Remote monitoring method and system for secondary water supply equipment

Abstract

The invention relates to the technical field of automatic control, in particular to a remote monitoring method and system for secondary water supply equipment, and the method comprises the following steps: analyzing the energy consumption of a plurality of water supply equipment through current and voltage data based on the operation log of the water supply equipment, and collecting the water pressure data of a plurality of positions through a water pressure sensor; and generating an energy consumption and water pressure data set. According to the invention, the operation current and voltage of the water supply equipment are analyzed in real time, the water pressure data of multiple positions are monitored, the energy consumption and water pressure change of the water supply equipment are evaluated in real time, and the seasonal change of water use is effectively identified in combination with the time sequence analysis of the water use data; adjustment of water supply pressure and flow is optimized, the water demand of residents is matched, the response speed and water supply stability of secondary water supply are improved, the energy efficiency ratio of the water pump under various operation conditions is evaluated by analyzing the operation power and water level setting of the water pump, energy use is optimized, and the operation efficiency and reliability of secondary water supply equipment are improved.

Description

Technical Field

[0001] The present invention relates to the field of automation control technology, and in particular to a remote monitoring method and system for secondary water supply equipment. Background Art

[0002] The field of automation control technology uses a variety of control systems and information technologies to automatically operate and manage machines and equipment, reduce human intervention, and improve efficiency and accuracy. It includes sensor technology, actuators, control algorithms, human-machine interfaces, and communication networks. It is applied to multiple industries such as manufacturing, water supply treatment, transportation, energy management, and environmental control. It collects key operating data through sensors, uses controllers to adjust the behavior of mechanical equipment, and combines multiple algorithms to predict and optimize operating results, thereby improving operating efficiency and cost-effectiveness, and achieving process control, quality control, safety monitoring, and resource optimization.

[0003] Among them, the remote monitoring method of secondary water supply equipment uses remote technology to monitor and manage secondary water supply equipment, and remotely collects equipment operation data to ensure the efficient and safe operation of the water supply system. It continuously monitors the operating status of water supply equipment and combines real-time data analysis to automatically adjust water supply parameters to match demand changes, optimize water resource allocation, promptly discover and handle faults, improve water supply reliability and efficiency, and realize monitoring of multiple key indicators of water quality and water pressure, thereby optimizing the continuity and stability of water supply.

[0004] Traditional remote monitoring methods for secondary water supply equipment cannot effectively synchronize multiple data sources in terms of data integration and real-time response, lack sufficient flexibility and accuracy in predicting water demand and adjusting water supply parameters, and cannot respond to changes in residents' water use patterns in real time, resulting in inefficiency and waste of resources in the water supply process. There are no targeted optimization measures for energy efficiency management, and the operating parameters of the water pump cannot be dynamically adjusted according to actual operating data, resulting in excessive energy consumption and increased maintenance costs, affecting the economy of the water supply system and reducing user satisfaction and the reliability of water supply equipment. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a remote monitoring method and system for secondary water supply equipment.

[0006] In order to achieve the above object, the present invention adopts the following technical solution, a remote monitoring method for secondary water supply equipment, comprising the following steps:

[0007] S1: Based on the operation log of water supply equipment, the energy consumption of multiple water supply equipment is analyzed through current and voltage data, and water pressure data at multiple locations are collected using water pressure sensors to generate energy consumption and water pressure data sets;

[0008] S2: Based on the energy consumption and water pressure data sets, perform time series analysis on the water pressure data to identify seasonal changes in residents’ water use and form water use pattern analysis results;

[0009] S3: Based on the water use pattern analysis results, analyze and predict the water demand at multiple times, calculate and adjust the pressure and flow of the secondary water supply, match the predicted demand to optimize the stability of the water supply pressure, and obtain a water demand matching result;

[0010] S4: Based on the water demand matching result, by analyzing the relationship between the operating power, temperature, operating time and operating efficiency of the water pump, the energy efficiency ratio of the water pump under various powers is evaluated to generate a water pump efficiency analysis result;

[0011] S5: Based on the water pump efficiency analysis result, by comparing the water pump energy consumption under various water level range settings, considering the actual water demand of residents, calculating the water tower water storage level, and generating a water level calculation result;

[0012] S6: According to the water level calculation results and in combination with the predicted results of residents' water demand, the operation schedule and power parameters of the water pump are adjusted to match the residents' water demand in multiple time periods and generate water supply equipment control parameters.

[0013] As a further solution of the present invention, the energy consumption and water pressure data set includes current peak data, minimum voltage data, and average water pressure information; the water use pattern analysis results include peak water use periods, low-peak water use periods, and seasonal water use change prediction results; the water demand matching results include water supply pressure adjustment results, water supply flow setting parameters, and expected water demand matching degree; the water pump efficiency analysis results include water pump energy efficiency ratio information under multiple power levels, analysis results of the impact of operating temperature on operating efficiency, and analysis results of the impact of operating time on operating efficiency; the water level calculation results include water level range setting parameters, water pump operating cost analysis results, and water supply equipment energy consumption prediction information; the water supply equipment control parameters include water pump operation schedule, power parameter settings, and water pump start and stop records.

[0014] As a further solution of the present invention, based on the water supply equipment operation log, the energy consumption of multiple water supply equipment is analyzed through current and voltage data, and water pressure data of multiple locations are collected by using a water pressure sensor. The steps of generating energy consumption and water pressure data sets are specifically as follows:

[0015] S101: Based on the water supply equipment operation log, the current and voltage change data of the equipment are collected and recorded in real time to generate current and voltage monitoring data;

[0016] S102: deploying water pressure sensors at multiple key nodes of the water supply system according to the current and voltage monitoring data, collecting water pressure values ​​at multiple locations in real time, and generating water pressure data collection results;

[0017] S103: Based on the water pressure data collection result, the energy consumption of the water supply equipment is calculated through the current and voltage data, and the water pressure data and energy consumption data are formatted, and the time information is recorded to generate energy consumption and water pressure data sets.

[0018] As a further solution of the present invention, based on the energy consumption and water pressure data set, the water pressure data is subjected to time series analysis to identify seasonal changes in residents' water use, and the steps of forming a water use pattern analysis result are specifically as follows:

[0019] S201: Based on the energy consumption and water pressure data set, collect and analyze residents' historical water use data, including water consumption and water use time information, to generate historical water use information;

[0020] S202: Based on the historical water use information, an autoregressive moving average model is used to analyze the residential water use data, identify the periodic change pattern of water use fluctuations, including water consumption peaks and valleys, and generate periodic fluctuation information;

[0021] S203: Analyze abnormal fluctuations and peak consumption in the water use pattern according to the periodic fluctuation information, identify seasonal changes and water use patterns during multiple holidays, and form a water use pattern analysis result.

[0022] As a further solution of the present invention, the autoregressive moving average model is according to the formula:

[0023]

[0024] Calculate water demand, where X t is the water consumption at the current time point, c is a constant term, ∈ t is the error term, φ i is the autoregression coefficient, X t-i is the water consumption at time ti, θ i is the moving average coefficient, ∈ t-i is the error value at time point ti, p is the order of autoregression, q is the order of moving average, β is the influence coefficient of temperature, T t is the average temperature at the current time point, γ is the seasonal influence coefficient, S t is a seasonal indicator, t is the current moment, i is the lag period, and ti is the current moment minus the i moment.

[0025] As a further solution of the present invention, based on the water use pattern analysis results, the water demand at multiple times is analyzed and predicted, the pressure and flow of the secondary water supply are calculated and adjusted, and the stability of the water supply pressure is optimized by matching the predicted demand. The steps of obtaining the water demand matching result are specifically as follows:

[0026] S301: predicting the water demand of residents in multiple time periods according to the water use pattern analysis results, analyzing the water supply demand in multiple time periods in combination with the real-time water pressure data, and generating predicted water demand data;

[0027] S302: Analyze the predicted water demand data, consider the continuity and stability of the secondary water supply, calculate the secondary water supply pressure and flow parameters that need to be adjusted, and form pressure and flow adjustment parameters;

[0028] S303: According to the pressure and flow adjustment parameters, the pressure and flow of the secondary water supply are adjusted, and the adjusted pressure and flow data are monitored in real time to generate a water demand matching result.

[0029] As a further solution of the present invention, based on the water demand matching result, by analyzing the relationship between the operating power, temperature, operating time and operating efficiency of the water pump, the energy efficiency ratio of the water pump under various powers is evaluated, and the steps of generating the water pump efficiency analysis result are specifically as follows:

[0030] S401: Based on the water demand matching result, collect the operating power and operating time data of the water pump in multiple time periods, and record the operating temperature data to generate a water pump operation data set;

[0031] S402: Based on the water pump operation data set, analyze the impact of ambient temperature and operation time on the water supply operation efficiency and power consumption of the water pump to generate environmental impact analysis data;

[0032] S403: Evaluate the water pump operation energy efficiency ratio at various power levels according to the environmental impact analysis data, and generate a water pump efficiency analysis result.

[0033] As a further solution of the present invention, based on the water pump efficiency analysis result, by comparing the water pump energy consumption under various water level range settings, considering the actual water demand of residents, calculating the water tower water storage level, and generating the water level calculation result in the following steps:

[0034] S501: According to the water pump efficiency analysis result, collect and analyze the power consumption and operation time data of the water pump under various water tower water storage levels to generate water level energy consumption data;

[0035] S502: Based on the water level energy consumption data, analyzing the energy efficiency ratio of the water pump operation under various water levels, calculating the power consumption and water supply efficiency of various water level settings, and generating an energy efficiency ratio analysis result;

[0036] S503: Based on the energy efficiency ratio analysis result and in combination with the actual water demand comparison of residents, the optimal water tower water storage level configuration parameters are calculated to obtain the water level calculation result.

[0037] As a further solution of the present invention, according to the water level calculation result, combined with the prediction result of residents' water demand, the operation schedule and power parameters of the water pump are adjusted to match the residents' water demand in multiple time periods, and the steps of generating the water supply equipment control parameters are specifically as follows:

[0038] S601: According to the water level calculation result, combined with the residents' water demand forecast result, by analyzing the water demand in multiple time periods, the water pump operation time and power parameters that need to be adjusted are calculated, and the adjustment demand analysis result is generated;

[0039] S602: According to the adjustment demand analysis result, the start and stop time of the water pump is adjusted to match the water supply and water pressure demand during the peak and valley periods of water use, and a water pump operation schedule is obtained;

[0040] S603: Based on the water pump operation schedule, the start and stop time and the operating power parameters of the water pump are adjusted and executed to generate water supply equipment control parameters.

[0041] A remote monitoring system for secondary water supply equipment, the remote monitoring system for secondary water supply equipment is used to execute the remote monitoring method for secondary water supply equipment, the system comprising:

[0042] The energy consumption data collection module collects the operation log of the water supply equipment, identifies the current and voltage data, uses the water pressure sensor to collect the water pressure information at multiple locations, and generates energy consumption and water pressure collection information;

[0043] The residential water use analysis module performs time series analysis on the water pressure data based on the energy consumption and water pressure collection information, identifies seasonal changes in residential water use, predicts water demand at multiple times, calculates and adjusts the pressure and flow of secondary water supply, and generates secondary water supply pressure parameters;

[0044] The operation efficiency evaluation module analyzes the relationship between the temperature, operation time and operation efficiency of the water pump under various operation powers based on the secondary water supply pressure parameter, evaluates the energy efficiency ratio of the water pump under various power settings, and generates water pump energy efficiency ratio information;

[0045] The water level setting comparison module compares the energy consumption under various water level settings based on the water pump energy efficiency ratio information, calculates the optimal water tower water storage level in combination with the actual water demand, and generates water level parameter analysis data;

[0046] The water supply parameter adjustment module adjusts the water pump operation schedule and power parameters based on the water level parameter analysis data, matches the water demand of residents in multiple time periods, and generates water supply equipment control parameters.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In the present invention, by real-time analysis of the operating current and voltage of the water supply equipment and monitoring the water pressure data of multiple locations, the energy consumption and water pressure changes of the water supply equipment are evaluated in real time. Combined with the time series analysis of the water use data, the seasonal changes in water use are effectively identified, the adjustment of the water supply pressure and flow is optimized and matched with the water use needs of the residents, the response speed and stability of the secondary water supply are improved, and by analyzing the operating power of the water pump and the water level setting, the energy efficiency ratio of the water pump under various operating conditions is evaluated, the energy use is optimized, and the operating efficiency and reliability of the secondary water supply equipment are improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0050] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0051] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0052] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0053] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0054] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0055] Figure 7 This is a detailed flow chart of S6 of the present invention;

[0056] Figure 8 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with 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.

[0058] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0059] See also Figure 1 The present invention provides a technical solution, a remote monitoring method for secondary water supply equipment, comprising the following steps:

[0060] S1: Based on the operation log of water supply equipment, the energy consumption of multiple water supply equipment is analyzed through current and voltage data, and water pressure data at multiple locations are collected using water pressure sensors to generate energy consumption and water pressure data sets;

[0061] S2: Based on the energy consumption and water pressure data sets, time series analysis of water pressure data is performed to identify seasonal changes in residents’ water use and form water use pattern analysis results;

[0062] S3: Based on the water use pattern analysis results, analyze and predict the water demand at multiple times, calculate and adjust the pressure and flow of the secondary water supply, match the predicted demand to optimize the stability of the water supply pressure, and obtain the water demand matching result;

[0063] S4: Based on the water demand matching results, the relationship between the operating power, temperature, operating time and operating efficiency of the water pump is analyzed to evaluate the energy efficiency ratio of the water pump under various powers and generate the water pump efficiency analysis results;

[0064] S5: Based on the results of the water pump efficiency analysis, by comparing the water pump energy consumption under various water level range settings, considering the actual water demand of residents, calculating the water tower storage level, and generating the water level calculation results;

[0065] S6: According to the water level calculation results and combined with the predicted results of residents’ water demand, the operation schedule and power parameters of the water pump are adjusted to match the residents’ water demand in multiple time periods and generate the water supply equipment control parameters.

[0066] The energy consumption and water pressure data sets include current peak data, minimum voltage data, and average water pressure information. The water use pattern analysis results include peak water use periods, low-peak water use periods, and seasonal water use change prediction results. The water demand matching results include water supply pressure adjustment results, water supply flow setting parameters, and expected water demand matching degree. The water pump efficiency analysis results include water pump energy efficiency ratio information under various power levels, analysis results of the impact of operating temperature on operating efficiency, and analysis results of the impact of operating time on operating efficiency. The water level calculation results include water level range setting parameters, water pump operating cost analysis results, and water supply equipment energy consumption prediction information. The water supply equipment control parameters include water pump operation schedule, power parameter settings, and water pump start and stop records.

[0067] See also Figure 2 ,Based on the operation log of water supply equipment, the energy consumption of multiple water supply equipment is analyzed through current and voltage data, and water pressure data at multiple locations are collected using water pressure sensors. The specific steps for generating energy consumption and water pressure data sets are as follows:

[0068] S101: Based on the water supply equipment operation log, the current and voltage change data of the equipment are collected and recorded in real time, and the specific process of generating current and voltage monitoring data is as follows;

[0069] In sub-step S101, based on the water supply equipment operation log, the current and voltage change data of the equipment are collected and recorded in real time, the current and voltage data are monitored, and the current and voltage signals are captured by an analog-to-digital converter. After the high-frequency noise is eliminated by a low-pass filter, the average current and voltage per minute are calculated to reduce the impact of data noise on the monitoring results. The voltage and current real-time monitoring formula is used: P z (t) = I z (t)·V z (t), where I z (t) is the current value at time t, V z (t) is the voltage value at time t, P z (t) represents the power consumption at time t, monitors the energy consumption status of the equipment in real time, and generates current and voltage monitoring data.

[0070] S102: deploying water pressure sensors at multiple key nodes of the water supply system according to the current and voltage monitoring data, collecting water pressure values ​​at multiple locations in real time, and generating water pressure data collection results in the following specific process;

[0071] In sub-step S102, according to the current and voltage monitoring data, water pressure sensors are deployed at multiple key nodes of the water supply system to collect water pressure values ​​at multiple locations in real time. Pressure sensors are installed at the inlet, outlet, and bend of the water supply pipeline. The output of each sensor is continuously monitored and sent to the central monitoring system via a wireless network. The water pressure monitoring formula is: B z (t) = ρ z ·g z ·h z (t), where B z (t represents the water pressure at time t, ρ z is the density of water, g z is the acceleration due to gravity, h z (t) is the height of the water column, which monitors the pressure changes inside the water supply system in real time, provides data support for maintenance and fault prevention, and generates water pressure data collection results.

[0072] S103: Based on the water pressure data collection result, the energy consumption of the water supply equipment is calculated through the current and voltage data, and the water pressure data and the energy consumption data are formatted, and the time information is recorded. The specific process of generating the energy consumption and water pressure data sets is as follows;

[0073] In sub-step S103, based on the water pressure data collection results, the energy consumption of the water supply equipment is calculated through the current and voltage data. According to the current and voltage data, combined with the time factor, the cumulative energy consumption of multiple time periods is calculated. The water pressure data is combined with the energy consumption data, and the energy consumption calculation formula is adopted: E z =∫I z (t)·V z (t)dt, where E z is the total energy consumption, I z (t) is the current value at time t, V z (t) is the voltage value at time t, dt is the differential form of the time interval, and the time is integrated after integration to express the accumulation of energy consumption over time. The calculation results are formatted and key time information is recorded, including the data collection time point and data processing timestamp, to ensure the integrity and traceability of the data and generate energy consumption and water pressure data sets.

[0074] See also Figure 3 ,Based on the energy consumption and water pressure data sets, the time series analysis of water pressure data is carried out to identify the seasonal changes in residents' water use. The specific steps to form the water use pattern analysis results are as follows:

[0075] S201: Based on the energy consumption and water pressure data sets, collect and analyze residents' historical water use data, including water consumption and water use time information, and generate the historical water use information in the following process:

[0076] In sub-step S201, based on the energy consumption and water pressure data sets, the historical water use data of residents, including water consumption and water use time information, is collected and analyzed. By monitoring the water consumption at the water outlet and recording the start and end time of each water use, the data is cleaned and normalized to exclude interference data of non-residential water use. The normalization formula is: Among them, Q x represents the target time t x of water consumption, is the average water consumption, is the standard deviation of water consumption, Q′ x For the standardized water consumption, the water consumption behaviors of multiple periods and multiple users are compared to generate historical water consumption information.

[0077] S202: Based on historical water use information, an autoregressive moving average model is used to analyze residential water use data to identify periodic change patterns of water use fluctuations, including peak and valley values ​​of water use. The specific process of generating periodic fluctuation information is as follows;

[0078] In sub-step S202, based on historical water use information, the autoregressive moving average model is used to analyze residents' water use data, identify the periodic change pattern of water use fluctuations, predict fluctuations in future time periods by calculating past water use data, identify periodic water use fluctuations, predict water use peaks and valleys, and generate periodic fluctuation information.

[0079] The autoregressive moving average model follows the formula:

[0080]

[0081] Calculate water demand, where X t is the water consumption at the current time point, which is used to represent the water consumption status at the target time. c is a constant term used to adjust the model to match the baseline water consumption. t is the error term, which represents the random deviation between the model prediction and the actual observation, φ i is the autoregressive coefficient, which is used to describe the impact of the water consumption at the previous i time points on the current water consumption. t-i is the water consumption at time point ti, which is used to influence the current water consumption prediction through the autoregressive coefficient, θ i is the moving average coefficient, which is used to smooth the impact of the error term and enhance the stability of the model, ∈ t-i is the error value at time point ti, which indicates the impact of past errors on the current prediction. p is the order of autoregression, which is used to determine how much historical water consumption data is considered in the model. q is the order of moving average, which is used to determine how much historical error data is considered in the model. β is the temperature influence coefficient, which is used to measure the impact of ambient temperature on water consumption. T t is the average temperature at the current time point, which is used to adjust the water demand forecast through the temperature influence coefficient. γ is the seasonal influence coefficient, which is used to adjust the impact of different seasons on water demand. t It is a seasonal indicator used to describe the water use characteristics of different seasons. t is the current moment, which is used to indicate the specific time point at which prediction or calculation is being performed. i is the lag period, which is used to measure the time interval of historical data points considered in autoregression and moving average calculations. ti is the current moment minus the i moment, which is used to obtain the data at the i-th time point before the t moment.

[0082] The specific execution process of the formula is as follows:

[0083] By analyzing historical water consumption data records and associated ambient temperature data, the water consumption and average temperature at each time point are obtained. Based on the historical data of water consumption and temperature, regression analysis is performed to determine the coefficients of autoregression and moving average, and the influence coefficients of temperature and season. The parameters are substituted into the model to calculate the predicted water consumption at each future time point, which is used to optimize the water supply management strategy and adjust the operating parameters of the water supply facilities.

[0084] S203: Analyze abnormal fluctuations and peak consumption in water use patterns according to periodic fluctuation information, identify seasonal changes and water use patterns during multiple holidays, and form a water use pattern analysis result. The specific process is as follows;

[0085] In sub-step S203, based on the periodic fluctuation information, the abnormal fluctuations and peak consumption in the water use pattern are analyzed, and the seasonal changes and water use patterns of multiple holidays are identified. By analyzing the periodic fluctuation information, the water use increase and decrease trends during the target holidays and seasonal changes are determined. The data analysis tools are used to detect and confirm the target changes and calculate the seasonal water use changes. The formula is: ΔW x =γ z (W x -W avg ), where ΔW x represents the seasonal variation, γ z is the seasonal adjustment factor, W x is the standardized water consumption during the current investigation period, W avg The standardized average water consumption is used to identify the changes in water consumption in different time periods and form the water consumption pattern analysis results.

[0086] See also Figure 4 Based on the water use pattern analysis results, analyze and predict the water demand at multiple times, calculate and adjust the pressure and flow of the secondary water supply, match the predicted demand to optimize the stability of the water supply pressure, and obtain the water demand matching results in the following steps:

[0087] S301: According to the water use pattern analysis results, the water demand of residents in multiple time periods is predicted, and the water supply demand in multiple time periods is analyzed in combination with the real-time water pressure data, and the specific process of generating predicted water demand data is as follows;

[0088] In step S301, based on the water use pattern analysis results, the water demand of residents in multiple time periods is predicted, combined with the real-time water pressure data P c , the water supply demand in different time periods is estimated through the forecasting model, and the future demand is predicted based on the past water use pattern and the current water pressure situation using the linear regression model to ensure the practicality and accuracy of the forecast results. The formula for predicting water demand is: D c =β c1 P c +β c2 T c +∈ c , where D c represents the predicted water demand, P c Indicates the real-time water pressure, T c is a time variable, reflecting the changing trend of water demand in different time periods, β c1is the regression coefficient related to water pressure, quantifying the impact of water pressure changes on water demand, β c2 is the time-related regression coefficient, describing the rate of change of water demand over time, ∈ c It is the error term, which represents the random fluctuation in the prediction. It analyzes the impact of water pressure changes on water demand, combines the analysis of historical data to improve the prediction accuracy, and generates predicted water demand data.

[0089] S302: Analyze and predict water demand data, consider the continuity and stability of secondary water supply, calculate the secondary water supply pressure and flow parameters that need to be adjusted, and form the pressure and flow adjustment parameters. The specific process is as follows;

[0090] In sub-step S302, water demand data is analyzed and predicted, the continuity and stability of the secondary water supply are considered, the secondary water supply pressure and flow parameters that need to be adjusted are calculated, and the water supply parameters that need to be adjusted are determined using a dynamic adjustment formula to ensure the balance and efficiency of the water supply system. The calculation formula for the pressure and flow adjustment parameters is: F c =κ c1 D pred,c +κ c2 S c , where F c is the adjusted flow parameter, D pred,c is the predicted water demand, S c is the current state of the system, including known water pressure and flow, κ c1 is the demand adjustment coefficient, which is used to convert the predicted water demand to the actual flow adjustment ratio, κ c2 It is the system status adjustment coefficient, which is used to adjust the water supply flow according to the current operating status of the system, optimize the stability of the water supply system, and form the pressure flow adjustment parameters.

[0091] S303: According to the pressure and flow adjustment parameters, the pressure and flow of the secondary water supply are adjusted, and the adjusted pressure and flow data are monitored in real time to generate a water demand matching result. The specific process is as follows;

[0092] In sub-step S303, the pressure P of the secondary water supply is adjusted according to the pressure flow adjustment parameter. adj,c and flow rate F adj,c , and monitor the adjusted pressure and flow data in real time, and use a real-time monitoring system to ensure the effectiveness of the adjustment measures. The formula is: R c =λ c1 P adj,c +λ c2 F adj,c , where R c Represents the monitoring results, which are used to evaluate the implementation effect of adjustment measures. adj,cThe adjusted pressure ensures that the water supply system maintains appropriate water pressure under changing demand. adj,c is the adjusted flow rate to match the water demand in different time periods, λ c1 and λ c2 In order to monitor the sensitivity coefficient, the sensitivity of pressure and flow adjustment is quantified respectively. The matching degree of water supply parameter adjustment is ensured through real-time monitoring, and the water demand matching result is generated.

[0093] See also Figure 5 Based on the water demand matching results, the energy efficiency ratio of the water pump under various powers is evaluated by analyzing the relationship between the operating power, temperature, operating time and operating efficiency of the water pump. The specific steps for generating the water pump efficiency analysis results are as follows:

[0094] S401: Based on the water demand matching result, the operation power and operation time data of the water pump in multiple time periods are collected, and the operation temperature data is recorded to generate the water pump operation data set. The specific process is as follows;

[0095] In sub-step S401, based on the water demand matching result, the operating power P of the water pump in multiple time periods is collected. v and runtime t v Data, and record the operating temperature data T v , automatically monitors each time the water pump starts and stops, the power and temperature of continuous operation. The data is collected in real time through sensors and sent to the central database for aggregation and storage. The daily operation status of the water pump is monitored. The data set records the performance and environmental conditions of the water pump in each time period, providing a data basis for efficiency and power consumption analysis, and generating a water pump operation data set.

[0096] S402: Based on the water pump operation data set, the impact of ambient temperature and operation time on the water pump water supply operation efficiency and power consumption is analyzed, and the specific process of generating environmental impact analysis data is as follows;

[0097] In sub-step S402, based on the water pump operation data set, the ambient temperature T v and runtime t v The impact on the water supply operation efficiency and power consumption of the water pump is used to generate environmental impact analysis data. Regression analysis is used to evaluate the impact of temperature and operating time on power consumption. The formula is: E v =α v P v +β v T v +γ v t v +∈ v , where E v is the energy consumption, α v , β v and γ vare the regression coefficients of power, temperature and time, ∈ v The error term is used to identify the energy efficiency and power consumption of the water pump under differentiated environmental conditions and operating strategies, provide a data basis for optimizing operating conditions, and generate environmental impact analysis data.

[0098] S403: According to the environmental impact analysis data, the energy efficiency ratio of the water pump operation at various power levels is evaluated, and the process of generating the water pump efficiency analysis result is specifically as follows;

[0099] In sub-step S403, based on the environmental impact analysis data, the energy efficiency ratio of the water pump operation at various power levels is evaluated, and the optimal operating conditions and configuration are calculated by calculating the energy efficiency ratio at differentiated power levels. The formula is: Among them, η v is the energy efficiency ratio of the water pump, P out,v is the output power, E v For energy consumption, by comparing the energy efficiency ratio under differentiated power settings, the most energy-saving operation mode and power setting are identified, providing a data basis for the daily management and maintenance of the water pump and generating water pump efficiency analysis results.

[0100] See also Figure 6 Based on the results of the water pump efficiency analysis, by comparing the water pump energy consumption under various water level range settings, considering the actual water demand of residents, the water tower water storage level is calculated, and the steps to generate the water level calculation results are as follows:

[0101] S501: According to the results of the water pump efficiency analysis, the power consumption and operation time data of the water pump under various water tower water storage levels are collected and analyzed, and the specific process of generating water level energy consumption data is as follows;

[0102] In sub-step S501, based on the results of the water pump efficiency analysis, the power consumption and operating time data of the water pump under various water tower water storage levels are collected and analyzed. By installing water level sensors and energy consumption monitoring equipment, the operating status of the water pump under differentiated water level conditions is recorded in real time, including the highest and lowest water levels, power consumption and operating time in each test cycle. A correlation model between water level and energy consumption is established, the impact of different water level settings on energy consumption is evaluated, and water level energy consumption data is generated.

[0103] S502: Based on the water level energy consumption data, the energy efficiency ratio of the water pump operation under various water levels is analyzed, the power consumption and water supply efficiency of various water level settings are calculated, and the process of generating the energy efficiency ratio analysis result is specifically as follows;

[0104] In sub-step S502, based on the water level energy consumption data, the energy efficiency ratio of the water pump operation under various water levels is analyzed, and the power consumption P of various water level settings is calculated. b And water supply efficiency, the energy efficiency ratio analysis method is used to evaluate the performance under different water level conditions, and the calculation formula is: Among them, η b is the energy efficiency ratio, Q b is the amount of water provided by the pump at the target water level, E b For the corresponding energy consumption, determine the power consumption and efficiency under various water level settings, identify the most economical operating water level, optimize the operating configuration of the pump, and generate energy efficiency analysis results.

[0105] S503: Based on the energy efficiency ratio analysis results and in combination with the actual water demand comparison of residents, the optimal water tower water storage level configuration parameters are calculated to obtain the water level calculation results. The specific process is as follows;

[0106] In sub-step S503, based on the energy efficiency analysis results and combined with the actual water demand of residents, the optimal water tower water storage level configuration parameters are calculated to obtain the water level calculation results, and the optimal water level range is determined using the linear optimization model to balance energy efficiency and meet water demand: L b = arg min(C b ·E b -U b Q b ), where L b is the optimal water level setting, C b is the unit energy cost, E b is energy consumption, U b is the user satisfaction per unit water volume, Q b In order to supply water, optimize operating costs and user satisfaction, the water level setting is adjusted to achieve the optimal operating efficiency based on actual water usage data and energy efficiency ratio analysis, and the water level calculation results are obtained.

[0107] See also Figure 7 According to the water level calculation results, combined with the predicted results of residents' water demand, the operation schedule and power parameters of the water pump are adjusted to match the residents' water demand in multiple time periods. The specific steps of generating the control parameters of the water supply equipment are as follows:

[0108] S601: Based on the water level calculation result and the predicted result of the water demand of residents, the water demand of multiple time periods is analyzed, and the operation time and power parameters of the water pump that need to be adjusted are calculated, and the process of generating the adjustment demand analysis result is specifically as follows;

[0109] In sub-step S601, based on the water level calculation results and the predicted results of residents' water demand, the water pump operation time t that needs to be adjusted is calculated by analyzing the water demand in multiple time periods. q And power parameter P q Based on the difference between predicted and actual water demand, the operating time and power setting are calculated to ensure the balance between efficiency and water supply demand. The calculation formula for adjusting demand is: ΔP q =K q (D pred,q -Dact,q ), Among them, ΔP q is the power difference that needs to be adjusted, K q is the adjustment coefficient, which is set according to the elasticity of water demand, D pred,q is the predicted water demand, D act,q is the actual water demand, Δt q To correspond to the running time that needs to be adjusted, P base,q and T base,q They are the benchmark power and benchmark operating time respectively. By adjusting the operating time and power of the water pump to match the changes in water demand, the operating efficiency and energy utilization efficiency of the water pump are improved, and the adjustment demand analysis results are generated.

[0110] S602: According to the adjustment demand analysis result, the start and stop time of the water pump is adjusted to match the water supply and water pressure demand during the peak and valley periods of water use, and the specific process of obtaining the water pump operation schedule is as follows;

[0111] In sub-step S602, according to the adjustment demand analysis results, the start and stop time of the water pump is adjusted to match the water supply and water pressure requirements during the peak and valley periods. The adjusted operating time and power parameters are used to formulate an operating schedule to optimize water supply and energy efficiency. The formula is: T op,q =T base,q +Δt q , where T op,q is the adjusted pump running time, T base,q is the original basic running time, Δt q In order to adjust the time difference based on water demand, the start and stop time of the water pump in different water demand periods is calculated to obtain the water pump operation schedule.

[0112] S603: Based on the water pump operation schedule, the start and stop time and the operating power parameters of the water pump are adjusted and executed, and the process of generating the water supply equipment control parameters is specifically as follows;

[0113] In sub-step S603, based on the water pump operation schedule, the start and stop time and operating power parameters of the water pump are adjusted and executed. By adjusting the control system, it is ensured that the water pump operation parameters match the schedule. The adjustment formula of the water supply equipment control parameters is: P ctrl,q =P base,q +ΔP q , where P ctrl,q is the adjusted control power, P base,q is the basic power, ΔP q The power difference that needs to be adjusted is used to ensure that the operating power of the water pump matches the operating requirements, optimize energy efficiency and meet the water needs of residents, and generate water supply equipment control parameters.

[0114] See also Figure 8 A remote monitoring system for secondary water supply equipment is provided. The remote monitoring system for secondary water supply equipment is used to execute the remote monitoring method for secondary water supply equipment. The system comprises:

[0115] The energy consumption data collection module collects the operation log of the water supply equipment, identifies the current and voltage data, uses the water pressure sensor to collect the water pressure information at multiple locations, and generates energy consumption and water pressure collection information;

[0116] The residential water use analysis module performs time series analysis on water pressure data based on energy consumption and water pressure collection information, identifies seasonal changes in residential water use, predicts water demand at multiple times, calculates and adjusts the pressure and flow of secondary water supply, and generates secondary water supply pressure parameters;

[0117] The operation efficiency evaluation module analyzes the relationship between the temperature, operation time and operation efficiency of the water pump under various operation powers based on the secondary water supply pressure parameter, evaluates the energy efficiency ratio of the water pump under various power settings, and generates water pump energy efficiency ratio information;

[0118] The water level setting comparison module compares the energy consumption under various water level settings based on the water pump energy efficiency ratio information, calculates the optimal water tower storage level based on the actual water demand, and generates water level parameter analysis data;

[0119] The water supply parameter adjustment module adjusts the water pump operation schedule and power parameters based on water level parameter analysis data, matches the water demand of residents in multiple time periods, and generates water supply equipment control parameters.

[0120] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. A remote monitoring method for secondary water supply equipment, characterized in that: The following steps are involved: Based on the operation logs of water supply equipment, the energy consumption of multiple water supply equipment is analyzed through current and voltage data, and water pressure data at multiple locations are collected using water pressure sensors to generate energy consumption and water pressure data sets; Based on the energy consumption and water pressure data sets, time series analysis is performed on the water pressure data to identify seasonal changes in residents' water use and form water use pattern analysis results; Based on the water use pattern analysis results, the water demand at multiple times is analyzed and predicted, the pressure and flow of the secondary water supply are calculated and adjusted, the stability of the water supply pressure is optimized by matching the predicted demand, and a water demand matching result is obtained; Based on the water demand matching result, by analyzing the relationship between the operating power, temperature, operating time and operating efficiency of the water pump, the energy efficiency ratio of the water pump under various powers is evaluated to generate a water pump efficiency analysis result; Based on the water pump efficiency analysis result, by comparing the water pump energy consumption under various water level range settings, considering the actual water demand of residents, calculating the water tower water storage level, and generating a water level calculation result; According to the water level calculation results, combined with the predicted results of residents' water demand, the operation schedule and power parameters of the water pump are adjusted to match the residents' water demand in multiple time periods and generate water supply equipment control parameters.

2. The remote monitoring method for secondary water supply equipment according to claim 1, characterized in that: The energy consumption and water pressure data set includes current peak data, minimum voltage data, and average water pressure information; the water use pattern analysis results include peak water use periods, low-peak water use periods, and seasonal water use change prediction results; the water demand matching results include water supply pressure adjustment results, water supply flow setting parameters, and expected water demand matching degree; the water pump efficiency analysis results include water pump energy efficiency ratio information under multiple power levels, analysis results of the impact of operating temperature on operating efficiency, and analysis results of the impact of operating time on operating efficiency; the water level calculation results include water level range setting parameters, water pump operating cost analysis results, and water supply equipment energy consumption prediction information; the water supply equipment control parameters include water pump operation schedule, power parameter settings, and water pump start and stop records.

3. The remote monitoring method for secondary water supply equipment according to claim 1, characterized in that: Based on the operation log of water supply equipment, the energy consumption of multiple water supply equipment is analyzed through current and voltage data, and water pressure data at multiple locations are collected using water pressure sensors. The specific steps for generating energy consumption and water pressure data sets are as follows: Based on the water supply equipment operation log, the current and voltage change data of the equipment are collected and recorded in real time to generate current and voltage monitoring data; Based on the current and voltage monitoring data, water pressure sensors are deployed at multiple key nodes of the water supply system to collect water pressure values ​​at multiple locations in real time and generate water pressure data collection results; Based on the water pressure data collection results, the energy consumption of the water supply equipment is calculated through the current and voltage data, and the water pressure data and energy consumption data are formatted, and the time information is recorded to generate energy consumption and water pressure data sets.

4. The remote monitoring method for secondary water supply equipment according to claim 1, characterized in that: Based on the energy consumption and water pressure data sets, the steps of performing time series analysis on the water pressure data, identifying seasonal changes in residents' water use, and forming water use pattern analysis results are as follows: Based on the energy consumption and water pressure data sets, collect and analyze residents' historical water use data, including water consumption and water use time information, to generate historical water use information; Based on the historical water use information, an autoregressive moving average model is used to analyze the residential water use data, identify the periodic change pattern of water use fluctuations, including peak and valley values ​​of water use, and generate periodic fluctuation information; According to the periodic fluctuation information, abnormal fluctuations and peak consumption in the water use pattern are analyzed, seasonal changes and water use patterns during multiple holidays are identified, and water use pattern analysis results are formed.

5. The remote monitoring method for secondary water supply equipment according to claim 4, characterized in that: The autoregressive moving average model is based on the formula: Calculate water demand, where X t is the water consumption at the current time point, c is a constant term, ∈ t is the error term, φ i is the autoregression coefficient, X t-i is the water consumption at time ti, θ i is the moving average coefficient, ∈ t-i is the error value at time point ti, p is the order of autoregression, q is the order of moving average, β is the influence coefficient of temperature, T t is the average temperature at the current time point, γ is the seasonal influence coefficient, S t is a seasonal indicator, t is the current moment, i is the lag period, and ti is the current moment minus the i moment.

6. The remote monitoring method for secondary water supply equipment according to claim 1, characterized in that: Based on the water use pattern analysis results, the water demand at multiple times is analyzed and predicted, the pressure and flow of the secondary water supply are calculated and adjusted, and the stability of the water supply pressure is optimized by matching the predicted demand. The specific steps of obtaining the water demand matching result are as follows: Based on the water use pattern analysis results, the water demand of residents in multiple time periods is predicted, and the water supply demand in multiple time periods is analyzed in combination with the real-time water pressure data to generate predicted water demand data; Analyze the predicted water demand data, consider the continuity and stability of the secondary water supply, calculate the secondary water supply pressure and flow parameters that need to be adjusted, and form pressure and flow adjustment parameters; According to the pressure and flow adjustment parameters, the pressure and flow of the secondary water supply are adjusted, and the adjusted pressure and flow data are monitored in real time to generate a water demand matching result.

7. The remote monitoring method for secondary water supply equipment according to claim 1, characterized in that: Based on the water demand matching result, by analyzing the relationship between the operating power, temperature, operating time and operating efficiency of the water pump, the energy efficiency ratio of the water pump under various powers is evaluated, and the steps of generating the water pump efficiency analysis result are specifically as follows: Based on the water demand matching result, collect the operating power and operating time data of the water pump in multiple time periods, and record the operating temperature data to generate a water pump operation data set; Based on the water pump operation data set, analyzing the impact of ambient temperature and operation time on the water supply operation efficiency and power consumption of the water pump, and generating environmental impact analysis data; Based on the environmental impact analysis data, the energy efficiency ratio of water pump operation at various power levels is evaluated to generate water pump efficiency analysis results.

8. The remote monitoring method for secondary water supply equipment according to claim 1, characterized in that: Based on the pump efficiency analysis results, by comparing the pump energy consumption under various water level range settings, considering the actual water demand of residents, calculating the water tower water storage level, the steps of generating the water level calculation results are as follows: According to the water pump efficiency analysis results, collect and analyze the power consumption and operation time data of the water pump under various water tower water storage levels to generate water level energy consumption data; Based on the water level energy consumption data, analyzing the energy efficiency ratio of the water pump operation under various water levels, calculating the power consumption and water supply efficiency of various water level settings, and generating energy efficiency ratio analysis results; Based on the energy efficiency ratio analysis results and in combination with the actual water demand comparison of residents, the optimal water tower water storage level configuration parameters are calculated to obtain the water level calculation results.

9. The remote monitoring method for secondary water supply equipment according to claim 1, characterized in that: According to the water level calculation results, combined with the predicted results of residents' water demand, the operation schedule and power parameters of the water pump are adjusted to match the residents' water demand in multiple time periods, and the steps of generating the water supply equipment control parameters are specifically as follows: According to the water level calculation results, combined with the residents' water demand forecast results, by analyzing the water demand in multiple time periods, the water pump operation time and power parameters that need to be adjusted are calculated to generate adjustment demand analysis results; According to the adjustment demand analysis results, the start and stop time of the water pump is adjusted to match the water supply and water pressure demand during the peak and valley water consumption periods to obtain a water pump operation schedule; Based on the water pump operation schedule, the start and stop time and the operation power parameters of the water pump are adjusted and executed to generate water supply equipment control parameters.

10. A remote monitoring system for secondary water supply equipment, characterized in that: According to any one of claims 1 to 9, the remote monitoring method for secondary water supply equipment comprises: The energy consumption data collection module collects the operation log of the water supply equipment, identifies the current and voltage data, uses the water pressure sensor to collect the water pressure information at multiple locations, and generates energy consumption and water pressure collection information; The residential water use analysis module performs time series analysis on the water pressure data based on the energy consumption and water pressure collection information, identifies seasonal changes in residential water use, predicts water demand at multiple times, calculates and adjusts the pressure and flow of secondary water supply, and generates secondary water supply pressure parameters; The operation efficiency evaluation module analyzes the relationship between the temperature, operation time and operation efficiency of the water pump under various operation powers based on the secondary water supply pressure parameter, evaluates the energy efficiency ratio of the water pump under various power settings, and generates water pump energy efficiency ratio information; The water level setting comparison module compares the energy consumption under various water level settings based on the water pump energy efficiency ratio information, calculates the optimal water tower water storage level in combination with the actual water demand, and generates water level parameter analysis data; The water supply parameter adjustment module adjusts the water pump operation schedule and power parameters based on the water level parameter analysis data, matches the water demand of residents in multiple time periods, and generates water supply equipment control parameters.

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