A control method for a secondary pressurized domestic water supply system

Abstract

The present invention relates to the field of water supply control technology, specifically a control method for a secondary pressurized domestic water supply system, comprising the following steps: collecting user water use data, screening time, water volume and water pressure parameters, performing statistical analysis of daily patterns, and obtaining the time distribution of conventional water use behavior; based on the time distribution, analyzing typical water use peaks and troughs, and generating a water demand forecast table. The present invention analyzes the adjusted water pressure data, calculates the maximum fluctuation value and the average fluctuation value, and compares them with a preset safe fluctuation range, so as to timely identify and mark abnormal water pressure fluctuations. Through the results of the fluctuation data analysis, the stability of the water pressure in the short term is further predicted, and dynamic evaluation and targeted planning of the water pressure operation trend are achieved. The starting frequency and power output of the booster pump are set based on the prediction results, and the operating status of the water supply equipment is dynamically adjusted to ensure the smooth operation of the water pressure in different usage scenarios.

Description

Technical Field

[0001] The present invention relates to the technical field of water supply control, and in particular to a control method for a secondary pressurized domestic water supply system. Background Art

[0002] Water supply control technology is a crucial component of modern infrastructure development, regulating water flow, pressure, quality, and energy consumption within water supply systems. The core of this technology lies in dynamically adjusting the operating status of water supply equipment through sensor networks and real-time data acquisition and analysis technologies, thereby meeting user water needs and ensuring efficient and stable system operation.

[0003] However, existing technologies have shortcomings in real-time analysis of water pressure changes. They tend to overlook the potential for long-term instability caused by small, short-term fluctuations. Their ability to predict water pressure stability is limited, making it difficult to effectively intervene before fluctuations accumulate. This can lead to equipment overload and a degraded user experience. These shortcomings limit the adaptability and overall effectiveness of water supply control systems in complex water supply environments. Summary of the Invention

[0004] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a control method for a secondary pressurized domestic water supply system.

[0005] In order to achieve the above object, the present invention adopts the following technical solution, a control method of a secondary pressurized domestic water supply system, comprising the following steps:

[0006] Collect user water usage data, filter time, water volume, and water pressure parameters, perform statistical analysis of daily patterns, and obtain the time distribution of regular water use behavior. Based on this time distribution, analyze typical water use peaks and troughs to generate a water demand forecast table.

[0007] Receive water use data in real time, compare it with the water demand forecast table, verify whether it is in the predicted peak period or valley period, and generate a real-time water use status result; adjust the speed and power of the booster pump according to the real-time water use status result, monitor the adjusted water pressure feedback, and generate an adjusted water pressure result;

[0008] Analyze the adjusted water pressure results, calculate the maximum and average fluctuation values ​​of the water pressure, compare the fluctuation values ​​with a preset safe fluctuation range, identify abnormal fluctuations, and generate a water pressure fluctuation analysis result; predict the short-term water pressure stability based on the water pressure fluctuation analysis result, and generate a water pressure stability prediction result;

[0009] According to the water pressure stability prediction result, the starting frequency and power output of the booster pump are set, the effect is monitored, and the control effect evaluation result is generated.

[0010] Preferably, the steps for obtaining the time distribution of the regular water use behavior are:

[0011] Collect user water use data through sensors, the water use data including each user's water use time, water volume and water pressure, and organize the water use data to generate a water use data set;

[0012] Extract time, water volume, and water pressure data from the water usage dataset, assign a timestamp to each data point, and calculate the average water volume and water pressure within each time period. The calculation formula is:

[0013]

[0014] and

[0015]

[0016] in, is the water volume of the i-th data point, is the water pressure of the ith data point, is the total number of data points, is the average water volume, is the average water pressure;

[0017] According to the average water volume and average water pressure in each time period, the changing trends of water volume and water pressure are analyzed to obtain the time distribution of regular water use behavior.

[0018] Preferably, the steps for obtaining the water demand forecast table are:

[0019] Analyze and determine the peak and valley periods of daily water use based on the temporal distribution of the regular water use behavior, identify the peak and valley periods through time series analysis, and generate a list of peak and valley periods of water use;

[0020] Based on the list of peak and low water usage periods, daily and weekly water usage patterns are analyzed. By counting the water usage frequency in each time period and quantifying the fluctuations in water consumption, the fluctuations in users' water demand in each time period are identified to obtain water usage behavior pattern data.

[0021] Utilizing the water use behavior pattern data, the expected water consumption for each period in the future is listed to develop a water demand forecast table.

[0022] Preferably, the steps for obtaining the real-time water usage status result are:

[0023] Receive water consumption data from sensors in real time and obtain water consumption data sets;

[0024] Based on the water use data set, a comparative analysis is performed with the water demand forecast table. By comparing the difference between the real-time data and the forecast data, it is identified whether the current period matches the peak or trough period forecast, and a real-time water use status analysis result is obtained;

[0025] According to the real-time water usage status analysis result, the current water usage status is verified to determine whether it is in a peak period or a trough period, and a real-time water usage status result is generated.

[0026] Preferably, the steps for obtaining the adjusted water pressure result are:

[0027] Based on the real-time water usage status results, the operating parameters of the booster pump, including speed and power, are adjusted to match the current water usage. According to the set values ​​of the adjustment parameters, the theoretical water pressure output of the booster pump after adjustment is calculated. The calculation formula is:

[0028]

[0029] in, For the adjusted water pressure, To adjust the water pressure before, and are the pump speeds before and after adjustment, and are the power before and after adjustment respectively;

[0030] Based on calculated adjusted water pressure , monitor water pressure feedback data, verify the effectiveness of adjustments, and generate adjusted water pressure results.

[0031] Preferably, the steps for obtaining the water pressure fluctuation analysis results are:

[0032] Continuously monitor the adjusted water pressure and record the water pressure readings at each time point, compiling them into a water pressure time series dataset;

[0033] The water pressure data of each measuring point are extracted from the water pressure time series data set, and the maximum fluctuation value and average fluctuation value of the water pressure are calculated. The calculation formula is:

[0034]

[0035] and

[0036]

[0037] in, represents the water pressure value at the i-th measurement point, is the average water pressure, is the total number of data points;

[0038] According to the maximum fluctuation value and the average fluctuation value, the maximum fluctuation value and the average fluctuation value are compared with a preset safe fluctuation range to identify whether abnormal fluctuations exceed the preset safe range and form a water pressure fluctuation analysis result.

[0039] Preferably, the steps for obtaining the water pressure stability prediction result are:

[0040] Based on the water pressure fluctuation analysis results, extracting the maximum fluctuation value and the average fluctuation value;

[0041] Based on the extracted maximum fluctuation value and average fluctuation value, the stability of water pressure in the future time period is calculated using the following formula:

[0042]

[0043] in, represents the predicted water pressure stability index, is the average fluctuation value extracted from the fluctuation data, and are the coefficients and thresholds for adjustment;

[0044] Based on the water pressure stability index, the degree of matching with the preset safety standard is analyzed to determine whether adjustment or monitoring is required, thereby forming a water pressure stability prediction result.

[0045] Preferably, the steps for obtaining the regulatory effect evaluation result are:

[0046] Obtaining the water pressure stability prediction result, adjusting the starting frequency and power output of the booster pump according to the water pressure stability prediction result to match the predicted demand change, and forming an adjustment parameter setting for the booster pump;

[0047] Based on the adjustment parameter settings of the booster pump, the starting frequency and power output are changed, and the adjusted booster pump operating data is monitored in real time to obtain preliminary control implementation results;

[0048] Based on the preliminary control implementation results, it is analyzed whether the adjustment effect has achieved the expected water pressure stability improvement goal, and the control effect evaluation results are generated.

[0049] Compared with the prior art, the advantages and positive effects of the present invention are:

[0050] The present invention analyzes the adjusted water pressure data, calculates the maximum fluctuation value and the average fluctuation value, and compares them with the preset safe fluctuation range, so as to promptly identify and mark abnormal water pressure fluctuations. Through the analysis results of the fluctuation data, the stability of the water pressure in the short term is further predicted, and dynamic evaluation and targeted planning of the water pressure operation trend are achieved. The starting frequency and power output of the booster pump are set based on the prediction results, and the operating status of the water supply equipment is dynamically adjusted to ensure the smooth operation of the water pressure in different usage scenarios. The monitoring effect link is combined with real-time feedback data to continuously verify and optimize the control parameters, so that the water supply equipment can respond to changes in demand more sensitively. A closed-loop process of analysis, prediction, control and feedback is formed, which improves decision-making ability and operational stability, while reducing energy waste and enhancing the reliability and sustainability of the water supply system in different demand scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 Schematic diagram of the steps of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0053] See also Figure 1 The present invention provides a technical solution, a control method for a secondary pressurized domestic water supply system, comprising the following steps:

[0054] Collect user water usage data, filter time, water volume, and water pressure parameters, conduct statistical analysis of daily patterns, and obtain the time distribution of regular water use behavior. Based on the time distribution, analyze typical peak and trough periods of water use and generate a water demand forecast table.

[0055] Receive water use data in real time, compare it with the water demand forecast table, verify whether it is in the predicted peak or trough period, and generate real-time water use status results; adjust the speed and power of the booster pump based on the real-time water use status results, monitor the adjusted water pressure feedback, and generate adjusted water pressure results;

[0056] Analyze the adjusted water pressure results, calculate the maximum and average fluctuation values ​​of the water pressure, compare the fluctuation values ​​with the preset safe fluctuation range, identify abnormal fluctuations, and generate water pressure fluctuation analysis results; based on the water pressure fluctuation analysis results, predict the short-term water pressure stability and generate water pressure stability prediction results;

[0057] Based on the water pressure stability prediction results, the starting frequency and power output of the booster pump are set, the effect is monitored, and the control effect evaluation results are generated.

[0058] The steps to obtain the time distribution of regular water use behavior are:

[0059] Collect user water usage data through sensors. The water usage data includes each user's water usage time, water volume, and water pressure. The water usage data is organized to generate a water usage dataset.

[0060] Extract time, water volume, and water pressure data from the water use dataset, assign a timestamp to each data point, and calculate the average water volume and water pressure in each time period. The calculation formula is:

[0061]

[0062] and

[0063]

[0064] in, is the water volume of the i-th data point, is the water pressure of the ith data point, is the total number of data points, is the average water volume, is the average water pressure;

[0065] According to the average water volume and average water pressure in each time period, the changing trends of water volume and water pressure are analyzed to obtain the time distribution of regular water use behavior.

[0066] Specifically, sensors are used to collect user water usage data, including the specific time, amount, and pressure of each user. These data are then collated to form a preliminary water usage dataset. Sensors are then installed at each user node to transmit the data in real time to the central processing unit. The data includes date, timestamp, water flow meter reading, and pressure gauge reading. This ensures the integrity and real-time nature of the collected data. Outliers, such as sudden changes in water flow to unusual values, are removed to ensure data quality, provide a reliable data foundation for subsequent analysis, and generate a preliminary water usage dataset.

[0067] In the formula, The steps to obtain the parameters are: the water flow rate measured at each detection point by the water flow meter, The steps to obtain the parameters are: the water pressure measured at each detection point by the pressure gauge, is the total number of data points, calculated by the number of records in the data collection period;

[0068] Calculation process: Set a specific collection cycle, collect data once every hour for 24 hours a day, and the data at 8:00 is Lift, psi, similarly, until 24:00, calculate the average water flow and water pressure for each hour of the day, and calculate by inserting specific values ​​to obtain the daily average water flow and water pressure;

[0069] Based on the average water volume and average water pressure in each time period, the changing trends of water volume and water pressure are analyzed. Time series analysis methods, such as moving average or exponential smoothing, are used to analyze the correlation and trend between data points. In addition, seasonal decomposition can be used to identify water usage patterns in specific time periods, such as changes in water consumption during the morning and evening peaks. Through these analyses, we can further understand consumers' water use habits and potential water supply needs, provide decision support for water resource management, and obtain the time distribution of regular water use behavior.

[0070] The steps to obtain the water demand forecast table are:

[0071] Analyze and determine the peak and trough periods of daily water use based on the temporal distribution of regular water use behavior. Through time series analysis, identify the peak and trough time periods and generate a list of peak and trough periods.

[0072] Based on a list of peak and low water usage periods, we analyze daily and weekly water usage patterns. By counting the frequency of water use in each time period and quantifying the fluctuations in water consumption, we identify fluctuations in user water demand in each time period and obtain water use behavior pattern data.

[0073] Using water use behavior pattern data, the expected water consumption for each period in the future is listed and a water demand forecast table is developed.

[0074] Specifically, starting from the time distribution data of regular water use behavior obtained in the previous step, we first perform time series analysis on these data. By calculating the moving average and standard deviation, we determine the time periods with the highest and lowest water consumption, thereby identifying the peak and trough periods of daily water use. In this process, we specifically cluster the 24-hour water use records by hour, analyze the water use patterns of each time period, evaluate the frequent time points of peak and trough periods, depict the changing trends of peak and trough periods, mark these periods and organize them into a list, and provide them for the next step of analysis to obtain a list of peak and trough periods of water use.

[0075] Based on the list of peak and low water usage periods, we further analyzed the changes in daily and weekly water usage patterns. We performed further statistical analysis on the data points in the list, such as calculating the standard deviation of water usage frequency and water consumption within each period, displaying the fluctuations in water consumption, and analyzing the fluctuations in water demand on different days and time periods. In this step, we paid special attention to associating water use behavior with specific days (such as holidays and weekdays) and evaluating the impact of external factors such as weather changes on water use patterns, thereby obtaining a water use behavior pattern dataset.

[0076] Utilizing the detailed analysis of water use behavior pattern data, a water demand forecast table is developed that details the expected water consumption for each period in the future. By comparing and analyzing historical data with forecast data for upcoming time periods, the operating strategy of the water supply system is adjusted to adapt to the water demand in different time periods. The water use behavior pattern data is compared with the control parameters of the water supply system (such as the start-up frequency and output power of the pump station) to develop operational recommendations aimed at optimizing water supply efficiency and resource allocation.

[0077] The steps to obtain real-time water usage status results are as follows:

[0078] Receive water consumption data from sensors in real time and obtain water consumption data sets;

[0079] Based on the water use data set, a comparative analysis is performed with the water demand forecast table. By comparing the differences between real-time data and forecast data, it is determined whether the current period matches the peak or trough forecast, and the real-time water use status analysis results are obtained;

[0080] According to the real-time water use status analysis results, verify the current water use status to see whether it is in the peak period or the trough period, and generate the real-time water use status results.

[0081] Specifically, the system receives water usage data from sensors in real time. This data is first formatted and verified to confirm its completeness and accuracy, ensuring the integrity of the data during transmission. The data is then aggregated into a real-time updated water usage dataset. The data within these datasets is timestamped to facilitate subsequent processing and analysis, thus forming a continuously updated data stream.

[0082] The received data set is compared with the previously prepared water demand forecast table. Each data point is identified and compared with the corresponding time period in the forecast table. These data points are aligned by time stamp and then the values ​​are compared. For each time period, the difference between the actual water volume and the predicted water volume is calculated. Through this difference analysis, it is determined whether the water use situation in the current period is consistent with the peak or trough forecast, thus providing accurate information on the current water use status.

[0083] Based on the aforementioned real-time water usage analysis results, we continue to conduct in-depth data verification and compare the current water usage data with the historical data for the same period. If data deviations are found, we analyze the causes of the deviations, such as whether they are due to seasonal changes or the impact of emergencies, and confirm whether the current water usage status is a normal peak or trough. This comparison not only helps to confirm abnormal situations, but also verifies the reliability of the current data through historical data. The final real-time water usage status results provide an intuitive description of the current water usage situation.

[0084] The steps to obtain the adjusted water pressure results are:

[0085] Based on the real-time water usage status results, the operating parameters of the booster pump, including speed and power, are adjusted to match the current water usage. According to the set values ​​of the adjustment parameters, the theoretical water pressure output of the booster pump after adjustment is calculated. The calculation formula is:

[0086]

[0087] in, For the adjusted water pressure, To adjust the water pressure before, and are the pump speeds before and after adjustment, and are the power before and after adjustment respectively;

[0088] Based on calculated adjusted water pressure , monitor water pressure feedback data, verify the effectiveness of adjustments, and generate adjusted water pressure results.

[0089] Specifically, it receives water usage data in real time, adjusts the speed and power of the booster pump based on the real-time water usage status results, monitors the adjusted water pressure feedback, collects water flow and water pressure data flowing into the main network through sensors, and analyzes whether the current water consumption deviates significantly from the daily data based on the received data. If an abnormal increase or decrease is found, the speed and power of the booster pump are adjusted immediately to ensure that the water pressure is maintained within a stable range, preventing excessive water pressure fluctuations caused by sudden increases or decreases in water consumption from affecting the user's water experience, and ensuring the efficient operation of the entire water supply system and stable water pressure.

[0090] The formula is useful in that by adjusting the pump speed and power The output water pressure can be precisely controlled according to actual water demand, thereby improving the efficiency of water resource use and the user's water experience; The parameter acquisition step is to obtain the average water pressure value of the previous detection cycle through real-time monitoring of the water pressure sensor. The pump speed of the last operating cycle is recorded by the control system of the booster pump. is the power output of the pump in the last operating cycle, also obtained through the control system data record;

[0091] Calculation process: The water pressure of the most recent monitoring At 2.5 bar, the pump speed At 1500rpm, power 10kW, real-time demand increases, new pump speed Set to 1800rpm, the new power Adjusted to 12kW, the formula is substituted into the calculation of 3.6. The result shows that the water pressure increases to 3.6bar after adjustment. In this way, the pump speed and power can be adjusted according to real-time data feedback to cope with changes in water consumption and ensure the stability of water pressure.

[0092] Based on the calculated adjusted water pressure, the actual water pressure feedback data is monitored to confirm the effectiveness of the adjustment. The data is collected in real time through the pressure sensors installed in the pipe network, and the previous predictions are compared with the actual values ​​to analyze whether there are fluctuations beyond the normal operating range. If abnormal fluctuations in water pressure are monitored, the operating parameters of the pump are adjusted through secondary regulation until the water pressure returns to normal, generating the adjusted water pressure result.

[0093] The steps to obtain the water pressure fluctuation analysis results are:

[0094] Continuously monitor the adjusted water pressure and record the water pressure readings at each time point, compiling them into a water pressure time series dataset;

[0095] Extract the water pressure data of each measuring point from the water pressure time series dataset and calculate the maximum and average fluctuation values ​​of the water pressure. The calculation formula is:

[0096]

[0097] and

[0098]

[0099] in, represents the water pressure value at the i-th measurement point, is the average water pressure, is the total number of data points;

[0100] According to the maximum fluctuation value and the average fluctuation value, the maximum fluctuation value and the average fluctuation value are compared with the preset safe fluctuation range to identify whether the abnormal fluctuation exceeds the predetermined safe range and form the water pressure fluctuation analysis result.

[0101] Specifically, the adjusted water pressure is continuously monitored through sensors, and the specific water pressure readings at different time points are recorded and organized into a water pressure time series dataset. Data is collected in real time, and each data point contains a timestamp and the corresponding water pressure value. Each data point received is organized into a time series, arranged in chronological order, and stored for use in subsequent data processing and analysis steps to ensure data integrity and traceability.

[0102] The formula is useful in that it allows monitoring and evaluating the stability of a water supply system by quantifying the fluctuations in water pressure readings; the parameter represents the water pressure value at the i-th measurement point. This value is directly obtained through the real-time monitoring system. The data of each measurement point is collected and automatically recorded by the water pressure sensor at a preset time interval; The average water pressure is calculated as the average of the water pressure values ​​at all measuring points, indicating the normal water supply pressure status; is the total number of data points, i.e. the number of water pressure data points collected during a specific monitoring period, which is usually set at one measurement per minute.

[0103] Calculation process: First calculate the average water pressure For example, 100 data points are collected and the water pressure at each point is , calculate the sum and divide by 100 to get ; Then, take the maximum absolute value of the difference between the water pressure value at each point and the average value to get the maximum fluctuation value At the same time, calculate the sum of the squares of the differences between the water pressure value at each point and the average value, divide it by 100, and take the square root of the result to get the average fluctuation value .

[0104] The result shows that if the maximum fluctuation value or the average fluctuation value exceeds the safety setting threshold, it indicates that there may be leakage or other technical problems, which require further inspection and maintenance.

[0105] According to the maximum fluctuation value and the average fluctuation value, the maximum fluctuation value and the average fluctuation value are compared with the preset safety fluctuation range to identify whether the abnormal fluctuation exceeds the preset safety range and form the water pressure fluctuation analysis result. In this process, the calculated maximum fluctuation value and the average fluctuation value are compared with the preset threshold value based on the set safety fluctuation range. If the fluctuation value exceeds the threshold value, it will be marked and the maintenance team will be notified for inspection to ensure the safe operation of the water supply system. The setting method of the abnormal fluctuation in the preset safety range is to determine it through statistics. For example, in statistics, when the abnormal fluctuation exceeds a certain value, the probability of failure is very high, and the fluctuation range within it will be set as the safety fluctuation range.

[0106] The steps for obtaining the water pressure stability prediction results are as follows:

[0107] Based on the water pressure fluctuation analysis results, the maximum fluctuation value and the average fluctuation value are extracted;

[0108] Based on the extracted maximum fluctuation value and average fluctuation value, the stability of water pressure in the future time period is calculated using the following formula:

[0109]

[0110] in, represents the predicted water pressure stability index, is the average fluctuation value extracted from the fluctuation data, and are the coefficients and thresholds for adjustment;

[0111] Based on the water pressure stability index, the degree of match with the preset safety standards is analyzed to determine whether adjustment or monitoring is needed, and a water pressure stability prediction result is formed.

[0112] Specifically, based on the water pressure fluctuation analysis results, the maximum fluctuation value and average fluctuation value were extracted from the data. These values ​​were obtained through statistical analysis of the adjusted water pressure data. The maximum fluctuation value indicated the single maximum water pressure deviation recorded during the monitoring period, while the average fluctuation value indicated the average level of water pressure deviation during the entire monitoring period.

[0113] The benefits of the formula are: predicting water pressure stability in the form of a logistic regression model, using exponential and logarithmic functions to adjust the prediction sensitivity and adapt to different fluctuation data characteristics;

[0114] is the average water pressure fluctuation value in the past week. and The parameters are optimized by minimizing the prediction error;

[0115] Calculation process: Historical data display is 2.5, is 1.2, is 2.0, and the result is 0.574. This result shows that: if A value close to 1 indicates that the water pressure state is relatively stable. A lower value indicates worse stability. The current result of 0.574 indicates that the water pressure stability is in a medium state and possible fluctuations need to be continuously monitored.

[0116] Based on the water pressure stability index, analyze the degree of match with the preset safety standards. The index is obtained through the aforementioned calculation and reflects the stability of the water pressure under the current operating conditions. In this step, by comparing the calculated stability index with the pre-set safety standard threshold, determine whether it is within an acceptable stability range or whether further adjustment or monitoring is required. The safety standard threshold can be set to 0.3, for example, based on the actual environmental test.

[0117] The steps for obtaining the results of the regulation effect evaluation are as follows:

[0118] Obtain the water pressure stability prediction results, adjust the starting frequency and power output of the booster pump according to the water pressure stability prediction results, match the predicted demand changes, and form the adjustment parameter settings of the booster pump;

[0119] Based on the adjustment parameter settings of the booster pump, the starting frequency and power output are changed, and the adjusted booster pump operating data is monitored in real time to obtain preliminary control implementation results;

[0120] Through the preliminary control implementation results, analyze whether the adjustment effect has achieved the expected water pressure stability improvement goal and generate the control effect evaluation results.

[0121] Specifically, based on the water pressure stability prediction results obtained, the booster pump's starting frequency and power are adjusted to accommodate the predicted changes in water pressure demand. Adjusting these parameters requires setting safety thresholds and operating ranges based on recent water pressure data and long-term water pressure records to ensure that the adjusted output matches the actual water pressure demand.

[0122] After adjusting the booster pump parameters, the new starting frequency and power output are implemented. Next, real-time monitoring is performed to track the effectiveness of the adjustments. This monitoring includes collecting real-time water pressure, flow, and power data from the booster pump to verify the compliance and effectiveness of the adjustments. The operations team regularly reviews these indicators to ensure that each adjustment is strictly implemented in accordance with the predetermined performance standards.

[0123] After comprehensively analyzing the data from the implementation of regulation, the effectiveness of the adjustment is evaluated by comparing the water pressure data before and after the adjustment, including the stability of the water pressure and the operating efficiency of the equipment.

[0124] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A control method for a secondary pressurized domestic water supply system, characterized in that: The following steps are involved: Collect user water usage data, filter time, water volume and water pressure parameters, conduct statistical analysis of daily patterns, and obtain the time distribution of regular water use behavior; Based on the time distribution, typical water consumption peak and trough periods are analyzed to generate a water demand forecast table; Receive water use data in real time, compare it with the water demand forecast table, verify whether it is in the predicted peak period or valley period, and generate a real-time water use status result; adjust the speed and power of the booster pump according to the real-time water use status result, monitor the adjusted water pressure feedback, and generate an adjusted water pressure result; Analyzing the adjusted water pressure results, calculating the maximum fluctuation value and the average fluctuation value of the water pressure, comparing the fluctuation value with a preset safe fluctuation range, identifying abnormal fluctuations, and generating a water pressure fluctuation analysis result; Predicting short-term water pressure stability based on the water pressure fluctuation analysis results to generate a water pressure stability prediction result; According to the water pressure stability prediction result, the starting frequency and power output of the booster pump are set, the effect is monitored, and a control effect evaluation result is generated; The steps for obtaining the water pressure fluctuation analysis results are: Continuously monitor the adjusted water pressure and record the water pressure readings at each time point, compiling them into a water pressure time series dataset; The water pressure data of each measuring point are extracted from the water pressure time series data set, and the maximum fluctuation value and average fluctuation value of the water pressure are calculated. The calculation formula is: and in, represents the water pressure value at the i-th measurement point, is the average water pressure, is the total number of data points; According to the maximum fluctuation value and the average fluctuation value, the maximum fluctuation value and the average fluctuation value are compared with a preset safe fluctuation range, and whether abnormal fluctuation exceeds the predetermined safe range is identified to form a water pressure fluctuation analysis result; The steps for obtaining the water pressure stability prediction result are: Based on the water pressure fluctuation analysis results, extracting the maximum fluctuation value and the average fluctuation value; Based on the extracted maximum fluctuation value and average fluctuation value, the stability of water pressure in the future time period is calculated using the following formula: in, represents the predicted water pressure stability index, is the average fluctuation value extracted from the fluctuation data, and are the coefficients and thresholds for adjustment; Based on the water pressure stability index, analyzing the degree of matching with the preset safety standards, determining whether adjustment or monitoring is required, and forming a water pressure stability prediction result; The steps for obtaining the real-time water usage status result are: Receive water consumption data from sensors in real time and obtain water consumption data sets; Based on the water use dataset, a comparative analysis is performed with the water demand forecast table, each data point is identified and compared with the corresponding time period in the forecast table, the data points are aligned by timestamps, and then the values ​​are compared. For each time period, the difference between the actual water volume and the predicted water volume is calculated to determine whether the water use situation in the current time period is consistent with the peak or trough period forecast, thereby obtaining a real-time water use status analysis result; Based on the real-time water usage status analysis results, compare the current water usage data with the historical data for the same period. If data deviation is found, analyze the cause of the deviation, confirm whether the current water usage status is a normal peak or trough, and generate a real-time water usage status result. The steps for obtaining the regulatory effect evaluation results are as follows: Obtaining the water pressure stability prediction result, adjusting the starting frequency and power output of the booster pump according to the water pressure stability prediction result to match the predicted demand change, and forming an adjustment parameter setting for the booster pump; Based on the adjustment parameter settings of the booster pump, the starting frequency and power output are changed, and the adjusted booster pump operating data is monitored in real time to obtain preliminary control implementation results; Based on the preliminary control implementation results, it is analyzed whether the adjustment effect has achieved the expected water pressure stability improvement goal, and the control effect evaluation results are generated.

2. The control method of the secondary pressurized domestic water supply system according to claim 1, characterized in that: The steps for obtaining the time distribution of the conventional water use behavior are: Collect user water use data through sensors, the water use data including each user's water use time, water volume and water pressure, and organize the water use data to generate a water use data set; Extract time, water volume, and water pressure data from the water usage dataset, assign a timestamp to each data point, and calculate the average water volume and water pressure within each time period. The calculation formula is: and in, is the water volume of the i-th data point, is the water pressure of the ith data point, is the total number of data points, is the average water volume, is the average water pressure; According to the average water volume and average water pressure in each time period, the changing trends of water volume and water pressure are analyzed to obtain the time distribution of regular water use behavior.

3. The control method of the secondary pressurized domestic water supply system according to claim 1, characterized in that: The steps for obtaining the water demand forecast table are: Analyze and determine the peak and valley periods of daily water use based on the temporal distribution of the regular water use behavior, identify the peak and valley periods through time series analysis, and generate a list of peak and valley periods of water use; Based on the list of peak and low water usage periods, daily and weekly water usage patterns are analyzed. By counting the water usage frequency in each time period and quantifying the fluctuations in water consumption, the fluctuations in users' water demand in each time period are identified to obtain water usage behavior pattern data. Utilizing the water use behavior pattern data, the expected water consumption for each period in the future is listed to develop a water demand forecast table.

4. The control method of the secondary pressurized domestic water supply system according to claim 1, characterized in that: The steps for obtaining the adjusted water pressure result are: Based on the real-time water usage status results, the operating parameters of the booster pump, including speed and power, are adjusted, and the theoretical water pressure output of the booster pump after adjustment is calculated using the following formula: in, For the adjusted water pressure, To adjust the water pressure before, and are the pump speeds before and after adjustment, and are the power before and after adjustment respectively; Based on calculated adjusted water pressure , monitor water pressure feedback data, verify the effectiveness of adjustments, and generate adjusted water pressure results.

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