A control method and system for an electrically powered valve

Abstract

This invention belongs to the field of electric valve technology and provides a control method and system for an electric valve. The method includes: acquiring real-time data and target data. The real-time data includes real-time temperature values ​​on the return water pipe, real-time pressure values ​​on the supply water pipe, real-time pressure values ​​on the return water pipe, real-time flow rates on the supply water pipe, and real-time flow rates on the return water pipe in a heating system; comparing and analyzing the real-time data with the target data to calculate a control command. The control command includes controlling the opening degree of the electric valve to bring the real-time data closer to the target data. This invention detects water temperature, water pressure, and flow rate by installing temperature sensors, pressure sensors, and flow meters on the pipeline, and analyzes the monitored water temperature, water pressure, and flow rate with target values. Based on the analysis results, the opening degree of the electric valve is adjusted. This method allows for real-time and rapid temperature control, improving the consumer experience.

Description

Technical Field

[0001] This invention relates to the field of electric valve technology, and more specifically, to a control method and system for an electric valve. Background Technology

[0002] With the continuous improvement of living standards, consumers are paying more and more attention to comfort during consumption. In the heating system, consumers have high requirements for water temperature. Too cold or too hot will affect the consumer experience. Therefore, it is particularly important to quickly adjust the water temperature to the target temperature. In addition, the normal operation of the water supply pipeline should be ensured in the entire heating system to avoid water supply failure. Summary of the Invention

[0003] The purpose of this invention is to provide a control method and system for an electric valve to improve the above-mentioned problems.

[0004] To achieve the above objectives, the embodiments of this application provide the following technical solutions:

[0005] On one hand, embodiments of this application provide a control method for an electric valve, the method comprising:

[0006] Acquire real-time data and target data. The real-time data includes the real-time temperature value on the return water pipe, the real-time pressure value on the supply water pipe, the real-time pressure value on the return water pipe, the real-time flow rate value on the supply water pipe, and the real-time flow rate value on the return water pipe in the heating system. The target data includes the target temperature value, the target pressure difference value, and the target flow rate value.

[0007] The real-time data is compared and analyzed with the target data to calculate a control command. The control command includes controlling the opening degree of the electric valve to make the real-time data move closer to the target data.

[0008] Secondly, embodiments of this application provide a control system for an electric valve, the system including an acquisition module and a control module.

[0009] The first acquisition module is used to acquire real-time data and target data. The real-time data includes the real-time temperature value on the return water pipe, the real-time pressure value on the supply water pipe, the real-time pressure value on the return water pipe, the real-time flow rate value on the supply water pipe, and the real-time flow rate value on the return water pipe in the heating system. The target data includes the target temperature value, the target pressure difference value, and the target flow rate value.

[0010] The control module is used to compare and analyze the real-time data with the target data, and calculate control commands. The control commands include controlling the opening degree of the electric valve to make the real-time data move closer to the target data.

[0011] Thirdly, embodiments of this application provide a readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described electric valve control method.

[0012] The beneficial effects of this invention are as follows:

[0013] 1. This invention detects water temperature, water pressure, and flow rate by installing temperature sensors, pressure sensors, and flow meters on the pipeline. The monitored water temperature, water pressure, and flow rate are analyzed against target values, and the opening degree of the electric valve is adjusted based on the analysis results. This method enables real-time and rapid temperature control, improving the consumer experience.

[0014] 2. The present invention also monitors the temperature of the water supply pipeline by using historical temperatures to predict the temperature in the future. This method allows for real-time monitoring of the pipeline's operating status to prevent pipeline malfunctions from affecting the water supply.

[0015] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing embodiments of the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description, claims, and drawings. Attached Figure Description

[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the control method for the electric valve described in this embodiment of the invention;

[0018] Figure 2 This is a schematic diagram of the control system structure of the electric valve described in this embodiment of the invention. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0020] It should be noted that similar reference numerals or letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0021] Example 1

[0022] like Figure 1 As shown, this embodiment provides a control method for an electric valve, which includes steps S1 and S2.

[0023] Step S1: Obtain real-time data and target data. The real-time data includes the real-time temperature value on the return water pipe, the real-time pressure value on the supply water pipe, the real-time pressure value on the return water pipe, the real-time flow rate value on the supply water pipe, and the real-time flow rate value on the return water pipe in the heating system. The target data includes the target temperature value, the target pressure difference value, and the target flow rate value.

[0024] In this step, the real-time temperature value on the return water pipe is collected by a temperature sensor installed on the return water pipe; the real-time pressure value on the supply water pipe is collected by a pressure sensor installed on the supply water pipe; the real-time pressure value on the return water pipe is collected by a pressure sensor installed on the return water pipe; the real-time flow rate value on the supply water pipe is collected by a flow meter installed on the supply water pipe; the real-time flow rate value on the return water pipe is collected by a flow meter installed on the return water pipe; the target data is uploaded by the staff, and the specific values ​​can be customized according to the requirements.

[0025] Step S2: Compare and analyze the real-time data with the target data to calculate a control command. The control command includes controlling the opening degree of the electric valve to make the real-time data move closer to the target data.

[0026] The specific implementation steps of this step include steps S21, S22 and S23;

[0027] Step S21: Compare the real-time temperature value with the target temperature value. If the real-time temperature value is greater than the target temperature value, send a first control command. The first control command includes a command to control the electric valve to reduce its opening. If the real-time temperature value is less than the target temperature value, send a second control command. The second control command includes a command to control the electric valve to increase its opening.

[0028] In a heating system, the return water temperature is linearly proportional to the unit temperature. Therefore, by controlling the return water temperature of the heating unit, the temperature control function of the heating unit is achieved. An external PT1000 temperature sensor is connected to the electric valve, which is installed on the return water pipe. The electric valve monitors the return water temperature in real time and compares it with the set return water temperature value. When the return water temperature exceeds the set value, the electric valve reduces its opening, thus reducing the hot water flow and lowering the unit temperature. Conversely, when the return water temperature is lower than the set value, the electric valve increases its opening, thus increasing the hot water flow and raising the unit temperature. To reduce the frequency of valve operation and ensure the stability of the heating network, relevant proportional-integral parameters can be set via local Bluetooth and a remote system during return water temperature control, ensuring stable and energy-efficient system operation.

[0029] Step S22: Calculate the difference between the real-time pressure value on the water supply pipe and the real-time pressure value on the return pipe to obtain the difference result; compare the difference result with the pressure difference target value; if the difference result is greater than the pressure difference target value, send a third control command, which includes a command to control the electric valve to reduce its opening; if the difference result is less than the pressure difference target value, send a fourth control command, which includes a command to control the electric valve to increase its opening.

[0030] In a heating system, the pressure difference between the supply and return water is linearly proportional to the unit's temperature. Therefore, by controlling the supply and return water pressure difference, the temperature of the heating unit can be controlled. An electric valve is connected to both a supply water pressure sensor and a return water pressure sensor. The supply water pressure sensor is installed on the heating supply pipe, and the return water pressure sensor is installed on the heating return pipe. The electric valve monitors and calculates the supply and return water pressure difference in real time and compares it with the set pressure difference value. When the pressure difference exceeds the set value, the electric valve reduces its opening, thus reducing the hot water flow and lowering the unit's temperature. Conversely, when the pressure difference is below the set value, the electric valve increases its opening, thus increasing the hot water flow and raising the unit's temperature. To reduce the frequency of valve operation and ensure the stability of the heating network, relevant proportional-integral parameters can be set via local Bluetooth and a remote system during pressure difference control, ensuring stable and energy-efficient system operation.

[0031] Step S23: Compare the real-time flow rate on the water supply pipe and the real-time flow rate on the return pipe with the target flow rate. If the real-time flow rate on the water supply pipe or the real-time flow rate on the return pipe is greater than the target flow rate, send a fifth control command, which includes a command to control the electric valve to reduce its opening. If the real-time flow rate on the water supply pipe or the real-time flow rate on the return pipe is less than the target flow rate, send a sixth control command, which includes a command to control the electric valve to increase its opening.

[0032] In a heating system, the water supply flow rate is linearly proportional to the unit temperature. Therefore, by controlling the flow rate of the heating unit, the temperature of the heating unit can be controlled. An electric valve is connected to an external flow meter, which is installed on the heating supply and return water pipes. The electric valve reads the instantaneous flow rate of the flow meter in real time via RS485 and compares it with the set flow rate value. When the flow rate exceeds the set value, the electric valve reduces its opening, thus reducing the hot water flow and lowering the unit temperature. Conversely, when the flow rate is lower than the set value, the electric valve increases its opening, thus increasing the hot water flow and raising the unit temperature. To reduce the frequency of valve operation and ensure the stability of the heating network, relevant proportional-integral parameters can be set via local Bluetooth and a remote system during flow control regulation, ensuring stable and energy-efficient system operation.

[0033] In addition to regulating the opening of the electric valve, this method also monitors the water supply pipe based on its surface temperature, considering that the temperature of the water pipe is an important indicator for its normal operation. Too high or too low a temperature may damage the water pipe. This is to prevent pipe failures from affecting the water supply. The specific method includes steps S3 and S4.

[0034] Step S3: Obtain the surface temperature data of the water supply pipe in the heating system during a preset historical period. Input each surface temperature data into a pre-trained variational autoencoder to obtain the predicted value corresponding to each surface temperature data. Calculate the difference between each surface temperature data and its corresponding predicted value to obtain the first calculation result.

[0035] In this step, the preset historical time period can be a period of time before the current time, such as the previous 24 hours, 12 hours, or 1 hour before the current time. The specific time period can be customized according to the user's needs.

[0036] In this step, surface temperature data from another preset historical period can be obtained to generate training samples, and then the initial variational autoencoder can be trained using the training samples to obtain the variational autoencoder.

[0037] Step S4: Add all the first calculation results to obtain the second calculation result, add all the predicted values ​​to obtain the third calculation result; based on the second calculation result and the third calculation result, determine whether there are any outliers in all the surface temperature data, complete the preprocessing of all the surface temperature data based on the determination result, predict the surface temperature data at future time points based on the preprocessed surface temperature data, compare the surface temperature data at future time points with the preset surface temperature threshold, and issue an alarm message if the surface temperature exceeds the surface temperature threshold.

[0038] The specific implementation steps of this step include step S41 and step S42;

[0039] Step S41: Divide the second calculation result by the square root of the third calculation result to obtain the fourth calculation result. Compare the fourth calculation result with a preset threshold. If it is less than the threshold, it is determined that there are outliers in all surface temperature data. Outliers are removed and filled to obtain the preprocessed data.

[0040] In this step, we first analyze whether there is any abnormal data. If so, we remove and fill out the outliers to ensure that there is no abnormal data in the data and improve the accuracy of the prediction.

[0041] In this step, outliers are identified in all surface temperature data. Outliers are removed and filled in to obtain preprocessed data. The specific implementation steps include steps S411 and S412.

[0042] Step S411: Collect all surface temperature data to obtain a first set, identify the variable points in the first set, divide the first set according to the variable points to obtain multiple subsets, use a distance-based clustering algorithm to cluster all the subsets, and calculate the threshold range corresponding to each cluster category according to each cluster category and the 3σ criterion.

[0043] In this step, the 3σ criterion is the Laida criterion. In addition to the Laida criterion, the Pareto principle can also be used.

[0044] Step S412: Take the maximum threshold range formed by all threshold ranges as the final threshold range. If the surface temperature data is not within the final threshold range, it is considered an outlier and is removed. The surface temperature data after removing outliers is obtained. The average of the surface temperature data after removing outliers is calculated to obtain the fifth calculation result. The missing values ​​are filled in using the fifth calculation result to obtain the preprocessed data.

[0045] In this step, the maximum threshold range formed by all threshold ranges can be understood as the final threshold range. For example, if the first threshold range is 20 to 45 and the second threshold range is 15 to 40, then the maximum threshold range formed by the two threshold ranges is 15 to 45.

[0046] Step S42: Construct a differential autoregressive moving average prediction model based on the preprocessed data, and predict the surface temperature data at future time points using the differential autoregressive moving average prediction model.

[0047] The differential autoregressive moving average prediction model constructed in this step can predict surface temperature data at any future time. Based on the surface temperature data, the operating status of the pipeline can be monitored in real time to prevent pipeline failures from affecting water supply.

[0048] Example 2

[0049] like Figure 2 As shown, this embodiment provides a control system for an electric valve, the system including a first acquisition module 701 and a control module 702.

[0050] The first acquisition module 701 is used to acquire real-time data and target data. The real-time data includes the real-time temperature value on the return water pipe, the real-time pressure value on the supply water pipe, the real-time pressure value on the return water pipe, the real-time flow rate value on the supply water pipe, and the real-time flow rate value on the return water pipe in the heating system. The target data includes the target temperature value, the target pressure difference value, and the target flow rate value.

[0051] The control module 702 is used to compare and analyze the real-time data with the target data and calculate control commands. The control commands include controlling the opening degree of the electric valve to make the real-time data move closer to the target data.

[0052] In one specific embodiment of this disclosure, the control module 702 further includes a first control unit 7021.

[0053] The first control unit 7021 is used to compare the real-time temperature value with the temperature target value. If the real-time temperature value is greater than the temperature target value, a first control command is sent. The first control command includes a command to control the electric valve to reduce its opening. If the real-time temperature value is less than the temperature target value, a second control command is sent. The second control command includes a command to control the electric valve to increase its opening.

[0054] In one specific embodiment of this disclosure, the control module 702 further includes a second control unit 7022.

[0055] The second control unit 7022 is used to calculate the difference between the real-time pressure value on the water supply pipe and the real-time pressure value on the return pipe to obtain a difference result; compare the difference result with the pressure difference target value; if the difference result is greater than the pressure difference target value, send a third control command, the third control command including a command to control the electric valve to reduce the opening degree; if the difference result is less than the pressure difference target value, send a fourth control command, the fourth control command including a command to control the electric valve to increase the opening degree.

[0056] In one specific embodiment of this disclosure, the control module 702 further includes a third control unit 7023.

[0057] The third control unit 7023 is used to compare the real-time flow value on the water supply pipe and the real-time flow value on the return pipe with the target flow value. If the real-time flow value on the water supply pipe or the real-time flow value on the return pipe is greater than the target flow value, a fifth control command is sent. The fifth control command includes a command to control the electric valve to reduce its opening. If the real-time flow value on the water supply pipe or the real-time flow value on the return pipe is less than the target flow value, a sixth control command is sent. The sixth control command includes a command to control the electric valve to increase its opening.

[0058] In one specific embodiment of this disclosure, the device further includes a second acquisition module 703 and a calculation module 704.

[0059] The second acquisition module 703 is used to acquire surface temperature data of the water supply pipe in the heating system during a preset historical period, input each surface temperature data into a pre-trained variational autoencoder to obtain a predicted value corresponding to each surface temperature data, and perform a difference calculation between each surface temperature data and its corresponding predicted value to obtain a first calculation result.

[0060] The calculation module 704 is used to add all the first calculation results to obtain the second calculation result, add all the predicted values ​​to obtain the third calculation result, determine whether there are any outliers in all the surface temperature data based on the second calculation result and the third calculation result, complete the preprocessing of all the surface temperature data based on the determination result, predict the surface temperature data at future time points based on the preprocessed surface temperature data, compare the surface temperature data at future time points with the preset surface temperature threshold, and issue an alarm message if the surface temperature exceeds the surface temperature threshold.

[0061] In one specific embodiment of this disclosure, the calculation module 704 further includes a calculation unit 7041 and a prediction unit 7042.

[0062] The calculation unit 7041 is used to divide the second calculation result by the square root of the third calculation result to obtain a fourth calculation result, compare the fourth calculation result with a preset threshold, and if it is less than the threshold, determine that there are outliers in all surface temperature data, remove and fill out the outliers, and obtain the preprocessed data.

[0063] The prediction unit 7042 is used to construct a differential autoregressive moving average prediction model based on the preprocessed data, and to predict the surface temperature data at future time points through the differential autoregressive moving average prediction model.

[0064] In one specific embodiment of this disclosure, the calculation unit 7041 further includes a set-up unit 70411 and a discard unit 70412.

[0065] The set unit 70411 is used to set all surface temperature data to obtain a first set, identify the variable points in the first set, divide the first set according to the variable points to obtain multiple subsets, use a distance-based clustering algorithm to cluster all the subsets, and calculate the threshold range corresponding to each cluster category according to each cluster category and the 3σ criterion.

[0066] The rejection unit 70412 is used to take the maximum threshold range formed by all threshold ranges as the final threshold range. If the surface temperature data is not within the final threshold range, the surface temperature data is considered to be an outlier and a rejection operation is performed to obtain the surface temperature data after rejecting the outlier. The average value of the surface temperature data after rejecting the outlier is calculated to obtain a fifth calculation result. The fifth calculation result is used to fill in the missing values ​​to obtain the preprocessed data.

[0067] It should be noted that the specific methods by which each module performs operations in the system described in the above embodiments have been described in detail in the embodiments related to the method, and will not be elaborated here.

[0068] Example 3

[0069] Corresponding to the above method embodiments, this disclosure also provides a readable storage medium. The readable storage medium described below can be referred to in conjunction with the electric valve control method described above.

[0070] A readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the electric valve control method described in the above method embodiments.

[0071] Specifically, the readable storage medium can be a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, or any other readable storage medium capable of storing program code.

[0072] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A control method for an electric valve, characterized in that, include: Acquire real-time data and target data. The real-time data includes the real-time temperature value on the return water pipe, the real-time pressure value on the supply water pipe, the real-time pressure value on the return water pipe, the real-time flow rate value on the supply water pipe, and the real-time flow rate value on the return water pipe in the heating system. The target data includes the target temperature value, the target pressure difference value, and the target flow rate value. The real-time data is compared and analyzed with the target data to calculate control commands. The control commands include controlling the opening degree of the electric valve to make the real-time data move closer to the target data. Also includes: In the heating system, the surface temperature data of the water supply pipe during a preset historical period is obtained. Each surface temperature data is input into a pre-trained variational autoencoder to obtain a predicted value corresponding to each surface temperature data. The difference between each surface temperature data and its corresponding predicted value is calculated to obtain a first calculation result. Add all the first calculation results to obtain the second calculation result, and add all the predicted values ​​to obtain the third calculation result. Based on the second calculation result and the third calculation result, determine whether there are any outliers in all the surface temperature data. Based on the determination result, complete the preprocessing of all the surface temperature data, and predict the surface temperature data at future time points based on the preprocessed surface temperature data. Compare the surface temperature data at future time points with the preset surface temperature threshold. If the surface temperature exceeds the surface temperature threshold, issue an alarm message.

2. The control method for the electric valve according to claim 1, characterized in that, The real-time data is compared and analyzed with the target data to calculate a control command. The control command includes controlling the opening degree of the electric valve to bring the real-time data closer to the target data, including: The real-time temperature value is compared with the target temperature value. If the real-time temperature value is greater than the target temperature value, a first control command is sent, which includes a command to control the electric valve to reduce its opening. If the real-time temperature value is less than the target temperature value, a second control command is sent, which includes a command to control the electric valve to increase its opening.

3. The control method for the electric valve according to claim 1, characterized in that, The real-time data is compared and analyzed with the target data to calculate a control command. The control command includes controlling the opening degree of the electric valve to bring the real-time data closer to the target data, including: The difference between the real-time pressure value on the water supply pipe and the real-time pressure value on the return pipe is calculated to obtain the difference result. The difference result is compared with the pressure difference target value. If the difference result is greater than the pressure difference target value, a third control command is sent. The third control command includes a command to control the electric valve to reduce its opening. If the difference result is less than the pressure difference target value, a fourth control command is sent. The fourth control command includes a command to control the electric valve to increase its opening.

4. The control method for the electric valve according to claim 1, characterized in that, The real-time data is compared and analyzed with the target data to calculate a control command. The control command includes controlling the opening degree of the electric valve to bring the real-time data closer to the target data, including: The real-time flow rate values ​​on the water supply pipe and the return pipe are compared with the target flow rate value. If the real-time flow rate value on the water supply pipe or the return pipe is greater than the target flow rate value, a fifth control command is sent, which includes a command to control the electric valve to reduce its opening. If the real-time flow rate value on the water supply pipe or the return pipe is less than the target flow rate value, a sixth control command is sent, which includes a command to control the electric valve to increase its opening.

5. The control method for the electric valve according to claim 1, characterized in that, Based on the second and third calculation results, it is determined whether there are outliers in all surface temperature data. Based on the determination results, preprocessing of all surface temperature data is performed, and surface temperature data at future time points is predicted based on the preprocessed surface temperature data, including: Divide the second calculation result by the square root of the third calculation result to obtain the fourth calculation result. Compare the fourth calculation result with a preset threshold. If it is less than the threshold, it is determined that there are outliers in all surface temperature data. Outliers are removed and filled to obtain preprocessed data. A differential autoregressive moving average prediction model is constructed based on the preprocessed data, and the surface temperature data at future time points is predicted using the differential autoregressive moving average prediction model.

6. The control method for the electric valve according to claim 5, characterized in that, Outliers are identified in all surface temperature data. These outliers are then removed and filled to obtain preprocessed data, including: All surface temperature data are collected to obtain a first set. Change points in the first set are identified. The first set is divided into multiple subsets based on the change points. All subsets are clustered using a distance-based clustering algorithm. The threshold range corresponding to each cluster category is calculated based on each cluster category and the 3σ criterion. The maximum threshold range formed by all threshold ranges is taken as the final threshold range. If the surface temperature data is not within the final threshold range, it is considered an outlier and is removed. The surface temperature data after removing outliers is obtained. The average of the surface temperature data after removing outliers is calculated to obtain a fifth calculation result. The missing values ​​are filled in using the fifth calculation result to obtain the preprocessed data.

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