Corrugated paper moisture resistance detection method and system

Abstract

The present application relates to the field of material performance detection, and discloses a corrugated paper moisture resistance detection method and system, comprising: first, obtaining the storage environment of the corrugated paper sample and collecting environmental data, and then performing dynamic moisture absorption analysis and calculating the moisture penetration rate; then, combining the rate analysis structure with the moisture state, querying the moisture regain index, and then performing layered humidity detection to obtain interlayer moisture change data; then, calculating the moisture resistance residual strength based on the data, generating the moisture resistance efficiency index combined with temperature and humidity, and dividing the moisture regain risk level; finally, configuring multi-stage early warning indicators according to the level, positioning the edge moisture absorption area and calculating the diffusion gradient value, generating a humidity stability signal and sending it to the terminal, and formulating a moisture regain detection strategy according to the feedback. The present application can guarantee the accuracy of the corrugated paper moisture regain detection.

Description

Technical Field

[0001] The invention relates to a method and system for detecting moisture resurgence resistance of corrugated paper, belonging to the field of material performance detection. Background Art

[0002] Corrugated paper is a paper packaging material made by gluing noodle paper and corrugated paper formed by corrugating rollers. It is widely used in logistics, transportation, product packaging and other fields. Its moisture resistance directly affects the safety of the packaged items and the physical strength of the corrugated paper itself.

[0003] At present, there are two main methods commonly used to test the moisture regain of corrugated paper: one is the traditional weighing method, which determines the degree of moisture regain by recording the weight change of corrugated paper in different humidity environments. This method is cumbersome, inefficient, and cannot be monitored in real time; the other is to use a humidity sensor to detect, and attach the sensor to the surface of the corrugated paper. However, the sensor is easily interfered by the external environment, and the detection data is inaccurate. At the same time, it is difficult to reflect the moisture regain inside the corrugated paper, and it is impossible to effectively prevent problems such as the decrease in the compressive strength of the corrugated paper and damage to the packaging caused by moisture regain. Therefore, a method for detecting the moisture regain of corrugated paper is needed to ensure the accuracy of corrugated paper moisture regain detection. Summary of the Invention

[0004] The present invention provides a method and system for detecting moisture regain resistance of corrugated paper, the main purpose of which is to ensure the accuracy of moisture regain detection of corrugated paper.

[0005] To achieve the above object, the present invention provides a method for detecting moisture regain resistance of corrugated paper, comprising:

[0006] Obtaining the storage environment of the corrugated paper sample and collecting detailed environmental data corresponding to the storage environment, performing a dynamic moisture absorption analysis on the corrugated paper sample based on the detailed environmental data to obtain a dynamic moisture absorption characteristic, and calculating a moisture permeation rate corresponding to the dynamic moisture absorption data;

[0007] Based on the moisture permeation rate, analyzing the structural moisture state corresponding to the corrugated paper sample, querying the moisture regain index corresponding to the structural moisture state, and performing layered humidity detection on the corrugated paper sample based on the moisture regain index to obtain inter-layer moisture change data;

[0008] Based on the interlayer moisture change data, analyzing the corresponding moisture resurgence residual strength of the corrugated paper sample, generating a moisture resurgence performance index corresponding to the corrugated paper sample based on the moisture resurgence residual strength combined with the current ambient temperature and humidity, and classifying the moisture resurgence risk level corresponding to the moisture resurgence performance index;

[0009] Based on the moisture regain risk level, configuring a multi-level warning indicator corresponding to the corrugated paper sample, locating the edge moisture absorption area corresponding to the corrugated paper sample based on the multi-level warning indicator, and calculating the moisture diffusion gradient value corresponding to the edge moisture absorption area;

[0010] Based on the moisture diffusion gradient value, a humidity stabilization signal corresponding to the corrugated paper sample is generated, and the humidity stabilization signal is sent to a preset humidity monitoring terminal to obtain terminal feedback data. Based on the terminal feedback data, a regain detection strategy corresponding to the corrugated paper sample is formulated.

[0011] Optionally, performing a dynamic moisture absorption analysis on the corrugated paper sample based on the detailed environmental data to obtain a dynamic moisture absorption characteristic includes:

[0012] Analyzing the initial environmental conditions corresponding to the detailed environmental data;

[0013] Querying the initial moisture content of the corrugated paper sample under the initial environmental conditions;

[0014] Analyze the moisture absorption rate characteristics corresponding to the initial moisture content;

[0015] Based on the moisture absorption rate characteristic, identifying moisture distribution data corresponding to the corrugated paper sample;

[0016] Based on the moisture distribution data, a dynamic moisture absorption analysis is performed on the corrugated paper sample to obtain a dynamic moisture absorption characteristic.

[0017] Optionally, calculating the moisture permeation rate corresponding to the dynamic moisture absorption data includes:

[0018] The moisture permeation rate corresponding to the dynamic moisture absorption data is calculated using the following formula:

[0019]

[0020] in, represents the moisture penetration rate corresponding to the dynamic moisture absorption data, represents the total number of environmental monitoring points, Indicates the number index of environmental monitoring points, and Respectively represent the start time and end time of the dynamic moisture absorption analysis process, Indicates in Environmental monitoring points, Moment and The relative humidity difference at time Indicates in Environmental monitoring points, Moment and The temperature difference at time represents the surface area of ​​the corrugated paper corresponding to the i-th environmental monitoring point, Indicates the total number of layers corresponding to the corrugated paper sample, Indicates the hierarchical index corresponding to the corrugated paper sample, represents the thickness of the jth layer of the corrugated paper sample, It represents the mass change rate of the jth layer of the corrugated paper sample at time t under the i-th environmental monitoring point.

[0021] Optionally, the step of performing layered humidity detection on the corrugated paper sample based on the moisture regain index to obtain inter-layer moisture change data includes:

[0022] Query the humidity stratification threshold corresponding to the moisture regain index;

[0023] Dividing the detection layers of the corrugated paper sample based on the humidity stratification threshold;

[0024] Scanning the measured humidity values ​​corresponding to each layer of the corrugated paper sample according to the detection layer position;

[0025] Comparing the measured humidity value with a preset humidity reference value to obtain an inter-layer difference sequence;

[0026] Based on the inter-layer difference sequence, the corrugated paper sample is subjected to layered humidity detection to obtain inter-layer moisture change data.

[0027] Optionally, analyzing the moisture resurgence resistance residual strength corresponding to the corrugated paper sample based on the interlayer moisture change data includes:

[0028] extracting interlayer distribution features from the interlayer tidal change data;

[0029] Determining a tide change impact area corresponding to the corrugated paper sample according to the interlayer distribution characteristics;

[0030] Quantify the humidity attenuation index corresponding to the tidal change affected area;

[0031] Based on the humidity attenuation index, evaluating the local moisture resistance difference corresponding to the corrugated paper sample;

[0032] Based on the local moisture resistance difference, the corresponding moisture resistance residual strength of the corrugated paper sample is analyzed

[0033] Optionally, the classifying the moisture resurgence risk level corresponding to the moisture resistance efficiency index includes:

[0034] Based on the moisture resistance index, query the key moisture change characteristics corresponding to the corrugated paper sample;

[0035] Analyzing characteristic fluctuation indexes in the key tidal characteristics;

[0036] Determining a core moisture range corresponding to the corrugated paper sample based on the characteristic fluctuation index;

[0037] Generate a moisture control threshold corresponding to the core moisture range;

[0038] Based on the moisture control threshold, the moisture resurgence risk level corresponding to the moisture resistance efficiency index is divided.

[0039] Optionally, locating the edge moisture absorption area corresponding to the corrugated paper sample based on the multi-stage warning indicator includes:

[0040] Analyze the abnormal baselines of each level corresponding to the multi-level warning indicators;

[0041] Delineating the potential moisture absorption range corresponding to the corrugated paper sample according to the abnormal baselines of each order;

[0042] Screening the core monitoring points in the potential moisture absorption range;

[0043] Collecting real-time humidity data corresponding to the core monitoring points;

[0044] The edge moisture absorption area corresponding to the corrugated paper sample is located according to the real-time humidity data.

[0045] Optionally, the calculating the moisture diffusion gradient value corresponding to the edge hygroscopic area includes:

[0046] The moisture diffusion gradient corresponding to the edge hygroscopic area is calculated using the following formula:

[0047]

[0048] in, Indicates the moisture diffusion gradient corresponding to the edge hygroscopic area, represents the total number of sub-regions corresponding to the edge hygroscopic region, Indicates the quantity index corresponding to the sub-region, and Respectively represent the start and end time of the detection time interval, Indicates the The humidity change of each sub-region at time t is: Indicates the The length of the sub-region, Indicates the average temperature within the detection time interval. represents the reference temperature, Represents the average relative humidity within the detection time interval, Indicates reference relative humidity.

[0049] Optionally, generating a humidity stability signal corresponding to the corrugated paper sample based on the moisture diffusion gradient value includes:

[0050] Analyze the dynamic permeability range corresponding to the water diffusion gradient value;

[0051] Based on the dynamic permeability interval, dividing the corrugated paper sample into humidity sensitive levels;

[0052] querying the moisture balance data associated with the level change in the humidity sensitive level;

[0053] extracting steady-state regulatory factors from the hygroscopic balance data;

[0054] Based on the steady-state control factor, a humidity stability signal corresponding to the corrugated paper sample is generated.

[0055] In order to solve the above problems, the present invention also provides a corrugated paper moisture resurgence detection system, the system comprising:

[0056] a rate calculation module, configured to obtain the storage environment of the corrugated paper sample and collect detailed environmental data corresponding to the storage environment; based on the detailed environmental data, perform a dynamic moisture absorption analysis on the corrugated paper sample to obtain a dynamic moisture absorption characteristic; and calculate a moisture permeation rate corresponding to the dynamic moisture absorption data;

[0057] a delamination detection module, configured to analyze the structural moisture state corresponding to the corrugated paper sample based on the moisture penetration rate, query the moisture regain index corresponding to the structural moisture state, and perform delamination moisture detection on the corrugated paper sample based on the moisture regain index to obtain inter-layer moisture change data;

[0058] a grading module for analyzing the moisture resurgence residual strength corresponding to the corrugated paper sample based on the interlayer moisture change data, generating a moisture resurgence performance index corresponding to the corrugated paper sample based on the moisture resurgence residual strength combined with the current ambient temperature and humidity, and grading the moisture resurgence risk level corresponding to the moisture resurgence performance index;

[0059] a gradient value calculation module, configured to configure a multi-stage warning index corresponding to the corrugated paper sample based on the moisture regain risk level, locate the edge moisture absorption area corresponding to the corrugated paper sample based on the multi-stage warning index, and calculate the moisture diffusion gradient value corresponding to the edge moisture absorption area;

[0060] A strategy formulation module is used to generate a humidity stability signal corresponding to the corrugated paper sample based on the moisture diffusion gradient value, send the humidity stability signal to a preset humidity monitoring terminal, obtain terminal feedback data, and formulate a regain detection strategy corresponding to the corrugated paper sample based on the terminal feedback data.

[0061] Compared with the problems described in the background art, the present application can provide basic information for subsequent analysis by obtaining the storage environment of the corrugated paper sample and collecting the corresponding environmental detailed data of the storage environment, accurately grasp the influence of environmental factors on the moisture regain of corrugated paper, and more accurately carry out dynamic moisture absorption analysis, structure moisture judgment and other work, thereby improving the effectiveness of the moisture resistance detection. Based on the moisture penetration rate, the present application can analyze the structure moisture state corresponding to the corrugated paper sample, accurately quantify the moisture intrusion degree, and clearly show the moisture difference in different regions and levels, thereby providing key basis for evaluating the structural stability and damage resistance, helping to early warning of failure risk, and optimizing the protection strategy in the storage and use links. Further, based on the interlayer moisture change data, the present application can analyze the moisture resistance residual strength corresponding to the corrugated paper sample, in-depth analyze the specific influence of moisture penetration on the strength of each layer structure, quantify the strength attenuation degree caused by moisture absorption, and accurately locate the moisture resistance weak link through the correlation analysis of the interlayer humidity difference and the strength loss, thereby supporting the development of targeted reinforcement or moisture-proof scheme. Further, based on the moisture regain risk level, the present application can configure the multi-stage early warning index corresponding to the corrugated paper sample, set different monitoring thresholds according to different threat levels, realize the whole-chain early warning coverage from slight moisture to serious risk, and improve the refinement and dynamic adaptability of the corrugated paper moisture regain risk control. Finally, based on the moisture diffusion gradient, the present application can generate the humidity stability signal corresponding to the corrugated paper sample, accurately quantify the moisture dynamics of the edge moisture absorption area, convert the complex diffusion data into intuitive stability state identifier, help to identify the moisture risk trend in advance, and ensure the quality and use reliability of corrugated paper from the source. Therefore, the corrugated paper moisture resistance detection method and system provided by the embodiment of the present application can ensure the accuracy of the corrugated paper moisture regain detection. BRIEF DESCRIPTION OF DRAWINGS

[0062] Figure 1 A flowchart of a corrugated paper moisture resistance detection method provided by an embodiment of the present application is shown in the figure.

[0063] Figure 2 A detection flowchart in a corrugated paper moisture resistance detection method provided by an embodiment of the present application is shown in the figure.

[0064] Figure 3 A module diagram of the corrugated paper moisture resistance detection system provided by an embodiment of the present application is shown in the figure.

[0065] The object implementation, functional features and advantages of the present application will be further described with reference to the embodiments and the accompanying drawings. DETAILED DESCRIPTION

[0066] It should be understood that the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application.

[0067] The present embodiment provides a method for testing the moisture resurgence resistance of corrugated paper. This method can be executed by at least one of a server, a terminal, or other electronic device capable of executing the method provided in the present embodiment. In other words, the method can be executed by software or hardware installed on a terminal or server device. The server includes, but is not limited to, a single server, a server cluster, a cloud server, or a cloud server cluster.

[0068] Example 1:

[0069] Reference Figure 1 FIG. 1 is a flow chart of a method for detecting moisture resurgence of corrugated paper according to an embodiment of the present invention. In this embodiment, the method for detecting moisture resurgence of corrugated paper includes:

[0070] S1. Obtain the storage environment of the corrugated paper sample and collect detailed environmental data corresponding to the storage environment. Based on the detailed environmental data, perform a dynamic moisture absorption analysis on the corrugated paper sample to obtain a dynamic moisture absorption characteristic, and calculate a moisture permeation rate corresponding to the dynamic moisture absorption data.

[0071] By obtaining the storage environment of the corrugated paper sample and collecting detailed environmental data corresponding to the storage environment, the present invention can provide basic information for subsequent analysis, accurately grasp the impact of environmental factors on the moisture regain of corrugated paper, and more accurately carry out dynamic moisture absorption analysis, structural moisture judgment and other tasks, thereby improving the effectiveness of anti-moisture regain detection.

[0072] Among them, the corrugated paper sample refers to a representative individual or part selected from the corrugated paper product to be tested, which is used for moisture regain resistance testing. For example, in a batch of corrugated boxes, several small pieces of corrugated cardboard are randomly selected as samples, and the moisture regain resistance of the entire batch of products is inferred by testing these samples; the storage environment refers to the spatial environment in which the corrugated paper sample is located, including various external conditions that affect its moisture regain. For example, when the corrugated paper sample is stored in a warehouse, the temperature and humidity in the warehouse, the air circulation conditions, whether it is in contact with water or in a humid corner, etc. all fall into the category of storage environment; the detailed environmental data refers to the various parameter values ​​that can specifically characterize the characteristics of the storage environment, covering multi-dimensional information related to moisture regain, for example, including ambient temperature (such as 25°C), relative humidity ( Such as 60% RH), air flow rate (such as 0.5m / s), light intensity (such as 500lux) and other data. These data provide a quantitative basis for analyzing the impact of the environment on the moisture regain of corrugated paper. Optionally, the storage environment in which the corrugated paper sample is stored can be obtained through an environmental monitoring sensor network, such as: using a temperature and humidity sensor combined with a LoRa wireless transmission module to collect warehouse environmental parameters in real time, and finally obtaining a storage environment including temperature, humidity, and light intensity; the collection of detailed environmental data corresponding to the storage environment can be achieved through multi-source data fusion technology, such as: using a ZigBee networked gas sensor array with Python's Pandas library for data cleaning and feature extraction, and finally obtaining detailed environmental data covering VOC concentration and PM2.5 value.

[0073] Furthermore, based on the detailed environmental data, the present invention performs a dynamic moisture absorption analysis on the corrugated paper sample to obtain dynamic moisture absorption characteristics, which can accurately reveal the moisture absorption rules and trends of the sample in the actual environment, and provide a core basis for quantifying the moisture penetration rate and evaluating the moisture state of the structure, so that the anti-moisture resurgence test can deeply reflect the dynamic process of sample moisture absorption and improve the detection results of the actual moisture change situation.

[0074] Among them, the dynamic moisture absorption characteristics refer to a comprehensive analysis of the various changing characteristics and laws of the corrugated paper sample during the moisture absorption process under the influence of the environment. It is an overall summary of the moisture absorption process. For example, the total amount of moisture absorbed by the sample within a certain period of time, the moisture absorption rate change curve, the humidity distribution evolution trend, etc. These information reflecting the dynamic moisture absorption process of the sample constitute the dynamic moisture absorption characteristics.

[0075] As an embodiment of the present invention, the dynamic moisture absorption analysis is performed on the corrugated paper sample based on the detailed environmental data to obtain dynamic moisture absorption characteristics, including: analyzing the initial environmental conditions corresponding to the detailed environmental data; querying the initial moisture content corresponding to the corrugated paper sample under the initial environmental conditions; parsing the moisture absorption rate characteristics corresponding to the initial moisture content; identifying the humidity distribution data corresponding to the corrugated paper sample based on the moisture absorption rate characteristics; and performing dynamic moisture absorption analysis on the corrugated paper sample based on the humidity distribution data to obtain dynamic moisture absorption characteristics.

[0076] Among them, the initial environmental conditions refer to the basic parameter states of the environment in which the corrugated paper sample is located when the dynamic moisture absorption analysis of the corrugated paper sample is started, which is the starting environmental background of the moisture absorption process. For example, the temperature of the warehouse where the corrugated paper sample is located before the test is 28°C, the relative humidity is 70%, and the air is still. These parameters such as temperature, humidity, and air flow constitute the initial environmental conditions; the initial moisture content refers to the proportion of moisture contained in the corrugated paper sample itself under the initial environmental conditions, reflecting the initial moisture state of the sample before the test. For example, the corrugated paper sample taken out of the warehouse has an initial moisture content of 8% after testing. This value is an important basic data for the subsequent analysis of moisture absorption changes; The moisture absorption rate characteristic refers to the law of change in the speed at which a corrugated paper sample absorbs moisture under a specific environment, including characteristics such as the speed of moisture absorption, acceleration or deceleration trends. For example, in a certain temperature and humidity environment, the corrugated paper sample absorbs moisture faster in the first two hours, and then the speed gradually slows down. This change in moisture absorption speed over time is the moisture absorption rate characteristic; the humidity distribution data refers to the specific values ​​and distribution of humidity in different parts or layers of the corrugated paper sample, reflecting the humidity difference inside the sample. For example, after testing, the surface humidity of the corrugated paper sample is 12%, and the humidity of the middle core layer is 9%. Recording the humidity values ​​and differences at these different positions forms the humidity distribution data.

[0077] Furthermore, the analysis of the initial environmental conditions corresponding to the detailed environmental data can be achieved through multivariate statistical analysis technology, such as: using principal component analysis combined with Python's Scikit-learn library to perform data dimensionality reduction processing, and finally obtaining the principal component initial environmental conditions that characterize the environmental characteristics; the query of the initial moisture content corresponding to the corrugated paper sample under the initial environmental conditions can be achieved through material database retrieval technology, such as: using MATLAB's MaterialDatabase Toolkit to call ASTM standard data, and finally obtaining the initial moisture content that meets the current temperature and humidity conditions; the analysis of the moisture absorption rate characteristics corresponding to the initial moisture content can be achieved through differential equation modeling technology, such as: using COMSOL Multiphysics software based on Fick's diffusion law to perform parameter fitting, and finally obtaining the moisture absorption rate characteristics that describe the dynamic process of moisture absorption; the identification of the moisture distribution data corresponding to the corrugated paper sample can be achieved through near-infrared imaging technology, such as: using FLIR The A655sc infrared thermal imager is used in conjunction with ImageJ software to reconstruct the humidity field, ultimately obtaining humidity distribution data reflecting the humidity gradient on the sample surface; the dynamic moisture absorption analysis of the corrugated paper sample can be achieved through time series prediction technology, such as using an LSTM neural network combined with the TensorFlow framework to model the moisture absorption process, ultimately obtaining dynamic moisture absorption characteristics including time-varying characteristics.

[0078] By calculating the moisture penetration rate corresponding to the dynamic moisture absorption data, the present invention can quantify the moisture absorption speed of the corrugated paper sample under the influence of the environment, providing a key indicator for evaluating its anti-moisture regain performance. This rate can intuitively reflect the speed at which moisture intrudes into the interior of the sample, helping to analyze the risk level of moisture in the structure.

[0079] Among them, the moisture permeation rate refers to the average speed / flux of moisture penetrating the corrugated paper sample per unit time and unit sample area (or combined with factors such as layer thickness) in a dynamic moisture absorption scenario. It quantifies the dynamic process of moisture penetration from the external environment to the interior of the corrugated paper by integrating multi-dimensional data such as changes in environmental temperature and humidity, sample stratification characteristics, and changes in quality over time. It reflects the key indicator of the moisture resistance of corrugated paper. The larger the value, the faster the moisture penetration and the more susceptible the sample to moisture.

[0080] As an embodiment of the present invention, the calculating the moisture permeation rate corresponding to the dynamic moisture absorption data includes:

[0081] The moisture permeation rate corresponding to the dynamic moisture absorption data is calculated using the following formula:

[0082]

[0083] in, represents the moisture penetration rate corresponding to the dynamic moisture absorption data, represents the total number of environmental monitoring points, Indicates the number index of environmental monitoring points, and Respectively represent the start time and end time of the dynamic moisture absorption analysis process, Indicates in Environmental monitoring points, Moment and The relative humidity difference at time Indicates in Environmental monitoring points, Moment and The temperature difference at time represents the surface area of ​​the corrugated paper corresponding to the i-th environmental monitoring point, Indicates the total number of layers corresponding to the corrugated paper sample, Indicates the hierarchical index corresponding to the corrugated paper sample, represents the thickness of the jth layer of the corrugated paper sample, It represents the mass change rate of the jth layer of the corrugated paper sample at time t under the i-th environmental monitoring point.

[0084] In detail, the environmental monitoring points refer to physical detection locations that are evenly / targetedly arranged around the sample (such as warehouses, test cabins and other spaces) in order to accurately capture the impact of the corrugated paper storage environment on moisture absorption. Each point independently collects environmental parameters such as temperature and humidity. The formula uses "n" to count the total number and "i" to distinguish the index. Multi-point data is used to eliminate environmental unevenness interference, making the moisture penetration analysis more in line with the real scene (for example, the temperature and humidity in different corners of the warehouse are different, and multi-point monitoring can fully reflect the effect of the environment on the sample); the dynamic moisture absorption analysis process refers to the continuous moisture absorption behavior monitoring cycle of the corrugated paper sample from the "initial state" to the "specific end state"; the relative humidity difference refers to the key indicator of water vapor content in the air. A positive difference indicates that the environment becomes humid (conducive to sample moisture absorption), and a negative difference indicates that the environment becomes dry (may cause the sample to lose water), which comprehensively reflects the driving effect of the environmental "moisture potential energy" on moisture penetration; the temperature difference refers to the influence of temperature on the activity of water vapor movement and the adsorption characteristics of corrugated paper fibers on moisture, which is related to relative humidity. The degree of moisture absorption acts synergistically in the moisture absorption process (for example, high temperature and high humidity environment usually accelerates moisture penetration), which constructs an "environmental driving factor" (a combination within the square root) with the humidity difference to quantify the comprehensive driving force of environmental temperature and humidity changes on moisture penetration; the surface area of ​​the corrugated paper refers to the effective area of ​​the corrugated paper sample corresponding to the i-th environmental monitoring point exposed to the environment, that is, the paper surface area that is in contact with the ambient air and where moisture exchange may occur (the actual contact form of the corrugated paper, such as the unfolded surface and folds, needs to be considered). The larger the area, the more moisture penetration channels there are in theory; the mass change rate refers to the mass change per unit time of the j-th layer of the corrugated paper sample at the i-th environmental monitoring point, which is the core data of dynamic moisture absorption. An increase in mass indicates that the sample absorbs moisture (moisture penetrates in), and a decrease indicates water loss (moisture seeps out or evaporates); partial derivative with respect to time It can accurately capture the "instantaneous" changes in moisture absorption rate (for example, when the environment changes suddenly, the mass change rate will fluctuate rapidly), reflect the real-time moisture absorption response of the layered structure, and enable moisture penetration analysis to be refined to each layer inside the sample.

[0085] S2. Based on the moisture permeation rate, analyze the structural moisture state corresponding to the corrugated paper sample, query the moisture regain index corresponding to the structural moisture state, and perform layered humidity detection on the corrugated paper sample based on the moisture regain index to obtain inter-layer moisture change data.

[0086] Based on the moisture permeation rate, the present invention analyzes the structural moisture status corresponding to the corrugated paper sample, can accurately quantify the degree of moisture intrusion, clarify the differences in moisture in different areas and layers, provide a key basis for evaluating structural stability and damage resistance, help to provide early warning of failure risks, and optimize protection strategies in storage and use.

[0087] Among them, the structural moisture state refers to the structural changes of the corrugated paper sample at the microscopic or macroscopic level due to moisture penetration, covering fiber expansion, interlayer adhesion changes, deformation and damage, etc., reflecting its performance and integrity state after being affected by environmental humidity. For example, after the corrugated paper is damp, the adhesive between the core paper and the surface paper fails, and the corrugated structure collapses, that is, it presents a poor structural moisture state. Optionally, the analysis of the structural moisture state corresponding to the corrugated paper sample can be achieved through dielectric property detection technology, such as: using a high-frequency impedance analyzer in conjunction with the ANSYS Maxwell tool to perform three-dimensional modeling of the dielectric constant, and finally obtaining a structural moisture state reflecting the moisture distribution between the fiber layers.

[0088] Furthermore, the present invention can convert qualitative moisture conditions into quantitative indicators by querying the regain index corresponding to the moisture state of the structure, providing a unified reference for evaluating the degree of performance attenuation of corrugated paper, and accurately correlating moisture with quality, strength, etc., helping to quickly determine its applicability in warehousing, transportation and other scenarios, and supporting moisture-proof strategy optimization and risk prediction.

[0089] Among them, the regain index refers to an indicator used to quantitatively characterize the degree of moisture of a corrugated paper sample. It is a quantitative value reflecting the impact of regain on performance, which is obtained by a specific algorithm based on factors such as the structural moisture state and moisture content. For example, by detecting the fiber expansion rate and interlayer peeling strength of the corrugated paper, the value 8 is calculated by the formula. This 8 is the regain index, which reflects the degree of performance attenuation after moisture. Optionally, the regain index corresponding to the structural moisture state can be queried by moisture adsorption isotherm analysis technology, such as using the dynamic moisture adsorption analyzer DVS Advantage combined with the Brunauer-Emmett-Teller theoretical model to calculate the equilibrium moisture content, and finally obtaining the regain index that characterizes the moisture absorption capacity of the material.

[0090] Furthermore, based on the regain index, the present invention performs layered humidity detection on the corrugated paper sample to obtain interlayer moisture change data, which can accurately locate abnormal humidity distribution areas inside the sample according to different moisture levels, reveal the penetration path and diffusion differences of moisture between each paper layer, and enable the detection to go deeper from macroscopic characterization to microscopic interlayer dynamics, thereby improving the pertinence and accuracy of anti-regain detection.

[0091] Among them, the interlayer moisture change data refers to a data set that reflects the moisture distribution and change trend of each layer inside the corrugated paper sample, which is formed by integrating the actual humidity measured values ​​of each detection layer, the interlayer difference sequence and other information. For example, the interlayer moisture distribution curve and difference analysis report containing characteristics such as high humidity in the surface paper layer and increasing humidity in the core paper layer are the interlayer moisture change data.

[0092] As an embodiment of the present application, the layered humidity detection of the corrugated paper sample based on the moisture regain index to obtain interlayer moisture change data comprises: querying the humidity layering threshold value corresponding to the moisture regain index; dividing the detection layer position of the corrugated paper sample based on the humidity layering threshold value; scanning the humidity measured value of each layer of the corrugated paper sample according to the detection layer position; comparing the humidity measured value with the preset humidity reference value to obtain the interlayer difference sequence; and performing layered humidity detection on the corrugated paper sample based on the interlayer difference sequence to obtain the interlayer moisture change data.

[0093] The humidity layering threshold value refers to the humidity critical value of each paper layer preset according to the moisture regain index, which is used to divide the detection layer level of the corrugated paper sample and judge the moisture degree of each layer. For example, when the moisture regain index is 5, the surface paper layer humidity threshold value is set to 10% RH and the core paper layer is 8% RH. If the threshold value is exceeded, it is determined that the layer is abnormally moist. The detection layer position refers to the specific detection layer position divided on the corrugated paper sample according to the humidity layering threshold value, which usually corresponds to different structural layers of the sample (such as surface paper, core paper, and bottom paper). For example, two detection layer positions of surface paper layer and core paper layer are divided for three-layer corrugated paper to detect the humidity of each layer respectively. The humidity measured value refers to the humidity data actually measured by the detection equipment at each detection layer position of the corrugated paper sample, which reflects the real moisture content of each layer. For example, the surface paper layer humidity of a certain corrugated paper sample is measured to be 12% RH and the core paper layer is 9% RH by using a micro humidity sensor, which is the humidity measured value of each layer. The interlayer difference sequence refers to the sequence formed by arranging the difference values calculated by comparing the humidity measured value of each detection layer position with the preset humidity reference value in order, which is used to represent the degree of deviation of the humidity of each layer from the normal state. For example, the reference value is 8% RH for the surface paper layer and 6% RH for the core paper layer, and the measured difference value is +4% RH and +3% RH, forming the sequence [+4%, +3%].

[0094] Furthermore, the query of the humidity stratification threshold corresponding to the regain index can be achieved through quantile regression analysis technology, such as: using Python's Statsmodels library to perform box plot outlier detection combined with industry standard threshold setting, and finally obtaining the stratification threshold for distinguishing different humidity levels; the division of the detection layer of the corrugated paper sample can be achieved through X-ray tomography technology, such as: using a Micro-CT scanner in conjunction with VGStudio MAX software is used to reconstruct the three-dimensional structure, and finally a detection layer based on density difference is obtained; the humidity measured values ​​corresponding to each layer of the corrugated paper sample can be achieved by microwave moisture detection technology, such as: using a resonant microwave sensor array combined with a LabVIEW data acquisition system, and finally obtaining accurate humidity measured values ​​of each layer; the comparison of the humidity measured value with the preset humidity reference value can be achieved by a difference analysis algorithm, such as: calculating the relative deviation based on the Z-score standardization method on the MATLAB platform, and finally obtaining a difference sequence reflecting the difference between layers; the layered humidity detection of the corrugated paper sample can be achieved by multi-sensor data fusion technology, such as: integrating infrared humidity sensors and capacitive moisture meter data through Kalman filtering algorithm, and finally obtaining interlayer tidal change data containing spatiotemporal change characteristics.

[0095] S3. Based on the interlayer moisture change data, analyze the corresponding moisture resurgence residual strength of the corrugated paper sample, generate the corresponding moisture resurgence performance index of the corrugated paper sample based on the moisture resurgence residual strength combined with the current ambient temperature and humidity, and classify the moisture resurgence risk level corresponding to the moisture resurgence performance index.

[0096] The present invention analyzes the moisture resurgence residual strength corresponding to the corrugated paper sample based on the interlayer moisture change data, can deeply analyze the specific impact of moisture penetration on the structural strength of each layer, quantify the degree of strength attenuation caused by moisture absorption, and accurately locate the weak links in moisture resistance through the correlation analysis of interlayer humidity differences and strength loss, thereby supporting the formulation of targeted reinforcement or moisture-proof plans.

[0097] Among them, the said anti-moisture resurgence residual strength refers to the ability of the corrugated paper sample to resist moisture intrusion and maintain structural performance after the comprehensive influence of interlayer moisture changes. It is usually expressed as the retention rate of initial strength (such as compressive strength, bursting resistance, etc.). For example, the initial compressive strength of a sample is 5000N, and the actual measured value after moisture is 3500N. Its anti-moisture resurgence residual strength is 70%.

[0098] As an embodiment of the present invention, the analysis of the moisture resurgence residual strength corresponding to the corrugated paper sample based on the inter-layer moisture change data includes: extracting the inter-layer distribution characteristics in the inter-layer moisture change data; determining the moisture change affected area corresponding to the corrugated paper sample according to the inter-layer distribution characteristics; quantifying the humidity attenuation index corresponding to the moisture change affected area; evaluating the local moisture resistance difference corresponding to the corrugated paper sample based on the humidity attenuation index; and analyzing the moisture resurgence residual strength corresponding to the corrugated paper sample based on the local moisture resistance difference.

[0099] Among them, the inter-layer distribution characteristics refer to the regular differences or change patterns in the humidity data between the various paper layers of the corrugated paper sample, such as the humidity increasing / decreasing with the number of layers, the abnormal and sudden change in the humidity of a certain layer, etc. For example, the humidity of the face paper layer of the three-layer corrugated paper is 15% RH, the core paper layer is 9% RH, and the bottom paper layer is 10% RH, forming a distribution characteristic of "the humidity of the face paper layer is significantly higher than that of other layers"; the tidal change affected area refers to the structural layer or local area that is significantly affected by moisture penetration, determined in the corrugated paper sample based on the inter-layer distribution characteristics, which is usually a location with abnormally high humidity or a key diffusion path. For example, if the detection finds that the humidity in the middle of the core paper layer reaches 12% RH (far exceeding the upper and lower layers), the middle of the core paper layer is determined to be the tidal change affected area; the humidity attenuation index refers to a numerical index that quantifies the degree to which the humidity in the tidal change affected area deviates from the normal state, and is calculated through parameters such as the difference between the measured humidity and the baseline humidity, and the humidity gradient. For example, the measured humidity in a tidal area is 14%RH, and the baseline humidity is 8%RH. The humidity attenuation index is calculated to be +6%RH (or a 75% increase relative to the baseline). The local moisture resistance difference refers to the difference in moisture resistance due to uneven humidity distribution in different layers or areas of the corrugated paper sample, reflecting the different tolerance of each part to moisture erosion. For example, the moisture resistance of the surface paper layer drops to 60% of the initial value due to long-term exposure to a high-humidity environment, while the core paper layer still maintains 85% strength, forming an obvious local moisture resistance difference between the two.

[0100] Furthermore, the extraction of inter-layer distribution characteristics in the inter-layer tidal change data can be achieved through spatial variation function analysis technology, such as: using GS+ geostatistical software to calculate the semi-variogram function parameters, and finally obtaining the inter-layer distribution characteristics that characterize the spatial variability of humidity; the determination of the tidal change affected area corresponding to the corrugated paper sample can be achieved through cluster analysis methods, such as: using the DBSCAN density clustering algorithm combined with Python's Scikit-learn library to detect abnormal areas, and finally obtaining the tidal change affected area with significant humidity changes; the quantification of the humidity attenuation index corresponding to the tidal change affected area can be achieved through exponential decay model fitting technology, such as: based on Le The venberg-Marquardt algorithm is used to perform nonlinear regression analysis on the OriginPro platform, and finally an attenuation index describing the change in humidity gradient is obtained; the evaluation of the local moisture resistance difference corresponding to the corrugated paper sample can be achieved through a multi-index comprehensive evaluation technology, such as: using the entropy weight TOPSIS method combined with MATLAB to calculate the moisture resistance performance score of each region, and finally obtaining the local moisture resistance difference reflecting the regional differences; the analysis of the corresponding anti-rebound residual strength of the corrugated paper sample can be achieved through a mechanical property testing technology, such as: using an INSTRON universal material testing machine to perform a wet ring compression strength test, and finally obtaining the anti-rebound residual strength considering the influence of moisture absorption.

[0101] The present invention generates a moisture resistance performance index corresponding to the corrugated paper sample based on the anti-moisture resurgence residual strength combined with the current ambient temperature and humidity. It can couple and quantify material properties with environmental stress factors, comprehensively reflect the moisture resistance of corrugated paper in actual scenarios, and provide an intuitive decision-making basis for storage environment regulation, packaging solution selection, etc.

[0102] Among them, the current environmental temperature and humidity refer to the real-time temperature and relative humidity values ​​of the environment in which the corrugated paper sample is located when calculating the moisture resistance index. They are key environmental variables that affect the moisture absorption and resorption of the sample. For example, the temperature in the warehouse is 22°C and the relative humidity is 65% at the time of detection. This set of real-time temperature and humidity data is the current environmental temperature and humidity, which directly affects the moisture absorption dynamics of the sample. The moisture resistance index refers to a quantitative indicator generated by a specific algorithm based on the comprehensive anti-moisture resorption residual strength and the current environmental temperature and humidity. It is used to comprehensively evaluate the moisture resistance of the corrugated paper sample in the actual environment. For example, a certain The sample's residual strength against moisture resurgence is 75%, and the current ambient temperature and humidity are 25°C / 70%RH. The moisture resistance index calculated by the algorithm is 68 (value range 0-100). The higher the value, the stronger the moisture resistance. Optionally, the moisture resistance index corresponding to the corrugated paper sample can be generated through a multi-dimensional comprehensive evaluation technology, such as: using the analytic hierarchy process (AHP) combined with Python's PyDecision library to construct an evaluation index system, and finally obtaining a moisture resistance index that comprehensively considers moisture absorption rate, humidity attenuation index and residual strength against moisture resurgence.

[0103] Furthermore, the present invention can convert the abstract moisture resistance into an intuitive risk level by dividing the moisture resistance index into the corresponding moisture regain risk level, which is convenient for quickly identifying the degree of moisture threat of corrugated paper samples, and can formulate targeted differentiated prevention and control strategies (such as giving priority to high-risk samples), thereby improving the efficiency and accuracy of storage maintenance and quality control.

[0104] Among them, the moisture regain risk level refers to the classification of the moisture regain threat level of corrugated paper samples into different levels (such as low, medium and high risks) based on the moisture resistance index and moisture control threshold. For example, a moisture resistance index of >80 is low risk (green level), 50-80 is medium risk (yellow level), and <50 is high risk (red level), which is convenient for hierarchical management and risk warning.

[0105] As an embodiment of the present invention, the classification of the regain risk level corresponding to the moisture resistance performance index includes: based on the moisture resistance performance index, querying the key moisture change characteristics corresponding to the corrugated paper sample; analyzing the characteristic fluctuation index in the key moisture change characteristics; based on the characteristic fluctuation index, determining the core moisture range corresponding to the corrugated paper sample; generating a moisture control threshold corresponding to the core moisture range; based on the moisture control threshold, classifying the regain risk level corresponding to the moisture resistance performance index.

[0106] The key moisture-dependent characteristics refer to core humidity changes or structural performance indicators that are strongly correlated with the moisture resistance index. These reflect the key factors affecting corrugated paper moisture. For example, they include the humidity gradient between sample layers, the rate of residual strength loss after moisture resurgence, and the amplitude of ambient temperature and humidity fluctuations. These characteristics directly determine the essential attributes of moisture resurgence risk. The characteristic fluctuation index is a numerical indicator that quantifies the instability of key moisture-dependent characteristics over time or environmental changes. It is calculated using algorithms such as standard deviation and coefficient of variation. For example, if the measured humidity fluctuation range of a sample within 24 hours is ±3%RH, the characteristic fluctuation index is calculated to be 2.5. Larger values ​​indicate more unstable moisture-dependent characteristics. The core moisture-dependent range refers to the area or structural layer in the corrugated paper sample that is most severely affected by moisture and has the most significant impact on performance, as determined by the characteristic fluctuation index. For example, if analysis reveals that the core paper layer experiences significant humidity fluctuations and strength loss exceeding 30%, this core paper layer is designated as the core moisture-dependent range. The moisture control threshold refers to the humidity or strength critical value set for the core moisture-dependent range, which is used to determine whether moisture-resistant intervention measures need to be initiated. For example, the humidity threshold of the core moisture-affected area is set to 12% RH. When the measured value exceeds the threshold, the ventilation and drying equipment is triggered to operate.

[0107] Furthermore, the query of the key tidal change features corresponding to the corrugated paper sample can be achieved through principal component extraction technology, such as: using kernel principal component analysis (KPCA) combined with Python's Scikit-learn library to perform feature dimensionality reduction, and finally obtaining the key tidal change features reflecting the main humidity change mode; the analysis of the characteristic fluctuation index in the key tidal change features can be achieved through time-frequency analysis technology, such as: using the wavelet transform algorithm to calculate the characteristic energy distribution on the MATLAB platform, and finally obtaining the characteristic fluctuation index that characterizes the humidity fluctuation intensity; the determination of the core moisture range corresponding to the corrugated paper sample can be achieved through density peak clustering technology, such as : The CFSFDP algorithm is applied through Python's PyClustering library to identify high-density areas, and finally the core moisture-affected range where humidity anomalies are concentrated is obtained; the moisture control threshold corresponding to the core moisture-affected range can be generated by statistical process control technology, such as: the upper and lower control limits of humidity data are calculated using the Six Sigma method, and finally the moisture control threshold for humidity control is obtained; the division of the moisture-resistance risk level corresponding to the moisture-resistance efficiency index can be achieved through fuzzy comprehensive evaluation technology, such as: the fuzzy C-means clustering algorithm is combined with the Fclust package of R language for classification, and finally the moisture-resistance risk level that distinguishes different risk levels is obtained.

[0108] Specifically, to further understand the detection process corresponding to the resurgence risk level in this solution, you can refer to the Figure 2 The detection flow chart in this solution's corrugated paper property detection system clearly illustrates the core network structure, with the process organized into an input layer, a CNN-LSTM layer, and an output layer. The input layer incorporates parameters such as process flow rate and hot air temperature, forming the foundation for subsequent analysis of interlayer moisture variation data and calculation of the remaining moisture resurgence strength. This provides the raw material for exploring moisture distribution characteristics and quantifying attenuation indicators. The CNN-LSTM layer, composed of multiple layers of LSTM, leverages its time series feature extraction capabilities to accurately capture the dynamic changes in interlayer moisture with the environment and time, meeting the needs of analyzing moisture diffusion gradients and classifying moisture sensitivity levels. The output layer outputs sample moisture content and temperature, directly contributing to the generation of the moisture resistance performance index and the determination of moisture resurgence risk levels. These layers work together to form a complete chain from data collection to risk assessment, flexibly adapting to relationship analysis and parameter adjustment in different scenarios.

[0109] S4. Based on the moisture regain risk level, configure a multi-stage warning indicator corresponding to the corrugated paper sample, locate the edge moisture absorption area corresponding to the corrugated paper sample based on the multi-stage warning indicator, and calculate the moisture diffusion gradient value corresponding to the edge moisture absorption area.

[0110] Based on the rewetting risk level, the present invention configures multi-level warning indicators corresponding to the corrugated paper samples, and can set differentiated monitoring thresholds for different threat levels to achieve full-chain warning coverage from slight moisture to serious risks, so as to improve the refinement and dynamic adaptability of corrugated paper rewetting risk management.

[0111] The multi-level warning indicators refer to different levels of warning thresholds and corresponding response rules based on the level of rewet risk, setting a tiered warning standard using multi-dimensional data (such as humidity, strength, and environmental parameters). For example, a three-level warning indicator is set for corrugated paper samples: low risk (humidity <10%RH, moisture resistance index >70) triggers a yellow alert; medium risk (humidity 10%-15%RH, index 50-70) triggers an orange alert; and high risk (humidity >15%RH, index <50) triggers a red emergency alert. Each level corresponds to a different monitoring frequency and response measures. Optionally, configuring the multi-level warning indicators corresponding to the corrugated paper samples can be achieved through dynamic threshold optimization technology, such as using an adaptive sliding window algorithm combined with Python's Pandas library to calculate environmental parameter percentiles in real time, ultimately obtaining three-level warning indicators (warning value, danger value, and critical value) based on the distribution of historical data.

[0112] Furthermore, the present invention locates the edge moisture absorption area corresponding to the corrugated paper sample based on the multi-level warning indicators, and can use the graded threshold to quickly lock the hidden moisture-affected parts of the sample edge caused by differences in environmental contact, thereby avoiding quality risks caused by conventional detection blind spots and improving the balance and reliability of the overall moisture resistance of the corrugated paper.

[0113] Among them, the edge moisture absorption area refers to the specific location and range of the actual moisture absorption phenomenon on the edge of the corrugated paper sample, confirmed based on real-time humidity data. It is usually an area where the humidity exceeds the abnormal baseline and shows a continuous upward trend. For example, by comparing the monitoring data, it is determined that the humidity at 20-40 cm on the right edge of the sample reaches 12%RH (exceeding the low-risk baseline of 10%RH) and is still rising. This area is identified as the edge moisture absorption area.

[0114] As an embodiment of the present invention, locating the edge moisture absorption area corresponding to the corrugated paper sample based on the multi-level warning indicators includes: analyzing the abnormal baselines of each level corresponding to the multi-level warning indicators; delineating the potential moisture absorption range corresponding to the corrugated paper sample based on the abnormal baselines of each level; screening the core monitoring points in the potential moisture absorption range; collecting real-time humidity data corresponding to the core monitoring points; and locating the edge moisture absorption area corresponding to the corrugated paper sample based on the real-time humidity data.

[0115] Among them, the abnormal baselines of each level refer to the critical values ​​or normal fluctuation range boundaries of the humidity, moisture resistance index and other data corresponding to each level of risk in the multi-level warning indicators, which are used to determine whether the sample has abnormal moisture absorption. For example, the abnormal baseline of the low-risk warning level is humidity ≥10%RH and moisture resistance index ≤70. When the measured data breaks through the baseline, it indicates that the abnormal state has been entered; the potential moisture absorption range refers to the suspected moisture range defined in the areas where the corrugated paper sample may be exposed to environmental moisture (such as edges and seams) based on the abnormal baselines of each level. For example, for the 5cm width area at the edge of the sample, the "humidity ≥8% "RH" is the potential moisture absorption range, which preliminarily locks the parts that need to be tested; the core monitoring points refer to key positions that are sensitive to moisture penetration or easily affected by moisture within the potential moisture absorption range, which are usually the corners of the sample edge, the interface between layers, etc. For example, on the left and right edges of three-layer corrugated paper, a monitoring point is set every 10 cm, and a total of 5 core points are selected for intensive collection of humidity data; the real-time humidity data refers to the humidity value obtained in real time by the sensor at the core monitoring points, reflecting the current actual moisture content of the sample edge, which is timely and dynamic. For example, the humidity of a core point is measured to be 11.2%RH at 14:00 and 11.5%RH after 1 hour. These two sets of data are the real-time humidity data of the point.

[0116] Furthermore, the analysis of each order abnormal baseline corresponding to the multi-order warning indicators can be achieved through quantile regression technology, such as: using Python's Statsmodels library to calculate the 95%, 85%, and 75% quantile values ​​of the environmental parameters, and finally obtaining each order abnormal baseline corresponding to different warning levels; the delineation of the potential moisture absorption range corresponding to the corrugated paper sample can be achieved through Gaussian mixture model, such as: using Scikit-learn's GMM algorithm to fit the historical humidity data distribution, and finally obtaining the potential moisture absorption range with a probability density exceeding a threshold; the screening of the core monitoring points in the potential moisture absorption range can be achieved through Spatial sampling optimization technology is implemented, such as: applying the Kriging interpolation method combined with the spatial analysis tool of ArcGIS to determine key representative points, and finally obtaining the core monitoring points covering the main variation areas; the collection of real-time humidity data corresponding to the core monitoring points can be achieved through the Internet of Things sensor network, such as: deploying the SHT85 high-precision sensor array of LoRaWAN networking, and finally obtaining time-synchronized real-time humidity data; the positioning of the edge moisture absorption area corresponding to the corrugated paper sample can be achieved through the edge detection algorithm, such as: using the Canny operator to process infrared thermal imaging data, and finally obtaining the edge moisture absorption area where the humidity gradient suddenly changes.

[0117] By calculating the moisture diffusion gradient corresponding to the edge moisture absorption area, the present invention can quantify the rate and range of moisture penetration from the edge of the sample to the interior, revealing the dynamic characteristics of the moisture absorption path. The gradient value can intuitively reflect the degree of threat posed by edge moisture to the main structure of the sample, and provide accurate data support for formulating targeted moisture-proof barrier solutions and optimizing storage environment control strategies.

[0118] Among them, the moisture diffusion gradient value refers to a comprehensive indicator used to quantify the speed and trend of moisture diffusion in the hygroscopic area of ​​the edge of corrugated paper. By integrating factors such as sub-area humidity changes, spatial length, ambient temperature and humidity, it reflects the "gradient intensity" of moisture penetration and diffusion in the edge area. The larger the value, the more intense the moisture diffusion in the area and the more significant the impact on the corrugated paper structure. It is the core quantitative basis for assessing the risk of edge moisture.

[0119] As an embodiment of the present invention, the calculating of the moisture diffusion gradient value corresponding to the edge hygroscopic area includes:

[0120] The moisture diffusion gradient corresponding to the edge hygroscopic area is calculated using the following formula:

[0121]

[0122] in, Indicates the moisture diffusion gradient corresponding to the edge hygroscopic area, represents the total number of sub-regions corresponding to the edge hygroscopic region, Indicates the quantity index corresponding to the sub-region, and Respectively represent the start and end time of the detection time interval, Indicates the The humidity change of each sub-region at time t is: Indicates the The length of the sub-region, Indicates the average temperature within the detection time interval. represents the reference temperature, Represents the average relative humidity within the detection time interval. Indicates reference relative humidity.

[0123] Furthermore, the sub-region refers to the smallest analysis unit that subdivides the moisture absorption area of ​​the corrugated paper edge. Since the moisture diffusion conditions at different positions of the edge (such as the upper left corner and the middle of the right side) are different (such as the contact area with the environment and the interlayer structure), it is necessary to divide it into multiple sub-regions (indexed by k), calculate them separately and then integrate them, so that the diffusion gradient value can more accurately reflect the local details and avoid the overall average covering up the key differences; the detection time interval refers to the continuous monitoring time range selected for analyzing the dynamics of moisture diffusion, from the starting time To the end , continuously collects sub-region humidity and ambient temperature and humidity data to capture the cumulative effect of moisture diffusion "over a period of time" rather than static instantaneous values, which is more in line with the actual dynamic process of moisture exposure. The humidity change refers to the difference in humidity between time t and the initial time (or adjacent time) in the k-th sub-region, reflecting the dynamic fluctuation of humidity in the sub-region over time (for example, if the humidity at time t is 3%RH higher than at time t-1, the difference is +3%RH). It is the basic data for calculating the "diffusion rate" and directly reflects the intensity of moisture intrusion / diffusion in the sub-region. The region length refers to the spatial extension of the k-th sub-region. Because moisture diffusion is affected by distance (the longer the diffusion, the greater the resistance), this parameter is used to normalize the "distribution of humidity change over space" to make diffusion data of sub-regions of different lengths comparable (similar to the "humidity change rate per unit length" logic). The average temperature refers to the arithmetic mean of the ambient temperature within the detection time interval (for example, if monitoring for 24 hours, the temperature is measured once every hour, and the sum is divided by 24). Temperature affects the water activity and hygroscopic properties of corrugated paper fibers. The average temperature is used to quantify the continuous driving effect of the environmental "thermal state" on water diffusion, and is compared with the reference temperature ( ), reflecting the degree to which the actual temperature deviates from the standard environment; the reference temperature refers to the set standard ambient temperature benchmark value (such as 20℃, which is the reference value of "no significant temperature change effect" agreed by the industry or experiment), which is compared with the average temperature ( ), converting the actual temperature into the "influence coefficient of the relative standard environment", eliminating the difference in absolute temperature values, and making the formula adaptable to the benchmark settings of different experiments / application scenarios; the average relative humidity refers to the arithmetic mean of the relative humidity of the environment within the detection time interval (similar to the average temperature, such as measuring RH every hour for 24 hours, summing the results and dividing by 24). Relative humidity is the core indicator of the "power source" of water diffusion. The average RH is used to quantify the overall humidity of the environment and is compared with the reference relative humidity ( ), reflecting the deviation of actual humidity from the standard environment and reflecting the environmental driving force of water diffusion; the reference relative humidity refers to the set standard environmental relative humidity benchmark value (such as 50%RH, which is the agreed "no significant hygroscopic driving" reference value), compared with the average relative humidity ( ), converting the actual humidity into a "driving coefficient relative to a standard environment", unifying the quantitative logic of humidity impact in different environments, and making the formula universal across scenarios.

[0124] S5. Based on the moisture diffusion gradient value, generate a humidity stabilization signal corresponding to the corrugated paper sample, send the humidity stabilization signal to a preset humidity monitoring terminal, obtain terminal feedback data, and formulate a regain detection strategy corresponding to the corrugated paper sample based on the terminal feedback data.

[0125] The present invention generates a humidity stability signal corresponding to the corrugated paper sample based on the moisture diffusion gradient value, can accurately quantify the moisture dynamics in the edge moisture absorption area, and convert complex diffusion data into an intuitive stable state indicator, so as to help identify moisture risk trends in advance and ensure the quality and reliability of corrugated paper from the source.

[0126] Among them, the humidity stabilization signal refers to the instruction / mark output based on the steady-state control factor to stabilize the humidity state of the corrugated paper (such as "start dehumidification, target humidity 50%RH", "maintain the current environment, the humidity has stabilized"). For example: when the control factor determines that dehumidification is required, a signal is generated to "turn on the dehumidification system and adjust the environmental RH to 45%" to guide the operation and ensure the stability of the sample humidity.

[0127] As an embodiment of the present invention, the generation of the humidity stability signal corresponding to the corrugated paper sample based on the moisture diffusion gradient includes: parsing the dynamic permeation interval corresponding to the moisture diffusion gradient; dividing the humidity sensitive level corresponding to the corrugated paper sample based on the dynamic permeation interval; querying the hygroscopic balance data associated with the level change in the humidity sensitive level; extracting the steady-state control factor in the hygroscopic balance data; and generating the humidity stability signal corresponding to the corrugated paper sample based on the steady-state control factor.

[0128] Among them, the dynamic penetration interval refers to the dynamic range of moisture penetration in the edge area of ​​corrugated paper based on the moisture diffusion gradient, which is divided by the gradient fluctuation boundary (such as the gradient value 0.2-1.5 corresponds to the penetration range), reflecting the "activity range" of moisture diffusion over time and space. For example, when the gradient value of the corrugated paper sample is 0.8-1.2, it corresponds to the moisture penetration depth range of 2-5mm, that is, the dynamic penetration interval is [2mm, 5mm]; the humidity sensitivity level refers to the grading of the sensitivity of corrugated paper to humidity according to the dynamic penetration interval. According to the gradient value size / penetration strength, the sample is divided into low sensitivity, medium sensitivity, high sensitivity and other levels, reflecting the difference in the impact of humidity changes on its structure. For example, a gradient value ≤0.5 corresponds to a "low sensitivity level" (humidity fluctuations have little effect on the strength of corrugated paper); a gradient value ≥1.2 corresponds to a "high sensitivity level" (easy to deform rapidly due to humidity); the moisture absorption balance data refers to a parameter set associated with the humidity sensitivity level when the moisture absorption / desorption of corrugated paper reaches a stable state under a specific humidity environment. (such as equilibrium humidity, moisture content, fiber expansion rate, etc.), for example: the hygroscopic balance data corresponding to the high-sensitivity level may include "equilibrium humidity 75%RH, fiber expansion rate 8%", reflecting the state of the material after stable moisture absorption; the steady-state control factor refers to the key parameters extracted from the hygroscopic balance data that can intervene in the humidity state of corrugated paper and make it tend to be stable (such as environmental humidity control threshold, ventilation volume, moisture-proof agent dosage, etc.), for example: at the low-sensitivity level, the steady-state control factor may be "ambient humidity maintained at 50%RH±5%, ventilation 2 times per hour", which is used to keep the sample humidity stable.

[0129] Further, the analyzing the dynamic permeation interval corresponding to the water diffusion gradient can be achieved by finite element simulation technology, such as: using COMSOL Multiphysics software to establish a porous medium mass transfer model, and finally obtaining the dynamic permeation interval of the water diffusion rate change; the dividing the humidity sensitive level corresponding to the corrugated paper sample can be achieved by fuzzy clustering analysis technology, such as: applying FCM algorithm combined with MATLAB Fuzzy Logic Toolbox to classify humidity response characteristics, and finally obtaining humidity sensitive levels of different sensitivity; the querying the moisture absorption equilibrium data associated with the level change in the humidity sensitive level can be achieved by database association mining technology, such as: using the association rule mining function of SQL Server to analyze the historical environment-moisture content corresponding relationship, and finally obtaining the moisture absorption equilibrium data corresponding to each level; the extracting the steady-state regulation factor in the moisture absorption equilibrium data can be achieved by principal component regression technology, such as: using PLS algorithm to calculate the key influence variable through SIMCA software, and finally obtaining the dominant humidity balance steady-state regulation factor; the generating the humidity stability signal corresponding to the corrugated paper sample can be achieved by control theory modeling technology, such as: establishing a PID control model to calculate the humidity deviation in real time through LabVIEW, and finally outputting the humidity stability signal representing the stable state.

[0130] The application sends the humidity stability signal to the preset humidity monitoring terminal, obtains terminal feedback data, opens the data interaction link, enables the terminal to obtain the corrugated paper humidity regulation requirement in real time, facilitates remote precise intervention on environmental parameters, verifies the effectiveness of the regulation strategy, forms a "monitoring-regulation-feedback-optimization" closed loop, dynamically ensures the stability of the corrugated paper storage environment, and improves the quality control efficiency from the data cooperation dimension.

[0131] The preset humidity monitoring terminal refers to a device or system that is deployed in advance and is used for monitoring and regulating the humidity of the corrugated paper storage environment, has data receiving, instruction execution and feedback functions, can integrate sensors and controllers, for example, an intelligent temperature and humidity monitoring system in a warehouse, can receive the humidity stability signal, automatically adjusts the dehumidifier and humidifier, and controls the environment in real time; the terminal feedback data refers to the execution state and environmental data returned by the humidity monitoring terminal after receiving and executing the humidity stability signal, including instruction execution results (such as whether the dehumidifier is started), real-time temperature and humidity, and equipment operating parameters (such as the working power of the humidifier), for example, the terminal feedback "has executed the dehumidification instruction, the current humidity is 55% RH, and the dehumidifier operating power is 800W"; optionally, the sending of the humidity stability signal to the preset humidity monitoring terminal can be achieved by Internet of Things protocol transmission technology, such as: using MQTT protocol combined with ESP32 microcontroller to build a low-power wireless transmission system, and finally obtaining terminal feedback data containing signal receiving confirmation and real-time state update.

[0132] Furthermore, the present invention formulates a regain detection strategy corresponding to the corrugated paper sample based on the terminal feedback data. It can accurately match the detection frequency, points and methods according to the actual effect of environmental control and the sample humidity dynamics, and can dynamically optimize the detection plan to ensure timely capture of regain risk changes, improve the timeliness and pertinence of detection, and realize the upgrade of the detection mode from passive response to active prevention.

[0133] Among them, the regain detection strategy refers to a systematic regain risk detection plan formulated for corrugated paper samples based on terminal feedback data, covering detection time (such as high frequency / low frequency), detection points (such as core moisture-affected areas / edges), detection methods (such as humidity sensors / compressive strength tests) and risk response rules. The strategy is dynamically adjusted with terminal data to adapt to real-time environmental changes and sample status. For example, if the terminal feedback shows that the humidity in a certain area continues to be higher than the threshold after control, the strategy can be adjusted to "three key humidity scans in the area every day + one compressive strength spot check per week", and the warehouse management system is linked to mark high-risk samples to achieve precise deployment of detection resources and closed-loop risk management. Optionally, the formulation of the regain detection strategy corresponding to the corrugated paper sample can be achieved through decision tree optimization technology, such as: using the CART algorithm combined with Python's Scikit-learn library to construct a multi-condition judgment model, and finally obtaining a regain detection strategy including detection frequency, monitoring points and warning thresholds.

[0134] Compared with the problems described in the background technology, the present invention obtains the storage environment of the corrugated paper sample and collects detailed environmental data corresponding to the storage environment, which can provide basic information for subsequent analysis, accurately grasp the impact of environmental factors on the moisture regain of corrugated paper, and more accurately carry out dynamic moisture absorption analysis, structural moisture judgment and other tasks, thereby improving the effectiveness of anti-moisture regain detection. The present invention analyzes the structural moisture state corresponding to the corrugated paper sample based on the moisture penetration rate, and can accurately quantify the degree of moisture intrusion, clarify the moisture differences in different areas and layers, and provide a key basis for evaluating structural stability and damage resistance, helping to provide early warning of failure risks and optimize protection strategies in storage and use. Furthermore, the present invention analyzes the anti-moisture regain residual strength corresponding to the corrugated paper sample based on the inter-layer moisture change data, which can deeply analyze the impact of moisture penetration on the structure of each layer. The specific impact of strength can be quantified, and the degree of strength attenuation caused by moisture absorption can be quantified. Through the correlation analysis of inter-layer humidity differences and strength loss, the weak links in moisture resistance can be accurately located, thereby supporting the formulation of targeted reinforcement or moisture-proofing plans. Furthermore, based on the rewetting risk level, the present invention configures multi-level warning indicators corresponding to the corrugated paper sample, and can set differentiated monitoring thresholds for different threat levels to achieve full-chain warning coverage from slight moisture to serious risks, so as to improve the refinement and dynamic adaptability of corrugated paper rewetting risk management. Finally, based on the moisture diffusion gradient, the present invention generates a humidity stability signal corresponding to the corrugated paper sample, which can accurately quantify the moisture dynamics of the edge moisture absorption area, convert complex diffusion data into an intuitive stable state indicator, help identify moisture risk trends in advance, and ensure the quality and reliability of corrugated paper from the source. Therefore, the corrugated paper anti-rewetting detection method and system provided by the embodiment of the present invention can ensure the accuracy of corrugated paper rewetting detection.

[0135] Example 2:

[0136] like Figure 3 FIG. 1 is a functional module diagram of a corrugated paper moisture-regain detection system according to the present invention.

[0137] The corrugated paper moisture resurgence detection system 200 described in the present invention can be installed in an electronic device. Depending on the functionality implemented, the system can include a rate calculation module 201, a delamination detection module 202, a grading module 203, a ladder value calculation module 204, and a strategy formulation module 205. A module, also referred to as a unit, is a series of computer program segments that can be executed by an electronic device processor and perform a fixed function. These modules are stored in the electronic device's memory.

[0138] In the embodiment of the present invention, the functions of each module / unit are as follows:

[0139] The rate calculation module 201 is used to obtain the storage environment of the corrugated paper sample and collect detailed environmental data corresponding to the storage environment. Based on the detailed environmental data, the module performs a dynamic moisture absorption analysis on the corrugated paper sample to obtain a dynamic moisture absorption characteristic and calculate the moisture penetration rate corresponding to the dynamic moisture absorption data.

[0140] The delamination detection module 202 is configured to analyze the structural moisture state of the corrugated paper sample based on the moisture permeation rate, query the moisture regain index corresponding to the structural moisture state, and perform delamination moisture detection on the corrugated paper sample based on the moisture regain index to obtain inter-layer moisture change data;

[0141] The grading module 203 is configured to analyze the moisture resurgence residual strength corresponding to the corrugated paper sample based on the inter-layer moisture change data, generate a moisture resurgence performance index corresponding to the corrugated paper sample based on the moisture resurgence residual strength combined with the current ambient temperature and humidity, and categorize the moisture resurgence risk level corresponding to the moisture resurgence performance index;

[0142] The gradient value calculation module 204 is used to configure a multi-level warning index corresponding to the corrugated paper sample based on the moisture regain risk level, locate the edge moisture absorption area corresponding to the corrugated paper sample based on the multi-level warning index, and calculate the moisture diffusion gradient value corresponding to the edge moisture absorption area;

[0143] The strategy formulation module 205 is used to generate a humidity stability signal corresponding to the corrugated paper sample based on the moisture diffusion gradient value, send the humidity stability signal to a preset humidity monitoring terminal, obtain terminal feedback data, and formulate a regain detection strategy corresponding to the corrugated paper sample based on the terminal feedback data.

[0144] In detail, each module in the corrugated paper moisture-regain detection system 200 according to the embodiment of the present invention adopts the same method as above when in use. Figure 1 The same technical means as the corrugated paper anti-regain detection method described in , and can produce the same technical effects, will not be repeated here.

[0145] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the spirit or essential characteristics of the present invention.

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not limiting. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention.

Claims

1. A method for detecting moisture regain resistance of corrugated paper, characterized in that: The method comprises: Obtaining a storage environment in which a corrugated paper sample is located, collecting detailed environmental data corresponding to the storage environment, and performing a dynamic moisture absorption analysis on the corrugated paper sample based on the detailed environmental data to obtain a dynamic moisture absorption characteristic, wherein performing a dynamic moisture absorption analysis on the corrugated paper sample based on the detailed environmental data to obtain a dynamic moisture absorption characteristic includes: Analyzing the initial environmental conditions corresponding to the detailed environmental data; Querying the initial moisture content of the corrugated paper sample under the initial environmental conditions; Analyze the moisture absorption rate characteristics corresponding to the initial moisture content; Based on the moisture absorption rate characteristic, identifying moisture distribution data corresponding to the corrugated paper sample; Based on the moisture distribution data, a dynamic moisture absorption analysis is performed on the corrugated paper sample to obtain a dynamic moisture absorption characteristic, and a moisture permeation rate corresponding to the dynamic moisture absorption characteristic is calculated, wherein the calculating of the moisture permeation rate corresponding to the dynamic moisture absorption characteristic includes: The water permeation rate corresponding to the dynamic moisture absorption characteristics is calculated using the following formula: in, represents the water penetration rate corresponding to the dynamic moisture absorption characteristics, represents the total number of environmental monitoring points, Indicates the number index of environmental monitoring points, and Respectively represent the start time and end time of the dynamic moisture absorption analysis process, Indicates in Environmental monitoring points, Moment and The relative humidity difference at time Indicates in Environmental monitoring points, Moment and The temperature difference at time represents the surface area of ​​the corrugated paper corresponding to the i-th environmental monitoring point, Indicates the total number of layers corresponding to the corrugated paper sample, Indicates the hierarchical index corresponding to the corrugated paper sample, represents the thickness of the jth layer of the corrugated paper sample, represents the mass change rate of the jth layer of the corrugated paper sample at time t under the i-th environmental monitoring point; Based on the moisture permeation rate, analyzing the structural moisture state corresponding to the corrugated paper sample, querying the moisture regain index corresponding to the structural moisture state, and performing layered humidity detection on the corrugated paper sample based on the moisture regain index to obtain inter-layer moisture change data, wherein the layered moisture detection on the corrugated paper sample based on the moisture regain index to obtain inter-layer moisture change data includes: Query the humidity stratification threshold corresponding to the moisture regain index; Dividing the detection layers of the corrugated paper sample based on the humidity stratification threshold; Scanning the measured humidity values ​​corresponding to each layer of the corrugated paper sample according to the detection layer position; Comparing the measured humidity value with a preset humidity reference value to obtain an inter-layer difference sequence; Based on the inter-layer difference sequence, the corrugated paper sample is subjected to layered humidity detection to obtain inter-layer moisture change data; Analyzing the moisture resurgence residual strength corresponding to the corrugated paper sample based on the inter-layer moisture change data, wherein analyzing the moisture resurgence residual strength corresponding to the corrugated paper sample based on the inter-layer moisture change data includes: extracting interlayer distribution features from the interlayer tidal change data; Determining a tide change impact area corresponding to the corrugated paper sample according to the interlayer distribution characteristics; Quantify the humidity attenuation index corresponding to the tidal change affected area; Based on the humidity attenuation index, evaluating the local moisture resistance difference corresponding to the corrugated paper sample; Based on the local moisture resistance difference, analyzing the corresponding moisture resurgence residual strength of the corrugated paper sample, generating the corresponding moisture resistance efficiency index of the corrugated paper sample based on the moisture resurgence residual strength combined with the current ambient temperature and humidity, and classifying the moisture resurgence risk level corresponding to the moisture resistance efficiency index; Based on the moisture regain risk level, a multi-stage warning indicator corresponding to the corrugated paper sample is configured; based on the multi-stage warning indicator, an edge moisture absorption area corresponding to the corrugated paper sample is located; and a moisture diffusion gradient value corresponding to the edge moisture absorption area is calculated. Calculating the moisture diffusion gradient value corresponding to the edge moisture absorption area includes: The moisture diffusion gradient corresponding to the edge hygroscopic area is calculated using the following formula: in, Indicates the moisture diffusion gradient corresponding to the edge hygroscopic area, represents the total number of sub-regions corresponding to the edge hygroscopic region, Indicates the quantity index corresponding to the sub-region, and Respectively represent the start and end time of the detection time interval, Indicates the The humidity change of each sub-region at time t is: Indicates the The length of the sub-region, Indicates the average temperature within the detection time interval. represents the reference temperature, Represents the average relative humidity within the detection time interval, Indicates the reference relative humidity; Based on the moisture diffusion gradient value, a humidity stabilization signal corresponding to the corrugated paper sample is generated, and the humidity stabilization signal is sent to a preset humidity monitoring terminal to obtain terminal feedback data. Based on the terminal feedback data, a regain detection strategy corresponding to the corrugated paper sample is formulated.

2. A method for detecting moisture regain resistance of corrugated paper according to claim 1, characterized in that: The classification of the moisture resurgence risk level corresponding to the moisture resistance index includes: Based on the moisture resistance index, query the key moisture change characteristics corresponding to the corrugated paper sample; Analyzing characteristic fluctuation indexes in the key tidal characteristics; Determining a core moisture range corresponding to the corrugated paper sample based on the characteristic fluctuation index; Generate a moisture control threshold corresponding to the core moisture range; Based on the moisture control threshold, the moisture resurgence risk level corresponding to the moisture resistance efficiency index is divided.

3. A method for detecting moisture regain resistance of corrugated paper according to claim 1, characterized in that: The step of locating the edge moisture absorption area corresponding to the corrugated paper sample based on the multi-level warning indicators includes: Analyze the abnormal baselines of each level corresponding to the multi-level warning indicators; Delineating the potential moisture absorption range corresponding to the corrugated paper sample according to the abnormal baselines of each order; Screening the core monitoring points in the potential moisture absorption range; Collecting real-time humidity data corresponding to the core monitoring points; The edge moisture absorption area corresponding to the corrugated paper sample is located according to the real-time humidity data.

4. A method for detecting moisture regain resistance of corrugated paper according to claim 1, characterized in that: Generating a humidity stability signal corresponding to the corrugated paper sample based on the moisture diffusion gradient value includes: Analyze the dynamic permeability range corresponding to the water diffusion gradient value; Based on the dynamic permeability interval, dividing the corrugated paper sample into humidity sensitive levels; querying the moisture balance data associated with the level change in the humidity sensitive level; extracting steady-state regulatory factors from the hygroscopic balance data; Based on the steady-state control factor, a humidity stability signal corresponding to the corrugated paper sample is generated.

5. A corrugated paper moisture resurgence detection system, characterized in that: The system is used to perform a method for detecting moisture regain resistance of corrugated paper according to any one of claims 1 to 4, comprising: A rate calculation module is used to obtain the storage environment of the corrugated paper sample and collect detailed environmental data corresponding to the storage environment. Based on the detailed environmental data, a dynamic moisture absorption analysis is performed on the corrugated paper sample to obtain a dynamic moisture absorption characteristic. The dynamic moisture absorption analysis is performed on the corrugated paper sample based on the detailed environmental data to obtain a dynamic moisture absorption characteristic, wherein the dynamic moisture absorption analysis is performed on the corrugated paper sample based on the detailed environmental data to obtain a dynamic moisture absorption characteristic, including: Analyzing the initial environmental conditions corresponding to the detailed environmental data; Querying the initial moisture content of the corrugated paper sample under the initial environmental conditions; Analyze the moisture absorption rate characteristics corresponding to the initial moisture content; Based on the moisture absorption rate characteristic, identifying moisture distribution data corresponding to the corrugated paper sample; Based on the moisture distribution data, a dynamic moisture absorption analysis is performed on the corrugated paper sample to obtain a dynamic moisture absorption characteristic, and a moisture permeation rate corresponding to the dynamic moisture absorption characteristic is calculated, wherein the calculating of the moisture permeation rate corresponding to the dynamic moisture absorption characteristic includes: The water permeation rate corresponding to the dynamic moisture absorption characteristics is calculated using the following formula: in, represents the water penetration rate corresponding to the dynamic moisture absorption characteristics, represents the total number of environmental monitoring points, Indicates the number index of environmental monitoring points, and Respectively represent the start time and end time of the dynamic moisture absorption analysis process, Indicates in Environmental monitoring points, Moment and The relative humidity difference at time Indicates in Environmental monitoring points, Moment and The temperature difference at time represents the surface area of ​​the corrugated paper corresponding to the i-th environmental monitoring point, Indicates the total number of layers corresponding to the corrugated paper sample, Indicates the hierarchical index corresponding to the corrugated paper sample, represents the thickness of the jth layer of the corrugated paper sample, represents the mass change rate of the jth layer of the corrugated paper sample at time t under the i-th environmental monitoring point; A delamination detection module is configured to analyze the structural moisture state corresponding to the corrugated paper sample based on the moisture permeation rate, query the moisture regain index corresponding to the structural moisture state, and perform delamination humidity detection on the corrugated paper sample based on the moisture regain index to obtain inter-layer moisture change data, wherein the delamination humidity detection on the corrugated paper sample based on the moisture regain index to obtain inter-layer moisture change data includes: Query the humidity stratification threshold corresponding to the moisture regain index; Dividing the detection layers of the corrugated paper sample based on the humidity stratification threshold; Scanning the measured humidity values ​​corresponding to each layer of the corrugated paper sample according to the detection layer position; Comparing the measured humidity value with a preset humidity reference value to obtain an inter-layer difference sequence; Based on the inter-layer difference sequence, the corrugated paper sample is subjected to layered humidity detection to obtain inter-layer moisture change data; A grading module is configured to analyze the moisture resurgence residual strength corresponding to the corrugated paper sample based on the inter-layer moisture change data, wherein the moisture resurgence residual strength corresponding to the corrugated paper sample based on the inter-layer moisture change data includes: extracting interlayer distribution features from the interlayer tidal change data; Determining a tide change impact area corresponding to the corrugated paper sample according to the interlayer distribution characteristics; Quantify the humidity attenuation index corresponding to the tidal change affected area; Based on the humidity attenuation index, evaluating the local moisture resistance difference corresponding to the corrugated paper sample; Based on the local moisture resistance difference, analyzing the corresponding moisture resurgence residual strength of the corrugated paper sample, generating the corresponding moisture resistance efficiency index of the corrugated paper sample based on the moisture resurgence residual strength combined with the current ambient temperature and humidity, and classifying the moisture resurgence risk level corresponding to the moisture resistance efficiency index; A gradient value calculation module is configured to configure a multi-stage warning index corresponding to the corrugated paper sample based on the moisture regain risk level, locate the edge moisture absorption area corresponding to the corrugated paper sample based on the multi-stage warning index, and calculate the moisture diffusion gradient value corresponding to the edge moisture absorption area, wherein the calculation of the moisture diffusion gradient value corresponding to the edge moisture absorption area includes: The moisture diffusion gradient corresponding to the edge hygroscopic area is calculated using the following formula: in, Indicates the moisture diffusion gradient corresponding to the edge hygroscopic area, represents the total number of sub-regions corresponding to the edge hygroscopic region, Indicates the quantity index corresponding to the sub-region, and Respectively represent the start and end time of the detection time interval, Indicates the The humidity change of each sub-region at time t is: Indicates the The length of the sub-region, Indicates the average temperature within the detection time interval. represents the reference temperature, Represents the average relative humidity within the detection time interval, Indicates the reference relative humidity; A strategy formulation module is used to generate a humidity stability signal corresponding to the corrugated paper sample based on the moisture diffusion gradient value, send the humidity stability signal to a preset humidity monitoring terminal, obtain terminal feedback data, and formulate a regain detection strategy corresponding to the corrugated paper sample based on the terminal feedback data.

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