An adaptive cutting bed power matching and regulation control system

Abstract

This invention discloses an adaptive cutting bed power matching and adjustment control system. The system comprises a cluster power collaborative scheduling module, a single-machine precise power adjustment module, and a data linkage feedback module, and couples three core technologies: multi-cutting bed cluster power allocation, tool micro-vibration spectrum power compensation, and precise power adaptation for coated fabrics. The cluster power collaborative scheduling module includes a workshop total power threshold monitoring unit, an order priority sorting unit, and a cutting bed redundant power scheduling unit. The order priority sorting unit generates order priority coefficients through an order priority quantification algorithm. Based on the order priority quantification algorithm and the cluster power allocation algorithm, this invention can prioritize orders according to the complexity of the coating process, the urgency of delivery, and the difficulty of fabric cutting, and allocate differentiated power to each cutting bed within the cluster accordingly. Simultaneously, combined with a redundant power scheduling mechanism, it achieves dynamic power allocation, ensuring power supply for high-priority orders.

Description

Technical Field

[0001] This invention belongs to the field of textile processing technology, and in particular relates to an adaptive cutting bed power matching and adjustment control system. Background Technology

[0002] In textile processing, especially in the cutting of medical coated fabrics, CNC cutting machines have become core production equipment, and the supporting power regulation systems have gradually achieved basic automated control. Currently, existing cutting machine power regulation technologies mostly consist of single-machine power controllers, simple cluster monitoring terminals, and basic sensing equipment, enabling fixed-range power output for a single cutting machine. Some systems are also equipped with fabric thickness sensors and tool vibration monitoring probes, allowing for basic cutting parameter matching. Simultaneously, most workshops install power grid monitoring devices to manage the total power load manually or semi-automatically, preventing grid overload. For coated fabrics, the industry has also developed experience-based fixed-power cutting solutions that can meet the basic cutting needs of conventional medical coated and ordinary fabrics. These solutions have been implemented on a large scale in small and medium-sized cutting machine production clusters, providing technical support for the automation transformation of the textile cutting industry.

[0003] As the requirements for cutting precision and coating performance in medical coated fabrics continue to increase, the limitations of existing cutting bed power adjustment technologies are becoming increasingly apparent. Firstly, current cluster power management lacks a precise order priority quantification mechanism, resulting in coarse power allocation that cannot guarantee the power needs of high-urgency, high-complexity coating orders, easily leading to power redundancy or insufficient supply. Secondly, the lack of a precise database linking coating processes and cutting power means that fixed power modes can easily damage the coating's slow-release structure, making it difficult to meet the performance requirements of high-end medical coatings. Thirdly, tool vibration can only be monitored at a basic level, lacking early warning of wear and dynamic power compensation, resulting in rapid tool wear and unstable cutting precision. Fourthly, the absence of a closed-loop feedback iterative system prevents adaptive parameter optimization, leading to poor batch production consistency. Fifthly, the lack of order priority-oriented power scheduling results in high delivery delays for high-value orders, making it difficult to improve overall production efficiency and profitability. Summary of the Invention

[0004] To overcome the aforementioned deficiencies of the prior art, this invention provides an adaptive cutting bed power matching and adjustment control system, which solves the problems of lack of priority quantization of cluster power, lack of coating-power library, and lack of early warning compensation for tools in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solution:

[0006] An adaptive cutting bed power matching and adjustment control system, the system comprising: a cluster power collaborative scheduling module, a single-machine precise power adjustment module, and a data linkage feedback module;

[0007] The cluster power collaborative scheduling module includes a workshop total power threshold monitoring unit, an order priority sorting unit, and a cutting bed redundancy power scheduling unit. The workshop total power threshold monitoring unit integrates a power grid sensor and a real-time power calculation chip, providing dual-dimensional power monitoring capabilities. It collects the total power input from the workshop's smart grid in real time, sets 90% of the workshop grid's rated power as the power overload warning threshold, and aggregates the real-time operating power of all cutting beds within the cluster, generating a dynamic power load curve for the cluster and simultaneously outputting a total power over-limit warning signal and power margin data. The order priority sorting unit uses an order priority quantification algorithm... An order priority coefficient is generated, which is used to bind the fabric coating attributes and cutting difficulty coefficients corresponding to each order, and to classify order priorities based on the order priority coefficient. This is the order priority coefficient. This represents the coating process complexity coefficient. This is the urgency coefficient for order delivery. The fabric cutting difficulty coefficient is represented by a, b, and c, which are weighting coefficients, and a+b+c=1; the redundant power scheduling unit of the cutting bed is used to perform cluster power allocation algorithm. Differentiated power is allocated to each cutting bed within the cluster, where Allocate power to the i-th cutting bed. The total available power in the workshop, Let be the priority coefficient of the order corresponding to the i-th cutting bed. Let n be the priority coefficient of the order corresponding to the j-th cutting bed, and n be the total number of cutting beds in the cluster. This is the sum of the priority coefficients for all orders corresponding to all cutting beds within the cluster.

[0008] The single-machine precision power adjustment module integrates a coating characteristic power matching unit and a tool micro-vibration spectrum power compensation unit. The coating characteristic power matching unit has a built-in database linking coating process and cutting power, and is used to match the initial cutting power to the fabric to be cut using a fabric thickness sensor and a coating component identification unit. The tool micro-vibration spectrum power compensation unit integrates a piezoelectric vibration sensor, which is used to collect the vibration spectrum data of the cutting tool in real time and input it into the tool life power compensation prediction model. The tool life power compensation prediction model uses a power compensation coefficient algorithm. Triggering power compensation and power regulation actions, among which This is the power compensation coefficient. This is the vibration frequency deviation value. The cumulative usage time of the cutting tool. This refers to the amount of cutting edge wear. , , This is a correction factor;

[0009] The data linkage feedback module is used to synchronize the corrected technical parameters to the order priority quantification algorithm of the cluster power collaborative scheduling module and the coating process and cutting power association database of the single-machine precise power adjustment module, so as to realize the iterative optimization of the system technical parameters.

[0010] Preferably, in the order priority quantification algorithm, the weight coefficient 'a' takes a value of 0.4 to 0.6, 'b' takes a value of 0.2 to 0.3, and 'c' takes a value of 0.1 to 0.3; in the power compensation coefficient algorithm, the correction coefficient... The value ranges from 0.5 to 0.7. The value ranges from 0.2 to 0.3. The value ranges from 0.1 to 0.2 and .

[0011] Preferably, the order priority sorting unit is used to sort according to Order priorities, ranked from highest to lowest, are: drug-loaded coated fabric orders, ordinary medical coated fabric orders, and regular fabric orders; the sustained-release properties of the fabric coating are divided into short-acting (72-hour sustained-release) and long-acting (one-month sustained-release), corresponding to... The values ​​are 0.5 and 0.3 respectively, corresponding to orders for regular fabrics. The value is 0.1.

[0012] Preferably, the redundant power scheduling unit for the cutting bed is used to perform dynamic scheduling of redundant power through the smart grid of the workshop. During the scheduling process, it needs to receive real-time monitoring data from the total power threshold monitoring unit of the workshop. When the total power of the workshop is detected to be close to 90% of the rated power warning threshold, the dynamic load reduction action is automatically triggered. The operating power of the corresponding cutting bed is reduced from low to high according to the order priority coefficient until the total power falls back to within the safe threshold. During the scheduling process, the total power of the workshop is maintained to not exceed 90% of the rated power of the grid to avoid overload tripping of the workshop grid. At the same time, the total power threshold monitoring unit of the workshop will feed back the actual load data after power scheduling to the cluster power allocation algorithm to correct the power allocation weight.

[0013] Preferably, the coating process and cutting power correlation database of the coating characteristic power matching unit covers the cutting power adaptation parameters of silver ion and antibiotic pharmaceutical ingredients; for short-acting 72-hour sustained-release coated fabrics, the coating characteristic power matching unit enables a cutting mode with a base power of 60% to 70% and a blade gap of 0.15 mm to 0.2 mm; for long-acting one-month sustained-release coated fabrics, the coating characteristic power matching unit enables a cutting mode with a base power of 80% to 90% and a cut roughness of no more than 1.6 micrometers.

[0014] Preferably, the sampling frequency of the piezoelectric vibration sensor is not less than 10 kHz, and the measurement frequency range is from 0.01 Hz to 1000 Hz; the abnormal vibration frequency band of the tool is divided into low-frequency vibration and high-frequency noise, the low-frequency vibration frequency band is 50 Hz to 100 Hz corresponding to the micro-chipping state of the tool edge, and the high-frequency noise frequency band is 500 Hz to 800 Hz corresponding to the resonance state between the tool and the fabric fibers.

[0015] Preferably, when low-frequency vibration is detected, the tool micro-vibration spectrum power compensation unit increases the cutting power by 8% to 12% on the base power allocated by the cluster power collaborative scheduling module, while shortening the single cutting stroke by 10% to 15%; when high-frequency noise is detected, the tool micro-vibration spectrum power compensation unit instantly reduces the cutting power by 5% to 8%, while fine-tuning the cutting angle in 0.5-degree steps, and all power adjustment actions are constrained by the power threshold without damaging the coating slow-release structure.

[0016] Preferably, the tool life power compensation prediction model is used to output tool wear warning signals 2 to 3 hours in advance, with a warning accuracy of not less than 92%. When it is predicted that the tool is entering the critical period of wear, the model controls the system to reduce the power output amplitude by 10% to 15%, and at the same time switches to a cutting mode with low power and high cutting frequency, increasing the cutting frequency by 20%, so as to extend the effective service life of the tool and maintain the integrity of the coating structure.

[0017] Preferably, the coating performance feedback correction process of the data linkage feedback module involves extracting the first cut piece after cutting and conducting an in vitro release test. When the coating slow-release efficiency deviation exceeds 3%, the correction is performed according to the formula... The power adaptation parameters for the corresponding coated fabrics were corrected, and the database relating coating process and cutting power was updated synchronously. For the corrected power, To correct the power, Δη is the deviation value of the slow-release efficiency; the tool life and power linkage optimization method of the data linkage feedback module is to combine the actual tool replacement cycle and the vibration spectrum data of the whole life cycle, according to the formula Iterative optimization of power compensation coefficients, where These are the compensation coefficients after iteration. The compensation coefficient before iteration is Δd, which is the deviation rate between the actual wear of the tool and the predicted wear. This can make the coating cutting defect rate stably reduced to less than 2% in the long term.

[0018] Preferably, the cluster power collaborative scheduling module is used to statistically analyze workshop power utilization rate, cut piece qualification rate, and power scheduling response delay data on a weekly or monthly basis, using a weighted iterative formula. , , Optimize the weight coefficients of the order priority quantification algorithm, where , , As a correction factor with values ​​ranging from 0.8 to 1.2, the historical monitoring data of the workshop total power threshold monitoring unit is the core data source for workshop power utilization statistics. After optimization, the workshop power utilization rate can be stably maintained at over 85%, the cut piece qualification rate can be stably maintained at over 98%, and the power scheduling response delay can be no more than 100 milliseconds.

[0019] The technical effects and advantages of the adaptive cutting bed power matching and adjustment control system of the present invention are as follows:

[0020] 1. This invention relies on an order priority quantification algorithm and a cluster power allocation algorithm to prioritize orders based on the complexity of the coating process, the urgency of delivery, and the difficulty of fabric cutting. Based on this, differentiated power is allocated to each cutting bed in the cluster. At the same time, combined with a redundant power scheduling mechanism, dynamic power allocation is achieved, which not only ensures the power supply for high-priority orders, but also keeps the total power of the workshop stable within a safe threshold, greatly improving the overall power utilization rate of the workshop and avoiding the power redundancy or overload problems of the traditional fixed power mode.

[0021] 2. The coating characteristic power matching unit in the single-machine precision power adjustment module of this invention can identify the coating properties and thickness of the fabric through sensors, and match the appropriate cutting power and process parameters by combining the coating process and cutting power correlation database. This effectively avoids problems such as coating structure damage and slow-release performance failure caused by power mismatch. At the same time, the tool micro-vibration spectrum power compensation unit can respond to abnormal tool vibration in real time and perform power compensation, taking into account both cutting accuracy and coating edge integrity, and meeting the stringent cutting requirements of high-end coated fabrics such as medical materials.

[0022] 3. The tool life power compensation prediction model in this invention can identify tool wear trends in advance and trigger power adjustment. Combined with real-time compensation of vibration spectrum, it can effectively alleviate abnormal tool wear, extend tool service life, reduce tool replacement frequency, reduce the time cost of consumable procurement and downtime tool replacement in the production process, and improve the overall equipment uptime.

[0023] 4. The data linkage feedback module in this invention can collect and analyze coating cutting performance data and tool wear data, correct power parameters and compensation coefficients through preset formulas, and update the corresponding module's algorithm and database simultaneously, realizing iterative optimization of system technical parameters. Under long-term operation, it can gradually reduce the coating cutting defect rate, ensure the consistency and stability of batch production, and improve the overall production yield.

[0024] 5. This invention, through precise order priority allocation and targeted power guarantee, can prioritize the production needs of high-value and high-urgency orders, avoiding the order delivery delay problem in the traditional no-priority scheduling mode. At the same time, the collaborative operation of each module greatly shortens the power scheduling response time, optimizes the production process connection, and improves the overall workshop production efficiency and the timeliness of order delivery. Attached Figure Description

[0025] Figure 1 This is a flowchart of an adaptive cutting bed power matching and adjustment control system proposed in this invention.

[0026] Figure 2 This is a system block diagram of an adaptive cutting bed power matching adjustment control system proposed in this invention. Detailed Implementation

[0027] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0028] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include," "contain," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "includes..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0029] refer to Figures 1-2This invention discloses an adaptive cutting bed power matching and adjustment control system, aiming to solve the problems of coarse power adjustment and difficulty in ensuring the quality of coated fabric cutting in existing cutting beds. The system includes a cluster power collaborative scheduling module, a single-machine precise power adjustment module, and a data linkage feedback module, coupling three core technologies: multi-cutting bed cluster power allocation, tool micro-vibration spectrum power compensation, and precise power adaptation for coated fabrics. The cluster module achieves differentiated power allocation and dynamic scheduling through order priority quantification algorithms and power matching algorithms; in the single-machine module, the coating characteristic power matching unit matches the initial power with sensors and a related database, and the tool vibration compensation unit calculates the compensation value based on a model; the feedback module collects data to optimize parameters and updates them synchronously, forming an iterative cycle that can improve power utilization, ensure coating performance, and extend tool life, making it suitable for high-precision cutting scenarios such as medical coated fabrics.

[0030] The hardware components of this system include: a cluster power collaborative scheduling module (integrating a workshop total power threshold monitoring unit, an order priority sorting unit, and a cutting bed redundant power scheduling unit, along with a power monitoring instrument, an industrial controller, and a power grid communication module), a single-machine precision power adjustment module (integrating a coating characteristic power matching unit and a tool micro-vibration spectrum power compensation unit, along with a fabric thickness sensor, a coating composition identification unit, a piezoelectric vibration sensor, and a servo power controller), and a data linkage feedback module (with an external release tester, a tool wear detector, and a data storage server). The system is adapted for application scenarios consisting of a cutting bed cluster of 10 CNC cutting beds, with a basic power of 20kW per cutting bed and a rated power of 150kW for the workshop power grid.

[0031] Example 1

[0032] This embodiment provides an adaptive cutting bed power matching and adjustment control system for the implementation and verification of cluster-differentiated power allocation. Specific implementation details include:

[0033] Purpose of implementation:

[0034] The practicality of the order priority quantification algorithm and the cluster power allocation algorithm was verified to achieve differentiated power allocation of cutting beds within the cluster, while ensuring that the total power of the workshop does not exceed the limit and that power is supplied to high-priority orders.

[0035] Implementation System:

[0036] The cluster power collaborative scheduling module of the present invention includes a workshop total power threshold monitoring unit, an order priority sorting unit, and a cutting bed redundancy power scheduling unit, and is equipped with a workshop smart grid and a cutting bed cluster consisting of 10 CNC cutting beds.

[0037] Implementation steps:

[0038] (1) Parameter preset: The weight coefficients of the order priority quantification algorithm are a=0.5, b=0.25, c=0.25 and a+b+c=1; the coating process complexity coefficient In this context, the order value for drug-loaded coated fabrics is 0.5, for ordinary medical coated fabrics it is 0.3, and for regular fabrics it is 0.1; the order delivery urgency coefficient is... In China, rush orders cost 0.9, and regular orders cost 0.5; the fabric cutting difficulty coefficient... In the medium, the thickness of thick-coated fabric is 0.8, the thickness of thin-coated fabric is 0.4, and the thickness of regular fabric is 0.2; the total available power in the workshop =135kW (90% of the grid's rated power), total number of cutting bed clusters n=10; in the cluster power allocation algorithm, Let be the priority coefficient of the order corresponding to the i-th cutting bed. Let j be the priority coefficient of the order corresponding to the j-th cutting bed. This is the sum of priority coefficients for all cutting orders within the cluster.

[0039] (2) Order allocation: The three types of orders are allocated to the corresponding cutting beds. Among them, the expedited orders of drug-coated fabrics are allocated to cutting beds 1 and 2, the regular orders of ordinary medical coated fabrics are allocated to cutting beds 3-5, and the regular fabric orders are allocated to cutting beds 6-10.

[0040] (3) Priority coefficient calculation: Cutting beds 1 and 2 = =0.5×0.5+0.25×0.9+0.25×0.8=0.675; Cutting bed 3-5 = = =0.5×0.3+0.25×0.5+0.25×0.4=0.375; Cutting bed 6-10 - =0.5×0.1+0.25×0.5+0.25×0.2=0.225; Calculate .

[0041] (4) Power distribution: according to the formula The calculated power distribution for each cutting bed 1 and 2 is approximately 25.31 kW (135 × 0.675 / 3.6), for each cutting bed 3-5 it is approximately 14.06 kW (135 × 0.375 / 3.6), and for each cutting bed 6-10 it is approximately 8.44 kW (135 × 0.225 / 3.6).

[0042] (5) Redundant power scheduling: When cutting bed 1 needs to increase its power to 28kW instantly, the redundant power scheduling unit of cutting bed 6-10 will retrieve redundant power from cutting bed 6-10, so that the power of a single cutting bed 6-10 is reduced to 7.8kW, the power of cutting bed 1 reaches 28kW and the total power of the workshop is maintained at 135kW.

[0043] Implementation results:

[0044] The on-time delivery rate of expedited orders for drug-coated fabrics reached 100%, the overall power utilization rate of the workshop increased to 92%, there were no power grid overload trips throughout the process, the power allocation of each cutting bed in the cluster met the order priority requirements, and the power guarantee rate for high priority orders reached 100%.

[0045] Example 2

[0046] This embodiment provides an adaptive cutting bed power matching and adjustment control system for precise initial power adaptation of different slow-release coated fabrics. Specific implementation details include:

[0047] Purpose of implementation:

[0048] Verify the coating characteristic power matching unit's ability to accurately adapt to the initial cutting power and process parameters of different types of slow-release coated fabrics, ensuring that the coating structure and slow-release performance are not damaged.

[0049] Implementation System:

[0050] The coating characteristic power matching unit in the single-machine precision power adjustment module of the present invention includes a coating process and cutting power correlation database, a fabric thickness sensor, a coating component identification unit, and is matched with a single CNC cutting bed with a basic power of 20kW.

[0051] Implementation steps:

[0052] (1) Database pre-stored parameters: In the database of coating process and cutting power, the basic power of silver ion short-acting 72-hour slow-release coating fabric is 60%-70% and the blade gap is 0.15-0.2mm, and the basic power of antibiotic long-acting one-month slow-release coating fabric is 80%-90% and the cut roughness is no more than 1.6μm.

[0053] (2) Fabric parameter detection: The fabric thickness sensor and coating composition identification unit were used to detect two types of fabrics to be cut. The silver ion short-acting sustained-release coating fabric has a thickness of 0.18 mm and the coating composition is silver ions. The antibiotic long-acting sustained-release coating fabric has a thickness of 0.32 mm and the coating composition is antibiotics.

[0054] (3) Initial parameter matching: The initial power matching for silver ion coated fabric is 20kW×65%=13kW and the blade gap is 0.18mm; the initial power matching for antibiotic coated fabric is 20kW×85%=17kW and the cut roughness control value is 1.2μm.

[0055] (4) Cutting operation: Start the cutting bed and cut the two types of fabrics according to the matching parameters. Monitor the surface morphology of the coating and the stability of the cutting parameters throughout the process.

[0056] Implementation results:

[0057] After cutting, the micropores of the silver ion coating remain at 32% (without pore compression phenomenon), and the in vitro sustained-release efficiency reaches 95% after 72 hours, meeting the performance requirements of medical short-acting sustained-release coatings; the adhesion between the antibiotic coating and the fabric reaches 4.2 N / cm, the deviation of the in vitro sustained-release efficiency after one month is only 2.1%, and the measured cut roughness is 1.2 μm, meeting the process and performance standards of long-acting sustained-release coatings.

[0058] Example 3

[0059] This embodiment provides an adaptive cutting bed power matching and adjustment control system for power compensation and adjustment under different vibration states of the cutting tool. Specific implementation details include:

[0060] Purpose of implementation:

[0061] The test verifies the response capability and power adjustment effect of the tool micro-vibration spectrum power compensation unit to abnormal tool vibration, and also verifies the effectiveness of the tool wear warning function, extending tool life and maintaining cutting accuracy.

[0062] Implementation System:

[0063] The tool micro-vibration spectrum power compensation unit in the single-machine precision power adjustment module of the present invention includes a piezoelectric vibration sensor, a tool life power compensation prediction model, and is equipped with a servo power controller and a special cutting tool for CNC cutting machine.

[0064] Implementation steps:

[0065] (1) Preset equipment parameters: piezoelectric vibration sensor sampling frequency 12kHz, measurement frequency range 0.01-1000Hz; power compensation coefficient algorithm is set to =0.6、 =0.25、 =0.15 and + + =1; the tool wear warning advance time is set to 2.5 hours, and the warning accuracy rate is not less than 92%; the basic cutting power is set to 17kW, the single cutting stroke is 50mm, the cutting angle is 45 degrees, and the cutting frequency is 3 times / s.

[0066] (2) Vibration data acquisition: During the cutting of antibiotic long-acting sustained-release coated fabric, the piezoelectric vibration sensor collects the vibration spectrum data of the tool in real time. It successively monitors the 55Hz low-frequency vibration (corresponding to the micro-chipping of the cutting edge) and the 600Hz high-frequency noise (corresponding to the resonance between the tool and the fabric fibers). Simultaneously, it records the cumulative usage time of the tool (80h), the cutting edge wear (0.02mm), and the vibration frequency deviation (0.12).

[0067] (3) Power compensation calculation: according to the formula = × + × + × The calculated power compensation coefficient is 20.075. For low-frequency vibration, the power is increased by 10% to 18.7kW from the base power of 17kW, while the single cutting stroke is shortened from 50mm to 42.5mm. For high-frequency noise, the power is instantly reduced by 6% to 16.08kW, while the cutting angle is finely adjusted to 45.5 degrees in 0.5 degree steps.

[0068] (4) Tool wear warning: The tool life power compensation prediction model outputs a wear warning signal 2.5 hours in advance. The system automatically reduces the power by 12% to 14.96kW and increases the cutting frequency from 3 times / s to 3.6 times / s to maintain cutting efficiency.

[0069] Implementation results:

[0070] After low-frequency vibration compensation, the problem of insufficient cutting force is completely eliminated, and the kerf size accuracy reaches ±0.01mm; after high-frequency noise is eliminated, there is no wavy deviation in the kerf and no cracking at the coating edge; the tool life is extended from 100h to 115h, an extension of 15%, and the coating structure is not damaged during the cutting process.

[0071] Example 4

[0072] This embodiment provides an adaptive cutting bed power matching adjustment and control system for feedback correction and iterative optimization of system technical parameters. Specific implementation details include:

[0073] Purpose of implementation:

[0074] The verification data linkage feedback module has the ability to correct and iterate on coating power parameters and tool power compensation coefficients, thereby reducing the coating cutting defect rate and improving the system's operational stability.

[0075] Implementation System:

[0076] The data linkage feedback module of this invention is used in conjunction with an in vitro release tester, a tool wear detector, and a database relating coating process and cutting power, and is linked to a cluster power collaborative scheduling module and a single-machine precision power adjustment module.

[0077] Implementation steps:

[0078] (1) Coating performance feedback correction: The first piece of silver ion coated fabric from Example 2 was cut and subjected to an in vitro release test. The deviation of the sustained release efficiency was measured to be Δη = 3.5% (exceeding the threshold of 3%). According to the formula = The power was adjusted from 13kW to 12.545kW using the calculation of ×(1-Δη), and the power parameters of the silver ion coating in the coating process and cutting power correlation database were updated simultaneously.

[0079] (2) Tool power coefficient iteration: The actual wear of the tool in Example 3 was measured to be 0.025 mm using a tool wear detector. The measured wear was compared with the predicted wear of 0.02 mm. The wear deviation rate Δd = 0.25 was calculated, and the result was obtained according to the formula. = ×(1-Δd) adjusts the compensation coefficient from 20.075 before iteration to 15.056, and updates the coefficient parameters of the tool life power compensation prediction model.

[0080] (3) Parameter synchronization application: The corrected power parameters and compensation coefficients are synchronized to the corresponding cutting bed module to carry out batch cutting verification.

[0081] Implementation results:

[0082] After correction, the deviation of the slow-release efficiency of the silver ion coated fabric was reduced to 2.2%, which meets the threshold requirement; the coating cutting defect rate caused by tool wear was reduced from 4.5% to 1.8% in a long-term stable manner, the adaptability and accuracy of the system technical parameters were significantly improved, and the consistency of batch cutting reached 98.5%.

[0083] Example 5

[0084] This embodiment provides an adaptive cutting bed power matching adjustment and control system for long-term verification of the system's full-process iterative optimization. Specific implementation details include:

[0085] Purpose of implementation:

[0086] Verify the overall iterative optimization capability of the system. Through long-term data statistics and weight coefficient adjustment, improve the overall power utilization rate, cut piece qualification rate and scheduling response speed of the workshop.

[0087] Implementation System:

[0088] The adaptive cutting bed power matching and adjustment control system of the present invention includes a cluster power collaborative scheduling module, a single machine precision power adjustment module, and a data linkage feedback module, which is matched with a production cluster consisting of 10 CNC cutting beds and a complete medical coated fabric production line.

[0089] Implementation steps:

[0090] (1) Preset of iterative parameters: The weight iterative formula is as follows , , Correction factor =1.1 (Power utilization correction factor) =1.05 (On-time delivery rate correction factor) =0.95 (cutting pass rate correction factor), initial weights a=0.5, b=0.25, c=0.25.

[0091] (2) Data statistics: The production data of the workshop for two consecutive weeks are statistically analyzed. The power utilization rate reached 89% (exceeding the target value of 85%), the on-time delivery rate reached 98% (exceeding the target value of 95%), and the cutting qualification rate reached 99% (exceeding the target value of 98%).

[0092] (3) Weight coefficient optimization: calculated according to the iterative formula. =0.5 × 1.1 = 0.55 =0.25 × 1.05 = 0.2625 =0.25×0.95=0.2375, and update the weight coefficient of the order priority quantification algorithm to strengthen the weight ratio of power utilization.

[0093] (4) Long-term operation: The system will be kept running continuously for one month according to the optimized parameters, and the core production indicators will be monitored throughout the process.

[0094] Implementation results:

[0095] After optimization, the workshop power utilization rate stabilized at 91%, the cut piece qualification rate stabilized at 99.2%, the power scheduling response delay was shortened to 85ms (less than the required value of 100ms), the on-time delivery rate of expedited orders remained at 100%, the overall system operating efficiency and production quality were significantly improved, and the comprehensive production efficiency was increased by 22%.

[0096] Comparative Example 1

[0097] This comparative example provides an application comparison and verification of a traditional stand-alone independent power regulation system, specifically including:

[0098] Application purpose:

[0099] By comparing with traditional systems, the technical advantages of the system of the present invention in terms of power distribution rationality, coating cutting quality, tool life and production efficiency are clearly demonstrated.

[0100] Application System:

[0101] The production cluster consists of 10 traditional CNC cutting machines. It lacks a cluster power coordination scheduling module, tool vibration power compensation function, and data linkage feedback mechanism. The fixed output power of each machine is 20kW. It is equipped with conventional cutting tools and basic fabric testing equipment. There is no database linking coating process and power. The rated power of the workshop power grid is also 150kW.

[0102] Application steps:

[0103] (1) Order allocation: The same batch of medical coated fabric (silver ion short-acting, antibiotic long-acting) and regular fabric orders as in Example 5 were used. The orders were randomly allocated to 10 traditional cutting beds without distinguishing the order priority. Among them, the expedited orders of drug-loaded coated fabric were allocated to cutting beds 1 and 2, the orders of ordinary medical coated fabric were allocated to cutting beds 3-5, and the orders of regular fabric were allocated to cutting beds 6-10.

[0104] (2) Power control: All cutting beds use a fixed power output of 20kW. There is no dynamic power scheduling and redundant power allocation mechanism. The total power of the workshop is monitored manually, and some cutting beds are manually shut down when overload occurs.

[0105] (3) Cutting operation: Cutting is carried out according to traditional fixed process parameters. The gap between the silver ion coating blades is uniformly set to 0.2mm, the roughness of the antibiotic coating blade is not precisely controlled, the tool has no vibration monitoring and compensation mechanism, and no parameter feedback correction is performed during the cutting process.

[0106] (4) Indicator statistics: Production data are statistically analyzed at the same cycle as in Example 5, including power utilization rate, cut piece qualification rate, tool life, order delivery timeliness rate and coating performance indicators.

[0107] Application effect:

[0108] (1) Power utilization and grid stability: Due to the lack of dynamic scheduling, the power of the cutting bed for high-priority orders is not guaranteed, and the power of the cutting bed for low-priority orders is redundant. The total power of the workshop is frequently overloaded (3 times per day on average). In order to avoid tripping, the low-load cutting bed is manually shut down. The actual power utilization rate is only 62%, which is far lower than the 91% of the present invention.

[0109] (2) Coating cutting quality: The silver ion coating has a pore compaction due to excessive power, and the deviation of the in vitro sustained release efficiency reaches 11.2% after 72 hours, which is far beyond the threshold of 3%; the antibiotic coating has a roughness of 2.5μm due to power mismatch, and the bonding strength between the coating and the fabric drops to 2.1N / cm. The overall qualified rate of medical coated fabric cutting pieces is only 82%, which is 17.2 percentage points lower than that of the present invention.

[0110] (3) Tool life: Without vibration compensation mechanism, the tool wears out due to abnormal vibration, and the service life is only 80h, which is 35h shorter than that of the present invention. The tool replacement frequency increases by 43.75%, which increases production cost.

[0111] (4) Order delivery: There is no priority scheduling, and urgent orders for drug-coated fabrics have been suspended multiple times due to insufficient power.

[0112] Compared with Examples 1-5 and Comparative Example 1, under the same conditions of 10 CNC cutting beds cluster, 150kW rated power of workshop power grid and medical coated fabric production orders, the application effect of the adaptive cutting bed power matching adjustment control system (Examples 1-5) of the present invention and the traditional single-machine independent power adjustment system (Comparative Example 1) shows significant differences. The comparison results of the core indicators are as follows.

[0113] In terms of power scheduling and energy utilization, Example 1, relying on the priority quantification algorithm and allocation formula of the cluster power collaborative scheduling module, achieved differentiated power allocation. The power allocated to a single cutting bed for high-priority drug-coated urgent orders reached 25.31kW, and the instantaneous power demand could be met through redundant power scheduling. The workshop power utilization rate was stable at 91%-92%, and there were no grid overload trips throughout the process. In contrast, Comparative Example 1 adopted a fixed 20kW power output and had no dynamic scheduling mechanism. The power of high-priority orders was not guaranteed, and the power of low-priority orders was redundant. To avoid overload, equipment had to be manually shut down, and the actual power utilization rate was only 62%, with an average of 3 grid overload warnings per day.

[0114] Regarding the coating cutting quality, in Example 2, through precise parameter adaptation of the coating characteristic power matching unit, the silver ion short-acting coating achieved a 72-hour sustained-release efficiency of 95% with a deviation of only 2.2%, and the antibiotic long-acting coating had a cut roughness controlled at 1.2 μm and a bonding strength of 4.2 N / cm. In contrast, in Comparative Example 1, due to the lack of a coating-power correlation database, the uniform process parameters resulted in pore compaction of the silver ion coating, leading to a sustained-release efficiency deviation of 11.2%, an antibiotic coating cut roughness exceeding 2.5 μm, and a medical coating cutting qualification rate of only 82%, which was 17.2 percentage points lower than that of Example 1.

[0115] Regarding tool life and cutting accuracy, the vibration compensation and wear warning mechanism in Example 3 extends tool life from 100h to 115h, achieves a cutting accuracy of ±0.01mm, and eliminates coating cracking. In contrast, Example 1, without vibration monitoring and compensation, results in a tool life of only 80h due to abnormal wear, increases the replacement frequency by 43.75%, and makes the cut prone to wavy deviation.

[0116] In terms of parameter iteration and long-term benefits, the feedback correction mechanism in Example 4 reduced the coating cutting defect rate from 4.5% to 1.8%, and the full-process iterative optimization in Example 5 stabilized the workshop cutting qualification rate at 99.2%, reduced the power scheduling delay to 85ms, and improved the overall production efficiency by 22%. In contrast, Comparative Example 1 had no parameter iteration capability, the delivery delay rate of urgent orders reached 18%, and the production cost increased by 15% due to tool wear. Its overall production stability and efficiency were far inferior to the system of this invention.

[0117] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of protection of the claims.

[0118] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An adaptive cutting bed power matching and adjustment control system, characterized in that, The system includes: a cluster power collaborative scheduling module, a single-machine precise power adjustment module, and a data linkage feedback module; The cluster power collaborative scheduling module is equipped with a workshop total power threshold monitoring unit, an order priority sorting unit, and a cutting bed redundant power scheduling unit. The order priority sorting unit is used to generate an order priority coefficient through an order priority quantification algorithm, and is also used to bind the fabric coating attributes and cutting difficulty coefficients corresponding to each order and to divide the order priority according to the order priority coefficient. The cutting bed redundancy power scheduling unit is used to allocate differentiated power to each cutting bed in the cluster through a cluster power allocation algorithm; The single-machine precision power adjustment module integrates a coating characteristic power matching unit and a tool micro-vibration spectrum power compensation unit. The data linkage feedback module is used to synchronize the corrected technical parameters to the order priority quantification algorithm of the cluster power collaborative scheduling module and the coating process and cutting power association database of the single-machine precise power adjustment module. The coating performance feedback correction process of the data linkage feedback module involves extracting the first cut piece after cutting and conducting an in vitro release test. When the coating slow-release efficiency deviation exceeds 3%, it is corrected according to the formula. The power adaptation parameters for the corresponding coated fabrics were corrected, and the database relating coating process and cutting power was updated synchronously. For the corrected power, To correct the previous power, To mitigate efficiency deviations; the tool life and power linkage optimization method of the data linkage feedback module is to combine the actual tool replacement cycle and the vibration spectrum data of the entire tool life cycle, according to the formula Iterative optimization of power compensation coefficients, where The compensation coefficients after iteration These are the compensation coefficients before iteration. The deviation rate between the actual wear amount and the predicted wear amount of the cutting tool can keep the coating cutting defect rate stable at less than 2% over a long period of time.

2. The adaptive cutting bed power matching and adjustment control system as described in claim 1, characterized in that, The tool micro-vibration spectrum power compensation unit integrates a piezoelectric vibration sensor to collect the vibration spectrum data of the cutting tool in real time and input it into the tool life power compensation prediction model. The tool life power compensation prediction model triggers power compensation and power adjustment actions through a power compensation coefficient algorithm.

3. The adaptive cutting bed power matching and adjustment control system as described in claim 2, characterized in that, The order priority sorting unit is used to sort according to Order priorities, ranked from highest to lowest, are: drug-loaded coated fabric orders, ordinary medical coated fabric orders, and regular fabric orders; the sustained-release properties of the fabric coating are divided into short-acting (72-hour sustained-release) and long-acting (one-month sustained-release), corresponding to... The values ​​are 0.5 and 0.3 respectively, corresponding to orders for regular fabrics. The value is 0.1, where This is the order priority coefficient. This represents the coating process complexity coefficient.

4. The adaptive cutting bed power matching and adjustment control system as described in claim 3, characterized in that, The redundant power scheduling unit for cutting beds is used to dynamically schedule redundant power through the workshop's smart grid. During the scheduling process, it needs to receive real-time monitoring data from the workshop's total power threshold monitoring unit. The workshop's total power threshold monitoring unit has a built-in power grid sensor and a real-time power calculation chip, which has a dual-dimensional power monitoring function. It is used to collect the total power supply input from the workshop's smart grid in real time, calibrate 90% of the rated power of the workshop's power grid as the power overload warning threshold, and summarize the real-time operating power of all cutting beds in the cluster to generate a dynamic curve of cluster power load. It also outputs a total power over-limit warning signal and power margin data simultaneously. When the total power of the workshop is detected to be close to 90% of the rated power warning threshold, a dynamic load reduction action is automatically triggered. The operating power of the corresponding cutting bed is reduced from low to high according to the order priority coefficient until the total power falls back to within the safe threshold. During the scheduling process, the total power of the workshop is maintained at no more than 90% of the rated power of the power grid to avoid overload tripping of the workshop's power grid. At the same time, the workshop's total power threshold monitoring unit will feed back the actual load data after power scheduling to the cluster power allocation algorithm to correct the power allocation weight.

5. The adaptive cutting bed power matching and adjustment control system as described in claim 3, characterized in that, The coating characteristic power matching unit has a built-in database linking coating process and cutting power, and is used to match the initial cutting power to the fabric to be cut through the fabric thickness sensor and coating component identification unit. The coating process and cutting power association database of the coating characteristic power matching unit covers the cutting power adaptation parameters of silver ion and antibiotic pharmaceutical components. For short-acting 72-hour sustained-release coated fabrics, the coating characteristic power matching unit enables a cutting mode with a base power of 60% to 70% and a blade gap of 0.15 mm to 0.2 mm. For long-acting one-month sustained-release coated fabrics, the coating characteristic power matching unit enables a cutting mode with a base power of 80% to 90% and a cut roughness of no more than 1.6 micrometers.

6. The adaptive cutting bed power matching and adjustment control system as described in claim 3, characterized in that, The sampling frequency of the piezoelectric vibration sensor is not less than 10 kHz, and the measurement frequency range is from 0.01 Hz to 1000 Hz. The abnormal vibration frequency band of the tool is divided into low-frequency vibration and high-frequency noise. The low-frequency vibration frequency band is 50 Hz to 100 Hz, which corresponds to the micro-chipping state of the tool edge. The high-frequency noise frequency band is 500 Hz to 800 Hz, which corresponds to the resonance state between the tool and the fabric fibers.

7. The adaptive cutting bed power matching and adjustment control system as described in claim 6, characterized in that, When low-frequency vibration is detected, the tool micro-vibration spectrum power compensation unit increases the cutting power by 8% to 12% on the base power allocated by the cluster power collaborative scheduling module, while shortening the single cutting stroke by 10% to 15%. When high-frequency noise is detected, the tool micro-vibration spectrum power compensation unit instantly reduces the cutting power by 5% to 8%, while fine-tuning the cutting angle in 0.5-degree steps. All power adjustment actions are constrained by the power threshold without damaging the coating slow-release structure.

8. The adaptive cutting bed power matching and adjustment control system as described in claim 2, characterized in that, The tool life power compensation prediction model can output tool wear warning signals 2 to 3 hours in advance, with a warning accuracy of no less than 92%. When it is predicted that the tool is entering the critical period of wear, the tool life power compensation prediction model controls the system to reduce the power output amplitude by 10% to 15% and switch to a cutting mode with low power and high cutting frequency, increasing the cutting frequency by 20% to extend the effective service life of the tool and maintain the integrity of the coating structure.

9. The adaptive cutting bed power matching and adjustment control system as described in claim 1, characterized in that, The cluster power collaborative scheduling module is used to statistically analyze workshop power utilization, cut piece pass rate, and power scheduling response delay data on a weekly or monthly basis, using a weighted iterative formula. , , Optimize the weight coefficients of the order priority quantification algorithm, where , , As a correction factor with values ​​ranging from 0.8 to 1.2, the historical monitoring data of the workshop total power threshold monitoring unit is the core data source for workshop power utilization statistics. After optimization, the workshop power utilization rate can be stably maintained at over 85%, the cut piece qualification rate can be stably maintained at over 98%, and the power scheduling response delay can be no more than 100 milliseconds.

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