Method and system for testing creep resistance of reinforced solid wood structure

Abstract

The invention discloses a method and a system for testing creep resistance of a reinforced solid wood structure, and belongs to the technical field of mechanical property testing of materials, and the method comprises the following steps: acquiring an environmental parameter combination and a load parameter combination, carrying out multi-field coupling loading on a solid wood sample, generating a loaded sample state, carrying out in-situ optical monitoring, and generating optical monitoring data, carrying out in-situ acoustic monitoring to generate acoustic monitoring data; according to correlation analysis of the optical monitoring data and the acoustic monitoring data, creep prediction parameters are generated, the load parameter combination is dynamically adjusted, a closed-loop test environment is formed, comprehensive analysis is carried out by combining the optical monitoring data and the acoustic monitoring data, and a creep resistance evaluation result is generated. According to the technical scheme, multi-field coupling loading and multi-source in-situ monitoring are combined, a closed-loop test is formed through feedback control, and accurate simulation, deep insight and intelligent evaluation of the solid wood creep process can be achieved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of material mechanical property testing, in particular to a test method and system for the creep resistance of reinforced solid wood structures. BACKGROUND

[0002] Creep is the phenomenon that the strain of a solid material slowly increases with time under the action of constant stress and temperature, and is a key indicator for evaluating the long-term stability of engineering structural materials. For reinforced solid wood structures, as a kind of high polymer composite material, the creep effect is particularly significant when they are subjected to long-term load in an environment with changing temperature and humidity, and is directly related to the safety and service life of the structure. Therefore, developing a precise and reliable test method to evaluate the creep resistance is of great significance for promoting the application of high-performance engineered wood.

[0003] The existing test method for the creep resistance of solid wood samples usually applies a single static load to the sample under constant temperature and humidity conditions, and records the deformation of a specific point over time through contact-type measurement means such as displacement sensors or strain gauges. Some studies have attempted to introduce environmental cycles or dynamic loads, but often consider the influence of a single factor in isolation, lacking simulation of the synergistic effect of multiple physical fields. At the same time, the monitoring means are mostly limited to the measurement of macroscopic deformation, lacking effective detection capability for the accumulation process of micro-damage within the material.

[0004] The traditional test method has obvious limitations. First, the test conditions differ greatly from the actual service environment, and the single-field, single-load loading method cannot truly reflect the creep behavior under the coupling action of environmental and mechanical factors. Second, point-type measurement methods cannot capture the non-uniformity of strain distribution and the localization characteristics of damage, and may miss critical damage initiation information. In addition, the test process is mostly open-loop control, and the loading strategy cannot be adjusted according to the real-time state of the sample. Once the sample enters the accelerated creep stage, it often fails quickly, resulting in missing data for the key damage evolution in the later stage. SUMMARY

[0005] To solve the above problems, the present application provides a test method and system for the creep resistance of reinforced solid wood structures, which combines multi-field coupling loading with multi-source in-situ monitoring, and forms a closed-loop test through feedback control, enabling precise simulation, deep insight, and intelligent evaluation of the creep process of solid wood.

[0006] The above objectives can be achieved by the following scheme: A method and system for testing the creep resistance of a reinforced wood structure, comprising obtaining a combination of environmental parameters and a combination of load parameters defining a test working condition, and based on the combination of environmental parameters and the combination of load parameters, a multi-field coupled loading is performed on a wood sample to generate a loaded sample state; based on the loaded sample state, in-situ optical monitoring is performed to generate optical monitoring data, and in-situ acoustic monitoring is performed to generate acoustic monitoring data; based on the correlation analysis of the optical monitoring data and the acoustic monitoring data, creep prediction parameters are generated; based on the creep prediction parameters, the combination of load parameters is dynamically adjusted to form a closed-loop test environment; based on the closed-loop test environment, the optical monitoring data and the acoustic monitoring data are combined for comprehensive analysis to generate an anti-creep performance evaluation result.

[0007] Optionally, the generating a loaded sample state comprises: based on the combination of environmental parameters, feature extraction is performed to obtain temperature and humidity parameter values, based on the combination of load parameters, feature extraction is performed to obtain axial static sustained load and radial low-frequency alternating load; according to the temperature and humidity parameter values, a pre-set multi-environment factor coupling test box is adjusted to form a steady-state temperature and humidity environment field; based on the steady-state temperature and humidity environment field, the multi-axis servo loading device in the multi-environment factor coupling test box is subjected to the axial static sustained load and the radial low-frequency alternating load to form a loaded sample state. Optionally, the in-situ optical monitoring based on the loaded sample state to generate optical monitoring data and the in-situ acoustic monitoring to generate acoustic monitoring data comprises: based on the loaded sample state, a micro high-resolution optical strain gauge is used to obtain full-field strain distribution data of the surface of the wood sample as optical monitoring data; an ultrasonic emission / receiving array is used to obtain sound velocity variation data and sound attenuation coefficient data inside the wood sample as acoustic monitoring data; the full-field strain distribution data, the sound velocity variation data and the sound attenuation coefficient data are time-stamped and aligned to generate multi-source synchronous monitoring data.

[0008] Optionally, the generating creep prediction parameters comprises: based on the full-field strain distribution data, identification and positioning are performed to generate strain concentration region coordinates; the strain concentration region coordinates are input to the ultrasonic emission / receiving array for targeted scanning to generate sound velocity variation feature values and sound attenuation feature values; based on the sound velocity variation feature values and the sound attenuation feature values, multi-feature fusion and trend quantization analysis are performed to generate creep prediction parameters.

[0009] Optionally, the forming the closed-loop test environment comprises: generating a load adjustment instruction when the creep prediction parameter exceeds a preset critical creep state threshold; adjusting the axial static sustained load and the radial low-frequency alternating load in real time based on the load adjustment instruction to obtain an adjusted load parameter; re-coupling the adjusted load parameter and the environmental parameter to form an updated multi-field coupling loading condition, and feeding back to the multi-environment factor coupling test box to realize dynamic closed-loop control of the test process.

[0010] Optionally, the method further comprises: performing time difference value calculation based on the sound velocity change data to generate a propagation time change amount; performing analysis calculation based on the sound attenuation coefficient data to obtain an amplitude attenuation percentage; and performing time differentiation operation on the propagation time change amount and the signal amplitude attenuation percentage to generate a derivative curve of acoustic characteristics changing over time.

[0011] Optionally, the generating the anti-creep performance evaluation result comprises: extracting strain evolution features based on the optical monitoring data and extracting acoustic response features based on the acoustic monitoring data; cross-domain fusing the strain evolution features and the acoustic response features to construct a creep damage evolution graph; identifying a damage development stage according to the creep damage evolution graph and extracting feature parameters; combining the load parameter combination and the environmental parameter combination to normalize and aggregate the feature parameters to generate the anti-creep performance evaluation result.

[0012] Optionally, the constructing the creep damage evolution graph comprises: mapping the strain evolution features into a spatial distribution matrix and converting the acoustic response features into a time sequence matrix; jointly reconstructing the spatial distribution matrix and the time sequence matrix to form a spatio-temporal fusion feature tensor; and based on the spatio-temporal fusion feature tensor, drawing an evolution trajectory of the creep damage in the time and space dimensions to generate the creep damage evolution graph.

[0013] Optionally, after the test is completed, the solid wood sample is unloaded and recovered for monitoring to obtain residual strain data and acoustic recovery data; based on the residual strain data and the acoustic recovery data, an elastic recovery rate and a plastic deformation amount are obtained; and based on the anti-creep performance evaluation result, the elastic recovery rate and the plastic deformation amount, a material durability rating is generated.

[0014] Based on the same inventive concept, the application also provides a test method and system for strengthening the anti-creep performance of solid wood structures, the system comprising: a multi-field coupled loading module for obtaining a combination of environmental parameters and a combination of load parameters defining a test working condition, and performing multi-field coupled loading on a solid wood sample based on the combination of environmental parameters and the combination of load parameters to generate a loaded sample state; an in-situ monitoring module for performing in-situ optical monitoring based on the loaded sample state to generate optical monitoring data, and performing in-situ acoustic monitoring to generate acoustic monitoring data; a creep parameter analysis module for generating creep prediction parameters through associated analysis of the optical monitoring data and the acoustic monitoring data; a closed-loop adjustment module for dynamically adjusting the combination of load parameters based on the creep prediction parameters to form a closed-loop test environment; and a performance evaluation module for performing comprehensive analysis based on the closed-loop test environment, combining the optical monitoring data and the acoustic monitoring data to generate an anti-creep performance evaluation result.

[0015] Compared with the prior art, the application has the following advantages: 1. The application can highly reproduce the real working conditions of solid wood structures during service by constructing a multi-field coupled loading environment, which faces the combined action of temperature, humidity and complex load. Compared with traditional single environment or static load testing, the creep behavior and damage mechanism induced by this method are closer to engineering practice, thereby ensuring the accuracy and practical application value of the anti-creep performance evaluation result, and providing more reliable data support for structural safety design.

[0016] 2. The application innovatively integrates in-situ optical and acoustic monitoring technologies and realizes synchronous associated analysis of the two. This cross-scale monitoring means can capture the macroscopic strain morphology of the material surface and the microscopic damage signal inside at the same time, directly links the external phenomenon with the internal mechanism, and reveals a more profound damage evolution law. The fusion of this multi-source information greatly improves the depth and richness of the test data, making the understanding of the creep process more comprehensive.

[0017] 3. The application proposes a closed-loop test method based on real-time monitoring feedback. By generating creep prediction parameters and dynamically adjusting the loading conditions, the test system has intelligent adaptive ability. This not only effectively avoids the sudden failure of the sample and protects the experimental equipment, but more importantly, it can perform fine loading and detection in the critical region of material performance, obtain key data that traditional test methods cannot reach, and significantly improve the safety and data value of the test.

[0018] 4.The application establishes a complete analysis process from multi-dimensional data fusion to quantitative evaluation. By constructing a creep damage evolution map, the abstract damage process is visualized, and finally a comprehensive anti-creep performance evaluation result and durability rating are generated. This method not only provides an intuitive understanding of material performance, but also realizes quantitative comparison between different materials or processes, and the evaluation conclusion is more three-dimensional and systematic, providing clear guidance for material selection and engineering application.

[0019] Other features and advantages of the present application will be set forth in the following description, and in part will be apparent from the description, or can be learned by practice of the application. The objects and other advantages of the present application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings. BRIEF DESCRIPTION OF DRAWINGS

[0020] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the following will briefly introduce the drawings needed to be used in the embodiments or the prior art description. Obviously, the drawings in the following description are some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0021] Figure 1 is a flowchart of a test method for strengthening the anti-creep performance of a solid wood structure according to an embodiment of the present application.

[0022] Figure 2 is a curve graph of axial and radial load change over time according to an embodiment of the present application.

[0023] Figure 3 is a strain concentration area identification schematic diagram according to an embodiment of the present application.

[0024] Figure 4 is a three-dimensional damage evolution model according to an embodiment of the present application.

[0025] Figure 5 is a structural schematic diagram of a test system for strengthening the anti-creep performance of a solid wood structure according to an embodiment of the present application. DETAILED DESCRIPTION

[0026] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following will combine the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are some of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the protection scope of the present application.

[0027] REFERENCE Figure 1One embodiment of the present application proposes a test method for strengthening the anti-creep performance of solid wood structure, which can realize precise simulation, deep insight and intelligent evaluation of the creep process of solid wood by adopting the technical scheme of multi-field coupling loading combined with multi-source in-situ monitoring and forming a closed-loop test through feedback control.

[0028] The method of the embodiment specifically includes: Obtaining an environmental parameter combination and a load parameter combination defining a test working condition, and performing multi-field coupling loading on a solid wood sample based on the environmental parameter combination and the load parameter combination to generate a loaded sample state; Performing in-situ optical monitoring based on the loaded sample state to generate optical monitoring data, and performing in-situ acoustic monitoring to generate acoustic monitoring data; Generating creep prediction parameters according to the correlation analysis of the optical monitoring data and the acoustic monitoring data; Based on the creep prediction parameters, dynamically adjusting the load parameter combination to form a closed-loop test environment; Based on the closed-loop test environment, combining the optical monitoring data and the acoustic monitoring data for comprehensive analysis to generate an anti-creep performance evaluation result.

[0029] Specifically, first, a highly realistic multi-field coupling loading environment is created by simulating the combination of environmental parameters and load parameters in actual service to induce the real creep behavior of solid wood samples and generate the loaded sample state. On this basis, the in-situ optical monitoring technology is used to capture the overall macroscopic strain evolution of the sample surface in real time, and the optical monitoring data are obtained. At the same time, the in-situ acoustic monitoring technology is used to synchronously detect the acoustic response of the internal microscopic damage, and the acoustic monitoring data are obtained. By time synchronization and correlation analysis of the monitoring data of different scales and dimensions, the creep prediction parameters that can reflect the current damage state and predict the future trend are extracted. The creep prediction parameters are used as key feedback signals to dynamically adjust the applied load, thereby forming an intelligent closed-loop control loop from "sample response" to "loading conditions". In this dynamically adjusted test environment, the comprehensive analysis and cross-domain fusion of the optical monitoring data and acoustic monitoring data throughout the process are carried out to generate a comprehensive evaluation result of the anti-creep performance of solid wood structures. The damage state is comprehensively understood from the surface to the interior and from the macroscopic to the microscopic, making the understanding of the creep mechanism more profound and comprehensive. The innovative closed-loop test environment, through real-time feedback and dynamic adjustment, not only avoids the premature destruction of the sample and effectively prolongs the valuable observation window in the later stage of damage evolution, but also explores the mechanical behavior of the material in the critical state, obtaining data that cannot be obtained by traditional open-loop tests. The anti-creep performance evaluation result generated by comprehensive analysis is more objective and three-dimensional because it integrates multi-dimensional information and considers the dynamic loading history, which can provide more reliable and detailed scientific basis for the research and development of reinforced wood materials, the optimization of structure design, and the prediction of long-term service life.

[0030] Optionally, the generating the loaded sample state comprises: performing feature extraction based on the combination of environmental parameters to obtain temperature and humidity parameter values, and performing feature extraction based on the combination of load parameters to obtain an axial static sustained load and a radial low-frequency alternating load; adjusting a preset multi-environment factor coupling test box based on the temperature and humidity parameter values to form a stable temperature and humidity environment field; applying the axial static sustained load and the radial low-frequency alternating load to a multi-axis servo loading device in the multi-environment factor coupling test box based on the stable temperature and humidity environment field to form a loaded sample state; Specifically, first, the parameter extraction of the test working condition is needed. The test personnel extracts a set of environmental parameter combinations and load parameter combinations from the preset working condition library. The feature extraction of the environmental parameter combination is mainly to determine the specific temperature and humidity parameter values, and to select specific temperature and relative humidity values as the environmental set points for this test. The feature extraction of the load parameter combination is to determine the two mechanical loads applied to the solid wood sample, i.e. an axial static sustained load along the grain direction of the sample and a radial low-frequency alternating load perpendicular to the grain direction. The axial static sustained load is used to simulate the self-weight or long-term constant external force borne by the structure, which is the main factor inducing creep; the radial low-frequency alternating load is used to simulate wind load, live load and other periodic external disturbances, which has an accelerating or modifying effect on the creep process. Then, the obtained temperature and humidity parameter values are input into the central control platform of the multi-environment factor coupling test box. The multi-environment factor coupling test box integrates heating, refrigeration, humidification, dehumidification and air circulation modules inside, and according to the set values, the environmental state is fed back in real time through precision sensors, while automatically adjusting the work of each module, so as to create an accurate, uniform and long-term stable steady-state temperature and humidity environment field for the solid wood sample inside the multi-environment factor coupling test box. After the steady-state temperature and humidity environment field is established and stabilized, the mechanical load is applied. The multi-environment factor coupling test box is pre-installed with a multi-axis servo loading device. The device includes at least two independently controllable actuators. The operator sets the previously extracted axial static sustained load value to the loading actuator parallel to the axial direction of the solid wood sample, and the actuator applies a constant force and remains for a long time. At the same time, the amplitude, frequency and other parameters of the radial low-frequency alternating load are set to the loading actuator perpendicular to the radial direction of the solid wood sample. The loading actuator will apply a transient load that changes periodically with time. For the transient load at time t, the instantaneous load at time t is: , wherein, is the load amplitude, is the angular frequency, is the initial phase. In the steady-state temperature and humidity environment field, the two mechanical loads are applied to the solid wood sample at the same time, at this time, the solid wood sample not only bears the constant temperature and humidity, but also bears the complex combined mechanical action, the physical state under this comprehensive action is defined as the loaded sample state, which provides a high-fidelity test object for subsequent in-situ monitoring. For example, Figure 2As shown, the black solid line in the figure represents the axial static sustained load, representing a constant force of 20 kN, simulating the constant load that the solid wood structure bears in actual use, such as the weight of the structure and the weight of fixed equipment; the black dashed line in the figure represents the radial low-frequency alternating load, representing a periodically varying force with an amplitude of 5 kN and a frequency of 0.2 Hz, simulating the dynamic load that may exist in the actual environment, such as wind load and traffic load; the two loads act on the sample at the same time, simulating the complex stress state in the real service environment. Compared with the traditional single-field single-load test, this multi-field coupled loading method can more truly reflect the creep mechanism and damage accumulation process of solid wood materials under the combined action of temperature, humidity, static load and dynamic load, so that the subsequent anti-creep performance test and evaluation results are more accurate and have more actual engineering guiding value.

[0031] Optionally, the in-situ optical monitoring based on the state of the loaded sample, generating optical monitoring data, and in-situ acoustic monitoring to generate acoustic monitoring data include: Based on the state of the loaded sample, the full-field strain distribution data of the surface of the solid wood sample is obtained by a micro high-resolution optical strain gauge as optical monitoring data; The sound velocity change data and the sound attenuation coefficient data inside the solid wood sample are obtained by an ultrasonic emission / reception array as acoustic monitoring data; The full-field strain distribution data, the sound velocity change data and the sound attenuation coefficient data are time-stamped aligned to generate multi-source synchronous monitoring data.

[0032] Specifically, the acquisition process of optical monitoring data and acoustic monitoring data is carried out synchronously in the state of the formed loaded sample, aiming to capture the internal and external response characteristics of the solid wood sample in the creep process without disturbance. The core of in-situ optical monitoring is to obtain full-field strain distribution data of the surface of the solid wood sample by using a miniature high-resolution optical strain gauge. Before the test starts, a random speckle pattern needs to be made on the surface of the solid wood sample to be observed. During the test, the miniature high-resolution optical strain gauge placed on the observation window outside the multi-environment factor coupling test box continuously shoots high-definition digital images of the surface of the sample at a preset time interval. By digital image correlation method, the image at the next moment is compared with the image at the reference moment, and the displacement and deformation of the speckle are tracked, so that the displacement field of thousands of points on the surface of the sample is calculated, and further the full-field strain distribution data is obtained through differential operation. The full-field strain distribution data directly shows the stretching or compression degree of each region on the surface of the sample in the form of a cloud chart, which is the optical monitoring data. At the same time, in-situ acoustic monitoring is carried out through an ultrasonic emission / receiving array which is precisely installed on the solid wood sample to ensure good acoustic coupling. During the monitoring, the emission probe emits a pulse of ultrasonic wave with a specific frequency and energy, which penetrates the interior of the solid wood sample and is received by the receiving probe. By recording the time required for the ultrasonic wave to propagate from the emission to the reception, and combining the known probe spacing, the propagation speed of the acoustic wave in the material interior can be calculated. Since the damage accumulation such as the generation of micro-cracks and the change of density in the material interior will change the propagation path of the acoustic wave and the elastic modulus of the medium, resulting in a change in the propagation speed, continuous monitoring can obtain the acoustic velocity change data. At the same time, by comparing the amplitude of the received signal with the initial amplitude of the emitted signal, the energy loss of the signal in the propagation process can be quantified, i.e. the acoustic attenuation. Acoustic attenuation will cause scattering and absorption of acoustic waves, resulting in a decrease in amplitude, from which the acoustic attenuation coefficient data can be obtained. For calculating the acoustic attenuation coefficient data there is: , wherein, represents the length of the ultrasonic wave propagation path; represents the initial amplitude of the emitted ultrasonic pulse. The acoustic velocity variation data and the acoustic attenuation coefficient data together constitute the acoustic monitoring data reflecting the internal microstructure state of the material. Finally, in order to ensure the comparability and relevance of data from different sources, the full-field strain distribution data, the acoustic velocity variation data, and the acoustic attenuation coefficient data must be time-stamped aligned. In operation, the optical monitoring system and the acoustic monitoring system are connected to the same central clock synchronization signal source. In this way, the capture time of each frame of full-field strain distribution data image and the emission and reception time of each ultrasonic pulse are both labeled with an accurate and unified time stamp. By aligning these time stamps, the originally independent data streams are integrated into a multi-source synchronous monitoring data, which has both surface strain information and internal acoustic characteristic information at any time point, laying a solid data foundation for subsequent cross-domain correlation analysis. Optical monitoring can accurately capture and locate the initiation and propagation of surface strain, while acoustic monitoring can sensitively reflect the evolution of internal damage invisible to the naked eye. The synchronization and correlation of the two make researchers able to directly link external strain phenomena with internal physical mechanisms, improving the depth and reliability of test data.

[0033] Optionally, the generating the creep prediction parameter comprises: identifying and locating based on the full-field strain distribution data to generate strain concentration region coordinates; inputting the strain concentration region coordinates into the ultrasonic wave emission / reception array for targeted scanning to generate acoustic velocity variation eigenvalues and acoustic attenuation eigenvalues; performing multi-feature fusion and trend quantization analysis based on the acoustic velocity variation eigenvalues and the acoustic attenuation eigenvalues to generate the creep prediction parameter.

[0034] Specifically, first, the full-field strain distribution data of the continuous time sequence is automatically analyzed by image analysis. By using gradient recognition algorithms such as Sobel operator or Canny edge detection algorithm, the areas where the strain value abnormally increases and forms local extreme value on the surface of the solid wood sample, i.e. the strain concentration areas, are automatically recognized and located. The geometric center or contour boundary of these strain concentration areas is extracted and converted into strain concentration area coordinates in the sample coordinate system. Subsequently, these strain concentration area coordinates are transmitted in real time to the control unit of the ultrasonic emission / reception array which has the ability of beam forming and electronic scanning. After receiving the coordinate instructions, the ultrasonic emission / reception array will no longer perform general scanning on the entire sample, but will perform a targeted scanning. The control unit will accurately calculate and apply the corresponding delay to each unit of the ultrasonic emission / reception array, so that the emitted ultrasonic beam can be focused in the three-dimensional space volume inside the sample corresponding to the strain concentration area coordinates. By performing high-density and high signal-to-noise ratio acoustic detection on this key area, more accurate acoustic response of the local area can be obtained. The change amount of the sound velocity value extracted therefrom relative to the sound velocity reference value in the initial healthy state is the sound velocity change characteristic value. For calculating the sound velocity change characteristic value , there is: , wherein, is the sound velocity reference value in the initial healthy state; is the sound velocity value monitored at the moment . The change amount of the sound attenuation coefficient value extracted therefrom relative to the initial reference value is the sound attenuation characteristic value. For calculating the sound attenuation characteristic value , there is: , wherein, is the sound attenuation coefficient reference value in the initial healthy state; is the sound attenuation coefficient monitored at the moment . This way of guiding micro-detection from macro-phenomenon greatly improves the efficiency and pertinence of monitoring. Finally, multi-feature fusion and trend quantization analysis are performed to generate a single creep prediction parameter with clear physical meaning. The sound velocity change characteristic value mainly reflects the change of material elastic modulus and the generation of micro-cracks, while the sound attenuation characteristic value is more sensitive to the density and size of cracks. Combining the two can more comprehensively evaluate the internal damage state. A feasible fusion method is to construct a weighted damage index, i.e. a creep prediction parameter. For calculating the creep prediction parameter , there is: , wherein, is the sound velocity change characteristic value; The characteristic value of the change in sound speed at any given time represents the normalized rate of change of the current sound speed relative to the initial healthy state sound speed. for The sound attenuation characteristic value at time t represents the normalized increment of the current sound attenuation coefficient relative to the initial value. and The sound velocity variation weighting coefficient and sound attenuation weighting coefficient are determined in advance through calibration tests. Several groups of samples from the same batch and with the same process as the solid wood material to be tested are selected, with at least 3 samples in each group. Under constant temperature and humidity, a gradually increasing static load is applied to the samples until visible damage or failure occurs. During each load step, data is simultaneously acquired. and Based on the appearance of strain concentration regions, abrupt changes in acoustic parameters, or the final failure state, the damage state is labeled at each time point; multiple linear regression, such as logistic regression, is used to... and Using damage state as the label and using the feature as the label, the optimal weights are fitted. and This approach ensures the strongest correlation between creep prediction parameters and damage state. Furthermore, trend quantification analysis includes differentiating the time series of creep prediction parameters, analyzing their first and second derivatives to determine the rate and acceleration of creep damage development, thereby achieving short-term prediction of future creep states. For example... Figure 3 As shown, the strain distribution on the surface of the solid wood sample is illustrated. The X and Y axes represent the physical coordinates (in millimeters) of the sample surface; the color intensity in the graph indicates the strain magnitude, with lighter colors indicating greater strain; the rectangles in the graph represent strain concentration areas, marking localized regions of abnormally high strain. These areas are potential damage initiation sites that may develop into cracks or failure. By first locating potential damage "hot spots" through optical monitoring, and then guiding acoustic monitoring for precise "deep diagnosis," the optimal allocation of monitoring resources and improved data quality are achieved. Furthermore, creep prediction parameters not only characterize the current degree of damage but also predict the approaching creep failure through their dynamic trends, providing crucial decision-making basis for achieving closed-loop control of the testing process and early warning of structural safety.

[0035] Optionally, the closed-loop test environment includes: When the creep prediction parameters exceed the preset critical creep state threshold, a load adjustment command is generated; Based on the load adjustment command, the axial static continuous load and the radial low-frequency alternating load are adjusted in real time to obtain the adjusted load parameters. The adjusted load parameter is re-coupled with the environmental parameter to form an updated multi-field coupling loading condition and is fed back to the multi-environment factor coupling test box to realize dynamic closed-loop control of the test process.

[0036] Specifically, the preset critical creep state threshold is a key judgment criterion. The critical creep state threshold is not a fixed empirical value, but is determined according to the test purpose, the material type, and the expected failure mode. A number of representative samples, such as 3-5, of the same batch and same process as the reinforced wood structure to be tested are subjected to a creep destructive test under a typical combination of environmental parameters and load parameters. During the entire destruction process, the time evolution curve of the creep prediction parameter is continuously recorded, and macroscopic damage such as visible crack initiation, large deformation acceleration, or the moment of final failure is monitored. The inflection point of the creep curve in the destructive test, where the transition from the stable creep stage to the accelerated creep stage occurs, and the creep prediction parameter value or its change rate before macroscopic damage occurs are used as the reference critical creep state threshold. For example, the creep prediction parameter value reaching 70-80% of the final destruction value can be used as the critical creep state threshold. During the test, the generated creep prediction parameters are continuously received and processed. The newly generated creep prediction parameter value is compared with the preset critical creep state threshold in real time. Once it is monitored that the value of the creep prediction parameter exceeds the critical creep state threshold or its growth rate exceeds the preset limit, it is immediately determined that the sample has entered or will soon enter the unstable damage acceleration stage. At this time, a load adjustment instruction is automatically triggered and generated. The instruction is not simply to stop loading, but contains a specific adjustment strategy. For example, the instruction can specify that the axial static sustained load be reduced by a specific percentage, or that the amplitude of the radial low-frequency alternating load be reduced at the same time to alleviate the accumulation rate of damage. After receiving the load adjustment instruction, the controller of the multi-axis servo loading device in the multi-environment factor coupling test box will immediately execute. The controller will accurately adjust the force applied to the sample, so that the axial static sustained load and the radial low-frequency alternating load are adjusted in real time according to the instruction requirements. After the adjustment is completed, the new load value is recorded, which is the adjusted load parameter. Then, the adjusted load parameter is re-integrated with the unchanged environmental parameter combination to form an updated multi-field coupling loading condition. This new loading condition is immediately fed back to the central control platform of the multi-environment factor coupling test box as the running target of the next stage. The multi-environment factor coupling test box then continues to load the sample according to the updated condition. The complete process of “monitoring-judging-adjusting-feedback” is continuously looped, forming a dynamic closed-loop control system. It can actively intervene before the sample fails macroscopically, adjust the loading condition, thereby avoiding the sudden failure of the sample and the accidental interruption of the test, and providing more detailed and reliable safety redundancy basis for structural design.

[0037] Optionally, the method further includes: Based on the sound speed change data, the time difference is calculated to generate the propagation time change. Based on the sound attenuation coefficient data, the amplitude attenuation percentage is obtained through analysis and calculation. The time derivative operation is performed on the change in propagation time and the percentage attenuation of the signal amplitude to generate the derivative curve of the acoustic feature over time.

[0038] Specifically, firstly, time difference calculations are performed based on sound velocity variation data to generate the propagation time variation. In acoustic monitoring, ultrasonic waves propagate over a fixed distance between the transmitting and receiving probes. Therefore, the sound wave propagation time can be calculated by dividing the fixed distance between the transmitting and receiving probes by the measured sound velocity value. The propagation time variation is defined as the difference between the sound wave propagation time at the current moment and the sound wave propagation time at the initial moment of the test, i.e., when the material is in a healthy state. The propagation time variation directly reflects the delay caused by the extension of the sound wave propagation path or the decrease in the medium modulus due to the accumulation of internal damage. The larger the value, the more severe the internal damage usually is. Next, calculations are performed based on the sound attenuation coefficient data to obtain the amplitude attenuation percentage. The essence of sound attenuation is the loss of sound wave energy during propagation, directly reflected in the reduction of the received signal amplitude, and the amplitude attenuation percentage is used to quantify the degree of this loss. For calculation... Percentage decrease in amplitude at time ,have: , in, It is the reference received signal amplitude measured in the non-destructive sample at the beginning of the test, or the initial calibrated amplitude of the transmitted signal; Then it is The received signal amplitude is monitored in real time. This amplitude attenuation percentage directly characterizes the proportion of signal strength reduction relative to the initial state, and is a sensitive indicator of the material's ability to scatter and absorb sound energy due to internal defects. To capture the instantaneous characteristics of damage evolution, time differentiation is performed on the two time-series data points: the change in propagation time and the percentage attenuation of signal amplitude. Numerical differentiation methods are used to calculate the rate of increase in sound wave propagation time and the rate of signal amplitude attenuation over time. The final result is a derivative curve of the acoustic characteristics over time. This elevates acoustic monitoring and analysis from comparing static values ​​to capturing dynamic trends. Compared to directly observing the absolute values ​​of sound velocity changes or attenuation coefficients, the first derivative, i.e., the rate of change, is more sensitive to abrupt changes in damage state. When solid wood creep enters the accelerated stage, internal microcracks propagate rapidly, at which point the derivative curve shows a significant peak or sharp increase, which can serve as an earlier and more reliable indicator for warning of creep instability.

[0039] Optionally, the generating the anti-creep performance evaluation result comprises: extracting strain evolution features based on the optical monitoring data, and extracting acoustic response features based on the acoustic monitoring data; cross-domain fusing the strain evolution features and the acoustic response features to construct a creep damage evolution graph; identifying damage development stages according to the creep damage evolution graph, and extracting feature parameters; combining the load parameter combination and the environmental parameter combination, normalizing and aggregating the feature parameters to generate the anti-creep performance evaluation result.

[0040] Specifically, first, key strain evolution features are extracted from the optical monitoring data. This includes calculating the average strain change curve of the entire monitoring area over time to represent the macroscopic creep behavior of the material; at the same time, the peak strain size and its spatial expansion range of the strain concentration area over time are identified and tracked, which reflects the initiation and development of local damage. Correspondingly, acoustic response features such as acoustic velocity change characteristic values, acoustic attenuation characteristic values, and their time derivatives are extracted from the acoustic monitoring data, which collectively depict the cumulative process of internal microstructure damage. Second, through specific data visualization techniques, the time series of strain evolution features such as strain cloud maps are associated with the acoustic response features such as the acoustic velocity or attenuation value change curve over time on a unified time axis, generating a creep damage evolution graph, where the background is a changing strain cloud map, and the acoustic feature curve at the corresponding time is superimposed on the creep damage evolution graph, and the target acoustic feature value of the strain concentration area is marked, which intuitively shows how the appearance of the surface strain hot spot corresponds to the mutation of the internal acoustic parameters, thereby establishing a spatiotemporal correlation between macroscopic deformation and microscopic damage. Then, the creep damage evolution graph is interpreted, and the entire creep process is divided into different damage development stages, such as the initial creep, stable creep, and accelerated creep stages, based on strain growth rate, strain distribution pattern, acoustic feature change trend, and other comprehensive information. Subsequently, feature parameters representing the core characteristics of each stage are extracted, such as the minimum creep rate in the stable creep stage, the starting time point in the accelerated creep stage, and the critical values of strain and acoustic features at the stage transition point. Finally, in order to comprehensively evaluate the performance of the material, the aforementioned feature parameters with different physical meanings and dimensions need to be quantitatively integrated under the applied load parameter combination and environmental parameter combination. For example, the same feature parameter value under high load and high humidity environment will be given different weights or evaluation scales under low load and dry environment to more accurately reflect the performance of the material under actual complex working conditions. First, each feature parameter is normalized to convert it into a dimensionless evaluation value. For the first feature parameter normalized evaluation value ,have: , in, These are the original feature parameters; , For the first The minimum and maximum reference values ​​for each parameter are determined. For example, the minimum creep rate can be compared to the rate of a standard reference material to obtain a relative evaluation value. Subsequently, weighting coefficients are assigned to different characteristic parameters based on their importance in evaluating creep resistance. Finally, all normalized characteristic parameters are aggregated into a single comprehensive score, i.e., the creep resistance evaluation result, through a weighted summation. The calculation of the creep resistance evaluation result... ,have: , in, It is the first The weights of each characteristic parameter, such as the minimum creep rate, accelerated creep initiation time, peak strain, and acoustic attenuation rate, are determined using an entropy weighting method combined with expert scoring. Multiple sets of experimental data are collected, the entropy value of each characteristic parameter is calculated, and the difference coefficient of each parameter is calculated based on the entropy value to determine the weight. This final result provides an intuitive and comparable quantitative indicator for the creep resistance of different solid wood materials or different strengthening processes. By constructing a complete analytical chain from multi-source data feature extraction to comprehensive indicator generation, a deep, multi-dimensional, and quantitative assessment of the creep resistance of solid wood is achieved. This visualizes the originally abstract damage process and enhances the understanding of material failure mechanisms.

[0041] Optionally, constructing the creep damage evolution map includes: The strain evolution characteristics are mapped to a spatial distribution matrix, and the acoustic response characteristics are converted into a time series matrix; The spatial distribution matrix and the time series matrix are jointly reconstructed to form a spatiotemporal fusion feature tensor; Based on the spatiotemporal fusion feature tensor, the evolution trajectory of creep damage in the time and space dimensions is plotted to generate a creep damage evolution map.

[0042] Specifically, first, the strain evolution features extracted from the optical monitoring data are processed. For each monitoring time point, the full-field strain distribution data itself is a two-dimensional strain value matrix, whose row and column indices correspond to the physical coordinates on the surface of the solid wood sample. Therefore, stacking the full-field strain distribution data at consecutive time points naturally forms a three-dimensional data volume, where two dimensions are spatial and one dimension is temporal. For subsequent processing, it can be represented as a spatial distribution matrix at each time point. Meanwhile, the acoustic response features extracted from the acoustic monitoring data are processed. These acoustic response features, such as the eigenvalues of the acoustic velocity variation or acoustic attenuation, are essentially one-dimensional scalar sequences that vary with time. These different types of acoustic eigenvalues can be organized into a feature vector at each time point, and then the feature vectors at all time points are arranged to form a time sequence matrix. Second, joint reconstruction is performed to form a spatiotemporal fusion feature tensor, i.e., the spatial distribution matrix describing the surface strain and the time sequence matrix describing the internal damage are organically combined. Based on the spatial distribution matrix, the acoustic features can be attached to each spatial pixel point as additional "channels" or "attributes". The acoustic response eigenvalues obtained by global or targeted scanning are broadcast or interpolated to each pixel point of the spatial distribution matrix at each time point to form a multi-channel two-dimensional image. When we stack all the time points of this multi-channel image, we get a higher-order data structure, i.e., the spatiotemporal fusion feature tensor. The dimension of this tensor is usually (width, height, number of feature channels, time), which contains both strain information and acoustic information at each spatiotemporal coordinate point. Then, based on the spatiotemporal fusion feature tensor, visualization is drawn to generate a creep damage evolution map. With this tensor containing all the information, we can draw the damage evolution trajectory through advanced visualization techniques. For example, we can select a spatial slice of the tensor to play, forming a dynamic video. The color of each pixel point in the video can be determined by the strain value, forming a dynamic evolution of the strain nephogram; at the same time, the transparency or superimposed specific symbol of this pixel point can be controlled by the size of the acoustic eigenvalue. In this way, the audience can intuitively see that, as time goes on, in the area where the strain is gradually concentrated, the internal acoustic properties have also changed significantly. Another more advanced visualization is to draw a three-dimensional or four-dimensional map, where the x and y axes represent spatial position, the z axis represents time, and the color or isosurface represents the fused damage index. As shown in FIG. 8, the evolution of damage in the spatial and temporal dimensions is shown, the X and Y axes represent the horizontal and vertical coordinates of the sample surface, respectively, the Z axis represents the time dimension, and the color of the scatter points represents the damage index, with lighter colors indicating more severe damage; the damage is from the center region Figure 4 to the edge of the sample. The color of the isosurface represents the damage index, with lighter colors indicating more severe damage. The evolution of damage in the spatial and temporal dimensions is shown. The beginning of the damage, over time, the damage gradually spread to the surrounding, the degree of damage increases with time, that is, the color of the scatter plot shown in the figure becomes lighter. This atlas can fully show the whole picture of the time and space propagation of the damage from nothing to something, from small to large, from local to global, that is, the creep damage evolution atlas. The creep damage evolution atlas breaks the limitations of traditional data curves, can reveal the "when" and "where" of the damage, as well as the "how" of the surface phenomenon and internal mechanism, and improves the interpretability of the data. It provides researchers with a powerful analysis tool to deeply understand the internal mechanism of solid wood creep and accurately identify the damage pattern.

[0043] Optionally, the method further comprises: After the test is completed, the residual strain data and the acoustic recovery data are obtained by unloading recovery monitoring of the solid wood sample; Based on the residual strain data and the acoustic recovery data, the elastic recovery rate and the plastic deformation are calculated; Combined with the anti-creep performance evaluation result, the elastic recovery rate and the plastic deformation, a material durability rating is generated.

[0044] Specifically, after the main test process is completed, that is, the predetermined test time or the creep prediction parameter triggers the termination condition, first, the unloading recovery monitoring is performed. The operator removes the axial static sustained load and the radial low-frequency alternating load applied to the solid wood sample to zero smoothly through the multi-axis servo loading device. After unloading is completed, the in-situ optical monitoring and in-situ acoustic monitoring modules do not stop working, but continue to monitor the sample at regular time intervals, recording the natural recovery process of the sample under no load. The miniature high-resolution optical strain gauge continuously obtains the full-field strain distribution data of the sample surface until the strain value basically no longer changes, thereby obtaining the final residual strain data. At the same time, the ultrasonic emission / receiving array also continuously monitors the changes of sound speed and sound attenuation, records the recovery trajectory of the acoustic characteristics from the loaded state to the relaxation state, and forms the acoustic recovery data. Next, based on the data obtained by the unloading recovery monitoring, the elastic recovery rate and the plastic deformation are calculated. The plastic deformation can be directly read from the final stable full-field strain distribution data or the average value thereof can be calculated. The elastic recovery rate is used to quantify the ability of the material to recover its initial shape. For the calculation of the elastic recovery rate , there are: , wherein, is the maximum total strain at the unloading moment, that is, at the end of the loading stage, which can be obtained from the optical monitoring data; is the final measured residual strain after the recovery phase, i.e. the plastic deformation. The elastic recovery rate reflects the proportion of the recoverable elastic deformation in the total deformation. Finally, the elastic recovery rate, the plastic deformation and the creep resistance evaluation result of the main test phase are combined to generate a more comprehensive material durability rating. A three-dimensional evaluation space can be constructed, with each axis representing an indicator. A material with high durability should exhibit a high creep resistance evaluation result score, indicating slow damage accumulation during loading, a high elastic recovery rate, indicating good elasticity, a large recoverable deformation, and a low plastic deformation, indicating small permanent damage. By setting different rating standard regions, such as "excellent", "good", "qualified", and "unqualified", the final performance of the sample can be positioned in a specific rating in the evaluation space. By extending the performance evaluation from the loading process to the post-loading behavior, valuable information about the elastic-plastic properties of the material is obtained, making the evaluation conclusion more three-dimensional and complete, and providing a more comprehensive and in-depth scientific basis for material selection and long-term service performance prediction of engineering structures.

[0045] Based on the same inventive concept, as shown in Figure 5 The present application also provides a test system for strengthening the creep resistance of a solid wood structure, which comprises: A multi-field coupled loading module for obtaining a combination of environmental parameters and a combination of load parameters defining a test working condition, and performing multi-field coupled loading on a solid wood sample based on the combination of environmental parameters and the combination of load parameters to generate a loaded sample state; An in-situ monitoring module for performing in-situ optical monitoring based on the loaded sample state to generate optical monitoring data, and performing in-situ acoustic monitoring to generate acoustic monitoring data; A creep parameter analysis module for generating creep prediction parameters through correlation analysis based on the optical monitoring data and the acoustic monitoring data; A closed-loop adjustment module for dynamically adjusting the combination of load parameters based on the creep prediction parameters to form a closed-loop test environment; A performance evaluation module for generating a creep resistance performance evaluation result based on the closed-loop test environment, combined with comprehensive analysis of the optical monitoring data and the acoustic monitoring data.

[0046] To verify the feasibility of the present application in implementation, the present application is applied to a certain wood structure engineering research center to test the long-term creep resistance of a new type of carbon fiber reinforced larch glued wood beam. The center needs to evaluate the service reliability of the reinforced wood beam in a simulated hot and humid bridge environment in southern China. Traditional test methods cannot simultaneously simulate the coupling effect of temperature, humidity, static load and dynamic load, and cannot effectively warn and evaluate the state before failure.

[0047] In this embodiment, a certain solid wood sample with the size of 500mmx100mmx50mm is selected and placed in a multi-environment factor coupling test chamber. First, the test conditions are defined, and the environmental parameter combination is set as constant temperature 30℃, relative humidity 85%, simulating a hot and humid environment; the load parameter combination is set as an axial static sustained load of 20kN to simulate the structure dead load, and a radial low-frequency alternating load with an amplitude of 5kN and a frequency of 0.2Hz to simulate the vehicle live load. The test chamber forms a stable temperature and humidity environment field according to these temperature and humidity parameter values, and based on this, the axial static sustained load and the radial low-frequency alternating load are applied through the multi-axis servo loading device, thereby generating a stable multi-field coupling loading environment, so that the sample enters the loaded sample state.

[0048] After the test starts, the miniature high-resolution optical strain gauge continuously collects speckle images on the surface of the sample at a frequency of one frame every 10 minutes, generating full-field strain distribution data. At the same time, the ultrasonic emission / reception array arranged on the sample performs scanning at the same frequency to obtain internal sound velocity variation data and sound attenuation coefficient data. Through the central clock, the two groups of data are time-stamped and aligned to generate multi-source synchronous monitoring data.

[0049] At the 250th hour of the test, according to the optical monitoring data, a strain concentration area is automatically identified and located at the middle position of the lower edge of the sample, and the peak strain of the area has reached 0.3%. The coordinates of the area are then input into the ultrasonic array for targeted scanning, and the characteristic values of the sound velocity variation and the sound attenuation characteristic values of the key area are obtained. Through multi-feature fusion and trend quantization analysis, the creep prediction parameter is calculated. Setting the sound velocity variation weight coefficient and the sound attenuation weight coefficient , the creep prediction parameter is obtained. The generated creep prediction parameter shows an accelerating growth trend.

[0050] At the 310th hour of the test, the value of the creep prediction parameter exceeds the preset critical creep state threshold value 1.0, indicating that the sample is about to enter the unstable accelerated creep stage. Immediately generate a load adjustment instruction to reduce the axial static sustained load by 15% to 17kN, and reduce the amplitude of the radial low-frequency alternating load by 20% to 4kN. After the loading device executes the instruction, the updated multi-field coupling loading conditions are formed, successfully avoiding the sudden fracture of the sample, and enabling the test to continue under conditions close to the material performance limit to collect more critical damage evolution late-stage data.

[0051] The test lasted a total of 500 hours. A comprehensive analysis of the monitoring data throughout the process was then conducted. First, a creep damage evolution map was constructed based on optical and acoustic data. This map visually demonstrates how strain concentration highly coincides with the internal sound velocity reduction region in space and time. The minimum creep rate in the stable creep stage was identified as 1.5 × 10⁻⁻⁻⁶. 6 / h, the starting point of the accelerated creep stage is the 305th hour. Combining these characteristic parameters with the test conditions, normalization and weighted aggregation are performed. The minimum creep rate is weighted at 0.35, the accelerated creep onset time at 0.30, the peak strain at 0.20, and the acoustic attenuation rate at 0.15, generating the creep resistance evaluation results of the specimen. After the test, the sample was unloaded and recovery monitoring was continuously performed. The final measured plastic deformation was 0.12%, and the calculated elastic recovery rate was 82%. Based on the comprehensive creep resistance evaluation results, elastic recovery rate, and plastic deformation, the material durability rating of the reinforced wood beam was ultimately rated as "Excellent".

[0052] Table 1. Monitoring data of key parameters for creep testing of solid wood samples. Table 2 Comparison of Performance Evaluation Results between Reinforced Solid Wood Samples and Ordinary Samples The table above records the practical application data of this invention in the creep resistance test of reinforced solid wood structures, detailing its performance in dynamic monitoring, closed-loop adjustment, and comprehensive evaluation. These data clearly demonstrate the advanced nature and effectiveness of the method of this invention.

[0053] Table 1 effectively captures the entire creep development process. In particular, it identifies strain concentration areas at 250 hours and successfully warns of the accelerated creep stage at 310 hours by exceeding the creep prediction threshold, promptly triggering closed-loop load adjustment. This demonstrates that the present invention can achieve accurate prediction and intelligent intervention of damage states, avoiding catastrophic damage common in traditional testing.

[0054] Table 2 clearly demonstrates the discriminative power of this evaluation system by comparing it with ordinary unreinforced specimens. The carbon fiber reinforced specimens significantly outperformed the ordinary specimens in all three core indicators: creep resistance, elastic recovery rate, and plastic deformation, ultimately achieving an "excellent" durability rating. This quantitative result provides a direct and reliable basis for material selection and engineering applications. These data fully demonstrate the accuracy, forward-looking nature, and comprehensiveness of this invention in testing the creep resistance of reinforced solid wood structures.

[0055] It should be noted that the electrical connection between the various units described above does not necessarily indicate a direct connection, and the indirect connection mode can also be applied to the embodiments of the present application as long as the purpose of the present application is achieved. The above is only an exemplary embodiment of the present application, and cannot limit the scope of the present application.

[0056] That is, any equivalent changes and modifications made in accordance with the teachings of the present application are still within the scope of the present application. Other embodiments of the present application will be readily apparent to those skilled in the art upon considering the description and practice of the true principles of the disclosure. The present application is intended to cover any variations, uses, or adaptive changes of the present application that follow the general principles of the present application and include common knowledge or conventional techniques in the art that are not described in the present application.

Claims

1. A method of testing the creep resistance of a reinforced solid wood structure, characterized in that, The method comprises: acquiring an environmental parameter combination and a load parameter combination defining a test working condition, and performing multi-field coupling loading on a solid wood sample based on the environmental parameter combination and the load parameter combination to generate a loaded sample state; performing in-situ optical monitoring based on the loaded sample state to generate optical monitoring data, and performing in-situ acoustic monitoring to generate acoustic monitoring data; correlation analysis according to the optical monitoring data and the acoustic monitoring data to generate a creep prediction parameter; based on the creep prediction parameter, dynamically adjusting the load parameter combination to form a closed-loop test environment; based on the closed-loop test environment, combining the optical monitoring data and the acoustic monitoring data for comprehensive analysis to generate an anti-creep performance evaluation result.

2. The method for testing the creep resistance of a reinforced solid wood structure according to claim 1, characterized in that, The generated loaded sample state comprises: based on the environmental parameter combination, feature extraction is performed to obtain temperature and humidity parameter values, and based on the load parameter combination, feature extraction is performed to obtain axial static sustained load and radial low-frequency alternating load; according to the temperature and humidity parameter values, a pre-set multi-environment factor coupling test box is adjusted to form a stable temperature and humidity environment field; based on the stable temperature and humidity environment field, the multi-axis servo loading device in the multi-environment factor coupling test box is subjected to the axial static sustained load and the radial low-frequency alternating load to form a loaded sample state.

3. The method of claim 1, wherein the method is characterized by: The in-situ optical monitoring based on the loaded sample state to generate optical monitoring data, and the in-situ acoustic monitoring to generate acoustic monitoring data comprises: based on the loaded sample state, the full-field strain distribution data of the surface of the solid wood sample is obtained by a micro high-resolution optical strain gauge as optical monitoring data; the sound velocity variation data and the sound attenuation coefficient data inside the solid wood sample are obtained by an ultrasonic wave transmitting / receiving array as acoustic monitoring data; the full-field strain distribution data, the sound velocity variation data and the sound attenuation coefficient data are time-stamped and aligned to generate multi-source synchronous monitoring data.

4. The method of claim 3, wherein the method is characterized by: The generated creep prediction parameter comprises: based on the full-field strain distribution data, identification and positioning are performed to generate strain concentration region coordinates; the strain concentration region coordinates are input into the ultrasonic wave transmitting / receiving array for targeted scanning to generate sound velocity variation characteristic values and sound attenuation characteristic values; based on the sound velocity variation characteristic values and the sound attenuation characteristic values, multi-feature fusion and trend quantization analysis are performed to generate a creep prediction parameter.

5. The method of claim 2, wherein the method is characterized by: The closed-loop test environment comprises: when the creep prediction parameter exceeds a pre-set critical creep state threshold, a load adjustment instruction is generated; based on the load adjustment instruction, the axial static sustained load and the radial low-frequency alternating load are adjusted in real time to obtain adjusted load parameters; the adjusted load parameters and the environmental parameters are recoupled to form updated multi-field coupling loading conditions, and are fed back to the multi-environment factor coupling test box to realize dynamic closed-loop control of the test process.

6. The method of claim 3, wherein the method is characterized by: The method further comprises: based on the sound velocity variation data, time difference value calculation is performed to generate propagation time variation; based on the sound attenuation coefficient data, analysis and calculation are performed to obtain an amplitude attenuation percentage; Time-differentiate the propagation time variation and the signal amplitude attenuation percentage to generate a derivative curve of acoustic characteristics changing over time.

7. The method of claim 1, wherein the method is characterized by: The generating the anti-cracking performance evaluation result comprises: Extracting strain evolution features based on the optical monitoring data and acoustic response features based on the acoustic monitoring data; Fusing the strain evolution features and the acoustic response features across domains to construct a creep damage evolution map; Identifying the damage development stage according to the creep damage evolution map and extracting feature parameters; Combining the load parameter combination and the environmental parameter combination, normalizing and aggregating the feature parameters to generate the anti-cracking performance evaluation result.

8. The method of claim 7, wherein the method is a method of testing the creep resistance of a reinforced solid wood structure. The constructing the creep damage evolution map comprises: Mapping the strain evolution features into a spatial distribution matrix and converting the acoustic response features into a time sequence matrix; Jointly reconstructing the spatial distribution matrix and the time sequence matrix to form a spatio-temporal fusion feature tensor; Based on the spatio-temporal fusion feature tensor, drawing the evolution trajectory of the creep damage in the time and space dimensions to generate the creep damage evolution map.

9. The method of claim 1, wherein the method is a method of testing the creep resistance of a reinforced solid wood structure. The method further comprises: After the test is completed, unloading recovery monitoring is performed on the solid wood sample to obtain residual strain data and acoustic recovery data; Based on the residual strain data and the acoustic recovery data, the elastic recovery rate and the plastic deformation amount are obtained; Combining the anti-cracking performance evaluation result, the elastic recovery rate and the plastic deformation amount, a material durability rating is generated.

10. A system for testing the creep resistance of a reinforced solid wood structure, for use in a method for testing the creep resistance of a reinforced solid wood structure according to any one of claims 1 to 9, characterized in that, The system comprises: A multi-field coupling loading module for obtaining an environmental parameter combination and a load parameter combination defining a test working condition, and performing multi-field coupling loading on a solid wood sample based on the environmental parameter combination and the load parameter combination to generate a loaded sample state; An in-situ monitoring module for performing in-situ optical monitoring based on the loaded sample state to generate optical monitoring data, and performing in-situ acoustic monitoring to generate acoustic monitoring data; A creep parameter analysis module for generating creep prediction parameters based on the correlation analysis of the optical monitoring data and the acoustic monitoring data; A closed-loop adjustment module for dynamically adjusting the load parameter combination based on the creep prediction parameters to form a closed-loop test environment; A performance evaluation module for generating an anti-cracking performance evaluation result based on the closed-loop test environment, combining the optical monitoring data and the acoustic monitoring data for comprehensive analysis.

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