3844 results about "Thermal deformation" patented technology

The invention relates to the technical field of numerical control machining, in particular to a tool cutting path machining error compensation method based on online monitoring, which comprises the following steps: establishing a cutting path data model; constructing a multi-modal sensor assembly, and collecting error data in real time; establishing an error state equation to carry out error calculation; constructing a double-layer compensation mechanism; and executing the compensation instruction by adopting a real-time control system. Through real-time synchronous monitoring of the multi-mode sensor, a mixed error resolving framework and a double-layer intelligent compensation mechanism, the influence of dynamic error sources such as cutter abrasion and machine tool thermal deformation can be effectively overcome, the machining precision and the surface quality are remarkably improved, and the high-precision machining requirements in the fields of aerospace, precise instruments and the like are met.

The invention relates to the technical field of electronic manufacturing equipment, in particular to an adaptive thermal compensation system and method for a high-precision mounting head of a chip mounter, and the system comprises a temperature-deformation sensing unit, a thermal-mechanical coupling analysis unit, a dynamic compensation control unit, and a closed-loop execution unit. The temperature-deformation sensing unit collects temperature and deformation data of multiple parts of the mounting head in real time, the thermal-mechanical coupling analysis unit reconstructs a three-dimensional temperature field based on a finite element algorithm, the thermal expansion distribution quantity is dynamically calculated, the problem of rough model of traditional single-point temperature measurement is solved, and the measurement precision is improved. The dynamic compensation control unit predicts the thermal drift amount in the future 5 ms through online parameter identification and a long-short-term memory network model, a compensation strategy is adaptively adjusted in combination with the motion working condition, the closed-loop execution unit decomposes the compensation amount into displacement and torsion correction instructions, accurate offset of thermal deformation is achieved, and a whole-process thermal compensation closed loop is constructed. The precision stability of the mounting head in a complex thermal environment is improved, and the production efficiency is improved.

The invention relates to the technical field of numerical control machine tools, and discloses a self-adaptive error compensation method and system for a high-precision numerical control machine tool, and the method comprises the steps: carrying out the mathematical modeling of a multi-dimensional error of a five-axis numerical control machine tool, and obtaining a thermal deformation displacement vector, a friction force vector and a path deviation vector; inputting into a multi-dimensional expansion state observer for error observation to obtain thermal deformation, a friction force value and a path error value; performing trust domain parameter optimization to obtain a thermal deformation compensation gain matrix, a friction force pre-compensation coefficient matrix and a path error compensation coefficient matrix; performing three-stage series compensation calculation to obtain a compensation position instruction, a compensation speed instruction and a compensation acceleration instruction; and track reconstruction operation is carried out to generate a position instruction sequence, a speed instruction sequence and an acceleration instruction sequence of each axis, so that self-adaptive error compensation of the high-precision numerical control machine tool is realized, and the machining precision of the high-precision numerical control machine tool is improved.

The invention relates to the technical field of 3D printing models, in particular to a 3D printing model slice feature compensation method and system and a medium. The method comprises the following steps that a 3D printing model is collected, a model feature skeleton is split, transverse slice features are generated, then a 3D printing environment is collected, virtual simulation is carried out, environment stress analysis is carried out on the skeleton slice features to obtain environment stress data, then deformation scale deduction and thermal deformation prediction are carried out based on the environment stress data, and a thermal deformation model is obtained. On the basis, reverse deformation simulation is carried out, deformation repair requirements are evaluated, a deformation compensation path is planned, finally, compensation simulation of a model feature skeleton is achieved, non-target deformation is analyzed, a compensation path is adjusted, and therefore the feature compensation method is optimized. According to the 3D printing model slice feature compensation method, the accuracy and quality of the 3D printing model are integrally improved.

The invention provides an aluminum alloy auxiliary frame welding accurate positioning and quality control method and system. The method comprises the steps that S4, welding gun track control parameters are updated through a dynamic adjustment instruction, laser tracking data are fused to optimize the welding path angle in real time, and the accurate movement track of each section of welding seam is determined; s5, acquiring real-time thermal expansion data during welding execution, monitoring temperature field distribution of a welding seam area by adopting an optical measurement technology, and judging whether thermal deformation adjustment exceeds a preset threshold value or not; s7, micron-sized welding spot positioning operation is executed according to the stable positioning state, the dynamic path optimization result is fused to generate a final welding instruction, and consistent welding seam quality data is output; and S8, after weld joint quality data are obtained, weld joint deviation and geometric consistency are detected through a laser tracking technology, whether welding quality meets design requirements or not is judged, and a quality verification report is generated. According to the method, the precision and consistency of intelligent welding of the aluminum alloy auxiliary frame are remarkably improved.

The invention relates to the technical field of program control, in particular to a servo position control method and system applied to an engraving and milling machine. The method comprises the following steps that real-time temperature data and real-time load data of lead screws of all shafts in the engraving and milling machine are obtained; collecting multi-node temperature distribution data of the engraving and milling machine; obtaining cutting force data and resonant frequency characteristic values in the engraving and milling machine; constructing a screw rod reverse clearance prediction model based on the real-time temperature data and the real-time load data of the screw rod, and generating a clearance compensation value; performing pre-compensation control before the servo position direction of each axis is changed based on the clearance compensation value to obtain a correction position instruction; and performing thermal deformation simulation on the engraving and milling machine based on the multi-node temperature distribution data to generate thermal deformation compensation amounts of all shafts. Through multi-source data fusion and intelligent control, comprehensive optimization of the servo position system of the engraving and milling machine is achieved, the machining precision, dynamic response and stability are effectively improved, and efficient and reliable operation of high-speed and high-precision machining is guaranteed.

The invention provides a thermal deformation intelligent compensation and control method and system in a metal part welding process, and relates to the technical field of metal welding, and the thermal deformation intelligent compensation and control method comprises the following steps: obtaining a three-dimensional model and process parameters, constructing a thermal-mechanical coupling analysis model, and collecting real-time temperature and strain data; thermal deformation is predicted through a dynamic hierarchical graph structure and a bidirectional propagation neural network, optimal welding process parameters are calculated through a recursive optimizer integrating a gradient strategy and an evolution strategy based on thermal deformation deviation, accurate prediction and intelligent compensation of thermal deformation in the welding process can be achieved, and the welding quality and precision are improved.

The invention belongs to the technical field of laser processing, and particularly relates to a special-shaped curved glass laser cutting track planning method. According to the method, the instantaneous thermal effect and the historical thermal accumulation effect are subjected to coupling calculation, high-precision prediction and compensation of thermal deformation in the laser cutting process are achieved, the accuracy of the cutting track is improved, contour deviation caused by thermal deformation is avoided, and the geometric precision is improved; according to the local geometric complexity of the special-shaped curved glass, regions are divided, and differential virtual scanning layers and scanning modes are matched, so that the dynamic balance of efficiency and precision is guaranteed, the processing quality of regions with high curvature, thin walls and the like is guaranteed, the cutting speed of flat regions is increased, and the processing period is shortened; by monitoring the temperature and feeding back actual thermal historical parameters during cutting, model parameters are reversely optimized by using contour precision data after cutting is completed, so that robustness and stability are enhanced, and the yield and process reliability of laser cutting of the special-shaped curved glass are improved.

The invention discloses a valve performance simulation and optimization method and system based on mixed deep learning, and the method comprises the steps: S1, carrying out the finite element simulation analysis of a valve, and solving through the thermosetting coupling of a multi-physics field, stress, deformation and temperature distribution data of the valve under different working conditions and maximum thermal stress and maximum thermal deformation displacement of key parts of the valve are obtained; s2, after data processing, taking stress, deformation and temperature distribution data of the valve under different working conditions as input parameters, taking maximum thermal stress and maximum thermal deformation displacement as output parameters, training a neural network model, and establishing a thermal-structural performance prediction model; s3, on the basis of a prediction result, a reference point-based non-dominated genetic algorithm is adopted, a reference point generation and self-adaptive agent model is combined, and multi-objective optimization is carried out to output an optimal parameter combination so as to adjust valve design; according to the invention, deep learning and multi-objective optimization are carried out on the finite element simulation result by using the neural network, and the valve performance prediction precision and optimization efficiency are improved.

The invention provides an intelligent real-time detection method and system for PCCP welding quality, and relates to the technical field of online detection and intelligent evaluation of pipeline welding quality through machine learning. Light energy data and multi-light-source images of a spiral weld pool are collected, exposure parameters are dynamically adjusted through the energy difference of visible light near-infrared bands, and the real-time detection of the PCCP welding quality is achieved. Inhibiting strong light interference and generating a weld surface image; a stress concentration area is positioned by scanning a welding seam thermal deformation area and combining speckle pattern change, sound frequency change and the elastic characteristic of the thin-wall steel cylinder; inputting the surface image and the deformation data into a space-time convolutional neural network, fusing light energy change, image details and spatial features to construct a weld joint space structure diagram, and adaptively correcting the position of a sensor; and comparing the sinking depth of the three-dimensional point cloud reconstruction, analyzing the correlation between the sinking degree and the stress, and generating a probability thermodynamic diagram to output the pressure-bearing failure risk level, so that the probabilistic early warning of the pressure-bearing failure risk can be realized.

The invention relates to the field of numerical control machining, discloses a numerical control machining method and system integrating thermal expansion dynamic compensation, and aims to solve the problem that precision is out of control due to thermal deformation in high-speed cutting of motorcycle light alloy castings. The method comprises the steps that distributed temperature and displacement sensors are arranged in a key area of a workpiece, and a temperature field and thermal expansion amount are collected in real time; constructing a local thermal deformation prediction model based on a material expansion coefficient and a geometric structure, and correcting a tool path in real time through a coordinate system dynamic offset algorithm; and an on-line measurement feedback mechanism is introduced, and model parameters are adaptively optimized, so that closed-loop compensation is realized. The system comprises a sensing module, a thermal deformation modeling and compensation calculation module, a coordinate dynamic correction module, an online measurement feedback module and a parameter adaptive updating module. Through millisecond-level dynamic compensation and closed-loop self-optimization, the size precision and form and position stability of the complex thin-wall part under the high-temperature working condition are remarkably improved, the rejection rate and cooling energy consumption are reduced, and the method is suitable for a high-precision batch machining scene.

The invention relates to the technical field of structure optimization design, and particularly discloses a box-type beam structure lightweight design method based on topological optimization, which comprises the following steps: constructing a multi-physics field coupled three-dimensional parameterized model, and performing cross-scale analysis on integrated structure rigidity, thermal deformation, vibration mode and fatigue life to obtain a three-dimensional parameterized model; a variable density method and level set method mixed topological optimization strategy is adopted, and an initial material distribution scheme meeting the structural function integrity is generated by modeling the relationship between density and stress strain; starting a quantum genetic algorithm and deep reinforcement learning fused intelligent optimization engine; according to the method, through the multi-physics field coupled three-dimensional parameterized model, a variable density method and level set method mixed topological optimization strategy is combined, the relation between the structural lightweight target and the additive manufacturing process is effectively balanced, multi-physics field analysis of thermal response, vibration, fatigue and the like is introduced, and the structural lightweight target is obtained. And it is guaranteed that the box-type beam meets the mechanical property and other functional requirements in actual application.

The invention relates to a thermal insulation evaluation method for a light recycled building block based on thermal coupling simulation, which comprises the following steps: modeling the recycled building block into a heterogeneous multiphase complex, and introducing a three-layer structure field of micro pores, mesoscopic aggregates and macroscopic blocks; a partition coupling strategy is adopted, a microstructure variability-heat flux density disturbance-stress field reconstruction causal chain is constructed, and macroscopic thermal insulation performance fluctuation caused by thermal deformation is captured; tracking a thermal stress concentration area caused by temperature difference change through thermal and force coupling simulation; analyzing the influence of a thermal stress migration path on local structure integrity, pore change and crack evolution; constructing a thermal stress and structure disturbance factor framework, and evaluating the influence degree of the structure local deformation on the thermal resistance; extracting high-dimensional feature data; establishing a heat and force characteristic space; constructing a response surface equation, and mapping a change track of the thermal insulation performance in a heat and force coupling response space; a time and structure response composite scoring system is formed, real coupling of multiple physical fields is achieved, and limitation of traditional evaluation is broken through.

The invention discloses a laser-assisted machining path thermal error pre-compensation method, which comprises the following steps of: establishing a force-thermal coupling analysis model for a laser-assisted machining system, accurately calculating the temperature field change and deformation condition of a tool rest structural part in the laser-assisted machining process, and accurately correcting the parameter precision of the force-thermal coupling analysis model through model calibration. Thermal deformation epsilon t of a system tool nose point, a tool placement pose theta and an uncompensated tool path (xt ', zt') are obtained based on model calculation, and a processing tool path (xt, zt) is obtained through pre-compensation tool nose thermal deformation calculation, so that high-precision laser-assisted ultra-precision processing is realized under the condition that a tool rest has a thermal drift error.

The invention discloses a control method and equipment suitable for a rotary turn-over clamp of a numerical control milling center, and relates to the technical field of numerical control machining. The clamping force is optimized through the multi-source sensing and digital twinning technology, and workpiece deformation is prevented; thermal compensation and an error transfer chain model are integrated, the turnover angle is accurately corrected, and error accumulation is restrained; real-time comparison, traceability and self-adaptive adjustment in the machining process are achieved through digital twin pre-verification and multi-sensor closed-loop monitoring; the problems of out-of-tolerance of precision and batch consistency caused by unstable clamping, thermal deformation and error transmission in multi-surface milling of high-precision parts are solved, and the precision, reliability and process adaptability of complex part machining are remarkably improved.

The invention discloses a thermal deformation prediction and optimization method and system in metal plastic composite product processing, and the method comprises the steps: building a composite product geometric model according to the material characteristics and preset boundary conditions of a composite product; according to the geometric model of the composite product, a finite element analysis method is used, a preset time step length and a nonlinear solver are selected for coupling solving of a thermal field and a mechanical field; the change data of the temperature field and the stress field along with time and thermomechanical circulation are analyzed through simulation, accumulated deformation and interface stress data of the material in circulation of the preset number of times are monitored, and a simulation prediction result is generated; and according to the simulation prediction result, the heating and cooling rate and the mold loading path are optimized. The thermal deformation prediction and optimization method in metal plastic composite product processing can be used for solving based on multi-physics field coupling in combination with a nonlinear finite element.

The invention discloses a ship plane segmented welding multi-robot path planning system based on visual inspection, and relates to the technical field of ship manufacturing, the ship plane segmented welding multi-robot path planning system comprises a multispectral visual inspection module which is mounted on a portal frame and comprises a laser scanning sensor and an infrared thermal imager, the system is used for collecting three-dimensional point cloud and temperature distribution data of ship plane segments in real time. According to the ship plane segmented welding multi-robot path planning system based on visual inspection, the problem of path planning misalignment caused by assembly errors, thermal deformation and complex working conditions in large ship plane segmented welding is fundamentally solved through a multispectral visual real-time perception and material self-adaption dynamic correction mechanism. A composite correction vector and space-time grid collaborative pre-judgment technology is adopted, the welding seam track precision is effectively improved, it is ensured that the weld leg size strictly reaches the standard in the high-difficulty processes such as wrap angle welding and vertical position welding of the maximum-size workpiece, the defects such as air holes and cracks are eliminated, and the rework rate and the quality risk are greatly reduced.

The invention relates to the technical field of workpiece airtightness detection, in particular to a workpiece airtightness detection method and system based on multi-source data fusion, and the method comprises the steps: collecting the pressure fluctuation, temperature field distribution and vibration spectrum data of a workpiece through a sensor array, and executing a stepped pressure excitation process; the method comprises the following steps: dynamically configuring an inflation rate according to the heat-conducting property of a material, reversely compensating pressure based on temperature field data in a pressure maintaining stage to eliminate thermal deformation interference, and extracting a pressure attenuation rate and nonlinear characteristics, an area proportion of an abnormal low-temperature region and space aggregation of an energy abrupt change point in a vibration spectrum from compensated data; according to the method, multi-physical field features are fused, the detection precision and reliability are improved, and the method is suitable for the airtightness detection requirement in the high-precision manufacturing field.

The invention relates to the technical field of machine tools, and particularly discloses a gantry machine tool overall real-time thermal error compensation method based on CNN-BIGRU-A. The gantry machine tool overall real-time thermal error compensation method comprises the steps that historical temperature data and historical thermal deformation data of a main shaft and a transmission shaft are obtained; constructing a thermal error prediction model, and training the thermal error prediction model according to the historical temperature data and the historical thermal deformation data to obtain a trained thermal error prediction model; transmitting the current temperature data of the main shaft and the transmission shaft to the trained thermal error prediction model to output a current thermal error compensation value of the main shaft and a current thermal deformation calculation value of the transmission shaft; the machine tool numerical control system calculates the current thermal error compensation value of the target position point according to the coordinate of the target position point on the transmission shaft; and the machine tool numerical control system performs compensation according to the current thermal error compensation value of the main shaft and the current thermal error compensation value of the target position point on the transmission shaft. According to the invention, a high-frequency and high-synchronization compensation strategy can be realized.

The invention relates to a multifunctional deformation measurement device and a measurement method, and belongs to the technical field of thermal deformation measurement. Manufacturing a multifunctional deformation measuring device; marking the test piece to be tested; calibrating the precision of the measurement system by using a reference standard substance; a temperature sensor is installed on the test platform; vacuumizing treatment is conducted through a vacuum system; temperature control is carried out through a temperature precise regulation and control module; forming a heat radiation boundary; adjusting the visual angle and focal length of the measuring camera; adjusting a monochromatic illumination light source to realize light coverage on the tested piece; spraying speckles on the test piece to be tested; measuring the initial state of the tested piece; temperature control is carried out through a temperature precise regulation and control module; testing and recording the deformation condition of the tested piece at each temperature point in the whole test process; the method can solve the problems that a measurement test piece is only limited to a material-grade sample, the measurement environment simulation application range is small, the measurement error is large and the like in a traditional method, and is used for guaranteeing high-precision measurement of thermal deformation of a large-size composite material structure of a spacecraft.

The invention relates to a body weight measuring method and device with automatic calibration and temperature compensation functions, and the method comprises the steps: synchronously obtaining the surface temperature and environment temperature data of a bearing structure through a temperature sensor array; calculating a current temperature difference value between the surface temperature and the environment temperature, generating a control signal when the current temperature difference value exceeds a material thermal deformation threshold value, and calculating a surface temperature change rate; selecting a compensation mode according to the compensation control signal and the surface temperature change rate, starting a compensation process based on a closed loop verification mechanism, and correcting the original weighing value according to a temperature-drift relational database to generate preliminary compensation data; when the calculated accumulated temperature impact value reaches a set threshold value, triggering a parameter self-updating operation to obtain final weighing data; and outputting final weighing data with temperature credibility rating to an interactive interface so as to solve the problems of error accumulation and manual intervention dependence caused by temperature fluctuation in a traditional scheme.

The invention relates to a dynamic precision compensation control method based on an intelligent PCB drilling machine, and the method comprises the steps: collecting a dynamic parameter set in real time through a multi-source sensor group disposed on a drilling main shaft, the dynamic parameter set comprises displacement deviation caused by axial deformation of a main shaft, thermal deformation analyzed based on interlayer temperature gradient and frequency spectrum characteristics reflecting tool-material coupling vibration, and according to the multi-dimensional compensation vector and current drilling process parameters, a space trajectory correction instruction and a motion parameter optimization instruction are dynamically synthesized, so that the dynamic parameter set is obtained. Wherein the trajectory correction instruction reconstructs a real-time interpolation path through a B-spline curve, the motion controller receives a space trajectory correction instruction and a motion parameter optimization instruction, at least three times of compensation iteration are completed in a single drilling period, a linear motor and a spindle motor are driven to execute online precision compensation, and the execution delay of the compensation instruction is smaller than 2 ms.

The invention relates to the technical field of control adjustment, in particular to an intelligent multi-head welding synchronous control system which comprises a data processing module, a modular cooperative control module, a load sensing module, a data transmission module, a self-adaptive pose execution module and a fault-tolerant module. The data processing module extracts three-dimensional geometrical characteristics of a workpiece through laser scanning, PID control parameters are migrated across working conditions in combination with a dynamic time warping algorithm, the inverse kinematics process is optimized, and the self-adaptive pose execution module drives phase synchronization of multiple welding heads based on a global reference trajectory and predicts and compensates thermal deformation errors through a thermal expansion coefficient. And the fault-tolerant module adopts a wavelet packet decomposition identification fault mode, and updates a historical parameter library in combination with an elastic weight algorithm. According to the method, three-dimensional space pose error accumulation caused by mechanical load fluctuation and signal asynchronization is inhibited through cooperation of multiple modules, and the welding process uniformity and the system dynamic stability are improved.

The invention relates to the technical field of artificial intelligence processing, in particular to a manufacturing and processing system based on artificial intelligence simulation control parameters. According to the manufacturing and processing system, three-dimensional space-time coding is carried out on vibration, temperature and deformation time-varying signals through a multi-mode sensing module; generating a composite feature body including an equipment rigidity distribution matrix, a thermal deformation gradient vector and a material residual stress tensor, and solving the problems of spatial-temporal asynchronization and physical field feature splitting of multi-source data; the parameter resolving module constructs a parameter incidence matrix based on a fractal neural network, combines dynamic constraint conditions of thermal deformation gradient vectors, performs multi-objective optimization on a rigidity distribution matrix and residual stress tensor, generates an initial parameter solution set for eliminating time-lag deviation, and breaks through the nonlinear coupling optimization bottleneck of a traditional static model; and the state dissociation module calls a historical wear feature library to construct a performance attenuation reference surface, and tool accumulated wear and instantaneous thermal deformation disturbance are synchronously inhibited through convolution operation and projection correction of a dynamic compensation factor.

The invention relates to a machine tool spindle thermal deformation prediction method based on a GCN-Transform model. The method comprises the following steps: constructing a sensor network for a machine tool; a space-time diagram data set is generated in the three-dimensional model of the machine tool, and the spatial characteristics of the sensor network are represented through an adjacent matrix; constructing a GCN-Transform model, wherein the model comprises an input layer, a one-dimensional convolution component, a multi-head self-attention mechanism, a feedforward neural network layer, an addition and normalization layer and an output layer; performing prediction, extracting spatial features through GCN, extracting time features through Transform, an adjacent matrix and sensor data as input, and performing thermal error; according to the method, the time characteristics are captured by using the Transform model, and then the spatial characteristics in the topological space of the sensor are captured by using the GCN, so that the time characteristics of the thermal error can be accurately captured, and the spatial information of the sensor can be fully utilized, so that the prediction result is more accurate and robust.

The invention provides an SMT patch correction system linked with AOI and a method thereof. The SMT patch correction system comprises a stokehole AOI detection module, a stokehole AOI detection module, a multi-dimensional sensing module, an intelligent data center module, an AI decision optimization module and a process simulation verification module. According to the method, the AOI detection data in front of and behind the furnace are fused through the intelligent data center module, the mapping relation of knowledge graph associated elements, the technology and offset data is constructed, a linkage closed loop is formed, and offset source tracing and full-process dynamic deviation correction are achieved; environmental parameters such as temperature, vibration and suction nozzle pressure are collected in real time through the multi-dimensional sensing module, and the environmental parameters are standardized through an intelligent data platform and then are included into correction logic of the AI decision optimization module, so that dynamic compensation of the influence of environmental factors on the mounting precision is realized; a deep learning and reinforcement learning cooperation strategy is adopted through the AI decision optimization module, parameters are dynamically optimized and corrected in combination with thermal deformation simulation and other multi-source information of the process simulation verification module, and the adaptability to different element types and production scenes is improved.

The invention belongs to the technical field of control valve adjustment, and particularly relates to a military and civilian dual-purpose ship electric control valve actuator which comprises a target analysis module, a dynamic compensation module, a parameter transmission module, a closed loop calibration module and an emergency braking module. Valve displacement increments and initial motor rotating speed parameters are distributed for all the sub-windows, the comprehensive influence of gear return difference, thermal deformation, friction and vibration interference on valve displacement is effectively considered in the execution process of the sub-windows, a mechanism coupling compensation factor with a dynamic learning optimization mechanism is generated, displacement errors are combined to be superposed to the rotating speed parameters of the next window, and a dynamic learning optimization mechanism is generated. According to a double-layer correction framework of child window dynamic compensation and tail end closed-loop calibration, technical closed-loop from local interference suppression to global precision guarantee is achieved, an emergency braking module is additionally arranged to avoid the risk of out-of-control displacement caused by sudden load impact, and efficient and safe operation of a ship is effectively guaranteed.

The invention discloses copper-containing maraging ultrahigh-strength steel and a preparation method thereof, and belongs to the field of steel and iron materials. The copper-containing maraging ultrahigh-strength steel is prepared from the following chemical components in percentage by mass: 14.5 to 16.0 percent of Co, 17.0 to 18.0 percent of Ni, 6.0 to 8.0 percent of Mo, 1.0 to 1.5 percent of Ti, 0.5 to 1.0 percent of Cu, 0.5 to 1.0 percent of Al and the balance of Fe and inevitable impurities. The preparation method comprises the steps of vacuum smelting, high-temperature homogenization, forging cogging, thermal deformation and thermal treatment. According to the copper-containing maraging ultrahigh-strength steel prepared through the preparation method, under the condition that the grain size is larger than or equal to 8.0, the tensile strength of the material reaches 2800 MPa or above, meanwhile, the elongation of 7% or above is kept, and the application requirements of different fields for the ultrahigh-strength steel with the tensile strength of 2800 MPa or above can be met.

The invention discloses an HDI micro blind hole laser drilling processing method and system, and relates to the field of HDI drilling processing, CO2 laser drilling is firstly carried out on a plate, then UV laser shaping is carried out, finally quality detection is carried out, and the core is that a plurality of local datum points distributed in a matrix mode are preset on the HDI plate to be processed. In the CO2 laser drilling process, the drilling task and the positioning action of the local datum point are executed alternately through a control program. By periodically measuring the actual position of the adjacent local datum point in the machining period, the dynamic position offset generated in the area due to the heat effect can be captured in real time, and the machining coordinates of the follow-up target drilling point in the area can be corrected in real time through the offset. The continuous local dynamic compensation effectively overcomes the dynamic thermally induced deformation problem which cannot be handled by the traditional single global correction, so that the drilling precision in the large-size and high-density machining process is ensured.

The invention discloses a method for simulating a mold temperature field and curing deformation through finite elements and a mold optimization design method based on the method. The finite element analogue simulation method comprises the following steps: firstly, modeling and simulating a mold grid; secondly, calculating equivalent thermal and mechanical parameters of the composite material by adopting a multi-scale homogenization method; then, a heat conduction model of the mold and the composite material blade is constructed and coupled with the curing dynamic model through temperature, and mold temperature distribution is simulated; and finally, establishing a mold thermal expansion and curing stress coupling model, and predicting thermal deformation and stress change of the mold. By identifying the weak area of the mold in the simulation process, the mold is optimally designed. By improving a mold temperature field distribution simulation method, optimizing a grid modeling process and introducing an accurate calculation method of equivalent material parameters, the precision of mold design and the controllability of a curing process are effectively improved, so that the problem of inaccurate mold temperature field distribution and curing deformation prediction is solved.