Water hammer effect real-time monitoring method and device

Abstract

The invention discloses a water hammer effect real-time monitoring method and device, and belongs to the technical field of water hammer effect parameter analysis, and the method comprises the steps: collecting key parameter data in a pipeline and on-off state data of key equipment in real time, and calculating a pipe network abnormity evaluation value; according to the size of the anomaly evaluation value, judging an anomaly level; when the abnormal grade is a high grade, evaluating the occurrence possibility of the water hammer effect by adopting a numerical simulation method; when the abnormal level is low, evaluating the occurrence possibility of the water hammer effect by adopting a characteristic parameter judgment method; and sending early warning information according to the occurrence possibility of the water hammer effect. According to the method, the abnormal evaluation value of the pipe network is calculated by monitoring the key parameters in the pipeline and the on-off state of the equipment in real time, and the occurrence possibility of the water hammer effect is judged by adopting different evaluation methods according to the abnormal level, so that early warning information is sent in time, and the safety and reliability of a pipeline system are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water hammer effect parameter analysis, and in particular to a real-time monitoring method and device for water hammer effect. Background Art

[0002] With the rapid development of computer technology and sensor technology, data monitoring and analysis are increasingly used in various fields. Especially in liquid pipeline systems, water hammer effect is a common and potentially harmful problem, and its real-time monitoring and early warning technology has become a research hotspot.

[0003] Traditional water hammer effect monitoring methods often rely on manual inspections and regular testing, which is not only inefficient but also difficult to detect and deal with potential risks in a timely manner. With the increasing complexity and scale of pipeline systems, traditional methods have been unable to meet the needs of real-time monitoring and early warning. How to use computer technology and sensor technology to achieve automated monitoring and early warning of water hammer effect has become an urgent problem to be solved. Summary of the invention

[0004] To solve the above problems, the present invention provides a real-time monitoring method and device for water hammer effect, which calculates the abnormal evaluation value of the pipeline network by real-time monitoring of key parameters and the switch status of equipment in the pipeline, and uses different evaluation methods according to the abnormal level to judge the possibility of water hammer effect, so as to send early warning information in time and improve the safety and reliability of the pipeline system.

[0005] The above objectives can be achieved through the following solutions: A real-time monitoring method for water hammer effect comprises: collecting key parameter data in a pipeline in real time to obtain a numerical parameter set, and collecting switch status data of key equipment in real time to obtain a state parameter set; calculating a pipe network abnormality assessment value by using the numerical parameter set and the state parameter set; judging the abnormality level according to the magnitude of the abnormality assessment value; when the abnormality level is high, using a numerical simulation method to assess the possibility of water hammer effect; when the abnormality level is low, using a characteristic parameter judgment method to assess the possibility of water hammer effect; and sending an early warning message according to the possibility of water hammer effect.

[0006] Optionally, the real-time collection of key parameter data in the pipeline to obtain a set of numerical parameters includes: collecting vibration intensity data of the pipeline and performing normalization processing to obtain a vibration standard value; judging whether the vibration standard value is greater than a preset first threshold value; if so, starting data collection and evaluating the possibility of water hammer effect; if not, not starting the evaluation process.

[0007] Optionally, the real-time acquisition of key parameter data in the pipeline to obtain a set of numerical parameters also includes: real-time acquisition of key parameter data in the pipeline, and adding it to a preset basic data set; preprocessing the basic data set; using the data in the preprocessed basic data set to calculate the mean of the key parameters; using the preprocessed basic data set and the mean of the key parameters to calculate the standard deviation of the key parameters; using the current key parameter data, the mean of the key parameters, and the standard deviation of the key parameters to calculate the standard value of the key parameters, and for the standard value ,have , In the formula, is the current key parameter data, is the mean value of the key parameter, is the standard deviation of the key parameters; the standard values ​​of each key parameter are integrated to obtain a set of numerical parameters.

[0008] Optionally, the real-time acquisition of switch status data of key equipment to obtain a state parameter set includes: real-time acquisition of switch status data of key equipment to obtain a state data set; defining digitization rules, and digitizing the status data according to the digitization rules to obtain state values ​​of key equipment; integrating the state values ​​of each key equipment to obtain a state parameter set.

[0009] Optionally, the calculating of the pipe network abnormality evaluation value by using the numerical parameter set and the state parameter set includes: establishing an evaluation function for characterizing the pipe network abnormality state evaluation value, ,have , In the formula, is the first The standard values ​​of key parameters, is the first The weight coefficient of the standard value of each key parameter is is the first The status value of each key device. is the first The weight coefficient of the key equipment status value is obtained by substituting the numerical parameter set and the status parameter set into the evaluation function to calculate the current abnormal evaluation value.

[0010] Optionally, judging the abnormality level according to the size of the abnormality assessment value includes: judging whether the current abnormality assessment value is greater than a preset second threshold; if the current abnormality assessment value is greater than the second threshold, judging the abnormality level to be high; if the current abnormality assessment value is less than or equal to the second threshold, judging the abnormality level to be low.

[0011] Optionally, the use of numerical simulation method to evaluate the possibility of water hammer effect includes: obtaining historical key parameter data in the pipeline and historical switching status data of key equipment to obtain a historical operation data set; establishing a pipeline network motion equation and a continuity equation for describing the change of velocity and pressure of the fluid in the pipeline over time according to the actual structure and operation characteristics of the pipeline network; setting boundary conditions and initial conditions, and calculating the motion equation and the continuity equation using the historical operation data set and a preset numerical method to obtain a time series data set of key parameters; analyzing and comparing the key parameter data in the numerical parameter set and the key parameter data corresponding to the current time in the time series data set to obtain the possibility of water hammer effect.

[0012] Optionally, the analyzing and comparing the key parameter data in the numerical parameter set and the key parameter data corresponding to the current time in the time series data set to obtain the possibility of the water hammer effect includes: calculating the difference between the key parameter data in the numerical parameter set and the key parameter data corresponding to the current time in the time series data set to obtain a first operation deviation value, and for the first operation deviation value ,have , In the formula, For the The weight coefficients corresponding to the key parameters are: For the The data corresponding to the key parameters in the numerical parameter set, For the The method comprises the following steps: determining the data corresponding to a key parameter in the time series data set; determining whether the first operation deviation value is greater than a preset third threshold value; if so, determining that the possibility of the water hammer effect is high; if not, determining that the possibility of the water hammer effect is low.

[0013] Optionally, the method of using characteristic parameter judgment to evaluate the possibility of water hammer effect includes: obtaining current data and previous data of key parameters in the pipeline; calculating the difference between the current data and the previous data of the key parameters in the pipeline, and performing normalization processing to obtain a standard deviation value; using the standard deviation value and the vibration standard value to calculate a second operating deviation value, and for the second operating deviation value ,have , In the formula, For the The weight coefficient of the standard deviation value of each key parameter is For the The standard deviation of the key parameters, is the weight coefficient of the vibration standard value, is the vibration standard value; determines whether the second operation deviation value is greater than a preset fourth threshold value; if so, determines that the possibility of the water hammer effect is high; if not, determines that the possibility of the water hammer effect is low.

[0014] Based on the same inventive concept, the present invention also provides a real-time monitoring device for water hammer effect, the device comprising: a wake-up module, used to collect vibration intensity data of the pipeline, and perform normalization processing to obtain a vibration standard value; determine whether the vibration standard value is greater than a preset first threshold value; if so, start data collection and evaluate the possibility of water hammer effect; if not, do not start the evaluation process; a data acquisition module, used to collect key parameter data in the pipeline in real time to obtain a numerical parameter set, and collect switch status data of key equipment in real time to obtain a state parameter set; an abnormality evaluation module, used to calculate the pipeline network abnormality evaluation value using the numerical parameter set and the state parameter set; an abnormality level judgment module, used to judge the abnormality level according to the size of the abnormality evaluation value; a high-level probability evaluation module, used to use a numerical simulation method to evaluate the possibility of water hammer effect when the abnormality level is high; a low-level probability evaluation module, used to use a characteristic parameter judgment method to evaluate the possibility of water hammer effect when the abnormality level is low; an early warning module, used to send early warning information according to the possibility of water hammer effect.

[0015] Compared with the prior art, the present invention has the following advantages: 1. The present invention can timely detect and warn of potential water hammer effects by real-time monitoring of key parameters in the pipeline and the switch status of equipment, thereby avoiding the inefficiency and lag of traditional methods that rely on manual inspections and regular testing; 2. The present invention accurately evaluates the possibility of water hammer effect, which helps to take measures in advance to effectively prevent the damage to the pipeline system caused by water hammer effect, thereby improving the safety and reliability of the pipeline system; 3. The present invention adopts two different evaluation methods, namely numerical simulation method and characteristic parameter judgment method, according to different abnormality levels. The numerical simulation method is suitable for situations with higher abnormality levels and can provide more accurate evaluation results. The characteristic parameter judgment method is suitable for situations with lower abnormality levels, with simple calculation and rapid response, thus improving evaluation efficiency.

[0016] 4. The present invention uses the key parameters in the pipeline and the switch status data of the equipment to determine the abnormality level by calculating the abnormal evaluation value of the pipeline network, and selects the evaluation method accordingly; this method is based on big data and intelligent algorithms, and realizes the intelligentization and automation of pipeline system monitoring; 5. The present invention also uses a wake-up mechanism. When the vibration standard value is less than the preset threshold, the present invention does not start the evaluation process, thereby saving computing resources and time; this design embodies the rational use and optimization of resources.

[0017] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0019] Figure 1 It is a flow chart of a method for real-time monitoring of water hammer effect according to an embodiment of the present invention.

[0020] Figure 2 It is an execution flow chart of a real-time monitoring method for water hammer effect according to an embodiment of the present invention.

[0021] Figure 3 It is a flow chart for evaluating the possibility of water hammer effect when the abnormality level is high according to an embodiment of the present invention.

[0022] Figure 4 It is a flow chart for evaluating the possibility of water hammer effect when the abnormality level is low according to an embodiment of the present invention.

[0023] Figure 5 It is a structural schematic diagram of a real-time monitoring device for water hammer effect according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] Reference Figure 1An embodiment of the present invention proposes a real-time monitoring method for water hammer effect, which calculates the abnormal evaluation value of the pipeline network by real-time monitoring of key parameters and the switch status of equipment in the pipeline, and uses different evaluation methods according to the abnormal level to judge the possibility of water hammer effect, so as to send early warning information in time and improve the safety and reliability of the pipeline system.

[0026] The method of this embodiment specifically includes: Collect key parameter data in the pipeline in real time to obtain a set of numerical parameters, and collect switch status data of key equipment in real time to obtain a set of status parameters; Specifically, various key parameters such as flow, pressure, temperature, vibration intensity, etc. are obtained from the pipeline in real time. These parameters are the basis for evaluating the operating status of the pipeline and judging the possibility of water hammer effect. The switching status of key equipment in the pipeline system (such as pumps, valves, etc.) is obtained. The switching status of the equipment directly affects the fluid flow state in the pipeline and is an important factor in judging the water hammer effect.

[0027] Calculating a pipe network abnormality assessment value using the numerical parameter set and the state parameter set; According to the magnitude of the abnormal evaluation value, determining the abnormal level; Specifically, a comprehensive analysis of numerical parameters and state parameters is performed to calculate an evaluation value that characterizes the abnormal state of the pipeline network; this evaluation value reflects the degree of deviation between the current pipeline operation state and the normal state; using a pre-set evaluation function, the numerical parameters and state parameters are substituted to calculate an abnormal evaluation value of the pipeline network; if the evaluation value is high, it means that the pipeline state is abnormal and may cause a water hammer effect.

[0028] When the abnormal level is high, the numerical simulation method is used to evaluate the possibility of water hammer effect; Specifically, when the abnormal level of the pipeline network is high, a numerical simulation method is used to accurately evaluate the possibility of water hammer effect. This method establishes the motion equation and continuity equation of the pipeline network and uses historical operation data and numerical methods for calculation. The equation is established according to the actual structure and operation characteristics of the pipeline network. Boundary conditions and initial conditions are set. Numerical simulation is performed using historical data sets. The possibility of water hammer effect is determined by comparing current data with simulation results.

[0029] When the abnormal level is low, the characteristic parameter judgment method is used to evaluate the possibility of water hammer effect; Specifically, when the abnormality level of the pipeline network is low, a faster and simpler characteristic parameter judgment method is used to evaluate the possibility of water hammer effect. This method makes judgments by analyzing the difference between the current data and the data of the previous moment of the key parameters; calculating the difference between the current data and the data of the previous moment of the key parameters and normalizing them; using this difference to compare with the preset threshold to judge the possibility of water hammer effect.

[0030] Send warning information based on the possibility of water hammer effect.

[0031] Specifically, according to the evaluation results, if it is judged that the possibility of water hammer effect is high, a warning message will be sent to relevant personnel or systems so that timely measures can be taken to avoid accidents; if numerical simulation or characteristic parameter judgment method concludes that the possibility of water hammer effect is high, a warning message will be sent through sound and light alarms, text messages, emails, etc.

[0032] Alternatively, if Figure 2 As shown, the real-time acquisition of key parameter data in the pipeline to obtain a set of numerical parameters includes: Collect the vibration intensity data of the pipeline and perform normalization processing to obtain the vibration standard value; Specifically, vibration sensors or similar detection equipment are installed at key locations of pipelines to obtain real-time vibration intensity data of the pipelines. The vibration intensity data can reflect the state of fluid flow in the pipeline, such as flow velocity, pressure fluctuations, etc., thereby indirectly reflecting the possibility of water hammer effect. Since the vibration intensity data may be affected by many factors (such as sensor sensitivity, environmental factors, etc.), normalization processing is required to eliminate the influence of these factors and obtain a unified vibration standard value. The normalization processing method can be selected according to actual conditions, such as linear normalization, nonlinear normalization, etc.

[0033] Determine whether the vibration standard value is greater than a preset first threshold; If yes, start data collection and evaluate the possibility of water hammer effect; If not, the evaluation process will not be initiated.

[0034] Specifically, a first threshold is preset, which can be set according to the actual situation of the pipeline system (such as pipeline material, fluid type, operating pressure, etc.); if the vibration standard value is greater than the preset first threshold, data collection (including other key parameter data, such as pressure, flow, etc.) and evaluation process are started to further determine the possibility of water hammer effect; if the vibration standard value is less than or equal to the preset first threshold, the evaluation process is not started to save computing resources and time.

[0035] For example, it is assumed that in a water supply system, a vibration sensor is used to collect vibration intensity data of the pipeline; the sensitivity of the sensor is 10mV / g (g is the acceleration of gravity), and the sampling frequency is 100Hz; vibration sensors are installed at key positions of the pipeline to obtain vibration intensity data in real time; for example, the vibration intensity data at a certain moment is 50mV, and the corresponding vibration acceleration is 5g; it is assumed that a linear normalization method is used to normalize the vibration acceleration to between 0 and 1; the maximum vibration acceleration is set to 10g (set according to the actual situation of the pipeline system), then the normalized vibration standard value is 5 / 10=0.5; the preset first threshold is 0.3 (set according to the actual situation of the pipeline system and safety requirements); since the normalized vibration standard value is 0.5, which is greater than the preset first threshold of 0.3, it is judged that it may be in an abnormal state; since the vibration standard value is greater than the preset first threshold, other key parameter data (such as pressure, flow, etc.) are started to be collected, and the evaluation process is started to further judge the possibility of water hammer effect; through subsequent calculations and analysis, it can be concluded whether it is necessary to send early warning information to ensure the safe operation of the pipeline system.

[0036] Optionally, the real-time acquisition of key parameter data in the pipeline to obtain a set of numerical parameters further includes: Collect key parameter data in the pipeline in real time and add it to the preset basic data set; Specifically, data of key parameters such as temperature, pressure, flow, etc. are collected from the pipeline in real time; these real-time data are added to a preset basic data set, which already contains some historical data.

[0037] Preprocessing the basic data set; Specifically, preprocessing may include steps such as data cleaning (removing outliers, processing missing values), data conversion (such as unit unification), etc. to ensure the quality and consistency of the data.

[0038] Using the data in the preprocessed basic data set, calculate the mean of key parameters; Using the preprocessed basic data set and the mean of the key parameters, the standard deviation of the key parameters is calculated; The standard value of the key parameter is calculated using the current key parameter data, the mean value of the key parameter, and the standard deviation of the key parameter. ,have , In the formula, is the current key parameter data, is the mean value of the key parameter, is the standard deviation of the key parameter; The standard values ​​of each key parameter are integrated to obtain a set of numerical parameters.

[0039] Specifically, the standard value converts the original data into a standard normal distribution form with the mean as the center and the standard deviation as the unit. The standard value reflects the position and dispersion of the current data relative to the mean, which facilitates further analysis and comparison. The standard values ​​of all key parameters are integrated together to form a set of numerical parameters, which can be used for further analysis, monitoring or decision support.

[0040] For example, suppose there is a pipeline system that collects data on two key parameters, temperature and pressure, in real time; suppose the basic data set already contains some historical data, add the real-time data to it, and clean and convert it, and calculate that the temperature mean is 25.5, the temperature standard deviation is 1, the pressure mean is 100, and the pressure standard deviation is 1.5; for the current temperature data collected in real time is 26, and the current pressure data is 102, then the standard value of the temperature is calculated to be 0.5, and the standard value of the pressure is 1.33; therefore, the numerical parameter set can be obtained as {temperature standard value: 0.5, pressure standard value: 1.33}.

[0041] Optionally, the real-time acquisition of switch status data of key equipment to obtain a set of status parameters includes: Collect the switch status data of key equipment in real time to obtain the status data set; Specifically, sensors or other technical means are used to obtain the switch status of key equipment in the pipeline in real time; these equipment may include valves, pumps, flow meters, etc. Their switch status is crucial to evaluating the overall operating status of the pipeline system; the collected switch status data is organized into a data set. This data set may contain status records at multiple time points, each record corresponding to a specific device and its switch status.

[0042] Defining numerical rules, and digitizing the status data according to the numerical rules to obtain the status value of the key equipment; Specifically, since the switching state of a device is usually discrete (for example, on or off), it is necessary to define a numerical rule to convert these discrete states into numerical values ​​that can be used for mathematical calculations; for example, the "on" state can be defined as 1, and the "off" state can be defined as 0, or other numerical representations can be used according to specific needs; applying the defined numerical rule, each state record in the state data set is converted into a corresponding numerical value; in this way, the state of each device at each point in time can be represented by a specific numerical value; after digital processing, the state of each key device at each point in time is converted into a specific numerical value, and these numerical values ​​are called the state values ​​of the key devices.

[0043] The status values ​​of each key device are integrated to obtain a set of status parameters.

[0044] Specifically, the status values ​​of all key equipment are integrated into a set to form a state parameter set; this set will be used for subsequent calculations and analysis to evaluate the abnormal status of the pipeline system and the possibility of water hammer effect.

[0045] For example, suppose there are two key devices in the pipeline system: valve A and pump B; the switch state of valve A is "open" at a certain moment, and the switch state of pump B is "closed" at the same moment; according to the numerical rule, the "open" state of valve A is defined as 1, and the "closed" state of pump B is defined as 0; therefore, at this moment, the state value of valve A is 1, and the state value of pump B is 0; these two state values ​​are integrated into a set to obtain the state parameter set {valve A: 1, pump B: 0}; this state parameter set will be used for subsequent calculations and analysis to evaluate the current state of the pipeline system and the possibility of water hammer effect. Through this method, it can be ensured that the real-time acquisition of the switch state data of key equipment can be effectively utilized to provide strong support for the safe operation of the pipeline system.

[0046] Optionally, the calculating the pipe network abnormality assessment value by using the numerical parameter set and the state parameter set includes: Establish an evaluation function for characterizing the evaluation value of the abnormal state of the pipeline network. ,have , In the formula, is the first The standard values ​​of key parameters, is the first The weight coefficient of the standard value of each key parameter is is the first The status value of each key device. is the first The weight coefficient of each key equipment status value; Substitute the numerical parameter set and the state parameter set into the evaluation function to calculate and obtain a current abnormal evaluation value.

[0047] Specifically, the evaluation function is used to characterize the evaluation value of the abnormal state of the pipeline network; this function comprehensively considers the numerical parameter set (i.e., the standard values ​​of key parameters in the pipeline) and the state parameter set (i.e., the state values ​​of key equipment); the numerical parameter set and the state parameter set collected in real time are substituted into the evaluation function, and the current pipeline network abnormality evaluation value is obtained by calculation; this evaluation value is a comprehensive indicator used to reflect the current abnormal state of the pipeline system.

[0048] For example, assume that there are two key parameters in the pipeline system: pressure and flow, and two key devices: valve A and pump B; assume that the original data of pressure collected in real time is 120 bar, and the standard value of pressure after standardization is 1.1, and the original data of flow collected in real time is 50 m³ / h, and the standard value of flow after standardization is 0.9; assume that valve A is currently in the open state, according to the numerical rule, its state value is 1; assume that pump B is currently in the closed state, according to the numerical rule, its state value is 0; assume that the weight coefficient of pressure is 0.6, the weight coefficient of flow is 0.4, the weight coefficient of valve A is 0.7, and the weight coefficient of pump B is 0.3, and substitute them into the evaluation function to calculate Therefore, the current abnormal evaluation value of the pipeline network is 1.72. According to the preset threshold, the current abnormal level of the pipeline system can be judged and corresponding early warning or treatment measures can be taken.

[0049] Alternatively, if Figure 2 As shown, judging the abnormality level according to the magnitude of the abnormality evaluation value includes: Determine whether the current abnormality assessment value is greater than a preset second threshold; Specifically, the second threshold is a value preset according to pipeline system characteristics, historical data, safety standards, etc.; it is used to classify abnormal evaluation values ​​into different levels so as to take corresponding measures.

[0050] If the current abnormality assessment value is greater than the second threshold, the abnormality level is determined to be high; Specifically, the calculated current abnormality assessment value is compared with the preset second threshold value. If the current abnormality assessment value is greater than the preset second threshold value, it means that the pipeline system is currently in a relatively high abnormal state and there is a greater risk of water hammer effect. Therefore, the abnormality level is determined to be high, and a numerical simulation method is used to evaluate the possibility of water hammer effect.

[0051] If the current abnormality assessment value is less than or equal to the second threshold, the abnormality level is determined to be low.

[0052] Specifically, if the current abnormality assessment value is less than or equal to the preset second threshold, it means that although there is an abnormality in the pipeline system, the risk is relatively low. Therefore, the abnormality level is judged to be low, and the characteristic parameter judgment method is used to assess the possibility of water hammer effect. This method is simple to calculate and has a quick response, which is suitable for the preliminary assessment of low-level abnormalities.

[0053] Alternatively, if Figure 3 As shown, the numerical simulation method used to evaluate the possibility of water hammer effect includes: Obtain historical key parameter data in the pipeline and historical switch status data of key equipment to obtain historical operation data sets; Specifically, it is necessary to collect historical key parameter data in the pipeline system, including but not limited to flow, pressure, temperature, etc.; at the same time, it is also necessary to obtain historical switching status data of key equipment, such as switching records of pumps and valves; these data together constitute the historical operation data set, which provides a basis for subsequent numerical simulation.

[0054] According to the actual structure and operation characteristics of the pipeline network, the pipeline network motion equation and continuity equation are established to describe the change of velocity and pressure of the fluid in the pipeline with time; Specifically, based on the actual structure and operating characteristics of the pipeline network, the pipeline network motion equation and continuity equation are established to describe the changes in the velocity and pressure of the fluid in the pipeline over time; these equations are basic equations of fluid mechanics and can accurately reflect the flow state of the fluid in the pipeline.

[0055] Setting boundary conditions and initial conditions, calculating the motion equation and the continuity equation using a historical operation data set and a preset numerical method, and obtaining a time series data set of key parameters; Specifically, before conducting numerical simulation, it is necessary to set appropriate boundary conditions and initial conditions; boundary conditions usually include the inlet and outlet conditions of the pipeline, such as flow rate, pressure, etc.; initial conditions refer to the state and parameters of the fluid in the pipeline at the beginning of the simulation; the setting of these conditions is crucial to the accuracy of the numerical simulation results; the historical operation data set is substituted into the pipeline network motion equation and continuity equation, and calculated using preset numerical methods (such as finite difference method, finite element method, etc.); by iteratively solving these equations, a time series data set of key parameters of the fluid in the pipeline (such as flow rate, pressure, etc.) can be obtained.

[0056] The key parameter data in the numerical parameter set and the key parameter data corresponding to the current time in the time series data set are analyzed and compared to obtain the possibility of the water hammer effect.

[0057] For example, assume that the flow and pressure data of the pipeline system over a period of time (such as a week) and the valve opening and closing records have been collected. These data constitute our historical operation data set. According to the actual structure of the pipeline system and the principles of fluid mechanics, the following pipeline network motion equation can be established: ; Establish the continuity equation: ; In the formula, is the flow rate data, is the pressure data, is the density, is the acceleration due to gravity, is the pipe height, is the friction coefficient, is the pipe diameter, is the cross-sectional area of ​​the pipe, is the length along the pipeline; it is assumed that the inlet flow rate of the pipeline is a constant value, the outlet pressure is atmospheric pressure, and the initial condition is that the fluid in the pipeline is in a static state, that is, the flow velocity is zero and the pressure is uniformly distributed; the flow and pressure data in the historical operation data set are substituted into the pipeline network motion equation and continuity equation, and the finite difference method is used for iterative solution; through calculation, the time series data set of the fluid flow and pressure in the pipeline is obtained.

[0058] Optionally, analyzing and comparing the key parameter data in the numerical parameter set and the key parameter data corresponding to the current time in the time series data set to obtain the possibility of the water hammer effect includes: Calculate the difference between the key parameter data in the numerical parameter set and the key parameter data corresponding to the current time in the time series data set to obtain a first running deviation value. ,have , In the formula, For the The weight coefficients corresponding to the key parameters are: For the The data corresponding to the key parameters in the numerical parameter set, For the The data corresponding to the key parameters in the time series data set; Specifically, the deviation between the current operating state and the expected or historical operating state is quantified by calculating the difference between the numerical parameter set and the corresponding key parameters in the time series data set.

[0059] Determining whether the first operation deviation value is greater than a preset third threshold; If yes, the probability of water hammer effect is judged to be high; If not, the possibility of water hammer effect is judged to be low.

[0060] Specifically, a threshold is set to determine whether the current operating deviation has reached a level that may cause a water hammer effect; if the first operating deviation value is greater than a third threshold, the possibility of the water hammer effect is determined to be high; if the first operating deviation value is less than or equal to the third threshold, the possibility of the water hammer effect is determined to be low.

[0061] For example, suppose there is a water supply system that needs to monitor two key parameters: pressure and flow; the weight coefficient of pressure is set to 0.6, the weight coefficient of flow is set to 0.4, and the third threshold is set to 5; the numerical parameter set collected is: {pressure: 100psi, flow: 50gpm}, and a time series data set is obtained through numerical simulation. The pressure data at the current time point is 110psi, and the flow data is 40gpm from the time series data set; calculate the first operation deviation value Since the first operation deviation value 10 is greater than the third threshold value 5, it is determined that the possibility of the water hammer effect is high.

[0062] Alternatively, if Figure 4 As shown, the characteristic parameter judgment method used to evaluate the possibility of water hammer effect includes: Get the current and previous data of key parameters in the pipeline; Specifically, the current data and the previous data of key parameters (such as pressure, flow rate, flow velocity, etc.) in the pipeline are obtained to calculate the change between them.

[0063] Calculate the difference between the current data and the previous data of the key parameters in the pipeline, and perform normalization to obtain the standard deviation value; Specifically, the difference between the current data and the data at the previous moment is calculated to reflect the rate of change of the parameter; the difference is normalized to obtain the standard deviation value; the normalization process is to eliminate the influence of the dimension and order of magnitude between different parameters, so that different parameters can be compared and weighted.

[0064] The second operation deviation value is calculated by using the standard deviation value and the vibration standard value. ,have , In the formula, For the The weight coefficient of the standard deviation value of each key parameter is For the The standard deviation of the key parameters, is the weight coefficient of the vibration standard value, is the vibration standard value; Determining whether the second operation deviation value is greater than a preset fourth threshold; If yes, the probability of water hammer effect is judged to be high; If not, the possibility of water hammer effect is judged to be low.

[0065] Specifically, a threshold is set to determine whether the current operating deviation has reached a level that may cause a water hammer effect; if the first operating deviation value is greater than a fourth threshold, the possibility of the water hammer effect is determined to be high; if the first operating deviation value is less than or equal to the fourth threshold, the possibility of the water hammer effect is determined to be low.

[0066] Exemplarily, assuming that the weight coefficient of the standard deviation value of pressure is 0.7, the weight coefficient of the standard deviation value of flow is 0.3, the weight coefficient of the vibration standard value is 0.2, the preset fourth threshold is 0.8, the vibration standard value collected and calculated is 0.5, the pressure data at the current time point is 105psi, the pressure data at the previous moment is 100psi, the flow data at the current time point is 45gpm, and the flow data at the previous moment is 50gpm; assuming that the numerical range of the difference between the current and previous pressures is 0-10psi, then the standard deviation value of pressure is 0.5; assuming that the numerical range of the difference between the current and previous flow is 0-10 gpm, then the standard deviation value of flow is 0.5, then the second running deviation value Since the second operating deviation value 0.6 is less than the fourth threshold value 0.8, it can be determined that the possibility of the water hammer effect is low.

[0067] Based on the same inventive concept, Figure 5 As shown, the present invention also provides a real-time monitoring device for water hammer effect, the device comprising: The wake-up module is used to collect the vibration intensity data of the pipeline and perform normalization processing to obtain the vibration standard value; determine whether the vibration standard value is greater than a preset first threshold; if so, start data collection and evaluate the possibility of water hammer effect; if not, do not start the evaluation process; The data acquisition module is used to collect the key parameter data in the pipeline in real time to obtain a set of numerical parameters, and to collect the switch status data of key equipment in real time to obtain a set of status parameters; An abnormality assessment module, used to calculate a pipe network abnormality assessment value using the numerical parameter set and the state parameter set; An abnormality level judgment module, used to judge the abnormality level according to the magnitude of the abnormality evaluation value; Advanced probability assessment module, used to assess the possibility of water hammer effect by numerical simulation when the abnormal level is high; The low-level probability assessment module is used to assess the possibility of water hammer effect by using characteristic parameter judgment method when the abnormal level is low; The early warning module is used to send early warning information according to the possibility of water hammer effect.

[0068] It should be noted that the electrical connection between the above-mentioned units does not necessarily mean direct connection of the lines, and the indirect connection mode can be applied to the embodiments of the present invention as long as the purpose of the present invention is achieved. The above is only an exemplary embodiment of the present invention and cannot be used to limit the scope of the present invention.

[0069] That is, any equivalent changes and modifications made according to the teachings of the present invention are still within the scope of the present invention. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present invention. This application is intended to cover any variation, use or adaptive change of the present invention, which follows the general principles of the present invention and includes common knowledge or customary technical means in the art that are not described in the present invention.

Claims

1. A real-time monitoring method for water hammer effect, characterized in that: The method comprises: Collect key parameter data in the pipeline in real time to obtain a set of numerical parameters, and collect switch status data of key equipment in real time to obtain a set of status parameters; Calculating a pipe network abnormality assessment value using the numerical parameter set and the state parameter set; According to the magnitude of the abnormal evaluation value, determining the abnormal level; When the abnormal level is high, the numerical simulation method is used to evaluate the possibility of water hammer effect; When the abnormal level is low, the characteristic parameter judgment method is used to evaluate the possibility of water hammer effect; Send warning information based on the possibility of water hammer effect.

2. A method for real-time monitoring of water hammer effect according to claim 1, characterized in that: The real-time acquisition of key parameter data in the pipeline to obtain a set of numerical parameters includes: Collect the vibration intensity data of the pipeline and perform normalization processing to obtain the vibration standard value; Determine whether the vibration standard value is greater than a preset first threshold; If yes, start data collection and evaluate the possibility of water hammer effect; If not, the evaluation process will not be initiated.

3. A method for real-time monitoring of water hammer effect according to claim 1, characterized in that: The real-time acquisition of key parameter data in the pipeline to obtain a set of numerical parameters also includes: Collect key parameter data in the pipeline in real time and add it to the preset basic data set; Preprocessing the basic data set; Using the data in the preprocessed basic data set, calculate the mean of key parameters; Using the preprocessed basic data set and the mean of the key parameters, the standard deviation of the key parameters is calculated; The standard value of the key parameter is calculated using the current key parameter data, the mean value of the key parameter, and the standard deviation of the key parameter. ,have ， In the formula, is the current key parameter data, is the mean value of the key parameter, is the standard deviation of the key parameters; The standard values ​​of each key parameter are integrated to obtain a set of numerical parameters.

4. A real-time monitoring method for water hammer effect according to claim 3, characterized in that: The real-time acquisition of switch status data of key equipment to obtain a set of status parameters includes: Collect the switch status data of key equipment in real time to obtain the status data set; Defining numerical rules, and digitizing the status data according to the numerical rules to obtain the status value of the key equipment; The status values ​​of each key device are integrated to obtain a set of status parameters.

5. A real-time monitoring method for water hammer effect according to claim 4, characterized in that: The calculating of the pipe network abnormality assessment value by using the numerical parameter set and the state parameter set comprises: Establish an evaluation function for characterizing the evaluation value of the abnormal state of the pipeline network. ,have ， In the formula, is the first The standard values ​​of key parameters, is the first The weight coefficient of the standard value of each key parameter is is the first The status value of each key device. is the first The weight coefficient of each key equipment status value; Substitute the numerical parameter set and the state parameter set into the evaluation function to calculate and obtain a current abnormal evaluation value.

6. A method for real-time monitoring of water hammer effect according to claim 5, characterized in that: The determining of the abnormality level according to the magnitude of the abnormality evaluation value includes: Determine whether the current abnormality assessment value is greater than a preset second threshold; If the current abnormality assessment value is greater than the second threshold, the abnormality level is determined to be high; If the current abnormality assessment value is less than or equal to the second threshold, the abnormality level is determined to be low.

7. A method for real-time monitoring of water hammer effect according to claim 1, characterized in that: The numerical simulation method used to evaluate the possibility of water hammer effect includes: Obtain historical key parameter data in the pipeline and historical switch status data of key equipment to obtain historical operation data sets; According to the actual structure and operation characteristics of the pipeline network, the pipeline network motion equation and continuity equation are established to describe the change of velocity and pressure of the fluid in the pipeline with time; Setting boundary conditions and initial conditions, calculating the motion equation and the continuity equation using a historical operation data set and a preset numerical method, and obtaining a time series data set of key parameters; The key parameter data in the numerical parameter set and the key parameter data corresponding to the current time in the time series data set are analyzed and compared to obtain the possibility of the water hammer effect.

8. A method for real-time monitoring of water hammer effect according to claim 7, characterized in that: The possibility of water hammer effect is obtained by analyzing and comparing the key parameter data in the numerical parameter set and the key parameter data corresponding to the current time in the time series data set, including: Calculate the difference between the key parameter data in the numerical parameter set and the key parameter data corresponding to the current time in the time series data set to obtain a first running deviation value. ,have ， In the formula, For the The weight coefficients corresponding to the key parameters are: For the The data corresponding to the key parameters in the numerical parameter set, For the The data corresponding to the key parameters in the time series data set; Determining whether the first operation deviation value is greater than a preset third threshold; If yes, the probability of water hammer effect is judged to be high; If not, the possibility of water hammer effect is judged to be low.

9. A method for real-time monitoring of water hammer effect according to claim 2, characterized in that: The characteristic parameter judgment method used to assess the possibility of water hammer effect includes: Get the current and previous data of key parameters in the pipeline; Calculate the difference between the current data and the previous data of the key parameters in the pipeline, and perform normalization to obtain the standard deviation value; The second operation deviation value is calculated by using the standard deviation value and the vibration standard value. ,have ， In the formula, For the The weight coefficient of the standard deviation value of each key parameter is For the The standard deviation of the key parameters, is the weight coefficient of the vibration standard value, is the vibration standard value; Determining whether the second operation deviation value is greater than a preset fourth threshold; If yes, the probability of water hammer effect is judged to be high; If not, the possibility of water hammer effect is judged to be low.

10. A real-time monitoring device for water hammer effect, using the real-time monitoring method for water hammer effect according to any one of claims 1 to 9, characterized in that: The device comprises: The wake-up module is used to collect the vibration intensity data of the pipeline and perform normalization processing to obtain the vibration standard value; determine whether the vibration standard value is greater than a preset first threshold; if so, start data collection and evaluate the possibility of water hammer effect; if not, do not start the evaluation process; The data acquisition module is used to collect the key parameter data in the pipeline in real time to obtain a set of numerical parameters, and to collect the switch status data of key equipment in real time to obtain a set of status parameters; An abnormality assessment module, used to calculate a pipe network abnormality assessment value using the numerical parameter set and the state parameter set; An abnormality level judgment module, used to judge the abnormality level according to the magnitude of the abnormality evaluation value; Advanced probability assessment module, used to assess the possibility of water hammer effect by numerical simulation when the abnormal level is high; The low-level probability assessment module is used to assess the possibility of water hammer effect by using characteristic parameter judgment method when the abnormal level is low; The early warning module is used to send early warning information according to the possibility of water hammer effect.

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