331 results about "Machining deformation" patented technology

Disclosed in the present invention is a large complex ellipsoidal part machining deformation control method based on dynamic cutting planning. The method comprises: performing initial clamping on a blank part, constructing a machining coordinate system, completing reference non-contact measurement and reference surface fitting of inner and outer shape surfaces of the blank part, and completing the division of a generatrix tangent plane; on the basis of product feature decomposition, completing in the same coordinate system the comparison between each theoretical section and an actually measured section, completing cutting evaluation based on the generatrix tangent plane in a machining area, and guiding overall machining route planning and local machining route planning; on the basis of route planning and a cuttable margin, using an adjustable support device to complete part clamping based on dynamic adjustment, so as to realize stable cutting under a variable cutting thickness, and thereby solving the problem of overall deformation control of a large complex ellipsoidal part; and completing high-rib feature twist amount identification in combination with adjustable support, and completing tool path trajectory offset compensation on the basis of a relationship between a circumferential offset and an allowance, and thereby realizing precise compensation machining of a mesh after a local twist. The present invention solves the key difficulties of high-rib local twist deformation compensation and overall deformation control on the basis of ensuring the precision of the residual wall thickness during numerical control machining of a large complex thin-walled ellipsoidal part, thereby further improving the overall manufacturing reliability of a large complex ellipsoidal part.

The embodiment of the invention provides a turning and milling combined machining deformation control method and system for a special-shaped part, and is used for the technical field of numerical control machining. The turning and milling combined machining deformation control method for the special-shaped part comprises the steps that structural feature analysis and process association marking are conducted on design data of the special-shaped part to generate a feature association data set, and clamping and process planning are conducted according to a machining constraint database and the feature association data set to generate initial turning and milling combined machining process data; cutting parameter multi-objective optimization solution is carried out on the initial turning-milling combined machining process data to obtain a turning-milling cutting parameter set, and multi-axis linkage analysis and instruction collaborative planning are carried out on the turning-milling cutting parameter set according to the equipment operation feature set to generate a combined machining control instruction set. According to the method, through part key feature recognition and risk marking, combined machining control instructions are generated after layered digital twinning verification in combination with process multi-objective optimization, and the one-time qualified rate of special-shaped part machining and turn-milling combined machining process stability are improved.

The invention discloses a thin-walled part milling deformation prediction method considering residual stress influence. The method comprises the following steps: (1) establishing an initial residual stress distribution model; (2) constructing a machining residual stress prediction model; (3) establishing an initial residual stress and machining residual stress coupling stress model; and (4) constructing a thin-wall part machining deformation prediction model under the action of the coupling stress. The method is used for accurately calculating the milling deformation of the thin-wall part, and the deformation of the thin-wall part is inhibited by controlling and optimizing the milling process parameters of each milling layer.

The invention relates to a preparation method of beryllium-copper alloy. The preparation method comprises the following steps: (S1) accurately weighing the following raw materials by mass: copper, beryllium, copper-yttrium alloy, copper-titanium alloy, copper-manganese alloy and nano ytterbium powder; (S2) the raw materials are added into a vacuum induction furnace, the temperature is increased to 1400-1600 DEG C under the inert atmosphere, after the raw materials are completely molten, a covering agent is spread on the melt, smelting, standing and slagging-off are conducted under the stirring condition, the melt is poured into a mold under the condition of 1100-1200 DEG C, and a beryllium copper alloy ingot is obtained; and (S3) the beryllium-copper alloy ingot is subjected to face milling treatment, solution treatment, cold machining deformation treatment and aging treatment in sequence, and the product beryllium-copper alloy is obtained. A small amount of metal elements are added, aging treatment is carried out under the microwave condition, and then slow cooling is carried out at the constant cooling rate, so that the overaging phenomenon can be remarkably inhibited, the hardness of the alloy is improved, and meanwhile, the mechanical property, especially the stress relaxation resistance, is also improved.

The invention discloses a preparation method for ensuring thickness uniformity and form and location tolerance of a coating of a slender shaft, the slender shaft is a slender stepped shaft-shaped part, the preparation method comprises base body processing before plating, hard chromium plating and machining after plating, in the base body processing process stage before plating, a center hole is adopted as a processing reference, finish machining is carried out according to the shape of the part, and the thickness uniformity and the form and location tolerance of the part are guaranteed. It is ensured that the form and position error and dimensional tolerance of the machined part meet the requirements; in the hard chromium plating stage, the non-chromium-plated part is protected, and the chromium-plated part is subjected to hard chromium plating; and in the post-plating machining stage, the center hole is adopted as a machining standard, post-plating rough machining is conducted firstly, then post-plating finish machining is conducted, grinding is conducted to meet the design requirement, and a plated workpiece is obtained. By the adoption of the preparation method, the problem of machining deformation of the slender shaft type structural part is thoroughly solved, the machining performance is stable, the production efficiency is high, special equipment and tools do not need to be configured, and the method is suitable for large-scale production and machining.

The invention belongs to the related technical field of robot machining deformation optimization, and discloses a redundant angle and process parameter joint optimization method and device for complex curved surface robot machining, and the method comprises the steps: (1) forming a multi-domain composite constraint by a joint movement limit constraint, a pose singularity constraint and a machining deformation error constraint corresponding to a robot machining system; carrying out fusion modeling in the redundant angular space based on multi-domain composite constraints so as to map constraints of different dimensions in different spaces into a unified fusion potential field; (2) establishing a kinetic equation taking a virtual torque generated by the fusion potential field as driving input, sequentially solving based on the obtained kinetic equation and a numerical solution method to obtain a redundant angle of each cutter location point, and then obtaining a continuous and smooth redundant angle track; and (3) based on the obtained redundant angular trajectory, performing iterative solution on the optimization model by using an optimization algorithm to obtain an optimal processing parameter combination. According to the method, collaborative optimization of the process parameters and the redundant corners is realized.

A follow-up auxiliary clamping device for suppressing machining deformation. The adsorption support module supports the workpiece by adsorption from the front, thereby improving the local stiffness of the workpiece; the intelligent recognition module collects the local features and position information of the workpiece; the vertical feed module drives the adsorption support module to feed vertically; the feed adjustment module adjusts the feed movement of the vertical feed module to ensure that the adsorption support module and the workpiece are relatively stationary, thereby achieving stable adsorption support for the workpiece; the quick-change fixing module selects the available connection area of the spindle according to the structure of the machine tool spindle head and selects the clamping buckle or magnetic unit according to its geometric structure and parameters, thereby achieving rapid installation and disassembly of the device; the control module processes the local features and position information of the workpiece and controls the operation of each module. The present invention follows the machine tool spindle, effectively reducing the number of times the fixture and auxiliary clamp are assembled and disassembled, improving the local stiffness of the workpiece through front adsorption support, effectively suppressing the deformation and vibration of the workpiece, and achieving low-cost, high-precision and high-efficiency machining of the workpiece.

The present invention discloses an assembled sealed orifice frame for a large-plate square cabin, comprising a corner profile, an extension profile, a positioning block, and a connector. The corner profile and the extension profile are connected to form a rectangular frame, the extension profile is used to extend the horizontal and / or vertical length of the rectangular frame, and the positioning block and the connector are used to connect two adjacent profiles. The corner profile and the extension profile are both hollow structures, the positioning block is inserted into the inner cavity of one of the two adjacent profiles, the positioning block and the profile in which it is located are detachably connected, the two ends of the connector are respectively inserted into the inner cavities of the two adjacent profiles, the connector is coaxially connected to the positioning block, and the end of the connector away from the positioning block is detachably connected to the profile in which it is located. The present invention solves the problems of difficult sealing and processing deformation of the orifice of a large-plate square cabin, and no longer uses a segmented welding method, without the influence of welding stress, thereby improving the overall skeleton strength, especially the strength of the orifice skeleton corner position.

The invention belongs to the technical field of machining, and particularly relates to a thin-wall structure milling boss clamping layout optimization method considering a feeding path. The method comprises the steps that multiple boss clamping layout schemes are obtained; constructing a thin-wall blank finite element model, and performing finite element calculation to obtain initial residual stress data; building a thin-wall blank milling boss clamping finite element model according to different boss clamping layout schemes, performing grid division, and applying the initial residual stress data to the thin-wall blank milling boss clamping finite element model; a milling feed path is selected, milling force is gradually applied to a milled unit of the thin-wall blank milling boss clamping finite element model according to the advancing distance of a milling cutter, the milling process is simulated, and machining deformation data and residual stress data are obtained; and determining optimal technical indexes of the boss clamping layout scheme, and screening out the boss clamping layout scheme meeting the requirements according to the technical indexes, the machining deformation data and the residual stress data.

The invention discloses a structure evolution method and system for phase change recrystallization coupling of a multiphase metal material, the orientation during martensite generation is calculated through martensite crystallography, martensite growth is carried out, and then the martensite phase change result of the material in a multiphase state is predicted through a metallographic structure determination method. The method is established by utilizing a geometrical relationship between different crystal structures of alpha and beta titanium during martensite phase transformation of the titanium alloy, so that the method can be suitable for predicting martensite phase transformation and dynamic recrystallization coupling of the two-phase titanium alloy. The method can be used for predicting the proportion of martensite phases generated in the actual production process of titanium alloys of different marks, further predicts the surface performance, can remarkably reduce the cost and improve the simulation and analysis efficiency in the actual industrial production, and has important significance on computer-aided analysis and design in the part machining deformation process.

The invention provides a large-scale complex structural member machining deformation simulation dynamic modeling method, and relates to the technical field of machining and manufacturing, and the method comprises the steps: building an intelligent model, and carrying out the dynamic optimization: building a three-dimensional model, marking an easy-to-deform region, embedding tolerance information, and carrying out the self-adaptive grid division; carrying out multi-source data driven physical modeling, collecting data and correcting material attributes, and constructing an intelligent constitutive model; multi-scale coupling dynamic simulation is carried out, and macro-micro model coupling and machining force dynamic prediction are achieved; and digital twinborn verification and closed-loop control are carried out, deformation deviation is quantified, and machining parameters are optimized. According to the method, the machining mechanical behavior of the large complex structural part can be more accurately simulated by accurately marking the easily-deformed area, embedding tolerance information, performing adaptive grid division, driving and correcting material attributes through multi-source data and constructing the intelligent constitutive model, and the simulation precision is improved.

The invention relates to a preparation process optimization method of a zirconium alloy material with high fretting wear resistance, which comprises the following steps: setting a chemical component optimization range of a zirconium alloy, including specific proportions of tin, iron, niobium, chromium and oxygen elements; establishing a computer simulation model, and predicting the wear volume, tribological stability and microstructure evolution of the material under the fretting wear condition; then, a complete optimization scheme is output based on the model optimization homogenization treatment temperature interval, the hot working deformation range, the cold working cumulative deformation degree and the annealing system; and finally, a preparation process sequence including smelting, homogenization treatment, hot working deformation, cold working deformation and final heat treatment is implemented, the zirconium alloy material with the equiaxed grain structure is prepared, and the wear resistance of the zirconium alloy material is verified through an experimental fretting wear performance test. Compared with the prior art, the method has the advantages that through systematic component design and process parameter simulation optimization, the material performance is remarkably improved, and the application reliability is enhanced.

A floating clamping machining process method for aerospace plate parts is characterized by comprising the steps that firstly, a stress groove is machined, and the stress change condition, namely deformation force, of a part machining gap clamping point is measured through a floating clamping device; secondly, in the rough machining stage of the part, when the stress of the clamping point of the part exceeds a set threshold value, the floating clamping device of the clamping point is loosened in a machining gap, and the part is clamped after the stress of the part is rebalanced; and finally, before the finish machining stage, an initial residual stress field is deduced based on the measured deformation force, and the finish machining allowance is simulated, analyzed and optimized based on the initial residual stress field. According to the method, the stress of the part is released in the machining process of the spaceflight plate type part, the finish machining allowance is optimized according to the inferred initial residual stress, and machining deformation control over the spaceflight plate type part can be achieved.

According to the thin-wall part machining method and device, the computer storage medium and the terminal, for a first change curve of strain energy and machining deformation in the layer-by-layer cutting process, it is ensured that the machining deformation newly added in the cutting process is smaller than the overall machining deformation by one grade with the strain energy reduced by 0.9 or above relative to the initial value as the criterion, and the machining deformation is reduced by one grade; the interference of newly increased deformation of finish machining on the machining precision is effectively restrained; the second change curve of the machining deformation of the part and the cutting thickness value of the part and the process allowance change curve are only fitted within the initial boundary range, and the curve fitting strength is reduced; the finish machining allowance when the second change curve and the process allowance change curve intersect is determined as the optimal finish machining allowance, and the requirements that the newly-added machining deformation corresponding to the finish machining allowance after cutting of each layer is minimum and the finish machining allowance needs to be larger than the deformation amount of previous machining are met; and data support is provided for improving the distribution quality of the finishing allowance.

The invention relates to a method for optimizing cutting machining parameters of a cast thin-wall cabin, which solves the problems of low machining efficiency and unstable machining precision of the current cast thin-wall cabin in numerical control machining, and comprises the following steps of: 1, classifying machining features of a cast thin wall, and determining feature allowance based on a three-dimensional scanning result of a casting; step 2, aiming at the divided machining features, based on machining deformation test data, establishing a feature machining deformation prediction model by using a least square support vector machine; and step 3, for the divided machining features, establishing a cutting machining parameter optimization model of the features, and performing optimization solution by using a genetic algorithm to realize cutting machining parameter optimization. According to the method, cutting machining parameter optimization selection is carried out on different machining characteristics, meanwhile, the influence of cutting machining parameters on machining deformation is considered when the cutting machining parameters are optimized, the machining efficiency and precision are considered, and the optimized cutting machining parameters have more guiding significance for actual production.

The invention discloses a milling path planning method and system for stress gradient steepest descent, and the method comprises the steps: carrying out the discretization of a residual stress field based on a lightweight bearing member, and mapping the discretized residual stress field to a milling model, so as to form a high-dimensional matrix; calculating a gradient vector and stress streamline distribution of the residual stress field, and according to the gradient vector and the stress streamline distribution, based on a minimum potential energy principle and a stress steepest descent strategy, performing milling path planning degradation to obtain an optimized baseline; and according to the high-dimensional matrix and the optimized baseline, milling path planning is converted into graph complete traversal with the graph theory as guidance, a steepest descent scheme of strain energy and rigidity is optimized, and an optimal milling path scheme is obtained. The method serves for precision machine manufacturing process design, and the problems of array geometric feature milling path planning and machining deformation control of current lightweight force bearing components are solved; and the method is particularly suitable for light-weight bearing components with array geometric characteristics and high dimensional precision.

The invention discloses a residual stress analysis method and device, a computer storage medium and a terminal.The method comprises the steps that a preset number of initial residual stress distribution data of a thin-walled workpiece blank is generated, and each initial residual stress distribution data is simulated through a finite element model; rough machining deformation field data caused by redistribution of the residual stress after the blank material is removed of each initial residual stress distribution data are obtained; in order to solve the problem that complexity in the manufacturing process needs to be considered when initial residual stress field data is obtained from rough machining deformation field data inversion, a deep neural network model used for determining the mapping relation between initial residual stress data and rough machining deformation data is established according to mapping relation data; rough machining deformation field data of actual machining is input into the deep neural network model, complex theoretical analysis and derivation are bypassed, and on the basis of not damaging the structure of the blank, the initial residual stress field prediction of the thin-walled workpiece blank is achieved.

The invention relates to a method for predicting force-induced deformation of a titanium alloy thin-wall part in an end milling machining process by considering tool wear, and belongs to the technical field of cutting machining. The method comprises the following steps: firstly, constructing an annular cutter milling thin-wall part overall milling force model considering cutter wear; on the basis, a force-induced deformation model of the material removal effect in the end milling machining process of the thin-walled workpiece is established based on a small deflection deformation theory. The model can correct element stiffness matrixes at different feeding positions after materials are removed in the milling process of the thin-wall part, and rapid extraction of force-induced deformation of the thin-wall part is achieved. Finally, an iterative calculation method is adopted, and accurate prediction of cutting force and machining deformation at different feeding positions in the end milling machining process of the thin-walled workpiece is achieved. According to the method, the influence of cutter abrasion on the milling force when titanium alloy type difficult-to-machine materials are milled is considered, and the force-induced deformation predicted value after cutter abrasion in end milling of the titanium alloy thin-wall part can be accurately obtained.

The invention discloses a high-precision optical element processing system based on ion beam shaping and self-adaptive detection, the optical element processing system comprises an ion beam processing module, a self-adaptive optical detection module and an intelligent control module, the ion beam processing module comprises an ion source system and a six-axis linkage workpiece table, the self-adaptive optical detection module comprises a wavelength tuning interferometer and a Hartmann wavefront sensor, the intelligent control module comprises a machining path optimization unit and a stress compensation unit, and the system realizes sub-nano-scale real-time feedback of machining errors through online detection of the Hartmann wavefront sensor and the wavelength tuning interferometer; the device breaks through the hysteresis of traditional off-line detection, solves the problem of machining deformation of ultrathin elements, supports machining of special-shaped elements such as aspheric surfaces, off-axis paraboloids and micro-lens arrays, and is suitable for different materials due to the modular design by allowing a detection module or a machining module to be replaced.

The invention discloses an aluminum-manganese alloy and a preparation method and application thereof, and relates to the technical field of alloy materials. The aluminum-manganese alloy disclosed by the invention is prepared from the following components in percentage by mass: 1.22 to 1.7 percent of Mn, 0.2 to 0.4 percent of Si, 0.2 to 0.5 percent of Cu, 0.05 to 0.2 percent of Mg, 0.01 to 0.05 percent of Ti, 0.32 to 0.8 percent of Fe, 0.05 to 0.3 percent of Gd, 0.05 to 0.1 percent of Zr, less than or equal to 0.15 percent of inevitable impurities and the balance of Al. The aluminum-manganese alloy has excellent yield strength, tensile strength and ductility, a hollow profile obtained after extrusion has high strength and toughness, the mechanical property requirement of the battery shell can be met without cold machining deformation such as drawing, and the aluminum-manganese alloy is particularly suitable for preparing the battery shell.

The invention discloses a thin-walled workpiece machining deformation prediction method. The thin-walled workpiece machining deformation prediction method comprises the following steps that S1, a time change model of the machining process of a thin-walled workpiece is established; s2, matching the cutting load point cloud with the geometric point cloud of the part; s3, a graph reconstruction process of the overall stress point cloud of the part; s4, processing deformation prediction based on depth map convolution; part geometry and actual cutting load data are modeled into a point cloud model in a three-dimensional space, the point cloud model and the point cloud model are effectively combined through point cloud matching, and accurate characterization of overall stress of the part in the cutting process is achieved. Thirdly, reconstructing the point cloud of the overall stress of the part into a graph model, taking points in the point cloud as nodes of the graph model, and taking an influence relationship between cutting loads as edges of the graph model, so as to realize simulation of geometric and stress changes of the part in the cutting process; and finally, designing a depth map convolution network, and realizing prediction of graph node attributes, namely processing deformation, by combining graph convolution operation with a multi-layer perceptron.

The invention discloses a high-precision automatic welding robot, and relates to the technical field of welding processing, the high-precision automatic welding robot comprises a supporting device and a welding device, the supporting device is provided with a fixing device I for externally clamping a three-way pipe to be processed, and the left part, the right part and the front part of the bottom wall of an upper pressing table are fixedly connected with U-shaped supporting frames; the U-shaped supporting frames are each provided with a second fixing device for conducting inner supporting on the three-way pipe to be machined, and the supporting devices and the U-shaped supporting frames are jointly provided with a butt joint device and a welding device. Through cooperation of the first fixing device and the second fixing device, the to-be-machined three-way pipe is fully limited, the stability is guaranteed, and machining deformation is prevented; the butt joint device is matched with the welding device, so that the feeding efficiency of the to-be-machined flange is improved, and butt joint is stable and accurate; and the cooling mechanism and the inner supporting piece are matched to cool the welding seam area and the inner supporting area correspondingly, and the cooling efficiency is improved.

The invention discloses a processing information analysis optimization method for furniture manufacturing and a related device, and relates to the technical field of data processing, and the method comprises the steps: carrying out the order splitting of furniture model data, and obtaining the part data of target furniture; performing machining deformation prediction based on initial machining process information determined by the part data and the cutting temperature model to correct the initial machining process information; processing equipment scheduling analysis is carried out based on the target processing technology information; performing equipment state detection on the target scheduling processing equipment based on the target processing technology information in combination with response surface modeling; adjusting the target processing technology information based on the equipment state detection information; furniture manufacturing analogue simulation is carried out based on the adjusted target processing technology information to optimize the processing technology information, and the control equipment carries out furniture manufacturing according to the optimized target processing technology information. According to the method, the reliability of processing technology information analysis can be guaranteed, and the manufacturing and processing of furniture are closer to an ideal effect.

The invention discloses a thin-walled workpiece machining deformation prediction method based on multi-source coupling residual stress, which comprises the following steps of: 1, obtaining a milling residual stress layer depth distribution curve under different machining parameters in a feeding coordinate system, and determining the position of a part surface calculation point in a workpiece coordinate system in a milling path, the milling residual stress in the feeding coordinate system is converted into equivalent milling residual stress distribution under the workpiece coordinate system by combining the included angle between the feeding direction and the coordinate axis of the workpiece; 2, based on an equivalent moment method, establishing a redistribution initial residual stress model of the thin-wall part in a bidirectional stress state; 3, according to the coupling characteristics of the plastic deformation area, the elastic recovery area and the elastic deformation area in the depth direction, a surface and subsurface coupling residual stress distribution model of the thin-wall part is established; and 4, on the basis of an equivalent moment method, enabling the coupling residual stress to be equivalent to additional torque, and predicting the bending deformation of the thin-wall part through the displacement and strain relation and the Hooke's law.

The invention provides a metal part additive and subtractive deformation prediction and control method and system. The method comprises the steps that a finite element model of an additive manufacturing process is established, material equivalent inherent strain of laser directional energy deposition under different processes is calculated, and a mapping relation between laser deposition process parameters and the material equivalent inherent strain is established; establishing a finite element model of a subtractive milling process, extracting milling loads applied to a workpiece by a milling tool bit under different processes, and establishing a mapping relation between a milling process and the milling loads; building a macrostructure additive and subtractive finite element model, calculating the residual stress of the structure under the laser directional energy deposition process through an inherent strain method, and loading a milling load according to a milling path to calculate the overall deformation of the structure in the subtractive process; and through the established mapping relation and the macro-structure additive and subtractive finite element model, the additive and subtractive composite process optimization design with the minimized structural deformation is developed, and macro-structure manufacturing deformation control is achieved.

The utility model discloses a thin-wall end socket machining deformation precision size control device which comprises a clamp body, a placing table is arranged on the upper portion of the clamp body, a centering structure and a fixing mechanism are arranged on the placing table, a center protruding portion is arranged on the placing table, the centering structure comprises a disc spring arranged around the center protruding portion, and the disc spring is connected with the fixing mechanism. A locking disc is arranged on the upper portion of the disc spring, a locking connecting rod is connected to the locking disc, a through hole is formed in the center of the center protruding part, the locking connecting rod is movably arranged in the through hole, the position of the locking connecting rod is adjusted so that the distance between the locking disc and the disc spring can be changed, and centering of the thin-wall end socket can be achieved. And the top of the thin-wall sealing head is pressed. Precise positioning and reliable clamping of the seal head part on a machine tool can be easily achieved, it is guaranteed that the machining size of the seal head part meets the requirement, and the problem that the machining size of the seal head is out of tolerance is solved.

The invention relates to the field of precision machining, and discloses a thin-walled workpiece machining deformation prediction and optimization method under multiple working conditions. Comprising the following steps: setting a fixed constraint and an initial environment temperature by constructing a finite element model containing an initial residual stress field; the cutting effect of the tool is equivalent to a milling force-temperature load, a stress and a temperature field of a tool-workpiece contact area are calculated, and material removal is simulated by using a life-death unit technology; based on a Python script, establishing a space mapping algorithm of tool location point coordinates and grid units to obtain a tool path file; a working condition combination matrix of a cutting mode-machining sequence is constructed, and multi-working-condition simulation is conducted on nine machining strategies; a deformation prediction matrix of multiple working conditions is constructed, and a minimum deformation processing strategy is output through iterative optimization; the machining deformation can be obviously reduced by preferably selecting the following peripheral mode and the cross machining sequence. The method solves the problems of prediction and optimization of machining deformation of the thin-walled workpiece under multiple working conditions, and contributes to key technical support for the field.

The embodiment of the invention discloses a multi-sensor monitoring and compensating method for machining deformation of a large annular part. According to the embodiment of the invention, the feed-forward compensation amount can be generated on the basis of the predicted radial deformation amount of the stress abrupt change area in the surface radial deformation appearing time when the large annular part is machined, and then the feedback compensation amount is generated according to the deviation between the expected machining contour and the actual radial position data of the large annular part; and generating a total compensation amount according to the feedback compensation amount and the feed-forward compensation amount, and adjusting the motion trail of a cutter on the machine tool according to the total compensation amount, and the expected machining contour, the shape tolerance and the position tolerance of the large annular piece. Therefore, according to the embodiment of the invention, deformation caused by stress release can be compensated in real time in the machining process of the large annular part, and the compensation efficiency is improved.

The invention relates to the technical field of aero-engines, and discloses a multi-sensor data fusion method for processing a blisk of a gas compressor, which comprises the following steps of: performing filtering and time alignment on data signals of each sensor, and normalizing the data; then, feature extraction is conducted on the vibration signals and the power signals through a time-frequency domain double-flow input BiLSTM feature extraction module, feature extraction is conducted on the temperature signals through the BiLSTM feature extraction module with a differential structure, extracted features and machining parameters are fused, and machining deformation prediction is conducted through a machining deformation prediction model based on a feature fusion result; the problem that multi-sensor signals are difficult to fuse is solved.