A system and method for detecting the anti-object impact performance of a handrail

Abstract

This invention relates to the field of building material structural testing technology, specifically a system and method for testing the impact resistance performance of railings and handrails. The system includes: launching a standard test impactor at a preset impact point using a controllable electromagnetic launcher; acquiring a sequence of transient deformation images from multiple perspectives using a high-speed camera; extracting the spatial coordinates of structural feature points through image enhancement and feature point calibration; and calculating the dynamic displacement field and dynamic strain field. An elastoplastic dynamics inversion algorithm is used to calculate the stress distribution time history and local plastic deformation within the impact contact area, identifying stress concentration areas and determining the stress peak and stress cycle number. Combined with the degree of residual deformation, the impact resistance performance level of the railing and handrail is quantitatively assessed, achieving standardization of the testing process and quantification of the results. This method enables controllable impact process and multi-dimensional deformation acquisition, accurately obtaining the internal mechanical response parameters of the component.

Description

Technical Field

[0001] This invention relates to the field of building material structural testing technology, and in particular to a testing system and method for testing the impact resistance of railings and handrails. Background Technology

[0002] As a building's supporting protective structure, the impact resistance of railings and handrails directly affects safety, necessitating professional performance testing and evaluation. Traditional impact testing often employs a simplistic method of free-falling heavy objects, which cannot achieve precise control over impact energy, angle, and location, and lacks a standardized impactor launch control mechanism. Deformation is recorded using only a single-view device, failing to comprehensively capture the overall transient deformation information of the component, accurately extract the temporal coordinates of structural feature points, and make it difficult to accurately calculate the dynamic displacement and strain fields throughout the entire impact process.

[0003] Current detection technologies can only observe the surface deformation of components and cannot obtain the changes in internal mechanical parameters in the impact contact area. Without the introduction of an elastoplastic dynamics inversion calculation mechanism, it is impossible to calculate the internal stress distribution time history and local plastic deformation from macroscopic deformation data, and it is impossible to locate stress concentration areas and quantitatively calculate stress peaks and stress cycle counts.

[0004] Conventional performance evaluation relies solely on apparent residual deformation as a single criterion, resulting in a limited evaluation dimension and a lack of multi-parameter comprehensive quantitative judgment standards. Consequently, the evaluation results are highly subjective and lack accuracy. The industry urgently needs to establish a standardized and controllable impact emission and multi-view deformation image acquisition mode, while simultaneously utilizing dynamic inversion algorithms to calculate internal mechanical parameters. This will enable the construction of a multi-index integrated quantitative evaluation system, meeting the application requirements for precise, standardized, and quantitative testing of the impact resistance performance of railings and handrails. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of the existing technology and to propose a system and method for testing the impact resistance of railings and handrails.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for testing the impact resistance of railings, comprising: At the preset impact point of the railing under test, a standard test impactor is launched by a controllable electromagnetic launcher, and at the same time, a high-speed camera is used to synchronously acquire a sequence of transient deformation images of the railing under test under impact from multiple perspectives. The acquired transient deformation image sequence is subjected to image enhancement and feature point calibration processing to extract the spatial coordinates of the structural feature points of the tested railing handrail at different times; Based on the spatial coordinate changes of the structural feature points, the dynamic displacement field and dynamic strain field of the tested railing handrail during the impact process are calculated. The dynamic displacement field and dynamic strain field are input into the elastoplastic dynamics inversion algorithm. Using the elastoplastic dynamics inversion algorithm, the internal stress distribution time history and local plastic deformation of the tested railing handrail in the impact contact area are inverted and calculated from the dynamic displacement field and dynamic strain field. Based on the internal stress distribution time history calculated by inversion, the stress concentration area of ​​the tested railing handrail is identified, and the stress peak value and stress cycle number of the stress concentration area are calculated. Based on the local plastic deformation, the degree of residual structural deformation of the tested railing handrail is evaluated; By combining the peak stress, the number of stress cycles, and the degree of residual deformation in the stress concentration area, the impact resistance level of the tested railing handrail is quantitatively evaluated.

[0007] As a further aspect of the present invention, the step of performing image enhancement and feature point calibration processing on the acquired transient deformation image sequence to extract the spatial coordinates of the structural feature points of the tested railing handrail at different times includes: Adaptive histogram equalization is applied to each frame of the transient deformable image sequence to enhance the contrast between the edge and surface texture of the tested railing handrail in the image; In the enhanced image, the accelerated segmentation test feature detection operator is used to automatically identify and locate the pre-set physical marker points on the handrail of the tested railing, as well as the corner points and edge features of the structure itself, as candidate structural feature points; The candidate structural feature points that are automatically identified are eliminated due to mismatches. Cross-frame tracking and consistency verification are performed based on the neighborhood texture descriptor of the feature points to filter out the set of feature points that appear stably in consecutive multi-frame images. Using the principle of binocular vision measurement, based on the calibrated internal and external parameters of the high-speed camera device, the successfully matched feature point pairs in the multi-view images synchronously acquired by the high-speed camera device are reconstructed in three dimensions to obtain the three-dimensional spatial position coordinates of each structural feature point relative to the world coordinate system at each moment. The three-dimensional spatial coordinates of all structural feature points at all times are organized in chronological order and by feature point number to form a spatiotemporal location dataset of structural feature points.

[0008] As a further aspect of the present invention, the dynamic displacement field and dynamic strain field of the tested railing handrail during the impact process are calculated based on the spatial coordinate changes of the structural feature points, including: Taking the initial moment before the impact as a reference, calculate the three-dimensional displacement vector of each of the structural feature points relative to its initial position at each subsequent moment; A two-dimensional parametric surface mesh is established on the surface of the tested railing handrail structure. The calculated three-dimensional displacement vectors of all structural feature points are interpolated and mapped to each node of the two-dimensional parametric surface mesh to generate a three-dimensional dynamic displacement field of the entire structural surface. Based on the three-dimensional dynamic displacement field, the displacement gradient of each element in the two-dimensional parameterized surface mesh in three directions is calculated; Based on the geometric relationship between strain and displacement gradient in continuum mechanics, the strain tensor at the center of the corresponding element is calculated from the displacement gradient of each element in the two-dimensional parameterized surface mesh. The strain tensors of all unit centers are integrated to form a dynamic strain field covering the surface of the tested railing handrail structure. The dynamic strain field contains data on the changes of normal strain components and shear strain components over time.

[0009] As a further aspect of the present invention, the working principle of the elastoplastic dynamics inversion algorithm includes: Establish a unified nonlinear constitutive model framework that includes material plastic hardening, strain rate effect and damage softening effect; The dynamic displacement field and dynamic strain field are used as known boundary conditions and observation data; Within the framework of the unified nonlinear constitutive model, internal variables characterizing the internal stress state and material damage state of the tested railing handrail are defined; Construct an inversion optimization problem with the objective of minimizing the differences between the calculated dynamic displacement field, dynamic strain field and the observed dynamic displacement field, dynamic strain field; In the iterative process of solving the inversion optimization problem, the adjoint state method is used to efficiently calculate the gradient of the objective function with respect to the internal variables, guiding the direction of iteration; A regularization term based on physical information is introduced to constrain the physical rationality of the inversion solution and prevent the inversion results from being non-physical due to noise in the observation data. The solution is iteratively solved until the convergence condition is met, and the final output is the internal stress distribution time history, the local plastic deformation amount, and the implicit material damage evolution process that best match the observation data.

[0010] As a further aspect of the present invention, the establishment of a unified nonlinear constitutive model framework including material plastic hardening, strain rate effect, and damage softening effect includes: A model combining isotropic hardening and kinematic hardening is used to describe the plastic hardening behavior of materials, and the yield surface equation and hardening rule are defined. A dynamic yield stress increment term related to the equivalent plastic strain rate is introduced into the yield surface equation to characterize the strain rate effect of the material. A damage evolution equation based on equivalent plastic strain and stress triaxiality is defined to describe the nucleation, growth and aggregation process of micro-defects inside the material; In the constitutive model framework, damage variables are coupled into the expressions for elastic modulus and yield stress to characterize the softening effect of damage on material stiffness and load-bearing capacity. By coupling the plastic flow rule, hardening rule, strain rate effect term, and damage evolution equation, a unified nonlinear constitutive model framework is formed that can describe the entire process of material from elasticity and plasticity to damage and failure.

[0011] As a further aspect of the present invention, the step of identifying the stress concentration region of the tested railing handrail based on the internal stress distribution time history calculated by inversion, and calculating the stress peak value and stress cycle number of the stress concentration region, includes: In the internal stress distribution time history obtained from the inversion solution, the equivalent stress time history curve of each calculation unit during the entire impact process is extracted; Scan the equivalent stress time history curves of all calculation units, identify the calculation units whose stress peak exceeds the preset proportional threshold of the material yield stress during the entire impact process, and mark the region formed by the calculation units as a potential stress concentration region. For each potential stress concentration region, spatial clustering analysis is performed to group spatially adjacent computational units with similar stress time history characteristics into the same stress concentration region. For each identified stress concentration region, the envelope of the equivalent stress time history curves of all calculation units within the corresponding stress concentration region is extracted, and the maximum value of the envelope is taken as the stress peak value of the corresponding stress concentration region. Analyze the equivalent stress time history curve of each stress concentration region, and count the number of times the stress value forms a complete fluctuation from low to high and then back to low. This number is taken as the stress cycle number of the corresponding stress concentration region.

[0012] As a further aspect of the present invention, the degree of residual structural deformation of the tested railing handrail is evaluated based on the amount of local plastic deformation, including: From the inversion solution results, extract the equivalent plastic strain values ​​of each calculation unit of the tested railing handrail structure after the impact. The equivalent plastic strain value of each calculation unit is compared with its corresponding elastic strain threshold. Calculation units whose equivalent plastic strain value exceeds the elastic strain threshold are determined to be units that have undergone plastic deformation. For all elements that undergo plastic deformation, they are classified according to the magnitude of their equivalent plastic strain values, and divided into a slight plastic deformation zone, a moderate plastic deformation zone, and a severe plastic deformation zone. Calculate the proportion of the total number of units that undergo plastic deformation to the total number of units in the entire tested railing handrail structure, and use this as an indicator of the overall plastic deformation range. Calculate the average and maximum values ​​of the equivalent plastic strain values ​​of all plastic deformation elements, and use them as the average plastic deformation degree index and the maximum plastic deformation degree index, respectively. The residual deformation of the structure is quantitatively evaluated by combining the overall plastic deformation range index, the average plastic deformation degree index, and the maximum plastic deformation degree index.

[0013] As a further aspect of the present invention, the impact resistance level of the tested railing handrail is quantitatively evaluated by combining the stress peak value, stress cycle number, and residual deformation degree of the stress concentration area, including: An impact resistance performance evaluation index system is established, which includes a peak stress score item, a stress cycle count score item, an overall plastic deformation range score item, an average plastic deformation degree score item, and a maximum plastic deformation degree score item. Multiple level thresholds are set for each scoring item. The calculated peak stress, number of stress cycles, overall plastic deformation range index, average plastic deformation degree index, and maximum plastic deformation degree index are compared with the level thresholds of the corresponding scoring items to determine the score of each scoring item. Based on the importance of different scoring items to the safety performance of the railings and handrails, a corresponding weight coefficient is assigned to each scoring item; A weighted summation method is used to combine the scores of all evaluation items to calculate a comprehensive impact resistance performance score; A pre-defined correspondence between comprehensive impact resistance performance score and performance level is established. Based on the calculated comprehensive impact resistance performance score, the correspondence is queried to determine the impact resistance performance level of the tested railing handrail.

[0014] As a further aspect of the present invention, the method further includes a non-destructive assessment step of structural integrity after impact: After completing the assessment of the impact resistance performance level, an ultrasonic flaw detector is used to scan and detect the stress concentration area and plastic deformation area of ​​the tested railing handrail. Receive and analyze the echo signal returned by the ultrasonic flaw detector to identify whether there are abnormal reflected waves or abnormal attenuation areas in the signal; Then, by combining the stress peak history corresponding to the identified stress concentration area and the deformation degree corresponding to the plastic deformation area, it is determined whether the abnormal reflected wave or attenuation abnormal area corresponds to the micro-crack or internal damage of the railing handrail. The location, size, and nature of potential internal damage detected by ultrasonic testing will be supplemented in the impact resistance performance evaluation report of the tested railing handrail as additional reference information for performance level evaluation.

[0015] As a further aspect of the present invention, the present invention also includes a railing handrail impact resistance performance testing system, the system including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, it implements the steps of the railing handrail impact resistance performance testing method described above.

[0016] Compared with the prior art, the advantages and positive effects of the present invention are as follows: The controllable electromagnetic launch device enables precise, controlled launch of standard test impactors, stabilizing and unifying impact energy, impact position, and impact attitude parameters. Multi-view high-speed cameras synchronously acquire transient deformation image sequences, providing a complete record of the instantaneous deformation state of the entire railing structure. Image enhancement and feature point calibration eliminate noise interference during acquisition, accurately obtaining the spatial coordinates of structural feature points in the temporal dimension. By analyzing the temporal variation patterns of these coordinates, a continuous and complete dynamic displacement and strain field is constructed, enabling refined extraction and normalization of transient structural deformation data during impact.

[0017] The elastoplastic dynamics inversion algorithm relies on dynamic displacement and strain fields to perform inverse calculations, enabling the deduction of the internal mechanical response state of a structure from macroscopic deformation data. It calculates the continuous temporal distribution characteristics of internal stress and local plastic deformation in the impact contact area. Based on the calculation results, it locates stress concentration areas, quantifies the stress peak and stress cycle number, and characterizes the degree of residual deformation after stress through local plastic deformation, achieving simultaneous analysis of internal mechanical parameters and structural deformation parameters.

[0018] By integrating multiple parameters such as peak stress, stress cycle count, and residual structural deformation, the evaluation criteria can be established, mitigating the bias caused by single-index judgments and eliminating subjective evaluation biases. A complete testing process is established, from controlled impact launch, multi-view image acquisition, deformation field solution to dynamic inversion and multi-index level evaluation. Unified testing execution standards and quantitative evaluation rules are implemented, improving the standardized operating system for railing handrail impact resistance testing and adapting to the application needs of batch engineering testing and compliance assessment. Attached Figure Description

[0019] Figure 1This is a state diagram of a method for testing the impact resistance of a railing handrail according to the present invention. Figure 2 A flowchart for extracting the spatiotemporal location of structural feature points; Figure 3 This is a flowchart for calculating the dynamic displacement field and dynamic strain field. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0021] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0022] See Figure 1 This invention provides a method for testing the impact resistance of railings, the overall implementation of which is as follows: At a predetermined impact point on the tested handrail, a standard test impactor is launched using a controllable electromagnetic launcher to simulate an impact event. During this process, multiple calibrated high-speed cameras are deployed to simultaneously capture the transient deformation process of the handrail under impact load from multiple different perspectives, resulting in a sequence of high-speed images from multiple viewpoints. Image enhancement and feature point calibration are performed on the acquired transient deformation image sequence to accurately extract the spatial three-dimensional coordinates of the surface structural feature points of the handrail at different times. Based on the changes in these structural feature point coordinates over time, the dynamic displacement field distribution and dynamic strain field distribution of the entire handrail structure during the impact process are calculated. The calculated dynamic displacement field and dynamic strain field data are used as known input conditions and imported into a pre-defined elastoplastic dynamics inversion algorithm for solution. This algorithm can invert and calculate the stress distribution over time within the impact contact area of ​​the tested handrail, as well as the magnitude of the local plastic deformation caused by the impact, from the observed deformation field data. Based on the inverted internal stress distribution time history, stress concentration regions in the structure can be identified, and the peak stress in these regions and the number of stress cycles experienced during the impact event can be calculated. Simultaneously, based on the inverted local plastic deformation, the degree of residual deformation of the tested railing handrail can be assessed. By combining multiple quantitative indicators such as the peak stress in the stress concentration regions, the number of stress cycles, and the degree of residual deformation, the impact resistance performance level of the tested railing handrail can be quantitatively evaluated.

[0023] In one embodiment of the present invention, see [reference] Figure 2 Adaptive histogram equalization is applied to each frame of the transient deformation image sequence to enhance the contrast between the edge contours and surface texture details of the tested railing handrail. In the enhanced images, an accelerated segmentation test feature detection operator is used to automatically identify and locate pre-pasted physical markers on the railing handrail, as well as the inherent corner and edge features of the structure itself, using these points as candidate structural feature points. Mismatches are eliminated from the automatically identified candidate structural feature points. This process involves cross-frame tracking and consistency verification based on the neighborhood texture descriptors of the feature points, filtering out a set of feature points that consistently appear across multiple consecutive frames. Using the principle of binocular vision measurement, based on the pre-calibrated intrinsic and extrinsic parameters of the high-speed camera, successfully matched feature point pairs from images simultaneously acquired by multiple high-speed cameras are reconstructed in 3D to obtain the 3D spatial coordinates of each tracked structural feature point relative to the world coordinate system at each moment. Finally, the 3D spatial coordinates of all structural feature points at all moments are organized chronologically and by feature point number to form a complete spatiotemporal location dataset of structural feature points.

[0024] In the specific implementation, for a section of metal tubular railing installed on an outdoor platform, high-contrast circular reflective markers are pre-attached to its surface as physical markers. A controllable electromagnetic launcher then launches a standard test impactor to the pre-set impact point on the railing post. In this implementation, multiple high-speed cameras, precisely calibrated, simultaneously capture the impact process from different perspectives at a frame rate of 10,000 frames per second, generating a sequence of transient deformation images of the tested railing under impact load. In some embodiments, adaptive histogram equalization is applied to each frame of the transient deformation image sequence to enhance the contrast between the fine textures formed by the paint on the metal surface of the tested railing, the edges of welded joints, and the pre-attached reflective markers and the background environment, making the structural outline and feature details clearer. In some embodiments, in the enhanced image, an accelerated segmentation test feature detection operator is used to automatically identify and locate pre-set circular reflective physical markers on the tested railing handrail, while simultaneously identifying the corners and edge features of the structure itself, such as the corners of pipe joints and the start and end points of welds. All identified points are used as candidate structural feature points. In a specific implementation, the automatically identified candidate structural feature points are erroneously eliminated, and cross-frame tracking and consistency verification are performed based on the neighborhood texture descriptors of the feature points. For example, the neighborhood texture descriptor of a reflective marker at a specific location on the railing handrail surface should maintain a stable match in a continuous sequence of transient deformed image frames. A set of feature points that can stably appear in multiple consecutive frames is selected, and false feature points caused by motion blur or sudden changes in illumination are eliminated.

[0025] It is understandable that, utilizing the principle of binocular vision measurement, and based on the endo- and extrinsic parameters of the calibrated high-speed camera, 3D reconstruction is performed on successfully matched feature point pairs from multi-view images synchronously acquired by the high-speed camera. For example, in a specific implementation, for a particular reflective marker point, its 2D pixel coordinates in images from different high-speed cameras are precisely matched, and its 3D spatial coordinates in the world coordinate system are calculated using the following relationship:

[0026] Where: symbol Represents the pixel coordinates of a feature point in an image from a high-speed camera, using the symbol... Represents a non-zero scaling factor, symbol The intrinsic parameter matrix of a high-speed camera device is represented by the symbol. The external parameter matrix of a high-speed camera device is represented by the symbol. This represents the three-dimensional spatial coordinates of the feature points in the world coordinate system. Optionally, the optimal solution for the three-dimensional spatial coordinates of each structural feature point relative to the world coordinate system at each moment can be obtained using the least squares adjustment method based on observation data from multiple high-speed cameras. In specific implementation, the three-dimensional spatial coordinates of all structural feature points at all moments are organized according to time order and feature point number to form a spatiotemporal location dataset of structural feature points. This dataset records the spatial trajectory of each physical marker point and natural feature point throughout the entire dynamic process from before to after the impact. It can be understood that the spatiotemporal location dataset of structural feature points is the direct input for subsequent calculations of the dynamic displacement field and dynamic strain field, and its accuracy directly depends on the accuracy of image enhancement, feature point matching, and 3D reconstruction. Optionally, during the 3D reconstruction process, bundle adjustment can be used to further optimize the extrinsic parameters of all high-speed cameras and the 3D coordinates of feature points to minimize reprojection errors, thereby improving the overall accuracy and consistency of the spatiotemporal location dataset of structural feature points.

[0027] In one embodiment of the present invention, see [reference] Figure 3 Using the initial moment before the impact as a reference, the three-dimensional displacement vector of each structural feature point relative to its initial position is calculated at every subsequent moment. A two-dimensional parametric surface mesh is established on the surface of the tested railing structure. The calculated three-dimensional displacement vectors of all structural feature points are mapped to each node of this two-dimensional parametric surface mesh using a spatial interpolation method, thereby generating a three-dimensional dynamic displacement field covering the entire structural surface. Based on the generated three-dimensional dynamic displacement field, the displacement gradient of each element in the two-dimensional parametric surface mesh in three directions is calculated. According to the geometric relationship between strain and displacement gradient in continuum mechanics, the strain tensor at the center of the corresponding element is calculated from the displacement gradient of each element in the two-dimensional parametric surface mesh. The strain tensors at the centers of all elements are integrated to form a dynamic strain field covering the surface of the tested railing structure. This dynamic strain field contains the time-varying data of the normal strain component and the shear strain component.

[0028] In specific implementations, based on the spatiotemporal position dataset of structural feature points obtained from Example 1, the dynamic displacement field and dynamic strain field of the tested railing handrail during the impact process are calculated. An example of the tested railing handrail is a metal railing post with a curved section. In specific implementations, using the initial moment before the standard test impactor contacts the tested railing handrail as a reference, the three-dimensional displacement vector of each structural feature point recorded in the spatiotemporal position dataset is calculated at each subsequent moment relative to its own three-dimensional spatial coordinates recorded at the initial moment. Each three-dimensional displacement vector represents the spatial movement of the corresponding structural feature point from its initial position to its current position. In some embodiments, a two-dimensional parametric surface mesh is established on the surface of the tested railing handrail structure. The two-dimensional parametric surface mesh consists of interconnected triangular or quadrilateral units, and its nodes cover the entire surface area of ​​the tested railing handrail structure. For example, for a complex-shaped metal casting railing post head, the two-dimensional parametric surface mesh is precisely fitted to its three-dimensional scanned model surface. In some embodiments, the three-dimensional displacement vector of each structural feature point is mapped to each node of the two-dimensional parametric surface mesh through a spatial interpolation method. For structural feature points located inside the mesh cell rather than on the node, their three-dimensional displacement vectors are interpolated and assigned to the cell node through the shape function of the cell, thereby generating a three-dimensional dynamic displacement field covering the entire surface of the tested railing handrail structure. The three-dimensional dynamic displacement field is a three-dimensional vector field defined on all nodes of the two-dimensional parametric surface mesh that changes with time.

[0029] It is understandable that, based on the generated three-dimensional dynamic displacement field, the displacement gradient of each element in the two-dimensional parametric surface mesh is calculated. The displacement gradient describes the rate of change of displacement in the local coordinate system of the element. In a specific implementation, for a quadrilateral element, the displacement components at any point inside it... In the local coordinates of the unit The rate of change in direction can be approximated by the central difference:

[0030] Where: symbol Represents displacement components exist Gradient components in the direction, sign and They represent along Displacement components of two adjacent nodes in the direction value, symbol This indicates that these two adjacent nodes are in The distance in the direction. Similarly, the displacement components can be calculated in... The direction and gradients between different displacement components are used to obtain the complete displacement gradient tensor for each element. Optionally, for curved mesh elements, when calculating the actual displacement gradient in three-dimensional space, the Jacobian transformation matrix from the element's local parametric coordinates to the three-dimensional world coordinates needs to be considered. In practice, based on the geometric relationship between strain and displacement gradient in continuum mechanics, the strain tensor at the corresponding element center is calculated from the displacement gradient tensor of each element in the two-dimensional parametric curved mesh. The strain tensor includes normal strain components and shear strain components, describing the deformation state at the point. Integrating the strain tensors calculated from all element centers forms a dynamic strain field covering the surface of the tested railing structure. The dynamic strain field is a time-varying tensor field defined on all elements of the two-dimensional parametric curved mesh, completely recording the changes in normal strain components and shear strain components at each point on the structural surface during the impact process. It can be understood that the accuracy of the dynamic strain field depends on the spatial resolution of the three-dimensional dynamic displacement field and the density of the two-dimensional parametric curved mesh. In practice, the mesh density needs to be high enough to capture the strain gradient changes in stress concentration areas. Optionally, to ensure computational stability, the three-dimensional dynamic displacement field data can be appropriately spatially smoothed and filtered before calculating the displacement gradient to suppress the amplification effect of measurement noise in differential operations.

[0031] In one embodiment of the present invention, the elastoplastic dynamics inversion algorithm first establishes a unified nonlinear constitutive model framework that includes material plastic hardening, strain rate effects, and damage softening effects during operation. This framework employs a combination of isotropic hardening and kinematic hardening to describe the plastic hardening behavior of the material, explicitly defining the yield surface equation and hardening rule. A dynamic yield stress increment term related to the equivalent plastic strain rate is introduced into the yield surface equation to characterize the strain rate effect of the material. Simultaneously, a damage evolution equation based on the equivalent plastic strain and stress triaxiality is defined to describe the nucleation, growth, and aggregation processes of micro-defects within the material. Within this constitutive model framework, damage variables are coupled into the expressions for elastic modulus and yield stress, realizing the softening effect of damage on the material's stiffness and load-bearing capacity. Finally, the plastic flow rule, hardening rule, strain rate effect term, and damage evolution equation are coupled to form a unified nonlinear constitutive model framework that can describe the entire process of material failure from elasticity and plasticity. The algorithm uses the dynamic displacement field and dynamic strain field as known boundary conditions and observation data. Within this unified nonlinear constitutive model framework, internal variables characterizing the internal stress state and material damage state of the tested railing handrail are defined. An inversion optimization problem is constructed with the objective of minimizing the differences between the calculated and observed dynamic displacement and strain fields. During the iterative process of solving the inversion optimization problem, the adjoint state method is used to efficiently calculate the gradient of the objective function with respect to the internal variables to guide the iteration direction. A regularization term based on physical information is introduced to constrain the physical rationality of the inversion solution and prevent non-physical solutions caused by noise in the observed data. The solution is iteratively solved until the preset convergence conditions are met, ultimately outputting the internal stress distribution time history, local plastic deformation, and the implicit material damage evolution process that best match the observed data.

[0032] In practical implementation, the elastoplastic dynamics inversion algorithm works based on a pre-established unified nonlinear constitutive model framework. This framework aims to describe the complex mechanical response of the tested railing material under impact load. The elastoplastic dynamics inversion algorithm uses the dynamic displacement and strain fields obtained from Example 2 as known boundary conditions and observation data inputs. The unified nonlinear constitutive model framework includes descriptions of the material's plastic hardening behavior, strain rate effect, and damage softening effect. In practical implementation, when establishing the unified nonlinear constitutive model framework, a model combining isotropic hardening and kinematic hardening is used to describe the material's plastic hardening behavior. The model explicitly defines the yield surface equation and hardening rule. In some embodiments, the yield surface equation adopts the von Mises yield criterion, whose expression includes a back stress tensor to describe kinematic hardening and a yield radius variable to describe isotropic hardening. In some embodiments, a dynamic yield stress increment term related to the equivalent plastic strain rate is introduced into the yield surface equation to characterize the material's strain rate effect; for example, a term similar to the Cowper-Symonds model is used to dynamically increase the yield stress. In practical implementation, a damage evolution equation based on equivalent plastic strain and stress triaxiality is defined to describe the nucleation, growth, and aggregation processes of micro-defects within the material. Stress triaxiality reflects the influence of stress state on damage development. Within the unified nonlinear constitutive model framework, damage variables are coupled into the expressions for elastic modulus and yield stress, characterizing the softening effect of damage on material stiffness and load-bearing capacity. As damage variables accumulate, the effective elastic modulus and yield stress of the material decrease. The elastoplastic dynamics inversion algorithm couples the plastic flow rule, hardening rule, strain rate effect term, and damage evolution equation to form a unified nonlinear constitutive model framework that can describe the entire process of material failure from elasticity and plasticity. It can be understood that the unified nonlinear constitutive model framework contains a series of material parameters, which need to be identified through the inversion process or have been calibrated through independent material experiments. Table 1 shows a list of material model parameters.

[0033] Table 1: Key Parameters of the Unified Nonlinear Constitutive Model

[0034] In practical implementation, an example of defining the damage evolution equation is as follows:

[0035] Where: symbol Indicating damage variables The derivative with respect to time, sign The damage strain energy release rate associated with the current stress state and damage is represented by the symbol. The critical damage energy parameter related to the damage toughness of a material is represented by the symbol. This represents the equivalent plastic strain rate. Within the framework of a unified nonlinear constitutive model, the elastoplastic dynamics inversion algorithm defines internal variables characterizing the internal stress state and material damage state of the tested railing handrail. These internal variables include, but are not limited to, the back stress tensor, equivalent plastic strain, and damage variables. The elastoplastic dynamics inversion algorithm constructs an inversion optimization problem with the objective of minimizing the differences between the calculated and observed dynamic displacement and strain fields. The objective function is typically constructed using a least-squares approach. During the iterative process of solving the inversion optimization problem, the elastoplastic dynamics inversion algorithm uses the adjoint state method to efficiently calculate the gradient of the objective function with respect to the internal variables. The adjoint state method obtains gradient information by solving an adjoint equation, guiding the iteration direction and accelerating convergence. The elastoplastic dynamics inversion algorithm introduces a physical information-based regularization term. This regularization term constrains the physical rationality of the inversion solution, such as constraining the smoothness of the stress field or the monotonically non-decreasing nature of the damage variables, preventing non-physical solutions from arising due to noise in the observed data. The elastoplastic dynamics inversion algorithm iteratively solves the problem until a preset convergence condition is met. This convergence condition can be that the change in the objective function value is less than a threshold or the number of iterations reaches an upper limit. The final output is the internal stress distribution time history, local plastic deformation, and the implicit material damage evolution process that best match the observed data. Optionally, during the inversion process, only some key unknown internal variables (such as the initial yield stress or damage parameters in local areas) can be inverted, while other material parameters use preset typical values. It can be understood that the computational domain of the elastoplastic dynamics inversion algorithm typically focuses on the impact contact area and its adjacent potentially high-deformation zone, rather than the entire tested railing structure, to reduce the computational scale. Optionally, during the iterative solution process, optimization algorithms such as the quasi-Newton method or the conjugate gradient method can be used to update the internal variables to minimize the objective function.

[0036] In one embodiment of the present invention, the equivalent stress time history curve of each computational unit during the entire impact process is extracted from the inverted internal stress distribution time history. The equivalent stress time history curves of all computational units are scanned to identify those whose stress peak exceeds a preset threshold of the material's yield stress during the entire impact process. The regions formed by these computational units are marked as potential stress concentration regions. For each potential stress concentration region, spatial clustering analysis is performed to group spatially adjacent computational units with similar stress time history characteristics into the same stress concentration region. For each identified stress concentration region, the envelope of the equivalent stress time history curves of all computational units within that region is extracted, and the maximum value of this envelope is taken as the stress peak value of that stress concentration region. The equivalent stress time history curve of each stress concentration region is analyzed, and the number of times the stress value forms a complete fluctuation from low to high and then decreases is counted. This number is taken as the stress cycle number of that stress concentration region.

[0037] In specific implementations, based on the internal stress distribution time history output from the elastoplastic dynamics inversion algorithm, the stress concentration regions of the tested railing handrail are identified, and the stress peak value and stress cycle number of the corresponding regions are calculated. The internal stress distribution time history includes the data on the change of stress tensor over time for each calculation unit of the tested railing handrail structure during the impact process. In specific implementations, the equivalent stress time history curve of each calculation unit over the entire impact process is extracted from the inverted internal stress distribution time history. The equivalent stress is calculated using the Mises equivalent stress formula to comprehensively reflect the intensity of the complex stress state at the unit point. In some embodiments, the equivalent stress time history curves of all calculation units are scanned to identify calculation units whose stress peak value exceeds a preset proportional threshold of the material's yield stress during the entire impact process. For example, the preset proportional threshold is set to 80% of the material's yield stress. The continuous spatial region formed by calculation units whose stress peak value exceeds this threshold is marked as a potential stress concentration region. In some embodiments, spatial clustering analysis is performed on each potential stress concentration region. The spatial clustering analysis is based on the spatial adjacency relationship of the computational units and the morphological similarity of the equivalent stress time history curves. Spatially adjacent computational units with similar stress time history characteristics are grouped into the same stress concentration region. The similarity of characteristics can be evaluated by comparing the peak value, fluctuation mode, or dominant frequency component of the time history curves.

[0038] It is understandable that, for each identified stress concentration region, the envelope of the equivalent stress time history curves of all calculation units within that region is extracted. This envelope is formed by connecting the maximum equivalent stress values ​​of all units at each moment, and the maximum value of the envelope is taken as the stress peak value of the corresponding stress concentration region. In practice, the equivalent stress time history curve of each stress concentration region is analyzed, and the number of times the stress value forms a complete fluctuation from low to high and back to low is counted. This number is taken as the stress cycle number of the corresponding stress concentration region. A complete fluctuation is defined as the process of the stress value rising from a local minimum to the next local maximum and then falling back to the next local minimum. For example, for a region that experiences damped vibration after impact, its equivalent stress time history curve may exhibit multiple continuous damped fluctuations. Refer to Table 2, which shows a summary of the calculation results for the main stress concentration regions identified after impact analysis of a railing post.

[0039] Table 2: Results of Stress Concentration Region Identification and Feature Calculation

[0040] In practical implementation, the peak stress can be calculated more accurately by smoothing the envelope and detecting the peak value, while the number of stress cycles can be counted using the rainflow counting method or a simple cross-flow counting method. Calculate the equivalent stress of the calculation unit. The formula is as follows:

[0041] Where: symbol Represents the Mises equivalent force, symbol , , These represent the three normal stress components of the current stress tensor at the computational unit, with symbols... , , These represent the three shear stress components of the current stress tensor for the calculated element. Optionally, when identifying potential stress concentration regions, in addition to using the stress peak threshold, the magnitude of the stress gradient can also be considered to include elements with stress gradients exceeding a certain threshold in the potential region, thus more comprehensively identifying areas of drastic stress changes. It can be understood that accurate identification of stress concentration regions provides a direct basis for subsequent assessment of the potential fatigue damage risk of the structure under cyclic stress. Optionally, for each identified stress concentration region, in addition to calculating the stress peak and the number of cycles, its average stress, stress amplitude, and other derived parameters can also be calculated for more in-depth fatigue analysis.

[0042] In one embodiment of the present invention, the equivalent plastic strain values ​​of each calculation unit of the tested railing handrail structure after the impact are extracted from the inversion solution results. The equivalent plastic strain value of each calculation unit is compared with its corresponding elastic strain threshold, and calculation units whose equivalent plastic strain values ​​exceed the elastic strain threshold are determined to have undergone plastic deformation. All units that have undergone plastic deformation are classified into slight plastic deformation, moderate plastic deformation, and severe plastic deformation zones based on the magnitude of their equivalent plastic strain values. The proportion of the total number of units undergoing plastic deformation to the total number of units in the entire tested railing handrail structure is calculated; this proportion serves as an indicator of the overall plastic deformation range. The average and maximum values ​​of the equivalent plastic strain values ​​of all plastic deformation units are calculated and used as the average plastic deformation degree indicator and the maximum plastic deformation degree indicator, respectively. By combining the overall plastic deformation range indicator, the average plastic deformation degree indicator, and the maximum plastic deformation degree indicator, a quantitative assessment of the residual deformation degree of the structure is completed. Next, an impact resistance performance evaluation index system was established, which includes peak stress score, stress cycle count score, overall plastic deformation range score, average plastic deformation degree score, and maximum plastic deformation degree score. Multiple level thresholds were set for each score item. The calculated peak stress, stress cycle count, overall plastic deformation range index, average plastic deformation degree index, and maximum plastic deformation degree index were compared with the corresponding level thresholds to determine the score for each score item. Based on the importance of different score items to the safety performance of the railing handrail, corresponding weight coefficients were assigned to each score item. A weighted summation method was used to combine the scores of all score items to calculate a comprehensive impact resistance performance score. Based on the established correspondence between the comprehensive impact resistance performance score and performance level, this correspondence was looked up according to the calculated comprehensive impact resistance performance score to finally determine the impact resistance performance level of the tested railing handrail. After completing the impact resistance performance level assessment, an ultrasonic flaw detector was used to scan and inspect the stress concentration areas and plastic deformation areas of the tested railing handrail. The ultrasonic flaw detector receives and analyzes the echo signals returned by the ultrasonic flaw detector to identify areas with abnormal reflected waves or abnormal signal attenuation. Combining the stress peak history experienced by identified stress concentration areas and the deformation degree corresponding to plastic deformation areas, it is determined whether the abnormal reflected waves or areas with abnormal attenuation detected by ultrasonic testing correspond to potential microcracks or other internal damage within the railing. The location, size, and nature of potential internal damage detected by ultrasonic testing are supplemented into the impact resistance performance evaluation report of the tested railing as additional reference information for performance level assessment.

[0043] In practice, based on the results calculated by the elastoplastic dynamics inversion algorithm, the degree of residual deformation of the tested railing handrail structure is evaluated. The local plastic deformation output by the elastoplastic dynamics inversion algorithm is given in the form of an equivalent plastic strain field. From the results of the elastoplastic dynamics inversion algorithm, the equivalent plastic strain values ​​of each calculation unit of the tested railing handrail structure after the impact are extracted. The equivalent plastic strain value of each calculation unit characterizes the degree of irreversible plastic deformation experienced by the material of that unit. In practice, the equivalent plastic strain value of each calculation unit is compared with its corresponding elastic strain threshold. The elastic strain threshold is calculated from the yield stress and elastic modulus of the material. Calculation units whose equivalent plastic strain values ​​exceed the elastic strain threshold are determined to be units that have undergone plastic deformation. For all elements exhibiting plastic deformation, they are classified according to the magnitude of their equivalent plastic strain values. For example, two classification thresholds are set: elements with equivalent plastic strain values ​​between the elastic strain threshold and the first classification threshold are classified as slightly deformed; elements with equivalent plastic strain values ​​between the first and second classification thresholds are classified as moderately deformed; and elements with equivalent plastic strain values ​​exceeding the second classification threshold are classified as severely deformed. The proportion of elements exhibiting plastic deformation to the total number of elements in the entire tested railing structure is calculated; this proportion serves as an indicator of the overall plastic deformation range. The average and maximum values ​​of the equivalent plastic strain values ​​of all plastically deformed elements are calculated, serving as the average plastic deformation degree indicator and the maximum plastic deformation degree indicator, respectively. By combining the overall plastic deformation range indicator, the average plastic deformation degree indicator, and the maximum plastic deformation degree indicator, a quantitative assessment of the residual deformation degree of the structure is completed. In some embodiments, the equivalent plastic strain value is evaluated. The formula is in the following cumulative form:

[0044] Where: symbol Represents the equivalent plastic strain value of the calculation element, with the symbol... The equivalent plastic strain rate of the calculation unit is represented, and integration is performed over the entire impact process. In some embodiments, an impact resistance performance evaluation index system is established, which includes a peak stress score, a stress cycle count score, an overall plastic deformation range score, an average plastic deformation degree score, and a maximum plastic deformation degree score. Multiple threshold levels are set for each score item. For example, the peak stress score is divided into four levels: excellent, good, acceptable, and unacceptable, and a corresponding peak stress value range is set for each level. The calculated peak stress, stress cycle count, overall plastic deformation range index, average plastic deformation degree index, and maximum plastic deformation degree index are compared with the corresponding threshold levels to determine the score for each score item. Based on the importance of different score items to the safety performance of the railing, corresponding weight coefficients are assigned to each score item; for example, the peak stress score and the maximum plastic deformation degree score may be given higher weights. A weighted summation method is used to combine the scores of all score items to calculate a comprehensive impact resistance performance score. A pre-defined correspondence between comprehensive impact resistance performance scores and performance levels is established. For example, a comprehensive impact resistance performance score of 90 or above corresponds to Level A (Excellent). Based on the calculated comprehensive impact resistance performance score, the correspondence between the comprehensive impact resistance performance score and performance level is queried to determine the impact resistance performance level of the tested railing handrail. It is understandable that the performance level classification can be adjusted according to specific safety standards or specifications.

[0045] After completing the impact resistance rating assessment, an ultrasonic flaw detector is used to scan and inspect the stress concentration areas and plastic deformation areas of the tested railing handrail. The echo signals returned by the ultrasonic flaw detector are received and analyzed to identify any abnormal reflected waves or areas of abnormal attenuation. Abnormal reflected waves may indicate the presence of discontinuous interfaces within the material. Combining the stress peak history corresponding to the identified stress concentration areas and the deformation degree corresponding to the plastic deformation areas, it is determined whether the abnormal reflected waves or areas of abnormal attenuation detected by ultrasonic testing correspond to micro-cracks or internal damage in the railing handrail. The presence of abnormal ultrasonic signals in areas with high stress histories and significant plastic deformation increases the likelihood of internal damage. The location, size, and nature of potential internal damage detected by ultrasonic testing are supplemented into the impact resistance rating report of the tested railing handrail as additional reference information for the performance rating. Optionally, ultrasonic testing can use multi-frequency probes to scan and assess potential defects of different depths and sizes. Understandably, ultrasonic testing provides a direct inspection of the internal integrity of the tested railing, complementing and validating the performance evaluation results based on mechanical inversion and deformation analysis. Optionally, for areas where definite cracks or severe damage are found during ultrasonic testing, regardless of their previous mechanical performance rating, it may be necessary to downgrade the final impact resistance rating or issue safety warning markings.

[0046] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for testing the impact resistance of railings and handrails, characterized in that, The method includes: At the preset impact point of the railing under test, a standard test impactor is launched by a controllable electromagnetic launcher, and at the same time, a high-speed camera is used to synchronously acquire a sequence of transient deformation images of the railing under test under impact from multiple perspectives. The acquired transient deformation image sequence is subjected to image enhancement and feature point calibration processing to extract the spatial coordinates of the structural feature points of the tested railing handrail at different times; Based on the spatial coordinate changes of the structural feature points, the dynamic displacement field and dynamic strain field of the tested railing handrail during the impact process are calculated. The dynamic displacement field and dynamic strain field are input into the elastoplastic dynamics inversion algorithm. Using the elastoplastic dynamics inversion algorithm, the internal stress distribution time history and local plastic deformation of the tested railing handrail in the impact contact area are inverted and calculated from the dynamic displacement field and dynamic strain field. Based on the internal stress distribution time history calculated by inversion, the stress concentration area of ​​the tested railing handrail is identified, and the stress peak value and stress cycle number of the stress concentration area are calculated. Based on the local plastic deformation, the degree of residual structural deformation of the tested railing handrail is evaluated; By combining the peak stress, the number of stress cycles, and the degree of residual deformation in the stress concentration area, the impact resistance level of the tested railing handrail is quantitatively evaluated.

2. The method for testing the impact resistance of a railing handrail according to claim 1, characterized in that, The process of image enhancement and feature point calibration of the acquired transient deformation image sequence, and extracting the spatial coordinates of the structural feature points of the tested railing handrail at different times, includes: Adaptive histogram equalization is applied to each frame of the transient deformable image sequence to enhance the contrast between the edge and surface texture of the tested railing handrail in the image; In the enhanced image, the accelerated segmentation test feature detection operator is used to automatically identify and locate the pre-set physical marker points on the handrail of the tested railing, as well as the corner points and edge features of the structure itself, as candidate structural feature points; The candidate structural feature points that are automatically identified are eliminated due to mismatches. Cross-frame tracking and consistency verification are performed based on the neighborhood texture descriptor of the feature points to filter out the set of feature points that appear stably in consecutive multi-frame images. Using the principle of binocular vision measurement, based on the calibrated internal and external parameters of the high-speed camera device, the successfully matched feature point pairs in the multi-view images synchronously acquired by the high-speed camera device are reconstructed in three dimensions to obtain the three-dimensional spatial position coordinates of each structural feature point relative to the world coordinate system at each moment. The three-dimensional spatial coordinates of all structural feature points at all times are organized in chronological order and by feature point number to form a spatiotemporal location dataset of structural feature points.

3. The method for testing the impact resistance of a railing handrail according to claim 1, characterized in that, Based on the spatial coordinate changes of the structural feature points, the dynamic displacement field and dynamic strain field of the tested railing handrail during the impact process are calculated, including: Taking the initial moment before the impact as a reference, calculate the three-dimensional displacement vector of each of the structural feature points relative to its initial position at each subsequent moment; A two-dimensional parametric surface mesh is established on the surface of the tested railing handrail structure. The calculated three-dimensional displacement vectors of all structural feature points are interpolated and mapped to each node of the two-dimensional parametric surface mesh to generate a three-dimensional dynamic displacement field of the entire structural surface. Based on the three-dimensional dynamic displacement field, the displacement gradient of each element in the two-dimensional parameterized surface mesh in three directions is calculated; Based on the geometric relationship between strain and displacement gradient in continuum mechanics, the strain tensor at the center of the corresponding element is calculated from the displacement gradient of each element in the two-dimensional parameterized surface mesh. The strain tensors of all unit centers are integrated to form a dynamic strain field covering the surface of the tested railing handrail structure. The dynamic strain field contains data on the changes of normal strain components and shear strain components over time.

4. The method for testing the impact resistance of a railing handrail according to claim 1, characterized in that, The working principle of the elastoplastic dynamics inversion algorithm includes: Establish a unified nonlinear constitutive model framework that includes material plastic hardening, strain rate effect and damage softening effect; The dynamic displacement field and dynamic strain field are used as known boundary conditions and observation data; Within the framework of the unified nonlinear constitutive model, internal variables characterizing the internal stress state and material damage state of the tested railing handrail are defined; Construct an inversion optimization problem with the objective of minimizing the differences between the calculated dynamic displacement field, dynamic strain field and the observed dynamic displacement field, dynamic strain field; In the iterative process of solving the inversion optimization problem, the adjoint state method is used to efficiently calculate the gradient of the objective function with respect to the internal variables, guiding the direction of iteration; A regularization term based on physical information is introduced to constrain the physical rationality of the inversion solution and prevent the inversion results from being non-physical due to noise in the observation data. The solution is iteratively solved until the convergence condition is met, and the final output is the internal stress distribution time history, the local plastic deformation amount, and the implicit material damage evolution process that best match the observation data.

5. The method for testing the impact resistance of a railing handrail according to claim 4, characterized in that, The establishment of a unified nonlinear constitutive model framework that includes material plastic hardening, strain rate effect, and damage softening effect includes: A model combining isotropic hardening and kinematic hardening is used to describe the plastic hardening behavior of materials, and the yield surface equation and hardening rule are defined. A dynamic yield stress increment term related to the equivalent plastic strain rate is introduced into the yield surface equation to characterize the strain rate effect of the material. A damage evolution equation based on equivalent plastic strain and stress triaxiality is defined to describe the nucleation, growth and aggregation process of micro-defects inside the material; In the constitutive model framework, damage variables are coupled into the expressions for elastic modulus and yield stress to characterize the softening effect of damage on material stiffness and load-bearing capacity. By coupling the plastic flow rule, hardening rule, strain rate effect term, and damage evolution equation, a unified nonlinear constitutive model framework is formed that can describe the entire process of material from elasticity and plasticity to damage and failure.

6. The method for testing the impact resistance of a railing handrail according to claim 1, characterized in that, The process of identifying stress concentration areas in the tested railing handrail based on the internal stress distribution time history calculated through inversion, and calculating the stress peak value and stress cycle number of the stress concentration areas, includes: In the internal stress distribution time history obtained from the inversion solution, the equivalent stress time history curve of each calculation unit during the entire impact process is extracted; Scan the equivalent stress time history curves of all calculation units, identify the calculation units whose stress peak exceeds the preset proportional threshold of the material yield stress during the entire impact process, and mark the region formed by the calculation units as a potential stress concentration region. For each potential stress concentration region, spatial clustering analysis is performed to group spatially adjacent computational units with similar stress time history characteristics into the same stress concentration region. For each identified stress concentration region, the envelope of the equivalent stress time history curves of all calculation units within the corresponding stress concentration region is extracted, and the maximum value of the envelope is taken as the stress peak value of the corresponding stress concentration region. Analyze the equivalent stress time history curve of each stress concentration region, and count the number of times the stress value forms a complete fluctuation from low to high and then back to low. This number is taken as the stress cycle number of the corresponding stress concentration region.

7. The method for testing the impact resistance of a railing handrail according to claim 1, characterized in that, Based on the local plastic deformation, the degree of residual structural deformation of the tested railing handrail is evaluated, including: From the inversion solution results, extract the equivalent plastic strain values ​​of each calculation unit of the tested railing handrail structure after the impact. The equivalent plastic strain value of each calculation unit is compared with its corresponding elastic strain threshold. Calculation units whose equivalent plastic strain value exceeds the elastic strain threshold are determined to be units that have undergone plastic deformation. For all elements that undergo plastic deformation, they are classified according to the magnitude of their equivalent plastic strain values, and divided into a slight plastic deformation zone, a moderate plastic deformation zone, and a severe plastic deformation zone. Calculate the proportion of the total number of units that undergo plastic deformation to the total number of units in the entire tested railing handrail structure, and use this as an indicator of the overall plastic deformation range. Calculate the average and maximum values ​​of the equivalent plastic strain values ​​of all plastic deformation elements, and use them as the average plastic deformation degree index and the maximum plastic deformation degree index, respectively. The residual deformation of the structure is quantitatively evaluated by combining the overall plastic deformation range index, the average plastic deformation degree index, and the maximum plastic deformation degree index.

8. The method for testing the impact resistance of a railing handrail according to claim 7, characterized in that, By combining the peak stress, the number of stress cycles, and the degree of residual deformation in the stress concentration area, the impact resistance level of the tested railing handrail is quantitatively evaluated, including: An impact resistance performance evaluation index system is established, which includes a peak stress score item, a stress cycle count score item, an overall plastic deformation range score item, an average plastic deformation degree score item, and a maximum plastic deformation degree score item. Multiple level thresholds are set for each scoring item. The calculated peak stress, number of stress cycles, overall plastic deformation range index, average plastic deformation degree index, and maximum plastic deformation degree index are compared with the level thresholds of the corresponding scoring items to determine the score of each scoring item. Based on the importance of different scoring items to the safety performance of the railings and handrails, a corresponding weight coefficient is assigned to each scoring item; A weighted summation method is used to combine the scores of all evaluation items to calculate a comprehensive impact resistance performance score; A pre-defined correspondence between comprehensive impact resistance performance score and performance level is established. Based on the calculated comprehensive impact resistance performance score, the correspondence is queried to determine the impact resistance performance level of the tested railing handrail.

9. A method for testing the impact resistance of a railing handrail according to claim 1, characterized in that, The method also includes a non-destructive assessment step for structural integrity after impact: After completing the assessment of the impact resistance performance level, an ultrasonic flaw detector is used to scan and detect the stress concentration area and plastic deformation area of ​​the tested railing handrail. Receive and analyze the echo signal returned by the ultrasonic flaw detector to identify whether there are abnormal reflected waves or abnormal attenuation areas in the signal; Then, by combining the stress peak history corresponding to the identified stress concentration area and the deformation degree corresponding to the plastic deformation area, it is determined whether the abnormal reflected wave or attenuation abnormal area corresponds to the micro-crack or internal damage of the railing handrail. The location, size, and nature of potential internal damage detected by ultrasonic testing will be supplemented in the impact resistance performance evaluation report of the tested railing handrail as additional reference information for performance level evaluation.

10. A system for testing the impact resistance performance of a railing handrail, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method for detecting the impact resistance performance of a railing handrail as described in any one of claims 1 to 9.

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