Intelligent monitoring method and system of Internet of Things ultrasonic water meter

Abstract

The invention relates to the technical field of remote meter reading, in particular to an intelligent monitoring method and system for an internet of things ultrasonic water meter, and the method comprises the following steps: obtaining three-period pressure difference, calculating absolute difference, accumulating and judging the variation range, if the variation range is exceeded, collecting a flow velocity sequence, calculating standard difference, judging stability, adjusting high frequency and sampling; according to the state extraction data, calculating a first order difference parity ratio to judge the credibility, if the credibility is low, performing weighted substitution on front and rear values, and judging fluctuation to recover the initial frequency by using a substitution value. According to the method, the state change of the pipeline is recognized through accumulation of periodic pressure difference values, the data fluctuation recognition capability is enhanced, the sampling frequency is dynamically adjusted by introducing the flow velocity fluctuation degree to improve the response speed, the data credibility is judged through a first-order difference ratio, and the data stability and continuity are improved through low-credibility periodic weighted correction; and the sampling recovery state is judged by comparing the previous and later periods, so that the sampling frequency is timely homed, a self-adaptive closed-loop dynamic mechanism is constructed, and the data accuracy and continuity under the complex working condition are enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of remote meter reading, and in particular to an intelligent monitoring method and system for an Internet of Things ultrasonic water meter. Background Art

[0002] The technical field of the intelligent monitoring method for Internet of Things ultrasonic water meters involves the integrated application of ultrasonic measurement, water meter metering, and Internet of Things communication. The core of this technical field lies in achieving high-precision acquisition of water flow through the ultrasonic measurement principle, and at the same time realizing remote transmission and centralized management of data through the Internet of Things communication network. The entire technical system covers multiple links such as sensing detection, data acquisition, wireless communication, background data interaction, and management, and has the capabilities of multi-terminal linkage and remote control. As a key device in this field, the Internet of Things ultrasonic water meter integrates functions such as low-power operation, wireless communication, and anomaly detection, and is suitable for the intelligent management and monitoring of distributed water supply systems.

[0003] Among them, remote meter reading refers to using a communication network to transmit the water consumption data collected by the water meter to a remote management platform to achieve centralized reading and management of user water consumption. The main theme of this patent aims at the problems of strong manual intervention, low real-time performance, and high reading costs in the process of user water meter data collection and transmission. It is proposed to integrate a low-power narrowband Internet of Things communication module and time synchronization control logic to complete automatic data collection at a set period, and send the data to a remote server through a point-to-point transmission protocol, and the server performs unified storage and management. The methods generally include setting a fixed time window to trigger data sampling, establishing a data packet coding structure, sending the data to a specified data center through a cellular network, and the data center completing data archiving and user allocation through parsing rules.

[0004] In the prior art, data collection and upload are carried out within a fixed time window, lacking a feedback response mechanism for the actual water flow fluctuation situation. When encountering short-term sudden changes in flow velocity, the system cannot adjust the sampling frequency in a timely manner, which may cause offsets in flow velocity data. There is a lack of a quantitative judgment method for the credibility of abnormal data, resulting in the upload of unrecognized abnormal data in a single cycle, affecting the subsequent water use analysis results. There is a lack of associated calculation between periodic data, and the system's self-correction ability for abnormal fluctuations is weak, and errors are easily accumulated in long-term monitoring, affecting the overall measurement accuracy and monitoring stability. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies existing in the prior art, and to propose an intelligent monitoring method and system for an Internet of Things ultrasonic water meter.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions: An intelligent monitoring method for an Internet of Things ultrasonic water meter includes the following steps: S1: Obtain the sequence of pipeline pressure difference readings for three consecutive periods in the ultrasonic water meter, calculate the absolute difference for adjacent period data, accumulate the differences and compare with the judgment benchmark to generate the variation amplitude of the period pressure difference; S2: According to the variation amplitude of the period pressure difference, if it exceeds the judgment benchmark, collect the sequence of instantaneous flow velocity readings for five periods in the ultrasonic water meter, perform standard deviation calculation to obtain the flow velocity fluctuation value of the current period, compare with the set flow velocity stability threshold, switch the sampling window and adjust the sampling frequency to the short-time high-frequency mode, and record the sampling frequency adjustment status; S3: Based on the sampling frequency adjustment status, extract the corresponding period pressure difference and flow velocity sequences, calculate the first-order difference and then find the co-location ratio, compare with the reference interval to obtain the flow velocity credibility judgment index; S4: According to the flow velocity credibility judgment index, if the data of the current period is in a low credibility state, extract the flow velocity readings of the previous and subsequent periods, perform weighted average in turn according to the weights, replace the original readings to generate the abnormal period replacement flow velocity; S5: Call the abnormal period replacement flow velocity, obtain the pressure difference and flow velocity sequences of the subsequent two periods, calculate the fluctuation values respectively and compare and judge, restore the initial sampling frequency to obtain the period sampling frequency status value.

[0007] As a further solution of the present invention, the variation amplitude of the period pressure difference is specifically the fluctuation range, deviation level, risk signal, the sampling frequency adjustment status is specifically the mode status, frequency configuration, adjustment record, the flow velocity credibility judgment index includes the stability score, trust level, judgment result, the abnormal period replacement flow velocity is specifically the smooth flow velocity, correction value, replacement data, and the period sampling frequency status value specifically refers to the initial mode, frequency recovery, status feedback.

[0008] As a further solution of the present invention, the specific steps for obtaining the variation amplitude of the period pressure difference are as follows: S101: Based on the sequence of pipeline pressure difference readings for three consecutive periods obtained in the ultrasonic water meter, extract two groups of pressure difference data for adjacent periods, calculate the absolute difference of the pressure difference at multiple time points, merge to generate a difference sequence, accumulate and sum the differences to generate the total amount of period pressure difference; S102: Call the total amount of period pressure difference, perform difference judgment on multiple groups of values and the set judgment benchmark, calculate the deviation degree between the difference and the benchmark, classify and summarize and set the numerical interval to generate the period pressure difference deviation interval; S103: According to the period pressure difference deviation interval, call the total amount of period pressure difference, combine the fluctuation value, pipe section length and sampling interval to perform operations, using the formula: ; Obtain the variation amplitude value to generate the variation amplitude of the period pressure difference; Obtain the change amplitude value and generate the periodic pressure difference change amplitude; Among them, represents the periodic pressure difference change amplitude of the first period, represents the pressure difference difference at the moment in the first period, represents the determination criterion of the first period, represents the pressure difference fluctuation value at the moment in the first period, represents the pipe section length at the moment in the first period, represents the flow velocity increase parameter of the first period, represents the sampling interval at the moment in the first period, represents the number of pressure difference sampling points within the period.

[0009] As a further solution of the present invention, the step of obtaining the sampling frequency adjustment state is specifically as follows: S201: Based on the difference between the periodic pressure difference change amplitude value and the set pressure difference determination reference value, calculate the amplitude difference of the periodic pressure difference change value, and judge whether the amplitude difference exceeds the pressure difference determination reference value threshold. If it exceeds, collect the flow velocity reading sequences within five periods in the ultrasonic water meter to obtain the instantaneous flow velocity sequence; S202: Call the instantaneous flow velocity sequence, calculate the fluctuation range based on each instantaneous flow velocity in five periods, and use the formula: ; Calculate the new corrected value of the flow velocity standard deviation; Among them, represents the new corrected value of the flow velocity standard deviation, represents the instantaneous flow velocity value at the moment within a single period, represents the average value of all instantaneous flow velocity values, represents the sample quantity, i.e., the number of periods, is a coefficient adjusted according to the flow velocity change trend; S203: Compare the difference between the new corrected value of the flow velocity standard deviation and the preset flow velocity stability threshold. If it exceeds the flow velocity stability threshold, switch the sampling window and adjust the sampling frequency to the short-time high-frequency mode, and record the current frequency state to obtain the sampling frequency adjustment state value.

[0010] As a further solution of the present invention, the step of obtaining the flow velocity credibility judgment index is specifically as follows: S301: Based on the sampling frequency adjustment state, a pressure difference sequence and a flow rate sequence within a period are selected, the sequences are synchronously intercepted and the time step is corrected, and then the difference between adjacent moments is obtained in the order of the time axis to construct a first-order difference sequence set; S302: calling the first-order difference sequence set, extracting the pressure difference difference value and the flow velocity difference value respectively according to the same time index, calculating the same position ratio, and establishing a numerical list for the ratio results corresponding to all moments to obtain a pressure difference flow velocity ratio sequence; S303: According to the pressure difference flow rate ratio sequence, combined with the upper and lower boundaries of the reference ratio interval of multiple ratios in the periodic segment, the deviation degree and the sequence fluctuation intensity are calculated in turn, using the formula: ; After the flow velocity deviation judgment value sequence is obtained by operation, the multiple judgment values ​​are compared with the credibility limit value to generate the flow velocity credibility judgment index; in, It indicates the flow velocity credibility judgment index. Indicates The pressure difference flow rate ratio at the time, represents the mean of the pressure difference flow rate ratio series, Indicates the ratio sequence The variance of the item, Indicates The absolute value of the first-order difference of the flow velocity at time , Indicates The half-width value of the reference ratio interval corresponding to the moment, Indicates the total number of sample points in the period.

[0011] As a further solution of the present invention, the step of obtaining the abnormal period alternative flow rate is specifically: S401: Based on the current cycle flow velocity reading and the current flow velocity credibility judgment index, determine whether the current cycle flow velocity data is in a credible state, compare the current cycle flow velocity credibility index with a preset flow velocity credibility judgment threshold, if it is less than the flow velocity credibility judgment threshold, determine that the current cycle is an abnormal cycle, and obtain an abnormal cycle marking state; S402: calling the abnormal cycle marking state, extracting the flow velocity readings of the adjacent cycles before and after the flow velocity data determined as the abnormal cycle, marking them as the flow velocity of the previous cycle and the flow velocity of the next cycle, and recording the flow velocity of the current cycle, using the formula: ; Calculate the adjusted cycle flow rate value, replace the original reading of the current abnormal cycle, and generate an alternative flow rate value for the abnormal cycle; in, Indicates the adjusted cycle flow rate value, represents the flow rate of the previous cycle, Indicates the flow velocity in the next cycle, indicating the flow velocity in the current cycle; S403: Invoke the abnormal cycle replacement flow velocity value to replace the current cycle flow velocity reading originally marked as abnormal, and update the value of the cycle position in the original flow velocity dataset to obtain the abnormal cycle replacement flow velocity.

[0012] As a further solution of the present invention, the step of obtaining the cycle sampling frequency status value is specifically as follows: S501: Based on the abnormal cycle replacement flow velocity, invoke the flow velocity information and differential pressure sampling sequence in the initial cycle, calculate the differential pressure amplitude and flow velocity change rate at multiple sampling points within the cycle, construct a set of continuous fluctuation indicators in the sampling sequence, and obtain the differential pressure flow velocity fluctuation indicator sequence; S502: Invoke the differential pressure flow velocity fluctuation indicator sequence, and based on the corresponding sampling points of the differential pressure and flow velocity in two cycles, construct the ratio of the differential pressure difference and flow velocity difference at adjacent moments, using the formula: ; Calculate the differential pressure flow velocity ratio at each moment to form a ratio sequence, and perform periodic fluctuation analysis based on the sequence average value and difference amplitude to obtain the cycle normalized fluctuation difference; Among them, represents the differential pressure flow velocity ratio of the cycle , indicating the differential pressure value at the th sampling point in the cycle , indicating the differential pressure value at the th sampling point in the cycle , indicating the flow velocity value at the th sampling point in the cycle , indicating a positive constant to avoid a zero denominator, indicating the sampling point number within the cycle; S503: Make a numerical amplitude judgment based on the cycle normalized fluctuation difference and the set cycle fluctuation threshold, and compare and judge in combination with the initial setting of the sampling frequency and the adjustment mark status value to generate the cycle sampling frequency status value.

[0013] An intelligent monitoring system for an Internet of Things ultrasonic water meter, the intelligent monitoring system for the Internet of Things ultrasonic water meter is used to execute the above-mentioned intelligent monitoring method for the Internet of Things ultrasonic water meter, and the system includes: The differential pressure detection module acquires the differential pressure signal sequences of three cycles for a pipe section, calculates the absolute differences between adjacent cycles and accumulates them, calls the differential pressure change reference value for comparison, and obtains the differential pressure change amplitude of the cycle; Based on the differential pressure change amplitude of the cycle, if it exceeds the differential pressure change reference value, the fluctuation judgment module collects five instantaneous flow velocity readings, calculates their standard deviation and compares it with the flow velocity stability threshold. If the triggering condition is met, it adjusts the sampling window and switches to the high-frequency mode, records the frequency switching situation, and generates the sampling frequency adjustment state; Based on the sampling frequency adjustment state, the credibility evaluation module extracts the corresponding differential pressure and flow velocity sequences, performs first-order difference processing and calculates the co-location ratio, calls the credible reference interval for judgment, and obtains the flow velocity credibility judgment index; Based on the flow velocity credibility judgment index, the data correction module extracts the flow velocity readings before and after the current cycle, assigns weights in sequence and performs weighted averaging, uses it to replace the current flow velocity value, and generates the abnormal cycle replacement flow velocity; The frequency control module calls the abnormal cycle replacement flow velocity, acquires the differential pressure and flow velocity sequences of the subsequent two cycles, calculates the fluctuation values respectively and compares them with the set reference value, determines whether to restore the sampling frequency, and obtains the cycle sampling frequency status value.

[0014] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In the present invention, by calculating the change amplitude through the accumulation of the differential pressure differences of consecutive cycles, the change of the pipeline state can be identified, and the data fluctuation recognition ability is enhanced. The introduction of the flow velocity fluctuation degree enables the sampling frequency to be dynamically adjusted according to abnormalities, improving the density and response speed of the instantaneous flow velocity sampling. The first-order difference ratio calculation is used to judge the credibility of the flow velocity data. By weighted correction of the data in the low-credibility cycle, the stability and continuity of the data in the abnormal cycle are improved. By calculating the sampling recovery state in combination with the comparison of the previous and subsequent cycles, it is ensured that the sampling frequency of the system returns in time after the abnormal fluctuation is processed, forming an adaptive and closed-loop dynamic adjustment mechanism, and enhancing the accuracy and continuity of the collected data under complex working conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 is a schematic diagram of the working process of the present invention; Figure 2 is a flow chart of the steps for obtaining the differential pressure change amplitude of the cycle of the present invention; Figure 3 is a flow chart of the steps for obtaining the sampling frequency adjustment state of the present invention; Figure 4 is a flow chart of the steps for obtaining the flow velocity credibility judgment index of the present invention; Figure 5 is a flow chart of the steps for obtaining the abnormal cycle replacement flow velocity of the present invention; Figure 6This is the flowchart for obtaining the periodic sampling frequency status value of the present invention. Detailed implementation manners

[0016] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0017] In the description of the present invention, it should be understood that the orientation or positional relationships indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationships shown in the accompanying drawings. These 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 thus should not be construed as limiting the present invention. In addition, in the description of the present invention, the meaning of "a plurality of" is two or more, unless otherwise specifically defined.

[0018] Embodiment 1. Please refer to Figure 1 , the present invention provides a technical solution: an intelligent monitoring method for an Internet of Things ultrasonic water meter, including the following steps: S1: Obtain three consecutive cycle pipeline pressure difference reading sequences in the ultrasonic water meter, calculate the absolute difference for adjacent cycle data, accumulate the differences and compare with a determination reference to generate the cycle pressure difference change amplitude; S2: According to the cycle pressure difference change amplitude, if it exceeds the determination reference, collect five cycle instantaneous flow velocity reading sequences in the ultrasonic water meter, perform standard deviation calculation to obtain the flow velocity fluctuation value of the current cycle, compare with a set flow velocity stability threshold, switch the sampling window and adjust the sampling frequency to a short-time high-frequency mode, and record the sampling frequency adjustment status; S3: Based on the sampling frequency adjustment status, extract the corresponding cycle pressure difference and flow velocity sequences, calculate the first-order difference and then find the co-location ratio, and compare with a reference interval to obtain the flow velocity credibility judgment index; S4: According to the flow velocity credibility judgment index, if the current cycle data is in a low credibility state, extract the flow velocity readings of the previous and subsequent cycles, perform weighted average in turn according to the weights, replace the original readings, and generate an abnormal cycle replacement flow velocity; S5: Call the abnormal cycle replacement flow velocity, obtain the pressure difference and flow velocity sequences of the subsequent two cycles, calculate the fluctuation values respectively and compare and determine, restore the initial sampling frequency, and obtain the cycle sampling frequency status value.

[0019] The specific range of periodic pressure difference variation is the fluctuation range, deviation level, and risk signal. The specific state of sampling frequency adjustment is the mode state, frequency configuration, and adjustment record. The flow velocity credibility judgment indicators include stability score, trust level, and judgment result. The abnormal cycle alternative flow velocity is specifically the smoothed flow velocity, correction value, and alternative data. The periodic sampling frequency status value specifically refers to the initial mode, frequency recovery, and status feedback.

[0020] Please refer to Figure 2 , and the specific steps for obtaining the range of periodic pressure difference variation are as follows: S101: Based on three consecutive cycle pipeline pressure difference reading sequences obtained from the ultrasonic water meter, extract two groups of pressure difference data for adjacent cycles, calculate the absolute difference of the pressure difference at multiple time points, merge to generate a difference sequence, accumulate and sum the differences to generate the total amount of periodic pressure difference differences; Specifically, when executing, first call the ultrasonic water meter to continuously monitor the internal pressure of the pipeline. A series of pressure difference readings are collected within three cycles (for example, cycle 1 is from 0 to 10 seconds, cycle 2 is from 10 to 20 seconds, and cycle 3 is from 20 to 30 seconds). For example, in cycle 1, the pressure difference readings measured at 0, 2, 4, 6, 8, and 10 seconds are {0.20 kPa, 0.22 kPa, 0.23 kPa, 0.26 kPa, 0.28 kPa, 0.30 kPa}, in cycle 2, the pressure difference readings measured at 10, 12, 14, 16, 18, and 20 seconds are {0.30 kPa, 0.33 kPa, 0.35 kPa, 0.38 kPa, 0.40 kPa, 0.43 kPa}, and in cycle 3, the pressure difference readings measured at 20, 22, 24, 26, 28, and 30 seconds are {0.43 kPa, 0.45 kPa, 0.47 kPa, 0.49 kPa, 0.52 kPa, 0.55 kPa}. Calculate the absolute difference at each time point for the pressure difference readings of adjacent cycles. For example, during the difference calculation at the corresponding time points between cycle 1 and cycle 2, the calculations are as follows: 0.30 kPa - 0.20 kPa = 0.10 kPa, 0.33 kPa - 0.22 kPa = 0.11 kPa, and so on until all corresponding points are calculated. Merge the differences to generate a new difference sequence {0.10 kPa, 0.11 kPa, 0.12 kPa, 0.12 kPa, 0.12 kPa, 0.13 kPa}. Further perform cumulative summation, and perform a summation operation on all elements of the difference sequence. Specifically, 0.10 + 0.11 + 0.12 + 0.12 + 0.12 + 0.13 = 0.70 kPa, and the total amount of periodic pressure difference differences of 0.70 kPa is obtained.

[0021] S102: Invoke the total amount of periodic pressure difference differences, perform difference judgments on multiple groups of values and the set judgment benchmark, calculate the degree of deviation between the difference and the benchmark, classify and summarize and set the value range, and generate the periodic pressure difference deviation range; Invoke the total amount of periodic pressure difference differences 0.70 kPa and compare it with the set judgment benchmark (determined by the water service department based on pipeline type, pipe diameter, water flow characteristics, and empirical data). Taking the standard water supply pipeline in the city (pipe diameter DN100, material is PE, judgment benchmark value is 0.50 kPa) as an example, the process of performing the difference judgment is as follows: Specifically, perform an absolute difference operation on the total amount of periodic pressure difference differences 0.70 kPa and the judgment benchmark 0.50 kPa, 0.70 kPa - 0.50 kPa = 0.20 kPa, and clearly obtain the degree of deviation of 0.20 kPa; Divide the obtained degree of deviation into value ranges. Through the preset range division standard, 0 - 0.05 kPa is the slight deviation range, 0.05 - 0.15 kPa is the medium deviation range, and above 0.15 kPa is the significant deviation range. Therefore, the degree of deviation of 0.20 kPa is classified into the significant deviation range; Finally, obtain the periodic pressure difference deviation range as "significant deviation range".

[0022] S103: According to the periodic pressure difference deviation range, invoke the total amount of periodic pressure difference differences, and perform operations in combination with the fluctuation value, pipe section length, and sampling interval. Use the formula: ; Obtain the change amplitude value and generate the periodic pressure difference change amplitude; Among them, represents the periodic pressure difference change amplitude of the first period, represents the pressure difference difference at the th moment of the first period, represents the judgment benchmark of the first period, represents the th moment of the first period of the pressure difference fluctuation value, represents the th moment of the first period of the pipe section length, represents the flow velocity increase parameter of the first period, represents the th moment of the first period of the sampling interval, represents the number of pressure difference sampling points within the period.

[0023] Invoke the total amount of periodic pressure difference differences 0.70 kPa, and perform subsequent operations with the fluctuation value, pipe section length, and sampling interval. The pressure difference fluctuation value inside the pipeline is obtained by collecting through monitoring equipment. For example, the pressure difference fluctuation values at 6 moments are respectively {0.03 kPa, 0.02 kPa, 0.03 kPa, 0.02 kPa, 0.03 kPa, 0.03 kPa}, and the pipe section length corresponding to each moment Obtained through actual measurement. For specific data, see Table 1: Table 1 Data Sheet for Measuring the Length of Pipe Sections , As shown in Table 1, the pipe section length data are all 10 meters, and each sampling interval is 2 seconds. The setting of the flow velocity increase parameter refers to the specification for the change in flow velocity of urban water supply pipes and is usually 0.05. The judgment criterion is 0.50 kPa. Based on the above data, calculate through the formula: ; Substitute the actual data for calculation: ; The further calculation process is as follows: First, calculate the values inside each pair of parentheses separately: The 1st item: (0.03 + 0.5) / 2 = 0.265, multiplied by 0.10 = 0.0265; The 2nd item: (0.02 + 0.5) / 2 = 0.260, multiplied by 0.11 = 0.0286; The 3rd item: (0.03 + 0.5) / 2 = 0.265, multiplied by 0.12 = 0.0318; The 4th item: (0.02 + 0.5) / 2 = 0.260, multiplied by 0.12 = 0.0312; The 5th item: (0.03 + 0.5) / 2 = 0.265, multiplied by 0.12 = 0.0318; The 6th item: (0.03 + 0.5) / 2 = 0.265, multiplied by 0.13 = 0.03445; Then sum them up: 0.0265 + 0.0286 + 0.0318 + 0.0312 + 0.0318 + 0.03445 = 0.18435; Finally, take the square root to get: ; This result of 0.4294 kPa represents the numerical value of the periodic pressure difference variation amplitude. Further, use this numerical value to represent the variation degree of the periodic pressure difference, and combine the periodic pressure difference deviation interval (significant deviation interval) to quantitatively describe the change in the pipeline state within the period. The benefit of the formula is that by multiplying the deviation between the parameter and by the standardized index combining the pipe section length and the pressure difference fluctuation, a more sensitive quantitative representation of the pressure difference variation amplitude is achieved.

[0024] Please refer to Figure 3 . The specific steps for obtaining the sampling frequency adjustment state are as follows: S201: Calculate the amplitude difference of the periodic pressure difference variation value based on the difference between the periodic pressure difference variation amplitude value and the set pressure difference determination reference value, determine whether the amplitude difference exceeds the pressure difference determination reference value threshold. If it exceeds, collect the flow velocity reading sequence within five cycles in the ultrasonic water meter to obtain the instantaneous flow velocity sequence; First, use the periodic pressure difference variation amplitude value as the starting data source for the execution action. The specific acquisition of the periodic pressure difference variation amplitude value is to obtain the pressure difference sequence between two measuring points before and after the pipeline through the ultrasonic water meter within a certain measurement period (for example, 5 consecutive measurement cycles, each cycle is 10 seconds). For example, the measured values of the pressure difference sequence are kPa, and the variation amplitude between adjacent measured values is obtained by using the successive difference calculation method for the above measured values. For example, the variation between the 1st and 2nd cycles is and the 2nd and 3rd cycles is and so on. The sequence of pressure difference variation amplitude values between each cycle is kPa. Then, select the maximum absolute value in this sequence (such as the maximum value in this example is 1.6 kPa) as the periodic pressure difference variation amplitude value. Subsequently, compare the periodic pressure difference variation amplitude value with the pressure difference determination reference value. The specific value of the pressure difference determination reference value is determined with reference to the usual allowable pressure difference fluctuation range in the water flow pipe network. A typical setting is shown in Table 2.

[0025] Table 2 Pressure Difference Determination Reference Value Setting Table , Referring to Table 2, in this example, a DN50 pipeline is used, the pressure difference determination reference value is set to 1.0 kPa, and its corresponding reference value threshold is 0.5 kPa. Subsequently, the specific execution action is to use the difference operation to judge the amplitude difference between the periodic pressure difference variation amplitude value and the pressure difference determination reference value. The specific operation is: , The difference result of 0.6 kPa exceeds the reference value threshold of 0.5 kPa, so it is determined to exceed the allowable range, and the next action is executed, that is, collect the instantaneous flow velocity reading sequence within 5 consecutive cycles from the ultrasonic water meter to obtain the instantaneous flow velocity sequence for the next calculation.

[0026] S202: Call the instantaneous flow velocity sequence, calculate the fluctuation range based on the instantaneous flow velocity of each of the five cycles, and use the formula: ; Calculate the new corrected value of the flow velocity standard deviation; Among them, represents the new corrected value of the flow velocity standard deviation, represents the instantaneous flow velocity value at the th moment within a single cycle, represents the average value of all instantaneous flow velocity values, represents the sample quantity, i.e., the number of cycles, is a coefficient adjusted according to the flow velocity change trend; Extract the sequence of instantaneous flow velocity readings within five consecutive cycles obtained from the previous step, and calculate the standard deviation fluctuation range based on this. Taking actual measurement as an example, the instantaneous flow velocity values read by the ultrasonic water meter within five cycles are m / s. Subsequently, perform a difference operation on each flow velocity value and the average flow velocity of the sequence. The calculation method of the average flow velocity of the sequence is: ; Next, calculate the square of the difference between each instantaneous flow velocity value and the average value of the sequence. The specific calculation process is as follows: The square of the difference of the first flow velocity point is calculated as , the second is , and so on. Complete the calculation of the square of the difference between all five flow velocity values and the average value to obtain the difference square sequence . After summing up the above sequence and dividing by the number of cycles minus 1, i.e., 4, the specific execution is: ; Perform a square root operation on this result to obtain the standard deviation as . Then adjust the standard deviation according to the adjustment coefficient of the flow velocity change trend. The value of this coefficient is determined by referring to the actual flow velocity fluctuation characteristics of the water meter. Usually, the setting range is from 1.0 to 1.5. In this example, it is taken as 1.2. The adjusted standard deviation is . In addition, perform a difference operation to determine the maximum flow velocity difference, that is, the difference between the maximum value 0.56 m / s and the minimum value 0.48 m / s in the sequence, which is 0.08 m / s. This difference is then weighted by the natural logarithm value of the number of cycles. The specific execution is , and finally sum up the two values, that is, 0.0385 m / s + 0.0497 m / s = 0.0882 m / s. Finally, a new corrected value of the flow velocity standard deviation is obtained.

[0027] S203: Compare the difference between the new corrected value of the flow velocity standard deviation and the preset flow velocity stability threshold. If it exceeds the flow velocity stability threshold, switch the sampling window and adjust the sampling frequency to the short-time high-frequency mode, and record the current frequency state to obtain the sampling frequency adjustment state value.

[0028] The specific execution is as follows: First, obtain the new corrected value of the flow velocity standard deviation from the previous step. For example, take the sequence of instantaneous flow velocity measured by the ultrasonic water meter within five cycles as (unit: m / s): , according to the formula provided in the previous step: ; Further explanation of the parameters in the formula: Among them, represents the instantaneous flow velocity in the th measurement period. For example, the above flow velocity values respectively correspond to , , and so on; represents the average value of five instantaneous flow velocities, calculated as: ; That is, the number of cycles is 5, is the flow velocity trend adjustment coefficient, which is set according to the water flow conditions. Usually, the value range is between 1.0 and 1.5. Here, 1.2 is taken as an example; the maximum flow velocity difference is 0.56 (maximum) minus 0.48 (minimum), that is, 0.08 m / s.

[0029] Substituting the values for calculation: ; The step-by-step calculation is as follows: First, calculate the variance part: ;

[0030] ; ;; ; The newly corrected value of the flow velocity standard deviation is 0.0882 m / s. The specific operation of comparing and analyzing this newly corrected value is to calculate the difference between this value and the preset flow velocity stability threshold. This threshold is usually set with reference to the flow velocity fluctuation range of the actual water meter during stable operation, as shown in Table 3.

[0031] Table 3 Flow Velocity Stability Threshold Setting Table , Referring to Table 3, the flow velocity corresponding to this example is 0.526 m / s, which belongs to the medium flow rate range. The selected flow velocity stability threshold is 0.050 m / s. Then, compare and calculate 0.0882 m / s obtained from the calculation with 0.050 m / s. The specific execution process is: ; This difference exceeds the preset threshold, which means that the fluctuation range of the current water meter's measured flow rate has exceeded the set allowable range. Perform a frequency adjustment action: switch the sampling window of the ultrasonic water meter to a shorter period, for example, adjust the original 10 seconds to 2 seconds, and at the same time adjust the sampling frequency from once per minute to once every 10 seconds. This adjustment process is achieved by modifying the cycle parameter in the program sampling instruction of the ultrasonic water meter. The specific instruction is to send a command to adjust the sampling parameters to the water meter through the communication interface. The parameter content is the sampling cycle "2s" and the frequency "6 times / min". After sending the instruction, the water meter immediately enters the short-term high-frequency mode and stores a record of the current frequency status mark in the device's memory, using this mark to indicate that the current device is operating in the high-frequency sampling mode, that is, the acquisition of the sampling frequency adjustment status value is completed.

[0032] Please refer to Figure 4 , and the specific steps for obtaining the flow rate credibility judgment index are as follows: S301: Based on the sampling frequency adjustment status, select the pressure difference sequence and the flow rate sequence within the period. After synchronously intercepting the sequences and correcting the time step, obtain the differences at adjacent moments in the order of the time axis, and construct a first-order difference sequence set; First, set the fluid measurement period. For example, it is determined that in an actual scenario, the pressure and flow rate of a certain oil pipeline are measured with a period of 5 seconds, and data is collected once per second. Then, a total of 5 groups of pressure difference information and flow rate data are obtained within the period, which are respectively recorded as the pressure difference sequence and the flow rate sequence . After intercepting the same time length for the above two sequences according to the time mark and unifying them into 5 data points, correct the time axis according to the set unified time step (one step per second here) to ensure that the pressure difference and flow rate data strictly correspond at each moment. Then, perform a difference operation on the pressure difference and flow rate sequences respectively, that is, calculate the difference between adjacent moment data to obtain the first-order difference sequence set. Specifically, calculate the pressure difference first-order difference sequence as , and at the same time obtain the flow rate first-order difference sequence as . The data volume of both sequences is 4 points, and this result constitutes the first-order difference sequence set for subsequent operations.

[0033] S302: Call the first-order difference sequence set, extract the pressure difference difference value and the flow rate difference value respectively according to the same time index, calculate the co-location ratio, and establish a numerical list for the ratio results corresponding to all moments to obtain the pressure difference - flow rate ratio sequence; During the execution of calling the first-order difference sequence set obtained above, extract the pressure difference difference value and the flow rate difference value one by one respectively, that is, in practice, call each data pair in turn. For example, the data pair at time 2 is the pressure difference difference value and the flow rate difference value . Subsequently, through the operation Calculate the co-location ratio values and store them in a numerical list. Repeat this operation to obtain 4 ratio values, forming a differential pressure - flow velocity ratio sequence. For example, the sequence may be , and an actual calculation example is that at a given moment, the differential pressure difference value is MPa, and the flow velocity difference value is m / s. Then the calculated co-location ratio value is , and so on.

[0034] S303: According to the differential pressure - flow velocity ratio sequence, combined with the upper and lower boundaries of the reference ratio interval of multiple ratios within the periodic segment, calculate the deviation degree and the sequence fluctuation intensity in turn, using the formula: ; After obtaining the flow velocity deviation determination value sequence through the operation, compare the multiple determination values with the confidence limit value to generate a flow velocity confidence judgment index; Among them, represents the flow velocity confidence judgment index, represents the differential pressure - flow velocity ratio at the th moment, represents the mean value of the differential pressure - flow velocity ratio sequence, represents the variance value of the th item in the ratio sequence, represents the absolute value of the first - order difference value of the flow velocity at the th moment, represents the half - width value of the reference ratio interval corresponding to the th moment, represents the total number of sample points within the period.

[0035] First, determine the reference ratio interval, which is obtained through the long - term data statistics of the measured differential pressure - flow velocity ratio on - site. For example, referring to the past 100 groups of measurement data, if the determined reference ratio range is , then the half - width value uniformly takes the interval half - width as 0.4. Further calculate the deviation degree of each ratio within the sequence from the mean value of the ratio sequence. For example, assume that the specific ratio sequence within this period is , then first calculate the sequence mean value , and further calculate the deviation amount. For example, the deviation value at moment 1 is . Continue to calculate the deviation amount of each point one by one to obtain a complete deviation degree sequence; at the same time, calculate the variance value of each item in the ratio sequence respectively. For example, the variance corresponding to moment 1 is . Similarly, calculate a complete variance sequence; further call the absolute value sequence of flow velocity differences . For example, the absolute value of the flow velocity difference at moment 1 is 0.05 m / s. Then sum up the respective for all points and then take the square root, such as ; Then, divide each of the above deviation values by the square root result respectively, and then divide by the half-width value of the corresponding reference ratio . Finally, sum up the results at all times to complete the calculation process of the credibility judgment index , as follows: ; The actual measurement data is shown in the following table: Table 4 Data table of pressure difference and flow rate measurement within the cycle , As shown in Table 4, the data at each time is obtained from the real-time monitoring of the on-site fluid transportation pipeline, and the data is measured by standard instruments. Among them, the pressure difference and the flow rate are measured by a pressure difference sensor and a flow meter respectively.

[0036] Compare the numerical value of the credibility judgment index with the preset credibility limit value (the reference value obtained through historical data statistics). For example, in the actual scenario, the credibility benchmark is set to 3.5. If 4.5 exceeds the benchmark value of 3.5, it means that the flow rate credibility within this cycle has decreased. This result indicates that there is an abnormal fluctuation in the flow rate within the cycle, and this numerical result is an important basis for generating the flow rate credibility judgment index.

[0037] The innovation of the formula lies in that by introducing a comprehensive fluctuation quantity composed of a pressure difference - flow rate ratio sequence, variance, and the absolute value of flow rate difference, it accurately expresses the amplitude of data fluctuation and the abnormal deviation situation in the operation, enhancing the sensitivity and accuracy of the credibility index to the abnormal fluctuation of the real flow rate.

[0038] Please refer to Figure 5 . The specific steps for obtaining the abnormal cycle to replace the flow rate are as follows: S401: Based on the current cycle flow rate reading and the current flow rate credibility judgment index, judge whether the current cycle flow rate data is in a credible state. Compare the current cycle flow rate credibility index with the preset flow rate credibility determination threshold. If it is less than the flow rate credibility determination threshold, then determine that the current cycle is an abnormal cycle and obtain the abnormal cycle marking status; The specific implementation is as follows: First, obtain the flow rate value measured within the current monitoring cycle. For example, at a certain hydrological measurement station, the current cycle flow rate reading is , and at the same time, call the numerical value of the flow rate credibility judgment index corresponding to the current cycle. For example, the credibility judgment index is ; Subsequently, by obtaining a pre-set threshold for judging the credibility of the flow rate, the setting process of this threshold is generally based on the statistical analysis result of the credibility of historical flow rate monitoring data. By statistically analyzing the historical data of a certain measuring station, for example, selecting 100 historical cycle data, it is found through analysis that the normal distribution range of the flow rate credibility index is 0.85 - 0.95. The credibility judgment threshold is set to the lower limit of this range, that is, the threshold is 0.85; then the numerical value of the credibility judgment index for the current cycle is numerically compared with the credibility threshold, and the numerical comparison action is performed. Specifically, directly is compared with the credibility threshold of 0.85. Since 0.78 is less than 0.85, it is determined that the data for this cycle is in an abnormal state. Therefore, the flow rate reading for the current cycle is marked as an abnormal cycle state, and this state mark is recorded.

[0039] S402: Call the abnormal cycle marking state, extract the flow rate readings of the adjacent previous and next cycles for the flow rate data determined to be an abnormal cycle, mark them as the flow rate of the previous cycle and the flow rate of the next cycle, and record the flow rate of the current cycle. Use the formula: ; Calculate the adjusted cycle flow rate value, replace the original reading of the current abnormal cycle, and generate an abnormal cycle alternative flow rate value; Among them, represents the adjusted cycle flow rate value, represents the flow rate of the previous cycle, represents the flow rate of the next cycle, represents the flow rate of the current cycle; The execution steps include: First, call the stored flow rate reading of the previous cycle and the flow rate reading of the next cycle . The specific process is, for example, if the current cycle is the 10th cycle, then the flow rate reading measured in the 9th cycle is , and the flow rate reading measured in the 11th cycle is ; and call the original flow rate reading of the current cycle , then use the formula: ; Calculate the adjusted abnormal cycle alternative flow rate value, and the detailed explanations of each parameter are as follows: : Represents the new flow rate value calculated to replace the abnormal flow rate of the current cycle; : Represents the actually monitored flow rate value of the previous normal cycle before the current abnormal cycle. In this embodiment, it is the flow rate value of the 9th cycle, and the value is 3.2 m / s; : Represents the actual monitored flow velocity value in the normal cycle following the current abnormal cycle. In this embodiment, it is the flow velocity value in the 11th cycle, with a value of 3.6 m / s; : Represents the original monitored flow velocity value in the current cycle, with a value of 3.4 m / s; Subsequently, the above values are substituted into the formula for calculation: First, perform the sum of squares calculation: ; Then, perform the square root operation: ; Then, multiply it with the flow velocity value in the current cycle for the product calculation: ; Then, calculate the absolute value of the flow velocity difference between the previous and current cycles: ; Then, sum it with the constant 1: ; Finally, perform the division operation to obtain the alternative flow velocity: ; The finally calculated alternative flow velocity value for the abnormal cycle is 11.6974 m / s.

[0040] S403: Call the alternative flow velocity value for the abnormal cycle, replace the current cycle flow velocity reading originally marked as abnormal, and update the value at the cycle position in the original flow velocity dataset to obtain the alternative flow velocity for the abnormal cycle.

[0041] Call the alternative flow velocity value for the abnormal cycle, that is , perform the specific replacement action: Through the data storage instruction, directly update the value at the position of the abnormal state cycle in the original flow velocity dataset, and replace the original flow velocity value marking the abnormal cycle with the currently calculated alternative value , and redeposit it at the original position in the flow velocity dataset. At this time, the flow velocity data of the 10th cycle in the original dataset is updated to the newly calculated alternative flow velocity value of 11.6974 m / s.

[0042] Please refer to Figure 6 , the specific steps for obtaining the cycle sampling frequency status value are as follows: S501: Based on the alternative flow velocity for the abnormal cycle, call the flow velocity information and pressure difference sampling sequence in the initial cycle, calculate the pressure difference amplitude and flow velocity change rate at multiple sampling points within the cycle, construct a set of continuous fluctuation indicators in the sampling sequence, and obtain the pressure difference - flow velocity fluctuation indicator sequence; First, call the flow velocity information and the corresponding differential pressure information obtained at each sampling point during the initial period. The process of obtaining this information is through multiple flow velocity sensors and differential pressure sensors arranged at fixed positions in the pipeline. Assume that 5 points are sampled within an initial period (for example, within 5 seconds), and the flow velocity sequence data and the corresponding differential pressure sequence data are collected. Call these data for point-by-point operations. For two adjacent sampling points, such as the first point (flow velocity 3.5 m / s, differential pressure 20 kPa) and the second point (flow velocity 3.6 m / s, differential pressure 22 kPa), calculate the differential pressure change amount and the flow velocity change rate respectively. That is, the differential pressure amplitude is , and the flow velocity change rate is (assuming the sampling interval is 0.2 seconds). Subsequently, call the next adjacent sampling point for similar calculations, and repeat the above actions in sequence to obtain the fluctuation indexes of all sampling points, and form a complete differential pressure - flow velocity fluctuation index sequence. That is, in the sequence of 5 points, gradually obtain the differential pressure amplitude sequence and the flow velocity change rate sequence . Then, form a set of continuous fluctuation indexes within the period for the above sequences, and finally obtain a complete differential pressure - flow velocity fluctuation index sequence as the final result of this paragraph.

[0043] S502: Call the differential pressure - flow velocity fluctuation index sequence, and based on the corresponding sampling points of differential pressure and flow velocity in two periods, construct the ratio of the differential pressure difference to the flow velocity difference at adjacent moments, using the formula: ; Calculate the differential pressure - flow velocity ratio at each moment to form a ratio sequence, and conduct periodic fluctuation analysis based on the sequence average value and the difference amplitude to obtain the period - normalized fluctuation difference; Among them, represents the differential pressure - flow velocity ratio of period , represents the differential pressure value of the th sampling point in period , represents the differential pressure value of the th sampling point in period , represents the flow velocity value of the th sampling point in period , represents the flow velocity value of the th sampling point in period , represents a positive constant to avoid a zero denominator, represents the sampling point number within the period; Call the differential pressure and flow velocity fluctuation index sequence, and take the sampled data of the differential pressure and flow velocity corresponding to adjacent periods (period a and period b, for example, two adjacent 5-second sampling periods). For example, the sampled data of period a is the differential pressure sequence and the flow velocity sequence , and the data of period b is the differential pressure sequence and the flow velocity sequence . Call the above data into the formula one by one: ; where and represent the differential pressure values at the jth sampling point in period a and period b respectively, and represent the flow velocity values at the jth sampling point in period a and period b respectively, is a small positive value to avoid the denominator being zero (such as ); Specific operation example: Substitute the first sampling point into the formula and calculate as: ; Calculate the sequence from the 2nd to the 5th sampling point in turn to obtain: . Call the above ratio sequence, perform numerical average operation and comparison of the difference amplitude on each value in the sequence, that is, calculate its sequence mean value as . Then call the deviation of each point from the sequence mean value, and then obtain the fluctuation difference value of each point. Finally, perform normalization processing on all fluctuation difference values, that is, divide each fluctuation difference value by the mean value to obtain the period-normalized fluctuation difference sequence as the final result.

[0044] S503: Make a numerical amplitude judgment based on the period-normalized fluctuation difference value and the set period fluctuation threshold, and make a comparison judgment in combination with the initial setting of the sampling frequency and the adjusted mark status value to generate the period sampling frequency status value.

[0045] The period-normalized fluctuation difference value is obtained through the above calculation, for example, it is , then call the initially set periodic fluctuation threshold for each value. For example, set the threshold to 0.02. The specific execution process for numerical amplitude judgment is as follows: Compare each element of the normalized fluctuation difference directly with the threshold. Assume that when the periodic normalized fluctuation difference is 0.01, which is less than the threshold 0.02, then the judgment status value is "stable"; when the normalized fluctuation difference is 0.02, equal to the threshold, the status value is judged as "critically stable"; when the normalized fluctuation difference is greater than 0.02, the status value is "unstable". Further, call the initially set sampling frequency (for example, the initial sampling frequency is 5Hz) and compare it with the sampling frequency adjustment marker status value. Specifically: If the above status value is "unstable", then perform the action of updating the frequency adjustment marker status value and mark the status value as "frequency needs to be increased"; if the status is "stable" or "critically stable", then mark the status value as "maintain the frequency unchanged". The sampling frequency status value obtained through the above comparison and judgment is: When any fluctuation difference within the period is judged as "unstable", then the overall marked periodic sampling frequency status value is "frequency increased"; otherwise, the status value remains "frequency unchanged".

[0046] Table 5 Periodic Sampling Parameter Table , As shown in Table 5, each parameter is specifically obtained from the measured data of periods a and b. After calculation, the pressure difference - flow velocity ratio of each sampling point is 9.90 kPa·s / m. After comparing the periodic normalized fluctuation difference with the preset threshold of 0.02, the sampling frequency adjustment marker status value is determined.

[0047] The benefit of the formula is that through the ratio operation between the pressure difference and the specific sampling points of the flow velocity, the stability of the flow within the period is accurately determined in real - time, and further determine whether it is necessary to adjust the periodic sampling frequency status.

[0048] An intelligent monitoring system for an Internet of Things ultrasonic water meter. The intelligent monitoring system for the Internet of Things ultrasonic water meter is used to execute the above - mentioned intelligent monitoring method for the Internet of Things ultrasonic water meter. The system includes: The pressure difference detection module acquires the pipe section pressure difference signal sequences of three periods, calculates and accumulates the absolute differences between adjacent periods, calls the pressure difference change reference value for comparison, and obtains the periodic pressure difference change amplitude; The fluctuation judgment module, based on the periodic pressure difference change amplitude, if it exceeds the pressure difference change reference value, collects five instantaneous flow velocity readings, calculates its standard deviation and compares it with the flow velocity stability threshold. If the trigger condition is met, adjusts the sampling window and switches to the high - frequency mode, records the frequency switching situation, and generates the sampling frequency adjustment status; The credibility evaluation module, based on the sampling frequency adjustment status, extracts the corresponding pressure difference and flow velocity sequences, performs the first - order difference processing and calculates the co - location ratio, calls the credible reference interval judgment, and obtains the flow velocity credibility judgment index; The data correction module extracts the flow velocity readings before and after the current period according to the flow velocity credibility judgment index, assigns weights in sequence and performs weighted averaging, uses it to replace the current flow velocity value, and generates an alternative flow velocity for the abnormal period. The frequency control module calls the alternative flow velocity for the abnormal period, collects the differential pressure and flow velocity sequences of the subsequent two periods, calculates the fluctuation values respectively and compares them with the set reference values to judge whether to resume the sampling frequency, and obtains the periodic sampling frequency status value.

[0049] The above is only a preferred embodiment of the present invention, and does not limit the present invention in other forms. Any person skilled in the art may use the technical content disclosed above to make changes or modifications 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 content of the present invention still belong to the protection scope of the technical solution of the present invention.

Claims

1. An intelligent monitoring method for an Internet of Things ultrasonic water meter, characterized in that: The following steps are involved: S1: Obtain a sequence of three consecutive cycle differential pressure readings in the ultrasonic water meter, calculate the absolute difference between adjacent cycle data, accumulate the difference and compare it with the judgment benchmark to generate the cycle differential pressure variation amplitude; S2: According to the fluctuation amplitude of the periodic pressure difference, if it exceeds the judgment standard, collect the instantaneous flow velocity reading sequence of five periods in the ultrasonic water meter, perform standard deviation calculation to obtain the flow velocity fluctuation value of the current period, compare it with the set flow velocity stability threshold, switch the sampling window and adjust the sampling frequency to the short-time high-frequency mode, and record the sampling frequency adjustment status; S3: based on the sampling frequency adjustment state, extract the corresponding periodic pressure difference and flow rate sequence, calculate the first-order difference and then find the isotopic ratio, compare it with the reference interval, and obtain the flow rate credibility judgment index; S4: Based on the velocity credibility judgment index, if the current cycle data is in a low credibility state, extract the velocity readings of the previous and next cycles, perform weighted average in sequence according to the weights, replace the original readings, and generate an alternative velocity for the abnormal cycle; S5: calling the abnormal cycle to replace the flow rate, obtaining the pressure difference and flow rate sequence of the next two cycles, respectively calculating the fluctuation values ​​and then comparing and judging, restoring the initial sampling frequency, and obtaining the periodic sampling frequency state value.

2. The intelligent monitoring method of the Internet of Things ultrasonic water meter according to claim 1 is characterized in that: The periodic pressure difference variation amplitude specifically includes the fluctuation range, deviation level, and risk signal; the sampling frequency adjustment state specifically includes the mode state, frequency configuration, and adjustment record; the flow velocity credibility judgment index includes the stability score, trust level, and judgment result; the abnormal periodic alternative flow velocity specifically includes the smoothed flow velocity, correction value, and alternative data; the periodic sampling frequency state value specifically includes the initial mode, frequency recovery, and state feedback.

3. The intelligent monitoring method of the Internet of Things ultrasonic water meter according to claim 2 is characterized in that: The steps for obtaining the periodic pressure difference variation amplitude are specifically as follows: S101: based on the pipeline pressure difference reading sequence of three consecutive cycles obtained from the ultrasonic water meter, extract two sets of pressure difference data of adjacent cycles, calculate the absolute difference of the pressure difference at multiple time points, merge to generate a difference sequence, accumulate and sum the differences, and generate a total period pressure difference difference; S102: calling the total amount of the periodic pressure difference difference, performing difference judgment on multiple groups of values ​​and the set judgment reference, calculating the degree of deviation between the difference and the reference, classifying and summarizing and setting the value interval, and generating the periodic pressure difference deviation interval; S103: According to the periodic pressure difference deviation interval, the total periodic pressure difference difference is called, and the calculation is performed in combination with the fluctuation value, the pipe section length and the sampling interval, using the formula: ； Obtain the variation amplitude value and generate the periodic pressure difference variation amplitude; in, Represents the cycle pressure difference variation amplitude of the first cycle, Represents the first cycle The pressure difference at each moment, represents the judgment criteria for the first cycle, Represents the first cycle The pressure difference fluctuation value at the moment, Represents the first cycle The length of the pipe section at the time, Represents the velocity increase parameter of the first cycle, Represents the first cycle The sampling interval at time, Represents the number of pressure difference sampling points in a cycle.

4. The intelligent monitoring method of the Internet of Things ultrasonic water meter according to claim 3 is characterized in that: The steps for obtaining the sampling frequency adjustment state are specifically as follows: S201: Based on the difference between the periodic pressure difference variation amplitude value and the set pressure difference judgment reference value, the amplitude difference of the periodic pressure difference variation value is calculated, and it is determined whether the amplitude difference exceeds the pressure difference judgment reference value threshold value. If it exceeds, the flow velocity reading sequence within five cycles of the ultrasonic water meter is collected to obtain the instantaneous flow velocity sequence; S202: calling the instantaneous flow rate sequence, and calculating the fluctuation range based on each instantaneous flow rate of five cycles, using the formula: ； Calculate and obtain a new corrected value of the flow velocity standard deviation; in, represents the new corrected value of the standard deviation of the flow rate, Represents the first The instantaneous flow velocity value at time, Represents the average value of all instantaneous flow velocity values, represents the number of samples, i.e. the number of cycles, It is the coefficient adjusted according to the flow velocity change trend; S203: Compare the difference between the new corrected value of the flow rate standard deviation and the preset flow rate stability threshold. If the flow rate stability threshold is exceeded, switch the sampling window and adjust the sampling frequency to the short-time high-frequency mode, record the current frequency state, and obtain the sampling frequency adjustment state value.

5. The intelligent monitoring method of the Internet of Things ultrasonic water meter according to claim 4 is characterized in that: The steps for obtaining the flow velocity credibility judgment index are specifically as follows: S301: Based on the sampling frequency adjustment state, a pressure difference sequence and a flow rate sequence within a period are selected, the sequences are synchronously intercepted and the time step is corrected, and then the difference between adjacent moments is obtained in the order of the time axis to construct a first-order difference sequence set; S302: calling the first-order difference sequence set, extracting the pressure difference difference value and the flow velocity difference value respectively according to the same time index, calculating the same position ratio, and establishing a numerical list for the ratio results corresponding to all moments to obtain a pressure difference flow velocity ratio sequence; S303: According to the pressure difference flow rate ratio sequence, combined with the upper and lower boundaries of the reference ratio interval of multiple ratios in the periodic segment, the deviation degree and the sequence fluctuation intensity are calculated in turn, using the formula: ； After the flow velocity deviation judgment value sequence is obtained by operation, the multiple judgment values ​​are compared with the credibility limit value to generate the flow velocity credibility judgment index; in, It indicates the flow velocity credibility judgment index. Indicates The pressure difference flow rate ratio at the time, represents the mean of the pressure difference flow rate ratio series, Indicates the ratio sequence The variance of the item, Indicates The absolute value of the first-order difference of the flow velocity at time , Indicates The half-width value of the reference ratio interval corresponding to the moment, Indicates the total number of sample points in the period.

6. The intelligent monitoring method of the Internet of Things ultrasonic water meter according to claim 5 is characterized in that: The steps for obtaining the abnormal period alternative flow rate are specifically as follows: S401: Based on the current cycle flow velocity reading and the current flow velocity credibility judgment index, determine whether the current cycle flow velocity data is in a credible state, compare the current cycle flow velocity credibility index with a preset flow velocity credibility judgment threshold, if it is less than the flow velocity credibility judgment threshold, determine that the current cycle is an abnormal cycle, and obtain an abnormal cycle marking state; S402: calling the abnormal cycle marking state, extracting the flow velocity readings of the adjacent cycles before and after the flow velocity data determined as the abnormal cycle, marking them as the flow velocity of the previous cycle and the flow velocity of the next cycle, and recording the flow velocity of the current cycle, using the formula: ； Calculate the adjusted cycle flow rate value, replace the original reading of the current abnormal cycle, and generate an alternative flow rate value for the abnormal cycle; in, Indicates the adjusted cycle flow rate value, Indicates the flow rate of the previous cycle, represents the flow rate of the next cycle, Indicates the flow rate of the current cycle; S403: calling the abnormal period replacement flow rate value to replace the current period flow rate reading originally marked as abnormal state, and updating the value of the period position in the original flow rate data set to obtain the abnormal period replacement flow rate.

7. The intelligent monitoring method of the Internet of Things ultrasonic water meter according to claim 6 is characterized in that: The steps for obtaining the periodic sampling frequency state value are specifically as follows: S501: Based on the abnormal cycle replacement flow rate, the flow rate information and the pressure difference sampling sequence in the initial cycle are called, the pressure difference amplitude and the flow rate change rate of multiple sampling points in the cycle are calculated, and a continuous fluctuation index set in the sampling sequence is constructed to obtain a pressure difference flow rate fluctuation index sequence; S502: Call the pressure difference and flow velocity fluctuation index sequence, and construct the ratio of the pressure difference difference to the flow velocity difference at adjacent moments based on the corresponding sampling points of the pressure difference and flow velocity in two cycles, using the formula: ； Calculate the pressure difference and flow rate ratio at each moment to form a ratio sequence, and perform periodic fluctuation analysis based on the sequence average and difference amplitude to obtain the periodic normalized fluctuation difference; in, Representative cycle The pressure difference flow rate ratio, Representation cycle Middle The pressure difference value of the sampling points, Representation cycle Middle The pressure difference value of the sampling points, Representation cycle Middle The flow velocity value at each sampling point, Representation cycle Middle The flow velocity value at each sampling point, Represents a positive constant that avoids zero denominator. Indicates the sampling point number within the cycle; S503: Performing numerical amplitude judgment based on the period normalized fluctuation difference and the set period fluctuation threshold, performing comparison and judgment in combination with the initial setting of the sampling frequency and the adjustment mark state value, and generating a period sampling frequency state value.

8. An intelligent monitoring system for an Internet of Things ultrasonic water meter, characterized in that: According to the intelligent monitoring method of the Internet of Things ultrasonic water meter according to any one of claims 1 to 7, the system comprises: The pressure difference detection module obtains the pipeline pressure difference signal sequence of three cycles, calculates and accumulates the absolute difference between adjacent cycles, calls the pressure difference change reference value for comparison, and obtains the cycle pressure difference change amplitude; The fluctuation judgment module collects five instantaneous flow rate readings according to the fluctuation amplitude of the periodic pressure difference. If it exceeds the pressure difference fluctuation reference value, the module calculates the standard deviation and compares it with the flow rate stability threshold. If the trigger condition is met, the module adjusts the sampling window and switches to the high-frequency mode, records the frequency switching situation, and generates the sampling frequency adjustment status. The credible assessment module extracts the corresponding pressure difference and flow rate sequence based on the sampling frequency adjustment state, performs first-order difference processing and calculates the isotope ratio, calls the credible reference interval judgment, and obtains the flow rate credibility judgment index; The data correction module extracts the flow velocity readings before and after the current cycle according to the flow velocity credibility judgment index, weights them in sequence and performs weighted average, and uses them to replace the current flow velocity value to generate an abnormal cycle replacement flow velocity; The frequency control module calls the abnormal cycle to replace the flow rate, collects the pressure difference and flow rate sequence of the subsequent two cycles, calculates the fluctuation value and compares it with the set reference value, determines whether to restore the sampling frequency, and obtains the periodic sampling frequency state value.

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