A storage material atmosphere conditioning maintenance early warning method and system based on environmental monitoring

Abstract

The present invention relates to the field of environmental monitoring technology, and specifically to a storage gas conditioning maintenance early warning method and system based on environmental monitoring, including the following steps: collecting real-time gas composition, temperature and humidity data, time-sorting the collected data, identifying the change trend of multiple parameters at each time point, and obtaining parameter trend prediction results. In the present invention, by combining data time sorting with change trend analysis, analyzing the relationship between parameters and environmental safety values ​​and identifying over-threshold variables, accurate adjustment of gas and temperature and humidity is ensured, and the pertinence of parameter control is improved. Through continuous monitoring and dynamic data classification, high-frequency fluctuation areas are marked for early warning, and the monitoring ability of the quality status of stored items is improved, thereby reducing the loss of items caused by environmental changes. The method of data analysis and real-time monitoring is integrated, the operating logic of the environmental controller is optimized, and the overall performance and resource utilization efficiency of the system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of environmental monitoring, and in particular to an environmental monitoring-based storage material atmosphere conditioning maintenance early warning method and system. Background Art

[0002] The field of environmental monitoring technology mainly studies the technologies and methods for monitoring and analyzing physical, chemical and biological elements in the environment. The focus is on obtaining the quality status and dynamic changes of air, water, soil and other media in the environment in real time, and monitoring and managing environmental factors through sensors, analytical instruments and data processing systems. This technology is widely used in climate change research, pollution source detection, ecological protection and environmental control in industrial production, providing scientific basis and technical support for environmental protection, resource management and sustainable development.

[0003] The storage gas conditioning maintenance early warning method based on environmental monitoring is a new technical solution for the maintenance of stored goods that combines modern environmental monitoring technology and gas control methods. Its core purpose is to ensure the quality and safety of stored goods by real-time monitoring of key factors such as temperature, humidity and gas composition in the storage environment, combined with gas conditioning control methods and early warning mechanisms, and reduce the risk of loss caused by environmental changes during storage. It is widely used in the storage management of agricultural products, food and industrial raw materials.

[0004] Existing technologies rely on traditional sensors and analytical instruments. The equipment cannot meet the requirements of high efficiency and high precision in terms of rapid detection and precise control of dynamic environmental changes. Existing data processing systems fail to fully implement advanced data analysis, such as automatic identification of fluctuation trends and early warning markers for key parameters, resulting in untimely or inaccurate response to environmental changes, increasing the risk of loss of stored items due to environmental inadaptability. The lack of real-time early warning and dynamic control functions has caused irreversible damage to stored agricultural products before sudden increases in temperature or humidity are detected. Summary of the invention

[0005] In order to solve the existing problems that the existing technology relies on traditional sensors and analytical instruments, the equipment cannot meet the requirements of high efficiency and high precision in the rapid detection and precise control of dynamic environmental changes, the existing data processing system fails to fully realize advanced data analysis, such as automatic identification of fluctuation trends and early warning marks of key parameters, resulting in untimely or inaccurate response to environmental changes, increasing the risk of loss of stored items due to environmental inadaptability, and the lack of real-time early warning and dynamic control functions, resulting in irreversible damage to stored agricultural products before the sudden increase in temperature or humidity is detected, the embodiment of the present invention provides a storage gas conditioning maintenance early warning method and system based on environmental monitoring. The technical solution is as follows:

[0006] On the one hand, a storage material atmosphere conditioning maintenance early warning method based on environmental monitoring is provided, comprising the following steps:

[0007] S1: Collect real-time gas composition, temperature and humidity data, sort the collected data by time, identify the changing trends of multiple parameters at each time point, and compare the parameter stability within the trend fluctuation range, analyze the upper and lower limits of gas concentration and the temperature and humidity change range, predict environmental changes in the future time period, and obtain parameter trend prediction results;

[0008] S2: Based on the parameter trend prediction results, compare multiple parameters with environmental safety values, identify gas concentration and temperature and humidity parameters that exceed the threshold, mark the fluctuation characteristics of the parameters, determine the target values ​​of gas concentration and temperature and humidity, and obtain parameter control operation results;

[0009] S3: Based on the parameter control operation results, the gas flow and temperature and humidity controllers are adjusted, and the optimized storage environment parameters are detected in real time to determine whether the environmental parameters meet the storage target and obtain the storage environment stability results;

[0010] S4: Based on the storage environment stability result, analyze the data change trend within the storage cycle, classify the data, calculate the fluctuation amplitude of the gas concentration and temperature and humidity parameters within multiple cycles, identify the high-frequency fluctuation area within the cycle for early warning marking, extract the characteristic change value of the parameter within multiple storage cycles, analyze the data in the early warning mark area, evaluate the shelf life of the stored items, and obtain the key change results of multiple cycles;

[0011] S5: Based on the multi-cycle key change results, analyze the time required to restore to the safe range after parameter adjustment, extract the influencing factors of response deviation, analyze the interactive change rules between gas concentration and temperature and humidity parameters, optimize the operating logic of the environmental controller, and adjust the execution priority and switching mechanism of gas and temperature and humidity parameters to obtain dynamic environmental optimization results.

[0012] On the other hand, the parameter trend prediction results are specifically the gas concentration range and the temperature and humidity change range. The parameter control operation results include parameter stability, gas concentration target value, and temperature and humidity target value. The storage environment stability results specifically refer to the storage environment optimization status and environmental parameter compliance status. The multi-cycle key change results include the gas concentration fluctuation amplitude, high-frequency fluctuation area, and parameter characteristic change value. The environmental dynamic optimization results are specifically the controller operation logic, parameter execution priority, and parameter switching mechanism.

[0013] On the other hand, real-time gas composition, temperature and humidity data are collected, the collected data are sorted by time, the changing trends of multiple parameters at each time point are identified, and the parameter stability of the trend fluctuation range is compared. The upper and lower limits of gas concentration and the temperature and humidity change range are analyzed, and the environmental changes in the future time period are predicted. The specific steps to obtain the parameter trend prediction results are as follows:

[0014] S101: Based on the collected gas composition, temperature and humidity data, the data are arranged in chronological order, the data differences between adjacent time points are compared, the variation range of each parameter is extracted, and the correlation with the values ​​of consecutive time points is analyzed to obtain the time series data of environmental parameters;

[0015] S102: Based on the environmental parameter time series data, calculate and compare the concentration range of the gas components and the upper and lower limits of temperature and humidity, extract the deviation value, classify and analyze the degree of deviation, mark the characteristics of the fluctuation amplitude, and obtain the parameter fluctuation characteristic analysis result;

[0016] S103: Based on the parameter fluctuation characteristic analysis results, combined with the fluctuation amplitude of gas concentration and temperature and humidity parameters, calculate the change rate of each parameter in adjacent time periods, extract the change interval of future data trends, and judge the stability of future change trends to obtain parameter trend prediction results.

[0017] On the other hand, based on the parameter trend prediction results, multiple parameters are compared with environmental safety values, gas concentration and temperature and humidity parameters exceeding the threshold are identified, and the fluctuation characteristics of the parameters are marked, and the target values ​​of gas concentration and temperature and humidity are determined. The steps of obtaining the parameter control operation results are specifically as follows:

[0018] S201: Based on the parameter trend prediction result, by comparing the gas concentration and temperature and humidity data in the warehouse, identifying abnormal parameters exceeding the safety threshold, and classifying the abnormal parameters to obtain an identification result of the parameters exceeding the threshold;

[0019] S202: Based on the identification result of the parameter exceeding the threshold, the change amplitude and change rate of the parameter are calculated in combination with the data timestamp, and the change amplitude and change rate are classified, and the fluctuation data of the parameter is marked to obtain the parameter fluctuation characteristic marking result;

[0020] S203: Based on the parameter fluctuation characteristic marking result, the target adjustment values ​​of the gas concentration and the temperature and humidity parameters are calculated according to the fluctuation data, the gas concentration and the temperature and humidity are adjusted by the adjustment values, and the adjusted parameters are continuously monitored to obtain the parameter control operation results.

[0021] On the other hand, based on the parameter control operation results, the gas flow and temperature and humidity controllers are adjusted, and the optimized storage environment parameters are detected in real time to determine whether the environmental parameters meet the storage target. The steps of obtaining the storage environment stability results are specifically as follows:

[0022] S301: Based on the parameter control operation result, the opening and closing degree of the gas flow control valve is adjusted to verify whether the gas concentration is within the target range, and the temperature and humidity controller is adjusted synchronously to match the storage environment standard to obtain the adjustment execution result;

[0023] S302: Based on the adjustment execution result, the gas concentration and temperature and humidity change data in the storage environment are detected in real time, the parameter deviation value is calculated between the detection data and the target value, the fluctuation trend of the deviation value is analyzed, and the parameters out of range are marked to obtain the storage environment detection and comparison results;

[0024] S303: Based on the storage environment detection and comparison results, determine whether the gas concentration and temperature and humidity meet the storage target, correct the deviation state by calibrating the control value of the non-standard parameter, and statistically analyze the change trend of the corrected parameter to obtain the storage environment stability result.

[0025] On the other hand, the determination of whether the gas concentration and temperature and humidity have reached the storage target is performed by correcting the deviation state by calibrating the control value of the parameter that has not reached the target, according to the formula:

[0026] ;

[0027] Calculate the calibrated control value parameters ;

[0028] In the formula, Represents the actual measured value of the current gas concentration or temperature and humidity. Represents the target value of the set gas concentration or temperature and humidity. Represents the detection time interval, Represents the environmental stability coefficient.

[0029] On the other hand, based on the storage environment stability results, the data change trend within the storage cycle is analyzed, the data is classified, the fluctuation amplitude of the gas concentration and temperature and humidity parameters within multiple cycles is calculated, and the high-frequency fluctuation area within the cycle is identified for early warning marking, the characteristic change value of the parameter within multiple storage cycles is extracted, the data of the early warning mark area is analyzed, and the shelf life of the stored items is evaluated. The specific steps of obtaining the key change results of multiple cycles are as follows:

[0030] S401: Based on the storage environment stability result, analyze the gas concentration and temperature and humidity of each data point in chronological order, extract the change amplitude within multiple storage cycles, and obtain the data change analysis result;

[0031] S402: Based on the data change analysis result, classify the fluctuation amplitude of each data point, identify data points with high frequency of change and data segments with large amplitude, and issue an early warning for the data segments to obtain a fluctuation area early warning result;

[0032] S403: Based on the fluctuation area warning results, extract the key fluctuation points of temperature and humidity, identify the key factors affecting the stability of the storage environment, analyze the root causes of the key factors, locate the abnormal points of parameter fluctuations, and then evaluate the shelf life of the stored items based on the abnormal points to obtain multi-cycle key change results.

[0033] On the other hand, the key fluctuation points of temperature and humidity are extracted to identify the key factors affecting the stability of the storage environment, according to the formula:

[0034] ;

[0035] and

[0036] ;

[0037] Calculating the rate of change and fluctuation range ;

[0038] In the formula, Represents the time period The gas concentration or temperature and humidity values ​​monitored at the time, Representative The gas concentration or temperature and humidity values ​​monitored at the time, is the total number of monitoring data, is the time interval between two monitorings, Represents the maximum value of all monitoring data in the high-frequency fluctuation area. Represents the minimum value of all monitoring data in the high-frequency fluctuation area.

[0039] On the other hand, based on the multi-cycle key change results, the time required to restore to the safe range after parameter adjustment is analyzed, the influencing factors of response deviation are extracted, the interactive change rules between gas concentration and temperature and humidity parameters are analyzed, the operation logic of the environmental controller is optimized, and the execution priority and switching mechanism of gas and temperature and humidity parameters are adjusted. The specific steps for obtaining the dynamic optimization results of the environment are as follows:

[0040] S501: Based on the multi-period key change results, a time series analysis is performed on the change trend of the data in each period, the recovery rate and the deviation value are extracted, the influencing factors of the slow recovery speed of the data range are identified, and the response deviation analysis results are obtained;

[0041] S502: Based on the response deviation analysis result, the interaction between gas concentration and temperature and humidity parameters is analyzed, the optimal correlation parameter combination is extracted, the variation range of the two types of parameters and the key fluctuation area of ​​the interaction are identified, and the law of parameter interaction is obtained;

[0042] S503: Based on the interaction law of the parameters, the execution priority of the environment controller logic is adjusted, and the operation instructions are set by analyzing the gas concentration and the temperature and humidity change values, and the instruction logic is redefined to obtain the dynamic optimization result of the environment.

[0043] On the other hand, a storage material atmosphere conditioning maintenance early warning system based on environmental monitoring is provided, and the system is applied to a storage material atmosphere conditioning maintenance early warning method based on environmental monitoring, comprising:

[0044] The environmental data acquisition module collects real-time gas composition, temperature and humidity data, sorts the collected data by time, identifies the changing trends of multiple parameters at each time point, compares the parameter stability within the trend fluctuation range, analyzes the upper and lower limits of gas concentration and the temperature and humidity change range, and obtains parameter trend prediction results;

[0045] The parameter trend analysis module compares multiple parameters with environmental safety values ​​based on the parameter trend prediction results, identifies gas concentrations and temperature and humidity parameters that exceed the thresholds, and marks the fluctuation characteristics of the parameters to obtain parameter control operation results;

[0046] The environment control module adjusts the gas flow and temperature and humidity controller based on the parameter control operation results, optimizes the current storage environment, determines whether the environmental parameters meet the storage target, and obtains the storage environment stability result;

[0047] Based on the storage environment stability results, the environmental stability analysis module analyzes the data change trend within the storage cycle, classifies the data, identifies the high-frequency fluctuation area within the cycle for early warning marking, extracts the characteristic change values ​​of the parameters within multiple storage cycles, analyzes the data in the early warning marking area, evaluates the shelf life of the stored items, and obtains the key change results of multiple cycles;

[0048] Based on the multi-cycle key change results, the environmental dynamic optimization module analyzes the time required to restore to the safe range after parameter adjustment, extracts the influencing factors of response deviation, analyzes the interactive change rules between gas concentration and temperature and humidity parameters, optimizes the operating logic of the environmental controller, and adjusts the execution priority and switching mechanism of gas and temperature and humidity parameters to obtain the environmental dynamic optimization results.

[0049] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0050] By combining data time sorting with trend analysis, analyzing the relationship between parameters and environmental safety values ​​and identifying over-threshold variables, we ensure accurate adjustment of gas, temperature and humidity, and improve the targeted nature of parameter control. Through continuous monitoring and dynamic data classification, we mark high-frequency fluctuation areas with early warnings, thereby improving the ability to monitor the shelf life of stored items and reducing the loss of items caused by environmental changes. We integrate data analysis and real-time monitoring methods, optimize the operating logic of the environmental controller, and improve the overall system performance and resource utilization efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0052] Figure 1 It is a main step flow chart of the present invention;

[0053] Figure 2 is a flow chart of the steps of S1 of the present invention;

[0054] Figure 3 is a flow chart of the steps of S2 of the present invention;

[0055] Figure 4 is a flow chart of the steps of S3 of the present invention;

[0056] Figure 5 is a flow chart of the steps of S4 of the present invention;

[0057] Figure 6 is a flow chart of the steps of S5 of the present invention;

[0058] Figure 7 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0059] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0060] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0061] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0062] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0063] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0064] The embodiment of the present invention provides a storage material atmosphere conditioning maintenance early warning method based on environmental monitoring, such as Figure 1 As shown, the following steps are included:

[0065] S1: Collect real-time gas composition, temperature and humidity data, sort the collected data by time, identify the changing trends of multiple parameters at each time point, and compare the parameter stability within the trend fluctuation range, analyze the upper and lower limits of gas concentration and the temperature and humidity change range, predict environmental changes in the future time period, and obtain parameter trend prediction results;

[0066] S2: Based on the parameter trend prediction results, compare multiple parameters with environmental safety values, identify gas concentrations and temperature and humidity parameters that exceed the thresholds, mark the fluctuation characteristics of the parameters, determine the target values ​​of gas concentrations and temperature and humidity, and obtain the parameter control operation results;

[0067] S3: Based on the results of the parameter control operation, the gas flow and temperature and humidity controllers are adjusted, and the optimized storage environment parameters are detected in real time to determine whether the environmental parameters meet the storage target and obtain the storage environment stability results;

[0068] S4: Based on the storage environment stability results, analyze the data change trend within the storage cycle, classify the data, calculate the fluctuation amplitude of gas concentration and temperature and humidity parameters within multiple cycles, identify the high-frequency fluctuation area within the cycle for early warning marking, extract the characteristic change value of the parameters within multiple storage cycles, analyze the data in the early warning mark area, evaluate the shelf life of the stored items, and obtain the key change results of multiple cycles;

[0069] S5: Based on the results of multi-cycle key changes, analyze the time required to restore to the safe range after parameter adjustment, extract the influencing factors of response deviation, analyze the interactive change rules between gas concentration and temperature and humidity parameters, optimize the operating logic of the environmental controller, and adjust the execution priority and switching mechanism of gas and temperature and humidity parameters to obtain the dynamic optimization results of the environment.

[0070] The parameter trend prediction results include gas concentration range, temperature and humidity change range, and future environmental change prediction. The parameter control operation results include parameter stability, gas concentration target value, and temperature and humidity target value. The storage environment stability results refer to the storage environment optimization status and environmental parameter compliance status. The multi-cycle key change results include gas concentration fluctuation amplitude, high-frequency fluctuation area, and parameter characteristic change value. The environmental dynamic optimization results include controller operation logic, parameter execution priority, and parameter switching mechanism.

[0071] like Figure 2 As shown in the figure, real-time gas composition, temperature and humidity data are collected, the collected data are sorted by time, the changing trends of multiple parameters at each time point are identified, and the parameter stability of the trend fluctuation range is compared. The upper and lower limits of gas concentration and the temperature and humidity change range are analyzed, and the environmental changes in the future time period are predicted. The specific steps to obtain the parameter trend prediction results are as follows:

[0072] S101: Based on the collected gas composition, temperature and humidity data, the data are arranged in chronological order, the data differences between adjacent time points are compared, the variation range of each parameter is extracted, and the correlation with the values ​​of consecutive time points is analyzed to obtain the time series data of environmental parameters;

[0073] First, the gas composition data are analyzed one by one, and the values ​​of carbon dioxide, carbon monoxide, methane and ammonia are extracted. The temperature and humidity data are uniformly formatted and arranged in chronological order. For each adjacent time point, the difference in gas composition concentration, temperature and humidity is calculated, and the numerical range of the difference is recorded to form a time series of parameter differences. Subsequently, according to the calculated difference sequence, the change amplitude of each parameter is summarized, a unified change interval is set, and the amplitude of parameter change is divided into multiple interval categories. At the same time, by comparing the changing trends of gas composition and temperature and humidity one by one, it is analyzed whether their changes are synchronized in time, and the time point with the largest change amplitude is marked. Finally, environmental parameter time series data containing time series, change amplitude and trend characteristics are generated.

[0074] S102: Based on the environmental parameter time series data, calculate and compare the concentration range of the gas components and the upper and lower limits of temperature and humidity, extract the deviation value, classify and analyze the degree of deviation, mark the characteristics of the fluctuation amplitude, and obtain the parameter fluctuation characteristic analysis results;

[0075] The upper and lower limits of the concentration of the main components in the gas composition are statistically analyzed, and the maximum and minimum values ​​of temperature and humidity are extracted, and their respective numerical ranges are calculated. The numerical range of each parameter is compared with its average value in the time series, and the absolute size of the deviation from the average value is recorded. According to the set deviation classification standard, the deviation values ​​are divided into three categories: slight, moderate and severe. For each type of deviation value, its fluctuation frequency and fluctuation amplitude are analyzed, and the main fluctuation characteristics are summarized. By summarizing the data of the fluctuation range and marking the data points with significant characteristics in each type of fluctuation, the classified statistical results of gas component concentration and temperature and humidity fluctuation amplitude are formed, and the final fluctuation characteristic analysis report is generated.

[0076] S103: Based on the analysis results of parameter fluctuation characteristics, combined with the fluctuation amplitude of gas concentration and temperature and humidity parameters, the change rate of each parameter in adjacent time periods is calculated, the change interval of future data trends is extracted, and the stability of future change trends is determined to obtain parameter trend prediction results.

[0077] The gas concentration data and temperature and humidity data are input into the change rate analysis module. According to the data difference between adjacent time points, the change rate of gas concentration and temperature and humidity in each time period is calculated one by one. The change rate range is divided into fixed intervals, such as normal change rate and abnormal change rate. The time series of the change rate is classified and processed. By analyzing the distribution of the change rate on the time axis, the possible change intervals in the future trend are extracted. Finally, these data are summarized and combined with the fluctuation amplitude to mark the stability of future trend changes and generate parameter trend prediction results.

[0078] like Figure 3 As shown in the figure, based on the parameter trend prediction results, multiple parameters are compared with environmental safety values, gas concentration and temperature and humidity parameters exceeding the threshold are identified, and the fluctuation characteristics of the parameters are marked. The target values ​​of gas concentration and temperature and humidity are determined, and the steps to obtain the parameter control operation results are as follows:

[0079] S201: Based on the parameter trend prediction results, by comparing the gas concentration and temperature and humidity data in the warehouse, identifying abnormal parameters that exceed the safety threshold, and classifying the abnormal parameters to obtain the identification results of the parameters exceeding the threshold;

[0080] First, screen the core components in the gas concentration, such as the upper and lower limits of carbon dioxide, carbon monoxide, methane and ammonia, and extract the regular monitoring range of temperature and humidity. Compare these historical data with the trend prediction results one by one. Through the preset safety threshold range, such as the specific standard value range of carbon dioxide concentration, the normal operating range of temperature, and the limited range of humidity, identify whether each parameter exceeds the safety threshold item by item, and classify the gas concentration or temperature and humidity data that exceeds the threshold. For example, divide them into three categories according to the deviation ratio: slight abnormality, moderate abnormality and severe abnormality, and establish data grouping according to the classification results. At the same time, record the specific exceeding values ​​and their classification at each time point. Finally, sort out all parameters that exceed the safety threshold and the corresponding abnormal classification results.

[0081] S202: Based on the identification result of the parameter exceeding the threshold, the change amplitude and change rate of the parameter are calculated in combination with the data timestamp, and the change amplitude and change rate are classified, and the fluctuation data of the parameter is marked to obtain the parameter fluctuation characteristic marking result;

[0082] Extract all gas concentrations and temperature and humidity values ​​that exceed the safety threshold, arrange them in timestamp order, calculate the numerical difference and change rate between the two time points by comparing the parameter changes at each time point with the previous time point, group the amplitudes according to the absolute value of the changes, for example, into small changes, medium changes and large changes, and divide the rates into low-speed changes, medium-speed changes and high-speed changes according to the speed of change, mark the amplitude and rate of change by matching timestamps, summarize the fluctuation range and characteristics, mark the specific time points and parameter values ​​of abnormal fluctuations, form a parameter fluctuation characteristic record based on time series, and finally generate parameter fluctuation characteristic marking results.

[0083] S203: Based on the parameter fluctuation characteristic marking results, the target adjustment values ​​of the gas concentration and temperature and humidity parameters are calculated according to the fluctuation data, the gas concentration and temperature and humidity are adjusted by the adjustment values, and the adjusted parameters are continuously monitored to obtain the parameter control operation results.

[0084] The gas concentration and temperature and humidity parameters in the marked data are extracted and classified according to the fluctuation amplitude and change rate categories. The target value that needs to be adjusted is determined by analyzing the deviation range and the current parameter status. The method for calculating the target adjustment value is to reduce the difference between the current parameter value and its normal range. At the same time, the adjustment value is refined in combination with the historical fluctuation characteristic data to obtain the target value of the gas concentration and temperature and humidity parameters. The target parameters are adjusted through the control equipment, and the value changes in each time period after adjustment are continuously monitored. At the same time, the change amplitude and rate before and after the adjustment are recorded, the data table is updated, and a record of the adjusted status is formed, and finally the operation result of the parameter control is generated.

[0085] Calculate the target adjustment values ​​of gas concentration and temperature and humidity parameters based on the fluctuation data according to the formula:

[0086] ;

[0087] Calculate target adjustment values ​​for gas concentration, temperature and humidity parameters .

[0088] In the formula, Representative The current gas concentration value at each observation point, Representative The calibration gas concentration value at each observation point, Representative The current temperature and humidity values ​​of the observation points, Representative The target temperature and humidity values ​​of the observation points are: Represents the number of observation points.

[0089] The monitoring data are as follows:

[0090] Current gas concentration ppm;

[0091] Calibration concentration ppm;

[0092] Current temperature and humidity Spend;

[0093] Target temperature and humidity Spend;

[0094] Number of observation points ;

[0095] The calculation formula is as follows:

[0096] Gas concentration adjustment value section:

[0097] ;

[0098] ;

[0099] Temperature and humidity adjustment value part:

[0100] ;

[0101] ;

[0102] Comprehensive adjustment value:

[0103] ;

[0104] The target adjustment value of gas concentration and temperature and humidity is 0.38, which represents the average deviation of the monitoring parameters from the calibration value and the target value. The control system needs to be adjusted based on this value to optimize the environmental parameters, and the adjusted data should be continuously monitored to verify the adjustment effect.

[0105] like Figure 4 As shown, based on the parameter control operation results, the gas flow and temperature and humidity controllers are adjusted, and the optimized storage environment parameters are detected in real time to determine whether the environmental parameters meet the storage target. The specific steps for obtaining the storage environment stability results are as follows:

[0106] S301: Based on the parameter control operation result, the opening and closing degree of the gas flow control valve is adjusted to verify whether the gas concentration is within the target range, and the temperature and humidity controller is adjusted synchronously to match the storage environment standard to obtain the adjustment execution result;

[0107] Extract the current gas concentration and temperature and humidity data, gradually adjust the opening and closing degree of the control valve according to the difference between the real-time concentration data and the target concentration range, set the adjustment step corresponding to different difference ranges, for example, when the concentration difference is small, a smaller adjustment step is used, and when the difference is large, a larger adjustment step is used. At the same time, process the temperature and humidity data, and adjust the output power of the temperature control heating element and the humidity regulator according to the difference between the temperature and humidity and the target value, set different power outputs to match the difference, monitor the adjusted gas concentration and temperature and humidity values ​​in real time, compare the adjusted data with the target range, and finally obtain the execution results after the gas concentration and temperature and humidity are adjusted.

[0108] S302: Based on the adjustment execution result, the gas concentration and temperature and humidity change data in the storage environment are detected in real time, the parameter deviation value is calculated between the detection data and the target value, the fluctuation trend of the deviation value is analyzed, and the parameters out of range are marked to obtain the storage environment detection and comparison results;

[0109] Acquire current monitoring data from gas sensors and temperature and humidity sensors in real time, compare the collected real-time data with the target range values ​​one by one, calculate the deviation value of each parameter, extract the part of gas concentration, temperature and humidity that exceeds the target range, record these out-of-range parameters, and further mark the time point when they exceed the range. Combined with the deviation value in a continuous time period, count the change amplitude and frequency of each parameter one by one, analyze its fluctuation trend, divide the fluctuation trend into different categories, classify and record the parameters according to the degree of deviation beyond the range, and finally form the detection and comparison results of the storage environment.

[0110] S303: Based on the storage environment detection and comparison results, determine whether the gas concentration and temperature and humidity meet the storage target, correct the deviation state by calibrating the control value of the non-standard parameter, and statistically analyze the change trend of the corrected parameter to obtain the storage environment stability result.

[0111] By calling the calibration function of the gas flow control valve, the gas flow that needs to be adjusted is recalculated according to the concentration difference that exceeds the range. The gas concentration value is brought closer to the target value by gradually adjusting the opening and closing ratio of the gas control valve. At the same time, the temperature and humidity are adjusted accordingly. The output power of the heating element is readjusted in combination with the deviated temperature difference. The deviation difference of humidity is used to reset the working intensity of the humidity controller. The control value of the parameter that does not meet the standard is gradually corrected. By real-time monitoring of the adjusted data, the stability of the adjustment trend is recorded, and finally the result of the stability of the storage environment is obtained.

[0112] Determine whether the gas concentration and temperature and humidity have reached the storage target, and correct the deviation by calibrating the control value of the parameter that does not reach the target, according to the formula:

[0113] ;

[0114] Calculate the calibrated control value parameters ;

[0115] In the formula, Represents the actual measured value of the current gas concentration or temperature and humidity. Represents the target value of the set gas concentration or temperature and humidity. Represents the detection time interval (hours), which refers to the time between two consecutive detections in the environmental data acquisition system, in hours. Represents the environmental stability coefficient, which is used to measure the sensitivity of the current environment to the control parameters.

[0116] The difference between the current measured value and the target value is corrected, and the correction amplitude is adjusted in combination with the time interval and environmental stability to obtain a more accurate parameter control value.

[0117] The specific parameter values ​​are as follows:

[0118] Current measured value of gas concentration The value was 35ppm as detected by online sensor;

[0119] Target gas concentration Set by the system, the value is 30ppm;

[0120] Detection time interval is the sampling time of the environmental data acquisition system, which is 2 hours;

[0121] Environmental stability coefficient Determined by experimental data, it is used to reflect the sensitivity of the current environment to the control parameters, and its value is 1.5;

[0122] Substitute the above parameters into the formula: 1. Calculate the absolute value of the difference between the current measured value and the target value:

[0123] ;

[0124] 2. Calculate the correction range:

[0125] ;

[0126] 3. Calculate the corrected control value parameters:

[0127] ;

[0128] After correction, the control value is adjusted to 33.43ppm, reflecting the dynamic correction of the deviation of the current gas concentration. This value can be used to further optimize the adjustment strategy of the environmental controller and promote the storage environment to develop stably towards the target parameters.

[0129] like Figure 5 As shown in the figure, based on the storage environment stability results, the data change trend within the storage cycle is analyzed, the data is classified, the fluctuation amplitude of the gas concentration and temperature and humidity parameters within multiple cycles is calculated, and the high-frequency fluctuation area within the cycle is identified for early warning marking. The characteristic change values ​​of the parameters within multiple storage cycles are extracted, and the data in the early warning mark area is analyzed to evaluate the shelf life of the stored items. The specific steps to obtain the key change results of multiple cycles are as follows:

[0130] S401: Based on the storage environment stability result, analyze the gas concentration and temperature and humidity of each data point in chronological order, extract the change range within multiple storage cycles, and obtain the data change analysis result;

[0131] All data points of gas concentration, temperature and humidity are extracted in chronological order, the recorded value of each data point is read, and the data within multiple storage cycles are analyzed. The variation range of the maximum and minimum values ​​of gas concentration in each cycle is calculated, and the variation range of the maximum and minimum values ​​of temperature and humidity is recorded. The variation data of each storage cycle is sorted, and the time periods with larger variation ranges are marked by cycle-by-cycle comparison. The detailed data of these time periods are further extracted and classified into slight, medium and large fluctuation intervals. According to these marked information, the variation characteristics of gas concentration, temperature and humidity in different storage cycles are counted, and finally the data variation analysis results are obtained.

[0132] S402: Based on the data change analysis results, the fluctuation amplitude of each data point is classified, the data points with high frequency of change and the data segments with large amplitude are identified, and early warning is issued for the data segments to obtain the fluctuation area early warning results;

[0133] Extract the marked data points with large fluctuations in each storage cycle, organize the changing trends of these data points, classify the data points according to the frequency of fluctuations, and mark the data points with higher fluctuation frequencies as key monitoring points. At the same time, extract the data segments with large fluctuations in each storage cycle, classify these segments separately, and further count the distribution of data segments with large fluctuations in different time periods. Set warnings for segments whose fluctuations exceed the set range, and record the corresponding time and parameter value range to finally complete the generation of fluctuation area warning results.

[0134] S403: Based on the fluctuation area warning results, extract the key fluctuation points of temperature and humidity, identify the key factors affecting the stability of the storage environment, analyze the root causes of the key factors, locate the abnormal points of parameter fluctuations, and then evaluate the shelf life of the stored items based on the abnormal points to obtain multi-cycle key change results.

[0135] Data points with significant changes in temperature and humidity are extracted, and the time periods corresponding to these data points are listed as the key analysis range. In combination with the changes in gas concentration, the key factors affecting the stability of the storage environment are checked one by one, and possible abnormal causes are classified, such as equipment abnormalities, external environment changes, or system adjustment problems. The fluctuating data points are divided into abnormal areas, and the starting and ending points of the abnormal changes are determined. The impact of these abnormal changes on the shelf life of stored items is analyzed, and the status of stored items is evaluated according to the set impact level. The change trend results of key data points in each storage cycle are generated, and finally the multi-cycle key change results are obtained.

[0136] Extract the key fluctuation points of temperature and humidity, identify the key factors affecting the stability of the storage environment, according to the formula:

[0137] ;

[0138] and

[0139] ;

[0140] Calculating the rate of change and fluctuation range ;

[0141] In the formula, Represents the time period The gas concentration or temperature and humidity values ​​monitored at the time, Representative The gas concentration or temperature and humidity values ​​monitored at the time, is the total number of monitoring data, used as the denominator when calculating the rate of change. is the time interval between two monitorings, Represents the maximum value of all monitoring data in the high-frequency fluctuation area. Represents the minimum value of all monitoring data in the high-frequency fluctuation area.

[0142] In calculating the rate of change of each parameter and fluctuation range ,These parameters directly reflect the changing characteristics of gas concentration, temperature and humidity in the high-frequency fluctuation area.

[0143] Parameter acquisition method and data assignment:

[0144] For monitoring data The gas concentration collected is acquired through real-time detection by sensors, with a value range of 30ppm to 50ppm. The specific value is determined based on the actual monitoring value.

[0145] is the total number of monitoring times, which is taken as 10 in this calculation.

[0146] As the monitoring time interval, 2 hours was taken.

[0147] and They are obtained by taking the maximum and minimum values ​​in the monitoring data respectively.

[0148] Data example:

[0149] Suppose the monitoring data is: 30ppm, 32ppm, 35ppm, 40ppm, 38ppm, 42ppm, 39ppm, 45ppm, 48ppm, 50ppm.

[0150] Calculation process:

[0151] Calculate the sum of the changes:

[0152] ;

[0153] Calculate the rate of change:

[0154] ;

[0155] Calculate the fluctuation range:

[0156] ;

[0157] Result interpretation:

[0158] Rate of change 1.5ppm / h, fluctuation range The result shows that the gas concentration changes more dramatically in the high-frequency fluctuation area, and the fluctuation range is larger. By further correlating these results with the shelf life of the items during the storage cycle, the potential impact of the current environmental parameters on the storage quality can be determined, and targeted adjustments can be made.

[0159] like Figure 6 As shown in the figure, based on the results of multi-cycle key changes, the time required to restore to the safe range after parameter adjustment is analyzed, the influencing factors of response deviation are extracted, the interactive change rules between gas concentration and temperature and humidity parameters are analyzed, the operation logic of the environmental controller is optimized, and the execution priority and switching mechanism of gas and temperature and humidity parameters are adjusted. The specific steps to obtain the dynamic optimization results of the environment are as follows:

[0160] S501: Based on the key change results of multiple periods, a time series analysis is performed on the change trend of the data in each period, the recovery rate and deviation value are extracted, the influencing factors of the slow recovery speed of the data range are identified, and the response deviation analysis results are obtained;

[0161] Extract the gas concentration and temperature and humidity change trend data within each storage cycle, analyze the recovery speed between data points in chronological order, calculate the change speed of each data point compared with the previous data point, and record the speed trend within each cycle. At the same time, extract the deviation value of each data point, and analyze the fluctuation trend of the deviation value within multiple cycles by comparing the difference between the target value and the actual value. Filter out the time period with slow recovery speed, and analyze the specific influencing factors that may cause the slow recovery speed of the data range in combination with the fluctuation range of the deviation value, such as too long response time of the control equipment or too many environmental interference factors, and finally obtain the response deviation analysis results.

[0162] Perform time series analysis on the changing trend of data in each period according to the formula:

[0163] ;

[0164] Calculating recovery rate ;

[0165] In the formula, Representative The first The observed value of data points, Representative The first The observed value of data points, Represents the total number of data points collected in each cycle.

[0166] The observed values ​​in the two cycles of system monitoring are as follows:

[0167] No. The periodic data points are ,

[0168] No. The periodic data points are .

[0169] but .

[0170] The calculation process of recovery rate is:

[0171] ;

[0172] ;

[0173] ;

[0174] No. The average recovery rate of the cycle is 2.25, which means that the average change in data from the previous cycle to the current cycle is 2.25. This rate can be used to further identify the factors that affect the slow data recovery speed.

[0175] S502: Based on the response deviation analysis results, the interaction between gas concentration and temperature and humidity parameters is analyzed, the optimal correlation parameter combination is extracted, the variation range of the two types of parameters and the key fluctuation area of ​​the interaction are identified, and the law of parameter interaction is obtained;

[0176] Extract the change data of gas concentration and temperature and humidity parameters, perform correlation analysis on the time interval and amplitude change between each data point, calculate the interaction between the two types of parameters one by one, and screen out the optimal combination of parameters by comparing the degree of correlation. For example, mark the highly correlated gas concentration and temperature and humidity parameters as the preferred combination, perform interactive analysis on the data range of each group of preferred combinations, extract key fluctuation areas, mark areas with large fluctuation amplitudes or high frequencies, and identify key fluctuation points and their corresponding time ranges by analyzing the interactive changes of the two types of parameters in the key fluctuation areas, and finally obtain the law of parameter interaction.

[0177] S503: Based on the law of parameter interaction, the execution priority of the environment controller logic is adjusted, and the operation instructions are set by analyzing the gas concentration and the temperature and humidity change values, and the instruction logic is redefined to obtain the dynamic optimization result of the environment.

[0178] Analyze the execution order of the current logic of the environmental controller, redefine the priority of the logic instructions according to the size of the gas concentration and the temperature and humidity changes, and adjust the parameters with a larger change range to priority processing. For example, when the change range of the gas concentration exceeds the set range, set it as the priority control logic. When the temperature and humidity change range is large, give priority to regulating the temperature and humidity. Update the logic instructions of the environmental controller, adjust the execution process of the controller by assigning a new priority instruction set, perform multiple tests in combination with the updated instruction logic, record the change trend and regulation effect of the adjusted parameters, and finally generate the environmental control optimization result.

[0179] like Figure 7 As shown, a storage material atmosphere conditioning maintenance early warning system based on environmental monitoring includes:

[0180] The environmental data acquisition module collects real-time gas composition, temperature and humidity data, sorts the collected data by time, identifies the changing trends of multiple parameters at each time point, compares the parameter stability within the trend fluctuation range, analyzes the upper and lower limits of gas concentration and the temperature and humidity change range, and obtains parameter trend prediction results;

[0181] The parameter trend analysis module compares multiple parameters with environmental safety values ​​based on parameter trend prediction results, identifies gas concentrations and temperature and humidity parameters that exceed the threshold, and marks the fluctuation characteristics of the parameters to obtain the results of parameter control operations;

[0182] The environmental control module adjusts the gas flow and temperature and humidity controllers based on the parameter control operation results, optimizes the current storage environment, determines whether the environmental parameters meet the storage target, and obtains the storage environment stability results;

[0183] The environmental stability analysis module analyzes the data change trend within the storage cycle based on the storage environment stability results, classifies the data, identifies the high-frequency fluctuation areas within the cycle and marks them for early warning, extracts the characteristic change values ​​of the parameters within multiple storage cycles, analyzes the data in the early warning mark area, evaluates the shelf life of the stored items, and obtains the key change results of multiple cycles;

[0184] Based on the results of multi-cycle key changes, the environmental dynamic optimization module analyzes the time required to restore to the safe range after parameter adjustment, extracts the influencing factors of response deviation, analyzes the interactive change rules between gas concentration and temperature and humidity parameters, optimizes the operating logic of the environmental controller, and adjusts the execution priority and switching mechanism of gas and temperature and humidity parameters to obtain the environmental dynamic optimization results.

[0185] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0186] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0187] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0188] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0189] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0190] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0191] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0192] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0193] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0194] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A storage material atmosphere conditioning maintenance early warning method based on environmental monitoring, characterized in that: The method comprises: S1: Collect real-time gas composition, temperature and humidity data, sort the collected data by time, identify the changing trends of multiple parameters at each time point, analyze the upper and lower limits of gas concentration and the temperature and humidity change range, predict environmental changes in future time periods, and obtain parameter trend prediction results; S2: Based on the parameter trend prediction results, compare multiple parameters with environmental safety values, identify gas concentration and temperature and humidity parameters that exceed the threshold, mark the fluctuation characteristics of the parameters, determine the target values ​​of gas concentration and temperature and humidity, and obtain parameter control operation results; S3: Based on the parameter control operation results, the gas flow and temperature and humidity controllers are adjusted, and the optimized storage environment parameters are detected in real time to determine whether the environmental parameters meet the storage target and obtain the storage environment stability results; S4: Based on the storage environment stability result, analyze the data change trend within the storage cycle, calculate the fluctuation amplitude of the gas concentration and temperature and humidity parameters within multiple cycles, identify the high-frequency fluctuation area within the cycle for early warning marking, extract the characteristic change value of the parameter within multiple storage cycles, and obtain the key change result of multiple cycles; S5: Based on the multi-cycle key change results, analyze the time required to restore to the safe range after parameter adjustment, extract the influencing factors of response deviation, analyze the interactive change rules between gas concentration and temperature and humidity parameters, and adjust the execution priority and switching mechanism of gas and temperature and humidity parameters to obtain the dynamic optimization result of the environment; Among them, the parameter trend prediction results are specifically the gas concentration range and the temperature and humidity change range; the parameter control operation results include parameter stability, gas concentration target value, and temperature and humidity target value; the storage environment stability results specifically refer to the storage environment optimization status and environmental parameter compliance status; the multi-cycle key change results include the gas concentration fluctuation amplitude, high-frequency fluctuation area, and parameter characteristic change value; the environmental dynamic optimization results are specifically the controller operation logic, parameter execution priority, and parameter switching mechanism.

2. The method for early warning of storage material atmosphere conditioning maintenance based on environmental monitoring according to claim 1 is characterized in that: Collect real-time gas composition, temperature and humidity data, sort the collected data by time, identify the changing trends of multiple parameters at each time point, analyze the upper and lower limits of gas concentration and the temperature and humidity change range, predict environmental changes in future time periods, and obtain parameter trend prediction results in the following steps: S101: Based on the collected gas composition, temperature and humidity data, the data are arranged in chronological order, the data differences between adjacent time points are compared, the variation range of each parameter is extracted, and the correlation with the values ​​of consecutive time points is analyzed to obtain the time series data of environmental parameters; S102: Based on the environmental parameter time series data, calculate and compare the concentration range of the gas components and the upper and lower limits of temperature and humidity, extract the deviation value, classify and analyze the degree of deviation, mark the characteristics of the fluctuation amplitude, and obtain the parameter fluctuation characteristic analysis result; S103: Based on the parameter fluctuation characteristic analysis results, combined with the fluctuation amplitude of gas concentration and temperature and humidity parameters, calculate the change rate of each parameter in adjacent time periods, extract the change interval of future data trends, and judge the stability of future change trends to obtain parameter trend prediction results.

3. The method for early warning of storage material atmosphere conditioning maintenance based on environmental monitoring according to claim 1 is characterized in that: Based on the parameter trend prediction results, multiple parameters are compared with environmental safety values, gas concentration and temperature and humidity parameters exceeding the threshold are identified, and the fluctuation characteristics of the parameters are marked to determine the target values ​​of gas concentration and temperature and humidity. The specific steps of obtaining the parameter control operation results are as follows: S201: Based on the parameter trend prediction result, by comparing the gas concentration and temperature and humidity data in the warehouse, identifying abnormal parameters exceeding the safety threshold, and classifying the abnormal parameters to obtain an identification result of the parameters exceeding the threshold; S202: Based on the identification result of the parameter exceeding the threshold, the change amplitude and change rate of the parameter are calculated in combination with the data timestamp, and the change amplitude and change rate are classified, and the fluctuation data of the parameter is marked to obtain the parameter fluctuation characteristic marking result; S203: Based on the parameter fluctuation characteristic marking result, the target adjustment values ​​of the gas concentration and the temperature and humidity parameters are calculated according to the fluctuation data, the gas concentration and the temperature and humidity are adjusted by the adjustment values, and the adjusted parameters are continuously monitored to obtain the parameter control operation results.

4. The method for early warning of storage material atmosphere conditioning maintenance based on environmental monitoring according to claim 1 is characterized in that: Based on the parameter control operation results, the gas flow and temperature and humidity controllers are adjusted, and the optimized storage environment parameters are detected in real time to determine whether the environmental parameters meet the storage target. The steps of obtaining the storage environment stability results are as follows: S301: Based on the parameter control operation result, the opening and closing degree of the gas flow control valve is adjusted to verify whether the gas concentration is within the target range, and the temperature and humidity controller is adjusted synchronously to match the storage environment standard to obtain the adjustment execution result; S302: Based on the adjustment execution result, the gas concentration and temperature and humidity change data in the storage environment are detected in real time, the parameter deviation value is calculated between the detection data and the target value, the fluctuation trend of the deviation value is analyzed, and the parameters out of range are marked to obtain the storage environment detection and comparison results; S303: Based on the storage environment detection and comparison results, determine whether the gas concentration and temperature and humidity meet the storage target, correct the deviation state by calibrating the control value of the non-standard parameter, and statistically analyze the change trend of the corrected parameter to obtain the storage environment stability result.

5. The method for early warning of storage material atmosphere conditioning maintenance based on environmental monitoring according to claim 4 is characterized in that: The determination of whether the gas concentration and temperature and humidity have reached the storage target is performed by correcting the deviation state by calibrating the control value of the parameter that has not reached the target, according to the formula: ； Calculate the calibrated control value parameters ; In the formula, Represents the actual measured value of the current gas concentration or temperature and humidity. Represents the target value of the set gas concentration or temperature and humidity. Represents the detection time interval, Represents the environmental stability coefficient.

6. The method for early warning of storage material atmosphere conditioning maintenance based on environmental monitoring according to claim 1 is characterized in that: Based on the storage environment stability result, the data change trend within the storage cycle is analyzed, the fluctuation amplitude of the gas concentration and temperature and humidity parameters within multiple cycles is calculated, and the high-frequency fluctuation area within the cycle is identified for early warning marking, and the characteristic change value of the parameter within multiple storage cycles is extracted to obtain the key change results of multiple cycles. The specific steps are: S401: Based on the storage environment stability result, analyze the gas concentration and temperature and humidity of each data point in chronological order, extract the change amplitude within multiple storage cycles, and obtain the data change analysis result; S402: Based on the data change analysis result, classify the fluctuation amplitude of each data point, identify data points with high frequency of change and data segments with large amplitude, and issue an early warning for the data segments to obtain a fluctuation area early warning result; S403: Based on the fluctuation area warning results, extract the key fluctuation points of temperature and humidity, identify the key factors affecting the stability of the storage environment, analyze the root causes of the key factors, locate the abnormal points of parameter fluctuations, and then evaluate the shelf life of the stored items based on the abnormal points to obtain multi-cycle key change results.

7. The method for early warning of storage material atmosphere conditioning maintenance based on environmental monitoring according to claim 6 is characterized in that: The key fluctuation points of temperature and humidity are extracted to identify the key factors affecting the stability of the storage environment according to the formula: ； and ； Calculating the rate of change and fluctuation range ; In the formula, Represents the time period The gas concentration or temperature and humidity values ​​monitored at the time, Representative The gas concentration or temperature and humidity values ​​monitored at the time, is the total number of monitoring data, is the time interval between two monitorings, Represents the maximum value of all monitoring data in the high-frequency fluctuation area. Represents the minimum value of all monitoring data in the high-frequency fluctuation area.

8. The method for early warning of storage material atmosphere conditioning maintenance based on environmental monitoring according to claim 1 is characterized in that: Based on the multi-cycle key change results, the time required to restore to the safe range after parameter adjustment is analyzed, the influencing factors of response deviation are extracted, the interactive change rules between gas concentration and temperature and humidity parameters are analyzed, and the execution priority and switching mechanism of gas and temperature and humidity parameters are adjusted. The specific steps to obtain the dynamic optimization results of the environment are as follows: S501: Based on the multi-period key change results, a time series analysis is performed on the change trend of the data in each period, the recovery rate and the deviation value are extracted, the influencing factors of the slow recovery speed of the data range are identified, and the response deviation analysis results are obtained; S502: Based on the response deviation analysis result, the interaction between gas concentration and temperature and humidity parameters is analyzed, the optimal correlation parameter combination is extracted, the variation range of the two types of parameters and the key fluctuation area of ​​the interaction are identified, and the law of parameter interaction is obtained; S503: Based on the interaction law of the parameters, the execution priority of the environment controller logic is adjusted, and the operation instructions are set by analyzing the gas concentration and the temperature and humidity change values, and the instruction logic is redefined to obtain the dynamic optimization result of the environment.

9. A storage material atmosphere conditioning maintenance early warning system based on environmental monitoring, the storage material atmosphere conditioning maintenance early warning system based on environmental monitoring is used to implement the storage material atmosphere conditioning maintenance early warning method based on environmental monitoring as claimed in any one of claims 1 to 8, characterized in that: The system comprises: The environmental data acquisition module collects real-time gas composition, temperature and humidity data, sorts the collected data by time, identifies the changing trends of multiple parameters at each time point, compares the parameter stability within the trend fluctuation range, analyzes the upper and lower limits of gas concentration and the temperature and humidity change range, and obtains parameter trend prediction results; The parameter trend analysis module compares multiple parameters with environmental safety values ​​based on the parameter trend prediction results, identifies gas concentrations and temperature and humidity parameters that exceed the thresholds, and marks the fluctuation characteristics of the parameters to obtain parameter control operation results; The environment control module adjusts the gas flow and temperature and humidity controller based on the parameter control operation results, optimizes the current storage environment, determines whether the environmental parameters meet the storage target, and obtains the storage environment stability result; Based on the storage environment stability results, the environmental stability analysis module analyzes the data change trend within the storage cycle, classifies the data, identifies the high-frequency fluctuation area within the cycle for early warning marking, extracts the characteristic change values ​​of the parameters within multiple storage cycles, analyzes the data in the early warning marking area, evaluates the shelf life of the stored items, and obtains the key change results of multiple cycles; Based on the multi-cycle key change results, the environmental dynamic optimization module analyzes the time required to restore to the safe range after parameter adjustment, extracts the influencing factors of response deviation, analyzes the interactive change rules between gas concentration and temperature and humidity parameters, optimizes the operating logic of the environmental controller, and adjusts the execution priority and switching mechanism of gas and temperature and humidity parameters to obtain the environmental dynamic optimization results.

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