Automotive Fastener Optimization Design Methods and Systems

Abstract

This invention discloses an optimized design method and system for automotive fasteners, relating to the field of fastener design technology. The method includes the following steps: acquiring real-time magnetic flux density distribution signals of the fastener during stressed operation; extracting magnetic field direction gradient information using a high-sensitivity vector magnetic sensing array to form a stress magnetization dynamic evolution curve; and establishing a continuous temporal baseline for residual magnetic field identification based on this curve. According to the established continuous temporal baseline, extracting abrupt changes in the magnetic domain rotation rate in the stress magnetization dynamic evolution curve, constructing a residual magnetic field accumulation characteristic function, and separating the steady-state magnetic domain signal from the transient stress response. This invention achieves precise correspondence between magnetic signals and stress states by constructing a stress magnetization dynamic evolution curve and a temporal baseline, separating residual magnetic interference and maintaining stable magnetic response. Through multi-dimensional magnetic flux reconstruction and dynamic compensation, the magnetic signal responds only to actual loosening, significantly improving the accuracy and operational reliability of fastener detection.

Description

Technical Field

[0001] This invention relates to the field of fastener design technology, and more specifically to a method and system for optimizing the design of automotive fasteners. Background Technology

[0002] Optimizing the design of automotive fasteners involves systematically analyzing and improving key parameters such as the fastener's geometry, material selection, connection method, stress path, and assembly process, while meeting requirements for structural strength, safety, reliability, and manufacturing cost. Through finite element analysis, fatigue life assessment, and dynamic load simulation, stress concentration areas and potential failure points of components such as bolts, nuts, and washers under different operating conditions are identified. Combined with lightweight design, the application of corrosion-resistant materials, and optimization of assembly precision, risks such as loosening, breakage, and overload are reduced, improving connection stability and service life, thereby achieving comprehensive optimization of vehicle performance, energy consumption, and production costs.

[0003] The existing technology has the following shortcomings:

[0004] During fastener design, when using magnetic detection technology for online monitoring, fasteners under long-term stress will experience irreversible stress magnetization due to the magnetostriction effect of the metallic material, forming localized residual magnetic fields. This residual magnetic signal can easily overlap with actual structural anomaly signals during detection, causing abnormal fluctuations in magnetic flux density distribution and misleading the monitoring algorithm into incorrectly judging the fastening status. When the algorithm misinterprets this false signal caused by stress magnetization as a sign of loose connection or failure, the system may erroneously trigger the stress release protection or abnormal response mechanism. This can lead to the fastener being incorrectly released from its stress constraint under normal operating conditions, resulting in structural instability or even connection detachment, seriously affecting the overall vehicle's operational safety and monitoring reliability.

[0005] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide an optimized design method and system for automotive fasteners to solve the problems mentioned in the background art.

[0007] To achieve the above objectives, the present invention provides the following technical solution: an automotive fastener optimization design method, comprising the following steps:

[0008] Step 1: Obtain the real-time magnetic flux density distribution signal of the fastener during the operation under stress, extract the magnetic field direction gradient information using a high-sensitivity vector magnetic sensing array, form a stress magnetization dynamic evolution curve, and establish a continuous time-series baseline for residual magnetic field identification based on the curve.

[0009] Step 2: Based on the established continuous time-series baseline, extract the abrupt change segment of magnetic domain rotation rate in the stress magnetization dynamic evolution curve, construct the residual magnetic field accumulation characteristic function, separate the steady-state magnetic domain signal from the transient stress response, and generate a magnetic signal weighting model.

[0010] Step 3: Based on the magnetic signal weighting model, a multi-dimensional magnetic flux vector projection algorithm is used to reconstruct the magnetic domain residual distribution map in the spatial domain, and weight correction is performed on the local hysteresis magnetic field signal to obtain the true magnetic flux input matrix.

[0011] Step 4: Using the real magnetic flux input matrix, a dynamic magnetic flux density compensation layer is established based on the stress magnetization coupling equation to perform real-time balanced modulation of the local magnetization delay and output a stable magnetic signal sequence after demagnetization.

[0012] Step 5: Input the stable magnetic signal sequence after demagnetization into the magnetic force fusion judgment engine, synchronously map the magnetic signal characteristics with the mechanical load distribution, and respond only to real mechanical loosening based on the synchronous mapping results.

[0013] Preferably, the step of acquiring the real-time magnetic flux density distribution signal of the fastener during the force-bearing operation includes:

[0014] When the fastener is under loading, unloading and variable load operation, the magnetic flux density distribution signal at multiple locations on the outer surface of the fastener is acquired in real time. The locations include the threaded area, head support surface, axial middle section and contact area with the connecting base. The three-dimensional magnetic flux response is synchronously acquired at millisecond time intervals through a high-sensitivity vector magnetic sensing unit.

[0015] After acquiring the magnetic flux density signal, the spatial position of each sampling point is marked. A coordinate reference system is established with the fastener axis as the Z-axis, the thread rotation direction as the θ-axis, and the radius direction as the R-axis. The magnetic flux vectors at the same moment are compared to obtain the magnetic field direction gradient.

[0016] Based on the time series, the magnetic flux density change process of the fastener during the entire stress cycle is transformed into a stress magnetization dynamic evolution curve, and the rising segment, the steady segment and the falling segment are divided by characteristic points to reflect the change of magnetic domain orientation.

[0017] Based on the steady phase of the stress magnetization dynamic evolution curve, the average magnetic flux value is calculated in the section where the magnetic flux density changes slowly, and a continuous time-series baseline is established for the identification of residual magnetic fields, which is used for the judgment of subsequent magnetic field changes and the identification of residual magnetic fields.

[0018] Preferably, the step of extracting the domain rotation rate abrupt change segment in the stress magnetization dynamic evolution curve based on the established continuous time-series baseline includes:

[0019] The magnetic flux density variation trend of each time segment in the stress magnetization dynamic evolution curve is compared with the continuous time-series baseline segment by segment. By analyzing the rate of change of magnetic flux density, the time segment of sudden change in magnetic domain rotation rate is identified.

[0020] Based on the identified abrupt change sections, the amplitude, duration and direction of magnetic flux change are statistically analyzed to construct the residual magnetic field accumulation characteristic distribution of fasteners at different time stages, and transient stress response interference is eliminated with a continuous time-series baseline as a reference.

[0021] The cumulative characteristic distribution of residual magnetic field is correlated with the dynamic evolution curve of stress magnetization on an hourly basis, and the steady-state magnetic domain signal and transient stress response signal are distinguished based on the degree of continuous deviation of magnetic flux density from the baseline.

[0022] A magnetic signal weighting model is generated based on steady-state magnetic domain signals. The stable value of magnetic flux density at each sampling point is correlated with its spatial force characteristics to determine the relative weight of different regions in the overall magnetic signal distribution.

[0023] Preferably, the step of reconstructing the magnetic domain residual distribution map in the spatial domain based on the magnetic signal weighting model includes:

[0024] Based on the magnetic signal weighting model, the spatial coordinates of the magnetic signals at different positions of the fastener are calibrated. A spatial reference frame is established with the central axis of the fastener as the longitudinal direction, so that each magnetic signal acquisition point has a clear spatial coordinate label.

[0025] The magnetic flux vector direction and intensity of sampling points on the surface and inside the fastener are spatially combined, and the regions with incomplete magnetic domain rotation and significant hysteresis response are identified based on the magnetic signal weighting model to form a preliminary magnetic flux spatial distribution map.

[0026] For regions with local hysteresis or uneven magnetic flux, the weight values ​​reflecting the stability of magnetic domains in the magnetic signal weight model are used for correction in order to eliminate abnormal deflection and maintain the continuity of magnetic flux distribution.

[0027] The corrected magnetic flux distribution results are integrated across the entire domain to form a true magnetic flux input matrix, which is used to reflect the actual magnetic flux distribution of the fastener in different stress regions.

[0028] Preferably, when correcting regions with local lag or uneven magnetic flux, the original magnetic flux direction is maintained for high-weight regions and the magnetic flux direction for low-weight regions is adjusted according to the average direction of adjacent regions based on the weight values ​​reflecting the stability of magnetic domains in the magnetic signal weight model. This is to eliminate abnormal deflection caused by local magnetic domain lag and maintain the spatial continuity and physical rationality of the magnetic field distribution by balancing the gradient of magnetic flux change.

[0029] Preferably, the step of establishing a dynamic flux density compensation layer using a real flux input matrix includes:

[0030] Based on the real magnetic flux input matrix, the magnetic flux density distribution at different spatial locations is physically interpreted to identify the magnetic domain orientation change law in each force region of the fastener, and the magnetization stable region and magnetization delay region are determined.

[0031] A dynamic magnetic flux density compensation layer is established by combining the stress magnetization coupling principle. The corresponding compensation amplitude is set according to the degree of magnetization delay at different spatial locations, so that the change in magnetic flux density keeps pace with the change in load.

[0032] Under the action of the dynamic compensation layer, the local magnetization delay region of the fastener is balanced and modulated in real time. By adjusting the magnetic flux change rate, the local asynchronous response is eliminated and the residual magnetism is dynamically dissipated.

[0033] The magnetic flux signal corrected by the dynamic compensation layer is integrated to output a stable magnetic signal sequence after residual magnetization removal, which is used to reflect the actual mechanical load distribution of the fastener under different stress states.

[0034] Preferably, the magnetic flux density dynamic compensation layer monitors the rate of change of magnetic flux in the magnetization delay region of the real magnetic flux input matrix in real time. When the rate of change of magnetic flux is lower than the neighborhood average, it applies reverse balance modulation. When the rate of change of magnetic flux is higher than the neighborhood average, it weakens the magnetization response amplitude, thereby improving the time stability of the magnetic signal and preventing the continuous accumulation of residual magnetization.

[0035] Preferably, the step of inputting the stable magnetic signal sequence after demagnetization processing into the magnetic fusion judgment engine includes:

[0036] The stable magnetic signal sequence after demagnetization is input into the signal receiving unit to perform time alignment and intensity calibration of the magnetic response signal, and to establish a unified time and intensity reference system.

[0037] Feature extraction is performed on the magnetic signal sequence to identify key feature points of magnetic flux change in different force regions in order to form a magnetization feature sequence;

[0038] The magnetization feature sequence is synchronously mapped with the mechanical load distribution of the fastener to establish a physical correspondence between the magnetization response and the force state, so as to distinguish between the real force response and the false magnetization signal.

[0039] The type of magnetic signal change is determined based on the synchronous mapping results, and the system only responds to real mechanical loosening, thus shielding against false triggering of stress magnetization signals.

[0040] The screened magnetic signals and mechanical state information are integrated to output fusion monitoring results, so as to realize dynamic tracking of fastener operating status and improve reliability.

[0041] Preferably, during the synchronous mapping process, the rate of change of magnetic flux, amplitude offset, and duration in the magnetization feature sequence are compared with the trend of change of mechanical load distribution item by item. When the change of magnetic signal is synchronous with the change of load, it is determined to be a real force response. When the two are not synchronous, it is determined to be a false magnetization signal, so as to ensure that the response is triggered only under real mechanical loosening and to avoid false triggering of the force release control.

[0042] The automotive fastener optimization design system includes a magnetic flux acquisition and analysis module, a residual magnetic feature extraction module, a magnetic flux space reconstruction module, a magnetic flux dynamic compensation module, and a magnetic force fusion judgment module.

[0043] The magnetic flux acquisition and analysis module acquires the real-time magnetic flux density distribution signal of the fastener during the force operation process, uses a high-sensitivity vector magnetic sensing array to extract the magnetic field direction gradient information, forms a stress magnetization dynamic evolution curve, and establishes a continuous time-series baseline for residual magnetic field identification based on the curve.

[0044] The residual magnetic feature extraction module extracts the abrupt change segment of magnetic domain rotation rate in the stress magnetization dynamic evolution curve based on the established continuous time-series baseline, constructs the residual magnetic field accumulation feature function, separates the steady-state magnetic domain signal from the transient stress response, and generates a magnetic signal weight model.

[0045] The magnetic flux spatial reconstruction module, based on the magnetic signal weight model, uses a multi-dimensional magnetic flux vector projection algorithm to reconstruct the magnetic domain residual distribution map in the spatial domain, performs weight correction on the local hysteresis magnetic field signal, and obtains the true magnetic flux input matrix.

[0046] The magnetic flux dynamic compensation module utilizes the real magnetic flux input matrix and establishes a dynamic magnetic flux density compensation layer based on the stress magnetization coupling equation. It performs real-time balanced modulation on the local magnetization delay and outputs a stable magnetic signal sequence after demagnetization processing.

[0047] The magnetic force fusion judgment module inputs the stable magnetic signal sequence after residual magnetization processing into the magnetic force fusion judgment engine, synchronously maps the magnetic signal characteristics with the mechanical load distribution, and responds only to real mechanical loosening based on the synchronous mapping results.

[0048] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0049] This invention achieves time-dimensional tracking and physical law identification of magnetic field response by constructing a dynamic evolution curve of stress magnetization and establishing a continuous temporal baseline during fastener operation, ensuring that magnetization changes correspond consistently to the stress state. By extracting abrupt changes in magnetic domain rotation and constructing residual magnetism accumulation characteristics, the steady-state residual magnetism signal caused by long-term loads can be effectively separated from the transient stress response, making the magnetic detection signal more physically representative and stable, fundamentally eliminating error accumulation caused by magnetostriction. The resulting magnetic signal maintains stable and continuous response characteristics under varying forces, significantly improving the accuracy and repeatability of magnetic detection of fasteners under complex load conditions.

[0050] This invention utilizes multidimensional magnetic flux vector space reconstruction and dynamic compensation balance modulation to achieve synchronous and consistent magnetization response of fasteners in time and space, outputting a stable magnetic signal sequence after residual magnetization processing. After fusion judgment, a real-time correspondence is formed between the magnetic signal and the mechanical load distribution, outputting a response only when actual mechanical loosening occurs, thereby effectively avoiding false triggering caused by spurious magnetization signals. Through this process, the operation monitoring of fasteners has higher safety reliability and judgment accuracy, achieving a high degree of synergy between magnetic detection and mechanical behavior, providing a guarantee for the intelligent design and long-term operational stability of vehicle connectors. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0052] Figure 1 This is a flowchart of the automotive fastener optimization design method of the present invention.

[0053] Figure 2 This is a schematic diagram of the modules of the automotive fastener optimization design system of the present invention. Detailed Implementation

[0054] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, they are provided so that the description of this disclosure will be more complete and fully convey the concept of the exemplary embodiments to those skilled in the art.

[0055] This invention provides, for example Figure 1 The automotive fastener optimization design method shown includes the following steps:

[0056] Step 1: Obtain the real-time magnetic flux density distribution signal of the fastener during the operation under stress, extract the magnetic field direction gradient information using a high-sensitivity vector magnetic sensing array, form a stress magnetization dynamic evolution curve, and establish a continuous time-series baseline for residual magnetic field identification based on the curve.

[0057] The specific implementation method for this step is as follows:

[0058] First, the magnetic flux density distribution signal generated by the fastener during operation is acquired in real time under loading, unloading, and variable load conditions. To ensure the integrity and continuity of the magnetic field data, multiple high-sensitivity vector magnetic sensing units are uniformly arranged on the outer surface of the fastener's threaded area, head support surface, axial middle section, and area in contact with the connecting base. Each unit is fixed in close contact with the fastener surface to simultaneously sense the radial magnetic flux, tangential magnetic flux, and magnetic flux density changes along the fastener's axis. Each sensing unit continuously samples at millisecond intervals during operation, recording the three-dimensional magnetic flux response of the fastener under stress through multi-channel synchronous acquisition. To avoid interference from external magnetic fields or adjacent components, a reference magnetic point is established outside the detection area of ​​the fastener to measure the ambient magnetic field baseline value, thus allowing the environmental background magnetic influence to be subtracted during signal processing. During operation, the magnetic domains inside the metal material of the fastener undergo orientation adjustment under external force, forming a captured change in magnetic flux density. As the load gradually increases, the magnetic domains tend to align uniformly, and the magnetic flux density increases; when the load decreases, the magnetic domains rotate in the opposite direction, and the magnetic flux density decreases. By continuously recording the magnetic flux intensity at different time points, a raw data sequence reflecting the magnetic response state of the fastener can be obtained, providing basic data support for subsequent steps.

[0059] After obtaining the magnetic flux density signal of the fastener over a continuous time period, the spatial position of each sampling point is clearly marked, ensuring that the magnetic flux information of each sampling point corresponds one-to-one with its specific physical position on the fastener surface. To this end, a coordinate reference system is preset on the outer surface of the fastener, with the fastener's axial direction as the Z-axis, the thread rotation direction as the θ-axis, and the radius direction as the R-axis, thus giving each sensing unit a fixed coordinate for its spatial acquisition position. By comparing the magnetic flux vectors of each sampling point within the same time period, the gradient of the magnetic field in the spatial direction can be obtained. Due to differences in stress concentration, metal grain orientation, and local force direction in different parts of the fastener, the spatial distribution of the magnetic field gradient often exhibits non-uniform characteristics. For example, the rate of change of the magnetic flux gradient is usually higher at the thread root and head support surface, while it is relatively gentler in the central region of the shank. By calculating the magnetic field direction gradient point by point and comparing it continuously over time, a three-dimensional trajectory of the magnetic field direction changing over time can be formed. To ensure the continuity of the magnetic field direction gradient data, the sampling interval must be kept constant, and the sampling time of each channel must be synchronously calibrated so that each set of magnetic flux gradient values ​​on the time axis corresponds to the stress state at the same moment. By using this spatial correspondence and time tracking method, the actual process of stress transfer and magnetization response inside the fastener can be reflected in the direction distribution and evolution trajectory of the magnetic field.

[0060] After clarifying the relationship between the magnetic field direction gradient and time, the change in magnetic flux density of the fastener throughout the entire loading cycle is transformed into a dynamic evolution curve of stress magnetization, with time as the main axis. During implementation, the continuously collected magnetic flux density sequence is used as input, and the magnetic flux intensity values ​​of each sampling point are arranged sequentially along the time axis. The trend of magnetic flux change over time is depicted using a sliding interval method. The rising phase of the curve typically corresponds to the magnetic domain orientation adjustment process of the fastener transitioning from an unloaded state to a pre-tightened state, during which the magnetic flux density increases rapidly. The stable phase of the curve reflects the magnetic domain orientation state of the fastener under stable force, during which the change in magnetic flux density is relatively small. The falling phase of the curve represents the magnetic domain rotation process after the force on the fastener weakens or is unloaded, with the magnetic flux density showing a slow decreasing trend. In multiple cycles of the curve, some sections show that the magnetic flux intensity has not completely returned to its initial value; this part reflects the cumulative effect of residual magnetization. Through trend analysis of each stage of the curve, the hysteresis phenomenon experienced by the magnetic domain orientation during loading and unloading can be observed intuitively, i.e., the different rates of magnetization and demagnetization. To enhance the readability of the curve, time-continuous feature points are selected, such as the initial moment of load application, the moment of maximum load, the moment of unloading start, and the moment of complete unloading, which correspond to the key nodes of the curve, so that the stress magnetization dynamic evolution curve can fully characterize the changes in magnetization behavior of the fastener throughout the entire stress process.

[0061] After obtaining the dynamic evolution curve of stress magnetization, a continuous temporal baseline for residual magnetic field identification is established based on the magnetic flux density variation characteristics during the stable loading stage. The continuous temporal baseline is established by selecting time segments in the curve where magnetic flux density changes slowly and with small fluctuations, calculating the average magnetic flux value at each time node within these segments, and using this as a reference value for the magnetic field stability of the fastener under normal loading. To improve the representativeness of the baseline, the average magnetic flux values ​​of the corresponding stable intervals in multiple loading cycles are compared longitudinally to extract common trends, thus forming a long-term baseline that reflects the natural evolution of magnetization over time. This baseline is continuously distributed along the time axis, encompassing both the magnetic response during the initial loading stage of the fastener and the magnetization equilibrium state after long-term operation. If a small drift in magnetic flux density occurs due to material stress accumulation or microstructural changes after the fastener has been running for a period of time, this drift will be recorded in the temporal baseline as a reference for subsequent identification of residual magnetization. In subsequent testing, by comparing the difference between the real-time magnetic flux signal and this time-series baseline, it can be determined whether the current magnetic field change is a natural evolution of stress magnetization or a sudden change caused by abnormal mechanical loosening. The continuous time-series baseline not only reflects the magnetization stability of the fastener under normal stress conditions, but also provides a physical reference for subsequent residual magnetism identification and magnetic signal correction, thereby ensuring that subsequent signal analysis has an accurate basis for judgment.

[0062] Through the above steps, the acquisition of magnetic flux density, extraction of spatial gradient, construction of magnetization evolution curves, and establishment of continuous temporal baselines during the operation of fasteners under stress are systematically completed. This entire process not only fully reveals the magnetization response law of fasteners under external forces but also effectively identifies the formation and evolution characteristics of residual magnetic fields. This lays the physical foundation for subsequent residual magnetic signal separation, real magnetic flux reconstruction, and stable magnetic signal output, significantly improving the accuracy and reliability of fastener operation status detection.

[0063] Step 2: Based on the established continuous time-series baseline, extract the abrupt change segment of magnetic domain rotation rate in the stress magnetization dynamic evolution curve, construct the residual magnetic field accumulation characteristic function, separate the steady-state magnetic domain signal from the transient stress response, and generate a magnetic signal weight model for subsequent magnetic signal spatial mapping.

[0064] The specific implementation method for this step is as follows:

[0065] On an established continuous time-series baseline, the magnetic flux density variation trend of each time segment in the stress magnetization dynamic evolution curve is compared segment by segment. By analyzing the difference between the magnetic flux density variation value at each time node and the reference value at the corresponding time of the baseline, unstable variation segments in the magnetization response process can be identified. When the fastener enters the load adjustment or stress transfer stage under stress, the magnetic domains inside the material undergo a sharp orientation adjustment, resulting in a significant increase or decrease in the rate of change of magnetic flux density within a short period of time. By smoothing and comparing the rate of change in continuous intervals of the curve, the time periods in which the magnetic domain rotation rate abruptly changes can be identified. These abrupt change segments often correspond to the rearrangement of the material's magnetic domains, local demagnetization, or stress release processes, and are key criteria for distinguishing between steady-state magnetization and transient magnetic response. In this process, the continuous time-series baseline serves as a reference line, providing the range of magnetization changes of the fastener under normal stress equilibrium, so that any rate abrupt change exceeding this range can be regarded as an abnormal magnetic domain rotation phenomenon.

[0066] After identifying abrupt changes in the magnetic domain rotation rate, the residual magnetic field accumulation characteristics of the fastener at different time stages are constructed based on the magnetic flux density variation characteristics of these segments. To achieve this, the amplitude, duration, and direction of magnetic flux change in each abrupt change segment are statistically summarized to form a time distribution sequence reflecting the residual magnetic accumulation trend. This distribution sequence reflects the gradual shift of magnetic domain orientation during long-term stress operation of the fastener. Typically, when the fastener is under stable stress, the magnetic flux change rate is small and fluctuates slowly; however, when the load is uneven or stress is concentrated over a long period, the magnetic domains shift in a fixed direction, and the residual magnetic field gradually accumulates over time. By superimposing the magnetic flux changes in multiple abrupt change segments, the accumulation trend of the magnetic field in the time dimension can be obtained. Meanwhile, to avoid interference from transient stress responses on the residual magnetic characteristics, a continuous time-series baseline is used as a reference during the statistical process. Small fluctuations within the baseline range are considered normal magnetization responses, and abrupt changes beyond this range are considered contributions to residual magnetic accumulation. This ensures that the residual magnetic field accumulation characteristics only reflect irreversible changes in the material's magnetic domains rather than temporary magnetic responses caused by load fluctuations.

[0067] After obtaining the temporal distribution of the residual magnetic field accumulation characteristics, these characteristics are further distinguished between steady-state and transient states to separate the steady-state magnetic domain signal from the transient stress response signal. In this stage, by hourly mapping the residual magnetic feature distribution to the stress magnetization dynamic evolution curve, the magnetic domain response properties within the same time interval can be determined. Generally, the steady-state magnetic domain signal corresponds to a segment where the magnetic domain structure has become relatively fixed, the magnetic flux density changes are small, and the direction is consistent; the transient stress response signal manifests as short-term magnetic flux fluctuations or direction reversals. To ensure the accuracy of the separation, a continuous temporal baseline is used as a stable reference. By analyzing the degree of continuous deviation of the magnetic flux density relative to the baseline, it is determined whether the deviation is recoverable. If the magnetic flux density can return to near the baseline after a certain time, the change is considered a transient response; if the magnetic flux density remains deviated for a longer period, it is determined to be a steady-state residual magnetic signal. Through this comparison method based on time continuity, the reversible magnetization behavior of fasteners under normal load fluctuations can be clearly distinguished from the irreversible magnetization behavior caused by stress solidification of the metal structure. The identification of steady-state magnetic domain signals provides a stable reference for subsequent real magnetic field mapping, while the elimination of transient stress responses avoids the interference of short-term disturbances on the overall magnetization analysis results.

[0068] After distinguishing between steady-state and transient magnetic responses, a magnetic signal weighting model is generated based on the steady-state magnetic domain signal to guide subsequent magnetic signal spatial mapping. In this process, the magnetic flux density value of each sampling point is mapped one-to-one with its physical characteristics in space, utilizing the previously obtained residual magnetism accumulation characteristics and steady-state magnetic domain signal distribution. Specifically, the stable magnetic flux density values ​​at each measurement location on the fastener's outer surface are statistically analyzed, and combined with the characteristics of the stress-bearing region (such as the thread root, bearing surface, and middle section of the rod), the relative importance of different regions in the overall magnetic signal distribution is determined. Based on the ratio of the magnetic domain stability to the magnetic flux variation amplitude in each region, corresponding weight values ​​are assigned to different sampling points, ensuring that the overall magnetic signal distribution reflects the true contribution ratio of the magnetic response in the stress-bearing region. The magnetic signal weighting model generated in this way reflects the actual influence of the magnetic field at different locations on the overall magnetization behavior of the fastener under complex stress conditions. This weighting model provides an accurate reference for subsequent magnetic signal spatial mapping, enabling the reconstruction and analysis of the magnetic flux distribution to no longer rely on the uniformity assumption, but rather to achieve spatial reproduction based on the magnetic field weight allocation under the actual stress state of the fastener.

[0069] Through the above implementation steps, the magnetic response generated during the stress process can be layered and accurately separated without damaging the fastener structure. This effectively eliminates the interference of transient loads on magnetic detection and retains the steady-state magnetic signal reflecting the intrinsic magnetization state of the material. This implementation method realizes a complete closed-loop process from continuous temporal baseline to magnetic domain rotation abrupt change identification, and then to residual magnetic feature extraction and magnetic signal weight generation. This ensures the physical authenticity and interpretability of the magnetic signal in subsequent spatial mapping, providing a reliable basis for subsequent magnetic flux reconstruction and stress state identification.

[0070] Step 3: Based on the magnetic signal weighting model, the multidimensional magnetic flux vector projection algorithm is used to reconstruct the magnetic domain residual distribution map in the spatial domain, and the weight correction is performed on the local hysteresis magnetic field signal to obtain the real magnetic flux input matrix. The real magnetic flux input matrix is ​​used to reflect the actual magnetic flux distribution of the fastener in different stress areas.

[0071] The specific implementation method for this step is as follows:

[0072] Based on the magnetic signal weighting model established in the previous implementation phase, the magnetic signals at different locations of the fastener are spatially calibrated to achieve accurate positioning of the magnetic flux density in three-dimensional space. To this end, a spatial reference frame is established based on the fastener's geometry, with the fastener's central axis as the longitudinal direction and the plane perpendicular to the axis as the radial plane. Angle markers are set along a spiral direction within this plane, ensuring that each magnetic signal acquisition point has a clear spatial coordinate identifier. The corresponding weight values ​​from the magnetic signal weighting model are assigned to these spatial sampling points, giving them both magnetic flux density amplitude information and relative weights reflecting local magnetic domain stability. In this way, the magnetic field data is no longer merely a discrete time series, but becomes a multidimensional magnetic flux vector set with a clear spatial distribution. Simultaneously, the residual magnetic field accumulation characteristics and steady-state magnetic domain signal distribution identified in the previous step are synchronously mapped onto this spatial reference frame, giving the magnetic signals a physical meaning corresponding to the force state in spatial location, providing a foundation for subsequent spatial projection and reconstruction.

[0073] After spatial calibration and weighting of the magnetic signals, the magnetic flux vector directions and intensities at each sampling point on the surface and inside the fastener are spatially combined to correlate the magnetic flux information at each point and form a continuous magnetic flux distribution. Specifically, magnetic flux vectors on the same radial plane are connected according to their spatial adjacency, and the extension direction of the magnetic domain orientation is determined by the continuity of the vector direction. Due to the axisymmetric nature of the fastener's geometry, the magnetic flux vectors usually exhibit a regular distribution at different angular positions. However, in areas with uneven stress or local stress concentration, the magnetic domain direction may deflect or reverse locally, resulting in localized dense or sparse magnetic flux lines. By combining the weight values ​​in the magnetic signal weighting model with the changes in magnetic flux density in these areas, regions with incomplete magnetic domain rotation and significant hysteresis responses can be identified. These regions manifest as bending, breakage, or aggregation of magnetic flux lines in the magnetic flux distribution, serving as important criteria for judging the residual distribution of magnetic domains. By correlating the continuity of the magnetic flux vector direction and density differences point by point within these spatial regions, a preliminary spatial distribution map of the magnetic flux reflecting the overall magnetization state of the fastener can be formed.

[0074] After obtaining the initial magnetic flux spatial distribution, for regions with localized magnetic domain lag or magnetic flux unevenness, the weight values ​​reflecting magnetic domain stability in the aforementioned magnetic signal weighting model are used for correction, so that the magnetic flux distribution can more realistically reflect the actual stress situation of the fastener. The correction process mainly includes correcting local magnetic field direction deviations and magnetic flux intensity imbalances. In practice, the magnetic flux vector of each sampling point is compared with the average magnetic flux direction of its adjacent regions. If the deviation angle exceeds a certain range, it indicates that there is lag or local demagnetization in the magnetic domains of that region. For such regions, based on their weight values ​​in the magnetic signal weighting model, corrections are made according to the relative degree of magnetic domain stability, so that the magnetic flux direction of high-weight regions maintains a stable trend, while the magnetic flux direction of low-weight regions is gradually adjusted to the neighborhood average direction to eliminate abnormal deflections caused by transient loads or local structural non-uniformity. At the same time, for points with excessively high or low magnetic flux density, the surrounding magnetic flux change gradient is balanced to maintain the continuity and physical rationality of the overall magnetic flux distribution. After this process, local anomalies in the magnetic flux distribution are smoothed, the spatial continuity of the magnetic field strength is enhanced, and the morphology of the magnetic domain residual region becomes clearer.

[0075] After correcting the local hysteresis magnetic field signal, the corrected spatial magnetic flux distribution results are integrated globally to form a true magnetic flux input matrix. This matrix is ​​based on the fastener's spatial coordinates, with each matrix element corresponding to a specific spatial location's magnetic flux density value and its direction information, thus forming a physical characterization matrix that comprehensively reflects the magnetization state of the fastener's stressed area. In this matrix, the magnetic flux variation along the fastener's axial direction reflects the difference in magnetic domain orientation caused by longitudinal force; the magnetic flux variation along the radial direction reflects the difference in load distribution between different threaded rings or contact surfaces; and the magnetic flux variation along the circumferential direction reveals the influence of torque on the magnetization direction. By observing the distribution patterns of magnetic flux density in different regions of the matrix, regions of concentrated force, hysteresis delay, and residual magnetization accumulation can be clearly identified. The establishment of the true magnetic flux input matrix not only achieves a one-to-one spatial correspondence between the fastener's stressed state and magnetization distribution but also provides a quantitative basis for subsequent dynamic compensation of magnetic signals based on true magnetic flux information.

[0076] Through the above steps, the magnetic signal undergoes weight allocation, spatial projection, and local correction, ultimately forming a true magnetic flux input matrix that reflects the actual magnetization state of the fastener. This process spatially reconstructs the magnetic field information and physically achieves a unified representation of magnetic domain remnants and stress state, ensuring the accuracy and consistency of the magnetic signal in the subsequent dynamic compensation stage. This implementation effectively overcomes the spatial distortion problem caused by local hysteresis and non-uniform magnetization in traditional detection, enabling the magnetic flux distribution to remain consistent with the actual stress characteristics of the fastener. Thus, without damaging the structure, it achieves high-precision, full-space magnetic response reconstruction of the fastener's stress health state.

[0077] Step 4: Using the real magnetic flux input matrix, a dynamic magnetic flux density compensation layer is established based on the stress magnetization coupling equation. The local magnetization delay is balanced and modulated in real time, and a stable magnetic signal sequence after demagnetization is output, so that the obtained magnetic signal can reflect the real mechanical load state.

[0078] The specific implementation method for this step is as follows:

[0079] Based on the obtained true magnetic flux input matrix, the magnetic flux density distribution at different spatial locations within the matrix is ​​physically interpreted to identify the variation patterns of magnetic domain orientation within each stress region of the fastener. The true magnetic flux input matrix contains magnetic flux density distribution information of the fastener in the axial, radial, and circumferential dimensions. The magnetic flux intensity in different regions reflects the degree of magnetization and stress concentration of the metal material under external force. By analyzing the magnetic flux distribution across continuous spatial layers in the matrix, the dominant direction of the magnetization response and local anomalous regions can be determined. For example, when the magnetic flux density at the thread root or head support surface is consistently higher than the average level, it usually indicates strong stress concentration and magnetization enhancement in that region; while when the magnetic flux distribution in certain regions exhibits periodic fluctuations, it is often related to the loading-unloading cyclic hysteresis effect of the material. In this way, the magnetization stability region and the magnetization delay region can be clearly delineated in the magnetic flux space, thus providing a spatial basis for the subsequent establishment of the compensation layer.

[0080] After identifying the magnetization delay region, a dynamic flux density compensation layer was established based on the stress-magnetization coupling principle to adjust the response balance of the magnetic signal in the time and spatial domains. The stress-magnetization coupling principle indicates that the magnetization state of ferromagnetic materials is not only affected by the applied magnetic field but also closely related to the mechanical stress they bear. When the stress state of a local area of ​​the material changes, the magnetic domain orientation adjusts accordingly, but this adjustment usually exhibits a response hysteresis, leading to time delay or amplitude distortion in the magnetic signal. To compensate for this hysteresis effect, corresponding compensation amplitudes are set at different spatial locations on and inside the fastener, based on the degree of magnetization delay, so that the change in magnetic flux density can remain synchronized with the change in load. During the construction of the compensation layer, the magnetic flux distribution provided by the real magnetic flux input matrix is ​​used as the basic data, and the magnetic flux intensity at each spatial point is correlated with its corresponding force direction, so that the compensation layer forms a magnetic flux balance structure in space consistent with the force path. In this way, the compensation layer can adjust the rate of change of magnetic flux density in each local area in real time during the overall magnetization response of the fastener, so that the magnetic signal remains continuous in time and coordinated in space, thereby effectively eliminating the asynchronous response caused by magnetization hysteresis.

[0081] After establishing the dynamic flux density compensation layer, real-time balancing modulation is applied to the local magnetization delay generated during the fastener's operation under load, further improving the stability and response accuracy of the magnetic signal. During fastener operation, the stress change rate varies across different regions. Differences in the plasticity of local material structures can lead to slower domain rotation speeds in certain regions, resulting in hysteresis delay. Therefore, under the dynamic compensation layer, these hysteresis-lagging regions are monitored and adjusted hourly. When the flux change rate in a region of the flux input matrix is ​​lower than the neighborhood average, the compensation layer applies reverse balancing modulation to that region, allowing the flux intensity to recover to the normal response level instantly with load changes. When the flux change rate in a region is significantly higher than the surrounding regions, a balancing mechanism weakens its magnetization response amplitude to prevent signal fluctuations caused by short-term magnetic impulses. After continuous balancing modulation, the flux response in each region tends to be consistent, significantly enhancing the overall temporal stability of the fastener's magnetic signal. At the same time, the compensation layer also dynamically dissipates the residual magnetism that gradually accumulates during long-term operation. By fine-tuning the orientation of local magnetic domains, the magnetic domains can be restored to their initial magnetization state after being subjected to force cycles, thereby preventing the continuous accumulation of residual magnetization.

[0082] After real-time balanced modulation of the local magnetization delay, the magnetic flux signal corrected by the dynamic compensation layer is integrated to output a stable magnetic signal sequence after residual magnetization removal. This sequence is then used as the magnetic response output reflecting the true stress state of the fastener. The compensated magnetic signal sequence exhibits continuous and smooth magnetic flux changes in the time dimension and magnetization characteristics consistent with the stress distribution in the spatial dimension. By comparing the magnetic flux signals at different time points, stress fluctuations, load transfers, and loosening signs generated in the fastener during the stress process can be accurately identified. Compared with the uncompensated original magnetic signal, the magnetic signal sequence after residual magnetization removal significantly reduces the influence of background magnetic noise and residual magnetic offset, making the detection results more physically realistic. This magnetic signal sequence can not only serve as a basis for real-time monitoring of the fastener's stress state but also provide high-precision data support for subsequent mechanical load inversion and structural health assessment. When the fastener is in different working stages, this stable magnetic signal sequence can remain synchronized with the actual stress changes, ensuring a direct correspondence between the magnetic response and the mechanical state.

[0083] Through the above implementation steps, the magnetization response of the fastener is fully realized from spatial reconstruction to time compensation. This process not only achieves a balanced distribution of magnetic flux density in the spatial domain and dynamic matching in the time domain, but also, by removing residual magnetism and correcting hysteresis, makes the magnetic signal a true physical mapping of load changes. The resulting compensated stable magnetic signal sequence has high repeatability and reliability, and can accurately reflect the true stress state of the fastener under complex load environments over a long period of time.

[0084] Step 5: Input the stable magnetic signal sequence after demagnetization into the magnetic force fusion judgment engine, synchronously map the magnetic signal characteristics with the mechanical load distribution, and respond only to real mechanical loosening based on the synchronous mapping results, thereby avoiding false triggering of the release control caused by false stress magnetization signals, and realizing the optimization design and improved reliability of fastener operation monitoring.

[0085] The specific implementation method for this step is as follows:

[0086] The stable magnetic signal sequence, after demagnetization, is input into the signal receiving unit of the fusion judgment process to achieve time alignment and intensity calibration of the magnetic response signal. The stable magnetic signal sequence was obtained in the previous stage through stress magnetization dynamic compensation and residual magnetization elimination, and its temporal continuity and spatial consistency have been optimized. At this point, to ensure a one-to-one correspondence between the magnetic signal and the actual stress state of the fastener, the signal sequence needs to be standardized. Specifically, within each loading cycle of the fastener's operation, the complete magnetic flux intensity change curve is extracted, and the time axis of the signal is recalibrated using the initial loading moment as the time reference point. Simultaneously, the magnetic flux amplitude of each stress region is normalized, allowing the magnetic flux response of different regions to be compared under the same reference scale. After this step, the magnetic signals generated by the fastener at different working stages are unified into the same time and intensity reference system, laying the data foundation for subsequent synchronization mapping.

[0087] After completing the time alignment and amplitude calibration of the magnetic signals, the magnetic field change characteristics reflected in the magnetic signal sequence are extracted to clarify the magnetization response characteristics of different stress regions. During the loading process of fasteners, due to the different geometries, material structures, and force directions of each part, the magnetic signal sequence exhibits differentiated change patterns over time. For example, the peaks, troughs, and rise rates of the magnetic flux change curves are different at the thread root, support surface, and middle section of the rod. By continuously comparing the temporal distribution of the magnetic signal change trends in each region, key feature points of magnetic field change can be identified, such as rapid rise points, stable sections, and falling inflection points. These feature points correspond to the physical processes of different stress stages such as fastener loading, holding, and unloading. By extracting these time nodes and their corresponding magnetic flux amplitude changes, a complete magnetization feature sequence can be formed, which characterizes the dynamic response characteristics of the magnetic signal throughout the entire stress cycle. This step transforms the magnetic signal from a single amplitude data point into a temporal feature structure synchronized with mechanical behavior.

[0088] After obtaining the characteristic sequence of the magnetic signal, it is synchronously mapped with the mechanical load distribution of the fastener to establish a physical correspondence between the magnetization response and the stress state. This process, based on the real magnetic flux input matrix and stress distribution information obtained in the previous stage, maps the magnetic signal in the time dimension to the mechanical load in the spatial dimension. Specifically, at different locations on the fastener, the magnitude, direction, and duration of the applied force vary, resulting in different magnetization response curve shapes. By matching the time nodes in the magnetic signal characteristics with the stress data at the same time, a synchronous mapping curve of magnetization intensity changing with mechanical load can be obtained. This curve reveals the nonlinear correlation between magnetization changes and load changes and reflects the sensitivity of the magnetic field to stress changes. Through this mapping relationship, it can be clearly determined whether the change in the magnetic signal is caused by real mechanical force or by stress magnetization history or material hysteresis. When the trend of the magnetic signal change is synchronous with the change in mechanical load, it is determined to be a real force response; when the change in the magnetic signal deviates from the load trend and shows an abnormal deviation, it is determined to be a false magnetization signal. This mapping process enables a dynamic correlation between magnetic signals and mechanical behavior, providing a physical basis for subsequent response determination.

[0089] After completing the synchronous mapping of magnetic signals and mechanical loads, the response results in the magnetic signal sequence are discriminated, responding only to genuine mechanical loosening. Fasteners may exhibit two types of magnetic signal anomalies during operation: one is genuine mechanical loosening caused by stress relaxation or thread slippage, and the other is a false signal caused by stress magnetization hysteresis or residual magnetism changes. To distinguish between the two, based on the synchronous mapping curve, the rate of change, amplitude shift, and duration of the magnetic signal are comprehensively judged. When the magnetic signal change is accompanied by a decrease in mechanical load, lasts for a long time, and repeats in multiple stress cycles, it can be confirmed as a genuine loosening response; when the magnetic signal change is brief and asynchronous with the change in mechanical load, it can be determined as a stress magnetization false response. For the latter, a real-time shielding mechanism is used to prevent false triggering of release control, avoiding the fastener being incorrectly released from constraint under normal stress conditions, thereby ensuring the operational safety and mechanical stability of the structure. This step achieves precise differentiation from magnetic signal identification to mechanical behavior response, enabling monitoring results to focus on genuine mechanical anomalies.

[0090] After identifying genuine mechanical loosening and suppressing false signals, the screened magnetic signals are integrated with the corresponding mechanical state information to form a fusion monitoring output of the fastener's operating status. This fusion output not only reflects the temporal consistency between the magnetic signal and the mechanical load but also demonstrates the spatial force distribution correspondence between the two. When the fastener is under stable stress, the fusion signal shows that the magnetization intensity fluctuates synchronously with the load level and is in phase. When the fastener shows a loosening trend, the magnetic flux response in the fusion signal will exhibit a phase delay or amplitude attenuation relative to the mechanical load, thus providing a basis for early fault identification. By continuously outputting the fusion signal, dynamic tracking and trend prediction of the fastener's stress health status can be achieved. Simultaneously, this fusion judgment method also has an optimization effect at the structural design level. Through long-term data accumulation, the influence of different structural parameters on magnetization stability can be deduced, providing a scientific basis for optimizing fastener geometry, material selection, and assembly methods, thereby achieving a synergistic improvement in magnetic detection characteristics and mechanical performance at the design level.

[0091] Through the above implementation steps, the magnetic response signal of the fastener is gradually mapped from the stable state after residual magnetism elimination to the actual mechanical load distribution, realizing the dynamic fusion and physical correspondence between the magnetic signal and the force behavior. The entire process not only effectively eliminates spurious signal interference caused by stress magnetization but also establishes a precise correlation between the magnetic response and the mechanical state, making the fastener's operational monitoring results more reliable and interpretable. This implementation method, by integrating magnetic and mechanical characteristics, achieves unified judgment from the signal layer to the structural layer, providing a high-precision and sustainable detection foundation for the intelligent monitoring and safe operation of automotive fasteners.

[0092] This invention achieves time-dimensional tracking and physical law identification of magnetic field response by constructing a dynamic evolution curve of stress magnetization and establishing a continuous temporal baseline during fastener operation, ensuring that magnetization changes correspond consistently to the stress state. By extracting abrupt changes in magnetic domain rotation and constructing residual magnetism accumulation characteristics, the steady-state residual magnetism signal caused by long-term loads can be effectively separated from the transient stress response, making the magnetic detection signal more physically representative and stable, fundamentally eliminating error accumulation caused by magnetostriction. The resulting magnetic signal maintains stable and continuous response characteristics under varying forces, significantly improving the accuracy and repeatability of magnetic detection of fasteners under complex load conditions.

[0093] This invention utilizes multidimensional magnetic flux vector space reconstruction and dynamic compensation balance modulation to achieve synchronous and consistent magnetization response of fasteners in time and space, outputting a stable magnetic signal sequence after residual magnetization processing. After fusion judgment, a real-time correspondence is formed between the magnetic signal and the mechanical load distribution, outputting a response only when actual mechanical loosening occurs, thereby effectively avoiding false triggering caused by spurious magnetization signals. Through this process, the operation monitoring of fasteners has higher safety reliability and judgment accuracy, achieving a high degree of synergy between magnetic detection and mechanical behavior, providing a guarantee for the intelligent design and long-term operational stability of vehicle connectors.

[0094] This invention provides, for example Figure 2 The automotive fastener optimization design system shown includes a magnetic flux acquisition and analysis module, a residual magnetic feature extraction module, a magnetic flux space reconstruction module, a magnetic flux dynamic compensation module, and a magnetic force fusion determination module.

[0095] The magnetic flux acquisition and analysis module acquires the real-time magnetic flux density distribution signal of the fastener during the force operation process, uses a high-sensitivity vector magnetic sensing array to extract the magnetic field direction gradient information, forms a stress magnetization dynamic evolution curve, and establishes a continuous time-series baseline for residual magnetic field identification based on the curve.

[0096] The residual magnetic feature extraction module extracts the abrupt change segment of magnetic domain rotation rate in the stress magnetization dynamic evolution curve based on the established continuous time-series baseline, constructs the residual magnetic field accumulation feature function, separates the steady-state magnetic domain signal from the transient stress response, and generates a magnetic signal weight model.

[0097] The magnetic flux spatial reconstruction module, based on the magnetic signal weight model, uses a multi-dimensional magnetic flux vector projection algorithm to reconstruct the magnetic domain residual distribution map in the spatial domain, performs weight correction on the local hysteresis magnetic field signal, and obtains the true magnetic flux input matrix.

[0098] The magnetic flux dynamic compensation module utilizes the real magnetic flux input matrix and establishes a dynamic magnetic flux density compensation layer based on the stress magnetization coupling equation. It performs real-time balanced modulation on the local magnetization delay and outputs a stable magnetic signal sequence after demagnetization processing.

[0099] The magnetic force fusion judgment module inputs the stable magnetic signal sequence after residual magnetization processing into the magnetic force fusion judgment engine, synchronously maps the magnetic signal characteristics with the mechanical load distribution, and responds only to real mechanical loosening based on the synchronous mapping results.

[0100] The automotive fastener optimization design method provided in this embodiment of the invention is implemented through the aforementioned automotive fastener optimization design system. For details of the specific methods and processes of the automotive fastener optimization design system, please refer to the embodiments of the aforementioned automotive fastener optimization design method, which will not be repeated here.

[0101] The foregoing has only described certain exemplary embodiments of the present invention by way of illustration. Undoubtedly, those skilled in the art can modify the described embodiments in various ways without departing from the spirit and scope of the present invention. Therefore, the foregoing drawings and descriptions are illustrative in nature and should not be construed as limiting the scope of protection of the claims of the present invention.

Claims

1. An optimized design method for automotive fasteners, characterized in that, Includes the following steps: Step 1: Obtain the real-time magnetic flux density distribution signal of the fastener during the operation under stress, extract the magnetic field direction gradient information using a high-sensitivity vector magnetic sensing array, form a stress magnetization dynamic evolution curve, and establish a continuous time-series baseline for residual magnetic field identification based on the curve. Step 2: Based on the established continuous time-series baseline, extract the abrupt change segment of magnetic domain rotation rate in the stress magnetization dynamic evolution curve, construct the residual magnetic field accumulation characteristic function, separate the steady-state magnetic domain signal from the transient stress response, and generate a magnetic signal weighting model. Step 3: Based on the magnetic signal weighting model, a multi-dimensional magnetic flux vector projection algorithm is used to reconstruct the magnetic domain residual distribution map in the spatial domain, and weight correction is performed on the local hysteresis magnetic field signal to obtain the true magnetic flux input matrix. Step 4: Using the real magnetic flux input matrix, a dynamic magnetic flux density compensation layer is established based on the stress magnetization coupling equation to perform real-time balanced modulation of the local magnetization delay and output a stable magnetic signal sequence after demagnetization. Step 5: Input the stable magnetic signal sequence after demagnetization into the magnetic force fusion judgment engine, synchronously map the magnetic signal characteristics with the mechanical load distribution, establish the physical correspondence between the magnetization response and the force state, and respond only to real mechanical loosening based on the synchronous mapping results. The steps for extracting abrupt changes in domain rotation rate from the established continuous time-series baseline stress magnetization dynamic evolution curve include: The magnetic flux density variation trend of each time segment in the stress magnetization dynamic evolution curve is compared with the continuous time-series baseline segment by segment. By analyzing the rate of change of magnetic flux density, the time segment of sudden change in magnetic domain rotation rate is identified. Based on the identified abrupt change sections, the amplitude, duration and direction of magnetic flux change are statistically analyzed to construct the residual magnetic field accumulation characteristic distribution of fasteners at different time stages, and transient stress response interference is eliminated with a continuous time-series baseline as a reference. The cumulative characteristic distribution of residual magnetic field is correlated with the dynamic evolution curve of stress magnetization on an hourly basis, and the steady-state magnetic domain signal and transient stress response signal are distinguished based on the degree of continuous deviation of magnetic flux density from the baseline. A magnetic signal weighting model is generated based on steady-state magnetic domain signals. The stable value of magnetic flux density at each sampling point is correlated with its spatial force characteristics to determine the relative weight of different regions in the overall magnetic signal distribution. The steps for establishing a dynamic flux density compensation layer using a real flux input matrix include: Based on the real magnetic flux input matrix, the magnetic flux density distribution at different spatial locations is physically interpreted to identify the magnetic domain orientation change law in each force region of the fastener, and the magnetization stable region and magnetization delay region are determined. A dynamic flux density compensation layer is established by combining the stress magnetization coupling principle. The corresponding compensation amplitude is set according to the magnetization delay degree at different spatial locations, so that the change in flux density keeps pace with the change in load.

2. The automotive fastener optimization design method according to claim 1, characterized in that, The steps for obtaining the real-time magnetic flux density distribution signal of a fastener during its operation under stress include: When the fastener is under loading, unloading and variable load operation, the magnetic flux density distribution signal at multiple locations on the outer surface of the fastener is acquired in real time. The locations include the threaded area, head support surface, axial middle section and contact area with the connecting base. The three-dimensional magnetic flux response is synchronously acquired at millisecond time intervals through a high-sensitivity vector magnetic sensing unit. After acquiring the magnetic flux density signal, the spatial position of each sampling point is marked. A coordinate reference system is established with the fastener axis as the Z-axis, the thread rotation direction as the θ-axis, and the radius direction as the R-axis. The magnetic flux vectors at the same moment are compared to obtain the magnetic field direction gradient. Based on the time series, the magnetic flux density change process of the fastener during the entire stress cycle is transformed into a stress magnetization dynamic evolution curve, and the rising segment, the steady segment and the falling segment are divided by characteristic points to reflect the change of magnetic domain orientation. Based on the steady phase of the stress magnetization dynamic evolution curve, the average magnetic flux value is calculated in the section where the magnetic flux density changes slowly, and a continuous time-series baseline is established for residual magnetic field identification.

3. The automotive fastener optimization design method according to claim 1, characterized in that, The steps for reconstructing the residual magnetic domain distribution map in the spatial domain based on the magnetic signal weighting model include: Based on the magnetic signal weighting model, the spatial coordinates of the magnetic signals at different positions of the fastener are calibrated. A spatial reference frame is established with the central axis of the fastener as the longitudinal direction, so that each magnetic signal acquisition point has a clear spatial coordinate label. The magnetic flux vector direction and intensity of sampling points on the surface and inside the fastener are spatially combined, and the incomplete magnetic domain rotation region and hysteresis response region are identified based on the magnetic signal weighting model to form a preliminary magnetic flux spatial distribution map. For regions with local hysteresis or uneven magnetic flux, the weight values ​​reflecting the stability of magnetic domains in the magnetic signal weighting model are used for correction to eliminate abnormal deflection. The corrected magnetic flux distribution results are integrated across the entire domain to form a true magnetic flux input matrix, which reflects the actual magnetic flux distribution of the fastener in different stress regions.

4. The automotive fastener optimization design method according to claim 3, characterized in that, When correcting regions with local lag or uneven magnetic flux, the magnetic flux direction is maintained in high-weight regions according to the weight values ​​reflecting the stability of magnetic domains in the magnetic signal weight model, while the magnetic flux direction in low-weight regions is adjusted according to the average direction of adjacent regions, thereby eliminating abnormal deflection caused by local magnetic domain lag.

5. The automotive fastener optimization design method according to claim 1, characterized in that, The local magnetization delay region of the fastener is balanced and modulated in real time under the action of the dynamic compensation layer. The local asynchronous response is eliminated and the residual magnetism is dynamically dissipated by adjusting the magnetic flux change rate. The magnetic flux signal corrected by the dynamic compensation layer is integrated to output a stable magnetic signal sequence after demagnetization, which reflects the actual mechanical load distribution of the fastener under different stress states.

6. The automotive fastener optimization design method according to claim 5, characterized in that, The magnetic flux density dynamic compensation layer monitors the rate of change of magnetic flux in the magnetization delay region of the real magnetic flux input matrix in real time. When the rate of change of magnetic flux is lower than the neighborhood average, it applies reverse balance modulation, and when the rate of change of magnetic flux is higher than the neighborhood average, it weakens the magnetization response amplitude.

7. The automotive fastener optimization design method according to claim 5, characterized in that, The steps for inputting the stable magnetic signal sequence after demagnetization processing into the magnetic fusion judgment engine include: The stable magnetic signal sequence after demagnetization is input into the signal receiving unit to perform time alignment and intensity calibration of the magnetic response signal, and to establish a unified time and intensity reference system. Feature extraction is performed on the magnetic signal sequence to identify key feature points of magnetic flux change in different force regions, forming a magnetization feature sequence; By synchronously mapping the magnetization feature sequence with the mechanical load distribution of the fastener, a physical correspondence between the magnetization response and the stress state is established, distinguishing between the real stress response and the false magnetization signal. The type of magnetic signal change is determined based on the synchronous mapping results, and the system only responds to real mechanical loosening, thus shielding against false triggering of stress magnetization signals. The screened magnetic signals and mechanical state information are integrated to output fusion monitoring results, enabling dynamic tracking of the fastener's operating status.

8. The automotive fastener optimization design method according to claim 7, characterized in that, During the synchronous mapping process, the rate of change of magnetic flux, amplitude shift, and duration in the magnetization feature sequence are compared with the trend of change of mechanical load distribution. When the change of magnetic signal is synchronous with the change of load, it is determined to be a real force response. When the two are not synchronous, it is determined to be a false magnetization signal.

9. An automotive fastener optimization design system, used to implement the automotive fastener optimization design method according to any one of claims 1-8, characterized in that, It includes a magnetic flux acquisition and analysis module, a residual magnetic feature extraction module, a magnetic flux spatial reconstruction module, a magnetic flux dynamic compensation module, and a magnetic force fusion determination module; The magnetic flux acquisition and analysis module acquires the real-time magnetic flux density distribution signal of the fastener during the force operation process, uses a high-sensitivity vector magnetic sensing array to extract the magnetic field direction gradient information, forms a stress magnetization dynamic evolution curve, and establishes a continuous time-series baseline for residual magnetic field identification based on the curve. The residual magnetic feature extraction module extracts the abrupt change segment of magnetic domain rotation rate in the stress magnetization dynamic evolution curve based on the established continuous time-series baseline, constructs the residual magnetic field accumulation feature function, separates the steady-state magnetic domain signal from the transient stress response, and generates a magnetic signal weight model. The magnetic flux spatial reconstruction module, based on the magnetic signal weight model, uses a multi-dimensional magnetic flux vector projection algorithm to reconstruct the magnetic domain residual distribution map in the spatial domain, performs weight correction on the local hysteresis magnetic field signal, and obtains the true magnetic flux input matrix. The magnetic flux dynamic compensation module utilizes the real magnetic flux input matrix and establishes a dynamic magnetic flux density compensation layer based on the stress magnetization coupling equation. It performs real-time balanced modulation on the local magnetization delay and outputs a stable magnetic signal sequence after demagnetization processing. The magnetic force fusion judgment module inputs the stable magnetic signal sequence after residual magnetization processing into the magnetic force fusion judgment engine, synchronously maps the magnetic signal characteristics with the mechanical load distribution, and responds only to real mechanical loosening based on the synchronous mapping results.

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