A mold intelligent temperature control system and method for microfluidic chip injection molding

Abstract

The present application relates to the technical fields of microfluidic chip injection molding, and especially relates to a mold intelligent temperature control system and method for microfluidic chip injection molding, which comprises: setting a cutoff point for each independent channel based on a paragraph curvature reference value, and determining a sub-paragraph according to the cutoff point; determining a sub-paragraph category according to the paragraph length and edge distance corresponding to the sub-paragraph, and determining a region generation mode according to the quantity proportion of a sub-paragraph category, determining a sub-region based on the region generation mode, and determining whether to perform temperature control adjustment based on the temperature deviation reference value and temperature deviation change rate corresponding to the sub-region; the present application adaptively adjusts the partition according to the actual injection molding scene, and improves the temperature control precision for complex microfluidic chips.

Description

Technical Field

[0001] This invention relates to the field of microfluidic chip injection molding technology, and in particular to an intelligent temperature control system and method for molds used in microfluidic chip injection molding. Background Technology

[0002] In the injection molding process of microfluidic chips, the microchannel structures are tiny and complex in shape, placing extremely high demands on the precision and response speed of mold temperature control. Current temperature control technologies for microfluidic chip injection molds generally have limitations. Traditional temperature control systems often employ global constant temperature or fixed zone temperature control, failing to implement precise, localized, point-based, and differentiated temperature control based on channel segment type, distribution density, and defect risk level. Therefore, how to adaptively zone and achieve precise point control and intelligent temperature adjustment based on the structural characteristics of microfluidic chips has become a key technical problem urgently needing to be solved in this field.

[0003] Chinese patent application CN101863104A discloses an injection molding process for a plastic microfluidic chip. The molded microfluidic chip has a flat structure with a thickness of 1.2–1.5 mm and cross-shaped microchannels. The cross-sectional shape of the microchannels is rectangular with a depth of approximately 50 μm and a width of 30–100 μm. PMMA material is used, with a mold temperature of 85–90℃ and a melt temperature of 230–250℃. The injection speed is controlled in a slow-fast-slow manner, with a high-speed range of approximately 140 mm / s. The injection pressure is 100–130 MPa, the holding pressure is 50–70 MPa, the holding time is 2–5 s, and the cooling time is 30–40 s. After cooling, the mold is opened and the product is removed, completing the molding process. However, the above technical solution has the following problems: the mold temperature is fixed during chip molding, making it impossible to adaptively adjust according to the actual injection molding scenario. For complex microfluidic chips, the low temperature control precision is insufficient to meet the manufacturing requirements. Summary of the Invention

[0004] To address this, the present invention provides an intelligent temperature control system and method for molds used in microfluidic chip injection molding, which overcomes the problem in the prior art that the mold temperature cannot be adaptively adjusted according to the actual injection molding scenario during the microfluidic chip molding process, and that the temperature control accuracy is low for complex microfluidic chips, making it difficult to meet the preparation requirements.

[0005] To achieve the above objectives, the present invention provides an intelligent temperature control system and method for molds used in microfluidic chip injection molding, comprising: Based on the curvature reference value of the segment obtained by continuous detection through the curvature detection window, the breakpoint is set for each independent channel, and the sub-segment is determined according to the breakpoint. The sub-paragraph is classified as either a first-class or second-class sub-paragraph based on its corresponding paragraph length and edge distance, and the first-class or second-class sub-paragraph generation method is determined based on the proportion of first-class sub-paragraphs. In the first region generation method, the region granularity generation or independent region generation is determined based on the area ratio of the target cluster region and the dispersion of the target cluster region to obtain several sub-regions; In the second region generation method, the morphological point is determined as the first morphological point or the second morphological point based on whether there is a difference between the categories corresponding to the upstream and downstream paragraphs of the morphological point, and sub-regions are constructed for each first morphological point. Whether to perform temperature control adjustment is determined based on the temperature deviation reference value and the rate of change of temperature deviation corresponding to the sub-region.

[0006] Furthermore, for a single independent channel, in its corresponding curvature analysis, taking either endpoint of the independent channel as the starting point and the other endpoint as the ending point, the curvature reference value of the segment is obtained based on the curvature detection window according to a preset step size. If the cumulative value of the segment curvature reference value is greater than the preset cumulative value at a certain moment, the center point of the curvature detection window at the corresponding moment is recorded as a break point, and the sub-segment is determined based on the segments between adjacent break points and endpoints.

[0007] Furthermore, sub-paragraphs whose paragraph length is less than or equal to the preset paragraph length or whose edge distance is less than or equal to the preset edge distance are identified as a type of sub-paragraph; Sub-paragraphs whose paragraph length is greater than the preset paragraph length and whose edge distance is greater than the preset edge distance are classified as Category II sub-paragraphs.

[0008] Furthermore, for a target template where the proportion of a certain type of sub-paragraphs is greater than the preset proportion of a certain type of sub-paragraphs, the method for generating the first region is determined. For a target template where the proportion of a certain type of sub-paragraph is less than or equal to the preset proportion of a certain type of sub-paragraph, determine the execution of the second region generation method.

[0009] Furthermore, for the distribution status of regions where the area ratio of the target clustered region is greater than the area ratio of the preset region and the dispersion of the target clustered region is less than or equal to the dispersion of the preset region, the granularity of the execution region is determined. The region granularity generation includes: performing fine-grained uniform division on the target continuous region and coarse-grained uniform division on the region outside the target continuous region, so as to obtain several sub-regions respectively; Among them, the area of ​​the sub-region obtained by fine-grained uniform division is smaller than the area of ​​the sub-region obtained by coarse-grained uniform division.

[0010] Furthermore, for regions where the number of target clustered regions is less than or equal to the number of preset regions or where the dispersion of target clustered regions is greater than the dispersion of preset regions, the execution region is determined to be generated independently. Independent region generation includes: constructing regions for each type of sub-paragraph according to the paragraph evaluation value from largest to smallest to obtain several sub-regions.

[0011] Furthermore, morphological points where there are differences in paragraph category between upstream and downstream paragraphs are identified as first morphological points; For morphological points where the upstream and downstream paragraphs correspond to the same paragraph category, they are identified as second morphological points.

[0012] Furthermore, sub-regions are constructed for each first morphological point, and the area of ​​sub-regions with a historical defect probability greater than the preset historical defect probability is reduced. The decrease in area is positively correlated with the probability of historical defects.

[0013] Furthermore, for sub-regions where the temperature deviation reference value is greater than the preset temperature deviation reference value or the temperature deviation change rate is greater than the preset temperature deviation change rate, temperature control adjustment is determined.

[0014] In addition, the present invention also provides an intelligent temperature control system for molds used in injection molding of microfluidic chips, comprising: The channel analysis unit is used to set the breakpoints for each independent channel based on the segment curvature reference value obtained by continuous detection through the curvature detection window, determine the sub-segment based on the breakpoints, and determine the sub-segment category based on the corresponding segment length and edge distance. A generation analysis unit, which is connected to the channel analysis unit, is used to select either the first region generation method or the second region generation method based on the proportion of a type of sub-segments. The first generation unit, which is connected to the generation and analysis unit, is used to execute the first region generation method. Based on the area ratio of the target clustered region and the dispersion of the target clustered region, it determines whether to perform region granular generation or region independent generation to obtain several sub-regions. The second generation unit, which is connected to the generation and analysis unit, is used to determine whether the morphological point is a first morphological point or a second morphological point based on whether there is a difference between the categories corresponding to the upstream and downstream paragraphs of the morphological point, and to construct sub-regions for each first morphological point. A temperature control unit, which is connected to the first generation unit and the second generation unit respectively, is used to determine whether to perform temperature control adjustment based on the temperature deviation reference value and the temperature deviation change rate corresponding to the sub-region.

[0015] Compared with the prior art, the beneficial effect of the present invention is that the present invention obtains the curvature reference value of the segment through the curvature detection window, and sets the break point according to the curvature accumulation value, and adaptively divides the independent channel into multiple sub-segments, so that the sub-segments can be adaptively divided based on the curvature change of the flow channel. Compared with the traditional equidistant division method, this division method is more in line with the flow channel geometry of the microfluidic chip, and provides a reliable foundation for subsequent differentiated temperature control.

[0016] Furthermore, this invention classifies sub-segments by segment length and edge distance to identify a category of sub-segments that are more difficult to manufacture. The proportion of a category of sub-segments reflects the complexity of the mold and the corresponding generation method of the subsequent sub-regions. This avoids the problem of poor molding capability when facing different types of microfluidic chip molds caused by a uniform partitioning strategy.

[0017] Furthermore, in the first region generation method of the present invention, the distribution ratio of a type of sub-segment clustered regions is reflected by the area ratio of the target clustered region, and the dispersion of the clustered region is reflected by the dispersion of the clustered region. Based on the area ratio and dispersion of the target clustered region, the granularity of the region generation or the independent generation of the region is determined, thereby improving the generation accuracy of the sub-region.

[0018] Furthermore, in the second region generation method of the present invention, a sub-region is constructed with the first morphological point where the upstream and downstream segments have different categories as the core, and the historical defect probability is introduced to adjust the area of ​​the region, paying more attention to the region where the segment type changes and the flow channel shape changes drastically, thereby reducing injection molding defects.

[0019] Furthermore, when making temperature control decisions, this invention performs individual temperature control for each sub-region, and uses two criteria, temperature deviation reference value and temperature deviation change rate, to improve the sensitivity of temperature judgment, thereby achieving dynamic and precise temperature control, which is beneficial to ensuring the molding quality of microfluidic chips. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of the intelligent temperature control method for molds used in microfluidic chip injection molding according to the present invention; Figure 2 This is a flowchart illustrating how the present invention determines the sub-segment category based on the corresponding paragraph length and edge distance. Figure 3 This is a flowchart illustrating the process of determining whether to generate execution region granularity or region independently based on the area ratio and dispersion of the target cluster region in this invention. Figure 4This is a flowchart illustrating how the morphological point category is determined based on whether there is a difference between the categories corresponding to the upstream and downstream segments of the morphological point in this invention. Figure 5 This is a unit connection diagram of the intelligent temperature control system for molds used in microfluidic chip injection molding according to the present invention. Detailed Implementation

[0021] To make the objectives and advantages of this invention clearer, the invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0022] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0023] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate directions or positional relationships, are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0024] Please see Figure 1 As shown, this is a schematic diagram of the intelligent temperature control method for molds used in microfluidic chip injection molding according to the present invention. The present invention provides an intelligent temperature control method for molds used in microfluidic chip injection molding, comprising: Based on the curvature reference value of the segment obtained by continuous detection through the curvature detection window, the breakpoint is set for each independent channel, and the sub-segment is determined according to the breakpoint. The sub-paragraph is classified as either a first-class or second-class sub-paragraph based on its corresponding paragraph length and edge distance, and the first-class or second-class sub-paragraph generation method is determined based on the proportion of first-class sub-paragraphs. In the first region generation method, the region granularity generation or independent region generation is determined based on the area ratio of the target cluster region and the dispersion of the target cluster region to obtain several sub-regions; In the second region generation method, the morphological point is determined as the first morphological point or the second morphological point based on whether there is a difference between the categories corresponding to the upstream and downstream paragraphs of the morphological point, and sub-regions are constructed for each first morphological point. Whether to perform temperature control adjustment is determined based on the temperature deviation reference value and the rate of change of temperature deviation corresponding to the sub-region.

[0025] The target mold is a three-dimensional physical model of the microfluidic chip to be injection molded. The target mold contains microchannels, and the segment determination and region generation in this invention are specific to the side of the target mold corresponding to the microchannels. Several miniature electric heating rods are embedded within the target mold. These heating rods are connected to a power supply via high-temperature resistant wires through a solid-state relay (SSR) or a thyristor voltage regulator module. The temperature control unit continuously adjusts the heating power by regulating the PWM duty cycle or the thyristor conduction angle. Several miniature cooling water channels are independently arranged within the target mold, machined inside the mold template using drilling or embedding methods. Each channel has an electrically controlled flow regulating valve installed at its inlet, and its outlet is connected to the return pipe of the mold's cooling water circulation system. The temperature control unit controls the flow rate of the cooling water flowing through the zone by outputting a 4-20mA current signal or a PWM signal to adjust the opening of the flow regulating valve. Several miniature thermocouples are embedded within the target mold. The cold junction of the thermocouples is connected to a signal conditioning circuit, and the temperature signal is converted into a digital value by an analog-to-digital converter (ADC) and sent to the temperature control unit. It is easy to understand that all heating rods, flow control valves, and thermocouples can be connected to the temperature control unit via shielded cables.

[0026] Specifically, for a single independent channel, in its corresponding curvature analysis, taking either endpoint of the independent channel as the starting point and the other endpoint as the ending point, the curvature reference value of the segment is obtained based on the curvature detection window according to the preset step size. If the cumulative value of the segment curvature reference value is greater than the preset cumulative value at a certain moment, the center point of the curvature detection window at the corresponding moment is recorded as a break point, and the sub-segment is determined based on the segments between adjacent break points and endpoints.

[0027] An independent channel is two directly connected morphological points and the microchannel segment between them. The endpoints of directly connected microchannels and morphological points and the microchannel segment between them can also be constructed as independent channels. Preferably, the curvature detection window is a square window with an area of ​​0.09 mm² and a step size of 0.15 mm. It is easy to understand that the smaller the area and step size of the curvature detection window, the higher the accuracy of obtaining the segment curvature reference value. The higher the user's requirement for the accuracy of obtaining the segment curvature reference value, the smaller the area and step size of the curvature detection window should be.

[0028] For a single curvature detection window, the corresponding segment curvature reference value is calculated as: actual length of the microchannel within the window / straight-line distance between the start and end points of the microchannel within the window. For any given moment, the cumulative value of the corresponding segment curvature reference value for the curvature detection window is the sum of the segment curvature reference values ​​for each window starting from the most recently set breakpoint before the current moment. The preset cumulative value is the number of windows participating in the calculation of the cumulative value × 1.2. It can be understood that the larger the cumulative value of the segment curvature reference value, the more complex the structure of the corresponding channel segment. Therefore, breakpoints are set accordingly to avoid obtaining overly complex sub-segments that would make subsequent analysis more difficult. Thus, the greater the user's sensitivity to the structural complexity of the microchannel, the smaller the preset cumulative value.

[0029] For a single independent channel, any two adjacent breakpoints or two adjacent breakpoints and endpoints, the microchannel segment between the two points is a sub-segment.

[0030] Please see Figure 2 As shown, it is a flowchart of the present invention for determining the sub-segment category based on the paragraph length and edge distance of the sub-segment. For sub-segments whose paragraph length is less than or equal to a preset paragraph length or whose edge distance is less than or equal to a preset edge distance, they are determined to be a sub-segment of a certain type. Sub-paragraphs whose paragraph length is greater than the preset paragraph length and whose edge distance is greater than the preset edge distance are classified as Category II sub-paragraphs.

[0031] For any sub-segment, its corresponding edge distance is the shortest straight-line distance between the sub-segment and the boundary of the mold cavity. In this embodiment of the invention, the preset edge distance is 0.8mm. The smaller the edge distance, the closer the sub-segment is to the boundary area of ​​the mold cavity, the more significant the boundary heat dissipation effect, and the more drastic the temperature gradient change. Therefore, this threshold is set to distinguish between a type of sub-segment that is significantly affected by boundary heat and a type of sub-segment with a relatively stable internal thermal environment. The greater the user's sensitivity to injection molding defects caused by boundary heat, the larger the value of the preset edge distance.

[0032] The paragraph length is the length of the sub-segment. In this embodiment of the invention, the preset paragraph length is 1.5mm. It can be understood that the smaller the paragraph length, the more drastic the curvature change within a unit length of the sub-segment, the more complex the structure, the greater the melt flow resistance, and the higher the filling difficulty. Therefore, this threshold is set to identify a type of sub-segment that is complex and difficult to form. The greater the user's sensitivity to injection molding defects caused by complex microstructures, the larger the preset paragraph length value.

[0033] Please continue reading. Figures 1 to 2 As shown, for a target mold where the proportion of a certain type of sub-segment is greater than the preset proportion of a certain type of sub-segment, the first region generation method is determined to be executed. For a target template where the proportion of a certain type of sub-paragraph is less than or equal to the preset proportion of a certain type of sub-paragraph, determine the execution of the second region generation method.

[0034] The proportion of the first type of sub-segment is equal to the number of first type sub-segments / the number of second type sub-segments. In this embodiment of the invention, the proportion of the first type of sub-segment is preset to 1.0. It can be understood that the larger the proportion of the first type of sub-segment, the more complex and difficult-to-fill sub-segments there are in the mold compared to the simple sub-segments, and the higher the overall molding challenge. Therefore, it is necessary to adopt the first area generation method that focuses on the first type of sub-segments. The greater the user's sensitivity to the risk of temperature control failure caused by the overall complexity of the mold, the smaller the value of the preset proportion of the first type of sub-segment.

[0035] Please see Figure 3 As shown, it is a flowchart of the present invention for determining the granularity generation of the execution region or the independent generation of the region based on the area ratio of the target clustered region and the dispersion of the target clustered region. For the distribution state of the region where the area ratio of the target clustered region is greater than the preset area ratio and the dispersion of the target clustered region is less than or equal to the preset dispersion of the region, the granularity generation of the execution region is determined. The region granularity generation includes: performing fine-grained uniform division on the target continuous region and coarse-grained uniform division on the region outside the target continuous region, so as to obtain several sub-regions respectively; Among them, the area of ​​the sub-region obtained by fine-grained uniform division is smaller than the area of ​​the sub-region obtained by coarse-grained uniform division.

[0036] The method for identifying the target cluster area is to perform cluster analysis on each sub-segment of a class that is not included in the cluster area in a random order to construct the cluster area. For a single sub-segment of a class, the corresponding cluster analysis is to record the smallest rectangle that can include the sub-segment of that class and all sub-segments of that class that meet the construction conditions as a cluster area. The construction conditions are that the distance between the sub-segment and the corresponding paragraph of that class is less than the preset paragraph distance and it is not included in other cluster areas. For any two sub-paragraphs of type I, the corresponding paragraph distance is the minimum distance that can be directly connected between the two sub-paragraphs of type I. In this embodiment of the invention, the preset paragraph distance is 1mm. It can be understood that the smaller the paragraph distance, the tighter the gap between the two sub-paragraphs of type I, the more they tend to be continuously distributed in space, and the easier it is to form a cluster area. The more sensitive the user is to the degree of clustering of complex paragraph space, the larger the value of the preset paragraph distance.

[0037] The area ratio of the target cluster region = the sum of the areas of each target cluster region / the projected area of ​​the cavity surface of the target mold perpendicular to the horizontal plane. The dispersion of the target cluster region is the area of ​​the smallest rectangle that can include all target cluster regions.

[0038] In this embodiment of the invention, the preset area ratio is set to 0.3. A larger target cluster area ratio reflects a higher proportion of a certain type of sub-segment cluster within the target mold, leading to greater overall temperature control difficulty. This necessitates the use of a region-level granularity generation method to achieve fine-grained, differentiated temperature control for a specific type of sub-segment. The greater the user's focus on the coverage of complex areas, the smaller the preset area ratio. In this embodiment, the preset area dispersion is set to 20 mm². This indicates that a smaller target cluster area dispersion represents a more concentrated spatial distribution and smaller span of complex sub-segments, resulting in stronger thermal interaction between clusters. This makes region-level granularity generation more suitable for temperature control. Therefore, this threshold is set to work in conjunction with the area ratio to determine the temperature control strategy. The greater the user's sensitivity to the complexity of the temperature control boundary caused by the spatial dispersion of complex segments, the smaller the preset area dispersion.

[0039] The target continuous region is the smallest rectangle that can encompass all target clustered regions. Both fine-grained and coarse-grained uniform divisions result in rectangular sub-regions. The area of ​​the sub-region obtained by fine-grained uniform division is 1 mm². Fine-grained uniform division is applied to the target continuous region, where complex sub-segments are highly clustered and temperature control accuracy is required. Therefore, a smaller sub-region is used to achieve rapid response and fine adjustment to local temperature deviations. The higher the user's requirement for temperature control accuracy in the core complex region, the smaller the area of ​​the fine-grained sub-region. The area of ​​the sub-region obtained by coarse-grained uniform division is 4 mm². Coarse-grained uniform division is applied to areas outside the target continuous region, where complex sub-segments are sparse or have simple structures and lower temperature control requirements. Therefore, a larger sub-region is used to reduce control complexity. The higher the user's requirement for ease of temperature control in this region, the larger the area of ​​the coarse-grained sub-region. If there is a remaining area that is insufficient to form a complete rectangular sub-region (i.e., the area of ​​the remaining part is smaller than the area of ​​the corresponding sub-region), then the remaining area is merged into the nearest random complete sub-region and the rectangular boundary of the sub-region is expanded accordingly to fully contain the remaining area.

[0040] Please continue reading. Figures 1 to 3 As shown, for regions where the number of target clustered regions is less than or equal to the number of preset regions or the dispersion of target clustered regions is greater than the dispersion of preset regions, the execution region is determined to be generated independently. Independent region generation includes: constructing regions for each type of sub-paragraph according to the paragraph evaluation value from largest to smallest to obtain several sub-regions.

[0041] For a single sub-paragraph of category A, its corresponding paragraph evaluation value = 1 / (paragraph length × α1 + edge distance × α2), where α1 is the first weight coefficient and α2 is the second weight coefficient. In this embodiment of the invention, α1 is 0.6 and α2 is 0.4. It can be understood that the weight coefficient is used to adjust the influence weight of the corresponding paragraph length or edge distance in the paragraph evaluation value calculation. The larger the paragraph evaluation value, the higher the processing priority of a sub-paragraph of category A in the independent generation of the region. Users can set the corresponding weight coefficient values ​​based on their attention to paragraph length and edge distance.

[0042] For a single sub-segment corresponding to a sub-region, the area is calculated as: Area = Base Area × k × Segment Evaluation Value. This calculation formula is dimensionless, where k is the area adjustment coefficient. In this embodiment, k is 0.5, and the base area is 2 mm². It can be understood that the base area is the basic reference value for calculating the sub-region area, representing the sub-region area corresponding to a segment evaluation value of 1. The larger the base area, the larger the area of ​​all sub-regions, the wider the coverage of the temperature control unit, and the smaller the system's computational burden. However, the local temperature control accuracy decreases accordingly. The higher the user's requirement for local temperature control accuracy, the smaller the value of the base area. k is used to adjust the amplification or reduction effect of the segment evaluation value on the sub-region area. The smaller the value of k, the less sensitive the sub-region area is to changes in the segment evaluation value, the smaller the area difference between sub-regions, and the more uniform the temperature control strategy tends to be. The higher the user's preference for differentiated allocation of temperature control resources between complex and simple segments, the larger the value of the coefficient k.

[0043] It is worth noting that for any sub-region, at least one of its edges is parallel to the edge of the mold boundary, and the mold boundary is rectangular.

[0044] Please see Figure 4 As shown, this is a flowchart of the present invention for determining the category of a morphological point based on whether there is a difference between the categories of the upstream and downstream paragraphs corresponding to the morphological point. For morphological points where there is a difference in paragraph categories between the upstream and downstream paragraphs, they are determined as first morphological points; for morphological points where the paragraph categories of the upstream and downstream paragraphs are the same, they are determined as second morphological points.

[0045] A morphology point is a point in the microchannel where the flow direction of the melt changes. For a single morphology point, its upstream segment is a sub-segment connected to the morphology point and flowing towards the morphology point, and its downstream segment is a sub-segment connected to the morphology point and flowing away from the morphology point. If the two sub-segments have the same category, it is determined that the upstream segment and the downstream segment have the same segment category. If the two sub-segments have different categories, it is determined that the upstream segment and the downstream segment have different segment categories.

[0046] Please continue reading. Figures 1 to 4 As shown, sub-regions are constructed for each first morphological point, and the area of ​​sub-regions with a historical defect probability greater than the preset historical defect probability is reduced. The decrease in area is positively correlated with the probability of historical defects.

[0047] If the historical defect probability corresponding to a sub-region is less than or equal to the preset historical defect probability of the sub-region, then the area of ​​the sub-region does not need to be adjusted.

[0048] When constructing a sub-region corresponding to the first morphological point, a rectangle with a preset area is constructed centered on the first morphological point, and at least one side of the rectangle is parallel to the edge of the mold boundary. In this embodiment of the invention, the preset area is 2mm². It can be understood that the preset area represents the baseline coverage range of the rectangular sub-region constructed for the first morphological point. The higher the user's requirement for precise point control of the heat-sensitive area near the morphological point, the smaller the value of the preset area.

[0049] When adjusting the area of ​​a single sub-region to reduce its size, the formula for calculating the adjusted area S is as follows: S = Preset area × (1- ×γ) The historical defect probability is determined by acquiring several historical samples. Each historical sample records the location of a defect in a single microfluidic chip generated in a single cycle. The historical defect probability is calculated by dividing the number of historical samples with defects in that sub-region by the total number of historical samples. The preset historical defect probability is 0.15. This preset historical defect probability represents the baseline threshold for determining whether the sub-region needs area reduction adjustment. A higher historical defect probability indicates a higher frequency of injection molding defects in the sub-region during previous molding processes, more stringent requirements for temperature control accuracy, and a greater need for area reduction to achieve fine control. The higher the user's requirements for the molding quality pass rate, the smaller the preset historical defect probability. γ is the maximum reduction coefficient, ranging from 0.3 to 0.5. In this embodiment, γ is 0.3. The maximum reduction coefficient is used to limit the maximum proportion of the sub-region area that can be reduced due to a high historical defect probability. The higher the user's requirements for the finer temperature control of defect-sensitive areas, the larger the value of γ.

[0050] For sub-regions where the temperature deviation reference value is greater than the preset temperature deviation reference value or the temperature deviation change rate is greater than the preset temperature deviation change rate, temperature control adjustment is determined.

[0051] During the injection molding process of microfluidic chips, the temperature deviation reference value and the temperature deviation change rate are sampled once every preset monitoring duration. For a single sub-region, the acquisition method of the temperature deviation reference value is: detecting the detection values of each thermocouple in the sub-region corresponding to the current sampling moment, calculating the average value of each detection value, where the temperature deviation reference value is the absolute value of the difference between the average detection value and the preset temperature reference value, and the temperature deviation change rate = (the absolute value of the difference between the temperature deviation reference value corresponding to the current moment and the temperature deviation reference value corresponding to the last sampling) / the preset monitoring duration; In the embodiment of the present invention, the preset monitoring duration is 0.8s. It can be understood that the preset monitoring duration represents the time interval between two samplings. The shorter the duration, the more sensitive the system is to the response of temperature changes, and the more timely the temperature deviation change rate can be captured, but the calculation burden and communication load increase correspondingly. The higher the user's requirement for the sensitivity and real-time performance of temperature control, the smaller the value of the preset monitoring duration will be.

[0052] In the embodiment of the present invention, the preset temperature reference value is 88°C. It can be understood that the preset temperature reference value represents the target temperature that the sub-region should maintain under ideal injection molding working conditions, and its value is determined according to the recommended mold temperature range of the material used for the microfluidic chip, which is content already mastered by those skilled in the art and will not be repeated here.

[0053] In the embodiment of the present invention, the preset temperature deviation reference value is 1.5°C, and the preset temperature deviation change rate is 0.5°C / s. It can be understood that the preset temperature deviation reference value is the allowable upper limit of static temperature deviation, and the preset temperature deviation change rate is the allowable upper limit of dynamic change rate of temperature deviation. The higher the user's requirement for temperature anti-interference capability, the smaller the values of the preset temperature deviation reference value and the preset temperature deviation change rate will be.

[0054] When it is determined that temperature control adjustment is required for a certain sub-region, T1 and T2 are compared, where T1 is the average value of the detection values of all thermocouples in the sub-region corresponding to the current sampling moment, T2 is the preset temperature reference value, and R is the temperature deviation change rate; If T1>T2, a cooling measure is started, and the cooling measure is to increase the flow rate of the cooling water channel corresponding to the sub-region; If T1<T2, a heating measure is started to increase the power of the heating rod corresponding to the sub-region.

[0055] It can be understood that the cooling measure and the heating measure are technical means already mastered by those skilled in the art, and the present invention preferably provides a cooling measure and a heating measure.

[0056] In the cooling measure, the flow increment of the cooling water channel = K1×(T1-T2)+K2×R; Wherein, K1 is the temperature difference flow coefficient, and K2 is the rate of change flow coefficient. In this embodiment of the invention, K1 is 0.2 and K2 is 0.1. The flow increment of the cooling water channel is calculated dimensionlessly, and the flow increment is fixed in L / min. For example, when T1-T2=1°C and R=0.5°C / s, the flow increment = 0.2×1+0.1×0.5=0.25, and the unit is set to L / min.

[0057] In the heating measures, the increase in power of the heating rod = L1 × (T2 - T1) + L2 × |R|; L1 is the temperature difference power coefficient, and L2 is the rate of change power coefficient. In this embodiment of the invention, the temperature difference power coefficient L1 is set to 10 W / °C. It can be understood that L1 is used to adjust the contribution of the target temperature difference to the increase in heating power. The larger L1 is, the larger the power increase corresponding to a unit temperature difference, the more intense the heating response, and the faster the heating rate. However, this may cause temperature overshoot or thermal inertia overshoot. The higher the user's requirements for the rapid heating capability of the heating system, the larger the value of L1. In this embodiment of the invention, the rate of change power coefficient L2 is set to 5 W / (°C / s). It can be understood that L2 is used to adjust the contribution of the absolute value of the temperature deviation change rate to the increase in heating power. Its core function is to feedforward compensate for the temperature drop trend or the insufficient heating trend. The larger L2 is, the larger the power increase when the temperature drops rapidly or the deviation expands at a fast rate. This can prevent the temperature drop in advance and avoid overcooling defects. The higher the user's requirements for temperature fluctuation suppression capability and microchannel filling integrity, the larger the value of L2.

[0058] Please see Figure 5 The diagram shown is a unit connection diagram of the intelligent temperature control system for microfluidic chip injection molding according to the present invention. The present invention also provides an intelligent temperature control system for microfluidic chip injection molding, comprising: The channel analysis unit is used to set the breakpoints for each independent channel based on the segment curvature reference value obtained by continuous detection through the curvature detection window, determine the sub-segment based on the breakpoints, and determine the sub-segment category based on the corresponding segment length and edge distance. A generation analysis unit, which is connected to the channel analysis unit, is used to select either the first region generation method or the second region generation method based on the proportion of a type of sub-segments. The first generation unit, which is connected to the generation and analysis unit, is used to execute the first region generation method. Based on the area ratio of the target clustered region and the dispersion of the target clustered region, it determines whether to perform region granular generation or region independent generation to obtain several sub-regions. The second generation unit, which is connected to the generation and analysis unit, is used to determine whether the morphological point is a first morphological point or a second morphological point based on whether there is a difference between the categories corresponding to the upstream and downstream paragraphs of the morphological point, and to construct sub-regions for each first morphological point. A temperature control unit, which is connected to the first generation unit and the second generation unit respectively, is used to determine whether to perform temperature control adjustment based on the temperature deviation reference value and the temperature deviation change rate corresponding to the sub-region.

[0059] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

Claims

1. A method for intelligent temperature control of molds used in injection molding of microfluidic chips, characterized in that, include: Based on the curvature reference value of the segment obtained by continuous detection through the curvature detection window, the breakpoint is set for each independent channel, and the sub-segment is determined according to the breakpoint. The sub-paragraph is classified as either a first-class or second-class sub-paragraph based on its corresponding paragraph length and edge distance, and the first-class or second-class sub-paragraph generation method is determined based on the proportion of first-class sub-paragraphs. In the first region generation method, the region granularity generation or independent region generation is determined based on the area ratio of the target cluster region and the dispersion of the target cluster region to obtain several sub-regions; In the second region generation method, the morphological point is determined as the first morphological point or the second morphological point based on whether there is a difference between the categories corresponding to the upstream and downstream paragraphs of the morphological point, and sub-regions are constructed for each first morphological point. Whether to perform temperature control adjustment is determined based on the temperature deviation reference value and the rate of change of temperature deviation corresponding to the sub-region.

2. The intelligent temperature control method for molds used in microfluidic chip injection molding according to claim 1, characterized in that, For a single independent channel, in its corresponding curvature analysis, the curvature reference value of the segment is obtained based on the curvature detection window according to the preset step size, with one end of the independent channel as the starting point and the other end as the ending point. If the cumulative value of the segment curvature reference value is greater than the preset cumulative value at a certain moment, the center point of the curvature detection window at the corresponding moment is recorded as a break point. Sub-segments are determined based on the segments between adjacent break points and endpoints.

3. The intelligent temperature control method for molds used in microfluidic chip injection molding according to claim 2, characterized in that, Sub-paragraphs whose paragraph length is less than or equal to the preset paragraph length or whose edge distance is less than or equal to the preset edge distance are identified as a type of sub-paragraph. Sub-paragraphs whose paragraph length is greater than the preset paragraph length and whose edge distance is greater than the preset edge distance are classified as Category II sub-paragraphs.

4. The intelligent temperature control method for molds used in microfluidic chip injection molding according to claim 3, characterized in that, For a target template where the proportion of a certain type of sub-paragraphs is greater than the preset proportion of a certain type of sub-paragraphs, determine the execution method for generating the first region. For a target template where the proportion of a certain type of sub-paragraph is less than or equal to the preset proportion of a certain type of sub-paragraph, determine the execution of the second region generation method.

5. The intelligent temperature control method for molds used in microfluidic chip injection molding according to claim 4, characterized in that, For regions whose area ratio of the target cluster area is greater than the preset area ratio and whose dispersion of the target cluster area is less than or equal to the preset dispersion, determine the granularity of the execution region. The region granularity generation includes: performing fine-grained uniform division on the target continuous region and coarse-grained uniform division on the region outside the target continuous region, so as to obtain several sub-regions respectively; Among them, the area of ​​the sub-region obtained by fine-grained uniform division is smaller than the area of ​​the sub-region obtained by coarse-grained uniform division.

6. The intelligent temperature control method for molds used in microfluidic chip injection molding according to claim 4, characterized in that, For regions where the number of target clustered regions is less than or equal to the number of preset regions, or where the dispersion of the target clustered regions is greater than the dispersion of the preset regions, the execution region is determined to be generated independently. Independent region generation includes: constructing regions for each type of sub-paragraph according to the paragraph evaluation value from largest to smallest to obtain several sub-regions.

7. The intelligent temperature control method for molds used in microfluidic chip injection molding according to claim 4, characterized in that, For morphological points where there are differences in paragraph category between upstream and downstream paragraphs, they are identified as the first morphological points; For morphological points where the upstream and downstream paragraphs correspond to the same paragraph category, they are identified as second morphological points.

8. The intelligent temperature control method for molds used in microfluidic chip injection molding according to claim 7, characterized in that, For each first morphological point, a sub-region is constructed, and for sub-regions where the historical defect probability is greater than the preset historical defect probability, the area of ​​the region is reduced. The decrease in area is positively correlated with the probability of historical defects.

9. The intelligent temperature control method for molds used in microfluidic chip injection molding according to any one of claims 4 to 8, characterized in that, For sub-regions where the temperature deviation reference value is greater than the preset temperature deviation reference value or the temperature deviation change rate is greater than the preset temperature deviation change rate, temperature control adjustment is determined.

10. A system for applying the intelligent temperature control method for molds used in microfluidic chip injection molding as described in any one of claims 1 to 9, characterized in that, include: The channel analysis unit is used to set the breakpoints for each independent channel based on the segment curvature reference value obtained by continuous detection through the curvature detection window, determine the sub-segment based on the breakpoints, and determine the sub-segment category based on the corresponding segment length and edge distance. A generation analysis unit, which is connected to the channel analysis unit, is used to select either the first region generation method or the second region generation method based on the proportion of a type of sub-segments. The first generation unit, which is connected to the generation and analysis unit, is used to execute the first region generation method. Based on the area ratio of the target clustered region and the dispersion of the target clustered region, it determines whether to perform region granular generation or region independent generation to obtain several sub-regions. The second generation unit, which is connected to the generation and analysis unit, is used to determine whether the morphological point is a first morphological point or a second morphological point based on whether there is a difference between the categories corresponding to the upstream and downstream paragraphs of the morphological point, and to construct sub-regions for each first morphological point. A temperature control unit, which is connected to the first generation unit and the second generation unit respectively, is used to determine whether to perform temperature control adjustment based on the temperature deviation reference value and the temperature deviation change rate corresponding to the sub-region.

Images