Multi-effect total heat recovery constant temperature and humidity system

Abstract

The application relates to the technical field of constant temperature and humidity control, and discloses a multi-effect full-heat recovery constant temperature and humidity system. A heat recovery distribution control module of the system analyzes the matching degree of heat recovery efficiency and energy stability, generates a heat recovery distribution control parameter set; a temperature and humidity balance optimization module adjusts the temperature and humidity distribution balance of a cavity, generates a temperature and humidity regulation and optimization parameter set; a fresh air dynamic adjustment module optimizes the fresh air input rate and path distribution, generates a fresh air dynamic regulation result; an abnormal working condition intervention module deals with temperature and humidity fluctuations, generates an abnormal intervention adjustment data set; and an environmental parameter optimization module adjusts target regulation path parameters, generates an environmental temperature and humidity optimization data table. Through the cooperative work of the modules, the system realizes efficient and accurate regulation and control of the environmental temperature and humidity, improves the stability and adaptability of the system under complex working conditions, and meets the demand of modern industrial production and other scenes for high-precision environmental control.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of constant temperature and humidity control, in particular to a multi-effect full-heat recovery constant temperature and humidity system. BACKGROUND

[0002] In modern industrial production, warehouse logistics and precision instrument operation scenarios, the stability of environmental temperature and humidity is increasingly demanding. Traditional constant temperature and humidity systems often use a single heat exchange mode, adjusting the indoor environment through simple fresh air introduction and exhaust treatment. This method is difficult to cope with temperature and humidity fluctuations in complex environments. For example, in high-temperature and high-humidity areas, traditional systems need to frequently start and stop heating and cooling equipment to maintain the target temperature and humidity, which not only causes a large amount of energy waste, but also easily leads to temperature and humidity regulation lag and local area temperature and humidity imbalance.

[0003] With the popularization of energy-saving concepts, some systems have begun to introduce heat recovery devices, but the efficiency of existing heat recovery equipment is low, and energy loss is serious during heat exchange. Most heat recovery systems can only achieve single recovery of sensible heat or latent heat, and cannot take into account the effectiveness of full-heat recovery, resulting in a significant reduction in energy utilization rate. At the same time, these systems use fixed parameter mode for temperature and humidity control, lacking dynamic adjustment capability. When the external environment changes suddenly, such as sudden temperature changes during seasonal transition, large temperature differences between morning and evening, or fluctuations in indoor heat sources and moisture sources, such as changes in equipment operation heat and moisture brought by personnel flow, the system is difficult to respond quickly, and is prone to temperature and humidity overshoot or delayed adjustment.

[0004] The traditional system's fresh air treatment method is relatively extensive, with fixed fresh air input rate and path, which cannot be dynamically adjusted according to real-time temperature and humidity changes, resulting in insufficient heat exchange between fresh air and indoor air, further affecting the stability of temperature and humidity. In actual operation, when the system faces abnormal working conditions, such as equipment failure, new air quality decline, etc., the traditional system lacks effective intervention mechanisms, often leading to uncontrolled environmental temperature and humidity, adversely affecting production and equipment operation.

[0005] The constant temperature and humidity systems on the market have obvious shortcomings in heat recovery efficiency, temperature and humidity balance, fresh air adaptability, and abnormal working condition handling. Energy loss is large during heat recovery, resulting in high system operation energy consumption; the power output of the temperature and humidity regulation device does not match the environmental demand, easily causing large local area temperature and humidity deviation; the coordination between fresh air introduction and heat exchange is insufficient, and the fresh air path and rate cannot be optimized in real time according to environmental changes; in the face of sudden environmental fluctuations, the system's response speed is slow, the adjustment precision is low, and it is difficult to maintain environmental stability. These problems not only affect the system's operation efficiency and stability, but also increase the maintenance cost and energy consumption of the equipment, and cannot meet the demand of modern industry for high-precision environmental control. SUMMARY

[0006] The present application aims to provide a multi-effect total heat recovery constant temperature and humidity system to solve the problems raised in the background.

[0007] To achieve the above-mentioned purpose, the present application provides a multi-effect total heat recovery constant temperature and humidity system, which comprises:

[0008] The heat recovery distribution control module calls the heat exchange efficiency parameters, temperature and humidity gradient difference and air flow circulation path data of the device according to the total heat recovery device operating state information, analyzes the matching degree of heat recovery efficiency and energy stability, distributes the device heat recovery control value and circulation balance parameters, and generates a set of heat recovery distribution control parameters;

[0009] The temperature and humidity balance optimization module extracts the temperature and humidity values and gradient change amounts in the device cavity based on the set of heat recovery distribution control parameters, analyzes the influence of temperature and humidity adjustment device power output on stability, adjusts the temperature and humidity distribution balance of the cavity, generates a set of temperature and humidity control optimization parameters, and;

[0010] The fresh air dynamic adjustment module analyzes the contact and penetration of fresh air on the heat exchange surface based on the set of temperature and humidity control optimization parameters, adjusts the fresh air input rate and flow rate path distribution ratio, redistributes the distribution trend and dynamic parameter value of fresh air humidity, and generates a fresh air dynamic control result;

[0011] The abnormal condition intervention module extracts the real-time temperature and humidity fluctuation rate and parameter offset amount in the total heat recovery process based on the fresh air dynamic control result, analyzes the influence of fluctuation range on stable operation of the system, dynamically adjusts the fresh air distribution path and temperature and humidity ratio in the target range, and generates an abnormal intervention adjustment data set;

[0012] The environmental parameter optimization module analyzes the distribution ratio and control time of the target environment temperature and humidity based on the abnormal intervention adjustment data set, adjusts the parameters of the target control path, and generates an environmental temperature and humidity optimization data table.

[0013] Preferably, the step of obtaining the matching degree of heat recovery efficiency and energy stability is specifically:

[0014] According to the total heat recovery device operating state information, the heat exchange efficiency parameters, gradient difference data and circulation path flow rate data of the device are extracted, a time window is set, time point matching data is selected, data correlation is compared and data is filtered to obtain the heat exchange efficiency parameters and gradient difference data.

[0015] Based on the heat exchange efficiency parameter and gradient difference data, the path is matched and verified, the difference between the heat exchange efficiency and the gradient difference is calculated, the heat recovery distribution and the gradient difference distribution are corrected combined with the flow rate change, the path parameters are adjusted through the influence of the flow rate on the data, and the matching condition of the heat exchange efficiency and the gradient difference is obtained.

[0016] Based on the heat exchange efficiency and gradient difference matching condition, energy stability analysis is performed, energy stability analysis standards are set, the efficiency distribution under differentiated flow rate conditions is evaluated combined with the dynamic changes of equipment operation, the stability index is compared and the flow rate conditions are optimized, and the matching degree of heat recovery efficiency and energy stability is obtained.

[0017] Preferably, the obtaining step of the heat recovery distribution control parameter set is specifically:

[0018] Based on the heat recovery efficiency and energy stability matching degree, the heat recovery transmission and stability change of the equipment under differentiated operation conditions are analyzed, and the heat recovery distribution of the equipment is weighted calculated to obtain the preliminary heat recovery regulation and control requirement of the equipment;

[0019] Based on the preliminary heat recovery regulation and control requirement of the equipment, the heat recovery balance between the equipment is analyzed, the heat transfer efficiency and load distribution relationship between the equipment are identified, and the heat recovery regulation and control parameters of the equipment are corrected;

[0020] Combined with the heat recovery regulation and control data set between the equipment and the energy stability matching result, the heat recovery between the equipment is distributed, the required balance and stability requirements are optimized and matched, and the heat recovery distribution control parameter set is obtained.

[0021] Preferably, the obtaining step of the temperature and humidity value and gradient change amount in the equipment cavity is specifically:

[0022] Based on the heat recovery distribution control parameter set, the temperature and humidity data in the equipment cavity are extracted, the temperature and humidity points in each time period are screened, the temperature and humidity fluctuation is analyzed combined with the temperature and humidity change trend of the differentiated positions in the cavity, and the temperature and humidity data in the equipment cavity are obtained;

[0023] Based on the temperature and humidity data in the equipment cavity, each temperature and humidity point and the corresponding adjustment parameter are calculated, the adjustment parameter change amount of each measurement point is identified by analyzing the relationship between the temperature and humidity and the adjustment parameter, the adjustment parameter change of the differentiated positions is compared combined with the equipment structure parameters, and the temperature and humidity distribution and gradient distribution data are obtained.

[0024] Based on the temperature and humidity distribution and gradient distribution data, the overall temperature and humidity distribution in the equipment cavity is analyzed, the adjustment gradient is optimized combined with the temperature and humidity data, the influence of the adjustment parameter change on the equipment performance is analyzed, the stable adjustment configuration under the differentiated operation conditions is determined, and the temperature and humidity value and gradient change amount in the equipment cavity are obtained.

[0025] Preferably, the obtaining step of the temperature and humidity regulation optimization parameter set is specifically:

[0026] Based on the temperature and humidity values and gradient changes in the device cavity, determine the time sequence of temperature and humidity changes, compare the current temperature and humidity values with the original temperature and humidity data, analyze the temperature and humidity gradient at each moment, and generate a preliminary temperature and humidity change parameter set according to the corresponding threshold defined by the device state partition;

[0027] Analyze the preliminary temperature and humidity change parameter set, analyze the influence of temperature and humidity in the cavity on the stability of the device power output, identify the correlation between temperature and humidity and power output, and obtain the section power stability influence coefficient;

[0028] By analyzing the section power stability influence coefficient, combining the cavity temperature and humidity change parameters, adjusting the temperature and humidity distribution balance, optimizing the temperature and humidity regulation data, and generating a temperature and humidity regulation optimization parameter set.

[0029] Preferably, the obtaining step of the fresh air dynamic regulation result is specifically:

[0030] Based on the temperature and humidity regulation optimization parameter set, extract the fresh air contact data of the heat exchange surface, monitor the contact rate of fresh air on the surface of different materials, combine the external environmental factors of time and temperature to infer the penetration characteristics of fresh air, define the contact and penetration rate coefficient, and generate a contact and penetration dynamic parameter set;

[0031] Analyze the influence of the contact and penetration dynamic parameter set on the flow rate and distribution of fresh air, optimize the ratio between the flow rate path and the fresh air input rate according to the demand of fresh air humidity distribution of the heat exchange surface, and obtain the optimized fresh air humidity regulation result;

[0032] Analyze the fresh air humidity regulation result, adjust the proportional relationship between the fresh air input rate and the flow rate path, distribute the distribution trend of fresh air humidity, combine the contact and penetration parameters and the adjustment coefficient, and obtain the fresh air dynamic regulation result.

[0033] Preferably, the obtaining step of the abnormal intervention adjustment data set is specifically:

[0034] Based on the fresh air dynamic regulation result, monitor the temperature and humidity fluctuation rate and parameter deviation in the real-time monitoring of the device during the whole heat recovery process, identify the fluctuation range, eliminate the abnormal values of the device failure, analyze the average fluctuation rate of the data, and obtain the temperature and humidity and parameter fluctuation data;

[0035] Analyze the influence of the temperature and humidity and parameter fluctuation range on the stable operation of the system, analyze the relationship between the parameters and the temperature and humidity by using the known system operation stability, and calculate the operation stability under the differential fluctuation range;

[0036] According to the operation stability, the fresh air distribution path and the temperature and humidity ratio in the target range are dynamically adjusted, the abnormal intervention adjustment dataset is generated by adjusting the relationship between the operation stability influence data and the temperature and humidity and the parameter fluctuation range, and the fresh air flow rate and the temperature and humidity control range are distributed.

[0037] Preferably, the obtaining step of the environment temperature and humidity optimization data table is specifically:

[0038] Based on the abnormal intervention adjustment dataset, target environment temperature and humidity distribution and regulation time are analyzed, temperature and humidity concentration data at different regulation time points are collected, temperature and humidity time distribution is arranged, concentration change trend is analyzed and data is classified, and environment temperature and humidity distribution data is obtained.

[0039] Based on the environment temperature and humidity distribution data, target regulation path parameter adjustment is performed, environment temperature and humidity optimal regulation time and concentration distribution are analyzed, concentration changes under different regulation conditions are compared, regulation temperature, time and fresh air humidity operation conditions are adjusted, and target regulation path parameters are obtained.

[0040] Based on the target regulation path parameters, the regulation conditions are adjusted according to the current operation parameters, the variable relationship of regulation time, temperature and fresh air humidity is controlled, real-time regulation is performed according to the adjusted parameters, and the environment temperature and humidity optimization data table is obtained.

[0041] Preferably, the obtaining step of the equipment operation state information is specifically:

[0042] Based on the environment temperature and humidity optimization data table, real-time monitoring data in the equipment operation process is extracted, key parameter points in each monitoring period are screened, differential characteristics of equipment operation stages are combined, parameter volatility is analyzed, and equipment operation state basic data is obtained.

[0043] Based on the equipment operation state basic data, each parameter point and the corresponding operation mode are associated and analyzed, the equipment state change trend is identified by comparing the historical operation data with the current data, the state characteristics of the differential operation stages are compared by combining the equipment design parameters, and the equipment operation state classification data is obtained.

[0044] Based on the equipment operation state classification data, real-time monitoring data and historical data are integrated, an equipment state evaluation model is established, the influence of state change on system performance is analyzed, and equipment operation state information under different working conditions is determined.

[0045] Preferably, the obtaining step of the circulation path flow rate data is specifically:

[0046] Based on the device running state information, real-time flow rate data of the air flow circulation path in the device is extracted, a flow rate monitoring interval is set, a flow rate sampling point in the interval is selected, and the circulation path basic flow rate data is obtained by comparing the correlation of the sampling point data and removing outliers;

[0047] Based on the circulation path basic flow rate data, the path structure and flow rate distribution are matched and verified, the flow rate difference of different path segments is calculated, the flow rate data is corrected combined with the pressure distribution in the device, the path parameters are adjusted through the influence of pressure on flow rate, and the circulation path flow rate distribution is obtained.

[0048] Based on the circulation path flow rate distribution, flow rate stability analysis is performed, flow rate stability evaluation criteria are set, and the flow rate distribution under differentiated path conditions is evaluated combined with the dynamic changes of device operation, the stability index is compared and the path structure is optimized, and the circulation path flow rate data is obtained.

[0049] Compared with the prior art, the beneficial effects of the present application are:

[0050] The multi-effect total heat recovery constant temperature and humidity system provided by the present application effectively solves the problems of traditional constant temperature and humidity systems in terms of heat recovery efficiency, temperature and humidity control stability, fresh air treatment adaptability and abnormal working condition response capability through the synergistic effect of multiple modules.

[0051] In terms of heat recovery, the traditional system often relies on fixed parameters for heat exchange, and it is difficult to adjust the heat recovery distribution ratio according to the real-time running state of the device, resulting in energy waste or insufficient recovery. The heat recovery distribution control module of the present system can combine the running state information of the total heat recovery device, dynamically analyze the matching degree of heat recovery efficiency and energy stability, accurately distribute the heat recovery control value and circulation balance parameters, significantly improve the efficiency of heat recovery and the rationality of energy utilization, so that the system can maximize the use of recovered heat energy during operation and reduce additional energy consumption.

[0052] In terms of temperature and humidity balance control, the traditional system is prone to uneven temperature and humidity distribution in the device cavity, affecting the stability of the overall environment. The temperature and humidity balance optimization module of the present system is based on the heat recovery distribution control parameter set, deeply analyzes the influence of temperature and humidity regulation device power output on stability, adjusts the temperature and humidity distribution balance of the cavity, and effectively improves the local temperature and humidity deviation. This precise control method can ensure that the temperature and humidity of each area in the device cavity is maintained within the target range, avoiding the adverse effects of unstable local environment on production or experiments.

[0053] For fresh air treatment, the traditional system adjusts the fresh air in a static mode, which cannot dynamically adjust the fresh air input parameters according to the temperature and humidity control requirements. The fresh air dynamic adjustment module of the system can analyze the contact and penetration of fresh air on the heat exchange surface based on the temperature and humidity control optimization parameter set, flexibly adjust the fresh air input rate, flow rate path distribution ratio, and fresh air humidity distribution trend, so that the fresh air treatment is more in line with the real-time requirements of the system. This dynamic adjustment mechanism not only improves the mixing efficiency of fresh air and circulating air, but also optimizes the distribution of fresh air in a timely manner according to environmental changes, further enhancing the accuracy of temperature and humidity control.

[0054] In response to abnormal conditions, the traditional system often reacts slowly and is difficult to quickly adjust parameters to maintain stable operation. The abnormal condition intervention module of the system can extract the temperature and humidity fluctuation rate and parameter offset in the whole heat recovery process in real time, analyze its impact on the stable operation of the system, and dynamically adjust the fresh air distribution path and temperature and humidity ratio, thereby quickly generating abnormal intervention adjustment data set. This mechanism enables the system to respond quickly when facing sudden situations, reduces the impact of parameter fluctuations on the overall environment, and ensures the continuous and stable operation of the system in complex environments.

[0055] In addition, the environmental parameter optimization module further optimizes the distribution ratio and control time of the target environment temperature and humidity through analysis of the abnormal intervention adjustment data set, adjusts the parameters of the target control path, and generates an environmental temperature and humidity optimization data table. This process realizes closed-loop optimization of the entire environmental control process, enabling the system to continuously improve the control strategy based on long-term operation data, continuously improve the accuracy and energy efficiency of temperature and humidity control, and meet the high standards of constant temperature and humidity environment in different scenarios. BRIEF DESCRIPTION OF DRAWINGS

[0056] Figure 1 The working principle diagram of the multi-effect whole heat recovery constant temperature and humidity system described in the present application;

[0057] Figure 2 Flow chart for matching degree of heat recovery efficiency and energy stability;

[0058] Figure 3 Flow chart for heat recovery distribution control parameter set;

[0059] Figure 4 Flow chart for fresh air dynamic control results. DETAILED DESCRIPTION

[0060] With reference to the accompanying drawings, the technical solutions in the embodiments of the present application will be clearly and completely described below, obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work belong to the scope of protection of the present application.

[0061] Please refer to Figures 1-4 The present application provides a multi-effect total heat recovery constant temperature and humidity system, and the specific implementation steps are as follows:

[0062] When the system is running, the heat recovery distribution control module plays a core role, which continuously receives the total heat recovery device running state information. Based on this information, the module calls the heat exchange efficiency parameters, temperature and humidity gradient difference and air flow circulation path data of the device itself. Through in-depth analysis of these data, the matching degree between heat recovery efficiency and energy stability is mainly considered, and then the heat recovery control value and circulation balance parameters of the device are accurately distributed, and finally the heat recovery distribution control parameter set is generated, which lays a foundation for subsequent temperature and humidity control.

[0063] After the temperature and humidity balance optimization module obtains the heat recovery distribution control parameter set, it immediately starts to extract the temperature and humidity values and gradient change amount in the device cavity. By analyzing the influence of temperature and humidity adjusting device power output on system stability, the balance of temperature and humidity distribution in the cavity is continuously adjusted, and after a series of accurate calculation and optimization, the temperature and humidity control optimization parameter set is generated.

[0064] The fresh air dynamic adjustment module is based on the temperature and humidity control optimization parameter set, and carefully analyzes the contact and penetration process of fresh air on the heat exchange surface. On this basis, the fresh air input rate and flow rate path distribution ratio are reasonably adjusted, and the distribution trend and dynamic parameter value of fresh air humidity are redistributed, and finally the fresh air dynamic control result is obtained.

[0065] After the abnormal working condition intervention module receives the fresh air dynamic control result, it extracts the temperature and humidity fluctuation rate and parameter offset amount in the total heat recovery process in real time. By analyzing the influence of these fluctuation ranges on the stable operation of the system, the fresh air distribution path and temperature and humidity ratio in the target range are dynamically adjusted, so as to generate the abnormal intervention adjustment data set.

[0066] The environmental parameter optimization module is based on the abnormal intervention adjustment data set, and comprehensively analyzes the distribution proportion and control time of the target environment temperature and humidity. According to the analysis result, the parameters of the target control path are optimized and adjusted, and finally the environment temperature and humidity optimization data table is generated, realizing the accurate control of the environment temperature and humidity.

[0067] Embodiment 1:

[0068] In the process of matching the heat recovery efficiency and energy stability, the required key data is extracted from the whole heat recovery equipment operation state information. These data include the heat exchange efficiency parameters of the equipment, the gradient difference data, and the circulation path flow rate data. The heat exchange efficiency parameters reflect the performance of the equipment in the heat exchange process, the gradient difference data reflect the difference of temperature and humidity in different regions of the equipment, and the circulation path flow rate data describe the flow speed characteristics of the air flow in the circulation path of the equipment. When extracting these data, different stages of equipment operation need to be covered to ensure the comprehensiveness and continuity of the data, so as to reflect the running characteristics of the equipment under various working conditions.

[0069] A suitable time window is set. The selection of the time window needs to be determined according to the running period of the equipment and the data change frequency, neither too long to cause data redundancy, nor too short to capture effective data association. In the set time window, multiple representative time points are selected, and the heat exchange efficiency parameters, gradient difference data and circulation path flow rate data corresponding to each time point are matched. By comparing the correlation between these data, such as the change trend of heat exchange efficiency parameters with gradient difference data, the influence of flow rate data on heat exchange efficiency parameters, etc., the data is screened. In the screening process, the data with weak correlation or obviously deviating from the normal change rule is eliminated, and the data accurately reflecting the running state of the equipment is retained, so as to obtain the effective heat exchange efficiency parameters and gradient difference data.

[0070] Based on the obtained heat exchange efficiency parameters and gradient difference data, the air flow circulation path is matched and verified. This step aims to verify whether the current circulation path can make the heat exchange efficiency parameters and gradient difference data reach a reasonable corresponding relationship. The difference between the heat exchange efficiency and the gradient difference is calculated, and whether this difference is within the normal range is analyzed. At the same time, combined with the change of circulation path flow rate data, the heat recovery distribution and gradient difference distribution are corrected. Because the change of flow rate will affect the heat transfer and distribution, and then affect the heat exchange efficiency and gradient difference, it is necessary to adjust the path parameters such as the width, the bending degree of the path according to the actual change of flow rate, so that the heat exchange efficiency and the gradient difference can be better matched, and finally the matching situation of heat exchange efficiency and gradient difference is obtained.

[0071] After obtaining the matching of heat exchange efficiency and gradient difference, energy stability analysis is carried out. First, the energy stability analysis standards need to be set, which can include the fluctuation range of energy output, the energy consumption change amplitude during equipment operation, etc. Combined with the dynamic changes during equipment operation, such as load increase and decrease, external environment fluctuation, etc., the efficiency distribution under different flow rate conditions is evaluated. Different flow rate conditions will cause the distribution of heat exchange efficiency in different regions of the equipment to present differences. By comparing the stability indicators under these different flow rate conditions, such as the stability of energy output, the accuracy of temperature control, etc., the flow rate conditions are further optimized. During the optimization process, the flow rate may need to be fine-tuned to find the flow rate setting that can achieve the best matching of heat recovery efficiency and energy stability, and finally determine the matching degree of heat recovery efficiency and energy stability.

[0072] During the whole process, the accuracy and timeliness of data collection need to be ensured to avoid deviations in the analysis results caused by data errors. At the same time, the monitoring of equipment operation state should be continuous to capture various changes in time and provide reliable basis for the extraction of heat exchange efficiency parameters, gradient difference data and circulating path flow rate data. When performing data matching and screening, scientific and reasonable methods should be used to ensure that the retained data can truly reflect the running characteristics of the equipment. In the path matching verification and parameter adjustment process, the physical structure and operation principle of the equipment should be fully considered to make the adjusted path parameters meet the actual operation requirements of the equipment. The setting of energy stability analysis standards should be combined with the design requirements of the system and the actual application scenarios to ensure the practicality and effectiveness of the analysis results.

[0073] Example 2:

[0074] When generating the heat recovery distribution control parameter set, the matching degree of heat recovery efficiency and energy stability should be used as the initial basis to comprehensively analyze the heat recovery transmission state and stability changes of the equipment under differentiated operation conditions. These differentiated operation conditions include different load levels, different external environment temperature and humidity, and different operation periods, etc. During the analysis process, various indicators in the heat recovery transmission process need to be continuously tracked, including heat transfer rate, heat loss proportion, and heat distribution between different regions, etc., and the specific manifestations of stability changes, such as parameter fluctuation frequency and amplitude, etc. are recorded. On this basis, the heat recovery distribution of the equipment is weighted calculated, and the heat exchange capacity, operation loss and role proportion in the overall system of each component of the equipment need to be considered comprehensively during the calculation. Through multi-dimensional weighted processing, the preliminary heat recovery regulation and control requirements of the equipment are obtained.

[0075] Based on the preliminary heat recovery regulation requirements of the equipment, further analysis of the heat recovery balance between multiple equipment is needed. When multiple total heat recovery equipment work together in the system, the heat transfer path, transfer efficiency and the heat recovery load of each equipment need to be monitored in detail. By comparing the heat recovery transmission efficiency of different equipment, the corresponding relationship between heat transfer efficiency and load distribution of equipment is determined, such as the change of heat transfer efficiency of a certain equipment under high load, and the influence of this change on the load distribution of other related equipment. According to the actual monitoring data, the heat recovery regulation parameters of the equipment are corrected. During the correction process, the rated parameters, historical operation records and current actual operation state of the equipment need to be combined, so that the regulation parameters can accurately reflect the cooperative operation requirements between equipment, and then the heat recovery regulation data set between equipment is obtained.

[0076] The heat recovery regulation data set between equipment is combined with the energy stability matching result to systematically distribute the heat recovery between equipment. During the distribution process, the heat recovery of each equipment needs to be dynamically adjusted from the perspective of the overall system to achieve the heat recovery balance of the whole system. At the same time, the specific requirements of the system for balance and stability are fully considered, for example, in some specific environments, the system may need to prioritize the balance of heat recovery to avoid local overheating or overcooling, while in other cases, it needs to prioritize the energy stability to maintain the continuous and efficient operation of the system. By continuously optimizing the distribution scheme, the heat recovery distribution between equipment can accurately match the balance and stability requirements of the system. After multiple rounds of parameter adjustment and verification, the heat recovery distribution control parameter set is finally generated.

[0077] During the whole process, real-time data collection and analysis is the key link. The accuracy and timeliness of data such as heat recovery efficiency, energy stability matching degree and equipment operation parameters used for analysis need to be ensured to avoid deviation of regulation parameters caused by data delay or error. For the scene of multiple equipment working together, a data interaction mechanism between equipment needs to be established to ensure that the operation state information of each equipment can be shared in time, so as to more accurately analyze the heat recovery balance between equipment. When performing weighted calculation and parameter correction, reasonable algorithms and models need to be used in combination with the actual operation characteristics of the system, so that the calculation results and corrected parameters can truly reflect the operation requirements of the system. In addition, the influence of factors such as aging and wear of the system in the long-term operation process on heat recovery transmission and stability needs to be considered, and a certain adjustment space needs to be reserved in the parameter setting and distribution scheme to adapt to the gradual change of equipment performance.

[0078] Example 3:

[0079] When acquiring the temperature and humidity values and gradient variation amounts in the equipment cavity, the temperature and humidity sensing devices in the equipment cavity are started based on the heat recovery distribution control parameter set, and the temperature and humidity data at different positions in the cavity are collected in real time. These sensing devices are distributed in various areas of the cavity, including the top, bottom, corners, and the vicinity of the air inlet and outlet, to ensure that the collected data can cover the entire space of the cavity. According to the preset time interval, the temperature and humidity points in each time period are selected, for example, data is selected once every 10 minutes to form a continuous temperature and humidity data sequence. By analyzing the temperature and humidity variation trends at different positions in the cavity, the volatility of temperature and humidity is analyzed, such as the temperature rise or fall amplitude in an hour, the humidity fluctuation frequency, etc., and the temperature and humidity data in the equipment cavity are obtained through these analyses.

[0080] Based on the temperature and humidity data in the equipment cavity, each temperature and humidity point and the corresponding adjustment parameter are calculated. The adjustment parameters include the power, running time, and wind speed of the temperature and humidity adjustment device, which directly affect the temperature and humidity changes in the cavity. By analyzing the relationship between temperature and humidity and adjustment parameters, such as the temperature change rate when the power increases, the humidity distribution when the wind speed changes, etc., the adjustment parameter variation amount of each measurement point is identified. By combining the structural parameters of the equipment, such as the volume, shape, and distribution of internal obstacles of the cavity, the adjustment parameter variation at different positions is compared, and the temperature and humidity distribution and gradient distribution data are obtained.

[0081] According to the temperature and humidity distribution and gradient distribution data, the overall temperature and humidity distribution in the equipment cavity is analyzed to determine whether there are local temperature and humidity abnormal areas. The adjustment gradient, which refers to the difference in temperature and humidity between adjacent areas, is optimized based on the temperature and humidity data to keep the difference within a reasonable range. The influence of adjustment parameter changes on equipment performance is analyzed, such as the influence of excessive adjustment device power on equipment energy consumption, the influence of excessive wind speed on the stability of air flow in the cavity, etc., to determine the stable adjustment configuration under different operating conditions, and finally obtain the temperature and humidity values and gradient variation amounts in the equipment cavity.

[0082] When generating the temperature and humidity control optimization parameter set, the time sequence of temperature and humidity changes is determined based on the temperature and humidity values and gradient variation amounts in the equipment cavity. The time sequence takes time as the horizontal axis and temperature and humidity values as the vertical axis, clearly showing the change law of temperature and humidity over time. The current temperature and humidity values are compared with the original temperature and humidity data, which refers to the temperature and humidity values at the system startup or initial state. The temperature and humidity gradient at each time is analyzed, which is the difference between the current temperature and humidity value and the previous temperature and humidity value. According to the definition of the corresponding threshold value for different state partitions of the equipment, including the startup stage, stable running stage, and load change stage, different threshold values are set for different stages to generate the preliminary temperature and humidity change parameter set.

[0083] Further analysis of the preliminary temperature and humidity variation parameter set is conducted to explore the influence of temperature and humidity in the cavity on the stability of the device power output. The stability of the device power output is manifested as the fluctuation of the power output. Through analysis, it can be determined that within what range of temperature and humidity will cause the power output to fluctuate greatly. The correlation between temperature and humidity and power output is accurately identified, such as the change trend of power output when the temperature exceeds a certain value, the synchronization of humidity change and power output change, etc. By analyzing the section power stability influence coefficient, which refers to the influence degree of a certain temperature and humidity section on the power stability, the temperature and humidity distribution uniformity is adjusted in combination with the cavity temperature and humidity variation parameters. During the adjustment process, the temperature and humidity control optimization parameter set is generated by changing the operating parameters of the adjustment device, such as power distribution of different regional adjustment devices, operating time interval, etc., and optimizing the temperature and humidity control data.

[0084] In analyzing the relationship between temperature and humidity and adjustment parameters, the following formula can be used to calculate the temperature and humidity adjustment response coefficient:

[0085]

[0086] wherein R represents the temperature and humidity adjustment response coefficient, represents the change amount of temperature and humidity in a certain area, S represents the area of the area, P represents the power of the adjustment device acting on the area, and t represents the operating time of the adjustment device. Through this coefficient, the influence degree of the adjustment parameter on the temperature and humidity change can be quantified, providing a reference for subsequent parameter adjustment.

[0087] During the entire process, the accuracy and stability of the sensing device need to be ensured, and it needs to be calibrated regularly to avoid distortion of the collected data due to equipment errors. The frequency of data collection should be reasonably set according to factors such as the size of the cavity, the rate of temperature and humidity change, etc., to ensure that subtle changes in temperature and humidity can be captured in a timely manner. When analyzing the relationship between temperature and humidity and adjustment parameters, the comprehensive influence of multiple factors needs to be considered to avoid one-sided results caused by single factor analysis. The optimization of adjustment gradient should be combined with the needs of actual application scenarios, for example, in some environments with high requirements for temperature and humidity accuracy, the adjustment gradient needs to be controlled within a smaller range.

[0088] Example 4:

[0089] The new air dynamic regulation result needs to be obtained based on the temperature and humidity regulation optimization parameter set. First, the new air contact data of the heat exchange surface is extracted, which includes the area, contact time and distribution of the new air contact with the heat exchange surface. The contact rate of the new air on the surface of different materials is monitored in real time. Different materials have different adsorption and conduction characteristics for the new air. For example, the contact rate of the new air on the surface of the metal material is different from that on the surface of the plastic material. At the same time, the external environmental factors such as time and temperature are considered comprehensively. The time factor reflects the difference in the flow state of the external air at different times, and the temperature factor affects the density and flowability of the new air. The penetration characteristics of the new air, i.e. the ability and speed of the new air penetrating through the heat exchange surface into the equipment interior, are inferred. The contact and penetration rate coefficients are defined according to these data. The contact rate coefficient reflects the speed of the new air contacting with the surface, and the penetration rate coefficient reflects the strength of the new air penetration ability, and then the contact and penetration dynamic parameter set is generated.

[0090] The influence of the contact and penetration dynamic parameter set on the flow rate and distribution of the new air is analyzed. The flow rate refers to the flow speed of the new air in the equipment interior, and the distribution refers to the coverage range and concentration of the new air in different areas. According to the actual demand of the new air humidity distribution of the heat exchange surface, i.e. the humidity level required by each part of the heat exchange surface, the ratio between the flow rate path and the new air input rate is optimized. The flow rate path is the route of the new air flowing in the equipment, and the input rate is the amount of new air entering the equipment per unit time. By optimization, the ratio of the two can meet the requirements of the heat exchange surface for humidity, ensuring uniform humidity distribution in each area of the surface.

[0091] The new air humidity regulation result is analyzed in depth, i.e. the humidity condition of the heat exchange surface after preliminary adjustment. The ratio relationship between the new air input rate and the flow rate path is further adjusted. The distribution trend of the new air humidity is redistributed, for example, increasing the new air input in a certain area to increase the humidity of that area, or changing the flow rate path to reduce the humidity of another area. Combined with the contact and penetration parameters and the adjustment coefficient, the adjustment coefficient is used to correct the influence of the contact and penetration rate on the humidity distribution. After multiple data comparisons and parameter adjustments, the new air dynamic regulation result is obtained.

[0092] The generation of the abnormal intervention adjustment data set starts from the new air dynamic regulation result. The equipment monitors the temperature and humidity fluctuation rate and parameter offset during the whole heat recovery process in real time. The temperature and humidity fluctuation rate refers to the change amplitude of the temperature and humidity value per unit time, and the parameter offset refers to the difference between the actual operating parameter and the set parameter. By setting reasonable identification criteria, such as marking when the fluctuation rate exceeds a certain percentage or the offset exceeds a certain range, the fluctuation range is accurately identified, and the abnormal values caused by equipment failure are removed. These abnormal values usually show a large deviation from the normal data trend. The average fluctuation rate of the data, i.e. the average value of the fluctuation rate in a period of time, is analyzed to obtain accurate temperature and humidity and parameter fluctuation data.

[0093] Analyze the impact of these temperature and humidity and parameter fluctuation ranges on the stable operation of the system, which is manifested as the parameters remaining within the set range and the equipment running smoothly. Use known system operation stability data, i.e., the stable state records of the system under different fluctuation conditions in historical operation, to explore the relationship between parameters and temperature and humidity, such as whether the deviation of a certain parameter will cause corresponding fluctuations in temperature and humidity. Calculate the operation stability under different fluctuation ranges, i.e., determine the impact level of different fluctuation degrees on the stable operation of the system.

[0094] According to the operation stability, dynamically adjust the fresh air distribution path and the temperature and humidity ratio in the target range. The target range refers to the equipment area or parameter interval that needs to be controlled, and adjusting the fresh air distribution path can be achieved by changing the angle of the flow guide device or opening different air ducts, and adjusting the temperature and humidity ratio is to change the control proportion of temperature and humidity. According to the relationship between the operation stability influence data and the temperature and humidity, parameter fluctuation range, reasonably allocate the fresh air flow rate and temperature and humidity control range, for example, when the fluctuation range is large, appropriately reduce the fresh air flow rate to reduce the disturbance to the system, and at the same time, reduce the temperature and humidity control range to improve the control accuracy, and finally generate an abnormal intervention adjustment data set.

[0095] During the whole process, the sensitivity of the monitoring equipment needs to be ensured to capture subtle changes in temperature and humidity and parameters. Data transmission needs to be stable to avoid affecting the analysis results due to data loss or delay. When adjusting the fresh air flow rate and path, the hindering effect of the internal structure of the equipment on the airflow needs to be considered to ensure that the adjusted path can effectively change the distribution of fresh air. For the elimination of outliers, it is necessary to combine the operation log of the equipment to judge whether the data anomaly is indeed caused by equipment failure to avoid mistakenly deleting valid data.

[0096] Example 5:

[0097] The acquisition of the environmental temperature and humidity optimization data table is based on the abnormal intervention adjustment data set. When analyzing the target environmental temperature and humidity distribution and control time, all areas of the environment need to be covered, including corners, near air vents, and core control areas, etc., to ensure that the collected data can reflect the temperature and humidity conditions of the overall environment. Collect temperature and humidity concentration data at different control time points, which need to cover different time periods, such as morning, noon, evening, and night, and include key nodes such as the initial stage of system startup, the middle stage of operation, and the load change. Organize the temperature and humidity time distribution to form a temperature and humidity change curve with time as the axis, analyze the concentration change trend, such as the rising and falling law of temperature and humidity with sunlight, the fluctuation characteristics with equipment operation time, etc., and classify the data by time period or region to obtain environmental temperature and humidity distribution data.

[0098] Based on the environmental temperature and humidity distribution data, the target control path parameters are adjusted. The correlation between the optimal control time of environmental temperature and humidity and the concentration distribution is analyzed, for example, in a certain time period, the temperature and humidity concentration of a specific area is more likely to reach the ideal state, which can be used as the priority control window. By comparing the concentration changes under different control conditions, such as changing the control intensity, adjusting the fresh air input amount, the response of temperature and humidity concentration, adjusting the control temperature, time, and fresh air humidity operation conditions. The adjustment of the control temperature needs to consider the environmental heat capacity, that is, the ability of the environment to absorb or release heat; the adjustment of the control time needs to consider the hysteresis of temperature and humidity changes, that is, the time required for temperature and humidity to reach a stable state after operation is executed; the adjustment of fresh air humidity needs to match the current humidity level of the environment to obtain the target control path parameters.

[0099] Based on the target control path parameters, the control conditions are adjusted according to the current operation parameters. The current operation parameters include real-time monitored temperature and humidity values, device running power, and fresh air input rate, etc. When adjusting, the coordination between parameters needs to be maintained, such as increasing the control temperature, adjusting the fresh air humidity accordingly to avoid the environment being too dry. The variable relationship of control time, temperature, and fresh air humidity is controlled, for example, when the control time is short, the control temperature is appropriately increased to speed up the temperature and humidity reaching the target value; when the fresh air humidity is high, the control time is extended to ensure that the moisture is fully dispersed. Real-time control is carried out according to the adjusted parameters, and temperature and humidity data are continuously collected and the control effect is recorded, and finally the environmental temperature and humidity optimization data table is formed.

[0100] The device running state information is obtained based on the environmental temperature and humidity optimization data table, and the real-time monitoring data in the device running process is extracted. Real-time monitoring data includes device running current, voltage, inlet and outlet temperature difference, vibration frequency, and noise decibel, etc. These data can intuitively reflect the running state of the device. Key parameter points in each monitoring period are selected, and the monitoring period can be set according to the device running characteristics, such as an intermittent running device with one working cycle as a period, and a continuous running device with a fixed time as a period. Combined with different characteristics of device running stages, such as sudden change of parameters at startup, smooth fluctuation of parameters during stable operation, and attenuation of parameters before shutdown, the parameter fluctuation is analyzed to obtain the device running state basic data.

[0101] Based on the equipment running state basic data, each parameter point is associated with the corresponding running mode for analysis. The running mode includes energy-saving mode, high-efficiency mode, emergency mode, etc., and the normal range of equipment parameters is different in different modes. By comparing the historical running data with the current data, the historical data needs to include the parameter records of the equipment under the same environmental conditions and the same running mode, and the trend of the equipment state change is identified, such as the gradual deviation of a parameter value with the running time. Combined with the design parameters of the equipment, such as rated power, maximum handling air volume, and allowable temperature range, the state characteristics of different running stages are compared, such as whether the parameters in the starting stage are within the design allowed fluctuation range, and whether the parameters in the stable running stage are close to the rated value, to obtain the equipment running state classification data.

[0102] Based on the equipment running state classification data, real-time monitoring data and historical data are integrated to establish an equipment state evaluation model. The model needs to cover the parameter normal fluctuation range, abnormal early warning threshold, and state conversion conditions, etc., and by analyzing the influence of state change on system performance, such as the change of heat recovery efficiency and the influence on temperature and humidity control accuracy when the parameters are abnormal, the equipment running state information under different working conditions is determined. The working conditions include high load working condition, low load working condition, and external environment mutation working condition, etc., and the running state information of the equipment under different working conditions needs to clearly define the reasonable interval of the parameters and the adjustment direction.

[0103] The acquisition of the circulation path flow rate data is based on the equipment running state information, and the real-time flow rate data of the air circulation path in the equipment is extracted. The real-time flow rate data is collected by flow rate sensors distributed at different positions of the path, and the sensors need to be installed at positions where flow rate changes easily, such as bends, cross-section changes, and inlets and outlets. The flow rate monitoring interval is set, the upper limit of which is the maximum flow rate allowed by the equipment, and the lower limit is the minimum flow rate that ensures the heat exchange efficiency, and the flow rate outside the interval needs to be paid special attention to. The flow rate sampling points within the interval are selected, and the sampling points need to be evenly distributed to reflect the flow rate distribution of the entire path. By comparing the correlation of the sampling point data, such as whether the flow rates of adjacent sampling points present a reasonable gradual change relationship, and eliminating abnormal values caused by sensor failure or air flow disturbance, the circulation path basic flow rate data is obtained.

[0104] Based on the circulation path basic flow rate data, the path structure and flow rate distribution are matched and verified. The path structure includes pipe diameter size, bending angle, and inner wall smoothness, etc., and the influence of these structural characteristics on the flow rate is analyzed, such as whether the flow rate increases correspondingly at the pipe diameter reduction. The flow rate difference of different path segments, i.e. the flow rate difference value of adjacent path segments, is calculated, and the flow rate data is corrected in combination with the pressure distribution in the equipment, and the pressure distribution is collected by pressure sensors. The flow rate in high pressure area is usually higher than that in low pressure area, and according to the influence amplitude of pressure difference on flow rate, the path parameters are adjusted, such as expanding the path cross-section in high pressure area to reduce the flow rate, to obtain the circulation path flow rate distribution.

[0105] Based on the flow rate distribution of the circulation path, flow rate stability analysis is performed. The flow rate stability evaluation criteria are set, including the maximum fluctuation value of the flow rate per unit time, the flow rate change trend of a plurality of consecutive sampling points, and the like. In combination with the dynamic changes of the equipment operation, such as the airflow demand changes caused by load increase and decrease, the interference of external wind pressure changes on the internal flow rate, and the like, the flow rate distribution under different path conditions, such as the flow rate stability difference between the long straight path and the curved path, is evaluated. The stability indexes, such as the standard deviation and the coefficient of variation, are compared, and the path structure is optimized, such as adding a flow guide plate to the path segment with large flow rate fluctuation, so as to finally obtain the circulation path flow rate data.

[0106] It should be noted that the relational terms herein such as first and second and the like are used solely to distinguish one entity or action from another, without necessarily requiring or implying any such actual relationship or order between such entities or actions. Moreover, the terms "comprises", "comprising", or any other variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but can also include other elements not expressly listed or inherent to such process, method, article, or apparatus.

[0107] Although embodiments of the present application have been shown and described, it is to be understood that various modifications, substitutions, replacements and changes can be made to these embodiments without departing from the principles and spirit of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A multi-effect total heat recovery constant temperature and humidity system, characterized in that, The system comprises: The heat recovery distribution control module calls the heat exchange efficiency parameter, the temperature and humidity gradient difference, and the air flow circulation path data of the device according to the total heat recovery device operating state information, wherein the heat exchange efficiency parameter reflects the performance of the device in the heat exchange process, the gradient difference data reflects the difference of temperature and humidity in different areas of the device, and the circulation path flow rate data describes the flow speed characteristics of the air flow in the circulation path inside the device. The heat recovery efficiency and energy stability matching degree are analyzed, the device heat recovery control value and circulation balance parameter are distributed, and the heat recovery distribution control parameter set is generated; The temperature and humidity balance optimization module extracts the temperature and humidity values and gradient changes in the device cavity based on the heat recovery distribution control parameter set, analyzes the influence of temperature and humidity regulation device power output on stability, adjusts the temperature and humidity distribution balance of the cavity, and generates a temperature and humidity regulation optimization parameter set; The fresh air dynamic adjustment module analyzes the contact and penetration of fresh air on the heat exchange surface based on the temperature and humidity regulation optimization parameter set, adjusts the fresh air input rate and flow rate path distribution ratio, redistributes the distribution trend and dynamic parameter value of fresh air humidity, and generates a fresh air dynamic regulation result; The abnormal condition intervention module extracts the real-time temperature and humidity fluctuation rate and parameter offset in the total heat recovery process based on the fresh air dynamic regulation result, analyzes the influence of the fluctuation range on the stable operation of the system, dynamically adjusts the fresh air distribution path and temperature and humidity ratio in the target range, and generates an abnormal intervention adjustment data set; The environment parameter optimization module analyzes the distribution ratio and regulation time of the target environment temperature and humidity based on the abnormal intervention adjustment data set, adjusts the parameters of the target regulation path, and generates an environment temperature and humidity optimization data table; The heat recovery efficiency and energy stability matching degree obtaining step is specifically: According to the total heat recovery device operating state information, the heat exchange efficiency parameter, the gradient difference data and the circulation path flow rate data of the device are extracted, a time window is set, the time point matching data is selected, the data correlation is compared and the data is filtered, and the heat exchange efficiency parameter and the gradient difference data are obtained; Based on the heat exchange efficiency parameter and the gradient difference data, the path is matched and verified, the difference between the heat exchange efficiency and the gradient difference is calculated, the heat recovery distribution and the gradient difference distribution are corrected combined with the flow rate change, the path parameters are adjusted through the influence of the flow rate on the data, and the heat exchange efficiency and the gradient difference matching condition is obtained; Based on the heat exchange efficiency and the gradient difference matching condition, energy stability analysis is performed, the energy stability analysis standard is set, the efficiency distribution under the differentiated flow rate condition is evaluated combined with the dynamic change of the device operation, the stability index is compared and the flow rate condition is optimized, and the heat recovery efficiency and energy stability matching degree is obtained; The heat recovery distribution control parameter set obtaining step is specifically: Based on the heat recovery efficiency and energy stability matching degree, the heat recovery transmission and stability change of the device under the differentiated operating condition are analyzed, and the heat recovery distribution of the device is weighted calculated, and the preliminary heat recovery regulation requirement of the device is obtained; Based on the preliminary heat recovery regulation requirements of the equipment, the heat recovery balance between the equipment is analyzed, the heat transfer efficiency and load distribution relationship between the equipment are identified, and the heat recovery regulation parameters of the equipment are corrected; Combined with the heat recovery regulation data set and the energy stability matching result between the equipment, the heat recovery between the equipment is distributed, the required balance and stability requirements are optimized and matched, and the heat recovery distribution control parameter set is obtained.

2. The multiple-effect total heat recovery thermostatic and humidistatic system according to claim 1, wherein, The acquisition steps of the temperature and humidity value and gradient change amount in the equipment cavity are specifically: Based on the heat recovery distribution control parameter set, the temperature and humidity data in the equipment cavity are extracted, the temperature and humidity points in each time period are screened, the temperature and humidity change trend in the differential position in the cavity is combined, the temperature and humidity fluctuation is analyzed, and the temperature and humidity data in the equipment cavity are obtained; Based on the temperature and humidity data in the equipment cavity, each temperature and humidity point and the corresponding adjustment parameter are calculated, the relationship between temperature and humidity and adjustment parameter is analyzed, the adjustment parameter change amount of each measurement point is identified, the adjustment parameter change of the differential position is compared combined with the equipment structure parameter, and the temperature and humidity distribution and gradient distribution data are obtained; Based on the temperature and humidity distribution and gradient distribution data, the overall temperature and humidity distribution in the equipment cavity is analyzed, the temperature and humidity data are combined to optimize the adjustment gradient, the influence of adjustment parameter change on equipment performance is analyzed, the stable adjustment configuration under differential operation conditions is determined, and the temperature and humidity value and gradient change amount in the equipment cavity are obtained.

3. The multiple-effect total heat recovery thermostatic and humidistatic system according to claim 2, wherein, The acquisition steps of the temperature and humidity regulation optimization parameter set are specifically: Based on the temperature and humidity value and gradient change amount in the equipment cavity, the time sequence of temperature and humidity change is determined, the current temperature and humidity value is compared with the original temperature and humidity data, the temperature and humidity gradient at each moment is analyzed, and the corresponding threshold value is defined according to the equipment state partition, and a preliminary temperature and humidity change parameter set is generated; The preliminary temperature and humidity change parameter set is analyzed, the influence of temperature and humidity in the cavity on equipment power output stability is analyzed, the correlation between temperature and humidity and power output is identified, and the section power stability influence coefficient is obtained; By analyzing the section power stability influence coefficient, combining the cavity temperature and humidity change parameter, adjusting the temperature and humidity distribution balance, optimizing the temperature and humidity regulation data, and generating the temperature and humidity regulation optimization parameter set.

4. The multiple-effect total heat recovery thermostatic and humidistatic system according to claim 3, wherein, The acquisition steps of the new air dynamic regulation result are specifically: Based on the temperature and humidity regulation optimization parameter set, the new air contact data of the heat exchange surface are extracted, the contact rate of new air on the surface of differential material is monitored, the penetration characteristics of new air are inferred combined with the external environmental factors of time and temperature, the contact and penetration rate coefficient is defined, and the contact and penetration dynamic parameter set is generated; The influence of the contact and penetration dynamic parameter set on the new air flow rate and distribution is analyzed, the proportion between the flow rate path and the new air input rate is optimized according to the new air humidity distribution requirements of the heat exchange surface, and the optimized new air humidity regulation result is obtained; The new air humidity regulation result is analyzed, the proportion relationship between the new air input rate and the flow rate path is adjusted, the distribution trend of new air humidity is distributed, the contact and penetration parameters and the adjustment coefficient are combined, and the new air dynamic regulation result is obtained.

5. The multiple-effect total heat recovery thermostatic and humidistatic system according to claim 4, wherein, The acquisition steps of the abnormal intervention adjustment data set are specifically: Based on the new air dynamic regulation result, the monitoring equipment monitors the temperature and humidity fluctuation rate and parameter offset in the whole heat recovery process in real time, identifies the fluctuation range, eliminates equipment failure abnormal values, analyzes the average fluctuation rate of data, and obtains temperature and humidity and parameter fluctuation data; Analyze the influence of the temperature and humidity and parameter fluctuation range on the stable operation of the system, analyze the relationship between the parameters and the temperature and humidity by using the known system operation stability, and calculate the operation stability under the differentiated fluctuation range; According to the operation stability, dynamically adjust the new air distribution path and the temperature and humidity ratio in the target range, adjust according to the relationship between the operation stability influence data and the temperature and humidity and parameter fluctuation range, distribute the new air flow rate and the temperature and humidity control range, and generate an abnormal intervention adjustment data set.

6. The multiple-effect total heat recovery thermostatic and humidistatic system according to claim 5, wherein, The obtaining step of the environment temperature and humidity optimization data table is specifically: Based on the abnormal intervention adjustment data set, analyze the target environment temperature and humidity distribution and regulation time, collect temperature and humidity concentration data at different regulation time points, arrange the temperature and humidity time distribution, analyze the concentration change trend and classify the data, and obtain environment temperature and humidity distribution data; Based on the environment temperature and humidity distribution data, adjust the target regulation path parameters, analyze the optimal regulation time and concentration distribution of the environment temperature and humidity, compare the concentration changes under different regulation conditions, adjust the regulation temperature, time, and new air humidity operation conditions, and obtain the target regulation path parameters; Based on the target regulation path parameters, adjust the regulation conditions according to the current operation parameters, control the variable relationship of the regulation time, temperature, and new air humidity, and perform real-time regulation according to the adjusted parameters to obtain an environment temperature and humidity optimization data table.

7. The multiple-effect total heat recovery thermostatic and humidistatic system according to claim 6, wherein, The obtaining step of the equipment operation state information is specifically: Based on the environment temperature and humidity optimization data table, extract real-time monitoring data during equipment operation, select key parameter points in each monitoring period, analyze parameter fluctuation by combining the differentiated characteristics of equipment operation stages, and obtain equipment operation state basic data; Based on the equipment operation state basic data, perform correlation analysis on each parameter point and the corresponding operation mode, identify the equipment state change trend by comparing historical operation data with current data, compare the state characteristics of different operation stages by combining equipment design parameters, and obtain equipment operation state classification data; Based on the equipment operation state classification data, integrate real-time monitoring data and historical data, establish an equipment state evaluation model, analyze the influence of state changes on system performance, and determine the equipment operation state information under different working conditions.

8. The multiple-effect total heat recovery thermostatic and humidistatic system according to claim 7, wherein, The obtaining step of the circulation path flow rate data is specifically: Based on the equipment operation state information, extract real-time flow rate data of the air circulation path in the equipment, set a flow rate monitoring interval, select flow rate sampling points in the interval, eliminate abnormal values by comparing the correlation of sampling point data, and obtain circulation path basic flow rate data; Based on the circulation path basic flow rate data, match and verify the path structure and flow rate distribution, calculate the flow rate difference of different path segments, correct the flow rate data by combining the pressure distribution in the equipment, adjust the path parameters by the influence of pressure on flow rate, and obtain the circulation path flow rate distribution. Based on the circulation path flow rate distribution, a flow rate stability analysis is performed, a flow rate stability evaluation standard is set, and under the condition of differentiated paths, the flow rate distribution is evaluated in combination with the dynamic changes of the equipment operation, the stability indexes are compared, and the path structure is optimized, and circulation path flow rate data is obtained.

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