CN-121980936-A - Medical polymer material 3D intelligent printing method based on laser selective sintering process

CN121980936ACN 121980936 ACN121980936 ACN 121980936ACN-121980936-A

Abstract

The invention relates to a 3D intelligent printing method of a medical polymer material based on a laser selective sintering process, which comprises the following steps of recommending optimal initial process parameters based on material characteristics and part requirements, processing according to the optimal initial process parameters, monitoring a processed material in real time through a sensor, calculating and adjusting the process parameters by adopting an AI model if processing defects are monitored, simultaneously executing local repair on the detected defects, updating a process parameter database after each layer of printing is completed, optimizing the process parameters of subsequent layers until the processing flow is finished, and in the printing process, once the defects are monitored, the AI model can quickly calculate and adjust the process parameters without manual intervention, thereby greatly shortening the time for finding problems and solving the problems, and simultaneously, a reinforcement learning algorithm can continuously learn and optimize the process parameter adjustment strategy, so that the adjustment is more accurate and efficient, and the repeated printing and repair time caused by unreasonable parameters is reduced.

Inventors

ZHAN YUN
XIE QING
WANG LIJUN
Qin Jiongsheng
LI BINGQI

Assignees

江西康齿云科技有限公司

Dates

Publication Date: 20260505
Application Date: 20260122

Claims (6)

1. The 3D intelligent printing method of the medical polymer material based on the laser selective sintering process is characterized by comprising the following steps of: S1, recommending optimal initial process parameters based on material characteristics and part requirements; S2, processing according to the optimal initial technological parameters, and monitoring a processed material in real time through a sensor; S3, if the machining defect is detected, calculating and adjusting technological parameters by adopting an AI model, and simultaneously, executing local repair on the detected defect; and S4, updating a process parameter database after printing each layer, and optimizing process parameters of subsequent layers until the processing flow is finished.
2. The method for 3D intelligent printing of medical polymer material based on selective laser sintering process of claim 1, wherein the step S1 comprises: S11, inputting material properties and part requirements; s12, establishing nonlinear mapping from input to output parameters by adopting Gaussian process regression; wherein E is the energy density constraint, v is the scan speed, P is the laser power, h is the layer thickness, and d is the scan pitch; s13, performing multi-objective optimization according to part requirements; Wherein Indicating the requirements of n parts, The weight required by the parts is as follows: ; And S14, solving the multi-objective function to obtain the optimal initial technological parameters.
3. The method for 3D intelligent printing of medical polymer material based on selective laser sintering process of claim 1, wherein the step S2 comprises: the sensor comprises a thermal infrared imager, a sensor and a control unit, wherein the thermal infrared imager monitors a molten pool temperature field; Detecting a processed material image through YOLOv; a laser displacement sensor for measuring layer thickness deviation; carrying out multi-mode fusion on molten pool temperature field data monitored by the thermal infrared imager, processed material image data detected by the high-speed CCD and layer thickness deviation data measured by the laser displacement sensor; and adopting a multi-mode fusion network in deep learning to extract and analyze characteristics of the fused data and locate the defect area.
4. The method for 3D intelligent printing of medical polymer material based on selective laser sintering process according to claim 1, wherein the step S3 comprises: energy density adjustment by PID control: ; Wherein the method comprises the steps of Is the adjustment amount of the laser power, Is a real-time error of the error, , And The target energy density and the real-time feedback energy density, 、 And Are PID gain coefficients, and are determined according to the thermal response characteristics of the material.
5. The method for 3D intelligent printing of a medical polymer material based on a selective laser sintering process according to claim 4, wherein the step S3 further comprises: adjusting the technological parameters through a reinforcement learning algorithm: The state is defect type + position + current parameter; The actions are that the technological parameters are adjusted; the reward function is that the smaller the defect area, the higher the reward, and the lower the energy consumption, the smaller the penalty.
6. The method for 3D intelligent printing of medical polymer material based on selective laser sintering process according to claim 1, wherein the step S4 comprises: According to the probability distribution of the process parameters dynamically adjusted by the real-time processing data, the self-adaptive optimization of the parameters is realized: ; as a vector of the process parameters, Is a priori distribution of the parameters, Is a likelihood function that is a function of the likelihood, Posterior distribution; the optimal parameters of the current layer are transferred to the next layer: ; Wherein, the Is the optimal parameter for the current kth layer, Is a default parameter of the material and, Is the attenuation coefficient.

Description

Medical polymer material 3D intelligent printing method based on laser selective sintering process Technical Field The invention relates to the technical field of manufacturing of biomedical materials, in particular to a 3D intelligent printing method of a medical polymer material based on a laser selective sintering process. Background In modern medicine, the application of medical polymer materials is very wide. The medical polymer materials can not be separated from the tissue engineering bracket, the implantable medical appliance, the drug slow release carrier, the oral cavity repairing material and the like. For example, in tissue engineering, a three-dimensional scaffold is required to be constructed by using a polymer material with good biocompatibility and biodegradability, so as to provide support for cell growth and tissue repair, and in the field of drug slow release, the polymer material can encapsulate drugs, so that the controllable release of the drugs is realized, the curative effect of the drugs is improved, and side effects are reduced. Conventional processing methods, such as injection molding, extrusion, etc., typically require the use of a die. These methods are effective for simple shaped product manufacture, but the accuracy and complexity of processing is greatly limited for complex three-dimensional structures, especially medical products with fine internal structures. For example, it is difficult to precisely control the size, shape and distribution of pores by conventional methods in the manufacture of tissue engineering scaffolds having complex pore structures. 3D printing technology, also known as additive manufacturing technology, is a manufacturing method based on the discrete-pile-up principle. It produces three-dimensional objects by discretizing a three-dimensional model into a series of two-dimensional slices, and then stacking the materials layer by layer. Compared with the traditional manufacturing method, the 3D printing technology has the advantages of no need of a die, capability of manufacturing a complex structure, short production period, high material utilization rate and the like, is very suitable for manufacturing personalized medical products, and is widely applied to the medical field at present, such as manufacturing medical models, operation guide plates, customized implants and the like. However, different 3D printing technologies have differences in material applicability, molding accuracy, mechanical properties, and the like, and an appropriate printing technology needs to be selected according to specific application requirements. At present, manual intervention such as parameter setting, material addition, fault removal and the like is mostly needed in the 3D printing process of the laser selective sintering medical polymer material. The labor intensity of operators is increased, human errors are easily introduced, and the printing quality and efficiency are affected. Meanwhile, the laser selective sintering process of the medical polymer material is influenced by various factors, such as laser power, scanning speed, powder particle size, powder spreading thickness and the like. The interaction between these factors makes control of print quality very difficult. For example, too high a laser power may cause thermal decomposition of the material, while too low a laser power may cause insufficient sintering of the material, affecting the mechanical properties of the product. Therefore, the invention provides a medical polymer material 3D intelligent printing method based on a laser selective sintering process. Disclosure of Invention Aiming at the technical problems existing in the prior art, the invention provides a medical high polymer material 3D intelligent printing method based on a laser selective sintering process. The technical scheme for solving the technical problems is as follows, the medical high polymer material 3D intelligent printing method based on the laser selective sintering process comprises the following steps: S1, recommending optimal initial process parameters based on material characteristics and part requirements; S2, processing according to the optimal initial technological parameters, and monitoring a processed material in real time through a sensor; S3, if the machining defect is detected, calculating and adjusting technological parameters by adopting an AI model, and simultaneously, executing local repair on the detected defect; and S4, updating a process parameter database after printing each layer, and optimizing process parameters of subsequent layers until the processing flow is finished. Further, the medical polymer material 3D intelligent printing method based on the laser selective sintering process, the step S1 comprises the following steps: S11, inputting material properties and part requirements; s12, establishing nonlinear mapping from input to output parameters by adopting Gaussian process regression; s13, performi