Intelligent heat exchange unit control system

Abstract

The invention provides an intelligent heat exchange unit control system, and relates to the technical field of unit intelligent control, and the system comprises a data collection and storage module which collects unit related parameters of a heat exchange unit in real time, processes the parameters, and transmits the parameters to a target cloud platform for storage; according to the unit regulation and control module, the target cloud platform conducts temperature analysis according to the received data, and the working state of the heat exchange unit is converted; according to the equipment maintenance module, the target cloud platform performs anomaly detection and maintenance on the heat exchange unit; and the visualization module is used for visualizing the state of the heat exchange unit and remotely monitoring a user. The method comprises the following steps: processing unit related parameters of a heat exchange unit collected in real time, and transmitting the processed parameters to a target cloud platform; the target cloud platform analyzes the data received in real time to realize working state conversion and anomaly detection and maintenance of the heat exchange unit; and state visualization and user remote monitoring are carried out on the heat exchange unit, so that the operation efficiency of the heat exchange unit can be effectively improved, unnecessary energy consumption is reduced, and the operation cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of unit intelligent control, and in particular to an intelligent heat exchange unit control system. Background Art

[0002] The heat exchanger is the main equipment for the heating company to implement residential heating. Whether it can be optimally applied is the biggest constraint on whether the heating company can provide reliable heating, equipment management, and energy saving and consumption reduction. However, the existing heat exchanger control system has problems such as low control accuracy, high energy consumption, and high equipment failure rate, resulting in low operating efficiency of the heat exchanger. Therefore, how to improve the operating efficiency of the heat exchanger and reduce operating costs has become one of the current research centers.

[0003] Therefore, the present invention provides an intelligent heat exchange unit control system. Summary of the invention

[0004] The present invention provides an intelligent heat exchanger control system, which is used to process the unit-related parameters of the heat exchanger collected in real time and transmit them to a target cloud platform; the target cloud platform realizes the working state conversion and abnormality detection and maintenance of the heat exchanger by analyzing the data received in real time; the state of the heat exchanger is visualized and the user remotely monitors the heat exchanger, which can effectively improve the operating efficiency of the heat exchanger, reduce unnecessary energy consumption, and thus reduce operating costs.

[0005] The present invention provides an intelligent heat exchange unit control system, comprising:

[0006] Data acquisition and storage module: used to collect relevant parameters of the heat exchange unit in real time using pre-set acquisition equipment, perform data preprocessing, and then transmit to the target cloud platform for storage;

[0007] Unit control module: used for the target cloud platform to perform temperature analysis based on the data received in real time, and to convert the working state of the heat exchange unit based on the analysis results;

[0008] Equipment maintenance module: used by the target cloud platform to detect and maintain equipment anomalies of the heat exchanger unit;

[0009] Visualization module: used for status visualization of heat exchanger units and remote user monitoring.

[0010] Preferably, the unit-related parameters include unit environmental parameters and unit operating parameters, wherein the unit environmental parameters refer to the indoor and outdoor temperature and humidity where the unit is installed.

[0011] Preferably, the data collection and storage includes:

[0012] Data acquisition unit: used to collect relevant parameter data of the heat exchange unit in real time using the preset acquisition equipment installed at the set position;

[0013] Data transmission unit: used to transmit unit-related parameter data to the target IoT device that communicates with the preset acquisition device;

[0014] The target IoT device pre-processes the received unit-related parameter data, obtains key parameter data and transmits it to the target cloud platform;

[0015] Data storage unit: used for the target cloud platform to divide the key parameter data according to data types to obtain environment-key parameter data and operation-key parameter data;

[0016] The environment-key parameter data and the operation-key parameter data are respectively stored in corresponding data storage areas of the target data warehouse.

[0017] Preferably, the unit control module includes:

[0018] Temperature prediction unit: used to input the outdoor temperature of the unit in the environment-key parameter data into the ideal temperature prediction model obtained by pre-training the neural network to obtain the ideal predicted temperature;

[0019] Temperature analysis unit: used to compare the indoor temperature of the unit in the environment-key parameter data with the ideal predicted temperature to obtain a first temperature absolute difference;

[0020] Analyzing the first temperature absolute difference to obtain a temperature difference coefficient;

[0021] Taking the temperature difference coefficient as a matching condition, determining the temperature difference level from the set temperature level list;

[0022] outputting the first temperature absolute difference and the temperature difference level as temperature analysis results;

[0023] If the unit indoor temperature in the current environment-key parameter data is greater than the ideal predicted temperature, it is determined that the unit indoor temperature of the current heat exchange unit is higher than the ideal predicted temperature and is output as a temperature analysis result;

[0024] If the unit indoor temperature in the current environment-key parameter data is lower than the ideal predicted temperature, it is determined that the unit indoor temperature of the current heat exchange unit is lower than the ideal predicted temperature and is output as a temperature analysis result;

[0025] State adjustment unit: used to combine the temperature analysis result with the current working mode of the heat exchanger unit to generate a state adjustment instruction, and transmit it to the heat exchanger unit to perform working state conversion.

[0026] Preferably, analyzing the first temperature absolute difference to obtain a temperature difference coefficient includes:

[0027] Extract the historical indoor temperature and historical indoor humidity of the current heat exchanger unit within a preset time period from the target data warehouse;

[0028] The temperature and humidity change curve is established with historical indoor temperature as the independent variable and historical indoor humidity as the dependent variable;

[0029] Obtaining the slope of the temperature and humidity change curve and treating it as the first slope;

[0030] The first temperature difference obtained at the current moment, the indoor temperature of the unit and the first slope are combined to calculate a temperature difference coefficient;

[0031] The calculation formula of the temperature difference coefficient is as follows:

[0032] Where, C1 represents the temperature difference coefficient; P1 represents the first temperature difference; P c It represents the set temperature difference threshold; ln represents the natural logarithm; e represents the natural base; ε1 represents the first slope; w0 represents the indoor temperature of the unit obtained at the current moment; w1 represents the indoor temperature of the unit obtained at the previous moment; s1 represents the indoor humidity of the unit obtained at the current moment; s0 represents the indoor humidity of the unit obtained at the previous moment.

[0033] Preferably, the state adjustment unit includes:

[0034] Lowering the temperature block: according to the temperature analysis result, if the indoor temperature of the current heat exchanger unit is higher than the ideal predicted temperature, when the heat exchanger unit is in the non-cooling mode and the temperature difference level is low difference, the unit is switched to the cooling mode as a state adjustment measure;

[0035] When the heat exchange unit is in non-cooling mode and the temperature difference level is medium or high, two measures are used as state adjustment measures: switching the unit to cooling mode and increasing the cooling capacity of the unit;

[0036] When the heat exchange unit is in cooling mode, the unit's cooling capacity increase measure is used as a state adjustment measure;

[0037] Increase temperature block: If the current indoor temperature of the heat exchanger unit is lower than the ideal predicted temperature, when the heat exchanger unit is in non-heating mode and the temperature difference level is low difference, the unit switching heating mode measure is used as a state adjustment measure;

[0038] When the heat exchange unit is in non-heating mode and the temperature difference level is medium or high, two measures are used as state adjustment measures: switching the unit to heating mode and increasing the heating capacity of the unit;

[0039] When the heat exchange unit is in heating mode, the unit's heating capacity increase measure is used as a state adjustment measure;

[0040] The specific contents of the corresponding measures of the state adjustment measures are generated into a state adjustment instruction and transmitted to the heat exchanger unit to control the current heat exchanger unit to realize the working state conversion.

[0041] Preferably, the equipment maintenance module includes:

[0042] Anomaly detection unit: used to compare the operation-key parameter data with the set safety parameter threshold of the heat exchanger unit to obtain the absolute difference of the first parameter;

[0043] Mark the operation-critical parameter data that is greater than the set safety parameter threshold as abnormal parameters;

[0044] The operation-critical parameter data that is not greater than the set safety parameter threshold and whose first parameter absolute difference is not greater than the preset parameter difference is marked as possible abnormal parameters;

[0045] The operation-critical parameter data that is not greater than the set safety parameter threshold and whose first parameter absolute difference is greater than the preset parameter difference is marked as normal parameters;

[0046] If there are currently abnormal parameters or possibly abnormal parameters, it is determined that the current heat exchanger unit is abnormal.

[0047] If there are no abnormal parameters or possible abnormal parameters at present, it is determined that the current heat exchanger unit is normal.

[0048] Abnormal processing unit: used to calculate the abnormal coefficient of the equipment based on the current abnormal parameters or possible abnormal parameters when the current heat exchange unit has an abnormality;

[0049] The calculation formula of the equipment abnormality coefficient is as follows:

[0050] In the formula, P represents the equipment abnormality coefficient of the current heat exchanger unit; n0 represents the total number of operation-key parameter data; n1 represents the total number of current abnormal parameters; x i It is expressed as the absolute difference between the i-th abnormal parameter and the corresponding set safety parameter threshold, where i = 1, 2, 3, ..., n1; It is represented by the weight of the influence of the ith abnormal parameter on the abnormal degree of the equipment; n2 is represented by the total number of possible abnormal parameters at present; y j It is expressed as the absolute difference of the first parameter corresponding to the jth possible abnormal parameter, where j = 1, 2, 3, ..., n2; It is expressed as the average absolute difference of the corresponding first parameter of all possible abnormal parameters; σ jIt is represented as the weight of the influence of the jth possible abnormal parameter on the abnormal degree of the equipment; e is represented as the natural base;

[0051] Determining the equipment abnormality level according to the equipment abnormality coefficient;

[0052] Using the currently existing abnormal parameters as matching conditions, obtain the abnormal maintenance strategy from the set abnormal maintenance list;

[0053] Taking the currently existing possible abnormal parameters and the corresponding absolute difference of the first parameter as matching conditions, a possible abnormality prevention strategy is obtained from the set possible range-prevention list;

[0054] Based on the currently existing abnormal parameters or possible abnormal parameters, and the corresponding abnormal maintenance strategy or possible abnormal prevention strategy, an equipment abnormality report is generated, and the equipment abnormality report is annotated with the equipment abnormality level and transmitted to the visualization module.

[0055] Preferably, the visualization module includes:

[0056] Status visualization unit: used to display the relevant parameters of the heat exchange unit in real time using the real-time display block and to display the abnormal information of the equipment using the abnormal display block;

[0057] Real-time display block: used to display the relevant parameters of the heat exchanger in real time in digital form in the set data display area of ​​the status visualization interface, and to use dynamic charts to display the change trend of the operating parameters of the heat exchanger within a preset time period;

[0058] Abnormal display block: used to display the existing abnormal parameters or possible abnormal parameters and the corresponding abnormal maintenance strategy or possible abnormal prevention strategy in the set abnormal display area of ​​the status visualization interface according to the received equipment abnormality report, and notify the maintenance personnel to intervene through sound prompts;

[0059] Remote monitoring unit: It is used for users to establish communication with the target cloud platform using smart devices, log in to the target cloud platform with username and password, and view device status and device abnormality information in real time on the status visualization interface.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] The relevant parameters of the heat exchanger units collected in real time are processed and transmitted to the target cloud platform; the target cloud platform realizes the working state conversion, abnormality detection and maintenance of the heat exchanger units by analyzing the data received in real time; the status visualization and user remote monitoring of the heat exchanger units can effectively improve the operating efficiency of the heat exchanger units, reduce unnecessary energy consumption, and thus reduce operating costs.

[0062] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0063] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0065] Figure 1 It is a structural diagram of an intelligent heat exchange unit control system in an embodiment of the present invention. DETAILED DESCRIPTION

[0066] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0067] The embodiment of the present invention provides an intelligent heat exchange unit control system, such as Figure 1 As shown, including:

[0068] Data acquisition and storage module: used to collect relevant parameters of the heat exchange unit in real time using pre-set acquisition equipment, perform data preprocessing, and then transmit to the target cloud platform for storage;

[0069] Unit control module: used for the target cloud platform to perform temperature analysis based on the data received in real time, and to convert the working state of the heat exchange unit based on the analysis results;

[0070] Equipment maintenance module: used by the target cloud platform to detect and maintain equipment anomalies of the heat exchanger unit;

[0071] Visualization module: used for status visualization of heat exchanger units and remote user monitoring.

[0072] In this embodiment, the set position refers to a pre-set location for installing a preset collection device, such as outside the heat exchanger unit; the preset collection device refers to a device for collecting unit-related parameter data of the heat exchanger unit, such as a temperature sensor and a humidity sensor.

[0073] In this embodiment, the unit-related parameters include unit environmental parameters and unit operating parameters, wherein the unit environmental parameters refer to the indoor and outdoor temperature and humidity of the unit installation room, and the unit operating parameters include the inlet and outlet temperatures, key component temperatures, inlet and outlet pressures, working pressures, and inlet and outlet flows of the heat exchanger unit, etc.; the target cloud platform refers to a cloud service platform that realizes remote monitoring and management of the entire heat exchanger unit system by receiving real-time unit-related parameter data transmitted from the data acquisition and transmission module, including data storage and management, data processing and analysis, unit control, equipment maintenance, and visual monitoring functions.

[0074] The beneficial effects of the above technical solution are: the unit-related parameters of the heat exchanger unit collected in real time are processed and transmitted to the target cloud platform; the target cloud platform realizes the working state conversion and abnormality detection and maintenance of the heat exchanger unit by analyzing the data received in real time; the state visualization and user remote monitoring of the heat exchanger unit can effectively improve the operating efficiency of the heat exchanger unit, reduce unnecessary energy consumption, and thus reduce operating costs.

[0075] An embodiment of the present invention provides an intelligent heat exchange unit control system, wherein the data acquisition and storage includes:

[0076] Data acquisition unit: used to collect relevant parameter data of the heat exchange unit in real time using the preset acquisition equipment installed at the set position;

[0077] Data transmission unit: used to transmit unit-related parameter data to the target IoT device that communicates with the preset acquisition device;

[0078] The target IoT device pre-processes the received unit-related parameter data, obtains key parameter data and transmits it to the target cloud platform;

[0079] Data storage unit: used for the target cloud platform to divide the key parameter data according to data types to obtain environment-key parameter data and operation-key parameter data;

[0080] The environment-key parameter data and the operation-key parameter data are respectively stored in corresponding data storage areas of the target data warehouse.

[0081] In this embodiment, the target IoT device refers to a device that can receive data from various sensors and communicate with the sensors through a built-in interface or communication protocol, such as an IoT gateway or an IoT router; key parameter data refers to data obtained after data preprocessing of unit-related parameter data, wherein data preprocessing includes data cleaning and format conversion.

[0082] In this embodiment, the data types include unit environmental parameters and unit operating parameters; environment-key parameter data refers to data preprocessing of unit environmental parameter data in unit-related parameter data, such as unit indoor temperature and unit outdoor temperature. Unit indoor temperature refers to the temperature in the room where the heat exchanger is installed, and unit outdoor temperature refers to the temperature outside the room where the heat exchanger is installed; operation-key parameter data refers to data preprocessing of unit operating parameter data in unit-related parameter data, such as unit pressure; target cloud platform refers to a cloud service platform that realizes remote monitoring and management of the entire heat exchanger unit system by receiving real-time unit-related parameter data transmitted from a data acquisition and transmission module, including data storage and management, data processing and analysis, unit control, equipment maintenance, and visual monitoring functions; target data warehouse refers to a centralized repository for storing and managing large amounts of historical data.

[0083] The beneficial effect of the above technical solution is: by utilizing the preset acquisition equipment to obtain the various parameter data of the heat exchanger unit in real time and combining it with the Internet of Things technology to transmit it to the target cloud platform, data support is provided for the subsequent operation status conversion and equipment maintenance of the heat exchanger unit.

[0084] The embodiment of the present invention provides an intelligent heat exchange unit control system, wherein the unit control module comprises:

[0085] Temperature prediction unit: used to input the outdoor temperature of the unit in the environment-key parameter data into the ideal temperature prediction model obtained by pre-training the neural network to obtain the ideal predicted temperature;

[0086] Temperature analysis unit: used to compare the indoor temperature of the unit in the environment-key parameter data with the ideal predicted temperature to obtain a first temperature absolute difference;

[0087] Analyzing the first temperature absolute difference to obtain a temperature difference coefficient;

[0088] Taking the temperature difference coefficient as a matching condition, determining the temperature difference level from the set temperature level list;

[0089] outputting the first temperature absolute difference and the temperature difference level as temperature analysis results;

[0090] If the unit indoor temperature in the current environment-key parameter data is greater than the ideal predicted temperature, it is determined that the unit indoor temperature of the current heat exchange unit is higher than the ideal predicted temperature and is output as a temperature analysis result;

[0091] If the unit indoor temperature in the current environment-key parameter data is lower than the ideal predicted temperature, it is determined that the unit indoor temperature of the current heat exchange unit is lower than the ideal predicted temperature and is output as a temperature analysis result;

[0092] State adjustment unit: used to combine the temperature analysis result with the current working mode of the heat exchanger unit to generate a state adjustment instruction, and transmit it to the heat exchanger unit to perform working state conversion.

[0093] In this embodiment, the environment-key parameter data refers to the data obtained after preprocessing the unit environment parameter data in the unit related parameter data, such as the unit indoor temperature and the unit outdoor temperature; the ideal temperature prediction model is a model obtained by training the neural network with the preset amount of preprocessed indoor and outdoor historical actual temperature data of the heat exchanger as training data, which is used to predict the ideal temperature in the heat exchanger indoor; the ideal predicted temperature refers to the expected temperature value in the current heat exchanger indoor obtained by inputting the unit outdoor temperature in the environment-key parameter data into the ideal temperature prediction model; the first temperature absolute difference refers to the absolute value of the temperature of the ideal predicted temperature minus the indoor temperature in the environment-key parameter data; the temperature difference coefficient is used to characterize the degree of temperature difference between the current indoor temperature and the ideal predicted temperature; the set temperature level list is composed of temperature levels and corresponding temperature difference coefficient ranges, wherein the temperature levels include three levels of low difference, medium difference and high difference; the temperature difference level refers to the temperature level selected from the set temperature level list with the current temperature difference coefficient as the matching condition; the working mode includes three modes: cooling mode, heating mode and standby mode; the state adjustment instruction is an instruction generated according to the specific content of the corresponding measure of the state adjustment measure, which is used to guide the heat exchanger unit to switch the working state.

[0094] The beneficial effects of the above technical solution are: by using the ideal temperature prediction model to predict the ideal predicted temperature, a scientific basis is provided for the subsequent control of the heat exchanger unit; and by comparing the temperatures and determining the temperature difference levels, the state adjustment instructions are generated to accurately control the working state of the heat exchanger unit, avoid unnecessary energy consumption, and realize intelligent control of the heat exchanger unit.

[0095] The embodiment of the present invention provides an intelligent heat exchanger control system, which analyzes the first temperature absolute difference to obtain a temperature difference coefficient, including:

[0096] Extract the historical indoor temperature and historical indoor humidity of the current heat exchanger unit within a preset time period from the target data warehouse;

[0097] The temperature and humidity change curve is established with historical indoor temperature as the independent variable and historical indoor humidity as the dependent variable;

[0098] Obtaining the slope of the temperature and humidity change curve and treating it as the first slope;

[0099] The first temperature difference obtained at the current moment, the indoor temperature of the unit and the first slope are combined to calculate a temperature difference coefficient;

[0100] The calculation formula of the temperature difference coefficient is as follows:

[0101] Where, C1 represents the temperature difference coefficient; P1 represents the first temperature difference; P c It represents the set temperature difference threshold; ln represents the natural logarithm; e represents the natural base; ε1 represents the first slope; w0 represents the indoor temperature of the unit obtained at the current moment; w1 represents the indoor temperature of the unit obtained at the previous moment; s1 represents the indoor humidity of the unit obtained at the current moment; s0 represents the indoor humidity of the unit obtained at the previous moment.

[0102] In this embodiment, the target data warehouse refers to a centralized repository for storing and managing a large amount of historical data; the preset time period is predetermined; the temperature and humidity change curve refers to a curve established with the historical indoor temperature as the independent variable and the historical indoor humidity as the dependent variable; the first slope refers to the slope of the temperature and humidity change curve; the temperature difference coefficient is used to characterize the degree of temperature difference between the current indoor temperature and the ideal predicted temperature; the temperature difference threshold is set equal to Among them, w y represents the ideal predicted temperature obtained at the current moment; w1 represents the indoor temperature of the unit obtained at the current moment.

[0103] The beneficial effect of the above technical solution is that by calculating the temperature difference coefficient, a data basis can be provided for determining the temperature difference level, which is conducive to generating accurate state adjustment instructions to accurately control the working state of the heat exchanger unit, thereby realizing intelligent control of the heat exchanger unit.

[0104] An embodiment of the present invention provides an intelligent heat exchanger control system, wherein the state adjustment unit comprises:

[0105] Lowering the temperature block: according to the temperature analysis result, if the indoor temperature of the current heat exchanger unit is higher than the ideal predicted temperature, when the heat exchanger unit is in the non-cooling mode and the temperature difference level is low difference, the unit is switched to the cooling mode as a state adjustment measure;

[0106] When the heat exchange unit is in non-cooling mode and the temperature difference level is medium or high, two measures are used as state adjustment measures: switching the unit to cooling mode and increasing the cooling capacity of the unit;

[0107] When the heat exchange unit is in cooling mode, the unit's cooling capacity increase measure is used as a state adjustment measure;

[0108] Increase temperature block: If the current indoor temperature of the heat exchanger unit is lower than the ideal predicted temperature, when the heat exchanger unit is in non-heating mode and the temperature difference level is low difference, the unit switching heating mode measure is used as a state adjustment measure;

[0109] When the heat exchange unit is in non-heating mode and the temperature difference level is medium or high, two measures are used as state adjustment measures: switching the unit to heating mode and increasing the heating capacity of the unit;

[0110] When the heat exchange unit is in heating mode, the unit's heating capacity increase measure is used as a state adjustment measure;

[0111] The specific contents of the corresponding measures of the state adjustment measures are generated into a state adjustment instruction and transmitted to the heat exchanger unit to control the current heat exchanger unit to realize the working state conversion.

[0112] In this embodiment, the temperature analysis result refers to that the indoor temperature of the current heat exchanger unit is higher than the ideal predicted temperature, the indoor temperature of the unit in the current environment-key parameter data is lower than the ideal predicted temperature, the temperature difference level, and the first temperature absolute difference; the non-cooling mode refers to the heating mode or the standby mode; the unit switching cooling mode measure refers to switching the working mode of the current heat exchanger unit to the cooling mode; the unit increasing the cooling capacity refers to increasing the cooling capacity of the current heat exchanger unit, wherein the cooling capacity is obtained by multiplying the first temperature absolute difference with the room volume, air density and specific heat capacity.

[0113] In this embodiment, non-heating mode refers to cooling mode or standby mode; switching the unit to heating mode refers to switching the current working mode of the heat exchanger unit to heating mode; increasing the heating capacity of the unit refers to increasing the heating capacity of the current heat exchanger unit, wherein the heating capacity is obtained by multiplying the absolute difference of the first temperature with the room volume, air density and specific heat capacity; the specific content of the measure refers to the adjustment behavior of the state adjustment measure, for example, the state adjustment measure is the switching of the unit to cooling mode, and the corresponding adjustment behavior is to start the refrigeration cycle; the state adjustment measure is the switching of the unit to heating mode, and the corresponding adjustment behavior is to start the heating cycle; the state adjustment measure is the increase of the cooling capacity of the unit, and the corresponding adjustment behavior is to increase the fan speed and increase the refrigerant flow rate; the state adjustment measure is the increase of the heating capacity of the unit, and the corresponding adjustment behavior is to increase the flow rate of the heat medium; the state adjustment instruction is an instruction generated according to the specific content of the corresponding measure of the state adjustment measure, which is used to guide the heat exchanger unit to convert the working state.

[0114] The beneficial effect of the above technical solution is: by combining and analyzing the gap between the current indoor temperature of the heat exchanger unit and the ideal predicted temperature, the temperature difference level and the current working mode of the unit, taking appropriate adjustment measures, and generating corresponding state adjustment instructions to control the current heat exchanger unit to achieve working state conversion, intelligent control of the heat exchanger unit can be achieved.

[0115] An embodiment of the present invention provides an intelligent heat exchange unit control system, wherein the equipment maintenance module comprises:

[0116] Anomaly detection unit: used to compare the operation-key parameter data with the set safety parameter threshold of the heat exchanger unit to obtain the absolute difference of the first parameter;

[0117] Mark the operation-critical parameter data that is greater than the set safety parameter threshold as abnormal parameters;

[0118] The operation-critical parameter data that is not greater than the set safety parameter threshold and whose first parameter absolute difference is not greater than the preset parameter difference is marked as possible abnormal parameters;

[0119] The operation-critical parameter data that is not greater than the set safety parameter threshold and whose first parameter absolute difference is greater than the preset parameter difference is marked as normal parameters;

[0120] If there are currently abnormal parameters or possibly abnormal parameters, it is determined that the current heat exchanger unit is abnormal.

[0121] If there are no abnormal parameters or possible abnormal parameters at present, it is determined that the current heat exchanger unit is normal.

[0122] Abnormal processing unit: used to calculate the abnormal coefficient of the equipment based on the current abnormal parameters or possible abnormal parameters when the current heat exchange unit has an abnormality;

[0123] The calculation formula of the equipment abnormality coefficient is as follows:

[0124] In the formula, P represents the equipment abnormality coefficient of the current heat exchanger unit; n0 represents the total number of operation-key parameter data; n1 represents the total number of current abnormal parameters; x i It is expressed as the absolute difference between the i-th abnormal parameter and the corresponding set safety parameter threshold, where i = 1, 2, 3, ..., n1; It is represented by the weight of the influence of the ith abnormal parameter on the abnormal degree of the equipment; n2 is represented by the total number of possible abnormal parameters at present; y j It is expressed as the absolute difference of the first parameter corresponding to the jth possible abnormal parameter, where j = 1, 2, 3, ..., n2; It is expressed as the average absolute difference of the corresponding first parameter of all possible abnormal parameters; σ j It is represented as the weight of the influence of the jth possible abnormal parameter on the abnormal degree of the equipment; e is represented as the natural base;

[0125] Determining the equipment abnormality level according to the equipment abnormality coefficient;

[0126] Using the currently existing abnormal parameters as matching conditions, obtain the abnormal maintenance strategy from the set abnormal maintenance list;

[0127] Taking the currently existing possible abnormal parameters and the corresponding absolute difference of the first parameter as matching conditions, a possible abnormality prevention strategy is obtained from the set possible range-prevention list;

[0128] Based on the currently existing abnormal parameters or possible abnormal parameters, and the corresponding abnormal maintenance strategy or possible abnormal prevention strategy, an equipment abnormality report is generated, and the equipment abnormality report is annotated with the equipment abnormality level and transmitted to the visualization module.

[0129] In this embodiment, the operation-critical parameter data refers to the data obtained after data preprocessing of the unit operation parameter data in the unit-related parameter data, such as the unit pressure; the set safety parameter threshold is determined according to the unit instruction manual of the current heat exchanger unit; the first parameter absolute difference refers to the absolute value of the parameter difference between the operation-critical parameter data and the corresponding set safety parameter threshold; the abnormal parameter refers to the operation-critical parameter data greater than the set safety parameter threshold; the possible abnormal parameter refers to the operation-critical parameter data that is not greater than the set safety parameter threshold and the first parameter absolute difference is not greater than the preset parameter difference.

[0130] In this embodiment, the preset parameter difference is pre-set and is 15% of the set safety parameter threshold. For example, the set safety parameter threshold of the unit inlet temperature of the current heat exchanger unit is 30°, then the preset parameter difference is 30°×15%=4.5°; the normal parameter refers to the operation-key parameter data that is not greater than the set safety parameter threshold and the absolute difference of the first parameter is greater than the preset parameter difference; the equipment abnormality coefficient is used to characterize the degree of equipment abnormality of the current heat exchanger unit; the equipment abnormality level is the abnormality level obtained from the preset abnormality level mapping table with the equipment abnormality coefficient as the matching condition, wherein the preset abnormality level is composed of the abnormality coefficient range and the corresponding abnormality level, and the abnormality level includes minor abnormality, general abnormality and severe abnormality; the set abnormal maintenance list is composed of abnormal parameters and corresponding abnormal maintenance strategies. For example, if the abnormal parameter is the unit pressure, the corresponding abnormal maintenance strategy is to reduce the unit working pressure and check the pressure sensor.

[0131] In this embodiment, the possible range-prevention list is set to be composed of possible abnormal parameters, the absolute difference range of the first parameter and possible abnormal prevention strategies. For example, if the possible abnormal parameter is the unit inlet temperature, the corresponding possible abnormal prevention strategy is to increase heat dissipation; the equipment abnormality report is composed of the time when the abnormality occurs, abnormal parameters or possible abnormal parameters, and the corresponding abnormal maintenance strategy or possible abnormality prevention strategy.

[0132] The beneficial effect of the above technical solution is: by performing equipment abnormality detection and maintenance on the heat exchanger unit based on the received unit operation data, it is possible to prevent the expansion of faults and reduce losses, thereby improving the equipment reliability and intelligent control level of the heat exchanger unit.

[0133] An embodiment of the present invention provides an intelligent heat exchange unit control system, wherein the visualization module comprises:

[0134] Status visualization unit: used to display the relevant parameters of the heat exchange unit in real time using the real-time display block and to display the abnormal information of the equipment using the abnormal display block;

[0135] Real-time display block: used to display the relevant parameters of the heat exchanger in real time in digital form in the set data display area of ​​the status visualization interface, and to use dynamic charts to display the change trend of the operating parameters of the heat exchanger within a preset time period;

[0136] Abnormal display block: used to display the existing abnormal parameters or possible abnormal parameters and the corresponding abnormal maintenance strategy or possible abnormal prevention strategy in the set abnormal display area of ​​the status visualization interface according to the received equipment abnormality report, and notify the maintenance personnel to intervene through sound prompts;

[0137] Remote monitoring unit: It is used for users to establish communication with the target cloud platform using smart devices, log in to the target cloud platform with username and password, and view device status and device abnormality information in real time on the status visualization interface.

[0138] In this embodiment, the status visualization interface refers to a graphical user interface for displaying relevant parameters and abnormal information of the heat exchanger unit; the set data display area is a specific area in the status visualization interface, which is used to display the unit-related parameters of the heat exchanger unit in real time, such as temperature and pressure; the dynamic chart refers to a chart for displaying the changing trend of the operating parameters of the heat exchanger unit within a preset time period, such as a line chart or a bar chart; the preset time period is predetermined, such as 6 hours.

[0139] In this embodiment, the operating parameter change trend refers to the change of various operating parameters of the heat exchanger unit within a preset time period, such as pressure and flow; the abnormal display area is set to be a specific area in the status visualization interface, which is used to display abnormal parameters or possible abnormal parameters of the heat exchanger unit, as well as corresponding abnormal maintenance strategies or possible abnormal prevention strategies, and when an abnormality occurs in the unit, the area will immediately display relevant information and notify maintenance personnel to intervene through sound prompts; smart devices refer to portable smart mobile devices, such as mobile phones; device abnormality information refers to the time when the abnormality of the heat exchanger unit occurs, abnormal parameters or possible abnormal parameters, corresponding abnormal maintenance strategies or possible abnormal prevention strategies, and abnormal handling results.

[0140] The beneficial effects of the above technical solution are: through visualization of the status of the heat exchanger unit and remote monitoring by users, it can help users better understand the operating status and performance changes of the unit, provide data support for optimizing management and maintenance strategies, and effectively improve the intelligent control level of the heat exchanger unit.

[0141] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. An intelligent heat exchange unit control system, characterized in that: include: Data acquisition and storage module: used to collect relevant parameters of the heat exchange unit in real time using pre-set acquisition equipment, perform data preprocessing, and then transmit to the target cloud platform for storage; Unit control module: used for the target cloud platform to perform temperature analysis based on the data received in real time, and to convert the working state of the heat exchange unit based on the analysis results; Equipment maintenance module: used by the target cloud platform to detect and maintain equipment anomalies of the heat exchanger unit; Visualization module: used for status visualization of heat exchanger units and remote user monitoring.

2. The intelligent heat exchanger control system according to claim 1, characterized in that: The unit-related parameters include unit environmental parameters and unit operating parameters, among which the unit environmental parameters refer to the indoor and outdoor temperature and humidity where the unit is installed.

3. The intelligent heat exchanger control system according to claim 1, characterized in that: The data collection and storage include: Data acquisition unit: used to collect relevant parameter data of the heat exchange unit in real time using the preset acquisition equipment installed at the set position; Data transmission unit: used to transmit unit-related parameter data to the target IoT device that communicates with the preset acquisition device; The target IoT device pre-processes the received unit-related parameter data, obtains key parameter data and transmits it to the target cloud platform; Data storage unit: used for the target cloud platform to divide the key parameter data according to data types to obtain environment-key parameter data and operation-key parameter data; The environment-key parameter data and the operation-key parameter data are respectively stored in corresponding data storage areas of the target data warehouse.

4. The intelligent heat exchanger control system according to claim 1, characterized in that: The unit control module includes: Temperature prediction unit: used to input the outdoor temperature of the unit in the environment-key parameter data into the ideal temperature prediction model obtained by pre-training the neural network to obtain the ideal predicted temperature; Temperature analysis unit: used to compare the indoor temperature of the unit in the environment-key parameter data with the ideal predicted temperature to obtain a first temperature absolute difference; Analyzing the first temperature absolute difference to obtain a temperature difference coefficient; Taking the temperature difference coefficient as a matching condition, determining the temperature difference level from the set temperature level list; outputting the first temperature absolute difference and the temperature difference level as temperature analysis results; If the unit indoor temperature in the current environment-key parameter data is greater than the ideal predicted temperature, it is determined that the unit indoor temperature of the current heat exchange unit is higher than the ideal predicted temperature and is output as a temperature analysis result; If the unit indoor temperature in the current environment-key parameter data is lower than the ideal predicted temperature, it is determined that the unit indoor temperature of the current heat exchange unit is lower than the ideal predicted temperature and is output as a temperature analysis result; State adjustment unit: used to combine the temperature analysis result with the current working mode of the heat exchanger unit to generate a state adjustment instruction, and transmit it to the heat exchanger unit to perform working state conversion.

5. The intelligent heat exchanger control system according to claim 4, characterized in that: The first temperature absolute difference is analyzed to obtain a temperature difference coefficient, including: Extract the historical indoor temperature and historical indoor humidity of the current heat exchanger unit within a preset time period from the target data warehouse; The temperature and humidity change curve is established with historical indoor temperature as the independent variable and historical indoor humidity as the dependent variable; Obtaining the slope of the temperature and humidity change curve and treating it as the first slope; The first temperature difference obtained at the current moment, the indoor temperature of the unit and the first slope are combined to calculate a temperature difference coefficient; The calculation formula of the temperature difference coefficient is as follows: Where C1 is the temperature difference coefficient; P1 is the first temperature difference; P c It represents the set temperature difference threshold; ln represents the natural logarithm; e represents the natural base; ε1 represents the first slope; w0 represents the indoor temperature of the unit obtained at the current moment; w1 represents the indoor temperature of the unit obtained at the previous moment; s1 represents the indoor humidity of the unit obtained at the current moment; s0 represents the indoor humidity of the unit obtained at the previous moment.

6. The intelligent heat exchanger control system according to claim 4, characterized in that: The state adjustment unit comprises: Lowering the temperature block: according to the temperature analysis result, if the indoor temperature of the current heat exchanger unit is higher than the ideal predicted temperature, when the heat exchanger unit is in the non-cooling mode and the temperature difference level is low difference, the unit is switched to the cooling mode as a state adjustment measure; When the heat exchange unit is in non-cooling mode and the temperature difference level is medium or high, two measures are used as state adjustment measures: switching the unit to cooling mode and increasing the cooling capacity of the unit; When the heat exchange unit is in cooling mode, the unit's cooling capacity increase measure is used as a state adjustment measure; Increase temperature block: If the current indoor temperature of the heat exchanger unit is lower than the ideal predicted temperature, when the heat exchanger unit is in non-heating mode and the temperature difference level is low difference, the unit switching heating mode measure is used as a state adjustment measure; When the heat exchange unit is in non-heating mode and the temperature difference level is medium or high, two measures are used as state adjustment measures: switching the unit to heating mode and increasing the heating capacity of the unit; When the heat exchange unit is in heating mode, the unit's heating capacity increase measure is used as a state adjustment measure; The specific contents of the corresponding measures of the state adjustment measures are generated into a state adjustment instruction and transmitted to the heat exchanger unit to control the current heat exchanger unit to realize the working state conversion.

7. The intelligent heat exchanger control system according to claim 1, characterized in that: The equipment maintenance module includes: Anomaly detection unit: used to compare the operation-key parameter data with the set safety parameter threshold of the heat exchanger unit to obtain the absolute difference of the first parameter; Mark the operation-critical parameter data that is greater than the set safety parameter threshold as abnormal parameters; The operation-critical parameter data that is not greater than the set safety parameter threshold and whose first parameter absolute difference is not greater than the preset parameter difference is marked as possible abnormal parameters; The operation-critical parameter data that is not greater than the set safety parameter threshold and whose first parameter absolute difference is greater than the preset parameter difference is marked as normal parameters; If there are currently abnormal parameters or possibly abnormal parameters, it is determined that the current heat exchanger unit is abnormal. If there are no abnormal parameters or possible abnormal parameters at present, it is determined that the current heat exchanger unit is normal. Abnormal processing unit: used to calculate the abnormal coefficient of the equipment based on the current abnormal parameters or possible abnormal parameters when the current heat exchange unit has an abnormality; The calculation formula of the equipment abnormality coefficient is as follows: In the formula, P represents the equipment abnormality coefficient of the current heat exchanger unit; n0 represents the total number of operation-key parameter data; n1 represents the total number of current abnormal parameters; x i It is expressed as the absolute difference between the i-th abnormal parameter and the corresponding set safety parameter threshold, where i = 1, 2, 3, ..., n1; It is represented by the weight of the influence of the ith abnormal parameter on the abnormal degree of the equipment; n2 is represented by the total number of possible abnormal parameters at present; y j It is expressed as the absolute difference of the first parameter corresponding to the jth possible abnormal parameter, where j = 1, 2, 3, ..., n2; It is expressed as the average absolute difference of the corresponding first parameter of all possible abnormal parameters; σ j It is represented as the weight of the influence of the jth possible abnormal parameter on the abnormal degree of the equipment; e is represented as the natural base; Determining the equipment abnormality level according to the equipment abnormality coefficient; Using the currently existing abnormal parameters as matching conditions, obtain the abnormal maintenance strategy from the set abnormal maintenance list; Taking the currently existing possible abnormal parameters and the corresponding absolute difference of the first parameter as matching conditions, a possible abnormality prevention strategy is obtained from the set possible range-prevention list; Based on the currently existing abnormal parameters or possible abnormal parameters, and the corresponding abnormal maintenance strategy or possible abnormal prevention strategy, an equipment abnormality report is generated, and the equipment abnormality report is annotated with the equipment abnormality level and transmitted to the visualization module.

8. The intelligent heat exchanger control system according to claim 1, characterized in that: The visualization module comprises: Status visualization unit: used to display the relevant parameters of the heat exchange unit in real time using the real-time display block and to display the abnormal information of the equipment using the abnormal display block; Real-time display block: used to display the relevant parameters of the heat exchanger in real time in digital form in the set data display area of ​​the status visualization interface, and to use dynamic charts to display the change trend of the operating parameters of the heat exchanger within a preset time period; Abnormal display block: used to display the existing abnormal parameters or possible abnormal parameters and the corresponding abnormal maintenance strategy or possible abnormal prevention strategy in the set abnormal display area of ​​the status visualization interface according to the received equipment abnormality report, and notify the maintenance personnel to intervene through sound prompts; Remote monitoring unit: It is used for users to establish communication with the target cloud platform using smart devices, log in to the target cloud platform with username and password, and view device status and device abnormality information in real time on the status visualization interface.

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