Gear production press-fitting and checking system and method

Abstract

The application relates to the technical field of gear production, and particularly provides a press-fitting verification system and method for gear production, which comprises a dynamic stress field capturing subsystem, a micro deformation field reconstruction subsystem and an integrated resonance verification subsystem. The method comprises the following steps: forming a piezoelectric nanowire network through a nanometer piezoelectric material deposition process, capturing a dynamic stress field in a press-fitting process, and outputting a stress field space-time sequence; receiving the stress field space-time sequence, reconstructing a micro deformation field of the gear through space-time deconvolution processing, realizing space-time deconvolution processing based on wave propagation principle, and outputting a deformation field distribution diagram; receiving the deformation field distribution diagram, synthesizing theoretical resonance characteristics through a structure resonance model, matching the structure resonance model with measured resonance characteristics through a discretized structure dynamics method, obtaining the measured resonance characteristics through an acoustic resonance scanner, and outputting a press-fitting quality verification value. The application improves the controllability of a gear press-fitting process and the reliability of a product.

Description

Technical Field

[0001] This invention relates to the field of gear manufacturing technology, and in particular to a press-fitting and calibration system and method for gear manufacturing. Background Technology

[0002] In the gear manufacturing industry, press fitting is a core step in assembling gears with key components such as shafts and bearings. Traditional press fitting processes rely primarily on manual experience or simple pressure-displacement monitoring, lacking systematic and real-time verification of press fitting quality. With increasing demands for industrial automation and precision manufacturing, gear transmission systems face increasingly stringent requirements for assembly accuracy, fit stability, and lifespan reliability. This is particularly true in fields such as new energy vehicles, high-end equipment, and aerospace, where even micron-level assembly deviations can lead to decreased transmission efficiency, increased noise, and even premature component failure. Therefore, developing a verification technology capable of real-time monitoring, intelligent evaluation, and automatic correction of press fitting quality has become an urgent need to improve the performance and consistency of gear products.

[0003] Prior art 1, Chinese Patent Application No. 201510074486.8, discloses a gear press-fit verification system, including an ultrasonic sensor, an infrared ranging sensor, a weight sensor, a sensor information processing module, an RFID tag reader, a data transmission module, a data server, an integrated data processing module, and a monitoring electronic dashboard. The ultrasonic sensor, infrared ranging sensor, and weight sensor are electrically connected to the sensor information processing module; the sensor information processing module and the RFID tag reader are electrically connected to the data transmission module; the data transmission module and the data server are electrically connected to each other; the data transmission module and the integrated data processing module are electrically connected to each other and transmit data; the monitoring electronic dashboard is electrically connected to the data transmission module. Its advantages are: it obtains the process information of the standard assembled gear through the RFID tag reader and installs the gear in place according to the assembly instructions; the sensors monitor the diameter and weight of the assembled gear in real time and verify it in a timely manner. Although it significantly reduces the rate of gear misassembly and omission, lowers the overall product failure rate, and makes production management more orderly, monitoring macroscopic physical quantities solely through ultrasonic, infrared ranging, and weight sensors cannot capture the dynamic stress distribution and microscopic deformation inside the gears and at the contact interfaces during the pressing process. Its verification is based on static comparison of geometric dimensions and weight, which cannot reveal changes in the internal microstructure of the material caused by assembly stress, and lacks the ability to detect potential hidden defects caused by the pressing process.

[0004] Prior art 2, Chinese patent application number 202411322498.3 discloses a press tool for producing speed reducers, including a workbench and two hydraulic presses. The top of the workbench is fixedly mounted with a bracket and a material cylinder by screws. The side wall of the bracket is integrally formed with a hydraulic chamber. One of the hydraulic presses is fixedly installed in the hydraulic chamber. The bottom of the workbench is integrally formed with a rotating chamber. Although the synchronous rotation of rotating shaft one and rotating shaft two can ensure that bearing one and gear shaft will not be misaligned or over-tightened during the pressing process due to positional deviation, and the moving spring plate three and top plate can ensure that the entire machine can be loaded without manual shutdown when the bearing clamps are filling bearing one, and the contact between spring one and rotating shaft one can ensure that the output gear shaft will not have bearing one not pressed or only one bearing one pressed during the pressing process; however, the focus is on improving the mechanical structure to ensure alignment accuracy and continuous loading, but no sensing and processing modules are integrated to monitor and quantify the pressing process itself in real time; its function is limited to physical positioning and process automation, and it cannot perform non-destructive verification of the internal connection quality, stress state, and structural integrity of the gear-shaft assembly after pressing.

[0005] Prior art 3, Chinese patent application number 202011016611.7, describes an automatic pressing fixture for open retaining rings on gear shafts, comprising a worktable, a gear feeding mechanism, a retaining ring feeding mechanism, and a pressing mechanism disposed on the worktable; the gear feeding mechanism includes a slide rail disposed on the worktable, a pressing base mounted on the slide rail and capable of sliding along the slide rail, and a gear positioning shaft disposed on the pressing base; the retaining ring feeding mechanism includes a feeding plate disposed on one side of the slide rail; the feeding plate is located above the slide rail and can move along its length, and a retaining ring receiving groove is provided at one end near the slide rail; the pressing mechanism includes a pressing head disposed directly above the slide rail, the pressing head including a frustum-shaped guide post, a retaining ring pressing block, and a retaining ring stop block integrally disposed between the guide post and the retaining ring pressing block. Although it can achieve automatic press-fitting of open retaining rings for gear shafts with high production efficiency, the automated feeding and positioning of the retaining ring press-fitting process does not involve mechanical state monitoring during the press-fitting process or quality assessment after press-fitting. The output is the physical component that completes the press-fitting action, and it does not have the function of performing any form of quality inspection or performance judgment on the press-fitting result.

[0006] Current technologies 1, 2, and 3 generally lack the ability to capture the internal stress field with high spatiotemporal resolution during the dynamic pressing process, and lack methods for quantitatively reconstructing and analyzing the microscopic deformation state of the pressed component. Consequently, they cannot achieve the problem of correlating process mechanical data with the final component structural resonance characteristics in a modeling manner. Therefore, this invention provides a pressing verification system and method for gear production. Summary of the Invention

[0007] To achieve the above objectives, the present invention adopts the following technical solution:

[0008] In one aspect, the present invention provides a press-fit calibration system for gear manufacturing, comprising:

[0009] The micro-deformation field reconstruction subsystem is responsible for receiving the spatiotemporal sequence of the stress field and reconstructing the micro-deformation field of the gear through spatiotemporal deconvolution processing. The spatiotemporal deconvolution processing is digitally implemented based on the wave propagation principle and outputs a deformation field distribution map.

[0010] The integrated resonance verification subsystem is responsible for receiving the deformation field distribution map, synthesizing theoretical resonance characteristics through the structural resonance model, performing mode matching between the structural resonance model and the measured resonance characteristics through the discretized structural dynamics method, acquiring the measured resonance characteristics through the acoustic resonance scanner, and outputting the press-fit quality verification value.

[0011] In one optional implementation, the micro-deformation field reconstruction subsystem includes:

[0012] The data fusion component is responsible for first fusing the spatiotemporal sequence of the stress field with the medium topology data, which contains the geometric and material distribution information inside the gear. The distortion of the stress wave propagating in the gear medium is corrected by the dispersion compensation algorithm to generate a medium-corrected stress field.

[0013] The model building component, responsible for the stress field of medium correction, is then input into the wave propagation inversion kernel. The wave propagation inversion kernel is built based on the propagation model of elastic waves in solids. It reverse-engineers the distributed force source acting on the gear surface during the press-fitting process through deconvolution operation, and generates an equivalent distributed force source map.

[0014] The force source mapping component is responsible for coupling the equivalent distributed force source map with the nonlinear compliance tensor field. The nonlinear compliance tensor field characterizes the deformation response relationship of the gear material under complex stress state. Through tensor field transformation, the distributed force source is mapped to the microscopic deformation distribution of the gear body, generating a deformation field distribution map.

[0015] In one optional implementation, the integrated resonant verification subsystem includes:

[0016] The digital adaptation component is responsible for digitally adapting the gear press-fitting system based on the principles of structural dynamics. It discretizes the gear structure into multiple micro-units, and the mechanical parameters of each micro-unit are determined by the deformation information at the corresponding position in the deformation field distribution diagram. By solving the discretized structural dynamics equations, it simulates the dynamic behavior of the gear under resonance conditions and synthesizes theoretical resonance characteristics from the structural resonance model. The theoretical resonance characteristics are presented in the form of a digital sequence.

[0017] The measured resonance feature acquisition component is responsible for scanning the press-fitted gear with an acoustic resonance scanner and capturing the resonance features. It excites the gear by emitting sound waves within a frequency range and monitors the gear's resonance response in real time. The measured resonance features are extracted from the resonance response and presented in the form of a digital sequence, including the gear's resonance frequency and vibration mode under actual press-fitting conditions.

[0018] The pattern matching and verification component is responsible for performing pattern matching between the theoretical resonance features output from the theoretical resonance feature synthesis process and the measured resonance features output from the measured resonance feature acquisition process. The pattern matching is based on the wave propagation principle of resonance features to achieve digital comparison, and the similarity or difference between the two in resonant frequency and vibration mode is analyzed by algorithm. Based on the results of pattern matching, the pressing quality verification value is generated.

[0019] In one optional implementation, the pattern matching and verification component includes:

[0020] The wave propagation path alignment sub-component is responsible for inputting the digitized sequences of theoretical and measured resonance characteristics, and generating a wave propagation path topology mesh for the gear structure based on the digital application of wave propagation principles. Using the wave propagation path topology mesh, each vibration mode in the theoretical sequence and the vibration mode in the measured sequence are aligned by structural spatial mapping according to the excitation node position and propagation attenuation profile in the wave propagation path topology mesh, forming a set of aligned theoretical-measured vibration mode feature pairs, and simultaneously completing the alignment of the resonant frequency on the topology mesh nodes.

[0021] The covariance quantization sub-component is responsible for receiving the aligned feature pairs output from the wave propagation path alignment process; for each aligned feature pair, it calculates in parallel the morphological variation between each pair of theoretical vibration modes and measured vibration modes, as well as the frequency shift between each pair of theoretical resonant frequencies and measured resonant frequencies at their respective nodes; and integrates the variation and frequency shift of all feature pairs to generate a multidimensional covariance distribution spectrum.

[0022] The integrated verification value generation sub-component is responsible for receiving the covariance distribution spectrum output from the covariance quantization process, fusing the multi-dimensional difference information in the covariance distribution spectrum; determining the contribution of each path in the wave propagation path topology grid to the overall resonance behavior through pre-analysis of wave energy flow; and combining the fused covariance distribution spectrum with the contribution to output the press-fit quality verification value.

[0023] In one optional implementation, the comprehensive verification value generation sub-component includes:

[0024] The contribution topology tensor construction module is responsible for receiving the multidimensional covariance distribution spectrum output by the covariance quantization sub-component; calling the pre-generated wave energy flow analysis results, defining the contribution weight of each path in the wave propagation path topology grid to the overall resonance behavior; and constructing a contribution topology tensor based on the contribution weight to encapsulate the coupling contribution relationship between paths. Its dimension matches the dimension of the covariance distribution spectrum, and the value of each element is determined by the contribution weight of the corresponding topology path and the weight of the path connected to it.

[0025] The spectral tensor shrinking module is responsible for combining the covariance distribution spectrum with the contribution topology tensor output from the contribution topology tensor construction process. Performing the spectral tensor shrinking operation is an operation in tensor algebra, which is applied to fuse the multidimensional difference information in the distribution spectrum along the association structure defined by the contribution topology tensor. Through the shrinking operation, the covariance distribution spectrum is mapped into a dimension-reduced fused difference tensor.

[0026] The resonant offset scalar generation module is responsible for receiving the fused difference tensor output from the spectral tensor shrinking process, inputting it into the resonant offset program, processing the fused difference tensor, and outputting the pressing quality verification value.

[0027] In one optional implementation, the resonant offset scalar generation module includes:

[0028] The intrinsic perturbation manifold construction submodule is responsible for receiving the fused difference tensor output by the spectral tensor shrinking module and constructing an intrinsic perturbation manifold based on the eigenmode space of the structural resonance model. The intrinsic perturbation manifold is defined as a continuous unified body of the resonance state changes caused by all possible structural perturbations. The geometric properties of the intrinsic perturbation manifold are jointly determined by the eigenvectors of the structural resonance model in its basis space and the metric tensor. The components of the metric tensor are initialized by the elements in the fused difference tensor.

[0029] The State Trajectory Mapping submodule is responsible for defining the multidimensional differences represented by the fusion difference tensor as a state evolution trajectory on the intrinsic perturbation manifold based on the geometric structure of the intrinsic perturbation manifold.

[0030] The global curvature integral submodule is responsible for integrating the intrinsic geometric curvature of the intrinsic perturbation manifold along the curve of the state evolution trajectory, and outputting a resonant offset scalar as a pressing quality verification value.

[0031] In one optional implementation, the global curvature integral submodule includes:

[0032] The normal bundle curvature density field construction unit is responsible for receiving the state evolution trajectory defined by the state trajectory mapping submodule; and constructing a normal bundle curvature density field based on the metric tensor of the intrinsic perturbation manifold and the tangent vector direction at each point on the trajectory.

[0033] The trajectory curvature density shrinking unit is responsible for performing integral preprocessing on the normal bundle curvature density field output from the normal bundle curvature density field construction process along the state evolution trajectory. It projects and compresses the high-dimensional object of the normal bundle curvature density field onto the one-dimensional path of the state evolution trajectory, thus obtaining the trajectory curvature density function with a curve distribution along the state evolution trajectory.

[0034] The gauge-invariant integrator unit is responsible for receiving the trajectory curvature density function output from the trajectory curvature density contraction process and performing gauge-invariant integration operations. It obtains scalar results in the curved space by means of the integrator kernel, which is independent of the coordinate selection. The construction of the integrator kernel depends on the global topological invariants of the eigen-perturbation manifold. It outputs a resonant offset scalar.

[0035] In one optional implementation, the gauge-invariant integral unit includes:

[0036] The indicative form extraction sub-unit is responsible for receiving the global differential structure of the manifold defined by the intrinsic perturbation manifold construction process, extracting the differential form representing its global topological properties from the curvature form of the intrinsic perturbation manifold, and outputting one or more closed topological indicative forms;

[0037] The canonical adaptation kernel function generation sub-unit is responsible for receiving the topological characteristic form output from the characteristic form extraction process; at the same time, it receives the domain and characteristics of the trajectory curvature density function output from the trajectory curvature density contraction process; based on the topological characteristic form and combined with the local coordinate neighborhood structure of the manifold where the state evolution trajectory is located, a canonical adaptation kernel function is constructed.

[0038] The invariant integral kernel synthesis subunit is responsible for synthesizing the standard-fit kernel function output from the standard-fit kernel function generation process with the parameterized representation of the state evolution trajectory itself, and performing the invariant integral kernel synthesis operation; it combines the standard-fit kernel function with the arc length infinitesimal of the trajectory induced by the metric tensor on the state evolution trajectory to form an integral infinitesimal form that is standard-invariant in line integrals.

[0039] In one optional embodiment, a dynamic stress field capture subsystem is further included, which is responsible for capturing the dynamic stress field array composed of a piezoelectric nanowire network formed by a nanopiezoelectric material deposition process, capturing the dynamic stress field during the pressing process, and outputting the spatiotemporal sequence of the stress field.

[0040] In another aspect, the present invention provides a press-fit verification method for gear production, used to implement the aforementioned press-fit verification system for gear production, the press-fit verification method for gear production comprising the following steps:

[0041] A dynamic stress field trapping array is constructed from a piezoelectric nanowire network. The piezoelectric nanowire network is formed through a nanopiezoelectric material deposition process to trap the dynamic stress field during the pressing process and output the spatiotemporal sequence of the stress field.

[0042] The system receives the spatiotemporal sequence of the stress field and reconstructs the microscopic deformation field of the gear through spatiotemporal deconvolution processing. The spatiotemporal deconvolution processing is digitally implemented based on the wave propagation principle and outputs a deformation field distribution map.

[0043] The system receives the deformation field distribution map, synthesizes theoretical resonance characteristics through a structural resonance model, performs mode matching between the structural resonance model and the measured resonance characteristics using a discretized structural dynamics method, acquires the measured resonance characteristics through an acoustic resonance scanner, and outputs the press-fit quality verification value.

[0044] This invention's dynamic stress field capture subsystem utilizes the high-density sensing characteristics of piezoelectric nanowire networks to continuously monitor transient stress distribution during press-fitting, generating high spatiotemporal resolution stress field sequence data. The micro-deformation field reconstruction subsystem, based on a spatiotemporal deconvolution algorithm using wave propagation principles, transforms the stress sequence into a visualized distribution of the micro-deformation field within the gear, revealing the local deformation behavior of the material during compression. The integrated resonance verification subsystem establishes a quantitative correlation between deformation field distribution and press-fitting quality through pattern matching between the theoretical characteristics of the structural resonance model and measured acoustic resonance scanning data, enabling non-destructive assessment of assembly consistency and structural integrity. Attached Figure Description

[0045] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0046] Figure 1 This is a block diagram of the gear manufacturing press-fit verification system provided in Embodiment 1 of the present invention;

[0047] Figure 2 This is a schematic diagram of the gear production press-fit verification system provided in Embodiment 1 of the present invention;

[0048] Figure 3 This is a block diagram of the dynamic stress field capture subsystem provided in Embodiment 3 of the present invention;

[0049] Figure 4 This is a block diagram of the micro-deformation field reconstruction subsystem provided in Embodiment 4 of the present invention;

[0050] Figure 5 This is a block diagram of the integrated resonant verification subsystem provided in Embodiment 7 of the present invention;

[0051] Figure 6This is a flowchart of the gear manufacturing press-fit verification method provided in Embodiment 13 of the present invention;

[0052] Figure 7 A block diagram of the electronic device provided by the present invention;

[0053] Figure 8 A block diagram of a computer-readable storage medium provided for this invention. Detailed Implementation

[0054] The technical solutions of the present invention will now be described with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0055] Hereinafter, the terms "first," "second," etc., are used for descriptive convenience only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0056] In this invention, unless otherwise explicitly specified and limited, the term "connection" should be interpreted broadly. For example, "connection" can be a fixed mechanical connection, a detachable mechanical connection, or an integral part; or, "connection" can be a direct connection or an indirect connection through an intermediate medium. Furthermore, unless otherwise explicitly specified and limited, the term "coupling" should be interpreted broadly. For example, "coupling" can be a direct electrical connection, such as physical contact and electrical conduction between two components; it can also be understood as an electrical connection between different components in a circuit structure through physical lines capable of transmitting electrical signals, such as copper foil or wires on a printed circuit board (PCB), to transmit electrical signals; or, "coupling" can be an indirect electrical connection between two components through an intermediate medium; or, "coupling" can be an electrical connection between two components in a non-contact manner, such as an electrical connection between two components using capacitive coupling to transmit electrical signals.

[0057] In this embodiment of the invention, directional terms such as "up," "down," "left," and "right" may be defined relative to the orientation of the components shown in the accompanying drawings. It should be understood that these directional terms can be relative concepts, used for relative description and clarification, and can change accordingly depending on the orientation of the components in the accompanying drawings.

[0058] Example 1: As Figure 1As shown, an embodiment of the present invention provides a press-fit verification system for gear production, comprising:

[0059] The dynamic stress field capture subsystem is responsible for capturing the dynamic stress field array composed of a piezoelectric nanowire network. The piezoelectric nanowire network is formed by the deposition process of nanopiezoelectric materials, which captures the dynamic stress field during the press-fitting process and outputs the spatiotemporal sequence of the stress field.

[0060] The micro-deformation field reconstruction subsystem is responsible for receiving the spatiotemporal sequence of the stress field and reconstructing the micro-deformation field of the gear through spatiotemporal deconvolution processing. The spatiotemporal deconvolution processing is digitally implemented based on the wave propagation principle and outputs a deformation field distribution map.

[0061] The integrated resonance verification subsystem is responsible for receiving the deformation field distribution map, synthesizing theoretical resonance characteristics through the structural resonance model, performing mode matching between the structural resonance model and the measured resonance characteristics through the discretized structural dynamics method, acquiring the measured resonance characteristics through the acoustic resonance scanner, and outputting the press-fit quality verification value.

[0062] In the above embodiments, the specific principle is as follows: Figure 2 As shown, the dynamic stress field capture subsystem in this embodiment utilizes the high-density sensing characteristics of piezoelectric nanowire networks to continuously monitor the transient stress distribution during the press-fitting process, generating stress field sequence data with high spatiotemporal resolution. The micro-deformation field reconstruction subsystem, based on a spatiotemporal deconvolution algorithm using the wave propagation principle, transforms the stress sequence into a visualized distribution of the micro-deformation field inside the gear, revealing the local deformation behavior of the material during compression. The integrated resonance verification subsystem establishes a quantitative correlation between the deformation field distribution and the press-fitting quality by matching the theoretical characteristics of the structural resonance model with the mode of the acoustic resonance scanning measured data, achieving a non-destructive assessment of assembly consistency and structural integrity.

[0063] In summary, this embodiment, through multi-level processing of stress capture, deformation reconstruction, and resonance verification, forms a closed-loop verification capability from process monitoring to quality judgment, thereby improving the controllability of gear pressing process and product reliability.

[0064] Example 2: Figure 3 As shown, based on Embodiment 1, the dynamic stress field capture subsystem provided in this embodiment of the invention includes:

[0065] The template vibration modulation component is responsible for the formation of the piezoelectric nanowire network. It begins with the preparation of a reconfigurable template, which is composed of a microscale elastic pillar array. The piezoelectric material is deposited in the gaps between the elastic pillar array through gas phase transport. The deposition process is modulated by the template vibration to form an interwoven nanowire network.

[0066] The pressure transmission component is responsible for removing the elastic column array to obtain a self-supporting piezoelectric nanowire network, and transferring the piezoelectric nanowire network to the bearing interface of the pressing mold. The bearing interface serves as the stress transmission medium. During the gear pressing process, the bearing interface receives dynamic pressure, which is transmitted to the nanowire network, causing mechanical deformation of the nanowires. The mechanical deformation excites the piezoelectric effect, generating local charges at the network nodes.

[0067] The charge conversion component is responsible for collecting node charges through an embedded conductive path, which is connected to a miniature charge sensing unit. The charge sensing unit converts the charges into analog voltage signals. Multiple analog voltage signals are input to the space-time encoder, which synchronously records the signals from each channel and encodes them according to the spatial position of the nodes. The time slice data is integrated to output a stress field space-time sequence.

[0068] In the above embodiments, this embodiment realizes a complete sensing chain from macroscopic dynamic pressure to microscopic charge distribution, and then to quantized spatiotemporal sequence; a high spatial resolution stress sensing array is obtained through controlled growth of three-dimensional nanowire network, and with the help of efficient interface pressure transmission and signal conversion encoding mechanism, the final output is high-dimensional spatiotemporal sequence data that can accurately reflect the dynamic evolution of the stress field at the contact interface during the press fitting process.

[0069] Example 3: Based on Example 2, the charge conversion component provided in this embodiment of the invention includes:

[0070] The phase-coordinated network synchronization module is responsible for inputting multiple analog voltage signals into the phase-coordinated network synchronizer. The phase-coordinated network synchronizer uses the capacitive coupling effect in the embedded conductive path to establish a phase reference. The capacitive coupling effect comes from the inherent capacitance between adjacent nodes in the piezoelectric nanowire network and outputs phase-synchronized multi-channel signal data.

[0071] The spatial fingerprint mapping and encoding module is responsible for inputting phase-synchronized multi-channel signal data into the spatial fingerprint mapping encoder. The spatial fingerprint mapping encoder encodes the data according to the node spatial fingerprint database, which is derived from the node geometric features obtained by high-resolution topological imaging before the piezoelectric nanowire network is transferred. The output is a signal data array with spatial fingerprint tags.

[0072] The temporal frame weaving module is responsible for inputting the signal data array with spatial fingerprint tags into the temporal frame weaver. The temporal frame weaver integrates the time slice data through temporal slice interleaving processing. The temporal slice interleaving processing is based on the wave propagation speed model of the dynamic stress field and outputs the spatiotemporal sequence of the stress field.

[0073] In the above embodiments, the charge conversion component of this embodiment achieves a complete conversion from multiple analog voltage signals to a spatiotemporal sequence of stress field through the collaborative work of various modules. The phase coordination network synchronization module utilizes the inherent capacitive coupling effect of the piezoelectric nanowire network to establish a phase reference, eliminating phase deviations between multiple signals and ensuring time consistency in subsequent processing. The spatial fingerprint mapping and encoding module spatially encodes the synchronization signal based on the node geometric feature database, accurately associating the electrical signal with the spatial location of the physical node to form a signal array with traceable spatial information. The temporal framework weaving module, combined with the dynamic stress field fluctuation propagation model, performs temporal slicing and interweaving recombination on the spatially encoded signal, ultimately generating a data sequence that reflects the continuous spatiotemporal evolution characteristics of the stress field. This embodiment realizes phase calibration, spatial positioning, and spatiotemporal reconstruction of multi-node signals of the piezoelectric nanowire network, providing a high-precision, high spatiotemporal resolution underlying data foundation for subsequent stress field analysis and system status monitoring.

[0074] Example 4: Figure 4 As shown, based on Example 1, the microscopic deformation field reconstruction subsystem provided in this embodiment of the invention includes:

[0075] The data fusion component is responsible for first fusing the spatiotemporal sequence of the stress field with the medium topology data, which contains the geometric and material distribution information inside the gear. The distortion of the stress wave propagating in the gear medium is corrected by the dispersion compensation algorithm to generate a medium-corrected stress field.

[0076] In this process, based on the mechanical connections between discrete unit nodes inside the gear defined by the medium topology data, and with the force distribution set on the gear surface as the initial condition, an explicit time-progression method is used to transfer stress and velocity changes based on the mechanical connections between adjacent nodes within each time step, and update the stress state of each node according to the elastic modulus. The calculation is carried out step by step in this way, and finally the stress response of all internal mesh nodes in the entire time history is calculated.

[0077] The model building component, responsible for the stress field of medium correction, is then input into the wave propagation inversion kernel. The wave propagation inversion kernel is built based on the propagation model of elastic waves in solids. It reverse-engineers the distributed force source acting on the gear surface during the press-fitting process through deconvolution operation, and generates an equivalent distributed force source map.

[0078] The force source mapping component is responsible for coupling the equivalent distributed force source map with the nonlinear compliance tensor field. The nonlinear compliance tensor field characterizes the deformation response relationship of the gear material under complex stress state. Through tensor field transformation, the distributed force source is mapped to the microscopic deformation distribution of the gear body, generating a deformation field distribution map.

[0079] In the above embodiments, the micro-deformation field reconstruction subsystem of this embodiment achieves high-precision reconstruction from the spatiotemporal sequence of the stress field to the micro-deformation distribution of the gear body through step-by-step processing of modules. The data fusion component fuses the stress field sequence with the topological data of the internal medium of the gear, and uses a dispersion compensation algorithm to correct the distortion caused by the propagation of stress waves in a non-uniform medium, obtaining stress field data that reflects the influence of the real medium. The model building component, based on the propagation model of elastic waves in solids, inversely deduces the distributed force source acting on the gear surface during the press-fitting process from the corrected stress field through deconvolution operation, forming an equivalent distributed force source map. The force source mapping component couples the distributed force source with a nonlinear compliance tensor field, and maps the force source to the micro-deformation response of the gear material under complex stress state through tensor field transformation, finally generating a deformation field distribution map that can characterize the spatial distribution of micro-deformation inside the gear. This embodiment realizes full-field, quantitative, and high-resolution reconstruction of the internal force and deformation of the gear during the press-fitting process, providing key data support for gear assembly quality assessment and process optimization.

[0080] Example 5: Based on Example 4, the model building component provided in this embodiment of the invention includes:

[0081] The stress response acquisition sub-component is responsible for providing the coordinates and elastic modulus of all discrete elements inside the gear with medium topology data, which is used to define the volume of each discrete element and the mechanical relationship between its nodes. By using the mechanical relationship between nodes and the explicit time-progression method, the stress response of the mesh nodes inside the gear over time can be gradually calculated based on any set force distribution on the gear surface through wave field propagation calculation relationship.

[0082] The difference degree acquisition sub-component is responsible for the stress field of wave field propagation and medium correction, which enters a cyclic adjustment process. First, an initial force distribution on the gear surface is preset, and the corresponding internal stress field is calculated through wave field propagation. The calculated stress field is compared with the stress field of medium correction point by point to obtain the overall difference degree. At the same time, the spatial concentration of the current preset surface force distribution is evaluated. Combining the two indicators, the amplitude and position of the preset surface force distribution are automatically adjusted until a preliminary force source distribution map that makes the internal stress field match the highest and the surface force distribution the most concentrated is found.

[0083] The rule correction sub-component is responsible for the physical rule correction stage of the initial force source distribution map. Based on the physical rule that the pressing force cannot be the tensile force, it corrects all negative values ​​representing tensile force in the initial force source distribution map to zero. It then performs spatial homogenization on the corrected force distribution. The degree of homogenization is dynamically controlled by the intensity of force distribution changes in local areas. Stronger homogenization is performed in areas with gentle force changes, while weaker homogenization is performed in areas with intense force changes, making the force distribution map continuous and natural in space. The result after amplitude correction and spatial homogenization is the equivalent distribution force source map.

[0084] In the above embodiments, the model building component of this embodiment achieves reverse reconstruction from the medium-corrected stress field to the equivalent distributed force source map through a phased process. The stress response acquisition subcomponent establishes a forward physical model from the surface force distribution of the gear to the internal stress response based on the discrete unit mechanical properties defined by the gear medium topology data, combined with the explicit time-progression method and wave field propagation calculation relationship. The difference degree acquisition subcomponent compares the stress field calculated by the forward model with the medium-corrected stress field point by point through an iterative adjustment process, while evaluating the concentration of the surface force distribution, automatically optimizing the amplitude and spatial position of the surface force distribution, and obtaining the preliminary force source distribution with the highest matching degree with the observed stress field. The rule correction subcomponent performs amplitude correction and spatial homogenization processing on the preliminary force source distribution based on the physical constraint that only pressure exists in the pressing process, eliminating tensile force components that do not conform to physical rules, and making the force distribution map spatially continuous and natural through dynamically controlled homogenization operations, finally generating an equivalent distributed force source map that conforms to the actual physical process and is spatially continuous. This embodiment achieves high-precision, physically consistent inverse solving from observed stress field to surface force distribution under complex medium conditions, providing a reliable force source input for deformation field reconstruction.

[0085] Example 6: Based on Example 4, the force source mapping component provided in this embodiment of the invention includes:

[0086] Combined with the operation sub-component, the force vectors at each point on the gear surface, which are responsible for describing the equivalent distributed force source map, are transmitted to the interior of the gear material and combined with the pre-established nonlinear compliance tensor field. The nonlinear compliance tensor field defines the deformation capability of the material under different stress levels. The force vectors and the corresponding compliance tensors are combined through a combination operation, following the stress-strain law of the material under complex stress, to generate a set of strain tensors describing the local deformation of the material.

[0087] The strain connection sub-component is responsible for transmitting and balancing the local strain tensor according to the physical constraint of maintaining continuity of the deformable body; all local strains are connected into a compatible whole, generating a full-field strain distribution covering the entire volume of the gear.

[0088] The state accumulation sub-component is responsible for accumulating and integrating the strain state at each point in the overall strain distribution to obtain the displacement vector of each mass point in space within the gear body; the set of displacement vectors of all mass points constitutes the deformation field distribution map.

[0089] In the above embodiments, the force source mapping component achieves a physical mapping from an equivalent distributed force source to the gear's micro-deformation field through multi-step calculations. The operation sub-component combines the surface force vector with the nonlinear compliance tensor field, and based on the constitutive relationship of the material under complex stress, converts the force distribution into a strain tensor reflecting local deformation characteristics. The strain connection sub-component, based on the continuity constraint of the deformable body, coordinates and integrates the local strain tensor to form a full-field strain distribution that satisfies geometric compatibility conditions throughout the gear's entire space. The state accumulation sub-component transforms the strain state into displacement vectors of each mass point by spatially integrating and accumulating the full-field strain distribution, ultimately constructing a deformation field distribution map that fully describes the spatial distribution of micro-deformation inside the gear. This embodiment achieves a physically accurate conversion from force source to deformation field, establishes a quantitative mapping relationship between surface force and internal micro-deformation, and provides high-fidelity full-field deformation data for deformation analysis and quality control during gear assembly.

[0090] Example 7: As Figure 5 As shown, based on Embodiment 1, the integrated resonant verification subsystem provided in this embodiment of the invention includes:

[0091] The digital adaptation component is responsible for digitally adapting the gear press-fitting system based on the principles of structural dynamics. It discretizes the gear structure into multiple micro-units, and the mechanical parameters of each micro-unit are determined by the deformation information at the corresponding position in the deformation field distribution diagram. By solving the discretized structural dynamics equations, it simulates the dynamic behavior of the gear under resonance conditions and synthesizes theoretical resonance characteristics from the structural resonance model. The theoretical resonance characteristics are presented in the form of a digital sequence, including the resonant frequency of the gear under ideal press-fitting conditions and its corresponding vibration mode.

[0092] The measured resonance feature acquisition component is responsible for scanning the press-fitted gear with an acoustic resonance scanner and capturing the resonance features. It excites the gear by emitting sound waves in a specific frequency range and monitors the gear's resonance response in real time. The measured resonance features are extracted from the resonance response and presented in the form of a digital sequence, including the gear's resonance frequency and vibration mode under actual press-fitting conditions.

[0093] The pattern matching and verification component is responsible for performing pattern matching between the theoretical resonance characteristics output from the theoretical resonance characteristic synthesis process and the measured resonance characteristics output from the measured resonance characteristic acquisition process. The pattern matching is based on the wave propagation principle of resonance characteristics to achieve digital comparison, and the similarity or difference between the two in resonant frequency and vibration mode is analyzed by algorithm. Based on the results of pattern matching, a pressing quality verification value is generated. The verification value is a quantitative index that reflects the degree of consistency between the theoretical resonance characteristics and the measured resonance characteristics, and evaluates the quality of gear pressing.

[0094] In the above embodiments, the integrated resonance verification subsystem achieves quantitative assessment of gear press-fit quality by comparing theoretical modeling with measured data. The digital adaptation component, based on structural dynamics principles and the mechanical parameters of micro-units determined by the deformation field distribution diagram, constructs a discretized structural dynamics model of the gear, simulates the resonance response under ideal press-fit conditions, and generates a theoretical resonance characteristic sequence. The measured resonance characteristic acquisition component applies acoustic excitation to the actual gear using an acoustic resonance scanner and monitors the resonance response, extracting a measured resonance characteristic sequence reflecting the actual press-fit state. The mode matching and verification component, based on wave propagation principles, digitally compares the theoretical and measured characteristics, analyzes the similarity or difference between the resonance frequency and vibration mode, and generates a press-fit quality verification value that quantitatively characterizes the consistency between the two. This embodiment establishes a correlation verification path from microscopic deformation to macroscopic resonance response, achieving non-contact, high-precision quantitative assessment of gear press-fit quality through closed-loop verification of theoretical simulation and experimental measurement, providing a reliable basis for process compliance judgment.

[0095] Example 8: Based on Example 7, the pattern matching and verification component provided in this embodiment of the invention includes:

[0096] The wave propagation path alignment sub-component is responsible for inputting the digitized sequences of theoretical and measured resonance characteristics. Based on the digital application of wave propagation principles, it generates a wave propagation path topology mesh for the gear structure. The wave propagation path topology mesh defines the transmission links of wave energy in the discretized gear structure. Using the wave propagation path topology mesh, each vibration mode in the theoretical sequence and the vibration mode in the measured sequence are aligned by structural space mapping according to the excitation node position and propagation attenuation profile in the wave propagation path topology mesh, forming a set of aligned theoretical-measured vibration mode feature pairs. At the same time, the resonant frequency is assigned to the topology mesh nodes.

[0097] The covariance quantization sub-component is responsible for receiving the aligned feature pairs output from the wave propagation path alignment process; for each aligned feature pair, it calculates in parallel the morphological variation between each pair of theoretical vibration modes and measured vibration modes, as well as the frequency shift between each pair of theoretical resonant frequencies and measured resonant frequencies at their respective nodes; and integrates the variation and frequency shift of all feature pairs to generate a multidimensional covariance distribution spectrum.

[0098] The integrated verification value generation sub-component is responsible for receiving the covariance distribution spectrum output from the covariance quantization process, fusing the multi-dimensional difference information in the covariance distribution spectrum; determining the contribution of each path in the wave propagation path topology grid to the overall resonance behavior through pre-analysis of wave energy flow; and combining the fused covariance distribution spectrum with the contribution to output the press-fit quality verification value.

[0099] In the above embodiments, the pattern matching and verification component of this embodiment achieves accurate verification of press-fit quality through multi-level feature alignment and quantization analysis. The wave propagation path alignment sub-component generates a wave propagation path topology mesh for the gear structure based on the wave propagation principle. Using this mesh, theoretical vibration modes and measured vibration modes are spatially mapped and aligned according to the excitation node position and propagation attenuation profile, forming aligned theoretical-measured feature pairs. Simultaneously, the resonant frequency is aligned to its corresponding topology node. The co-variance quantization sub-component calculates the vibration mode morphology variation and resonant frequency node frequency shift in parallel for each aligned feature pair, integrating them to generate a co-variance distribution spectrum reflecting multi-dimensional differences. The comprehensive verification value generation sub-component fuses the multi-dimensional difference information of the co-variance distribution spectrum, combining the contribution weights of each path in the wave propagation path topology mesh to the overall resonance behavior, ultimately generating a press-fit quality verification value. This embodiment, through wave propagation path-driven structural spatial alignment and multi-dimensional variation quantization, achieves a refined comparison of theoretical and measured resonance characteristics at the physical essence level, overcoming the problem of insensitivity to local structural differences in traditional direct comparison of frequency response functions, and significantly improving the accuracy and reliability of press-fit quality assessment.

[0100] Example 9: Based on Example 8, the comprehensive verification value generation sub-component provided in this embodiment of the invention includes:

[0101] The contribution topology tensor construction module is responsible for receiving the multidimensional covariance distribution spectrum output by the covariance quantization sub-component; calling the pre-generated wave energy flow analysis results, defining the contribution weight of each path in the wave propagation path topology grid to the overall resonance behavior; and constructing a contribution topology tensor based on the contribution weight to encapsulate the coupling contribution relationship between paths. Its dimension matches the dimension of the covariance distribution spectrum, and the value of each element is determined by the contribution weight of the corresponding topology path and the weight of the path connected to it.

[0102] The spectral tensor shrinking module is responsible for combining the covariance distribution spectrum with the contribution topology tensor output from the contribution topology tensor construction process. Performing the spectral tensor shrinking operation is an operation in tensor algebra, which is applied to fuse the multidimensional difference information in the distribution spectrum along the association structure defined by the contribution topology tensor. Through the shrinking operation, the covariance distribution spectrum is mapped into a dimension-reduced fused difference tensor.

[0103] The resonant offset scalar generation module is responsible for receiving the fused difference tensor output from the spectral tensor shrinking process, inputting it into the resonant offset program, processing the fused difference tensor, and outputting the pressing quality verification value.

[0104] In the above embodiments, the comprehensive verification value generation sub-component of this embodiment achieves the fusion of multidimensional difference information and physical contribution weights through tensor operations. The contribution topology tensor construction module constructs a contribution topology tensor that matches the dimension of the covariance distribution spectrum based on the contribution weight of the wave propagation path, encapsulating the coupling contribution relationship between paths. The spectrum tensor shrinking module fuses the covariance distribution spectrum along the association structure defined by the contribution topology tensor through tensor shrinking operations, generating a dimension-reduced fused difference tensor. The resonance offset scalar generation module performs final processing on the fused difference tensor and outputs the press-fit quality verification value. This embodiment structurally fuses the physical contribution weight of the wave propagation path with multidimensional covariance information, overcoming the limitation of the traditional weighted average method in failing to adequately characterize the path coupling relationship. It achieves high-fidelity compression and synthesis of difference information within a physical association framework, and the final generated verification value more accurately reflects the consistency between theoretical resonance characteristics and measured resonance characteristics at the essential level of wave propagation, improving the physical interpretability and discrimination sensitivity of press-fit quality assessment.

[0105] Example 10: Based on Example 9, the resonant offset scalar generation module provided in this embodiment of the invention includes:

[0106] The intrinsic perturbation manifold construction submodule is responsible for receiving the fused difference tensor output by the spectral tensor shrinking module and constructing an intrinsic perturbation manifold based on the eigenmode space of the structural resonance model. The intrinsic perturbation manifold is defined as a continuous unified body of the resonance state changes caused by all possible structural perturbations. The geometric properties of the intrinsic perturbation manifold are jointly determined by the eigenvectors of the structural resonance model in its basis space and the metric tensor. The components of the metric tensor are initialized by the elements in the fused difference tensor.

[0107] The State Trajectory Mapping submodule is responsible for defining the multidimensional differences represented by the fused difference tensor based on the geometric structure of the intrinsic perturbation manifold, and mapping them to a state evolution trajectory on the intrinsic perturbation manifold. The starting point of the state evolution trajectory is determined by the ideal state point corresponding to the theoretical resonance feature, and the path and length of the trajectory are jointly determined by the magnitude and sign of the differences in each dimension in the fused difference tensor.

[0108] The global curvature integral submodule is responsible for integrating the intrinsic geometric curvature of the intrinsic perturbation manifold along the curve of the state evolution trajectory, and outputting a resonance offset scalar as a press-fit quality verification value; it quantifies the degree of overall geometric deviation of the actual gear's resonance state from the ideal state on the intrinsic perturbation manifold.

[0109] In the above embodiments, this embodiment achieves the quantitative conversion of the deviation from the structural resonance model to the actual resonance state through the construction and geometric analysis of the intrinsic perturbation manifold; based on the intrinsic perturbation manifold constructed by fusing the difference tensor, the multidimensional difference is mapped to the evolution trajectory in the continuous state space; by integrating the manifold curvature along the trajectory, the geometric deviation is converted into a scalar output. A mathematical correlation is established between the structural resonance characteristics and the pressing quality, so that the minute perturbations of the resonance state can be captured and quantified by the manifold geometric properties, thereby achieving indirect high-precision verification of the gear pressing quality.

[0110] Example 11: Based on Example 10, the global curvature integral submodule provided in this embodiment of the invention includes:

[0111] The normal bundle curvature density field construction unit is responsible for receiving the state evolution trajectory defined by the state trajectory mapping submodule; based on the metric tensor of the intrinsic perturbation manifold and the tangent vector direction at each point on the trajectory, it constructs a normal bundle curvature density field; the normal bundle curvature density field is defined as the distribution field describing the intensity of the change in the normal direction of the manifold at each neighboring point of the state evolution trajectory; the specific form of the normal bundle curvature density field is determined by the Riemann curvature tensor induced by the metric tensor and the trajectory tangent vector field through tensor contraction operation;

[0112] The trajectory curvature density shrinking unit is responsible for performing integral preprocessing on the normal bundle curvature density field output from the normal bundle curvature density field construction process along the state evolution trajectory. It projects and compresses the high-dimensional object of the normal bundle curvature density field onto the one-dimensional path of the state evolution trajectory, thus obtaining the trajectory curvature density function with a curve distribution along the state evolution trajectory.

[0113] The expression for the trajectory curvature density function can be:

[0114]

[0115] In the formula, The trajectory curvature density function represents the trajectory along the state evolution path in terms of parameters. The curvature density value at that point is a scalar function; The arc length parameter represents the trajectory of state evolution, and its value ranges from 1 to 2. , used to mark positions on the trajectory; The Riemann curvature tensor of the intrinsic perturbation manifold is given by the metric tensor. Calculated using the Levi-Civita connection, describing the intrinsic curvature of the manifold. (Subscript) Represents the tensor components in the local coordinate system of the manifold; The state evolution trajectory represents the parameters The tangent vector components at point 0 satisfy the normalization condition. Indicates the instantaneous direction of motion of the trajectory. and These are different component indices of the same tangent vector, representing the merging of different representations of the same vector component under the Einstein summation convention; Indicates the trajectory in parameters The normal vector components at point satisfy the orthogonality condition. , representing the manifold normal direction perpendicular to the trajectory. This expression obtains the scalar curvature density distributed along the trajectory by performing a double contraction operation on the Riemann curvature tensor with the tangent and normal vectors. Its geometric meaning is: at each point of the trajectory At this point, the intensity of the change in the trajectory direction under the influence of manifold curvature is measured, reflecting the degree of local deviation of the trajectory in the curved space; this density function provides curvature weights that are continuously distributed along the trajectory for subsequent gauge invariant integrals.

[0116] The gauge-invariant integrator unit is responsible for receiving the trajectory curvature density function output from the trajectory curvature density contraction process and performing gauge-invariant integration operations. It obtains scalar results in the curved space by means of the integrator kernel, which is independent of the coordinate selection. The construction of the integrator kernel depends on the global topological invariants of the eigen-perturbation manifold. It outputs a resonant offset scalar.

[0117] In the above embodiments, this embodiment achieves geometric invariance quantification of the resonant offset scalar by constructing a normal bundle curvature density field and using gauge-invariant integrals. Based on the tangent vector field of the state evolution trajectory and the normal bundle curvature density field constructed using manifold metrics, the local bending intensity distribution along the manifold normal direction is geometrically correlated with the trajectory. Through integral contraction along the trajectory, the high-dimensional curvature field is compressed into a one-dimensional density function, preserving the curvature accumulation characteristics along the trajectory path. Finally, through gauge-invariant integral kernel processing, it is ensured that the output resonant offset scalar is unaffected by local coordinate selection and depends only on the intrinsic geometry and topological properties of the manifold. This enables the press-fit quality verification value to possess mathematical coordinate independence and geometric stability, thereby improving the reliability and repeatability of measuring the degree of gear resonant state deviation.

[0118] Example 12: Based on Example 11, the canonical invariant integral unit provided in this embodiment of the invention includes:

[0119] The characteristic form extraction sub-unit is responsible for receiving the global differential structure of the manifold defined by the intrinsic perturbation manifold construction process, extracting the differential form representing its global topological properties from the curvature form of the intrinsic perturbation manifold, and outputting one or more closed topological characteristic forms, the specific form of which is determined by the representation of topological invariants such as Chern classes or Pontryagin classes of the manifold at the differential form level.

[0120] The canonical adaptation kernel function generation sub-unit is responsible for receiving the topological characteristic form output from the characteristic form extraction process; simultaneously, it receives the domain and characteristics of the trajectory curvature density function output from the trajectory curvature density contraction process; based on the topological characteristic form and combined with the local coordinate neighborhood structure of the manifold where the state evolution trajectory is located, a canonical adaptation kernel function is constructed; the role of the canonical adaptation kernel function is to serve as the weight kernel for the integration operation, and its core construction is to ensure that the transformation law of the canonical adaptation kernel function under manifold coordinate transformation can cancel out the non-tensor transformation that the trajectory curvature density function may undergo, so that the final integration result is independent of the selected local coordinates for calculation; the specific functional form of the canonical adaptation kernel function is generated by the constraints of the topological characteristic form and the manifold metric structure.

[0121] The invariant integral kernel synthesis subunit is responsible for synthesizing the standard-fit kernel function output from the standard-fit kernel function generation process with the parameterized representation of the state evolution trajectory itself, and performing the invariant integral kernel synthesis operation; it combines the standard-fit kernel function with the arc length infinitesimal of the trajectory induced by the metric tensor on the state evolution trajectory to form an integral infinitesimal form that is standard-invariant in line integrals, which is the final required integral kernel.

[0122] In the above embodiments, this embodiment achieves strict gauge invariance of the resonance offset scalar at the differential geometry level by synthesizing the topological characteristic form and the gauge-fitted integral kernel. The closed characteristic form extracted from the overall topological invariants of the manifold provides a geometric constraint basis for the integral kernel that is independent of local coordinates. By constructing a gauge kernel function adapted to the transformation law of the trajectory curvature density function, the non-tensor effect caused by coordinate transformation is offset. The finally synthesized invariant integral kernel integrates topological constraints, metric structures, and trajectory parameterization, forming an integral infinitesimal element that remains invariant under any local coordinate selection. This embodiment ensures that the final output resonance offset scalar is completely determined by the intrinsic geometry and topological properties of the manifold, giving the press-fit quality verification value strict mathematical invariance and physical consistency, thus stably characterizing the overall deviation of the resonance state even under complex structural disturbances.

[0123] Example 13: As Figure 6 As shown, based on Examples 1-12, the gear manufacturing press-fit verification method provided by this invention specifically includes the following steps:

[0124] Step S100: A dynamic stress field trapping array is constructed from a piezoelectric nanowire network. The piezoelectric nanowire network is formed by a nanopiezoelectric material deposition process to trap the dynamic stress field during the pressing process and output the spatiotemporal sequence of the stress field.

[0125] Step S200: Receive the spatiotemporal sequence of the stress field, reconstruct the micro-deformation field of the gear through spatiotemporal deconvolution processing. The spatiotemporal deconvolution processing is digitally implemented based on the wave propagation principle, and outputs the deformation field distribution map.

[0126] Step S300: Receive the deformation field distribution map, synthesize theoretical resonance characteristics through the structural resonance model, perform mode matching between the structural resonance model and the measured resonance characteristics through the discretized structural dynamics method, acquire the measured resonance characteristics through the acoustic resonance scanner, and output the press-fit quality verification value.

[0127] In the above embodiments, this embodiment achieves high-precision cross-scale verification of gear press-fit quality through dynamic stress field capture, microscopic deformation field reconstruction, and resonance feature synthesis and matching. A dynamic stress field capture array based on a piezoelectric nanowire network acquires the spatiotemporal distribution of stress during the press-fit process in real time at nanometer-level resolution. The stress field sequence is reconstructed into a gear microscopic deformation field through spatiotemporal deconvolution processing, establishing a mapping relationship between the macroscopic press-fit process and microscopic structural deformation. Mode matching is performed by combining the theoretical resonance characteristics of the structural resonance model with the measured characteristics of acoustic resonance scanning to convert the deformation field distribution into press-fit quality verification values. This embodiment forms a complete closed loop from nanoscale stress perception to macroscopic resonance characteristic verification, enabling the assessment of press-fit quality to possess both high spatiotemporal resolution and physical consistency, and sensitively detects macroscopic resonance characteristic shifts caused by the accumulation of microscopic deformation.

[0128] Figure 7 A block diagram of an exemplary electronic device suitable for implementing embodiments of the present invention is shown.

[0129] Electronic devices may include a central processing unit / microprocessor / main control chip; and a storage medium coupled to the central processing unit / microprocessor / main control chip, wherein computer-executable instructions are stored for performing the steps of various methods of embodiments of the present invention when executed by a processor.

[0130] The central processing unit / microprocessor / main control chip may include, but is not limited to, one or more processors or microprocessors.

[0131] Storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (such as hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).

[0132] In addition, the electronic device may include (but is not limited to) a data bus, an input / output bus / external bus / device bus, a display, and input / output devices (e.g., keyboard, mouse, speaker, etc.).

[0133] The central processing unit / microprocessor / main control chip can communicate with external devices via wired or wireless networks through input / output buses / external buses / device buses.

[0134] The storage medium may also store at least one computer-executable instruction for performing the steps of various functions and / or methods in the embodiments described herein when the central processing unit / microprocessor / main control chip is running.

[0135] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0136] Figure 8 A schematic diagram of a computer-readable storage medium according to an embodiment of the present invention is shown.

[0137] like Figure 8 As shown, instructions, such as computer-readable instructions, are stored on a non-transitory computer-readable storage medium. When the computer-readable instructions are executed by a processor, the various methods described above can be performed. The non-transitory computer-readable storage medium includes, but is not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-transitory non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, the non-transitory computer-readable storage medium can be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the non-transitory computer-readable storage medium, the various methods described above can be performed.

[0138] In the embodiments provided by this invention, it should be understood that the disclosed systems and methods can be implemented in other ways. For example, the system embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between systems or units may be electrical, mechanical, or other forms.

[0139] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0140] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0141] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for executing all or part of the steps of the methods of the various embodiments of this invention through a computer device (which may be a personal computer, server, or network device, etc.). The aforementioned storage medium includes: USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, optical disks, and other media capable of storing program code.

[0142] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A press-fitting and calibration system for gear manufacturing, characterized in that, Include: The micro-deformation field reconstruction subsystem is responsible for receiving the spatiotemporal sequence of the stress field and reconstructing the micro-deformation field of the gear through spatiotemporal deconvolution processing. The spatiotemporal deconvolution processing is digitally implemented based on the wave propagation principle and outputs a deformation field distribution map. The integrated resonance verification subsystem is responsible for receiving the deformation field distribution map, synthesizing theoretical resonance characteristics through the structural resonance model, performing mode matching between the structural resonance model and the measured resonance characteristics through the discretized structural dynamics method, acquiring the measured resonance characteristics through the acoustic resonance scanner, and outputting the press-fit quality verification value. The micro-deformation field reconstruction subsystem includes: The data fusion component is responsible for first fusing the spatiotemporal sequence of the stress field with the medium topology data, which contains the geometric and material distribution information inside the gear. The distortion of the stress wave propagating in the gear medium is corrected by the dispersion compensation algorithm to generate a medium-corrected stress field. The model building component, responsible for the stress field of medium correction, is then input into the wave propagation inversion kernel. The wave propagation inversion kernel is built based on the propagation model of elastic waves in solids. It reverse-engineers the distributed force source acting on the gear surface during the press-fitting process through deconvolution operation, and generates an equivalent distributed force source map. The force source mapping component is responsible for coupling the equivalent distributed force source map with the nonlinear compliance tensor field. The nonlinear compliance tensor field characterizes the deformation response relationship of the gear material under complex stress state. Through tensor field transformation, the distributed force source is mapped to the microscopic deformation distribution of the gear body, generating a deformation field distribution map. The integrated resonant verification subsystem includes: The digital adaptation component is responsible for digitally adapting the gear press-fitting system based on the principle of structural dynamics. It discretizes the gear structure into multiple micro-units, and the mechanical parameters of each micro-unit are determined by the deformation information at the corresponding position in the deformation field distribution diagram. By solving the discretized structural dynamics equations, the dynamic behavior of the gear under resonance conditions is simulated, and the theoretical resonance characteristics are synthesized from the structural resonance model. The theoretical resonance characteristics are presented in the form of a digital sequence; The measured resonance feature acquisition component is responsible for scanning the press-fitted gear with an acoustic resonance scanner and capturing the resonance features. It excites the gear by emitting sound waves within a frequency range and monitors the gear's resonance response in real time. The measured resonance features are extracted from the resonance response and presented in the form of a digital sequence, including the gear's resonance frequency and vibration mode under actual press-fitting conditions. The pattern matching and verification component is responsible for performing pattern matching between the theoretical resonance features output from the theoretical resonance feature synthesis process and the measured resonance features output from the measured resonance feature acquisition process. The pattern matching is based on the wave propagation principle of resonance features to achieve digital comparison, and the similarity or difference between the two in resonant frequency and vibration mode is analyzed by algorithm. Based on the results of pattern matching, the pressing quality verification value is generated.

2. The gear manufacturing press-fitting and calibration system as described in claim 1, characterized in that, Pattern matching and validation components, including: The wave propagation path alignment sub-component is responsible for inputting the digitized sequences of theoretical and measured resonance characteristics, and generating a wave propagation path topology mesh for the gear structure based on the digital application of wave propagation principles. Using the wave propagation path topology mesh, each vibration mode in the theoretical sequence and the vibration mode in the measured sequence are aligned by structural spatial mapping according to the excitation node position and propagation attenuation profile in the wave propagation path topology mesh, forming a set of aligned theoretical-measured vibration mode feature pairs, and simultaneously completing the alignment of the resonant frequency on the topology mesh nodes. The collaborative variational quantization sub-component is responsible for receiving the aligned feature pairs output from the fluctuation propagation path alignment process; For each pair of aligned feature pairs, the morphological variation between each pair of theoretical and measured vibration modes, as well as the frequency shift between each pair of theoretical and measured resonant frequencies at their respective nodes, are calculated in parallel. The variation and frequency shift of all feature pairs are integrated to generate a multidimensional cooperative variation distribution spectrum. The integrated verification value generation sub-component is responsible for receiving the covariance distribution spectrum output from the covariance quantization process, fusing the multi-dimensional difference information in the covariance distribution spectrum; determining the contribution of each path in the wave propagation path topology grid to the overall resonance behavior through pre-analysis of wave energy flow; and combining the fused covariance distribution spectrum with the contribution to output the press-fit quality verification value.

3. The gear manufacturing press-fitting and calibration system as described in claim 2, characterized in that, The comprehensive validation value generation sub-component includes: The contributing topology tensor construction module is responsible for receiving the multidimensional covariance distribution spectrum output by the covariance quantization sub-component; calling the pre-generated wave energy flow analysis results, and defining the contribution weight of each path in the wave propagation path topology grid to the overall resonance behavior; Based on the contribution weight, a contribution topology tensor is constructed to encapsulate the coupling contribution relationship between paths. Its dimension matches the dimension of the covariance distribution spectrum, and the value of each element is determined by the contribution weight of the corresponding topology path and the weight of the path connected to it. The spectral tensor shrinking module is responsible for combining the covariance distribution spectrum with the contribution topology tensor output from the contribution topology tensor construction process. Performing the spectral tensor shrinking operation is an operation in tensor algebra, which is applied to fuse the multidimensional difference information in the distribution spectrum along the association structure defined by the contribution topology tensor. Through the shrinking operation, the covariance distribution spectrum is mapped into a dimension-reduced fused difference tensor. The resonant offset scalar generation module is responsible for receiving the fused difference tensor output from the spectral tensor shrinking process, inputting it into the resonant offset program, processing the fused difference tensor, and outputting the pressing quality verification value.

4. The gear manufacturing press-fitting and verification system as described in claim 3, characterized in that, The resonant offset scalar generation module includes: The intrinsic perturbation manifold construction submodule is responsible for receiving the fused difference tensor output by the spectral tensor shrinking module and constructing an intrinsic perturbation manifold based on the eigenmode space of the structural resonance model. The intrinsic perturbation manifold is defined as a continuous unified body of the resonance state changes caused by all possible structural perturbations. The geometric properties of the intrinsic perturbation manifold are jointly determined by the eigenvectors of the structural resonance model in its basis space and the metric tensor. The components of the metric tensor are initialized by the elements in the fused difference tensor. The State Trajectory Mapping submodule is responsible for defining the multidimensional differences represented by the fusion difference tensor as a state evolution trajectory on the intrinsic perturbation manifold based on the geometric structure of the intrinsic perturbation manifold. The global curvature integral submodule is responsible for integrating the intrinsic geometric curvature of the intrinsic perturbation manifold along the curve of the state evolution trajectory, and outputting a resonant offset scalar as a pressing quality verification value.

5. The gear manufacturing press-fitting and verification system as described in claim 4, characterized in that, The global curvature integral submodule includes: The normal bundle curvature density field construction unit is responsible for receiving the state evolution trajectory defined by the state trajectory mapping submodule; and constructing a normal bundle curvature density field based on the metric tensor of the intrinsic perturbation manifold and the tangent vector direction at each point on the trajectory. The trajectory curvature density shrinking unit is responsible for performing integral preprocessing on the normal bundle curvature density field output from the normal bundle curvature density field construction process along the state evolution trajectory. It projects and compresses the high-dimensional object of the normal bundle curvature density field onto the one-dimensional path of the state evolution trajectory, thus obtaining the trajectory curvature density function with a curve distribution along the state evolution trajectory. The gauge-invariant integrator unit is responsible for receiving the trajectory curvature density function output from the trajectory curvature density contraction process and performing gauge-invariant integration operations. It obtains scalar results in the curved space by means of the integrator kernel, which is independent of the coordinate selection. The construction of the integrator kernel depends on the global topological invariants of the eigen-perturbation manifold. It outputs a resonant offset scalar.

6. The gear manufacturing press-fitting and calibration system as described in claim 5, characterized in that, The canonical invariant integral unit includes: The indicative form extraction sub-unit is responsible for receiving the global differential structure of the manifold defined by the intrinsic perturbation manifold construction process, and extracting the differential form representing its global topological properties from the curvature form of the intrinsic perturbation manifold. Output one or more closed topological characteristic forms; The canonical adaptation kernel function generation sub-unit is responsible for receiving the topological characteristic form output from the characteristic form extraction process; at the same time, it receives the domain and characteristics of the trajectory curvature density function output from the trajectory curvature density contraction process; based on the topological characteristic form and combined with the local coordinate neighborhood structure of the manifold where the state evolution trajectory is located, a canonical adaptation kernel function is constructed. The invariant integral kernel synthesis subunit is responsible for synthesizing the standard-fit kernel function output from the standard-fit kernel function generation process with the parameterized representation of the state evolution trajectory itself, and performing the invariant integral kernel synthesis operation; it combines the standard-fit kernel function with the arc length infinitesimal of the trajectory induced by the metric tensor on the state evolution trajectory to form an integral infinitesimal form that is standard-invariant in line integrals.

7. The gear manufacturing press-fitting and calibration system as described in claim 1, characterized in that, It also includes a dynamic stress field capture subsystem, which is responsible for capturing the dynamic stress field array composed of a piezoelectric nanowire network. The piezoelectric nanowire network is formed by a nanopiezoelectric material deposition process, which captures the dynamic stress field during the pressing process and outputs the spatiotemporal sequence of the stress field.

8. A method for press-fit verification in gear production, used to implement the press-fit verification system for gear production as described in any one of claims 1 to 7, characterized in that, The gear manufacturing press-fit verification method includes the following steps: A dynamic stress field trapping array is constructed from a piezoelectric nanowire network. The piezoelectric nanowire network is formed through a nanopiezoelectric material deposition process to trap the dynamic stress field during the pressing process and output the spatiotemporal sequence of the stress field. The system receives the spatiotemporal sequence of the stress field and reconstructs the microscopic deformation field of the gear through spatiotemporal deconvolution processing. The spatiotemporal deconvolution processing is digitally implemented based on the wave propagation principle and outputs a deformation field distribution map. The system receives the deformation field distribution map, synthesizes theoretical resonance characteristics through a structural resonance model, performs mode matching between the structural resonance model and the measured resonance characteristics using a discretized structural dynamics method, acquires the measured resonance characteristics through an acoustic resonance scanner, and outputs the press-fit quality verification value.

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