obtain the pressure fluctuation propagation rate generated by the core-pulling mechanism, and calculate the propagation delay of the pressure fluctuation generated by each core-pulling mechanism to reach the adjacent cavity based on the spatial adjacency relationship between each cavity and the pressure fluctuation propagation rate. The propagation rate and propagation delay of the pressure fluctuation generated by each core-pulling mechanism are convolved to obtain the delayed pressure response amplitude of each core-pulling mechanism to the adjacent cavity. The velocity coupling weight factor is determined, and the velocity coupling transfer matrix between each core-pulling mechanism is constructed. Obtain the motion speed of each core-pulling mechanism at the current moment, form a current speed column vector, and perform matrix multiplication operation between the current speed column vector and the speed coupling transfer matrix to obtain the speed compensation amount of each core-pulling mechanism affected by the delayed pressure response of the adjacent core-pulling mechanism. The current speed of each core-pulling mechanism is superimposed with the corresponding speed compensation amount to obtain the target speed vector of each core-pulling mechanism.

[0073] In one specific implementation, pressure distribution data along the core-pulling direction within the cavity is collected during the movement of each core-pulling mechanism. Specifically, multiple pressure sensors are installed in each cavity, and these sensors are evenly distributed along the movement direction of the core-pulling mechanism. For example, for an injection mold with three cavities, five pressure sensors are installed in each cavity, located at different positions from the entrance of the core-pulling mechanism. When the core-pulling mechanism begins to move, these sensors collect pressure data at a frequency of one hundred times per second, forming a time-series dataset.

[0074] After acquiring the pressure data, spatial differentiation is performed to calculate the pressure spatial gradient vector. Taking a certain cavity as an example, let the positions of five measuring points along the core-pulling direction within the cavity be x1, x2, x3, x4, and x5, with corresponding pressure values ​​P1, P2, P3, P4, and P5. The pressure gradient at each position is calculated using the central difference method: the pressure gradient at position x2 is (P3-P1) / (x3-x1), and so on, to obtain the pressure gradient values ​​at each point. The pressure gradient values ​​of all points are combined to form the pressure spatial gradient vector of the cavity.

[0075] Extract the projection component of the pressure spatial gradient vector onto the motion direction of each core-pulling mechanism. Assuming the motion direction of a core-pulling mechanism is a unit vector e, the projection component of the pressure spatial gradient vector in that direction is the dot product of the two vectors. Multiply this projection component by the current motion velocity of the corresponding core-pulling mechanism to obtain the pressure fluctuation propagation rate. For example, if the motion velocity of the first core-pulling mechanism is v1, and the projection component of its generated pressure spatial gradient in the motion direction is G1, then the pressure fluctuation propagation rate generated by this mechanism is v1×G1.

[0076] The propagation delay is calculated based on the spatial adjacency of the cavities and the propagation rate of pressure fluctuations. It is assumed that the first and second cavities are adjacent, and the center-to-center distance between the two cavities is L. 12 If the propagation rate of the pressure fluctuation generated by the first core-pulling mechanism is R1, then the time delay for the pressure fluctuation to propagate from the first cavity to the second cavity is L. 12 / R1. Similarly, the propagation delay between all adjacent cavities can be calculated.

[0077] The delayed pressure response amplitude is obtained by convolving the pressure fluctuation propagation rate with the propagation delay. Specifically, the propagation rate is considered as a function r(t) that varies with time, and the propagation delay is denoted as τ. Then, the delayed pressure response amplitude can be expressed as the convolution of r(t) and the time delay function δ(t-τ). The calculated delayed pressure response amplitude represents the magnitude of the pressure influence of the movement of a core-pulling mechanism on adjacent cavities.

[0078] Based on the delayed pressure response amplitude, the velocity coupling weighting factor is determined, and a velocity coupling transfer matrix is ​​constructed. Assuming the system contains n core-pulling mechanisms, an n×n matrix M is constructed, where element M(i,j) represents the velocity influence coefficient of the j-th core-pulling mechanism on the i-th core-pulling mechanism. The diagonal elements of the matrix are set to 1, representing the contribution of the core-pulling mechanism's own velocity; the off-diagonal elements are determined based on the calculated delayed pressure response amplitude, with a larger amplitude corresponding to a larger velocity coupling weighting factor.

[0079] Obtain the current velocity of each core-pulling mechanism, forming a current velocity column vector V. Perform matrix multiplication on V and the velocity coupling transfer matrix M to obtain the velocity compensation vector ΔV. For example, for a system with three core-pulling mechanisms, the current velocity vector is V = [v1, v2, v3]. T If the velocity coupling transfer matrix is ​​M, then the velocity compensation vector ΔV = M·VV.

[0080] The target velocity vector is obtained by superimposing the current velocity of each core-pulling mechanism with its corresponding velocity compensation value. If the current velocity vector is V and the velocity compensation value vector is ΔV, then the target velocity vector is V + ΔV. This target velocity vector is then sent to the control system of each core-pulling mechanism to achieve coordinated speed adjustment.

[0081] In practical applications, an update frequency can be set, such as updating the target speed ten times per second, to ensure that the system can respond to changes in cavity pressure in real time. Furthermore, an adaptive adjustment mechanism can be introduced to automatically adjust the weighting factors in the speed coupling transfer matrix based on actual production results, further improving system stability and product quality.

[0082] The above method can effectively coordinate the movement speed of multiple core-pulling mechanisms, reduce pressure fluctuations within the mold cavity, and improve the consistency and quality of injection molded products.

[0083] In one optional implementation, the propagation delay of pressure fluctuations generated by each core-pulling mechanism to reach adjacent cavities is calculated based on the spatial adjacency relationship between each cavity and the pressure fluctuation propagation rate, including: Construct a topological graph of spatial adjacency relationships between cavities, with each cavity as a node and the melt connection channels between cavities as edges, and identify all melt connection paths between the corresponding cavity of each core-pulling mechanism and adjacent cavities; For each melt connection path, the spatial length of the melt connection path is measured, and the melt flow resistance on the melt connection path is calculated. The basic propagation delay is calculated based on the spatial length and the pressure fluctuation propagation rate. The basic propagation delay is corrected according to the melt flow resistance to obtain the pressure fluctuation propagation delay of the melt connection path. The propagation delay of pressure fluctuations in each melt connection path is sorted, and the main path with the shortest propagation delay and the second shortest secondary path are extracted. The difference in propagation delay between the main path and the secondary path is calculated. When the propagation delay difference is less than the preset delay threshold, the pressure fluctuation propagation delay of the main path and the pressure fluctuation propagation delay of the secondary path are weighted and averaged according to their respective pressure fluctuation propagation rates to obtain the equivalent propagation delay of the multi-path superposition effect, and the propagation delay of the pressure fluctuation generated by each core pulling mechanism to the adjacent cavity is determined.

[0084] In one specific implementation, to achieve multi-point synchronous intelligent control injection molding, a topological graph of cavity spatial adjacency relationships needs to be constructed. This topological graph uses each cavity as a node and the melt flow path between cavities as edges, recording the topological relationships. During the construction process, the three-dimensional data of the mold is first acquired, including the cavity positions, shapes, and connecting channel information. Spatial adjacency analysis determines mutually connected cavity pairs; two cavities are considered adjacent if there is a direct melt flow path between them. After the adjacency relationships are determined, an adjacency matrix is ​​generated to represent the overall topological structure, with the element values ​​indicating whether two cavities are connected. For example, in an injection mold containing eight cavities, cavities T1 are adjacent to T2 and T3; the corresponding positions in the adjacency matrix are marked as 1, and non-adjacent positions are marked as 0.

[0085] For each core-pulling mechanism, identify all melt connection paths between its corresponding cavity and adjacent cavities. Traverse the topology graph using a depth-first search or breadth-first search algorithm to record all possible paths from the source cavity to the target cavity. In an eight-cavity plastic pallet injection mold, core-pulling mechanism A1 corresponds to cavity T1, has melt connection paths P1 and P2 with adjacent cavity T2, and has a melt connection path P3 with cavity T3.

[0086] For each melt connection path, the spatial length is measured and the melt flow resistance is calculated. The spatial length is obtained through three-dimensional geometric calculations, including the actual length of the centerline of the connecting channel. The melt flow resistance considers factors such as changes in the channel cross-sectional area, the degree of curvature, and the wall roughness, and the resistance coefficient is calculated using fluid dynamics principles. For example, if the length of connecting path P1 is 85 mm, the cross-sectional diameter is 3.5 mm, and the curvature angle is 45 degrees, the calculated flow resistance coefficient is 1.25.

[0087] The basic propagation delay is calculated based on the spatial length and the pressure fluctuation propagation rate. The pressure fluctuation propagation rate is related to the melt material properties, temperature, and pressure, and is empirically determined under actual process conditions. The basic propagation delay equals the path length divided by the pressure fluctuation propagation rate. For polypropylene, under the conditions of a melting temperature of 220℃ and an injection pressure of 80MPa, the pressure fluctuation propagation rate is approximately 1250mm / s, and the basic propagation delay of the connected path P1 is 0.068s.

[0088] The actual pressure fluctuation propagation delay is obtained by correcting the base propagation delay based on the melt flow resistance. The correction considers the pressure attenuation and propagation velocity changes caused by flow resistance, and is performed using the product of the resistance coefficient and the base delay. The corrected propagation delay is 0.085s for path P1, 0.092s for path P2, and 0.078s for path P3.

[0089] The propagation delays of pressure fluctuations along each melt connection path are sorted, and the shortest primary path and the second shortest secondary path are extracted. For the connection between cavities T1 and T3, path P3 is the primary path; for the connection between cavities T1 and T2, path P1 is the primary path, and P2 is the secondary path. The difference in propagation delay between the primary and secondary paths is calculated. The difference in delay between the primary and secondary paths between T1 and T2 is 0.007 s.

[0090] When the difference in propagation delay is less than a preset delay threshold, the multi-path superposition effect is considered. The preset delay threshold is determined according to the injection molding process requirements, typically 0.01-0.02 s. A difference in propagation delay between the primary and secondary paths being less than the threshold indicates that pressure fluctuations will reach the target cavity almost simultaneously through multiple paths, resulting in a superposition effect. The propagation delays of the primary and secondary paths are weighted and averaged according to their respective pressure fluctuation propagation rates to obtain the equivalent propagation delay. The weighting coefficient is proportional to the pressure fluctuation propagation rate of each path. In the example above, the propagation rate of path P1 is 1180 mm / s, and the propagation rate of path P2 is 1080 mm / s; the calculated equivalent propagation delay of the multi-path superposition effect is 0.0835 s.

[0091] The propagation time delay of pressure fluctuations generated by each core-pulling mechanism to adjacent cavities is determined using the above method, forming a time delay matrix. For an eight-cavity plastic pallet injection mold, the propagation time delay from core-pulling mechanism A1 to cavity T2 is 0.0835s, and to cavity T3 is 0.078s. This propagation time delay matrix is ​​used as the basic data for multi-point synchronous control, enabling coordinated movement of the core-pulling mechanisms.

[0092] In practical applications, taking a four-cavity plastic pallet injection mold as an example, the cavities are denoted as T1, T2, T3, and T4. The melt connection channels between the cavities form a topological network. T1 is connected to T2 and T3, T2 is connected to T3 and T4, and T3 is connected to T4. The measured path length from T1 to T2 is 75 mm with a flow resistance coefficient of 1.15; the path length from T1 to T3 is 85 mm with a flow resistance coefficient of 1.08; the path length from T2 to T3 is 65 mm with a flow resistance coefficient of 1.22; the path length from T2 to T4 is 90 mm with a flow resistance coefficient of 1.18; and the path length from T3 to T4 is 70 mm with a flow resistance coefficient of 1.25. Using polypropylene material, under the process conditions, the pressure fluctuation propagation rate is 1200 mm / s. The calculated pressure propagation time delay matrix shows the following delays: T1 to T2 is 0.072 s, T1 to T3 is 0.076 s, T2 to T3 is 0.066 s, T2 to T4 is 0.089 s, and T3 to T4 is 0.073 s. The core-pulling mechanism A1 corresponds to cavity T1. When A1 is activated, the time it takes for the pressure fluctuation to propagate to other cavities is calculated using the time delay matrix, achieving precise timing control of the core-pulling action.

[0093] In pallet injection molds, there are often two or more connecting paths between adjacent cavities. For example, there is a direct connecting path P1 between cavities T2 and T3 with a length of 65mm and a propagation delay of 0.066s. There is also an indirect path P2 via T1 with a length of 160mm and a propagation delay of 0.148s. Since the delay difference of 0.082s is greater than the preset threshold of 0.015s, only the propagation delay of the main path P1 is considered. The direct path P3 between cavities T3 and T4 has a delay of 0.073s, and the indirect path P4 via T2 has a delay of 0.080s. The delay difference of 0.007s is less than the threshold. Considering the multi-path superposition effect, the equivalent propagation delay is calculated to be 0.076s.

[0094] By accurately calculating the propagation delay of pressure fluctuations, each core-pulling mechanism is ensured to operate at the appropriate time, preventing molding defects caused by pressure fluctuation interference, and improving the accuracy of multi-point core-pulling synchronous control and product quality stability.

[0095] The multi-point synchronous intelligent control molding system for the core-pulling mechanism of the plastic pallet injection mold of this invention includes: The data acquisition module is used to acquire the position information of multiple core-pulling mechanisms and the pressure information of the corresponding cavities; The interference identification module is used to establish a cross-influence mapping relationship between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity when each core-pulling mechanism performs the test stroke, extract the extreme value position of the cross-influence coefficient from the cross-influence mapping relationship, determine the interference-sensitive position, construct a cross section passing through the interference-sensitive position, project the motion trajectory of each core-pulling mechanism onto the cross section and construct the envelope, and determine the synchronization control reference point. The trajectory planning module is used to divide the motion stroke of each core-pulling mechanism into a front stroke and a rear stroke, with the synchronous control reference point as the dividing node; based on the distribution of resistance response characteristic points in the front stroke and the rear stroke, the lead amount of the front trajectory or the lag amount of the rear trajectory is determined, and the segmented motion trajectory of each core-pulling mechanism is generated. The velocity coupling module is used to collect the spatial gradient vector of the pressure distribution in each cavity, calculate the delayed pressure response amplitude based on the spatial gradient vector and the spatial adjacency relationship of the cavity, construct the velocity coupling transfer matrix based on the delayed pressure response amplitude, and perform matrix operations on the current velocity to obtain the target velocity vector. The synchronous execution module is used to drive each core-pulling mechanism to perform core-pulling actions synchronously according to the segmented motion trajectory and the target velocity vector, so as to complete the demolding and forming of the plastic tray.

[0096] A third aspect of the present invention provides an electronic device, comprising: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the aforementioned method.

[0097] A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon computer program instructions that, when executed by a processor, implement the aforementioned method.

[0098] This invention can be a method, apparatus, system, and / or computer program product. The computer program product may include a computer-readable storage medium having computer-readable program instructions loaded thereon for performing various aspects of the invention.

[0099] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-point synchronous intelligent control molding method for core-pulling mechanism of plastic pallet injection mold, characterized in that, include: Obtain the position information of multiple core-pulling mechanisms and the pressure information of the corresponding cavities; When each core-pulling mechanism performs the test stroke, a cross-influence mapping relationship between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity is established. The extreme value position of the cross-influence coefficient is extracted from the cross-influence mapping relationship to determine the interference-sensitive position. A cross section passing through the interference-sensitive position is constructed, and the motion trajectory of each core-pulling mechanism is projected onto the cross section and an envelope is constructed to determine the synchronous control reference point. Using the synchronous control reference point as the dividing node, the motion stroke of each core-pulling mechanism is divided into the front stroke and the back stroke; based on the distribution of resistance response characteristic points in the front stroke and the back stroke, the lead amount of the front trajectory or the lag amount of the back trajectory is determined, and the segmented motion trajectory of each core-pulling mechanism is generated. Collect the spatial gradient vector of the pressure distribution in each cavity, calculate the delayed pressure response amplitude based on the spatial gradient vector and the spatial adjacency relationship of the cavity, construct the velocity coupling transfer matrix with the delayed pressure response amplitude, and perform matrix operations on the current velocity to obtain the target velocity vector; Based on the segmented motion trajectory and the target velocity vector, each core-pulling mechanism is driven to synchronously perform the core-pulling action, thereby completing the demolding and forming of the plastic tray.

2. The method according to claim 1, characterized in that, During the test stroke of each core-pulling mechanism, a cross-influence mapping relationship is established between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity. The extreme value positions of the cross-influence coefficient are extracted from the cross-influence mapping relationship, and the interference-sensitive positions are determined, including: When each core-pulling mechanism performs the test stroke, the first core-pulling mechanism is driven to move independently in sequence, while the other core-pulling mechanisms remain stationary. The pressure change data of non-corresponding cavities during the movement of the first core-pulling mechanism is monitored in real time. The position coordinates of the first core-pulling mechanism are correlated with the pressure change data of the non-corresponding cavities. The ratio of the pressure change data to the position change of the first core-pulling mechanism is extracted to determine the cross-influence coefficient. The correspondence between the cross-influence coefficient and the position coordinates constitutes the cross-influence mapping relationship between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity. Extract the location coordinates where the cross-influence coefficient reaches its maximum value from the cross-influence mapping relationship. Then, perform spatial integration on the cross-influence coefficients of all core-pulling mechanisms within a preset spatial range around the location coordinates to obtain the spatial location corresponding to the maximum value of the spatial integration, which is then identified as the interference-sensitive location.

3. The method according to claim 1, characterized in that, Construct a cross section passing through the interference-sensitive location, project the motion trajectory of each core-pulling mechanism onto the cross section and construct an envelope, and determine the synchronization control reference point, including: Extract the complete motion trajectory of each core-pulling mechanism from the starting position to the ending position, calculate the tangent direction vector of each complete motion trajectory at the interference-sensitive position, and perform vector weighted average of all tangent direction vectors to obtain the composite motion direction vector. Construct a plane perpendicular to the composite motion direction vector with the interference-sensitive position as the origin, and determine the plane as the cross section passing through the interference-sensitive position. Discrete spatial points on each complete motion trajectory are projected onto the cross section along a direction parallel to the direction vector of the composite motion to obtain a set of discrete projection points of each core-pulling mechanism on the cross section. The sets of discrete projection points are sequentially connected to form a projection trajectory. The outermost boundary points of all projection trajectories are extracted and sequentially connected in circumferential order to form a closed curve, and the envelope of the projection trajectory is determined. A two-dimensional plane coordinate system is established on the cross section. The average coordinate value of all points within the area enclosed by the envelope of the projected trajectory is calculated. The plane position point corresponding to the average coordinate value is mapped back to the three-dimensional space along the opposite direction of the composite motion direction vector to obtain the three-dimensional space coordinate point and determine the synchronous control reference point.

4. The method according to claim 1, characterized in that, Using the synchronous control reference point as the dividing node, the motion stroke of each core-pulling mechanism is divided into a front stroke and a rear stroke. Based on the distribution of resistance response characteristic points in the front and rear strokes, the lead amount of the front trajectory or the lag amount of the rear trajectory is determined, generating the segmented motion trajectory of each core-pulling mechanism, including: Using the synchronous control reference point as the central node, the initial trajectory of each core-pulling mechanism from the starting position to the synchronous control reference point, and the subsequent trajectory from the synchronous control reference point to the ending position are planned respectively. Collect the normal pressure distribution data of the core surface in the cavity corresponding to each core pulling mechanism, identify the local maximum points in the normal pressure distribution data, screen out the local maximum points where the cavity cross-sectional shrinkage rate exceeds the preset shrinkage threshold, and determine the resistance response characteristic points. The number of resistance response characteristic points of each core-pulling mechanism in the first and second strokes is counted, and the ratio of the number of resistance response characteristic points in the first stroke to the number of resistance response characteristic points in the second stroke is calculated to obtain the resistance stroke distribution ratio of each core-pulling mechanism. When the resistance stroke distribution ratio is greater than 1, measure the time it takes for the core-pulling mechanism to move from the starting position to the last resistance response characteristic point of the first stroke to determine the lead amount of the first trajectory. When the resistance stroke distribution ratio is less than 1, measure the time it takes for the core-pulling mechanism to move from the first resistance response characteristic point in the latter part of the stroke to the termination position to determine the hysteresis of the latter part of the trajectory. The leading and trailing trajectories are adjusted based on the lead and lag amounts, and then connected at the synchronous control reference point to generate the segmented motion trajectories of each core-pulling mechanism.

5. The method according to claim 4, characterized in that, The number of resistance response characteristic points of each core-pulling mechanism in the first and second stages of the stroke includes: For each resistance response feature point identified by each core-pulling mechanism during the core-pulling stroke, the resistance response feature points are sorted and numbered in the order from the starting position to the ending position in the core-pulling direction. Extract the cavity region between two adjacent resistance response feature points as a transfer segment. In this transfer segment, collect the distribution gradient of melt pressure along the core pulling direction. When the pressure distribution gradient is monotonically decreasing and the gradient value exceeds the preset gradient threshold, mark the latter resistance response feature point as the pressure transfer derivative point of the former resistance response feature point. Identify resistance response feature points that are not marked as pressure transmission derivative points, determine independent resistance source points, and when counting the number of resistance response feature points of each core-pulling mechanism in the front and rear trajectories, only count the number of independent resistance source points.

6. The method according to claim 1, characterized in that, The spatial gradient vectors of the pressure distribution in each cavity are collected. The delayed pressure response amplitude is calculated based on the spatial gradient vectors and the spatial adjacency relationships of the cavities. A velocity coupling transfer matrix is ​​constructed using the delayed pressure response amplitude. The target velocity vector is obtained by performing matrix operations on the current velocity, including: During the movement of each core-pulling mechanism, pressure distribution data along the core-pulling direction in each cavity is collected, and spatial differentiation is performed on the pressure distribution data to obtain the pressure spatial gradient vector. Extract the projection component of the pressure spatial gradient vector in the motion direction of each core-pulling mechanism, multiply the projection component with the current motion speed of the corresponding core-pulling mechanism to obtain the pressure fluctuation propagation rate generated by the core-pulling mechanism, and calculate the propagation delay of the pressure fluctuation generated by each core-pulling mechanism to reach the adjacent cavity based on the spatial adjacency relationship between each cavity and the pressure fluctuation propagation rate. The propagation rate and propagation delay of the pressure fluctuation generated by each core-pulling mechanism are convolved to obtain the delayed pressure response amplitude of each core-pulling mechanism to the adjacent cavity. The velocity coupling weight factor is determined, and the velocity coupling transfer matrix between each core-pulling mechanism is constructed. Obtain the motion speed of each core-pulling mechanism at the current moment, form a current speed column vector, and perform matrix multiplication operation between the current speed column vector and the speed coupling transfer matrix to obtain the speed compensation amount of each core-pulling mechanism affected by the delayed pressure response of the adjacent core-pulling mechanism. The current speed of each core-pulling mechanism is superimposed with the corresponding speed compensation amount to obtain the target speed vector of each core-pulling mechanism.

7. The method according to claim 6, characterized in that, Based on the spatial adjacency relationship between each cavity and the propagation rate of pressure fluctuations, the propagation delay of pressure fluctuations generated by each core-pulling mechanism to reach adjacent cavities is calculated, including: Construct a topological graph of spatial adjacency relationships between cavities, with each cavity as a node and the melt connection channels between cavities as edges, and identify all melt connection paths between the corresponding cavity of each core-pulling mechanism and adjacent cavities; For each melt connection path, the spatial length of the melt connection path is measured, and the melt flow resistance on the melt connection path is calculated. The basic propagation delay is calculated based on the spatial length and the pressure fluctuation propagation rate. The basic propagation delay is corrected according to the melt flow resistance to obtain the pressure fluctuation propagation delay of the melt connection path. The propagation delay of pressure fluctuations in each melt connection path is sorted, and the main path with the shortest propagation delay and the second shortest secondary path are extracted. The difference in propagation delay between the main path and the secondary path is calculated. When the propagation delay difference is less than the preset delay threshold, the pressure fluctuation propagation delay of the main path and the pressure fluctuation propagation delay of the secondary path are weighted and averaged according to their respective pressure fluctuation propagation rates to obtain the equivalent propagation delay of the multi-path superposition effect, and the propagation delay of the pressure fluctuation generated by each core pulling mechanism to the adjacent cavity is determined.

8. A multi-point synchronous intelligent control molding system for the core-pulling mechanism of a plastic pallet injection mold, used to implement the method of any one of claims 1-7, characterized in that, include: The data acquisition module is used to acquire the position information of multiple core-pulling mechanisms and the pressure information of the corresponding cavities; The interference identification module is used to establish a cross-influence mapping relationship between the position of the core-pulling mechanism and the pressure of the non-corresponding cavity when each core-pulling mechanism performs the test stroke, extract the extreme value position of the cross-influence coefficient from the cross-influence mapping relationship, determine the interference-sensitive position, construct a cross section passing through the interference-sensitive position, project the motion trajectory of each core-pulling mechanism onto the cross section and construct the envelope, and determine the synchronization control reference point. The trajectory planning module is used to divide the motion stroke of each core-pulling mechanism into a front stroke and a rear stroke, with the synchronous control reference point as the dividing node; based on the distribution of resistance response characteristic points in the front stroke and the rear stroke, the lead amount of the front trajectory or the lag amount of the rear trajectory is determined, and the segmented motion trajectory of each core-pulling mechanism is generated. The velocity coupling module is used to collect the spatial gradient vector of the pressure distribution in each cavity, calculate the delayed pressure response amplitude based on the spatial gradient vector and the spatial adjacency relationship of the cavity, construct the velocity coupling transfer matrix based on the delayed pressure response amplitude, and perform matrix operations on the current velocity to obtain the target velocity vector. The synchronous execution module is used to drive each core-pulling mechanism to perform core-pulling actions synchronously according to the segmented motion trajectory and the target velocity vector, so as to complete the demolding and forming of the plastic tray.

9. An electronic device, characterized in that, include: processor; Memory used to store processor-executable instructions; The processor is configured to invoke instructions stored in the memory to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having computer program instructions stored thereon, characterized in that, When the computer program instructions are executed by the processor, they implement the method described in any one of claims 1 to 7.

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