Method for testing weather resistance of material based on low-temperature ice and snow environment

Abstract

The invention discloses a method for testing weather resistance of a material based on a low-temperature ice and snow environment, which belongs to the technical field of material testing, and comprises the following steps: generating a dynamic environment parameter set according to an environment simulation script, applying dynamically changing ice and snow loads and multiple physical and chemical environment stresses in a preset composite environment stress cabin, constructing a coupling environment field acting on the to-be-tested sample; and acquiring the state of the to-be-tested sample in the coupling environment field in real time, generating a multi-dimensional monitoring data set, performing comparative analysis on the multi-dimensional monitoring data set and a preset material aging characteristic template, generating material response data representing the current state of the to-be-tested sample, and constructing an environment parameter adjustment instruction set to regulate and control the coupling environment field in the composite environment stress cabin in real time. According to the method, a closed-loop feedback control strategy combining construction of a dynamic coupling environment field and real-time monitoring of material response is adopted, intelligent acceleration of the testing process can be achieved on the premise that the authenticity of a failure mechanism is guaranteed, and the testing efficiency and the accuracy of a result are remarkably improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of material testing, in particular to a material weather resistance test method based on low-temperature ice and snow environment. BACKGROUND

[0002] The weather resistance of a material refers to the ability of the material to maintain its original physical and chemical properties under the combined action of natural environmental factors such as sunlight, temperature, wind, rain, ice and snow. For structural and functional materials widely used in aerospace, transportation, construction engineering and polar exploration, their weather resistance in low-temperature ice and snow environment is a key indicator that determines their service life and safety and reliability. Therefore, developing a precise and efficient weather resistance test method is of great significance for the research, selection and application of new materials.

[0003] Existing material weather resistance tests mainly rely on environmental test chambers or outdoor exposure test fields. In a laboratory environment, test equipment usually uses constant humidity, heat, salt spray, ultraviolet radiation or simple cold and hot cycles to simulate single or combined stress conditions. For low-temperature ice and snow environments, some tests form an ice layer on the surface of the material by cooling and spraying water, and perform periodic freeze-thaw cycles to evaluate the material's resistance to freeze-thaw performance. These methods can evaluate the material's resistance to specific environmental factors to some extent.

[0004] However, existing test methods often simply superimpose temperature, humidity, light and other environmental stresses, ignoring the complex physical and chemical coupling effects between these factors and ice and snow loads. The environmental parameters are mostly constant or have a simple periodic variation, which cannot reproduce the nonlinear and dynamic characteristics of real environmental parameters. In addition, the test process is usually open-loop, and the environmental stress cannot be adjusted according to the real-time state of the material, resulting in a disconnect between the test process and the actual aging process, low test efficiency and the possibility of inducing failure modes that do not match reality. SUMMARY

[0005] To solve the above problems, the present application provides a material weather resistance test method based on low-temperature ice and snow environment, which adopts a closed-loop feedback control strategy combining the construction of a dynamic coupling environment field and real-time monitoring of material response, which can realize intelligent acceleration of the test process while ensuring the authenticity of the failure mechanism, significantly improving the test efficiency and accuracy of the results.

[0006] The above objectives can be achieved by the following solutions: The application discloses a weather resistance test method for low-temperature ice and snow environment materials, and relates to the field of material testing.

[0007] Optionally, the method further comprises: analyzing the dynamic environment parameter set to obtain the target ice and snow form parameter, the target temperature parameter, the target humidity parameter, the target light intensity parameter and the target deicing agent concentration parameter; dynamically depositing an ice and snow layer on the surface of the sample to be tested according to the target ice and snow form parameter; and synchronously adjusting the environmental parameters in the preset composite environmental stress chamber to match the target temperature parameter, the target humidity parameter, the target light intensity parameter and the target deicing agent concentration parameter, so as to jointly form the coupling environment field together with the ice and snow layer.

[0008] Optionally, the method further comprises: obtaining the surface temperature distribution of the sample to be tested and the interface stress and strain data generated by frost heaving in the material-ice and snow interface micro area; obtaining the ice and snow layer state data representing the physical characteristics of the ice and snow layer; and performing spatio-temporal registration and fusion on the interface stress and strain data and the ice and snow layer state data to generate the multidimensional monitoring data set.

[0009] Optionally, the method further comprises: matching the interface stress and strain data with the material aging characteristic template to identify the material aging state characteristics; comparing the actual parameter data of the in-chamber environment in the multidimensional monitoring data set with the dynamic environment parameter set, and identifying the environmental simulation deviation characteristics according to an environmental simulation fidelity threshold; and structurally integrating the material aging state characteristics and the environmental simulation deviation characteristics to generate the material response data.

[0010] Optionally, the generating the environment parameter adjustment instruction set based on the material response data comprises: judging whether the material response data exceeds a material state safety threshold set for preventing the to-be-tested sample from having a non-realistic failure; if yes, generating a protective environment adjustment instruction; if no, calculating and generating an accelerated parameter combination according to the material response data; and integrating the protective environment adjustment instruction or the accelerated parameter combination into the environment parameter adjustment instruction set.

[0011] Optionally, the calculating and generating the accelerated parameter combination according to the material response data comprises: identifying a key stress factor related to a current-stage material aging contribution based on the material aging feature template analysis of the material response data; calculating an allowed increase of an action level of the key stress factor under the constraint of maintaining a realistic failure mechanism of the to-be-tested sample; and increasing the action level of the key stress factor based on the allowed increase, and generating the accelerated parameter combination by cooperatively matching and adjusting environmental stress factors according to a physical coupling relationship among environmental factors.

[0012] Optionally, the real-time regulation of the coupled environment field in the composite environment stress chamber according to the environment parameter adjustment instruction set comprises: analyzing the environment parameter adjustment instruction set, issuing a regulation instruction to an environment control system, and dynamically regulating a deposition characteristic of the ice and snow layer; and synchronously regulating an operation state of the composite environment stress chamber to reconstruct a multi-physical-chemical environment stress.

[0013] Optionally, the method further comprises: in each test cycle, judging whether the material response data reaches a preset material failure threshold, or judging whether a cumulative test time reaches a preset maximum test period; and terminating the test when any of the judgment conditions is met.

[0014] Based on the same inventive concept, the application also provides a weather resistance test system for low-temperature ice and snow environment materials, characterized in that the system comprises: an environment data setting module for generating a dynamic environment parameter set comprising at least target temperature parameters, target humidity parameters, target light intensity parameters, target deicing agent concentration parameters and target ice and snow morphology parameters according to an environment simulation script; an environment coupling simulation module for applying dynamic changing ice and snow loads and multi-physical and chemical environment stresses in a preset composite environment stress chamber to construct a coupling environment field acting on a test sample according to the dynamic environment parameter set; a multi-dimensional in-situ monitoring module for real-time acquisition of the state of the test sample in the coupling environment field and generation of a multi-dimensional monitoring data set; a feedback module for comparison and analysis of the multi-dimensional monitoring data set with a preset material aging characteristic template to generate material response data representing the current state of the test sample; an instruction generation module for generating an environment parameter adjustment instruction set based on the material response data; and an instruction execution module for real-time regulation and control of the coupling environment field in the composite environment stress chamber according to the environment parameter adjustment instruction set.

[0015] Compared with the prior art, the application has the following advantages: 1. The application constructs a dynamic coupling environment field to apply multiple environment stresses such as target temperature, humidity, light, deicing agent concentration and dynamically deposited ice and snow morphology in coordination, highly reproducing the dynamic and multi-factor coupling effect encountered by materials in real low-temperature ice and snow service environment, rather than simple stress superposition or static simulation in traditional tests; this significantly improves the environmental simulation fidelity of the test, makes the test results more accurately reflect the actual weather resistance of the material, and enhances the reliability and engineering guidance value of the test conclusion; 2. The application establishes a closed-loop control mechanism from environment simulation, state monitoring to feedback regulation; by real-time acquisition of multi-dimensional monitoring data of the test sample and comparison with the material aging characteristic template, the system can dynamically evaluate the current state of the material; based on this evaluation, the system can intelligently generate environment parameter adjustment instructions, which can not only prevent non-real failure caused by excessive acceleration, but also identify key aging stress factors and specifically improve their action level, thereby greatly shortening the test period and improving the test efficiency while ensuring the authenticity of the failure mechanism; 3、The application adopts multi-dimensional in-situ monitoring means including interface stress-strain monitoring, and combines with material aging characteristic template for deep analysis; this makes the test no longer limited to observing macro performance decline phenomenon, but can go deep into the interface of material and ice and snow, and accurately capture the micro area stress evolution caused by frost heaving, melting and the like; in this way, the damage evolution process and internal failure mechanism of the material in the complex environment can be more clearly revealed, the accurate characterization from macro phenomenon to micro response is realized, and deeper data support is provided for performance evaluation and improvement of the material.

[0016] Other features and advantages of the present application will be set forth in the following description, and in part will become apparent to those skilled in the art from the description, or can be learned by practice of the application. The objects and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims. BRIEF DESCRIPTION OF DRAWINGS

[0017] 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 those skilled in the art can obtain other drawings according to these drawings without any creative effort.

[0018] Figure 1 is a flowchart of a low-temperature ice and snow environment material weather resistance test method according to an embodiment of the present application.

[0019] Figure 2 is a schematic diagram of dynamic environmental parameter set changing with time according to an embodiment of the present application.

[0020] Figure 3 is a decoupling schematic diagram of interface stress-strain data according to an embodiment of the present application.

[0021] Figure 4 is a structural schematic diagram of a low-temperature ice and snow environment material weather resistance test system according to an embodiment of the present application. DETAILED DESCRIPTION

[0022] 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, but not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without any creative effort are within the protection scope of the present application.

[0023] REFERENCE Figure 1One embodiment of the present application proposes a low-temperature ice and snow environment material weather resistance test method, which adopts a closed-loop feedback control strategy combining the construction of a dynamic coupling environment field and real-time monitoring of material response, can realize intelligent acceleration of the test process under the premise of ensuring the authenticity of the failure mechanism, and significantly improves the test efficiency and the accuracy of the test results.

[0024] The method of this embodiment specifically includes: According to the environmental simulation script, a set of dynamic environmental parameters is generated, including at least target temperature parameters, target humidity parameters, target light intensity parameters, target snow-melting agent concentration parameters, and target ice and snow morphology parameters; According to the set of dynamic environmental parameters, a dynamically changing ice and snow load and a multi-physical and chemical environmental stress are applied in a preset composite environmental stress chamber to construct a coupling environment field acting on the test sample; Real-time acquisition of the state of the test sample in the coupling environment field generates a multi-dimensional monitoring data set; The multi-dimensional monitoring data set is compared and analyzed with a preset material aging characteristic template to generate material response data representing the current state of the test sample; Based on the material response data, an environmental parameter adjustment instruction set is generated; According to the environmental parameter adjustment instruction set, the coupling environment field in the composite environmental stress chamber is real-time regulated.

[0025] Specifically, the preset dynamic target parameters simulating the real environment are taken as input to construct a multi-physical and chemical stress coupling field in the composite environmental stress chamber. In this environment, the state change of the test sample is captured in real time through in-situ monitoring technology, and these original monitoring data are compared and analyzed with a pre-established material aging characteristic knowledge base, so as to convert the physical signal into structured data representing the current aging degree and response characteristics of the material. The response data is then used to drive the decision system to generate instructions for adjusting the environmental stress. Finally, the system executes these instructions to real-time regulate the coupling environment field, thereby forming a complete closed loop from "environmental application-material response-intelligent evaluation-environmental regulation", so that the entire test process can be dynamically and intelligently self-optimized and adjusted according to the actual state of the material. According to the real-time aging state of the material, the strength of the environmental stress can be autonomously judged and adjusted, so as to safely and effectively accelerate the aging process under the premise of ensuring that non-real failure mechanisms are not triggered, greatly shortening the test cycle and improving the test efficiency.

[0026] Optionally, the construction of the coupling environment field acting on the test sample includes: The dynamic environment parameter set is analyzed to obtain a target ice and snow form parameter, a target temperature parameter, a target humidity parameter, a target light intensity parameter, and a target deicing agent concentration parameter; According to the target ice and snow form parameter, an ice and snow layer is dynamically deposited on the surface of the test sample; The preset composite environment stress chamber is synchronously adjusted to match the target temperature parameter, the target humidity parameter, the target light intensity parameter, and the target deicing agent concentration parameter, and the ice and snow layer together forms a coupled environment field.

[0027] Specifically, first, the system receives and analyzes a dynamic environment parameter set generated in advance according to an environment simulation script. The parameter set defines the target trajectory of each environmental parameter dynamically changing over time during the test. The dynamic environment parameter set can be represented as a parameter vector changing over time, as shown in the following formula: Figure 2 The formula is used to accurately guide the simulation of the environment: , Where t represents the time of the test; is the dynamic environment parameter set at time t; is the target temperature parameter, which is realized by controlling the refrigeration and heating system in the composite environment stress chamber, and the unit is Celsius; is the target humidity parameter, which is controlled by the humidification and dehumidification system in the chamber, and is expressed in relative humidity percentage; is the target light intensity parameter, which is provided by a group of solar simulation lamps or ultraviolet lamps with adjustable power in the chamber, and the unit is watts per square meter; is the target deicing agent concentration parameter, which is sprayed in the form of atomization onto the ice and snow layer on the surface of the test sample by a precision metering pump, and is characterized by mass concentration per unit volume or per unit area; is the target ice and snow form parameter, which is a composite parameter defining the physical properties of the ice and snow layer, such as thickness, density, ice crystal structure, etc. The ice and snow layer is dynamically deposited on the surface of the test sample by controlling the nozzle flow, air pressure, and water temperature of the snowmaking system. After obtaining the specific parameter values analyzed above, the control system starts to build a coupled environment field in the composite environment stress chamber. The core operation is to dynamically deposit an ice and snow layer on the surface of the test sample according to the target ice and snow form parameter , the snow or ice system in the cabin is started and regulated, and a layer of ice and snow with physical properties meeting the requirements is accurately deposited on the surface of the sample to be tested. This process is dynamic, meaning that the thickness, density, etc. of the ice and snow layer can be adjusted over time t. At the same time, almost synchronously, other environmental control units in the composite environmental stress cabin begin to work, which respectively adjust the temperature, humidity and light intensity in the cabin to strictly match the target temperature parameter, target humidity parameter and target light intensity parameter at the current time. At the same time, the snow-melting agent spraying system also sprays snow-melting agent with a corresponding concentration to the formed ice and snow layer according to the target snow-melting agent concentration parameter. The four kinds of environmental stresses are not independent, but interact with and couple with the deposited ice and snow layer, together forming a highly simulated multi-physical and chemical coupling environmental field acting on the sample to be tested.

[0028] Optionally, the generating the multi-dimensional monitoring data set comprises: acquiring surface temperature distribution of the sample to be tested and interface stress and strain data generated by frost heaving in the material-ice and snow interface micro area; acquiring ice and snow layer state data characterizing physical properties of the ice and snow layer; spatiotemporally registering and fusing the interface stress and strain data and the ice and snow layer state data to generate the multi-dimensional monitoring data set.

[0029] Specifically, first, the surface temperature distribution of the sample to be tested and the interface stress and strain data generated by frost heaving in the material-ice and snow interface micro area are acquired. The specific operation is to deploy a non-contact high-resolution infrared thermal imager inside the composite environmental stress cabin, continuously scan the surface of the sample to be tested, and generate a two-dimensional surface temperature distribution map. At the same time, an array of fiber Bragg grating sensors is pre-deployed on the surface of the sample to be tested. These sensors are pasted or embedded in the material surface layer before the ice and snow layer is deposited. When the ice and snow layer is formed and undergoes freezing and melting under temperature changes, its volume change, i.e. frost heaving effect, generates pressure on the material-ice and snow interface micro area, causing the surface of the sample to be tested to deform slightly. The fiber Bragg grating sensor can accurately capture this deformation, i.e. the interface stress and strain data. The measurement principle of the sensor is based on the shift of the Bragg wavelength, which can be characterized by the following formula: , Here, is the drift amount of the center reflection wavelength of the fiber Bragg grating sensor, which is directly measured by a spectrum analyzer or a grating demodulator. is the mechanical strain of the surface of the sample to be tested due to frost heaving, which is the core interface stress and strain data to be acquired. is the temperature change amount of the position where the sensor is located, which can be obtained by a strain-free grating deployed nearby or according to the surface temperature distribution data measured by the infrared thermal imager. is the strain sensitivity coefficient of the sensor, is the temperature sensitivity coefficient of the sensor, both of which are inherent calibration parameters of the grating sensor. Figure 3 As shown, through decoupling calculations, the drift caused by stress and strain can be accurately separated from the total wavelength drift, thereby obtaining interface stress and strain data. Secondly, the state data of the ice and snow layer, which characterizes the physical properties of the ice and snow layer, are simultaneously acquired. This can be achieved by integrating laser displacement sensors or 3D laser scanners within a composite environmental stress chamber to measure the thickness, coverage, and macromorphology of the ice and snow layer on the surface of the test sample in real time. Finally, the collected interface stress and strain data are spatiotemporally registered and fused with the ice and snow layer state data. Spatiotemporal registration involves unifying all sensor data to the same time reference and spatial coordinate system, ensuring that at any moment, the strain data at any point on the test sample surface accurately corresponds to the temperature at that point and the state data of the ice and snow layer above it. Data fusion integrates these registered multi-source heterogeneous data into a structured dataset, namely a multidimensional monitoring dataset, which can comprehensively and dynamically describe the response behavior of the test sample in the coupled environmental field.

[0030] Optionally, generating material response data representing a current state of the sample to be tested includes: Matching the interface stress-strain data with the material aging feature template to identify material aging state characteristics; Comparing the actual parameter data of the cabin environment in the multi-dimensional monitoring data set with the dynamic environment parameter set, and identifying the environmental simulation deviation characteristics according to the environmental simulation fidelity threshold; The material aging state characteristics and the environmental simulation deviation characteristics are structurally integrated to generate material response data.

[0031] Specifically, the process of generating the material response data representing the current state of the test sample is a deep analysis and information extraction of the multi-dimensional monitoring data set generated in the previous step. This process is divided into two parallel analysis streams, which are finally integrated. First, the interfacial stress-strain data contained in the multi-dimensional monitoring data set is matched with the pre-set material aging characteristic template to identify the material aging state characteristics. The material aging characteristic template here is a priori knowledge base established through a large number of experiments or theoretical analysis. It stores the typical patterns or characteristic signatures of the interfacial stress-strain signals of a specific material at different aging stages, such as stress amplitude, stress cycle frequency, strain accumulation rate, etc., and the corresponding relationship with the material micro-damage evolution, such as micro-crack initiation, interfacial debonding, etc. The matching process compares the real-time acquired interfacial stress-strain data stream with the characteristics in the template through pattern recognition algorithms. Once the current data pattern is highly consistent with the characteristic signature of a certain aging stage in the template, the system identifies the corresponding material aging state characteristics. Second, the actual parameter data of the cabin environment in the multi-dimensional monitoring data set is compared with the initially set dynamic environment parameter set to identify the environment simulation deviation characteristics. The actual parameter data of the cabin environment is derived from various sensors in the composite environmental stress cabin, such as thermometers, hygrometers, light intensity meters, etc., which collect real-time readings during the test. The comparison process calculates the deviation between the actual environment parameters and the target parameters. For any environmental parameter, the normalized deviation can be expressed as: , In this formula, is the normalized deviation, which is a dimensionless value used for subsequent threshold judgment. is the real-time value of the environmental parameter measured by the sensor, is the target value of the same time in the dynamic environment parameter set, and the two quantities have the same physical dimension. is the pre-set normalization factor of the environmental parameter, such as its variation range or a standard fluctuation amount within the entire test period, which is used to eliminate the influence of different parameter dimensions and numerical range differences. The system compares the calculated deviation with the pre-set environment simulation fidelity threshold value. If the deviation exceeds the threshold value, it is considered that there is a significant deviation in the environment simulation, and it is recorded as the environment simulation deviation characteristic. Finally, the results obtained from the above two analysis streams, i.e., the identified material aging state characteristics and environment simulation deviation characteristics, are structurally integrated. This integration is not a simple mathematical addition, but rather the combination of the two as independent but related information fields into a unified data structure, i.e., the material response data. This data structure completely describes the aging state of the test sample under what kind of environmental deviation.

[0032] Optionally, the generating of the environment parameter adjustment instruction set based on the material response data comprises: determining whether the material response data exceeds a material state safety threshold set to prevent non-realistic failure of the test sample; if yes, generating protective environmental adjustment instructions; if no, generating an accelerated parameter combination based on the material response data; integrating the protective environmental adjustment instructions or the accelerated parameter combination into an environmental parameter adjustment instruction set.

[0033] Specifically, a key safety assessment is first performed on the material response data. The system extracts a key indicator representing the material aging state feature from the material response data, such as the maximum interfacial stress or strain accumulation rate calculated from the interfacial stress-strain data, and compares it with a pre-set material state safety threshold. The threshold is set to prevent the test sample from experiencing a failure mode that does not correspond to the actual service environment under excessive accelerated stress, i.e., non-realistic failure. This judgment process can be represented as: wherein, represents a current material state quantitative indicator extracted from the material response data, such as the maximum interfacial stress value, which is updated in real time. is a material state safety threshold set in advance for the test sample, which has the same dimension as If the judgment result is yes, i.e., the current material state has approached or exceeded the safety limit, the system will determine that the test sample is at risk of non-realistic failure. At this time, the system will immediately generate a set of protective environmental adjustment instructions. The goal of this set of instructions is to reduce the stress level of the coupled environmental field, such as instructing the composite environmental stress chamber to reduce the cooling rate, reduce the light intensity, or suspend the application of snow melting agent, so as to return the state of the test sample to the safety range. If the judgment result is no, it indicates that the state of the test sample is stable, and the test can continue or even be accelerated. At this time, the system will calculate and generate an accelerated parameter combination based on the current material response data. This calculation process will comprehensively analyze the aging rate of the current material and the fidelity of the environmental simulation, aiming to find a new set of environmental parameter settings that can effectively improve the aging rate and shorten the test period, while ensuring that non-realistic failure is not triggered. Finally, whether it is the protective environmental adjustment instructions generated or the accelerated parameter combination calculated, they will be integrated into a standardized data package, i.e., an environmental parameter adjustment instruction set, to guide the real-time regulation of the coupled environmental field in the next step.

[0034] Optionally, the generating an accelerated parameter combination based on the material response data comprises: analyzing the material response data based on the material aging feature template to identify key stress factors related to the current stage material aging contribution; calculating an allowed increase of the action level of the key stress factor under the constraint of maintaining the real failure mechanism of the sample to be tested; increasing the action level of the key stress factor based on the allowed increase, and adjusting the environmental stress factors in a coordinated manner according to the physical coupling relationship among the environmental factors to generate the combination of acceleration parameters.

[0035] Specifically, the calculation and generation of the combination of acceleration parameters based on the material response data starts from the in-depth analysis of the material response data, aiming to identify the key stress factors that play a dominant role in the material aging at the current test stage. This identification process is based on a pre-set material aging feature template, which is a knowledge base containing the aging behavior patterns of the material under different environmental stresses. The system compares and analyzes the material aging state features contained in the material response data, such as the amplitude, frequency, and cumulative damage rate of the interface stress and strain, with the feature signatures in the template. Through correlation analysis or pattern recognition algorithms, the system can determine which one or several environmental stresses, such as temperature drop, ultraviolet radiation, or salt spray corrosion, are most closely related to the current aging phenomenon, thereby identifying these environmental stresses as the key stress factors at the current stage. After identifying the key stress factors, the next step is to calculate the allowed increase of the action level of these key stress factors under the constraint of maintaining the real failure mechanism of the sample to be tested. The real failure mechanism refers to the progressive damage process of the material that occurs in the actual service environment and conforms to its physical and chemical nature. In order to ensure the effectiveness of the test, the acceleration process cannot introduce non-natural failure modes, such as material melting due to excessively high temperature instead of aging. Therefore, the system needs to set a dynamic upper limit for each key stress factor based on the principles of material science and the failure boundaries defined in the material aging feature template. The calculation of the allowed increase can be expressed as: , wherein, is the allowed increase of the key stress factor k, which is the target value to be solved. is the current action level of the key stress factor in the composite environmental stress chamber, which can be directly obtained from system state monitoring. represents the current material state quantitative indicators extracted from the material response data. is the maximum action level that the key stress factor k can reach under the current material state . Exceeding this level may induce non-real failure. This upper limit value is a function that depends on the current health status of the material and is provided by the material aging feature template. The system calculates an value that can significantly accelerate aging while ensuring safety through optimization algorithms under this constraint. Finally, the system increases the action level of the key stress factor based on the calculated allowed increase to enhance the level of the key stress factor, and to adjust other environmental stress factors in a coordinated manner according to the physical coupling relationship between the environmental factors, and finally to generate an acceleration parameter combination. For example, if the key stress factor is temperature, the system will enhance it After that, the water vapor partial pressure in the cabin must be adjusted accordingly to maintain the accuracy of the target humidity parameter according to physical laws such as the saturation vapor pressure curve. This series of newly adjusted environmental parameter settings collectively constitutes an acceleration parameter combination for the next stage of testing.

[0036] Optionally, the real-time regulation of the coupled environmental field in the composite environmental stress chamber according to the environmental parameter adjustment instruction set comprises: Analyzing the environmental parameter adjustment instruction set and issuing regulation instructions to the environmental control system to dynamically regulate the deposition characteristics of the ice and snow layer; Synchronously regulating the operating state of the composite environmental stress chamber to reconstruct the multi-physical and chemical environmental stress.

[0037] Specifically, real-time regulation of the coupled environmental field in the composite environmental stress chamber according to the generated environmental parameter adjustment instruction set is the execution link of the closed-loop feedback control of the testing process. This process begins with the analysis of the environmental parameter adjustment instruction set by the control system. Here, analysis refers to the control system reading and decoding the structured data contained in the instruction set, extracting the specific target parameter values and rates for each environmental control subsystem, such as the new target temperature parameter, target humidity parameter, target light intensity parameter, target snow-melting agent concentration parameter, and target ice and snow morphology parameter. After analysis, the central controller converts these high-level instructions into bottom-layer regulation instructions that can be directly executed by hardware, and issues them to each environmental control system. A core operation is to dynamically regulate the deposition characteristics of the ice and snow layer. According to the new target ice and snow morphology parameter analyzed, the control system issues precise instructions to the snowmaking or ice-making system, which may include adjusting water supply flow, nozzle air pressure, water temperature, etc., to change the density, crystal type or deposition rate of the newly formed ice and snow, thereby directly adjusting the physical load applied to the test sample. At the same time, the control system synchronously regulates the overall operating state of the composite environmental stress chamber. This means that the refrigeration and heating systems, humidification and dehumidification systems, adjustable light source systems, and snow-melting agent spraying systems in the chamber will simultaneously adjust their output power or operating modes according to the new target values in the instruction set to reconstruct the multi-physical and chemical environmental stress. For example, when executing an acceleration parameter combination, the refrigeration system may cool at a faster rate, while the light source system increases the ultraviolet output intensity. The key to the entire process is synchronization and coordination, ensuring that all environmental stress changes are coordinated and consistent, collectively forming a new, instantaneous stable coupled environmental field that meets the requirements of the instructions.

[0038] Optionally, the method further comprises: In each test cycle, the system determines whether the material response data reaches a preset material failure threshold, or whether the accumulated test time reaches a preset maximum test period; When either of the two conditions is met, the system terminates the test.

[0039] Specifically, in each test cycle, the system makes two independent determinations in parallel. The first determination is based on the actual state of the sample under test. The system extracts from the latest material response data a key performance degradation indicator that quantifies the degree of material cumulative damage or performance degradation, and compares it with a preset material failure threshold. This determination can be expressed as: , wherein, is a key performance degradation indicator derived from the material response data, such as a cumulative damage variable calculated from the interface stress-strain data or the length of a crack on the material surface, which reflects the health state of the sample under test in real time. is a preset threshold value representing the state of complete failure of the material in engineering applications, and has the same dimension as . The second determination is based on the length of the test. The system queries the internal timer to obtain the accumulated test time since the start of the test, and compares it with a preset maximum test period. This determination can be expressed as: , wherein, is the accumulated time since the start of the test, which is directly provided by the system clock. is the longest allowed test time set for the current test, which is an actual constraint based on experimental economics or project cycle. The system combines the two determination conditions with a logical OR relationship. This means that, regardless of whether the performance degradation of the sample under test reaches the failure standard or the test time reaches the preset upper limit, as long as either of the two conditions is met first, the system will immediately generate a termination instruction that will stop all environmental simulation activities in the composite environmental stress chamber and end the entire weather resistance test process.

[0040] Based on the same inventive concept, as shown in Figure 4 , the present application also provides a low-temperature ice and snow environment material weather resistance test system, characterized in that the system comprises: an environmental data setting module for generating a set of dynamic environmental parameters according to an environmental simulation script, wherein the set of dynamic environmental parameters at least includes a target temperature parameter, a target humidity parameter, a target light intensity parameter, a target snow-melting agent concentration parameter, and a target ice and snow form parameter; an environmental coupling simulation module, configured to apply dynamic changing ice and snow loads and multi-physical and chemical environmental stresses in the preset composite environmental stress chamber according to the dynamic environmental parameter set, so as to construct a coupling environmental field acting on the test sample; a multi-dimensional in-situ monitoring module, configured to acquire the state of the test sample in the coupling environmental field in real time, and generate a multi-dimensional monitoring data set; a feedback module, configured to compare and analyze the multi-dimensional monitoring data set with a preset material aging characteristic template, and generate material response data representing the current state of the test sample; an instruction generation module, configured to generate an environmental parameter adjustment instruction set based on the material response data; an instruction execution module, configured to real-time regulate and control the coupling environmental field in the composite environmental stress chamber according to the environmental parameter adjustment instruction set.

[0041] In order to verify the feasibility, efficiency and high fidelity of the present application in implementation, the present application is applied to weather resistance test of a new type of aviation composite material. The composite material is planned to be used to manufacture the wings of unmanned aerial vehicles deployed in high-cold regions, which need to withstand the coupling action of various environmental stresses such as severe low temperature, ice and snow adhesion, freeze-thaw cycle and solar radiation during service. The traditional weather resistance test method usually uses constant or simple cycle stress conditions, which cannot truly reproduce the dynamic and coupled natural environment, resulting in long test period and large deviation of test results from actual service conditions. The present application aims to solve this problem and provide a fast and accurate weather resistance evaluation scheme.

[0042] In order to verify the effectiveness of the present application, a piece of 30cm*30cm new type of aviation composite material is selected as a test sample, and an accelerated weather resistance test of 500 hours is carried out. The dynamic regulation of environmental parameters, real-time response of materials and closed-loop feedback decision of the system are recorded during the test.

[0043] Before the test starts, the system first generates a 72-hour typical "snowstorm-sunny freeze-thaw" environmental simulation script according to the historical meteorological data of the target service area, i.e. a high mountain airport, through the environmental data setting module. The script is compiled into a dynamic environmental parameter set , which provides a target trajectory for the entire test.

[0044] After the test starts, the environmental coupling simulation module begins to work. At the first hour of the test, the system applies a 5mm-thick dry snow with a density of 0.2g / cm 3 to the surface of the test sample according to the parameters, and the snowmaking system in the instruction chamber deposits a layer of dry snow with a thickness of 5mm and a density of 0.2g / cm 3 on the surface of the test sample at the same time. Meanwhile, the temperature in the chamber is adjusted according to from 10°C to -15°C. In the next 12 hours, the system simulated a continuous snowfall and temperature drop process, and the ice and snow layer gradually increased to 20mm in thickness.

[0045] At the 13th hour of the test, the environmental scenario entered the "sunny freeze-thaw" phase. The parameter instruction cabin solar simulation lamp turned on, the light intensity reached 800 W / m 2 , simulating daytime solar radiation. The parameter instructed the cabin temperature to slowly rise from -15°C to 2°C. At this time, the multi-dimensional in-situ monitoring module played a key role. The fiber Bragg grating sensor array embedded in the surface layer of the composite material monitored the stress changes at the material-ice and snow interface in real time. The data showed that as the bottom of the ice and snow layer began to melt, the interface stress rapidly decreased from the peak value of 8 MPa in the frozen state, but due to the "ice wedge" effect caused by the refreezing of meltwater, local stress concentration occurred at the micro-pores of the material.

[0046] The feedback module received and analyzed this multi-dimensional monitoring data set in real time. The system compared the monitored 8 MPa interface stress with the pre-set material aging characteristic template and identified that this stress level was a key driving force for the initiation of micro-cracks in the material matrix, but had not yet exceeded the 15 MPa material state safety threshold set to prevent non-real failure (such as material yielding). At the same time, the system found through comparison that the actual temperature in the cabin was 2.2°C, which deviated from the target value of 2°C by 0.2°C, but this deviation was within the pre-set environmental simulation fidelity threshold of ±0.5°C. These information were integrated into a material response data.

[0047] Based on this material response data, the instruction generation module judged that the state of the material to be tested was stable and could be safely accelerated. The system started the acceleration parameter calculation and analyzed that the "temperature change rate" and "ultraviolet light intensity" were the main contributors to accelerating micro-crack propagation, i.e. the key stress factors; under the constraint of maintaining the real failure mechanism (fatigue crack propagation rather than thermal melting), the system calculated that the temperature drop rate could be increased from -5°C / h to -8°C / h, and the ultraviolet light intensity could be increased from 800 W / m 2 to 1000 W / m 2 ; the system generated an acceleration parameter combination containing the above new parameters, and adjusted the humidity parameter to match the new temperature curve, finally forming a complete set of environmental parameter adjustment instructions.

[0048] The instruction execution module parsed the instruction set and issued control instructions to the control system of the composite environmental stress cabin. The refrigeration system power was increased to achieve a temperature drop rate of -8°C / h; the solar simulation lamp power was increased, and the ultraviolet output was enhanced. The coupled environmental field was reconstructed in real time into a more challenging accelerated test environment.

[0049] The whole test runs in a continuous "monitoring-analysis-decision-regulation" closed loop. At the 482th hour of the test, the monitoring system detects a sharp increase in the propagation rate of a main crack on the material surface, and the calculated cumulative damage variable reaches the preset material failure threshold. The system automatically determines that the test is over, and saves all the test data.

[0050] To highlight the advantages of the present application, the test results are compared with those obtained by using the traditional constant low temperature cycle method. The traditional method takes 2000 hours and can only simulate a single freeze-thaw fatigue.

[0051] Table 1 Dynamic environmental parameter real-time regulation data

[0052] Table 2 Material response and system dynamic adjustment data

[0053] Table 3 Comparison of test results of the present application and the traditional method

[0054] As can be seen from the data in Tables 1-3 above, the method of the present application exhibits significant advantages. Table 1 demonstrates the high precision dynamic tracking capability of the system for complex environmental parameters. Table 2 clearly shows the process of intelligent decision-making and closed-loop feedback adjustment of the system based on real-time material response, achieving "thousand materials and thousand faces" in the test process, ensuring safety and efficiency. The comparison results in Table 3 show that the test length of the present application is shortened by about 75%, but through intelligent acceleration, the estimated equivalent service life is longer, and the observed failure mode is more complex and closer to the real situation, containing multiple coupled damages, thus providing more accurate and comprehensive data support for material life prediction and reliability design than the traditional method. These data results fully demonstrate the efficiency, high fidelity and intelligent advantages of the present application in material weather resistance testing.

[0055] It should be noted that the above formulas can be translated into unitless standard values or same-dimension superimposable parameters by means of dimensional consistency principle and mathematical standardization means (such as normalization processing, dimensionless parameter conversion or unit system unification), so as to eliminate the interference of different dimensions on the operation logic, make the formula have mathematical operation rationality and objective law adaptability while retaining the original data distribution characteristics. It is a conventional technical means, and will not be repeated here. The electrical connections between the above-mentioned units do not necessarily represent direct connections, and indirect connection methods can also be used as long as the purpose of the present application is achieved. The above-described are only exemplary embodiments of the present application, and cannot limit the scope of the present application.

[0056] That is, any equivalents of the above described subject matter, as well as other modifications and variations that can occur to those skilled in the art are intended to be covered. Other embodiments of the application will be apparent to those skilled in the art from consideration of the specification and practice of the application disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the application being indicated by the following claims.

Claims

1. A method for testing the weather resistance of materials in low-temperature ice and snow environments, characterized in that: The method comprises: Generate a dynamic environmental parameter set according to the environmental simulation script, wherein the dynamic environmental parameter set includes at least a target temperature parameter, a target humidity parameter, a target light intensity parameter, a target deicing agent concentration parameter, and a target ice and snow morphology parameter; According to the dynamic environmental parameter set, dynamically changing ice and snow loads and multi-physical and chemical environmental stresses are applied in a preset composite environmental stress chamber to construct a coupled environmental field acting on the sample to be tested; Acquire the state of the sample to be tested in the coupled environment field in real time to generate a multi-dimensional monitoring data set; Comparing and analyzing the multi-dimensional monitoring data set with a preset material aging characteristic template to generate material response data representing the current state of the sample to be tested; generating an environmental parameter adjustment instruction set based on the material response data; The coupled environmental field in the composite environmental stress chamber is regulated in real time according to the environmental parameter adjustment instruction set.

2. The method for testing the weather resistance of materials in a low-temperature ice and snow environment according to claim 1, characterized in that: The construction of the coupled environment field acting on the sample to be tested includes: parsing the dynamic environmental parameter set to obtain target ice and snow morphology parameters, target temperature parameters, target humidity parameters, target light intensity parameters, and target snow melting agent concentration parameters; Dynamically depositing an ice and snow layer on the surface of the test sample according to the target ice and snow morphological parameters; The environmental parameters in the preset composite environmental stress chamber are synchronously adjusted to match the target temperature parameter, the target humidity parameter, the target light intensity parameter, and the target snow melting agent concentration parameter, thereby forming a coupled environmental field together with the ice and snow layer.

3. The method for testing the weather resistance of materials in a low-temperature ice and snow environment according to claim 2, characterized in that: Generating a multi-dimensional monitoring data set includes: Obtaining the surface temperature distribution of the test sample and the interface stress and strain data generated by frost heave in the material-ice and snow interface microregion; Acquiring ice and snow layer state data representing physical properties of the ice and snow layer; The interface stress and strain data are temporally and spatially registered and fused with the ice and snow layer status data to generate the multi-dimensional monitoring data set.

4. The method for testing the weather resistance of materials in a low-temperature ice and snow environment according to claim 3, characterized in that: Generating material response data representing the current state of the sample to be tested includes: Matching the interface stress-strain data with the material aging feature template to identify material aging state characteristics; Comparing the actual parameter data of the cabin environment in the multi-dimensional monitoring data set with the dynamic environment parameter set, and identifying the environmental simulation deviation characteristics according to the environmental simulation fidelity threshold; The material aging state characteristics and the environmental simulation deviation characteristics are structurally integrated to generate material response data.

5. The method for testing the weather resistance of materials in a low-temperature ice and snow environment according to claim 4, characterized in that: Generating an environmental parameter adjustment instruction set based on the material response data includes: Determining whether the material response data exceeds a material state safety threshold set to prevent a non-real failure of the test sample; If so, a protective environment adjustment instruction is generated; If not, calculating and generating an acceleration parameter combination based on the material response data; The protective environment adjustment instructions or the acceleration parameter combination are integrated into an environment parameter adjustment instruction set.

6. The method for testing the weather resistance of materials in a low-temperature ice and snow environment according to claim 5, characterized in that: The generating of the acceleration parameter combination by calculation according to the material response data comprises: Analyzing the material response data based on the material aging characteristic template to identify key stress factors related to the material aging contribution at the current stage; Under the constraint of maintaining the true failure mechanism of the test sample, calculating the allowable increase in the action level of the key stress factor; The action level of the key stress factor is increased based on the allowable increase, and the environmental stress factor is adjusted in a coordinated manner according to the physical coupling relationship between the environmental factors to generate the acceleration parameter combination.

7. The method for testing the weather resistance of materials in a low-temperature ice and snow environment according to claim 6, characterized in that: The real-time regulation of the coupled environmental field in the composite environmental stress chamber according to the environmental parameter adjustment instruction set includes: parsing the environmental parameter adjustment instruction set, issuing control instructions to the environmental control system, and dynamically controlling the deposition characteristics of the ice and snow layer; The operating state of the composite environmental stress chamber is synchronously regulated to reconstruct multiple physical and chemical environmental stresses.

8. The method for testing the weather resistance of materials in a low-temperature ice and snow environment according to claim 7, characterized in that: The method further comprises: In each test cycle, determining whether the material response data reaches a preset material failure threshold, or determining whether the accumulated test time reaches a preset maximum test period; When any of the judgment conditions is met, the test is terminated.

9. A material weather resistance testing system based on low temperature ice and snow environment, characterized in that: The system comprises: An environmental data setting module is used to generate a dynamic environmental parameter set according to an environmental simulation script, wherein the dynamic environmental parameter set includes at least a target temperature parameter, a target humidity parameter, a target light intensity parameter, a target deicing agent concentration parameter, and a target ice and snow morphology parameter; An environmental coupling simulation module is used to apply dynamically changing ice and snow loads and multi-physical and chemical environmental stresses in a preset composite environmental stress chamber based on the dynamic environmental parameter set, thereby constructing a coupled environmental field acting on the sample to be tested; A multi-dimensional in-situ monitoring module is used to obtain the state of the test sample in the coupled environment field in real time and generate a multi-dimensional monitoring data set; A feedback module is used to compare and analyze the multi-dimensional monitoring data set with a preset material aging characteristic template to generate material response data representing the current state of the test sample; An instruction generation module, configured to generate an environmental parameter adjustment instruction set based on the material response data; An instruction execution module is used to adjust an instruction set according to the environmental parameters and regulate the coupled environmental field in the composite environmental stress chamber in real time.

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