Intelligent temperature and humidity control system for clean air conditioning unit

Abstract

The invention discloses an intelligent temperature and humidity control system for a clean air conditioning unit, relates to the technical field of air conditioning unit control, and solves the problems that numerical regulation and control are not carried out based on the related change process of temperature and humidity data, and the control accuracy of the intelligent temperature and humidity control system still needs to be enhanced. Based on a specific analysis process, change conditions associated with different air volumes and different temperatures can be determined, and based on specific numerical value change conditions, correlation confirmation of corresponding intervals is carried out, so that corresponding change intervals are locked, subsequent accurate regulation and control of temperature and humidity are facilitated, and real-time regulation and control of humidity are carried out based on specific temperature and humidity regulation and control data. And for the adjusted related humidity data, on the basis of a real-time monitoring related result, carrying out abnormity evaluation on the humidity data, identifying whether the humidity data has relatively large deviation, and carrying out readjustment on the humidity data so as to achieve a better temperature and humidity control effect.

Description

Technical Field

[0001] The present invention relates to the technical field of air-conditioning unit control, and in particular to a temperature and humidity intelligent control system for a clean air-conditioning unit. Background Art

[0002] For pharmaceutical clean rooms, the indoor temperature and humidity need to be precisely controlled to ensure the effective storage of indoor items. The air-conditioning unit control mainly involves the precise adjustment of parameters such as temperature, humidity, and air flow to ensure the comfort and air quality of the indoor environment. Modern air-conditioning units are usually equipped with intelligent control systems, which can be remotely monitored and controlled through network connections; users can use mobile phones, tablets and other devices to adjust air-conditioning parameters anytime and anywhere, improving convenience.

[0003] The application with patent publication number CN112503732B involves a temperature and humidity control method, device, system and an air-conditioning unit for an air-conditioning unit. The temperature and humidity control method for an air-conditioning unit includes: obtaining the actual temperature value of the room and the actual humidity values ​​of the room and outside; comparing the actual temperature value with the target temperature value, and the actual humidity values ​​of the room and outside with the target humidity value respectively; determining the operation mode of the air-conditioning unit according to the comparison result; controlling the operation of the air-conditioning unit according to the operation mode to adjust the indoor temperature and humidity; the control method described in the invention collects the actual temperature value of the room and the actual humidity values ​​of the room and outside, and analyzes and judges the actual temperature value of the room and the actual humidity values ​​of the room and outside, determines the corresponding operation mode, and switches the air-conditioning unit to the operation mode for operation, thereby realizing precise control of indoor temperature and humidity to meet the user's usage needs.

[0004] During the temperature control process of its clean air-conditioning unit, the humidity will change during the temperature adjustment. Therefore, when the air-conditioning unit is adjusting the temperature and humidity, the humidity is affected by the temperature, which will cause relevant errors in the subsequent adjustment of the humidity. This will cause large deviations in temperature and humidity during the actual control process. The numerical control is not based on the relevant change process of the temperature and humidity data, and its control accuracy needs to be strengthened. Summary of the invention

[0005] In view of the deficiencies in the prior art, the present invention provides an intelligent temperature and humidity control system for a clean air-conditioning unit, which solves the problem that numerical control is not performed based on the relevant change process of temperature and humidity data, and its control accuracy needs to be improved.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a temperature and humidity intelligent control system for a clean air conditioning unit, comprising:

[0007] The test data acquisition terminal acquires the test data generated by the air-conditioning unit during the test process, and transmits the acquired test data to the test data analysis terminal;

[0008] The test data analysis end receives and analyzes the acquired test data, confirms the indoor temperature change data and indoor humidity change data associated with the air volume from the test data, and constructs two sets of data change curves. Based on the change trends of the two sets of data change curves, the change ranges of the corresponding air volume and the corresponding output temperature are locked. The specific method is as follows:

[0009] Analyze the acquired single group of test data, and generate a temperature change curve belonging to the temperature change data and a humidity change curve belonging to the humidity change data based on the time sequence. Different test data correspond to different air volumes and different output temperatures. The time lines associated with the humidity change curve and the temperature change curve are consistent, and the horizontal coordinate axis associated with the two is the time line, and the vertical coordinate axis is the humidity data or the temperature data.

[0010] Identify the temperature difference CZ at adjacent moments from the temperature change curve i , and CZ i = Temperature data of the next moment - temperature data of the previous moment, where i represents different adjacent moments, and then the humidity difference ZZ of adjacent moments is identified from the humidity change curve i , and ZZ i = humidity data at the next moment - humidity data at the previous moment;

[0011] Adopt G i =CZ i ÷ZZ i Lock the associated variable G i , according to the time sequence, the confirmed several associated variable values ​​G i Sort and determine the variable value sequence;

[0012] For the associated variable G contained in the variable sequence i Perform clustering: From the first group of associated variables G i Start by selecting G i Perform variance processing and determine the variance parameter F. If F < Y1, continue to select, where Y1 is the preset value. If F ≥ Y1, the G selected at this moment is i As the initial G of the second stage i , and the several G associated with the first stage i As the first data column, and perform the same variance processing again, from the initial G i Start to follow up with G i Select and confirm the variance, and confirm the subsequent different data columns in turn;

[0013] For different associated variable values ​​G contained in the confirmed data columns i Perform mean processing to determine the associated mean J belonging to the corresponding data column k , where k represents different data columns, and then from several related means J k Select the minimum value, take the data column associated with the minimum value as the standard data column, and based on the associated variable G in the standard data column i The minimum value and the maximum value are used to determine the variation interval of the test data, and the determined variation interval is transmitted to the interval data storage terminal for storage;

[0014] The temperature control end controls the temperature of the clean air conditioning unit based on the external input temperature control data, and controls the humidity in a related manner based on the specific temperature control process and the determined change range. The specific methods are as follows:

[0015] Based on the temperature control data, determine the air volume and temperature to be adjusted of the clean air conditioning unit, and directly control the clean air conditioning unit based on the air volume and temperature to be adjusted;

[0016] Based on the air volume to be adjusted and the temperature to be adjusted, the change interval associated with the air volume to be adjusted and the temperature to be adjusted is searched from the interval data storage end, and the middle value of the change interval is used as the selected value Xz;

[0017] Based on the control process of the clean air conditioning unit, the temperature change value Sz per unit time is identified, and the humidity value Sd to be adjusted is determined by using Sz÷Xz=Sd. Based on Sd, the clean air conditioning unit is made to reversely adjust the humidity, and the adjustment value is (-Sd);

[0018] The associated control end monitors the real-time control humidity data of the room, and based on the monitoring results, evaluates whether the humidity data of the room is up to standard. If not, relevant adjustments are made to make the stable data up to standard. If it is up to standard, continuous monitoring is performed. The specific methods are as follows:

[0019] Monitor the regulated indoor humidity in real time, generate an indoor humidity change curve in real time, and confirm the median line of the humidity change curve in real time, where the median line is the middle value between the maximum value and the minimum value of the humidity change curve;

[0020] Based on the position of the median line, the median line is moved up and down to determine the standard range. The moving range value is Y2, where Y2 is a preset value. The median line changes up and down following the real-time generation process of the indoor humidity change curve, and the determined standard range also changes accordingly. When the indoor humidity change curve does not belong to the standard range, it is adjusted again:

[0021] If the indoor humidity change curve is in an upward state, it means that the adjusted humidity value is too large and the humidity value needs to be reduced until the indoor humidity change curve is within the standard range;

[0022] If the indoor humidity change curve is in a downward state, it means that the adjusted humidity value is too small and the humidity value needs to be increased until the indoor humidity change curve falls within the standard range.

[0023] Preferably, the test data includes indoor temperature change data at different air volumes and different output temperatures and associated indoor humidity change data.

[0024] Preferably, the interval data storage end stores the change intervals associated with different air volumes and different output temperatures, and provides the temperature control end with storage for retrieval.

[0025] Preferably, the median line is a set of straight lines.

[0026] The present invention provides a temperature and humidity intelligent control system for clean air conditioning units. Compared with the prior art, it has the following beneficial effects:

[0027] The present invention analyzes the associated test data, and based on a specific analysis process, it can determine the changes associated with different air volumes and temperatures, and based on the specific numerical changes, it can confirm the corresponding intervals, thereby locking the corresponding change intervals, facilitating the subsequent precise control of temperature and humidity, and based on the specific temperature and humidity control data, it can control the humidity in real time, so as to achieve better control effects;

[0028] For the adjusted humidity data, based on the relevant results of real-time monitoring, the humidity data is evaluated for abnormalities to identify whether there is a large deviation in the humidity data. Based on the identification results, the humidity data is readjusted to achieve better temperature and humidity control effects, and to ensure accurate control of humidity when the temperature changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic diagram of the principle framework of the present invention;

[0030] Figure 2 It is a schematic diagram of the humidity change curve of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] First embodiment

[0033] See also Figure 1 , the present application provides a temperature and humidity intelligent control system for a clean air-conditioning unit, including a test data acquisition end, a test data analysis end, an interval data storage end, a temperature control end, and an associated control end, wherein the test data acquisition end is electrically connected to an input node of the test data analysis end, and the test data analysis end, the interval data storage end, the temperature control end, and the associated control end are all electrically connected from an output node to an input node;

[0034] Among them, the test data acquisition end acquires the test data generated by the air-conditioning unit during the test process, and transmits the acquired test data to the test data analysis end, and the test data includes indoor temperature change data of different air volumes and different output temperatures and the associated indoor humidity change data. The test data is obtained by the relevant operators in advance or input based on the test results. The reason for the relevant analysis of the test data is to lock the corresponding analysis results to determine the corresponding data interval, so as to facilitate the subsequent control and adjustment of the temperature and humidity data, so as to ensure a more accurate control effect;

[0035] Among them, the test data analysis end receives and analyzes the acquired test data, confirms the indoor temperature change data and indoor humidity change data associated with the air volume from the test data, and constructs two sets of data change curves. Based on the change trends of the two sets of data change curves, the change intervals belonging to the corresponding air volume and the corresponding output temperature (where the output temperature is the relevant temperature output by the corresponding air-conditioning unit after receiving the relevant instructions) are locked, and the determined change interval is transmitted to the interval data storage end. The specific method of determining the change interval is as follows:

[0036] Analyze the acquired single group of test data, and generate a temperature change curve belonging to the temperature change data and a humidity change curve belonging to the humidity change data based on the time sequence. Different test data correspond to different air volumes and different output temperatures. The time lines associated with the humidity change curve and the temperature change curve are consistent, and the horizontal coordinate axis associated with the two is the time line, and the vertical coordinate axis is the humidity data or the temperature data.

[0037] Identify the temperature difference CZ at adjacent moments from the temperature change curve i , and CZ i = Temperature data of the next moment - temperature data of the previous moment, where i represents different adjacent moments, and then the humidity difference ZZ of adjacent moments is identified from the humidity change curve i , and ZZ i = humidity data at the next moment - humidity data at the previous moment;

[0038] Adopt G i =CZ i ÷ZZ i Lock the associated variable G i , according to the time sequence, the confirmed several associated variable values ​​G i Sort and determine the variable value sequence;

[0039] For the associated variable G contained in the variable sequence i Perform clustering: From the first group of associated variables G i Start by selecting G i Perform variance processing and determine the variance parameter F. If F < Y1, continue to select, where Y1 is a preset value, and its specific value is determined by the operator based on experience. If F ≥ Y1, the G selected at this moment is i As the initial G of the second stage i , and the several G associated with the first stage i As the first data column, and perform the same variance processing again, from the initial G i Start to follow up with G i Select and confirm the variance, and confirm the subsequent different data columns in turn. For example, the proposed variable value sequence is {11, 12, 13, 14, 17, 18, 19, 21, 23, 25}. According to this processing method, the proposed Y1 value is 2, among which the variance value of 11, 12, 13, 14 is 1.25, which meets the evaluation conditions. When 11, 12, 13, 14, 17 are calculated for variance, the determined variance value is 4.24, which exceeds the Y1 value. Therefore, 11, 12, 13, 14 are determined as the first group of data columns, and then the value 17 is used as the initial value of the second value and the relevant confirmation of the subsequent data columns is carried out. The subsequent data columns are 17, 18, 19 and 21, 23, 25;

[0040] For different associated variable values ​​G contained in the confirmed data columns i Perform mean processing to determine the associated mean J belonging to the corresponding data column k , where k represents different data columns, and then from several related means J k Select the minimum value, take the data column associated with the minimum value as the standard data column, and based on the associated variable G in the standard data column i The minimum value and the maximum value are used to determine the variation interval of the test data, and the determined variation interval is transmitted to the interval data storage end for storage.

[0041] Among them, the interval data storage end stores the change intervals associated with different air volumes and different output temperatures, and provides them for extraction by the temperature control end. Since the air volumes and output temperatures corresponding to the test data are different, the corresponding change intervals can be confirmed for each set of test data. Therefore, different change intervals need to be determined for different air volumes and different output temperatures, and based on the determined different change intervals, subsequent related temperature control processes are carried out to achieve better control effects.

[0042] Second embodiment

[0043] In the specific implementation process of this embodiment, compared with the above embodiment, this embodiment mainly focuses on the specific control process of the unit temperature, and its specific execution end includes a temperature control end and an associated control end;

[0044] Among them, the temperature control end controls the temperature of the clean air conditioning unit based on the externally input temperature control data, and performs associated control on the humidity based on the specific temperature control process and the determined change range. The specific method of associated control is:

[0045] Based on the temperature control data, determine the air volume and temperature to be adjusted of the clean air conditioning unit, and directly control the clean air conditioning unit based on the air volume and temperature to be adjusted;

[0046] Based on the air volume to be adjusted and the temperature to be adjusted, the change interval associated with the air volume to be adjusted and the temperature to be adjusted is searched from the interval data storage end, and the middle value of the change interval is used as the selected value Xz;

[0047] Based on the control process of the clean air conditioning unit, the temperature change value Sz in unit time is identified, and the humidity value Sd to be adjusted is determined by Sz÷Xz=Sd. Based on Sd, the clean air conditioning unit reversely adjusts the humidity, and its adjustment value is (-Sd). Specifically, when the temperature data changes, the corresponding humidity data will change, so that the indoor humidity will change accordingly. In order to keep the corresponding indoor humidity in the original unchanged state, it is necessary to reversely adjust according to the changed related values, so as to ensure that the indoor humidity data is relatively up to standard, so that the indoor humidity will not be affected by the specific impact of the temperature control process;

[0048] This adjustment and control process belongs to the relevant process of real-time adjustment and control. When the temperature data changes within a unit of time, the corresponding humidity data will also change, so real-time adjustment is required to ensure the spatial humidity of the indoor environment;

[0049] For example: the selected value Xz is -2, where the temperature data that rises per unit time is 4. Then the humidity value to be adjusted determined after processing is -2, so humidity control is required to make the indoor humidity rise by 2 per unit time, so as to complete the synchronous control processing process.

[0050] The associated control end monitors the real-time control humidity data of the room, and based on the monitoring results, evaluates whether the control humidity data meets the standard. If not, relevant adjustments are made to make the stable data meet the standard. If it meets the standard, continuous monitoring is performed. Specifically, when the humidity data is being controlled, as the temperature data changes, the humidity data will also change accordingly, so the adjustment process will cause the humidity data to deviate.

[0051] The specific method for evaluating whether the indoor humidity data meets the standard is:

[0052] Monitor the regulated indoor humidity in real time, generate an indoor humidity change curve in real time, and confirm the median line of the humidity change curve in real time, where the median line is the middle value between the maximum value and the minimum value of the humidity change curve, and the median line is a set of straight lines;

[0053] Based on the position of the median line, the median line is moved up and down to determine the standard range. The moving range value is Y2, where Y2 is a preset value. The specific value is determined by the operator based on experience. The median line changes up and down following the real-time generation process of the indoor humidity change curve, and the determined standard range also changes accordingly. When the indoor humidity change curve does not belong to the standard range, it is adjusted again:

[0054] If the indoor humidity change curve is in an upward state, it means that the adjusted humidity value is too large and the humidity value needs to be reduced until the indoor humidity change curve is within the standard range;

[0055] If the indoor humidity change curve is in a downward state, it means that the adjusted humidity value is too small and the humidity value needs to be increased until the indoor humidity change curve is within the standard range;

[0056] Specifically, when the indoor humidity data has a large deviation change, it is necessary to make a related change to the associated humidity value, change it or reduce it, so as to ensure the related effect of humidity control. Figure 2, confirm the median line of the humidity change curve in real time. The median line moves up and down with the real-time generated temperature change curve. When moving, the corresponding standard range also moves. During the movement, the corresponding humidity change curve will exceed the corresponding standard range when changing, which means that the corresponding humidity controlled in real time belongs to the corresponding state that does not meet the standard. It is necessary to make relevant adjustments to the corresponding state of humidity that does not meet the standard, so as to complete the specific humidity adjustment process, thereby ensuring that the humidity can be effectively controlled during the temperature change process and achieving better data control effect.

[0057] Third embodiment

[0058] The specific implementation process of this embodiment includes the entire implementation process of the above two groups of embodiments.

[0059] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0060] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A temperature and humidity intelligent control system for a clean air conditioning unit, characterized in that: include: The test data acquisition terminal acquires the test data generated by the air-conditioning unit during the test process, and transmits the acquired test data to the test data analysis terminal; The test data analysis end receives and analyzes the acquired test data, confirms the indoor temperature change data and indoor humidity change data associated with the air volume from the test data, and constructs two sets of data change curves. Based on the change trends of the two sets of data change curves, the change ranges belonging to the corresponding air volume and the corresponding output temperature are locked; The temperature control end controls the temperature of the clean air conditioning unit based on the external input temperature control data, and controls the humidity in a related manner based on the specific temperature control process and the determined change range; The associated control end monitors the real-time indoor humidity data and, based on the monitoring results, assesses whether the indoor humidity data meets the standard. If not, relevant adjustments are made to ensure that the stable data meets the standard. If it does, continuous monitoring is performed.

2. According to claim 1, a temperature and humidity intelligent control system for clean air conditioning units is characterized in that: The test data includes indoor temperature change data of different air volumes and different output temperatures and the associated indoor humidity change data.

3. According to claim 1, the intelligent temperature and humidity control system for clean air conditioning units is characterized in that: The specific method of determining the change range of the corresponding air volume and the corresponding output temperature at the test data analysis end is: Analyze the acquired single group of test data, and generate a temperature change curve belonging to the temperature change data and a humidity change curve belonging to the humidity change data based on the time sequence. Different test data correspond to different air volumes and different output temperatures. The time lines associated with the humidity change curve and the temperature change curve are consistent, and the horizontal coordinate axis associated with the two is the time line, and the vertical coordinate axis is the humidity data or the temperature data. Identify the temperature difference CZ at adjacent moments from the temperature change curve i , and CZ i = Temperature data of the next moment - temperature data of the previous moment, where i represents different adjacent moments, and then the humidity difference ZZ of adjacent moments is identified from the humidity change curve i , and ZZ i = humidity data at the next moment - humidity data at the previous moment; Adopt G i =CZ i ÷ZZ i Lock the associated variable G i , according to the time sequence, the confirmed several associated variable values ​​G i Sort and determine the variable value sequence; For the associated variable G contained in the variable sequence i Perform clustering: From the first group of associated variables G i Start by selecting G i Perform variance processing and determine the variance parameter F. If F < Y1, continue to select, where Y1 is the preset value. If F ≥ Y1, the G selected at this moment is i As the initial G of the second stage i , and the several G associated with the first stage i As the first data column, and perform the same variance processing again, from the initial G i Start to follow up with G i Select and confirm the variance, and confirm the subsequent different data columns in turn; For different associated variable values ​​G contained in the confirmed data columns i Perform mean processing to determine the associated mean J belonging to the corresponding data column k , where k represents different data columns, and then from several related means J k Select the minimum value, take the data column associated with the minimum value as the standard data column, and based on the associated variable G in the standard data column i The minimum value and the maximum value are used to determine the variation interval of the test data, and the determined variation interval is transmitted to the interval data storage end for storage.

4. The intelligent temperature and humidity control system for clean air conditioning units according to claim 3 is characterized in that: The interval data storage end stores the change intervals associated with different air volumes and different output temperatures, and provides the temperature control end with the storage end for retrieval.

5. The intelligent temperature and humidity control system for clean air conditioning units according to claim 1 is characterized in that: The specific method of the temperature control end for performing associated control on the humidity is: Based on the temperature control data, determine the air volume and temperature to be adjusted of the clean air conditioning unit, and directly control the clean air conditioning unit based on the air volume and temperature to be adjusted; Based on the air volume to be adjusted and the temperature to be adjusted, the change interval associated with the air volume to be adjusted and the temperature to be adjusted is searched from the interval data storage end, and the middle value of the change interval is used as the selected value Xz; Based on the control process of the clean air-conditioning unit, the temperature change value Sz per unit time is identified, and the humidity value Sd to be adjusted is determined by using Sz÷Xz=Sd. Based on Sd, the clean air-conditioning unit reversely adjusts the humidity, and its adjustment value is (-Sd).

6. The temperature and humidity intelligent control system for clean air conditioning units according to claim 1 is characterized in that: The specific method of evaluating whether the humidity data of indoor control meets the standard at the associated control end is: Monitor the regulated indoor humidity in real time, generate an indoor humidity change curve in real time, and confirm the median line of the humidity change curve in real time, where the median line is the middle value between the maximum value and the minimum value of the humidity change curve; Based on the position of the median line, the median line is moved up and down to determine the standard range. The moving range value is Y2, where Y2 is a preset value. The median line changes up and down following the real-time generation process of the indoor humidity change curve, and the determined standard range also changes accordingly. When the indoor humidity change curve does not belong to the standard range, it is adjusted again: If the indoor humidity change curve is in an upward state, it means that the adjusted humidity value is too large and the humidity value needs to be reduced until the indoor humidity change curve falls within the standard range.

7. The intelligent temperature and humidity control system for clean air conditioning units according to claim 6 is characterized in that: If the indoor humidity change curve is in a downward state, it means that the adjusted humidity value is too small and the humidity value needs to be increased until the indoor humidity change curve falls within the standard range.

8. The intelligent temperature and humidity control system for clean air conditioning units according to claim 6 is characterized in that: The median lines are a set of straight lines.

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