Dynamic control method and device for balance adjustment constant-flow constant-pressure valve of internet of things

Abstract

The invention relates to a dynamic control method and device for a balance adjustment constant-current constant-pressure valve of the Internet of Things. The method comprises the steps that flow pressure monitoring data and current valve control data of a constant-flow and constant-pressure valve are obtained, and current flow pressure change distribution information is recognized based on the flow pressure monitoring data; on the basis of the current flow pressure change distribution information, regulation and control demand information of the constant-flow and constant-pressure valve is recognized through a flow pressure regulation strategy, and on the basis of the regulation and control demand information, a target regulation and control scheme of the constant-flow and constant-pressure valve is generated through a dynamic valve control stable regulation strategy; and on the basis of the current valve control data and the target control scheme, a current control process of the constant-current and constant-pressure valve is generated, and on the basis of the current control process of the constant-current and constant-pressure valve, balance dynamic adjustment processing is conducted on the constant-current and constant-pressure valve through a control alignment unit. By means of the method, the dynamic adjusting stability of the constant-flow constant-pressure valve can be improved.

Description

Technical Field

[0001] This application relates to the field of constant flow and constant pressure valve technology, and in particular to a dynamic control method and device for an IoT-based balanced regulating constant flow and constant pressure valve. Background Technology

[0002] A constant flow and constant pressure valve is a self-operated valve that integrates constant flow and constant pressure functions. Through its internal structural design, it maintains stable flow and pressure simultaneously during media flow. Its working principle is based on differential pressure control and flow path regulation. It keeps the media flow constant, unaffected by differential pressure fluctuations, while automatically adjusting the valve opening to maintain stable outlet pressure. However, when a constant flow and constant pressure valve is adjusted or its flow path is changed, fluctuations in flow and pressure often occur, resulting in poor balancing during regulation and affecting the valve's stable control performance. Therefore, improving the dynamic regulation stability of constant flow and constant pressure valves is a current research focus.

[0003] Existing technologies achieve smooth switching by keeping the flow channel area constant during flow path switching, thus avoiding pressure and flow fluctuations. However, this method is only applicable to flow path switching scenarios and cannot be applied to other adjustment scenarios of constant flow and constant pressure valves. Furthermore, it imposes significant limitations on practical applications, resulting in poor dynamic adjustment stability of constant flow and constant pressure valves. Summary of the Invention

[0004] Therefore, it is necessary to provide a dynamic control method and device for an IoT-based balanced regulating constant flow and constant pressure valve to address the aforementioned technical problems.

[0005] In a first aspect, this application provides a dynamic control method for an IoT-based balanced regulating constant flow and constant pressure valve, comprising: Acquire flow and pressure monitoring data, as well as the current valve control data of the constant flow and constant pressure valve, and identify the current flow and pressure change distribution information based on the flow and pressure monitoring data; Based on the current flow and pressure change distribution information, the control demand information of the constant flow and constant pressure valve is identified through the flow and pressure regulation strategy, and based on the control demand information, the target control scheme of the constant flow and constant pressure valve is generated through the dynamic valve control stability regulation strategy. Based on the current valve control data and the target control scheme, the current control process of the constant flow and constant pressure valve is generated, and based on the current control process of the constant flow and constant pressure valve, the constant flow and constant pressure valve is dynamically adjusted for balance through the control alignment unit.

[0006] Optionally, identifying the current flow pressure change distribution information based on the flow pressure monitoring data includes: The traffic pressure monitoring data is split into current pressure monitoring data and current traffic monitoring data. Based on the current pressure monitoring data and the current traffic monitoring data, current pressure change data and current traffic change data are generated through data processing strategies. Based on the current pressure change data and the current flow change data, a data fitting adjustment strategy is used to generate current pressure change distribution information and current flow change distribution information, and the current pressure change distribution information and the current flow change distribution information are used as the current flow pressure change distribution information.

[0007] Optionally, the step of identifying the control demand information of the constant flow and constant pressure valve based on the current flow and pressure change distribution information and through a flow and pressure regulation strategy includes: Identify each dynamic range of flow pressure change in the current flow pressure change distribution information, and for each dynamic range of flow pressure change, identify each range change parameter corresponding to the dynamic range of flow pressure change. Based on the range change parameters corresponding to the dynamic change range of flow and pressure, sub-control data of the constant flow and constant pressure valve is generated through the flow and pressure control network, and the sub-control data of each constant flow and constant pressure valve is used as the control requirement information of the constant flow and constant pressure valve.

[0008] Optionally, the step of generating a target control scheme for the constant flow and constant pressure valve based on the control demand information and through a dynamic valve control stabilization adjustment strategy includes: Based on the sub-control data corresponding to each of the aforementioned flow and pressure dynamic change ranges, control data change information of the constant flow and constant pressure valve is generated, and based on the control data change information, valve control data adjustment amount of each valve control type at each control adjustment point is identified. For each control point, based on the valve control data adjustment amount of each valve control type at the control point, and based on the valve control data adjustment amount of each valve control type, a sub-control scheme for each valve control type is generated through a valve control stability control network. Each of the valve control types is used as a sub-control scheme for the control point, and the sub-control schemes for each control point are sorted according to the node order of each control point to obtain the target control scheme for the constant flow and constant pressure valve.

[0009] Optionally, generating the current control process for the constant flow and constant pressure valve based on the current valve control data and the target control scheme includes: The current valve control data is split into current sub-valve control data for each valve control type, and the control time point of each control adjustment point is identified. Based on the control time points of each of the aforementioned control points, the first control point is selected, and based on the current flow pressure change distribution information, the flow data before the first control point and the pressure data before the first control point are identified. Based on the flow data before the first control adjustment point, the pressure data before the first control adjustment point, and the current sub-valve control data of each valve control type, a first adjustment scheme for each valve control type is generated; The first control scheme of each valve control type and the sub-control scheme of each control point are sorted according to the control time point of each control point to obtain the current control process of the constant flow and constant pressure valve.

[0010] Optionally, the current control process based on the constant flow and constant pressure valve, through the control alignment unit, performs a dynamic balance adjustment on the constant flow and constant pressure valve, including: The distance between the acquisition point of the flow and pressure monitoring data and the constant flow and constant pressure valve, as well as the generation time of the current control process, are obtained, and the control time interval value of the constant flow and constant pressure valve is calculated based on the distance value. Based on the generation time of the current control process and the control time interval of the constant flow and constant pressure valve, the adjustment start time of the constant flow and constant pressure valve is calculated, and the current control process is adjusted based on the adjustment start time to obtain the target control process. According to the target control process, the constant flow and constant pressure valve is subjected to dynamic balance adjustment.

[0011] Secondly, this application also provides an IoT-based dynamic control device for a constant flow and constant pressure valve, comprising: The acquisition module is used to acquire flow and pressure monitoring data and current valve control data of the constant flow and constant pressure valve, and to identify the current flow and pressure change distribution information based on the flow and pressure monitoring data. The generation module is used to identify the control demand information of the constant flow and constant pressure valve based on the current flow and pressure change distribution information and through the flow and pressure adjustment strategy, and to generate the target control scheme of the constant flow and constant pressure valve based on the control demand information and through the dynamic valve control stability adjustment strategy. The adjustment module is used to generate the current control process of the constant flow and constant pressure valve based on the current valve control data and the target control scheme, and to perform balanced dynamic adjustment processing on the constant flow and constant pressure valve through the adjustment alignment unit based on the current control process of the constant flow and constant pressure valve.

[0012] Optionally, the acquisition module is specifically used for: The traffic pressure monitoring data is split into current pressure monitoring data and current traffic monitoring data. Based on the current pressure monitoring data and the current traffic monitoring data, current pressure change data and current traffic change data are generated through data processing strategies. Based on the current pressure change data and the current flow change data, a data fitting adjustment strategy is used to generate current pressure change distribution information and current flow change distribution information, and the current pressure change distribution information and the current flow change distribution information are used as the current flow pressure change distribution information.

[0013] Optionally, the generation module is specifically used for: Identify each dynamic range of flow pressure change in the current flow pressure change distribution information, and for each dynamic range of flow pressure change, identify each range change parameter corresponding to the dynamic range of flow pressure change. Based on the range change parameters corresponding to the dynamic change range of flow and pressure, sub-control data of the constant flow and constant pressure valve is generated through the flow and pressure control network, and the sub-control data of each constant flow and constant pressure valve is used as the control requirement information of the constant flow and constant pressure valve.

[0014] Optionally, the generation module is specifically used for: Based on the sub-control data corresponding to each of the aforementioned flow and pressure dynamic change ranges, control data change information of the constant flow and constant pressure valve is generated, and based on the control data change information, valve control data adjustment amount of each valve control type at each control adjustment point is identified. For each control point, based on the valve control data adjustment amount of each valve control type at the control point, and based on the valve control data adjustment amount of each valve control type, a sub-control scheme for each valve control type is generated through a valve control stability control network. Each of the valve control types is used as a sub-control scheme for the control point, and the sub-control schemes for each control point are sorted according to the node order of each control point to obtain the target control scheme for the constant flow and constant pressure valve.

[0015] Optionally, the adjustment module is specifically used for: The current valve control data is split into current sub-valve control data for each valve control type, and the control time point of each control adjustment point is identified. Based on the control time points of each of the aforementioned control points, the first control point is selected, and based on the current flow pressure change distribution information, the flow data before the first control point and the pressure data before the first control point are identified. Based on the flow data before the first control adjustment point, the pressure data before the first control adjustment point, and the current sub-valve control data of each valve control type, a first adjustment scheme for each valve control type is generated; The first control scheme of each valve control type and the sub-control scheme of each control point are sorted according to the control time point of each control point to obtain the current control process of the constant flow and constant pressure valve.

[0016] Optionally, the adjustment module is specifically used for: The distance between the acquisition point of the flow and pressure monitoring data and the constant flow and constant pressure valve, as well as the generation time of the current control process, are obtained, and the control time interval value of the constant flow and constant pressure valve is calculated based on the distance value. Based on the generation time of the current control process and the control time interval of the constant flow and constant pressure valve, the adjustment start time of the constant flow and constant pressure valve is calculated, and the current control process is adjusted based on the adjustment start time to obtain the target control process. According to the target control process, the constant flow and constant pressure valve is subjected to dynamic balance adjustment.

[0017] Thirdly, this application provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described in any one of the first aspects.

[0018] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0019] Fifthly, this application provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the method described in any one of the first aspects.

[0020] The aforementioned IoT-based dynamic control method and apparatus for a constant flow and constant pressure valve involves acquiring flow and pressure monitoring data, as well as the current valve control data of the constant flow and constant pressure valve. Based on the flow and pressure monitoring data, it identifies the current flow and pressure change distribution information. Based on the current flow and pressure change distribution information, it identifies the control demand information of the constant flow and constant pressure valve through a flow and pressure regulation strategy. Based on the control demand information, it generates a target control scheme for the constant flow and constant pressure valve through a dynamic valve control stabilization regulation strategy. Based on the current valve control data and the target control scheme, it generates the current control process of the constant flow and constant pressure valve. Based on the current control process of the constant flow and constant pressure valve, it performs dynamic balance adjustment processing on the constant flow and constant pressure valve through a control alignment unit. This solution analyzes changes in flow and pressure using real-time collected flow monitoring data, enabling dynamic adjustment and generating a target control scheme for the constant flow and constant pressure valve. This allows for the prediction and generation of the valve's control process in advance. To ensure the stability of the generated control process, this solution employs a pre-designed dynamic valve control stabilization strategy. This strategy generates the control scheme for the constant flow and constant pressure valve and then combines it with the current valve control data to perform secondary steady-state control of the valve's current control process, effectively improving the stability of the valve's control. Finally, the solution incorporates a control alignment unit to precisely align the control time points of the constant flow and constant pressure valve, avoiding the impact of intelligent processing time on actual control and improving the accuracy of dynamic control. This comprehensively enhances the dynamic adjustment stability of the constant flow and constant pressure valve. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart illustrating the dynamic control method for an IoT-based balanced regulating constant current and constant pressure valve in one embodiment. Figure 2 This is a flowchart illustrating an example of dynamic control of an IoT-based balance regulating constant current and constant pressure valve in one embodiment. Figure 3 This is a structural block diagram of an IoT-based dynamic control device for a constant flow and constant pressure valve in one embodiment. Figure 4 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0024] It should be noted that the terms "first," "second," etc., used in this application can be used to describe various elements, but these elements are not limited by these terms. These terms are only used to distinguish the first element from the second element. The terms "comprising" and "having," and any variations thereof, used in this application, are intended to cover non-exclusive inclusion. The term "multiple" used in this application refers to two or more. The term "and / or" used in this application refers to one of the embodiments, or any combination of multiple embodiments.

[0025] The IoT-based dynamic control method for a constant flow and constant pressure valve, provided in this embodiment, can be applied to IoT-based systems for dynamic control of constant flow and constant pressure valves. This system can be used with terminals, including but not limited to various personal computers, laptops, and mid-range computers. The terminal analyzes changes in flow and pressure using real-time collected flow monitoring data, thereby dynamically adjusting and generating a target control scheme for the constant flow and constant pressure valve. This allows for advance prediction and generation of the valve's control process. To ensure the stability of the generated control process, this method uses a pre-designed dynamic valve control stabilization strategy to generate the control scheme for the constant flow and constant pressure valve. Then, combined with the current valve control data of the constant flow and constant pressure valve, a secondary steady-state control is performed on the current control process, effectively improving the stability of the valve's control. Finally, the control alignment unit designed in this method precisely aligns the control time points of the constant flow and constant pressure valve, avoiding the problem of actual control being affected by the intelligent processing time, and improving the accuracy of dynamic control of the constant flow and constant pressure valve. This comprehensively improves the dynamic adjustment stability of the constant flow and constant pressure valve.

[0026] In one exemplary embodiment, such as Figure 1 As shown, a dynamic control method for an IoT-based balanced regulating constant flow and constant pressure valve is provided. Taking the application of this method to a terminal as an example, the method includes the following steps S101 to S103. Wherein: Step S101: Obtain flow and pressure monitoring data and current valve control data of the constant flow and constant pressure valve, and identify the current flow and pressure change distribution information based on the flow and pressure monitoring data.

[0027] In this embodiment, the terminal collects flow monitoring data and pressure monitoring data in real time through a flow monitoring sensor and a pressure sensor installed at the fluid pipeline upstream of the constant flow and constant pressure valve, obtaining flow and pressure monitoring data. Then, the terminal obtains the control data of each valve control type fed back in real time by the constant flow and constant pressure valve. The distance between the sensor location and the constant flow and constant pressure valve is greater than the product of the time length for generating the current control process and the fluid flow rate. The sensor location can be the input end of the fluid pipeline where the constant flow and constant pressure valve is located.

[0028] The valve control type includes, but is not limited to, valve core opening control type and pressure compensation module control type. Then, the terminal identifies the current flow and pressure change distribution information based on the flow and pressure monitoring data. This flow and pressure change distribution information includes the current pressure change distribution information and the current flow change distribution information. The specific identification process will be explained in detail later.

[0029] Step S102: Based on the current flow and pressure change distribution information, the control demand information of the constant flow and constant pressure valve is identified through the flow and pressure regulation strategy. Based on the control demand information, the target control scheme of the constant flow and constant pressure valve is generated through the dynamic valve control stabilization regulation strategy.

[0030] In this embodiment, the terminal, based on the current flow and pressure variation distribution information, identifies the control demand information of the constant flow and constant pressure valve through a flow and pressure regulation strategy. Based on this control demand information, it generates a target control scheme for the constant flow and constant pressure valve through a dynamic valve control stabilization adjustment strategy. This flow and pressure regulation strategy generates the control data for the constant flow and constant pressure valve based on the current flow and pressure variation distribution information. This strategy is generated through the flow and pressure regulation network designed in this embodiment. This flow and pressure regulation network is an artificial neural network trained on a large amount of training data. The artificial neural network identifies the sub-control data of the constant flow and constant pressure valve by inputting the dynamic range of flow and pressure variation. This sub-control data includes the valve control data adjustment amount for each control valve type. The dynamic valve control stabilization adjustment strategy is used to stabilize the adjustment schemes for each valve type at control points between different dynamic ranges of flow and pressure variation. This adjustment scheme is used to perform gradient adjustment on each valve control type, thereby improving the control stability of each valve control type. The specific control process will be described in detail later.

[0031] Step S103: Based on the current valve control data and the target control scheme, generate the current control process of the constant flow and constant pressure valve, and based on the current control process of the constant flow and constant pressure valve, perform balanced dynamic adjustment processing on the constant flow and constant pressure valve through the control alignment unit.

[0032] In this embodiment, the terminal generates the current control process for the constant flow and constant pressure valve based on the current valve control data and the target control scheme. Based on this current control process, the terminal performs balanced dynamic adjustment of the constant flow and constant pressure valve through a control alignment unit. This current control process includes sub-adjustment schemes for the constant flow and constant pressure valve at each control time point. This is used for intelligent control of the constant flow and constant pressure valve's adjustment process. The control alignment unit is used to align the control time points of the constant flow and constant pressure valve, ensuring the immediacy and accuracy of the control.

[0033] Based on the above scheme, by analyzing changes in flow and pressure through real-time collected flow monitoring data, dynamic adjustments are made to generate a target control scheme for the constant flow and constant pressure valve. This allows for the prediction and generation of the control process for the constant flow and constant pressure valve in advance. To ensure the stability of the generated control process, this scheme generates a control scheme for the constant flow and constant pressure valve through a pre-designed dynamic valve control stabilization adjustment strategy. Then, combined with the current valve control data of the constant flow and constant pressure valve, a secondary steady-state control is performed on the current control process of the constant flow and constant pressure valve, effectively improving the control stability of the constant flow and constant pressure valve. Finally, by combining the control alignment unit designed in this scheme, the control time points of the constant flow and constant pressure valve are precisely aligned, avoiding the problem of actual control being affected by the intelligent processing time, and improving the accuracy of dynamic control of the constant flow and constant pressure valve. Thus, the dynamic adjustment stability of the constant flow and constant pressure valve is comprehensively improved.

[0034] Optionally, based on traffic pressure monitoring data, identify the current traffic pressure change distribution information, including: splitting the traffic monitoring data into current pressure monitoring data and current traffic monitoring data, and generating current pressure change data and current traffic change data based on the current pressure monitoring data and current traffic monitoring data through a data processing strategy; generating current pressure change distribution information and current traffic change distribution information based on the current pressure change data and current traffic change data through a data fitting and adjustment strategy, and using the current pressure change distribution information and current traffic change distribution information as the current traffic pressure change distribution information.

[0035] In this embodiment, the terminal splits the flow monitoring data into current pressure monitoring data and current flow monitoring data. Based on the current pressure monitoring data and current flow monitoring data, a data processing strategy is used to generate current pressure change data and current flow change data. Since there is considerable data noise in the fluid pipeline, the data processing strategy designed in this solution involves processing the acquired current pressure monitoring data and current flow monitoring data through data cleaning, data standardization, and noise reduction before identifying the pressure change data and flow change data, thus obtaining more accurate current pressure change data and current flow change data.

[0036] Then, based on the current pressure change data and the current flow rate change data, the terminal generates current pressure change distribution information and current flow rate change distribution information through a data fitting adjustment strategy, and uses the current pressure change distribution information and current flow rate change distribution information as the current flow rate and pressure change distribution information. Specifically, the data fitting adjustment strategy involves using curve fitting technology to linearly fit the discrete and irregularly changing flow rate and pressure change data to obtain the current pressure change distribution information and current flow rate change distribution information.

[0037] Based on the above scheme, by processing and fitting the monitoring data, the accuracy of the generated flow pressure change distribution information is ensured, and the adjustment effect on interference data and influencing data in the monitoring data is improved.

[0038] Optionally, based on the current flow and pressure change distribution information, the control demand information of the constant flow and constant pressure valve is identified through a flow and pressure regulation strategy. This includes: identifying each dynamic change range of flow and pressure in the current flow and pressure change distribution information, and identifying the range change parameters corresponding to each dynamic change range of flow and pressure; based on the range change parameters corresponding to each dynamic change range of flow and pressure, generating sub-control data of the constant flow and constant pressure valve through a flow and pressure regulation network, and using the sub-control data of each constant flow and constant pressure valve as the control demand information of the constant flow and constant pressure valve.

[0039] In this embodiment, the terminal identifies the dynamic change ranges of traffic pressure in the current traffic pressure change distribution information, and for each dynamic change range, identifies the corresponding range change parameters. The identification method for the dynamic change range of traffic pressure is that the terminal filters each continuously changing distribution range in the current traffic pressure change distribution information as the dynamic change range of traffic pressure. These range change parameters include, but are not limited to, change trend parameters, change fluctuation range parameters, and change range trend parameters. The terminal identifies the range change parameters corresponding to the dynamic change range of traffic pressure by using a linear feature extraction network of a convolutional neural network to extract the linear change features of the traffic change curve and pressure change curve in each dynamic change range of traffic pressure.

[0040] Next, based on the parameters corresponding to the dynamic changes in flow and pressure, the terminal generates sub-control data for the constant flow and constant pressure valve through a flow and pressure control network. This flow and pressure control network is a classifier neural network used to identify the valve control data adjustment amount for each valve control type within each dynamic flow and pressure change range by combining the parameters for each range. This classifier neural network is obtained by training an initial classifier neural network using different sample range parameters and sample valve control data adjustment amounts for each valve control type. By adjusting the valve control data for each valve control type within the aforementioned dynamic flow and pressure change ranges, it is ensured that when fluid flows through the constant flow and constant pressure valve, the change ranges of fluid flow and pressure are below a preset change range threshold on the terminal. This change range threshold is the standard fluctuation range for pressure and fluid flow set by the operator for the constant flow and constant pressure valve on the terminal.

[0041] Finally, the terminal uses the sub-control data of each constant flow and constant pressure valve as the control demand information for the constant flow and constant pressure valve.

[0042] Based on the above scheme, this scheme first identifies the dynamic change range of each flow and pressure in the current flow and pressure change distribution information, and then accurately identifies the control range of the constant flow and constant pressure valve according to each dynamic change range of flow and pressure, thereby improving the stability of the flow and pressure of the constant flow and constant pressure valve after control.

[0043] Optionally, based on the control demand information, a target control scheme for the constant flow and constant pressure valve is generated through a dynamic valve control stabilization adjustment strategy. This includes: generating control data change information for the constant flow and constant pressure valve based on the sub-control data corresponding to the dynamic change range of each flow and pressure, and identifying the valve control data adjustment amount for each valve control type at each control point based on the control data change information; for each control point, generating sub-control schemes for each valve control type based on the valve control data adjustment amount for each valve control type through a valve control stabilization adjustment network; using the sub-control schemes for each valve control type as sub-control schemes for the control point, and sorting the sub-control schemes for each control point according to the node order of each control point to obtain the target control scheme for the constant flow and constant pressure valve.

[0044] In this embodiment, the terminal generates control data change information for the constant flow and constant pressure valve based on the sub-control data corresponding to each dynamic flow and pressure change range. Based on this control data change information, it identifies the valve control data adjustment amount for each valve control type at each control point. The control data change information for the constant flow and constant pressure valve is obtained by arranging the sub-control data of the constant flow and constant pressure valve corresponding to each dynamic flow and pressure change range according to their sorting position in the current flow and pressure change distribution information. Each control point is a connection point between two sub-control data points. This connection point characterizes the control data change information of the constant flow and constant pressure valve between the two sub-control data points. That is, when the constant flow and constant pressure valve adjusts between two sub-control data points, it needs to adjust the preceding sub-control data to the following sub-control data. During this adjustment process, the constant flow and constant pressure valve needs to actively adjust to maintain the stability of the flow and pressure in the fluid pipeline where the constant flow and constant pressure valve is located. The valve control data adjustment amount for each valve control type at each control point is the sub-data change information for each valve control type in the data change information between the sub-control data at each control point.

[0045] For each control point, the terminal adjusts the valve control data for each valve control type based on the adjustment amount at that point. Then, based on these adjustment amounts, it generates sub-control schemes for each valve control type through a valve control stability control network. This valve control stability control network is a valve control steady-state control model based on an AI (Artificial Intelligence) intelligent model. Specifically, the terminal presets a fluid pipeline model. Then, based on the valve control data for each valve control type, it generates initial control schemes for each valve control type through the AI ​​intelligent model. Based on this fluid pipeline model and the initial control schemes for each valve control type, the terminal simulates the valve control process of the fluid pipeline model using digital twin technology, outputting the simulated flow rate data change information and the simulated pressure data change information. Finally, the terminal calculates the flow rate data deviation value and the pressure data deviation value using preset standard flow rate data and standard pressure data. Then, when the above deviation value is greater than the deviation threshold preset in the terminal, the terminal adjusts the valve control steady-state regulation model based on the above deviation value, iteratively executes the valve control data adjustment amount based on each valve control type, and generates the initial regulation scheme for each valve control type through the AI ​​intelligent model until the deviation value of the fir tree is not greater than the deviation threshold preset in the terminal. Then, the terminal uses the initial sub-regulation scheme obtained in the last iteration as the sub-regulation scheme.

[0046] Then, the terminal takes the sub-control schemes of each valve control type as the sub-control schemes of the control point, and sorts the sub-control schemes of each control point according to the node order of each control point to obtain the target control scheme of the constant flow and constant pressure valve.

[0047] Based on the above scheme, the valve-controlled stabilization network designed in this scheme generates sub-control schemes for different control points, thereby improving the stabilization effect at different control points.

[0048] Optionally, based on the current valve control data and the target control scheme, the current control process of the constant flow and constant pressure valve is generated, including: splitting the current valve control data into current sub-valve control data for each valve control type, and identifying the control time point of each control adjustment point; based on the control time point of each control adjustment point, selecting the first control adjustment point, and based on the current flow and pressure change distribution information, identifying the flow data and pressure data before the first control adjustment point; based on the flow data and pressure data before the first control adjustment point, and the current sub-valve control data of each valve control type, generating the first control scheme for each valve control type; sorting the first control scheme for each valve control type and the sub-control schemes for each control adjustment point according to the control time point of each control adjustment point to obtain the current control process of the constant flow and constant pressure valve.

[0049] In this embodiment, the terminal breaks down the current valve control data into sub-valve control data for each valve control type and identifies the control time point for each control adjustment point. Then, based on the control time point of each control adjustment point, the terminal selects the first and first control adjustment point, and based on the current flow and pressure change distribution information, identifies the flow data and pressure data preceding the first and first control adjustment point. The first and first control adjustment point is the control adjustment point used first for constant flow and constant pressure valve regulation among all control adjustment points.

[0050] Then, based on the flow rate data before the first control adjustment point, the pressure data before the first control adjustment point, and the current sub-valve control data for each valve control type, the terminal generates a first control scheme for each valve control type. This first control scheme is generated in the same way as the control schemes for each control adjustment point, and will not be described in detail here. The terminal sorts the first control schemes for each valve control type and the sub-control schemes for each control adjustment point according to the control time point of each control adjustment point to obtain the current control process for the constant flow and constant pressure valve.

[0051] Based on the above scheme, by combining the current valve control data, the stability of the initial adjustment process of the constant flow and constant pressure valve is adjusted again, thereby improving the stability of the entire process of fluid regulation.

[0052] Optionally, based on the current control process of the constant flow and constant pressure valve, the constant flow and constant pressure valve is dynamically adjusted for balance through the control alignment unit. This includes: acquiring the distance between the acquisition point of the flow and pressure monitoring data and the constant flow and constant pressure valve, as well as the generation duration of the current control process, and calculating the control time interval value of the constant flow and constant pressure valve based on the distance value; calculating the adjustment start time point of the constant flow and constant pressure valve based on the generation duration of the current control process and the control time interval value of the constant flow and constant pressure valve, and adjusting the current control process based on the adjustment start time point to obtain the target control process; and performing dynamic adjustment for balance of the constant flow and constant pressure valve according to the target control process.

[0053] In this embodiment, the terminal acquires the distance between the acquisition point of the flow and pressure monitoring data and the constant flow and constant pressure valve, as well as the generation duration of the current control process, and calculates the control time interval value of the constant flow and constant pressure valve based on the distance value. Specifically, the calculation formula is: Time interval value = Distance value / Preset fluid flow rate value.

[0054] The terminal calculates the adjustment start time of the constant flow and constant pressure valve based on the generation time of the current control process and the control time interval value of the constant flow and constant pressure valve. Based on the adjustment start time, the terminal adjusts the current control process to obtain the target control process. The adjustment start time is calculated as: Adjustment start time = Current time + (Control time interval value - Generation time). The adjustment scheme for the current control process (i.e., the control process of the control alignment unit) involves identifying the adjustment time of each control point in the current control process. The terminal then uses this adjustment start time as the start time of the first control scheme. Following the order of the current flow and pressure change distribution information, the terminal adjusts the adjustment time of each control point to obtain the new adjustment time of each control node, thus obtaining the target control process. Finally, the terminal performs dynamic balance adjustment on the constant flow and constant pressure valve according to the target control process.

[0055] Based on the above scheme, by adjusting the alignment unit, the adjustment time point of the constant flow and constant pressure valve is aligned, ensuring the timely adjustment of the constant flow and constant pressure valve, thereby indirectly improving the accuracy of fluid control.

[0056] This application also provides an example of dynamic control of an IoT-based balanced regulating constant flow and constant pressure valve, such as... Figure 2 As shown, the specific processing procedure includes the following steps: Step S201: Obtain flow and pressure monitoring data, as well as the current valve control data of the constant flow and constant pressure valve.

[0057] Step S202: The traffic pressure monitoring data is split into current pressure monitoring data and current traffic monitoring data. Based on the current pressure monitoring data and current traffic monitoring data, current pressure change data and current traffic change data are generated through data processing strategies.

[0058] Step S203: Based on the current pressure change data and the current flow change data, the current pressure change distribution information and the current flow change distribution information are generated through a data fitting adjustment strategy, and the current pressure change distribution information and the current flow change distribution information are used as the current flow pressure change distribution information.

[0059] Step S204: Identify the dynamic change range of each flow pressure in the current flow pressure change distribution information, and for each dynamic change range of flow pressure, identify the range change parameters corresponding to the dynamic change range of flow pressure.

[0060] Step S205: Based on the range change parameters corresponding to the dynamic change range of flow and pressure, sub-control data of constant flow and constant pressure valves are generated through the flow and pressure control network, and the sub-control data of each constant flow and constant pressure valve is used as the control demand information of constant flow and constant pressure valves.

[0061] Step S206: Based on the sub-control data corresponding to the dynamic change range of each flow and pressure, generate control data change information for the constant flow and constant pressure valve, and based on the control data change information, identify the valve control data adjustment amount of each valve control type at each control adjustment point.

[0062] Step S207: For each control point, based on the valve control data adjustment amount of each valve control type at the control point, and based on the valve control data adjustment amount of each valve control type, generate a sub-control scheme for each valve control type through the valve control stable control network.

[0063] Step S208: Take the sub-control schemes of each valve control type as the sub-control schemes of the control point, and sort the sub-control schemes of each control point according to the node order of each control point to obtain the target control scheme of the constant flow and constant pressure valve.

[0064] Step S209: The current valve control data is split into current sub-valve control data for each valve control type, and the control time point of each control adjustment point is identified.

[0065] Step S210: Based on the control time points of each control point, select the first control point, and based on the current flow pressure change distribution information, identify the flow data before the first control point and the pressure data before the first control point.

[0066] Step S211: Based on the flow data before the first control adjustment point, the pressure data before the first control adjustment point, and the current sub-valve control data of each valve control type, generate the first control scheme for each valve control type.

[0067] Step S212: Sort the first control scheme of each valve control type and the sub-control scheme of each control point according to the control time point of each control point to obtain the current control process of the constant flow and constant pressure valve.

[0068] Step S213: Obtain the distance between the acquisition location of the flow and pressure monitoring data and the constant flow and constant pressure valve, as well as the generation time of the current control process, and calculate the control time interval value of the constant flow and constant pressure valve based on the distance value.

[0069] Step S214: Based on the generation time of the current control process and the control time interval value of the constant flow and constant pressure valve, calculate the adjustment start time point of the constant flow and constant pressure valve, and adjust the current control process based on the adjustment start time point to obtain the target control process.

[0070] Step S215: Perform dynamic balance adjustment on the constant flow and constant pressure valve according to the target control process.

[0071] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages in other steps. It is understood that the steps in different embodiments can be freely combined as needed, and all non-contradictory solutions formed by such combinations are within the scope of protection of this application.

[0072] Based on the same inventive concept, this application also provides an IoT-based dynamic control device for implementing the aforementioned IoT-based dynamic control method for a constant flow and constant pressure valve. The solution provided by this device is similar to the solution described in the above method. Therefore, the specific limitations of one or more IoT-based dynamic control device embodiments provided below can be found in the limitations of the IoT-based dynamic control method for a constant flow and constant pressure valve described above, and will not be repeated here.

[0073] In one exemplary embodiment, such as Figure 3 As shown, an IoT-based dynamic control device for a constant flow and constant pressure valve is provided, comprising: an acquisition module 310, a generation module 320, and an adjustment module 330, wherein: The acquisition module 310 is used to acquire flow and pressure monitoring data and current valve control data of the constant flow and constant pressure valve, and to identify the current flow and pressure change distribution information based on the flow and pressure monitoring data. The generation module 320 is used to identify the control demand information of the constant flow and constant pressure valve based on the current flow and pressure change distribution information and through the flow and pressure adjustment strategy, and to generate the target control scheme of the constant flow and constant pressure valve based on the control demand information and through the dynamic valve control stability adjustment strategy. The adjustment module 330 is used to generate the current control process of the constant flow and constant pressure valve based on the current valve control data and the target control scheme, and to perform balanced dynamic adjustment processing on the constant flow and constant pressure valve through the adjustment alignment unit based on the current control process of the constant flow and constant pressure valve.

[0074] Optionally, the acquisition module 310 is specifically used for: The traffic pressure monitoring data is split into current pressure monitoring data and current traffic monitoring data. Based on the current pressure monitoring data and the current traffic monitoring data, current pressure change data and current traffic change data are generated through data processing strategies. Based on the current pressure change data and the current flow change data, a data fitting adjustment strategy is used to generate current pressure change distribution information and current flow change distribution information, and the current pressure change distribution information and the current flow change distribution information are used as the current flow pressure change distribution information.

[0075] Optionally, the generation module 320 is specifically used for: Identify each dynamic range of flow pressure change in the current flow pressure change distribution information, and for each dynamic range of flow pressure change, identify each range change parameter corresponding to the dynamic range of flow pressure change. Based on the range change parameters corresponding to the dynamic change range of flow and pressure, sub-control data of the constant flow and constant pressure valve is generated through the flow and pressure control network, and the sub-control data of each constant flow and constant pressure valve is used as the control requirement information of the constant flow and constant pressure valve.

[0076] Optionally, the generation module 320 is specifically used for: Based on the sub-control data corresponding to each of the aforementioned flow and pressure dynamic change ranges, control data change information of the constant flow and constant pressure valve is generated, and based on the control data change information, valve control data adjustment amount of each valve control type at each control adjustment point is identified. For each control point, based on the valve control data adjustment amount of each valve control type at the control point, and based on the valve control data adjustment amount of each valve control type, a sub-control scheme for each valve control type is generated through a valve control stability control network. Each of the valve control types is used as a sub-control scheme for the control point, and the sub-control schemes for each control point are sorted according to the node order of each control point to obtain the target control scheme for the constant flow and constant pressure valve.

[0077] Optionally, the adjustment module 330 is specifically used for: The current valve control data is split into current sub-valve control data for each valve control type, and the control time point of each control adjustment point is identified. Based on the control time points of each of the aforementioned control points, the first control point is selected, and based on the current flow pressure change distribution information, the flow data before the first control point and the pressure data before the first control point are identified. Based on the flow data before the first control adjustment point, the pressure data before the first control adjustment point, and the current sub-valve control data of each valve control type, a first adjustment scheme for each valve control type is generated; The first control scheme of each valve control type and the sub-control scheme of each control point are sorted according to the control time point of each control point to obtain the current control process of the constant flow and constant pressure valve.

[0078] Optionally, the adjustment module 330 is specifically used for: The distance between the acquisition point of the flow and pressure monitoring data and the constant flow and constant pressure valve, as well as the generation time of the current control process, are obtained, and the control time interval value of the constant flow and constant pressure valve is calculated based on the distance value. Based on the generation time of the current control process and the control time interval of the constant flow and constant pressure valve, the adjustment start time of the constant flow and constant pressure valve is calculated, and the current control process is adjusted based on the adjustment start time to obtain the target control process. According to the target control process, the constant flow and constant pressure valve is subjected to dynamic balance adjustment.

[0079] Each module in the aforementioned IoT-based dynamic control device for balancing and regulating constant flow and pressure valves can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0080] In one exemplary embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 4As shown, the computer device includes a processor, memory, input / output interfaces, a communication interface, a display unit, and an input device. The processor, memory, and input / output interfaces are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interfaces. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The input / output interfaces are used for exchanging information between the processor and external devices. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, Near Field Communication (NFC), or other technologies. When the computer program is executed by the processor, it implements a dynamic control method for a constant current and constant pressure valve in the Internet of Things (IoT) system. The display unit is used to form a visually visible image and can be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0081] Those skilled in the art will understand that Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0082] In one exemplary embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, the processor executing the computer program to implement the steps of a beer warehouse inventory optimization method.

[0083] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of a beer warehouse inventory optimization method.

[0084] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of a beer warehouse inventory optimization method.

[0085] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0086] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0087] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0088] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A dynamic control method of an Internet of Things balancing regulating constant current constant voltage valve, characterized in that, The method comprises: acquiring flow pressure monitoring data and current valve control data of the constant flow and pressure valve, and identifying current flow pressure change distribution information based on the flow pressure monitoring data; based on the current flow pressure change distribution information, identifying the control requirement information of the constant flow and pressure valve through a flow pressure adjustment strategy, and generating a target control scheme of the constant flow and pressure valve through a dynamic valve control stable adjustment strategy based on the control requirement information; based on the current valve control data and the target control scheme, generating a current control process of the constant flow and pressure valve, and performing balanced dynamic adjustment processing on the constant flow and pressure valve through a control alignment unit based on the current control process of the constant flow and pressure valve.

2. The method of claim 1, wherein, The method comprises: splitting the flow pressure monitoring data into current pressure monitoring data and current flow monitoring data, and generating current pressure change data and current flow change data through a data processing strategy based on the current pressure monitoring data and the current flow monitoring data; based on the current pressure change data and the current flow change data, generating current pressure change distribution information and current flow change distribution information through a data fitting adjustment strategy, and taking the current pressure change distribution information and the current flow change distribution information as the current flow pressure change distribution information.

3. The method of claim 1, wherein, The method comprises: identifying each flow pressure dynamic change range in the current flow pressure change distribution information, and identifying each range change parameter corresponding to the flow pressure dynamic change range for each flow pressure dynamic change range; based on each range change parameter corresponding to the flow pressure dynamic change range, generating sub-control data of the constant flow and pressure valve through a flow pressure control network, and taking each sub-control data of the constant flow and pressure valve as the control requirement information of the constant flow and pressure valve.

4. The method of claim 3, wherein, The method comprises: based on the sub-control data corresponding to each flow pressure dynamic change range, generating control data change information of the constant flow and pressure valve, and identifying the valve control data adjustment amount of each valve control type of each control node based on the control data change information; for each control node, based on the valve control data adjustment amount of each valve control type of the control node, and based on the valve control data adjustment amount of each valve control type, generating a sub-adjustment scheme of each valve control type through a valve control stable adjustment network; taking each sub-adjustment scheme of each valve control type as a sub-control scheme of each control node, and sorting each sub-control scheme of each control node according to the node order of each control node to obtain the target control scheme of the constant flow and pressure valve.

5. The method of claim 4, wherein, The generating, based on the current valve control data and the target regulation scheme, of a current regulation process of the constant-flow constant-pressure valve comprises: splitting the current valve control data into current sub-valve control data of each valve regulation type, and identifying a regulation time point of each regulation node; based on the regulation time point of each regulation node, screening a first regulation node, and based on the current flow pressure change distribution information, identifying flow data before the first regulation node and pressure data before the first regulation node; based on the flow data before the first regulation node, the pressure data before the first regulation node, and the current sub-valve control data of each valve regulation type, generating a first adjustment scheme of each valve regulation type; sorting the first adjustment scheme of each valve regulation type and the sub-regulation scheme of each regulation node according to the regulation time point of each regulation node to obtain the current regulation process of the constant-flow constant-pressure valve.

6. The method of claim 1, wherein, The balancing dynamic adjustment processing of the constant-flow constant-pressure valve based on the current regulation process of the constant-flow constant-pressure valve through a regulation alignment unit comprises: obtaining a distance value between the acquisition position point of the flow pressure monitoring data and the constant-flow constant-pressure valve, and a generation time length of the current regulation process, and based on the distance value, calculating a regulation time interval value of the constant-flow constant-pressure valve; based on the generation time length of the current regulation process and the regulation time interval value of the constant-flow constant-pressure valve, calculating an adjustment start time point of the constant-flow constant-pressure valve, and based on the adjustment start time point, adjusting the current regulation process to obtain a target regulation process; performing balancing dynamic adjustment processing on the constant-flow constant-pressure valve according to the target regulation process.

7. A dynamic control device of Internet of Things balance adjustment constant current constant voltage valve, characterized in that, The device comprises: an acquisition module for acquiring flow pressure monitoring data and current valve control data of a constant-flow constant-pressure valve, and based on the flow pressure monitoring data, identifying current flow pressure change distribution information; a generation module for identifying regulation demand information of the constant-flow constant-pressure valve through a flow pressure adjustment strategy based on the current flow pressure change distribution information, and generating a target regulation scheme of the constant-flow constant-pressure valve through a dynamic valve control stable adjustment strategy based on the regulation demand information; an adjustment module for generating a current regulation process of the constant-flow constant-pressure valve based on the current valve control data and the target regulation scheme, and performing balancing dynamic adjustment processing on the constant-flow constant-pressure valve through a regulation alignment unit based on the current regulation process of the constant-flow constant-pressure valve.

8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to implement the steps of the method of any one of claims 1 to 6.

9. A computer readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 6.

10. A computer program product comprising a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the method of any one of claims 1 to 6.

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