Method for controlling weather resistance of automotive trim part based on xenon lamp test

Abstract

The invention provides a method for controlling the weather resistance of an automobile interior part based on a xenon lamp test, and relates to the technical field of the weather resistance of the automobile interior part, the weather resistance test is performed on the automobile interior part through a xenon lamp, the weather resistance test data is collected, and the life cycle of the weather resistance of the interior part is established; splitting is carried out to obtain a plurality of observation periods, a sliding window is set to carry out weather resistance data monitoring on each observation period, weather resistance monitoring data is obtained, and then weather resistance abnormal nodes are obtained; establishing a weather resistance trend chart, determining weather resistance fluctuation data, obtaining the number of weather resistance abnormal nodes, and performing normal or abnormal labeling on preset parameters according to the number of the weather resistance abnormal nodes; according to the method, the aging rate factor is calculated, then the test adjustment coefficient is calculated, the preset parameter is adjusted according to the test adjustment coefficient, and then the weather resistance adjustment parameter is obtained, so that the accuracy and comprehensiveness of the test are improved, and the flexibility of weather resistance evaluation and adjustment is enhanced.

Description

Technical Field

[0001] The invention proposes a method for controlling the weather resistance of automobile interior decoration parts based on a xenon lamp test, and relates to the technical field of weather resistance of automobile interior decoration parts, and specifically to the technical field of controlling the weather resistance of automobile interior decoration parts based on a xenon lamp test. Background Art

[0002] With the rapid development of the automobile industry, consumers have increasing requirements for the durability and appearance retention of automobile interior parts. Interior parts such as plastics, leather, fabrics, etc. will be affected by various environmental factors such as light, temperature, humidity, etc. during long-term use, resulting in aging phenomena such as fading, discoloration, and strength loss, which seriously affect the appearance and service life of the car. Therefore, it has become an important issue for automobile manufacturers and suppliers to conduct weather resistance tests on automobile interior parts, evaluate their performance changes under different environmental conditions, and select materials and optimize processes accordingly. The weather resistance test of traditional automobile interior parts is usually an overall test. The test results are obtained at the end of the test and cannot be analyzed and adjusted based on real-time data. It has low intelligence and flexibility. Summary of the invention

[0003] The present invention provides a method for controlling the weather resistance of automobile interior parts based on a xenon lamp test, which is used to solve the problems that the weather resistance test of traditional automobile interior parts is usually an overall test, the test results are obtained at the end of the test, and it is impossible to analyze and adjust according to real-time data, and the intelligence and flexibility are low. The present invention provides a method for controlling the weather resistance of automobile interior parts based on a xenon lamp test, the method comprising: S1. Performing a weather resistance test on automobile interior components by using a xenon lamp, collecting weather resistance test data, and establishing a weather resistance life cycle of the interior components according to the monitoring time of the weather resistance test data; S2. Obtain multiple aging index thresholds, split the weather resistance life cycle of the interior component, obtain multiple observation periods, set a sliding window to monitor weather resistance data for each observation period, obtain weather resistance monitoring data, and then obtain weather resistance abnormality nodes; S3, establishing a weather resistance trend graph, determining weather resistance fluctuation data, obtaining the number of weather resistance abnormal nodes, and marking the preset parameters as normal or abnormal according to the number of weather resistance abnormal nodes; S4. Calculate the aging rate factor, and then calculate the test adjustment coefficient, adjust the preset parameters according to the test adjustment coefficient, and then obtain the weather resistance adjustment parameter.

[0004] Further, the S1 includes: Perform weather resistance tests on different interior parts of automobiles made of different materials using xenon lamps with different preset parameters, and collect weather resistance test data of different interior parts made of different materials under different preset parameters; The weather resistance life cycle of each type of interior trim component is obtained according to the monitoring start time of the weather resistance test data to the monitoring end time of the weather resistance test data.

[0005] Further, the S2 includes: Obtaining weather resistance index thresholds of multiple stages for each type of interior components, and splitting the weather resistance life cycle of each type of interior components according to the weather resistance index thresholds to obtain multiple observation periods; A sliding window is set for each observation period, and weather resistance data of the observation period is monitored through the sliding window to obtain weather resistance monitoring data; Comparing the weather resistance monitoring data with a preset monitoring threshold to obtain a weather resistance comparison result; According to the weather resistance comparison result, the weather resistance abnormal node is obtained, and according to the weather resistance abnormal node, the weather resistance abnormal node is marked on the weather resistance monitoring data to obtain the abnormal node marking information.

[0006] Further, the S3 includes: With weather resistance monitoring data as the ordinate and preset parameters as the abscissa, a weather resistance trend graph is established; Obtaining a preset fluctuation threshold range, and determining weather resistance fluctuation data according to the preset fluctuation preset range; Obtaining the number of abnormal weather resistance nodes in the weather resistance fluctuation data; When the number of abnormal weather resistance nodes is greater than or equal to 1, the preset parameters corresponding to the abnormal weather resistance nodes are marked as abnormal parameters; When the number of abnormal weather resistance nodes is 0, the preset parameters corresponding to the abnormal weather resistance nodes are marked as normal parameters.

[0007] Further, the S4 includes: Calculating an aging rate factor based on the weather resistance fluctuation data combined with weather resistance abnormal node data; Comparing the aging rate factor with a preset rate threshold to obtain aging rate comparison information; Calculate a test adjustment coefficient according to the aging rate factor, the aging rate comparison information and the preset parameter information; The corresponding preset parameters are adjusted according to the test adjustment coefficient to obtain an adjustment result.

[0008] Furthermore, the system comprises: A periodic test module, used to perform weather resistance test on automobile interior parts by xenon lamp, collect weather resistance test data, and establish weather resistance life cycle of interior parts according to the monitoring time of the weather resistance test data; A split monitoring module is used to obtain multiple aging index thresholds, split the weather resistance life cycle of the interior component, obtain multiple observation periods, set a sliding window to monitor the weather resistance data of each observation period, obtain weather resistance monitoring data, and then obtain weather resistance abnormal nodes; The fluctuation anomaly marking module is used to establish a weather resistance trend chart, determine the weather resistance fluctuation data, obtain the number of weather resistance anomaly nodes, and mark the preset parameters as normal or abnormal according to the number of weather resistance anomaly nodes; The calculation and adjustment module is used to calculate the aging rate factor, and then calculate the test adjustment coefficient, adjust the preset parameters according to the test adjustment coefficient, and then obtain the weather resistance adjustment parameter.

[0009] Furthermore, the periodic test module includes: A test collection module, used to perform weather resistance tests on different interior parts of automobiles made of different materials by using xenon lamps with different preset parameters, and collect weather resistance test data of different interior parts made of different materials under different preset parameters; The cycle establishment module is used to obtain the weather resistance life cycle of each type of interior decoration parts according to the monitoring start time of the weather resistance test data to the monitoring end time of the weather resistance test data.

[0010] Furthermore, the split monitoring module includes: A cycle splitting module, used to obtain weather resistance index thresholds of multiple stages for each type of interior parts, and split the weather resistance life cycle of each type of interior parts according to the weather resistance index thresholds to obtain multiple observation cycles; A sliding monitoring module, used to set a sliding window for each observation period, monitor the weather resistance data of the observation period through the sliding window, and obtain weather resistance monitoring data; An abnormal comparison module is used to compare the weather resistance monitoring data with a preset monitoring threshold to obtain a weather resistance comparison result; According to the weather resistance comparison result, the weather resistance abnormal node is obtained, and according to the weather resistance abnormal node, the weather resistance abnormal node is marked on the weather resistance monitoring data to obtain the abnormal node marking information.

[0011] Furthermore, the fluctuation anomaly marking module includes: A trend establishment module is used to establish a weather resistance trend graph with weather resistance monitoring data as the ordinate and preset parameters as the abscissa; A node quantity acquisition module, used to acquire a preset fluctuation threshold range, and determine weather resistance fluctuation data according to the preset fluctuation preset range; Obtaining the number of abnormal weather resistance nodes in the weather resistance fluctuation data; A node parameter marking module is used to mark the preset parameters corresponding to the weather resistance abnormal nodes as abnormal parameters when the number of weather resistance abnormal nodes is greater than or equal to 1; When the number of abnormal weather resistance nodes is 0, the preset parameters corresponding to the abnormal weather resistance nodes are marked as normal parameters.

[0012] Furthermore, the calculation and adjustment module includes: A factor calculation module, used to calculate an aging rate factor based on the weather resistance fluctuation data combined with the weather resistance abnormal node data; Comparing the aging rate factor with a preset rate threshold to obtain aging rate comparison information; An adjustment calculation module, used to calculate a test adjustment coefficient according to the aging rate factor, aging rate comparison information and preset parameter information; The adjustment module is used to adjust the corresponding preset parameters according to the test adjustment coefficient to obtain the adjustment result.

[0013] Beneficial effects of the present invention: By simulating the lighting conditions in the actual use environment, combined with sophisticated data monitoring and analysis, this method can more accurately evaluate the weather resistance of automotive interior components and reduce misjudgments and missed judgments. Based on detailed weather resistance test data and life cycle models, designers can improve the material selection and structural design of interior components in a targeted manner to improve their durability and anti-aging capabilities. By quickly identifying and adjusting test conditions, this method can accelerate the product testing and verification process, shorten the research and development cycle of automotive interior components, and reduce costs. High-quality weather resistance test data helps to improve the overall quality and market competitiveness of automotive products and meet consumer demand for high-quality automotive interiors. By optimizing the weather resistance of interior components and reducing the frequency of replacement due to material aging and performance degradation, it helps to achieve the sustainable development goals of the automotive industry. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 A schematic diagram of a method for controlling the weather resistance of automotive interior parts based on a xenon lamp test; Figure 2 Schematic diagram of weather resistance trend. DETAILED DESCRIPTION

[0015] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0016] One embodiment of the present invention provides a method for controlling the weather resistance of automobile interior parts based on a xenon lamp test, the method comprising: S1. Performing a weather resistance test on automobile interior components by using a xenon lamp, collecting weather resistance test data, and establishing a weather resistance life cycle of the interior components according to the monitoring time of the weather resistance test data; S2. Obtain multiple aging index thresholds, split the weather resistance life cycle of the interior component, obtain multiple observation periods, set a sliding window to monitor weather resistance data for each observation period, obtain weather resistance monitoring data, and then obtain weather resistance abnormality nodes; S3, establishing a weather resistance trend graph, determining weather resistance fluctuation data, obtaining the number of weather resistance abnormal nodes, and marking the preset parameters as normal or abnormal according to the number of weather resistance abnormal nodes; S4, calculate the aging rate factor, and then calculate the test adjustment coefficient, adjust the preset parameters according to the test adjustment coefficient, and then obtain the weather resistance adjustment parameters. Obtain the weather resistance parameters of different types of interior parts of different materials under different environmental information, and then obtain the adjustment data of both sides, such as Figure 1 shown.

[0017] The working principle of the above technical solution is: xenon lamp equipment is used to simulate the lighting conditions in the natural environment to conduct long-term weather resistance tests on automotive interior parts. By collecting various data during the test (such as color changes, material hardness, tensile strength, etc.), and based on the change trend of these data over time, a weather resistance life cycle model of interior parts is established. This model reflects the performance status of the parts at different time points. In order to analyze the changes in the weather resistance performance of interior parts more carefully, the life cycle is divided into multiple observation cycles. In each observation cycle, the sliding window technology is used to monitor the weather resistance data in real time. This method can dynamically capture the change trend of the data and timely discover abnormal nodes (data outside the threshold). By constructing a weather resistance trend chart, the change of component performance over time is intuitively displayed. The fluctuation data in the trend chart is analyzed to determine the number and location of weather resistance abnormal nodes. Based on the number of these abnormal nodes, the preset parameters are marked as normal or abnormal for subsequent adjustment. The aging rate factor is calculated to evaluate the aging speed of the interior parts. Then, the test adjustment coefficient is calculated based on the aging rate, which is used to adjust the preset parameters (such as test time, light intensity, etc.) to obtain more accurate weather resistance adjustment parameters. This step aims to optimize the test conditions so that the test results can better reflect the actual use. Taking into account the different environmental information and the differences in the materials of interior components, the weather resistance parameters under different conditions are collected and analyzed. Through comprehensive evaluation, more comprehensive and accurate two-way adjustment data are obtained to provide a scientific basis for the design and production of automotive interior components.

[0018] The technical effect of the above technical solution is: by simulating the lighting conditions in the actual use environment, combined with sophisticated data monitoring and analysis, this method can more accurately evaluate the weather resistance of automotive interior parts and reduce misjudgments and missed judgments. Based on detailed weather resistance test data and life cycle models, designers can improve the material selection and structural design of interior parts in a targeted manner to improve their durability and anti-aging capabilities. By quickly identifying and adjusting test conditions, this method can accelerate the product testing and verification process, shorten the research and development cycle of automotive interior parts, and reduce costs. High-quality weather resistance test data helps to improve the overall quality and market competitiveness of automotive products and meet consumer demand for high-quality automotive interiors. By optimizing the weather resistance of interior parts and reducing the frequency of replacement due to material aging and performance degradation, it helps to achieve the sustainable development goals of the automotive industry.

[0019] In one embodiment of the present invention, the S1 includes: Perform weather resistance tests on different interior parts of automobiles made of different materials using xenon lamps with different preset parameters, and collect weather resistance test data of different interior parts made of different materials under different preset parameters; The weather resistance life cycle of each type of interior trim component is obtained according to the monitoring start time of the weather resistance test data to the monitoring end time of the weather resistance test data.

[0020] The working principle of the above technical solution is: prepare xenon lamp test equipment with multiple preset parameter configurations, which may include light intensity, spectral distribution, temperature, humidity, and test cycle. At the same time, prepare samples of automotive interior parts of various materials, such as plastic, leather, fabric, etc., and ensure that each material covers different types of interior parts (such as dashboards, seat fabrics, door panel decorations, etc.). Each interior part sample is placed in a xenon lamp test equipment under preset parameters for weather resistance testing. During the test, the weather resistance test data of each sample is continuously collected, which may include performance indicators in multiple aspects such as color change, hardness loss, tensile strength, and crack formation. According to the monitoring start and end time of the test data, combined with the performance change trend of the sample during the test, the weather resistance life cycle of each interior part under each preset parameter is obtained. This life cycle reflects the time period from the initial state to the significant performance degradation or failure of the sample.

[0021] The technical effect of the above technical solution is that the weather resistance of automotive interior parts under different use conditions can be comprehensively evaluated through combined tests of different preset parameters and different materials. This comprehensiveness helps to more accurately understand the actual service life and performance of the parts. The test results provide a scientific basis for the material selection of automotive interior parts. By comparing the performance of different materials under the same test conditions, better and more durable materials can be selected, thereby improving the overall quality of automotive interiors. Understanding the weather resistance life cycle of interior parts helps designers more accurately predict the performance changes of parts during use, thereby optimizing the structural design of parts and improving their durability and reliability. The test results can also guide the production process of automotive interior parts. By adjusting the production process and quality control standards, it is ensured that the produced parts can meet the expected weather resistance requirements. Through continuous testing and data accumulation, the continuous innovation of automotive interior materials and technologies can be promoted. For example, new weather resistance test methods can be developed, the performance of xenon lamp test equipment can be improved, etc., so as to more efficiently evaluate and optimize the weather resistance of interior parts. This method not only helps to improve the quality and performance of automotive interior parts, but also promotes technological progress and sustainable development of the entire automotive industry.

[0022] In one embodiment of the present invention, S2 includes: Obtaining weather resistance index thresholds of multiple stages for each type of interior components, and splitting the weather resistance life cycle of each type of interior components according to the weather resistance index thresholds to obtain multiple observation periods; A sliding window is set for each observation period, and weather resistance data of the observation period is monitored through the sliding window to obtain weather resistance monitoring data; Comparing the weather resistance monitoring data with a preset monitoring threshold to obtain a weather resistance comparison result; According to the weather resistance comparison result, the weather resistance abnormal node is obtained, and according to the weather resistance abnormal node, the weather resistance abnormal node is marked on the weather resistance monitoring data to obtain the abnormal node marking information.

[0023] When the weather resistance monitoring data is greater than a preset monitoring threshold, marking the weather resistance abnormal node for the weather resistance monitoring data; When the weather resistance monitoring data is less than or equal to a preset monitoring threshold, the weather resistance monitoring data is marked as a normal weather resistance node.

[0024] The weather resistance monitoring data includes the degree of fading, the degree of discoloration or the extent of strength reduction, etc.

[0025] The working principle of the above technical solution is: according to the type of interior parts (such as plastic, leather, fabric, etc.) and the expected performance standards, multiple stages of weather resistance index thresholds are set. These thresholds may include different stage boundaries of key performance indicators such as the degree of fading, the degree of discoloration, and the magnitude of strength reduction. Using the set weather resistance index thresholds, the weather resistance life cycle of each type of interior parts is divided into multiple observation cycles. Each observation cycle represents a specific stage of component performance change, which helps to monitor and analyze its weather resistance changes in more detail. In each observation cycle, a sliding window is set to monitor the data in real time. The sliding window technology allows dynamic capture of data changes to ensure that the latest weather resistance monitoring data can be obtained at any time point. The weather resistance monitoring data captured by the sliding window is compared with the preset monitoring threshold. If the monitoring data is greater than the preset threshold, it is considered that weather resistance anomaly occurs at this time point, and the abnormal node is marked; if the monitoring data is less than or equal to the preset threshold, the normal node is marked. This process helps identify the time point (i.e., abnormal node) when the performance suddenly decreases or changes significantly. By marking the weather resistance monitoring data, abnormal node marking information is generated. This information is of great value for subsequent performance analysis, troubleshooting, and product design optimization.

[0026] The technical effect of the above technical solution is: by setting weather resistance index thresholds at multiple stages and using sliding window technology for real-time monitoring, refined monitoring of weather resistance changes of interior parts is achieved. This helps to capture the details and abnormal points of performance changes more accurately. By timely discovering and marking weather resistance abnormal nodes, the technology can warn of possible performance problems of interior parts in advance. This helps manufacturers take remedial measures before the problem worsens, avoiding product quality problems and customer complaints. Based on the abnormal node marking information, manufacturers can optimize the design, materials and production processes of interior parts. By improving these factors, the weather resistance and overall quality of the parts can be improved. It provides strong support for data-driven decision-making. By collecting and analyzing a large amount of weather resistance monitoring data, manufacturers can formulate product improvement plans and quality control standards more scientifically. By improving the weather resistance and overall quality of interior parts, this technology helps to enhance the market competitiveness of automotive products. High-quality interior parts can enhance consumers' willingness to buy and satisfaction, thereby driving sales growth and improving brand reputation.

[0027] In one embodiment of the present invention, S3 includes: With the weather resistance monitoring data as the vertical axis and the preset parameters as the horizontal axis, a weather resistance trend chart is established, such as Figure 2 As shown; Obtain a preset fluctuation threshold range, and determine the weather resistance fluctuation data according to the preset fluctuation preset range; the preset fluctuation threshold range is used for fluctuation comparison, and can be compared with multiple fluctuation data. If the abnormal node is not within the fluctuation range, its number is not obtained.

[0028] Obtaining the number of abnormal weather resistance nodes in the weather resistance fluctuation data; When the number of abnormal weather resistance nodes is greater than or equal to 1, the preset parameters corresponding to the abnormal weather resistance nodes are marked as abnormal parameters; When the number of abnormal weather resistance nodes is 0, the preset parameters corresponding to the abnormal weather resistance nodes are marked as normal parameters.

[0029] The working principle of the above technical solution is: using weather resistance monitoring data (such as fading degree, discoloration degree, intensity reduction, etc.) as the horizontal axis and preset parameters (such as light intensity, temperature, humidity, etc.) as the vertical axis, a two-dimensional weather resistance trend chart is established. This chart intuitively shows the changing trend of the weather resistance performance of interior parts under different preset parameter conditions. In order to identify the fluctuations in the trend chart, a preset fluctuation threshold range needs to be set. This range defines what is a normal performance fluctuation and what is an abnormal fluctuation. By comparing the actual data in the trend chart with the preset fluctuation threshold range, it can be determined which data points belong to the weather resistance fluctuation data. After determining the weather resistance fluctuation data, the weather resistance abnormal nodes are identified in the preset fluctuation threshold range. The number of these abnormal nodes is counted to evaluate the degree of influence of the preset parameters on the weather resistance performance of the interior parts. According to the number of weather resistance abnormal nodes, the preset parameters are marked. If the number of weather resistance abnormal nodes is greater than or equal to 1, it means that under the preset parameter conditions, the weather resistance performance of the interior parts has abnormal fluctuations, so the preset parameter is marked as an abnormal parameter. On the contrary, if the number of abnormal weather resistance nodes is 0, it means that under the preset parameter conditions, the weather resistance performance of the interior parts is stable and there is no abnormal fluctuation, so the preset parameter is marked as a normal parameter.

[0030] The technical effect of the above technical solution is: the weathering trend graph graphically and intuitively displays the changing trend of the weathering performance of interior parts under different preset parameters, which is convenient for researchers and engineers to quickly understand the data. By setting the preset fluctuation threshold range and counting the number of weathering abnormal nodes, the technology can accurately identify the preset parameter conditions under which the weathering performance of interior parts has abnormal fluctuations, providing a strong basis for subsequent parameter adjustment and optimization. Based on the weathering trend graph and the annotation results of abnormal parameters, manufacturers can adjust and optimize the preset parameter settings in a targeted manner to improve the weathering performance and overall quality of interior parts. By promptly discovering and correcting abnormal problems in the preset parameters, the technology helps to reduce performance problems of interior parts caused by improper parameter settings, thereby improving the overall quality and reliability of automotive products. This method provides a new idea and method for weathering testing and analysis of automotive interior parts, which helps to promote the innovation and development of related technologies.

[0031] In one embodiment of the present invention, the S4 includes: Calculating an aging rate factor based on the weather resistance fluctuation data combined with weather resistance abnormal node data; The calculation formula of the aging rate factor is:

[0032] Among them, LHY is the aging rate factor, BO max BO is the maximum value of the fluctuation data within the fluctuation range. min is the minimum value of the fluctuation data within the fluctuation range, FN gl is the number of abnormal nodes within the fluctuation range, FW gl is the number of abnormal nodes outside the fluctuation range, ZJ gl is the normal number of nodes; Comparing the aging rate factor with a preset rate threshold to obtain aging rate comparison information; Calculate a test adjustment coefficient according to the aging rate factor, the aging rate comparison information and the preset parameter information; The calculation formula of the test adjustment coefficient is:

[0033] Among them, CTX is the test adjustment coefficient, CS ys is the preset parameter, LYZ is the preset rate threshold; The corresponding preset parameters are adjusted according to the test adjustment coefficient to obtain an adjustment result.

[0034] In order to fully evaluate the weather resistance of interior parts, the above process needs to be repeated, but for different environmental information (such as temperature, humidity, light, etc.), different types of interior parts (such as seat fabrics, dashboard materials, etc.) and different materials (such as leather, plastic, fabric, etc.). This will generate a large amount of weather resistance data, which is of great significance for the design, production and quality control of interior parts.

[0035] "Two-sided adjustment data" may refer to taking into account both the characteristics of the interior parts themselves (such as materials, structure, etc.) and the impact of external environmental conditions on the performance of the parts. By combining these two factors, the weather resistance of interior parts can be more accurately evaluated and a more scientific and reasonable adjustment strategy can be formulated. This adjustment strategy not only helps to improve the weather resistance of interior parts, but also reduces production costs and improves product quality.

[0036] Based on the above data, the abnormal weather resistance data is determined, and the weather resistance of the material is enhanced by adding additives such as stabilizers, antioxidants, and UV absorbers.

[0037] Adjust the structural design of components to reduce stress concentrations and the potential for crack formation.

[0038] Surface treatment technologies such as coating and plating are used to improve the weather resistance and aesthetics of components.

[0039] Optimize production process parameters such as temperature, pressure, time, etc. to improve product quality and consistency.

[0040] The formulated adjustment strategy is implemented to improve the materials, structure, surface treatment and production process of interior parts. During the improvement process, it is necessary to pay close attention to the performance changes of the product and make necessary adjustments and optimizations.

[0041] The adjusted interior parts are retested to verify whether their weather resistance has been improved. At the same time, the impact of the adjustment measures on production costs and product quality is evaluated to ensure the economy and feasibility of the adjustment strategy.

[0042] Weathering adjustment of interior parts is an ongoing process. With the continuous development of materials science, environmental science and testing technology, it is necessary to keep paying attention to new research results and technological progress, and continuously optimize and improve the adjustment strategy.

[0043] The working principle of the above technical solution is: according to the weather resistance fluctuation data and the weather resistance abnormal node data, the aging rate factor is calculated. This factor reflects the aging speed or performance degradation degree of the interior parts under specific preset parameters. The calculated aging rate factor is compared with the preset rate threshold. The preset rate threshold is set based on experience, industry standards or design requirements, and is used to determine whether the current aging rate is acceptable or needs to be adjusted. If the aging rate factor exceeds the preset rate threshold, it is necessary to calculate the test adjustment coefficient based on the aging rate factor, the aging rate comparison information and the preset parameter information. This coefficient is used to guide how to adjust the preset parameters to slow down the aging rate or improve the weather resistance performance. According to the calculated test adjustment coefficient, the corresponding preset parameters are adjusted. The direction and amplitude of the adjustment are determined by the test adjustment coefficient, which aims to return the aging rate of the interior parts during the test to an acceptable range, or to further optimize their weather resistance performance. The preset parameters are adjusted to obtain the status of interior parts of different materials under different environments, providing a data comparison basis for weather resistance adjustment.

[0044] The technical effect of the above technical solution is that by calculating the aging rate factor and comparing it with the preset rate threshold, the aging of interior parts under specific preset parameters can be more accurately evaluated, thereby avoiding misjudgment or omission of test results. or The larger the aging rate factor is, the larger the aging rate factor is. The aging rate factor can be calculated in each sliding window or in the entire cycle. The corresponding data can be flexibly selected for calculation. Dynamic adjustment of preset parameters based on the aging rate factor and the test adjustment coefficient can ensure that the test process is always kept in the best state and improve the efficiency and accuracy of the test. Relatively speaking, when the formula The larger the value, the greater the adjustment range. By optimizing the test parameters and processes, the aging of interior parts in the actual use environment can be more accurately simulated, thereby helping manufacturers to promptly discover and solve potential quality problems and improve the overall quality and reliability of products. This workflow provides a new idea and method for weather resistance testing of automotive interior parts, which helps promote the innovation and development of related technologies and provides strong support for the formulation and improvement of industry standards. By accurately adjusting the test parameters, unnecessary test times and resource waste can be reduced, thereby reducing test costs and improving the economic benefits of testing.

[0045] In one embodiment of the present invention, the system comprises: A periodic test module, used to perform weather resistance test on automobile interior parts by xenon lamp, collect weather resistance test data, and establish weather resistance life cycle of interior parts according to the monitoring time of the weather resistance test data; A split monitoring module is used to obtain multiple aging index thresholds, split the weather resistance life cycle of the interior component, obtain multiple observation periods, set a sliding window to monitor the weather resistance data of each observation period, obtain weather resistance monitoring data, and then obtain weather resistance abnormal nodes; The fluctuation anomaly marking module is used to establish a weather resistance trend chart, determine the weather resistance fluctuation data, obtain the number of weather resistance anomaly nodes, and mark the preset parameters as normal or abnormal according to the number of weather resistance anomaly nodes; The calculation and adjustment module is used to calculate the aging rate factor, and then calculate the test adjustment coefficient, adjust the preset parameters according to the test adjustment coefficient, and then obtain the weather resistance adjustment parameters. The weather resistance parameters of interior parts of different types and materials under different environmental information are obtained, and then the adjustment data of both sides is obtained.

[0046] The working principle of the above technical solution is: xenon lamp equipment is used to simulate the lighting conditions in the natural environment to conduct long-term weather resistance tests on automotive interior parts. By collecting various data during the test (such as color changes, material hardness, tensile strength, etc.), and based on the change trend of these data over time, a weather resistance life cycle model of interior parts is established. This model reflects the performance status of the parts at different time points. In order to analyze the changes in the weather resistance performance of interior parts more carefully, the life cycle is divided into multiple observation cycles. In each observation cycle, the sliding window technology is used to monitor the weather resistance data in real time. This method can dynamically capture the change trend of the data and timely discover abnormal nodes (data outside the threshold). By constructing a weather resistance trend chart, the change of component performance over time is intuitively displayed. The fluctuation data in the trend chart is analyzed to determine the number and location of weather resistance abnormal nodes. Based on the number of these abnormal nodes, the preset parameters are marked as normal or abnormal for subsequent adjustment. The aging rate factor is calculated to evaluate the aging speed of the interior parts. Then, the test adjustment coefficient is calculated based on the aging rate, which is used to adjust the preset parameters (such as test time, light intensity, etc.) to obtain more accurate weather resistance adjustment parameters. This step aims to optimize the test conditions so that the test results can better reflect the actual use. Taking into account the different environmental information and the differences in the materials of interior components, the weather resistance parameters under different conditions are collected and analyzed. Through comprehensive evaluation, more comprehensive and accurate two-way adjustment data are obtained to provide a scientific basis for the design and production of automotive interior components.

[0047] The technical effect of the above technical solution is: by simulating the lighting conditions in the actual use environment, combined with sophisticated data monitoring and analysis, this method can more accurately evaluate the weather resistance of automotive interior parts and reduce misjudgments and missed judgments. Based on detailed weather resistance test data and life cycle models, designers can improve the material selection and structural design of interior parts in a targeted manner to improve their durability and anti-aging capabilities. By quickly identifying and adjusting test conditions, this method can accelerate the product testing and verification process, shorten the research and development cycle of automotive interior parts, and reduce costs. High-quality weather resistance test data helps to improve the overall quality and market competitiveness of automotive products and meet consumer demand for high-quality automotive interiors. By optimizing the weather resistance of interior parts and reducing the frequency of replacement due to material aging and performance degradation, it helps to achieve the sustainable development goals of the automotive industry.

[0048] In one embodiment of the present invention, the periodic test module includes: A test collection module, used to perform weather resistance tests on different interior parts of automobiles made of different materials by using xenon lamps with different preset parameters, and collect weather resistance test data of different interior parts made of different materials under different preset parameters; The cycle establishment module is used to obtain the weather resistance life cycle of each type of interior decoration parts according to the monitoring start time of the weather resistance test data to the monitoring end time of the weather resistance test data.

[0049] The working principle of the above technical solution is: prepare xenon lamp test equipment with multiple preset parameter configurations, which may include light intensity, spectral distribution, temperature, humidity, and test cycle. At the same time, prepare samples of automotive interior parts of various materials, such as plastic, leather, fabric, etc., and ensure that each material covers different types of interior parts (such as dashboards, seat fabrics, door panel decorations, etc.). Each interior part sample is placed in a xenon lamp test equipment under preset parameters for weather resistance testing. During the test, the weather resistance test data of each sample is continuously collected, which may include performance indicators in multiple aspects such as color change, hardness loss, tensile strength, and crack formation. According to the monitoring start and end time of the test data, combined with the performance change trend of the sample during the test, the weather resistance life cycle of each interior part under each preset parameter is obtained. This life cycle reflects the time period from the initial state to the significant performance degradation or failure of the sample.

[0050] The technical effect of the above technical solution is that the weather resistance of automotive interior parts under different use conditions can be comprehensively evaluated through combined tests of different preset parameters and different materials. This comprehensiveness helps to more accurately understand the actual service life and performance of the parts. The test results provide a scientific basis for the material selection of automotive interior parts. By comparing the performance of different materials under the same test conditions, better and more durable materials can be selected, thereby improving the overall quality of automotive interiors. Understanding the weather resistance life cycle of interior parts helps designers more accurately predict the performance changes of parts during use, thereby optimizing the structural design of parts and improving their durability and reliability. The test results can also guide the production process of automotive interior parts. By adjusting the production process and quality control standards, it is ensured that the produced parts can meet the expected weather resistance requirements. Through continuous testing and data accumulation, the continuous innovation of automotive interior materials and technologies can be promoted. For example, new weather resistance test methods can be developed, the performance of xenon lamp test equipment can be improved, etc., so as to more efficiently evaluate and optimize the weather resistance of interior parts. This method not only helps to improve the quality and performance of automotive interior parts, but also promotes technological progress and sustainable development of the entire automotive industry.

[0051] In one embodiment of the present invention, the split monitoring module includes: A cycle splitting module, used to obtain weather resistance index thresholds of multiple stages for each type of interior parts, and split the weather resistance life cycle of each type of interior parts according to the weather resistance index thresholds to obtain multiple observation cycles; A sliding monitoring module, used to set a sliding window for each observation period, monitor the weather resistance data of the observation period through the sliding window, and obtain weather resistance monitoring data; An abnormal comparison module is used to compare the weather resistance monitoring data with a preset monitoring threshold to obtain a weather resistance comparison result; According to the weather resistance comparison result, the weather resistance abnormal node is obtained, and according to the weather resistance abnormal node, the weather resistance abnormal node is marked on the weather resistance monitoring data to obtain the abnormal node marking information.

[0052] When the weather resistance monitoring data is greater than a preset monitoring threshold, marking the weather resistance abnormal node for the weather resistance monitoring data; When the weather resistance monitoring data is less than or equal to a preset monitoring threshold, the weather resistance monitoring data is marked as a normal weather resistance node.

[0053] The weather resistance monitoring data includes the degree of fading, the degree of discoloration or the extent of strength reduction, etc.

[0054] The working principle of the above technical solution is: according to the type of interior parts (such as plastic, leather, fabric, etc.) and the expected performance standards, multiple stages of weather resistance index thresholds are set. These thresholds may include different stage boundaries of key performance indicators such as the degree of fading, the degree of discoloration, and the magnitude of strength reduction. Using the set weather resistance index thresholds, the weather resistance life cycle of each type of interior parts is divided into multiple observation cycles. Each observation cycle represents a specific stage of component performance change, which helps to monitor and analyze its weather resistance changes in more detail. In each observation cycle, a sliding window is set to monitor the data in real time. The sliding window technology allows dynamic capture of data changes to ensure that the latest weather resistance monitoring data can be obtained at any time point. The weather resistance monitoring data captured by the sliding window is compared with the preset monitoring threshold. If the monitoring data is greater than the preset threshold, it is considered that weather resistance anomaly occurs at this time point, and the abnormal node is marked; if the monitoring data is less than or equal to the preset threshold, the normal node is marked. This process helps identify the time point (i.e., abnormal node) when the performance suddenly decreases or changes significantly. By marking the weather resistance monitoring data, abnormal node marking information is generated. This information is of great value for subsequent performance analysis, troubleshooting, and product design optimization.

[0055] The technical effect of the above technical solution is: by setting weather resistance index thresholds at multiple stages and using sliding window technology for real-time monitoring, refined monitoring of weather resistance changes of interior parts is achieved. This helps to capture the details and abnormal points of performance changes more accurately. By timely discovering and marking weather resistance abnormal nodes, the technology can warn of possible performance problems of interior parts in advance. This helps manufacturers take remedial measures before the problem worsens, avoiding product quality problems and customer complaints. Based on the abnormal node marking information, manufacturers can optimize the design, materials and production processes of interior parts. By improving these factors, the weather resistance and overall quality of the parts can be improved. It provides strong support for data-driven decision-making. By collecting and analyzing a large amount of weather resistance monitoring data, manufacturers can formulate product improvement plans and quality control standards more scientifically. By improving the weather resistance and overall quality of interior parts, this technology helps to enhance the market competitiveness of automotive products. High-quality interior parts can enhance consumers' willingness to buy and satisfaction, thereby driving sales growth and improving brand reputation.

[0056] In one embodiment of the present invention, the fluctuation anomaly marking module includes: A trend establishment module is used to establish a weather resistance trend graph with weather resistance monitoring data as the ordinate and preset parameters as the abscissa; A node quantity acquisition module, used to acquire a preset fluctuation threshold range, and determine weather resistance fluctuation data according to the preset fluctuation preset range; Obtaining the number of abnormal weather resistance nodes in the weather resistance fluctuation data; A node parameter marking module is used to mark the preset parameters corresponding to the weather resistance abnormal nodes as abnormal parameters when the number of weather resistance abnormal nodes is greater than or equal to 1; When the number of abnormal weather resistance nodes is 0, the preset parameters corresponding to the abnormal weather resistance nodes are marked as normal parameters.

[0057] The working principle of the above technical solution is: using weather resistance monitoring data (such as fading degree, discoloration degree, intensity reduction, etc.) as the horizontal axis and preset parameters (such as light intensity, temperature, humidity, etc.) as the vertical axis, a two-dimensional weather resistance trend chart is established. This chart intuitively shows the changing trend of the weather resistance performance of interior parts under different preset parameter conditions. In order to identify the fluctuations in the trend chart, a preset fluctuation threshold range needs to be set. This range defines what is a normal performance fluctuation and what is an abnormal fluctuation. By comparing the actual data in the trend chart with the preset fluctuation threshold range, it can be determined which data points belong to the weather resistance fluctuation data. After determining the weather resistance fluctuation data, the weather resistance abnormal nodes are identified in the preset fluctuation threshold range. The number of these abnormal nodes is counted to evaluate the degree of influence of the preset parameters on the weather resistance performance of the interior parts. According to the number of weather resistance abnormal nodes, the preset parameters are marked. If the number of weather resistance abnormal nodes is greater than or equal to 1, it means that under the preset parameter conditions, the weather resistance performance of the interior parts has abnormal fluctuations, so the preset parameter is marked as an abnormal parameter. On the contrary, if the number of abnormal weather resistance nodes is 0, it means that under the preset parameter conditions, the weather resistance performance of the interior parts is stable and there is no abnormal fluctuation, so the preset parameter is marked as a normal parameter.

[0058] The technical effect of the above technical solution is: the weathering trend graph graphically and intuitively displays the changing trend of the weathering performance of interior parts under different preset parameters, which is convenient for researchers and engineers to quickly understand the data. By setting the preset fluctuation threshold range and counting the number of weathering abnormal nodes, the technology can accurately identify the preset parameter conditions under which the weathering performance of interior parts has abnormal fluctuations, providing a strong basis for subsequent parameter adjustment and optimization. Based on the weathering trend graph and the annotation results of abnormal parameters, manufacturers can adjust and optimize the preset parameter settings in a targeted manner to improve the weathering performance and overall quality of interior parts. By promptly discovering and correcting abnormal problems in the preset parameters, the technology helps to reduce performance problems of interior parts caused by improper parameter settings, thereby improving the overall quality and reliability of automotive products. This method provides a new idea and method for weathering testing and analysis of automotive interior parts, which helps to promote the innovation and development of related technologies.

[0059] In one embodiment of the present invention, the calculation and adjustment module includes: A factor calculation module, used to calculate an aging rate factor based on the weather resistance fluctuation data combined with the weather resistance abnormal node data; The calculation formula of the aging rate factor is:

[0060] Among them, LHY is the aging rate factor, BO max BO is the maximum value of the fluctuation data within the fluctuation range. min is the minimum value of the fluctuation data within the fluctuation range, FN gl is the number of abnormal nodes within the fluctuation range, FW gl is the number of abnormal nodes outside the fluctuation range, ZJ gl is the normal number of nodes; Comparing the aging rate factor with a preset rate threshold to obtain aging rate comparison information; An adjustment calculation module, used to calculate a test adjustment coefficient according to the aging rate factor, aging rate comparison information and preset parameter information; The calculation formula of the test adjustment coefficient is:

[0061] Among them, CTX is the test adjustment coefficient, CS ys is the preset parameter, LYZ is the preset rate threshold; The adjustment module is used to adjust the corresponding preset parameters according to the test adjustment coefficient to obtain the adjustment result.

[0062] The working principle of the above technical solution is: according to the weather resistance fluctuation data and the weather resistance abnormal node data, the aging rate factor is calculated. This factor reflects the aging speed or performance degradation degree of the interior parts under specific preset parameters. The calculated aging rate factor is compared with the preset rate threshold. The preset rate threshold is set based on experience, industry standards or design requirements, and is used to determine whether the current aging rate is acceptable or needs to be adjusted. If the aging rate factor exceeds the preset rate threshold, it is necessary to calculate the test adjustment coefficient based on the aging rate factor, the aging rate comparison information and the preset parameter information. This coefficient is used to guide how to adjust the preset parameters to slow down the aging rate or improve the weather resistance performance. According to the calculated test adjustment coefficient, the corresponding preset parameters are adjusted. The direction and amplitude of the adjustment are determined by the test adjustment coefficient, which aims to return the aging rate of the interior parts during the test to an acceptable range, or to further optimize their weather resistance performance. The preset parameters are adjusted to obtain the status of interior parts of different materials under different environments, providing a data comparison basis for weather resistance adjustment.

[0063] The technical effect of the above technical solution is: by calculating the aging rate factor and comparing it with the preset rate threshold, the aging of interior parts under specific preset parameters can be more accurately evaluated, thereby avoiding misjudgment or omission of test results. Dynamic adjustment of preset parameters according to the aging rate factor and the test adjustment coefficient can ensure that the test process is always kept in the best state, improving the efficiency and accuracy of the test. By optimizing the test parameters and processes, the aging of interior parts in the actual use environment can be more accurately simulated, thereby helping manufacturers to promptly discover and solve potential quality problems and improve the overall quality and reliability of the product. This workflow provides a new idea and method for weather resistance testing of automotive interior parts, helps promote the innovation and development of related technologies, and provides strong support for the formulation and improvement of industry standards. By accurately adjusting the test parameters, unnecessary test times and resource waste can be reduced, thereby reducing test costs and improving the economic benefits of testing.

[0064] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for controlling the weather resistance of automobile interior parts based on a xenon lamp test, characterized in that: The method comprises: S1. Performing a weather resistance test on automobile interior components by using a xenon lamp, collecting weather resistance test data, and establishing a weather resistance life cycle of the interior components according to the monitoring time of the weather resistance test data; S2. Obtain multiple aging index thresholds, split the weather resistance life cycle of the interior component, obtain multiple observation periods, set a sliding window to monitor weather resistance data for each observation period, obtain weather resistance monitoring data, and then obtain weather resistance abnormality nodes; S3, establishing a weather resistance trend graph, determining weather resistance fluctuation data, obtaining the number of weather resistance abnormal nodes, and marking the preset parameters as normal or abnormal according to the number of weather resistance abnormal nodes; S4. Calculate the aging rate factor, and then calculate the test adjustment coefficient, adjust the preset parameters according to the test adjustment coefficient, and then obtain the weather resistance adjustment parameter.

2. The method for controlling the weather resistance of automobile interior parts based on the xenon lamp test according to claim 1, characterized in that: The S1 includes: Perform weather resistance tests on different interior parts of automobiles made of different materials using xenon lamps with different preset parameters, and collect weather resistance test data of different interior parts made of different materials under different preset parameters; The weather resistance life cycle of each type of interior trim component is obtained according to the monitoring start time of the weather resistance test data to the monitoring end time of the weather resistance test data.

3. The method for controlling the weather resistance of automobile interior parts based on the xenon lamp test according to claim 1, characterized in that: The S2 includes: Obtaining weather resistance index thresholds of multiple stages for each type of interior components, and splitting the weather resistance life cycle of each type of interior components according to the weather resistance index thresholds to obtain multiple observation periods; A sliding window is set for each observation period, and weather resistance data of the observation period is monitored through the sliding window to obtain weather resistance monitoring data; Comparing the weather resistance monitoring data with a preset monitoring threshold to obtain a weather resistance comparison result; According to the weather resistance comparison result, the weather resistance abnormal node is obtained, and according to the weather resistance abnormal node, the weather resistance abnormal node is marked on the weather resistance monitoring data to obtain the abnormal node marking information.

4. The method for controlling the weather resistance of automobile interior parts based on the xenon lamp test according to claim 1, characterized in that: The S3 includes: With weather resistance monitoring data as the ordinate and preset parameters as the abscissa, a weather resistance trend graph is established; Obtaining a preset fluctuation threshold range, and determining weather resistance fluctuation data according to the preset fluctuation preset range; Obtaining the number of abnormal weather resistance nodes in the weather resistance fluctuation data; When the number of abnormal weather resistance nodes is greater than or equal to 1, the preset parameters corresponding to the abnormal weather resistance nodes are marked as abnormal parameters; When the number of abnormal weather resistance nodes is 0, the preset parameters corresponding to the abnormal weather resistance nodes are marked as normal parameters.

5. The method for controlling the weather resistance of automobile interior parts based on the xenon lamp test according to claim 1, characterized in that: The S4 includes: Calculating an aging rate factor based on the weather resistance fluctuation data combined with weather resistance abnormal node data; Comparing the aging rate factor with a preset rate threshold to obtain aging rate comparison information; Calculate a test adjustment coefficient according to the aging rate factor, the aging rate comparison information and the preset parameter information; The corresponding preset parameters are adjusted according to the test adjustment coefficient to obtain an adjustment result.

6. A system for implementing the method for controlling the weather resistance of automobile interior parts based on the xenon lamp test as claimed in claim 1, characterized in that: The system comprises: A periodic test module, used to perform weather resistance test on automobile interior parts by xenon lamp, collect weather resistance test data, and establish weather resistance life cycle of interior parts according to the monitoring time of the weather resistance test data; A split monitoring module is used to obtain multiple aging index thresholds, split the weather resistance life cycle of the interior component, obtain multiple observation periods, set a sliding window to monitor the weather resistance data of each observation period, obtain weather resistance monitoring data, and then obtain weather resistance abnormal nodes; The fluctuation anomaly marking module is used to establish a weather resistance trend chart, determine the weather resistance fluctuation data, obtain the number of weather resistance anomaly nodes, and mark the preset parameters as normal or abnormal according to the number of weather resistance anomaly nodes; The calculation and adjustment module is used to calculate the aging rate factor, and then calculate the test adjustment coefficient, adjust the preset parameters according to the test adjustment coefficient, and then obtain the weather resistance adjustment parameter.

7. The system of claim 6, wherein the method for controlling the weather resistance of automobile interior parts based on the xenon lamp test is characterized in that: The periodic test module includes: A test collection module, used to perform weather resistance tests on different interior parts of automobiles made of different materials by using xenon lamps with different preset parameters, and collect weather resistance test data of different interior parts made of different materials under different preset parameters; The cycle establishment module is used to obtain the weather resistance life cycle of each type of interior decoration parts according to the monitoring start time of the weather resistance test data to the monitoring end time of the weather resistance test data.

8. The system of claim 6, wherein the method for controlling the weather resistance of automobile interior parts based on the xenon lamp test is characterized in that: The split monitoring module includes: A cycle splitting module, used to obtain weather resistance index thresholds of multiple stages for each type of interior parts, and split the weather resistance life cycle of each type of interior parts according to the weather resistance index thresholds to obtain multiple observation cycles; A sliding monitoring module, used to set a sliding window for each observation period, monitor the weather resistance data of the observation period through the sliding window, and obtain weather resistance monitoring data; An abnormal comparison module is used to compare the weather resistance monitoring data with a preset monitoring threshold to obtain a weather resistance comparison result; According to the weather resistance comparison result, the weather resistance abnormal node is obtained, and according to the weather resistance abnormal node, the weather resistance abnormal node is marked on the weather resistance monitoring data to obtain the abnormal node marking information.

9. The system of claim 6, wherein the method for controlling the weather resistance of automobile interior parts based on the xenon lamp test is characterized in that: The fluctuation anomaly marking module includes: A trend establishment module is used to establish a weather resistance trend graph with weather resistance monitoring data as the ordinate and preset parameters as the abscissa; A node quantity acquisition module, used to acquire a preset fluctuation threshold range, and determine weather resistance fluctuation data according to the preset fluctuation preset range; Obtaining the number of abnormal weather resistance nodes in the weather resistance fluctuation data; A node parameter marking module is used to mark the preset parameters corresponding to the weather resistance abnormal nodes as abnormal parameters when the number of weather resistance abnormal nodes is greater than or equal to 1; When the number of abnormal weather resistance nodes is 0, the preset parameters corresponding to the abnormal weather resistance nodes are marked as normal parameters.

10. The system of claim 6, wherein the method for controlling the weather resistance of automobile interior parts based on the xenon lamp test is characterized in that: The calculation and adjustment module comprises: A factor calculation module, used to calculate an aging rate factor based on the weather resistance fluctuation data combined with the weather resistance abnormal node data; Comparing the aging rate factor with a preset rate threshold to obtain aging rate comparison information; An adjustment calculation module, used to calculate a test adjustment coefficient according to the aging rate factor, aging rate comparison information and preset parameter information; The adjustment module is used to adjust the corresponding preset parameters according to the test adjustment coefficient to obtain the adjustment result.

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