Electronic paper display film material performance detection system based on temperature fluctuation analysis

Abstract

The invention belongs to the technical field of electronic paper display membrane material detection, and particularly relates to an electronic paper display membrane material performance detection system based on temperature fluctuation analysis. Comprising a temperature gradient precise temperature control module, a membrane material parameter multi-dimensional detection and acquisition module, a self-adaptive preprocessing module, a membrane material performance dynamic analysis module, a result intelligent output module and an intelligent management and control end, according to the method, core performance parameters are accurately captured by providing stable and fit temperature conditions for membrane material performance detection, a high-quality data set is generated by eliminating original data defects, deep correlation analysis of performance and temperature is realized by taking preprocessed data and real-time temperature fluctuation data as supports, an analysis report is visually presented, and the detection accuracy is improved. A structured detection report is generated, qualification judgment is completed according to the standard, dynamic and precise detection of the performance of the membrane material is achieved, and the controllability of the detection process and the reliability of the result are remarkably improved.

Description

Technical Field

[0001] This invention relates to the field of electronic paper display film material testing technology, specifically an electronic paper display film material performance testing system based on temperature fluctuation analysis. Background Technology

[0002] Electronic paper displays, with their core advantages such as low power consumption, paper-like visual effects, and flexibility, have been widely used in many fields such as e-book readers, smart shelf labels, automotive displays, and wearable devices. Film materials are a core component of electronic paper displays, so accurate testing of film material performance is a key link in ensuring the quality of electronic paper products.

[0003] However, when testing the performance of electronic paper display film materials, most testing systems only conduct static performance tests at a fixed room temperature (such as the industry-standard 25°C), completely ignoring the temperature fluctuations faced by the film materials in actual use. This results in test results that are out of touch with real application scenarios and cannot reflect the performance stability of the film materials under dynamic temperature environments.

[0004] Furthermore, while some current solutions attempt to introduce temperature variables, they lack real-time monitoring and early warning mechanisms for the temperature control process, affecting the reliability of the evaluation results. They also cannot quantify the impact of dynamic temperature changes on the overall performance of the film material, making it difficult to achieve dynamic and accurate evaluation of the film material performance. Consequently, they cannot provide reliable data support for the R&D optimization and production quality control of electronic paper display film materials. Therefore, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to provide a performance testing system for electronic paper display film materials based on temperature fluctuation analysis, so as to solve the above-mentioned technical defects.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a performance testing system for electronic paper display film materials based on temperature fluctuation analysis, comprising a precise temperature gradient control module, a multi-dimensional detection and acquisition module for film material parameters, an adaptive preprocessing module, a dynamic analysis module for film material performance, an intelligent output module for results, and an intelligent control terminal; The temperature gradient precision temperature control module precisely regulates the ambient temperature of the testing environment according to the preset temperature fluctuation curve, providing a stable temperature environment that conforms to the simulated scenario for the performance testing of electronic paper display film materials; The multi-dimensional detection and acquisition module for membrane material parameters collects three key performance parameters of the membrane material—transmittance, response speed, and haze—under the temperature environment provided by the temperature gradient precise temperature control module, and outputs the raw dataset. The adaptive preprocessing module performs noise removal, outlier correction, and data standardization on the raw acquired data to generate a high-quality preprocessed dataset. The membrane material performance dynamic analysis module generates a membrane material performance dynamic analysis report based on the preprocessed dataset and real-time temperature information. The result intelligent output module visualizes the membrane material performance dynamic analysis report and judges whether the membrane material performance is qualified according to preset standards, and sends the test results to the intelligent control terminal.

[0007] Furthermore, the multi-dimensional detection and acquisition module for membrane parameters receives real-time temperature data output by the temperature gradient precision temperature control module. When the temperature inside the detection chamber reaches the preset stable condition, the parameter acquisition process is triggered. Data is acquired based on the built-in transmittance detection unit, response speed detection unit, and haze detection unit. Each acquired data is accompanied by the current temperature value and acquisition timestamp to form the raw dataset and transmit it to the adaptive preprocessing module.

[0008] Furthermore, the transmittance detection unit emits detection light of a specific wavelength, which passes through the film material to be tested and is captured by the receiving sensor to calculate the transmittance value; the response speed detection unit captures the pixel switching process of the film material under the drive of the electrical signal to determine the time for the film material to switch from "black state" to "white state"; the haze detection unit calculates the haze value by measuring the intensity of scattered light and transmitted light of the film material to the detection light.

[0009] Furthermore, the specific operation process of the membrane material performance dynamic analysis module is as follows: It receives the preprocessed dataset output by the adaptive preprocessing module and the real-time temperature fluctuation data output by the temperature gradient precise temperature control module; it constructs a dynamic analysis model of membrane material performance and introduces the membrane material performance comprehensive evaluation index EI as the core analysis indicator. The EI value is calculated every 30 seconds, and the changing trend of the EI value with temperature fluctuation rate V and fluctuation period T is analyzed. A dynamic analysis report of membrane material performance is generated and transmitted to the intelligent output module.

[0010] Furthermore, the analysis and calculation process of the membrane material performance comprehensive evaluation index EI is as follows: The transmittance change rate ΔTt, response speed change rate ΔTr, and haze change rate ΔH were obtained through change rate calculation and analysis. Based on ΔTt, ΔTr, and ΔH, the comprehensive performance evaluation index EI of the membrane material was obtained through calculation.

[0011] Furthermore, the specific analytical process for calculating and analyzing the rate of change is as follows: The transmittance of the membrane material at the start of the test is obtained and marked as the initial transmittance. The current transmittance of the membrane material is also collected. The transmittance change rate ΔTt is calculated by the transmittance change rate = (initial transmittance - current transmittance) / initial transmittance × 100%. The response speed of the membrane material at the start of the test is obtained and marked as the initial response speed. The current response speed of the membrane material is also collected. The response speed change rate ΔTr is calculated by the response speed change rate = (current response speed - initial response speed) / initial response speed × 100%. The haze value of the membrane material at the start of the test is obtained and marked as the initial haze. The current haze of the membrane material is also collected. The haze change rate ΔH is calculated by haze change rate = (current haze - initial haze) / initial haze × 100%.

[0012] Furthermore, the intelligent output module receives the dynamic analysis report of membrane material performance and displays the EI change curve, the change rate curve of each parameter, and the temperature fluctuation curve in the form of charts through the built-in visualization engine. The analysis report is then structured, generating a structured test report in the format of "membrane material number - test time - temperature fluctuation parameters - change rate of each performance parameter - EI curve - pass / fail judgment result". The pass / fail judgment is based on the preset industry standard, comparing the data in the membrane material performance dynamic analysis report with the standard and outputting the pass or fail judgment result. Finally, the visualization charts, structured test report and pass / fail judgment result are stored in the local database, and the test results are sent to the intelligent control terminal for display.

[0013] Furthermore, the intelligent control terminal is connected to the temperature control overlap warning module. The temperature control overlap warning module evaluates and analyzes the temperature control performance of the detection cavity within a unit of time. Through analysis, it determines whether a temperature control abnormality signal is generated. When a temperature control abnormality signal is generated, it is sent to the intelligent control terminal. When the intelligent control terminal receives the temperature control abnormality signal, it issues a corresponding warning.

[0014] Furthermore, the specific analysis process of the temperature control overlap warning module is as follows: The actual temperature curve and preset temperature fluctuation curve of the detection cavity are obtained from the temperature gradient precise temperature control module within a unit time. The actual temperature curve and the preset temperature fluctuation curve are overlapped to obtain the proportion of non-overlapping trajectories and mark them as temperature track abnormality values. If the temperature track abnormality value exceeds the preset temperature track abnormality threshold, a temperature control abnormality signal is generated. If the temperature track abnormality value does not exceed the preset temperature track abnormality threshold, the intersection area formed by the actual temperature curve and the preset temperature fluctuation curve is obtained. The area of ​​the corresponding intersection area is marked as the intersection coefficient. The number of intersection areas whose intersection coefficient exceeds the preset intersection coefficient threshold is marked as the intersection risk frequency value. The intersection coefficients of all intersection areas are summed to obtain the intersection surface value, and the intersection coefficient with the largest value is marked as the intersection amplitude value. The temperature control intersection characteristic value is obtained by weighted summation of the intersection risk frequency value, the intersection surface value, and the intersection amplitude value. If the temperature control intersection characteristic value exceeds the preset temperature control intersection characteristic threshold, a temperature control abnormality signal is generated.

[0015] Compared with the prior art, the beneficial effects of the present invention are: In this invention, by providing stable and suitable temperature conditions for membrane material performance testing to accurately capture core performance parameters, eliminating defects in the original data, conducting in-depth correlation analysis between performance and temperature, and visualizing the analysis report, a structured test report is generated and qualified judgment is completed according to standards, thereby realizing dynamic and precise testing of membrane material performance and significantly improving the controllability of the testing process and the reliability of the results.

[0016] In this invention, the temperature control coincidence early warning module evaluates and analyzes the temperature control performance of the detection chamber to determine whether an abnormal temperature control signal is generated. When an abnormal temperature control signal is generated, the testing personnel are reminded to investigate and analyze the situation and take corresponding control and improvement measures to ensure the stability of the testing environment and indirectly ensure the reliability of the entire testing process and the accuracy of the performance testing results. Attached Figure Description

[0017] To facilitate understanding by those skilled in the art, the present invention will be further described below with reference to the accompanying drawings; Figure 1 This is a system block diagram of Embodiment 1 of the present invention; Figure 2 This is a system block diagram of Embodiment 2 of the present invention. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Example 1: As Figure 1As shown, the electronic paper display film material performance testing system based on temperature fluctuation analysis proposed in this invention includes a temperature gradient precise temperature control module, a multi-dimensional detection and acquisition module for film material parameters, an adaptive preprocessing module, a film material performance dynamic analysis module, a result intelligent output module, and an intelligent control terminal. Specifically, the temperature gradient precision temperature control module precisely regulates the ambient temperature of the testing environment according to the preset temperature fluctuation curve, providing a stable temperature environment that conforms to the simulated scenario for the performance testing of electronic paper display film materials. This ensures the accuracy of the performance test results from the source, and sends the temperature control information to the intelligent management terminal, as well as supporting manual intervention control at the intelligent management terminal.

[0020] The multi-dimensional detection and acquisition module for membrane material parameters collects three key performance parameters—transmittance, response speed, and haze—within the temperature environment provided by the precise temperature gradient control module. It outputs raw datasets, ensuring comprehensive parameter acquisition and providing traceable data support for subsequent correlation analysis between performance and temperature fluctuations. The specific operation process is as follows: The system receives real-time temperature data from the temperature gradient precision temperature control module. When the temperature inside the detection chamber reaches the preset stable condition (temperature is 25℃, temperature fluctuation ≤0.1℃ / min, lasting for 5min), the parameter detection and acquisition process is triggered: data is acquired based on the built-in transmittance detection unit, response speed detection unit, and haze detection unit. Each acquired data is accompanied by the current temperature value and acquisition timestamp to form the raw dataset and transmit it to the adaptive preprocessing module.

[0021] It should be noted that the transmittance detection unit (using a UV-Vis spectrophotometer, wavelength range 400–700 nm, accuracy ±0.1%) emits detection light of a specific wavelength, which passes through the film material to be tested and is captured by the receiving sensor to calculate the transmittance value; where transmittance = (transmitted light intensity / incident light intensity) × 100%; The response speed detection unit (using a high-speed camera with a frame rate of 1000fps) captures the pixel switching process of the film material under the drive of an electrical signal (the driving voltage is consistent with the actual working voltage of the electronic paper, which is adjustable from 1.5 to 5V). By analyzing the changes in pixel grayscale values ​​in adjacent frames, the time it takes for the film material to switch from a "black state" to a "white state" is determined, i.e., the response speed. The haze detection unit (using an integrating sphere haze meter with an accuracy of ±0.01%) calculates the haze value by measuring the intensity of scattered light and transmitted light from the membrane material to the detection light. The haze value is calculated as: haze = scattered light intensity / (transmitted light intensity + scattered light intensity) × 100%.

[0022] The adaptive preprocessing module performs noise removal, outlier correction, and data standardization on the raw collected data to generate a high-quality preprocessed dataset. This effectively eliminates data defects and transforms the scattered and disordered raw data into a high-quality, highly consistent preprocessed dataset, clearing data obstacles for the membrane material performance dynamic analysis module to perform accurate analysis.

[0023] The membrane material performance dynamic analysis module, based on preprocessed datasets and real-time temperature information, generates a dynamic analysis report of membrane material performance. This overcomes the limitations of static analysis based on single parameters or fixed temperatures, achieving in-depth correlation analysis between performance and temperature fluctuations. The specific operation and analysis process is as follows: The system receives preprocessed datasets from the adaptive preprocessing module and real-time temperature fluctuation data from the temperature gradient precise temperature control module, including temperature fluctuation rate V and fluctuation period T. It then constructs a dynamic analysis model for membrane material performance, introducing the membrane material performance comprehensive evaluation index EI as the core analysis indicator. The transmittance of the membrane material at the start of the test (i.e., the initial start time of the entire test operation) is obtained and marked as the initial transmittance. The current transmittance of the membrane material is also collected. The transmittance change rate ΔTt is calculated by the transmittance change rate = (initial transmittance - current transmittance) / initial transmittance × 100%. The response speed of the membrane material at the start of the test is obtained and marked as the initial response speed. The current response speed of the membrane material is also collected. The response speed change rate ΔTr is calculated by the response speed change rate = (current response speed - initial response speed) / initial response speed × 100%. The haze value of the membrane material at the start of the test is obtained and marked as the initial haze, and the current haze of the membrane material is collected. The haze change rate ΔH is calculated by haze change rate = (current haze - initial haze) / initial haze × 100%. It should be noted that the entire testing operation startup process is as follows: user inputs testing parameters (scene, temperature fluctuation curve, etc.) → system initialization → the temperature gradient precise temperature control module stabilizes the temperature inside the testing chamber to 25℃ (fluctuation ≤0.1℃, lasting 5 minutes) → the system triggers the "test start" command → the membrane material parameter multi-dimensional acquisition module collects the first set of data (transmittance T0, response speed R0, haze H0) at 25℃. This set of data is the unique benchmark value for "initial transmittance, initial response speed, and initial haze". All subsequent single-time data acquisitions in temperature fluctuation scenarios during this testing operation will use this 25℃ benchmark value as the denominator for calculating ΔTt, ΔTr, and ΔH, ensuring that the performance change rate at all temperature points is quantified based on the benchmark value of the same standard environment, avoiding analytical bias caused by inconsistent benchmarks.

[0024] The comprehensive performance evaluation index EI of the membrane material is calculated using the formula EI=[w1×(1-ΔTt)] / [w2×ΔTr+w3×ΔH+ε]. It should be noted that the larger the value of the comprehensive performance evaluation index EI of the membrane material, the better the overall performance of the membrane material under the current temperature fluctuation. Among them, w1, w2, and w3 are preset weight factors, and w1+w2+w3=1; ε is a local minimum and takes the value 10. -6 This is used to avoid cases where the denominator is 0; According to the above formula, the EI value is calculated every 30 seconds. At the same time, the trend of EI value with temperature fluctuation rate V and fluctuation period T is analyzed (such as whether EI decreases significantly when V increases, and whether EI has periodic fluctuations when T shortens). A dynamic analysis report of membrane material performance is generated (including EI change curve, change rate curve of each parameter, and temperature fluctuation-performance correlation conclusion), which is then transmitted to the intelligent output module of results.

[0025] The intelligent output module visualizes the dynamic analysis report of membrane material performance and judges whether the membrane material performance is qualified according to preset standards. It then sends the test results to the intelligent control terminal, which not only allows users to quickly grasp the changing patterns of membrane material performance, but also achieves standardized storage and efficient transmission of test results, and provides users with a convenient viewing and management portal.

[0026] Specifically, firstly, the intelligent output module receives the dynamic analysis report of membrane material performance and displays the EI change curve, the change rate curve of each parameter, and the temperature fluctuation curve in the form of charts (such as line charts and bar charts) through the built-in visualization engine; among them, the range of EI value below 0.6 is marked in red (indicating the performance failure range). The analysis report is then structured and generated according to the format of "membrane material number - test time - temperature fluctuation parameter - change rate of each performance parameter - EI curve - pass / fail judgment result". The pass / fail judgment is based on the preset industry standard (e.g., if the EI value is ≥0.6 throughout the test period, and ΔTt≤10%, ΔTr≤20%, ΔH≤15%, it is judged as pass). The data in the membrane material performance dynamic analysis report is compared with the standard, and the pass or fail judgment result is output. Finally, the visualized charts, structured test reports, and pass / fail results are stored in a local database (supporting export in Excel and PDF formats). At the same time, the test results are sent to the intelligent management terminal for display via an Ethernet interface, facilitating real-time viewing and subsequent analysis by users.

[0027] Example 2: Figure 2As shown, the difference between this embodiment and Embodiment 1 is that the intelligent control terminal is connected to the temperature control overlap warning module. The temperature control overlap warning module evaluates and analyzes the temperature control performance of the detection cavity within a unit of time, and determines whether a temperature control abnormality signal is generated through analysis. When a temperature control abnormality signal is generated, it is sent to the intelligent control terminal. When the intelligent control terminal receives a temperature control anomaly signal, it issues a corresponding warning to remind testing personnel to investigate and analyze the situation and take appropriate control and improvement measures. This ensures the stability of the testing environment and indirectly guarantees the reliability of the entire testing process and the accuracy of performance testing results. The specific analysis process is as follows: The actual temperature curve and preset temperature fluctuation curve of the detection cavity are obtained from the temperature gradient precise temperature control module within a unit time. The actual temperature curve and the preset temperature fluctuation curve are overlaid to obtain the proportion of non-overlapping trajectories and mark them as temperature track abnormality values. The temperature track abnormality values ​​are compared with the preset temperature track abnormality threshold. If the temperature track abnormality value exceeds the preset temperature track abnormality threshold, it indicates that the temperature control performance of the detection cavity within a unit time is poor, and a temperature control abnormality signal is generated.

[0028] Furthermore, if the temperature track deviation value does not exceed the preset temperature track deviation threshold, the intersection area formed by the actual temperature curve and the preset temperature fluctuation curve is obtained, the area of ​​the corresponding intersection area is marked as the intersection coefficient, the number of intersection areas whose intersection coefficient exceeds the preset intersection coefficient threshold is marked as the intersection risk value, and the intersection coefficients of all intersection areas are summed to obtain the intersection surface value, and the intersection coefficient with the largest value is marked as the intersection amplitude value. The temperature control cross characteristic value is obtained by weighted summation of cross risk frequency value, cross surface value, and cross surface amplitude value. Specifically, the cross risk frequency value, cross surface value, and cross surface amplitude value are assigned corresponding preset weight coefficients, and the cross risk frequency value, cross surface value, and cross surface amplitude value are multiplied by the corresponding preset weight coefficients. The sum of the three product results is marked as the temperature control cross characteristic value. It should be noted that the larger the value of the temperature control cross-feature value, the worse the overall temperature control performance of the detection cavity per unit time. The temperature control cross-feature value is compared with the preset temperature control cross-feature threshold. If the temperature control cross-feature value exceeds the preset temperature control cross-feature threshold, it indicates that the overall temperature control performance of the detection cavity per unit time is poor, and a temperature control abnormality signal is generated.

[0029] The working principle of this invention is as follows: During use, the temperature gradient precision temperature control module provides stable and suitable temperature conditions for membrane material performance testing. The multi-dimensional detection and acquisition module for membrane material parameters accurately captures three core performance parameters: transmittance, response speed, and haze. The adaptive preprocessing module eliminates data defects to generate a high-quality dataset. The membrane material performance dynamic analysis module, supported by preprocessed data and real-time temperature fluctuation data, introduces the EI comprehensive evaluation index to dynamically track the changing trend of EI values ​​with temperature fluctuation rate and period, realizing a deep correlation analysis between performance and temperature. The intelligent output module visualizes the analysis report, generates a structured test report, and completes the qualification judgment according to the standard, realizing dynamic and precise testing of membrane material performance, significantly improving the controllability of the testing process and the reliability of the results.

[0030] In this invention, the threshold, preset value, or preset range settings are for result comparison and analysis to determine whether the result is good or bad. The magnitude of these values ​​is determined by a combination of large-scale model analysis of sample data and human experience, and can also be appropriately adjusted based on seasonal or common-sense influence conditions. Similarly, the preset weight coefficients and influence factors are assigned specific values ​​based on the magnitude of each parameter's influence on the result, ultimately reflecting the impact on the result. These settings are also determined by a combination of large-scale model analysis of sample data and human experience, and can also be appropriately adjusted based on seasonal or common-sense influence conditions.

[0031] The preferred embodiments of the present invention disclosed above are merely illustrative of the invention. These preferred embodiments do not exhaustively describe all details, nor do they limit the invention to any specific implementation. Clearly, many modifications and variations can be made based on the content of this specification. This specification selects and specifically describes these embodiments to better explain the principles and practical applications of the invention, enabling those skilled in the art to better understand and utilize it. The invention is limited only by the claims and their full scope and equivalents.

Claims

1. A performance testing system for electronic paper display film materials based on temperature fluctuation analysis, characterized in that, It includes a temperature gradient precise temperature control module, a membrane material parameter multi-dimensional detection and acquisition module, an adaptive preprocessing module, a membrane material performance dynamic analysis module, a result intelligent output module, and an intelligent control terminal; The temperature gradient precise temperature control module provides a stable temperature environment that conforms to the simulated scenario for the performance testing of film materials in electronic paper displays. The multi-dimensional detection and acquisition module for film material parameters collects three key performance parameters of the film material—transmittance, response speed, and haze—under the provided temperature environment and outputs the raw dataset. The adaptive preprocessing module performs noise removal, outlier correction, and data standardization on the raw acquired data to generate a high-quality preprocessed dataset. The membrane material performance dynamic analysis module generates a membrane material performance dynamic analysis report based on the preprocessed dataset and real-time temperature information. The intelligent output module visualizes the dynamic analysis report of membrane material performance and judges whether the membrane material performance is qualified according to preset standards, and sends the test results to the intelligent control terminal.

2. The electronic paper display film material performance testing system based on temperature fluctuation analysis according to claim 1, characterized in that, The multi-dimensional detection and acquisition module for membrane parameters receives real-time temperature data output by the temperature gradient precision temperature control module. When the temperature inside the detection chamber reaches the preset stable condition, the parameter acquisition process is triggered. Data is acquired based on the built-in transmittance detection unit, response speed detection unit, and haze detection unit. Each acquired data is accompanied by the current temperature value and acquisition timestamp to form the original dataset.

3. The electronic paper display film material performance testing system based on temperature fluctuation analysis according to claim 2, characterized in that, The transmittance detection unit emits detection light of a specific wavelength, which passes through the film material to be tested and is captured by the receiving sensor to calculate the transmittance value; the response speed detection unit captures the pixel switching process of the film material under the drive of the electrical signal to determine the time for the film material to switch from "black state" to "white state"; the haze detection unit calculates the haze value by measuring the intensity of scattered light and transmitted light of the film material to the detection light.

4. The electronic paper display film material performance testing system based on temperature fluctuation analysis according to claim 1, characterized in that, The specific operation process of the membrane material performance dynamic analysis module is as follows: The system receives the preprocessed dataset output by the adaptive preprocessing module and the real-time temperature fluctuation data output by the temperature gradient precise temperature control module, constructs a dynamic analysis model for membrane material performance, and introduces the membrane material performance comprehensive evaluation index EI as the core analysis indicator. The EI value is calculated every 30 seconds, and the changing trend of the EI value with temperature fluctuation rate V and fluctuation period T is analyzed. A dynamic analysis report of membrane material performance is generated and transmitted to the result intelligent output module.

5. The electronic paper display film material performance testing system based on temperature fluctuation analysis according to claim 4, characterized in that, The analysis and calculation process of the membrane material performance comprehensive evaluation index EI is as follows: The transmittance change rate ΔTt, response speed change rate ΔTr, and haze change rate ΔH were obtained through change rate calculation and analysis. Based on ΔTt, ΔTr, and ΔH, the comprehensive performance evaluation index EI of the membrane material was obtained through calculation.

6. The electronic paper display film material performance testing system based on temperature fluctuation analysis according to claim 5, characterized in that, The specific analysis process for calculating the rate of change is as follows: The transmittance change rate ΔTt is calculated using the transmittance change rate = (initial transmittance - current transmittance) / initial transmittance × 100%. The response speed change rate ΔTr is calculated using the response speed change rate = (current response speed - initial response speed) / initial response speed × 100%. The haze change rate ΔH is calculated using the haze change rate = (current haze - initial haze) / initial haze × 100%.

7. The electronic paper display film material performance testing system based on temperature fluctuation analysis according to claim 4, characterized in that, The intelligent output module displays the EI change curve, the change rate curve of each parameter, and the temperature fluctuation curve in the form of charts through the built-in visualization engine; then it performs structured processing on the analysis report to generate a structured test report, and compares the data in the membrane material performance dynamic analysis report with the standard, and outputs the judgment result of whether it is qualified or unqualified. Finally, the visualized charts, structured test reports, and pass / fail results are stored in the local database, and the test results are sent to the intelligent management terminal for display.

8. The electronic paper display film material performance testing system based on temperature fluctuation analysis according to claim 7, characterized in that, The intelligent control terminal communicates with the temperature control overlap warning module. The temperature control overlap warning module evaluates and analyzes the temperature control performance of the detection cavity within a unit of time. When an abnormal temperature control signal is generated, the intelligent control terminal issues a corresponding warning.

9. The electronic paper display film material performance testing system based on temperature fluctuation analysis according to claim 8, characterized in that, The specific analysis process of the temperature control overlap warning module is as follows: if the temperature rail occupancy value exceeds the preset temperature rail occupancy threshold, a temperature control anomaly signal is generated; if the temperature rail occupancy value does not exceed the preset temperature rail occupancy threshold, the temperature control crossover characteristic value is calculated by weighted summation of the crossover frequency value, crossover surface value, and crossover amplitude value; if the temperature control crossover characteristic value exceeds the preset temperature control crossover characteristic threshold, a temperature control anomaly signal is generated.

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