Drip metering method of ultrasonic water meter

Abstract

The invention provides a drip metering method for an ultrasonic water meter, which improves the metering precision of the water meter by accurately measuring tiny changes in water flow, particularly drip events, and comprises the following steps: firstly, a sensor of the ultrasonic water meter acquires water flow signal data in real time, including flow information, flow fluctuation and water flow state, and transmits the data to a signal processing module; through noise removal, signal gain adjustment, waveform amplitude detection and other processing, a system compares the data with a set threshold value, identifies a water dripping event, calculates a flow fluctuation difference value and judges the occurrence of a water dripping behavior, and finally, the system records detailed information of the event and stores the detailed information in a memory for subsequent query. Through the precise signal processing and water dripping event recognition method, the recognition precision of the low-flow water dripping event is effectively improved, missing report and false report are avoided, meanwhile, recording of detailed information and efficient data storage are supported, data integrity and accuracy are ensured, and the intelligent level and practicability of the water meter are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of water meters, and specifically to an ultrasonic water meter dripping measurement method. Background Art

[0002] With the rapid development of intelligent technologies, water meters, as common devices in daily life, have gradually received extensive attention in their intelligent transformation. Traditional water meters mainly rely on mechanical pointers or electronic components to measure water flow, which have certain limitations. Especially in the measurement and monitoring of tiny dripping behaviors, traditional technologies fail to fully meet the requirements. To solve this problem, ultrasonic water meters have emerged. Ultrasonic water meters utilize ultrasonic technology to calculate the flow velocity of water through the time difference of propagation, thereby accurately reflecting the water flow rate;

[0003] Although the existing technologies have made certain progress in the field of water meters, the existing ultrasonic water meters generally have difficulties in identifying dripping events. They rely on the fluctuation of the overall flow rate to judge whether a dripping event occurs, but this often cannot accurately distinguish normal flow rate changes and tiny dripping behaviors. The tiny changes in water flow are often masked by noise, resulting in missed reports or false reports of dripping events. At the same time, the current technologies lack effective algorithms to accurately identify dripping behaviors, especially in the case where the amplitude of flow rate fluctuation is extremely small and the periodicity is strong. In addition, the existing technologies also have deficiencies in the accuracy of data storage and subsequent analysis of dripping events, especially in the data storage and query efficiency during long-term operation. Therefore, there is an urgent need for a new ultrasonic water meter dripping measurement method to solve the above problems and improve the identification accuracy of dripping events and data processing efficiency. Summary of the Invention

[0004] In order to solve the technical problems of missed reports or false reports in low-flow dripping events, inability to accurately identify tiny dripping behaviors, and deficiencies in the data storage and query efficiency of dripping events in the existing technologies mentioned in the current background art, the present invention proposes an ultrasonic water meter dripping measurement method.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] An ultrasonic water meter dripping measurement method, comprising:

[0007] S1. Real-time collect the water flow signal data flowing through the water pipe through the sensor of the ultrasonic water meter. The water flow signal data includes water flow information, flow rate fluctuation, and sequential information of the water flow state. The sensor collects the water flow signal data based on the ultrasonic reflection principle;

[0008] S2. Process the water flow signal data. The processed water flow signal data is used to calculate and extract water flow parameters. The extraction of water flow parameters includes the calculation of water flow velocity and the calculation of flow rate fluctuations. At the same time, through the analysis of the water flow state, the periodic fluctuations of the water flow parameters are further analyzed, and the frequency and amplitude of the change in water flow rate are calculated;

[0009] S3. Based on the comparison between the extracted water flow parameters and the set dripping event detection thresholds, identify the dripping events. The threshold setting includes the setting of amplitude threshold and frequency threshold. The identification of the dripping events includes the comparison of the amplitude of flow rate fluctuations and the comparison of the frequency of flow rate fluctuations, which is used for the further confirmation and identification of the dripping events;

[0010] S4. After the dripping event is identified, calculate the change amplitude of the water flow by calculating the difference in flow rate fluctuations in the water flow parameters, and compare this difference with the detection threshold in S3 to determine the occurrence of the dripping behavior;

[0011] S5. When the dripping behavior is determined, record the detailed information of the dripping event, including the start time, end time, duration, and cumulative water droplet volume of the event, and store this information in the memory of the water meter for subsequent query and analysis.

[0012] Further, the water flow signal processing includes noise removal, signal gain adjustment, and waveform amplitude detection. Among them, the noise filtering module is used to remove external interference in the water flow signal, the gain adjustment module is used to adjust the amplitude of the water flow signal, and the waveform analysis module is used to analyze the signal waveform.

[0013] Further, the water flow velocity in the water flow parameters is calculated by the time difference Δt of ultrasonic signal propagation. The calculation formula is:

[0014]

[0015] where v is the water flow velocity, c is the propagation velocity of ultrasonic waves in water, Δt is the time difference of signal propagation, and d is the distance from the sensor to the water flow.

[0016] Further, the flow rate fluctuation in the water flow parameters is calculated by the change in water flow velocity, and there is the following relationship between the flow rate Q of the water flow and the velocity v:

[0017] ΔQ = A·Δv

[0018] where ΔQ is the flow rate fluctuation, A is the cross-sectional area of the water pipe, and Δv is the change in velocity.

[0019] Further, the periodic fluctuation analysis in S2 quantifies the water flow signal through three methods: RMS calculation, Fourier transform, and autocorrelation function;

[0020] RMS calculation is used to quantify the amplitude variation of the water flow signal, and the calculation formula is:

[0021]

[0022] where RMS is the root mean square value of the water flow signal, x i is the value of each sampling point of the water flow signal, and N is the total number of sampling points of the water flow signal;

[0023] Fourier transform analyzes the frequency components of periodic fluctuations by converting the time-domain signal to the frequency domain, and the calculation formula is:

[0024]

[0025] where F freq (ω) is the frequency-domain representation of the water flow signal, f(t) is the time-domain representation of the water flow signal, and ω is the angular frequency of the water flow signal;

[0026] The autocorrelation function is used to detect periodic fluctuations in the water flow signal, and the calculation formula is:

[0027]

[0028] where R(τ) is the autocorrelation function of the water flow signal, τ is the delay time, x i and x i+τ are two sampling points of the time-domain signal respectively.

[0029] Furthermore, the water flow variation amplitude in S4 can be reflected by calculating the difference between the maximum and minimum values of the flow rate fluctuation in the water flow parameters, and the calculation formula is:

[0030] ΔQ = Q max -Q min

[0031] where ΔQ is the flow rate fluctuation difference, Q max is the maximum value in the flow rate fluctuation, and Q min is the minimum value in the flow rate fluctuation.

[0032] Furthermore, the cumulative water drip volume in S5 refers to the cumulative flow rate fluctuation of the water flow during the drip event, which is calculated by combining the amplitude of the flow rate fluctuation and the duration of the event, and provides detailed data on the impact of the drip event on water consumption for the system by calculating the cumulative amount of the flow rate fluctuation during the drip event. The calculation formula is:

[0033]

[0034] where Q total is the cumulative water drip volume, Q(t) is the instantaneous flow rate during the event, t 1 and t2 They are the start time and end time of the event respectively.

[0035] Furthermore, the information storage in S5 is generally carried out in the form of data fields. The specific data storage fields include:

[0036] 1) event id: The unique identifier of the dripping event;

[0037] 2) starttime: The start time of the dripping event, recorded as a timestamp;

[0038] 3) end time: The end time of the dripping event, recorded as a timestamp;

[0039] 4) duration: The duration of the dripping event;

[0040] 5) total drip volume: The cumulative water drip volume during the dripping event;

[0041] 6) additional data: Supplementary information.

[0042] Furthermore, the data transmission methods in S1 are divided into wired transmission and wireless transmission. Among them, wired transmission means that the data is transmitted to the signal processing module through a wired connection, and wireless transmission means that in the case of flexible layout or remote monitoring required, the collected water flow signal data can be transmitted to the remote signal processing module through the wireless communication module.

[0043] Furthermore, the water meter supports quick retrieval of dripping event data, and the query methods include querying by time interval, event type, and by cumulative water drip volume.

[0044] Compared with the prior art, the advantages of the present invention are as follows:

[0045] 1. Aiming at the problems of missed reports or false reports in the prior art for low-flow dripping events, the present invention can accurately identify the tiny changes in water flow by collecting the water flow signal data in real time based on the sensor of the ultrasonic water meter, combining the comparison of the flow fluctuation amplitude and frequency, and through the extraction of water flow parameters and the analysis of periodic fluctuations. The present invention can effectively distinguish normal water flow fluctuations and dripping behaviors, thus greatly improving the identification accuracy of dripping events and avoiding the phenomena of missed reports or false reports;

[0046] 2. In view of the problem that the prior art cannot accurately identify tiny dripping behaviors, the present invention introduces a method of comparing the flow rate fluctuation difference with a set detection threshold. After the dripping event is identified, the difference between the maximum value and the minimum value of the flow rate fluctuation in the water flow parameters is further calculated, which accurately reflects the change range of the water flow. This method can effectively exclude external interference and noise, accurately determine the occurrence of the dripping behavior, and provide a more accurate basis for the subsequent data recording and analysis of the dripping event;

[0047] 3. In view of the deficiencies of the prior art in terms of the data storage and query efficiency of dripping events, the present invention accurately records the detailed data of the dripping events (such as the start time, end time, duration, and cumulative water droplet volume of the event), and uses non-volatile memory for storage. At the same time, the present invention also supports the rapid retrieval of data and can query according to fields such as time intervals, event types, and cumulative water droplet volume, greatly improving the data storage and query efficiency of the water meter during long-term operation and ensuring data integrity and convenience of use. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present application. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0049] Figure 1 It is a flowchart of the ultrasonic water meter dripping measurement method of the present invention;

[0050] Figure 2 It is a schematic diagram of the water flow state analysis method of the present invention;

[0051] Figure 3 It is a schematic diagram of the dripping behavior determination steps of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0052] To make the objectives, technical solutions, and advantages of the embodiments of the present application clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present application without creative efforts shall fall within the scope of protection of the present application.

[0053] To achieve the above objectives, the present invention is implemented through the following technical solutions. The present invention provides an ultrasonic water meter dripping measurement method, as Figure 1 shown, the method includes:

[0054] S1. Real - time collect the water flow signal data flowing through the water pipe by the sensor of the ultrasonic water meter. The water flow signal data includes water flow information, flow rate fluctuation and the timing information of the water flow state. The sensor collects the water flow signal data based on the ultrasonic reflection principle.

[0055] Real - time collect the water flow signal data flowing through the water pipe by the sensor of the ultrasonic water meter. The specific collection process is as follows:

[0056] Water flow information: The water flow information mainly refers to the flow velocity of the water flow. The propagation speed of ultrasonic waves in the water flow is closely related to the flow velocity of the water flow. In places with a faster flow velocity, the propagation time of the ultrasonic signal is shorter; while in places with a slower flow velocity, the propagation time is longer. By measuring the propagation time difference of the signal, the sensor can sense the change in the flow velocity of the water flow.

[0057] The specific collection steps are: The sensor emits an ultrasonic signal. When the signal passes through the water flow, affected by the water flow velocity, the propagation time changes. Through the propagation time difference of the reflected signal, the sensor can collect the water flow information, that is, the flow velocity.

[0058] Flow rate fluctuation: The flow rate fluctuation refers to the change of the water flow within a certain period of time. The fluctuation of the water flow rate will cause the change of the water flow rate. The propagation time of the ultrasonic signal changes with the fluctuation of the water flow rate. The sensor identifies the fluctuation of the water flow rate by capturing these changes in the propagation time.

[0059] The specific collection steps are: When the flow velocity of the water flow changes, the propagation time of the ultrasonic signal also fluctuates. The fluctuation of the flow velocity is manifested as the periodic change of the signal propagation time, which reflects the flow rate fluctuation. The sensor monitors these fluctuations and can collect the flow rate fluctuation information of the water flow by analyzing the time - domain characteristics of the ultrasonic signal.

[0060] Timing information of the water flow state: The timing information of the water flow state reflects different dynamic characteristics of the water flow, such as steady flow, turbulent flow, dripping, etc. The state of the water flow will affect the amplitude and frequency of the ultrasonic signal, and thus affect the timing characteristics of the signal.

[0061] The specific collection steps are: The sensor can collect the timing information of the water flow state by monitoring the periodic change of the ultrasonic signal. For example, in the case of a stable flow velocity, the change of the sensor signal is stable, with a regular and small amplitude. In the turbulent flow state, the irregularity of the water flow velocity makes the change of the ultrasonic signal more intense, with a large amplitude and an irregular frequency. When dripping, the signal shows periodic and small - amplitude fluctuations.

[0062] Data transmission methods are divided into wired transmission and wireless transmission: Among them, wired transmission means that data is transmitted to the signal processing module through a wired connection (such as a serial port, Ethernet). This method provides more stable and low-latency data transmission and is suitable for short-distance application scenarios; wireless transmission is used when flexible layout or remote monitoring is required. The collected water flow signal data can be transmitted to the remote signal processing module through a wireless communication module (such as Wi-Fi, Bluetooth, and Zigbee), which is suitable for large-scale application scenarios and can reduce the complexity of wiring;

[0063] At the same time, whether it is wired or wireless transmission, the collected water flow signal data is formatted and encoded as necessary to ensure data integrity and stability during transmission, and finally transmitted to the signal processing module;

[0064] S2. Process the water flow signal data. The processed water flow signal data is used to calculate and extract water flow parameters. Water flow parameter extraction includes water flow velocity calculation and flow rate fluctuation calculation. At the same time, through water flow state analysis, the periodic fluctuations of water flow parameters are further analyzed, and the frequency and amplitude of water flow rate changes are calculated.

[0065] Water flow signal processing includes noise removal, signal gain adjustment, and waveform amplitude detection;

[0066] Noise removal: The water flow signal is affected by external environmental factors (such as electromagnetic interference, temperature changes, etc.) and the noise of the sensor itself. To improve the signal quality, it is necessary to remove the noise from the signal. Commonly used methods include low-pass filtering, high-pass filtering, and band-pass filtering. These methods can effectively remove high-frequency or low-frequency noise and retain the effective signal related to the water flow. Noise removal is a key step to ensure the accuracy of subsequent steps. Especially when analyzing dripping events, noise removal can improve the analysis accuracy;

[0067] Signal gain adjustment: Since the water flow signal may be attenuated or enhanced under different environmental conditions, signal gain adjustment is used to ensure that the amplitude of the signal is within a suitable range for processing. Through gain adjustment, it is possible to avoid information loss caused by too weak a signal or signal distortion caused by too strong a signal. This process makes the signal amplitude more balanced in the subsequent processing stage, which is beneficial to improving data stability;

[0068] Waveform amplitude detection: Waveform amplitude detection is to analyze the amplitude of the signal waveform, especially focusing on the amplitude changes of water flow fluctuations. In special situations such as dripping events, the amplitude changes of the signal are small and occur frequently. Through waveform amplitude detection, the subtle changes in the water flow can be accurately identified to ensure that the key fluctuation information of the signal is not ignored;

[0069] After data preprocessing, the signal has been purified. Next is the step of extracting water flow parameters. Extracting water flow parameters is the core task of water flow signal data processing, which will directly provide key data support for subsequent analysis of dripping events, calculation of flow rate fluctuations, etc. Extracting water flow parameters includes calculating water flow velocity, calculating flow rate fluctuations, and analyzing water flow state;

[0070] Calculation of flow velocity: The sensor of the ultrasonic water meter emits ultrasonic signals. When the signals propagate in the water flow, they are affected by factors such as water flow rate and temperature. Since the water flow rate directly determines the propagation speed of the ultrasonic signals, when the flow rate is fast, the propagation speed of the ultrasonic signals is fast, and vice versa. Therefore, the flow velocity of the water flow can be calculated through the time difference Δt of the propagation of the ultrasonic signals. The calculation formula is:

[0071]

[0072] where v is the flow velocity of the water flow, c is the propagation speed of ultrasonic waves in water (a constant, affected by water flow and temperature), Δt is the time difference of signal propagation, and d is the distance from the sensor to the water flow;

[0073] Calculation of flow rate fluctuations: Flow rate fluctuations are caused by changes in the flow velocity of the water flow. Fluctuations in the flow velocity will cause changes in the amount of water flowing through the pipeline per unit time (flow rate). Therefore, flow rate fluctuations are calculated through changes in the flow velocity. There is the following relationship between the flow rate Q of the water flow and the flow velocity v:

[0074] ΔQ = A·Δv

[0075] where ΔQ is the fluctuation of the flow rate, A is the cross-sectional area of the water pipe, and Δv is the change in the flow velocity;

[0076] By monitoring the fluctuations in the water flow velocity, the sensor can extract the magnitude and frequency of the water flow rate fluctuations;

[0077] Analysis of water flow state: The state of the water flow (such as steady flow, turbulent flow, dripping, etc.) will affect the amplitude and frequency of the ultrasonic signals. The change in the water flow state can be comprehensively calculated and quantified through the following formula:

[0078] ① RMS (root mean square value) is a method for measuring the signal strength and degree of change, used to quantify the change in signal amplitude. In the water flow state, the RMS value is small and stable during steady flow, while the dripping phenomenon and turbulent flow are characterized by large and irregular changes in the RMS value. The calculation formula is:

[0079]

[0080] where RMS is the root mean square value of the water flow signal, x i is the value of each sampling point of the water flow signal, and N is the total number of sampling points of the water flow signal;

[0081] The RMS value helps to quantify the amplitude change of the water flow signal and can be used to identify the occurrence of dripping events. When the RMS value of the water flow signal amplitude is small and fluctuates frequently, it indicates the dripping phenomenon.

[0082] ② Fourier transform is a mathematical method that converts a time-domain signal to a frequency-domain signal, which can help extract the frequency components of periodic fluctuations from the water flow signal. For the dripping phenomenon, it appears as high-frequency, low-amplitude periodic fluctuations, while turbulence will appear as fluctuations with irregular frequency changes. The calculation formula is:

[0083]

[0084] where, F freq (ω) is the frequency-domain representation of the water flow signal, f(t) is the time-domain representation of the water flow signal, and ω is the angular frequency of the water flow signal (unit: radian / second);

[0085] Through Fourier transform, the time-domain signal can be converted into a frequency-domain representation, thereby analyzing the main frequency components in the water flow signal. In the dripping phenomenon, frequency analysis can reveal periodic changes, while turbulence has no clear period and the frequency changes are relatively irregular.

[0086] ③ The autocorrelation function is a tool used to analyze whether a signal has periodicity. By calculating the autocorrelation function of the signal, it can be detected whether there are regular fluctuations in the signal. In the dripping phenomenon, the signal will show periodic fluctuations, and the value of the autocorrelation function will have relatively high peaks at the periodic positions. The calculation formula is:

[0087]

[0088] where, R(τ) is the autocorrelation function of the water flow signal, τ is the delay time (i.e., the time interval between two water flow signals), x i and x i+τ are respectively two sampling points of the time-domain signal;

[0089] The autocorrelation function is used to identify the periodicity in the signal. When the dripping phenomenon occurs, the signal will show periodic and small-amplitude fluctuations, and at the same time, the autocorrelation function will produce significant peaks on these periodic fluctuations. Through the autocorrelation function, the periodic fluctuations can be quantitatively detected, thus helping to identify the dripping event.

[0090] S3. Based on the comparison between the extracted water flow parameters and the set dripping event detection thresholds, the dripping event is identified. The threshold setting includes amplitude threshold setting and frequency threshold setting. The identification of the dripping event includes the comparison of the flow fluctuation amplitude and the comparison of the flow fluctuation frequency, which is used for the further confirmation and identification of the dripping event.

[0091] To accurately identify dripping events, a detection threshold for dripping events needs to be set for the detection of dripping events. This threshold is determined based on the amplitude and frequency of flow fluctuations. By setting an appropriate threshold, normal flow changes can be effectively distinguished from dripping events;

[0092] Threshold setting includes amplitude threshold setting and frequency threshold setting;

[0093] Amplitude threshold: The amplitude of flow fluctuations in dripping events is relatively small. Therefore, an amplitude threshold needs to be set. When the amplitude of flow fluctuations is less than this threshold and the fluctuations have a certain periodicity, it can be recognized as a dripping event. This threshold is set based on the characteristics of dripping events. After certain experiments and debugging, it is ensured that dripping events can be correctly identified;

[0094] Frequency threshold: Dripping events are characterized by high-frequency and low-amplitude periodic fluctuations. Therefore, a frequency threshold can be set. When the frequency of flow fluctuations is higher than this threshold, the occurrence of a dripping event is further confirmed. The frequency of dripping events is generally high, so this threshold is low and is used to capture these frequent small-amplitude changes;

[0095] By setting these thresholds, normal flow fluctuations can be effectively distinguished from dripping events, enabling accurate identification;

[0096] The identification of dripping events includes the comparison of the amplitude of flow fluctuations and the comparison of the frequency of flow fluctuations;

[0097] Comparison of the amplitude of flow fluctuations: In S2, the amplitude of flow fluctuations has been calculated. Subsequently, the extracted amplitude of flow fluctuations is compared with the set amplitude threshold. If the amplitude of flow fluctuations is less than the set threshold and has the characteristics of periodic fluctuations, it can be recognized as a dripping event;

[0098] Comparison of the frequency of flow fluctuations: In S2, the frequency of flow fluctuations has been extracted. Subsequently, the frequency of flow fluctuations is compared with the set frequency threshold. If the frequency is higher than the set threshold and the amplitude is small, it conforms to the characteristics of a dripping event and is used to further confirm the identification of a dripping event;

[0099] S4. After identifying a dripping event, the change amplitude of the water flow is reflected by calculating the difference in flow fluctuations in the water flow parameters, and this difference is compared with the detection threshold in S3 to determine the occurrence of a dripping behavior.

[0100] Dripping behavior is manifested as small-amplitude and periodic flow fluctuations. Such fluctuations often reflect the minute changes in the water flow. To accurately identify dripping behavior, it can be assisted by calculating the difference in flow fluctuations, comparing the difference with the threshold, and judging the dripping behavior for precise identification;

[0101] In S3, it has been determined whether a dripping event has occurred based on threshold comparison. However, the flow rate fluctuations of the dripping event may be relatively small, and it cannot be fully confirmed as a dripping behavior through simple amplitude and frequency comparison. Therefore, in S4, by calculating the difference between the maximum value and the minimum value of the flow rate fluctuations in the water flow parameters, the actual amplitude of the water flow fluctuations can be reflected, thereby enabling a more accurate confirmation of whether a dripping behavior has occurred. The specific steps are as follows:

[0102] Difference between the maximum value and the minimum value: Calculate the gap between the maximum value and the minimum value of the flow rate fluctuations in the water flow signal. This difference reflects the change amplitude of the water flow. The difference of the dripping behavior is relatively small. The calculation formula is:

[0103] ΔQ = Q max - Q min

[0104] Where, ΔQ is the difference of the flow rate fluctuations, Q max is the maximum value in the flow rate fluctuations, Q min is the minimum value in the flow rate fluctuations;

[0105] Comparison of the difference with the threshold: Through the dripping event detection threshold set in S3, compare the difference of the flow rate fluctuations calculated in S4 with this threshold. When the difference of the flow rate fluctuations is less than the threshold and shows periodic fluctuation characteristics, confirm the dripping behavior. It should be noted that S4 mainly further verifies the dripping event through the calculation of the difference, while S3 has completed the preliminary judgment of the flow rate fluctuations. Therefore, S4 is only a confirmation step

[0106] Determination of the dripping behavior: If the difference ΔQ is small and conforms to the periodic fluctuation characteristics, it is determined that the dripping behavior has occurred. If the difference ΔQ is large, the possibility of the dripping behavior is excluded, and it is considered that there are other abnormalities in the water flow;

[0107] S5. When the dripping behavior is determined, record the detailed information of the dripping event, including the start time, end time, duration, and cumulative water droplet volume of the event, and store this information in the memory of the water meter for subsequent query and analysis.

[0108] Start time of the event: The start time of the dripping event refers to the moment when the characteristics of the dripping event are first detected in the water flow signal. This time is recorded by the system according to the change points of the periodic fluctuation or the flow rate fluctuation amplitude. The recording of the start time ensures that the starting moment of the dripping event can be traced back and provides basic data for subsequent event analysis;

[0109] End Time: The end time of a dripping event refers to the moment when the dripping phenomenon stops, the fluctuations disappear, or it no longer conforms to the characteristics of dripping behavior. The recording of the end time is crucial for accurately calculating the duration of the dripping event. Generally speaking, the end time is triggered when the amplitude of the flow rate fluctuation of the dripping event returns to the normal range or when the water flow state changes;

[0110] Duration: The duration of a dripping event refers to the time difference between the start time and the end time of the dripping event, reflecting the length of time the dripping event lasts. This information helps to quantify the impact range of the dripping event and also helps to evaluate whether the dripping event exceeds the warning time limit preset by the system.

[0111] Total Drip Volume: The total drip volume refers to the cumulative flow rate fluctuation of the water flow during the dripping event. It is calculated by combining the amplitude of the flow rate fluctuation and the duration of the event, and provides detailed data on the impact of the dripping event on water consumption for the system by calculating the cumulative amount of the flow rate fluctuation during the dripping event. The calculation formula for the total drip volume is:

[0112]

[0113] where Q total is the total drip volume, Q(t) is the instantaneous flow rate during the event, and t 1 and t 2 are the start time and end time of the event respectively;

[0114] Structure for Storing Information: When storing the information of a dripping event, it is first necessary to select a suitable storage format. The storage formats include JSON format, CSV format, or binary format. For embedded devices (such as water meters), the binary format is more efficient because it occupies less memory space and has a faster read and write speed;

[0115] The data fields to be stored include but are not limited to the following fields:

[0116] event id: The unique identifier of the dripping event;

[0117] start time: The start time of the dripping event, recorded as a timestamp;

[0118] end time: The end time of the dripping event, recorded as a timestamp;

[0119] duration: The duration of the dripping event, in minutes or hours;

[0120] total drip volume: The total cumulative drip volume during the dripping event, in liters (L);

[0121] Additional data: may include other supplementary information, such as event types, abnormal water flow conditions, etc.;

[0122] Data storage efficiency: To optimize storage space and memory usage, the water meter will adopt compressed storage or a circular buffer structure:

[0123] Compressed storage: Through compression techniques (such as data deduplication, data compression algorithms, etc.), reduce the occupancy of storage space, especially for data on dripping events recorded over a long period.

[0124] Circular buffer: When the memory of the water meter is limited, a circular buffer can be used to overwrite old records of dripping events with new ones, ensuring that only a certain amount of the latest dripping event data is stored in memory. In this way, as many dripping events as possible can be recorded under limited memory space;

[0125] In subsequent queries and analyses, the water meter will support quick retrieval of dripping event data. Query methods include querying by time interval, event type, and by cumulative drip volume:

[0126] Query by time interval: Users or systems can view relevant data by specifying a query interval (for example, querying dripping events in the past month).

[0127] Query by event type: Filter through fields such as event identifiers and event types to quickly find specific types of dripping events;

[0128] Query by cumulative drip volume: Filter out dripping events within a certain range based on the cumulative drip volume;

[0129] The stored data not only needs to be recorded but also regularly maintained. Dripping event data may be modified, deleted, or updated (for example, due to certain abnormal situations, the cumulative drip volume needs to be recalculated). The update operation is either incremental update or overwrite update to ensure data accuracy.

[0130] The above are only specific implementation manners of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claimed rights.

[0131] Finally: The above are only preferred embodiments of the present invention and are not used to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An ultrasonic water meter dripping measurement method, characterized in that: include: S1. Using an ultrasonic water meter sensor to collect water flow signal data flowing through a water pipe in real time, the water flow signal data includes water flow information, flow fluctuations, and timing information of water flow status. The sensor collects water flow signal data based on the ultrasonic reflection principle. S2. Processing the water flow signal data. The processed water flow signal data is used to calculate and extract water flow parameters. The water flow parameter extraction includes water flow velocity calculation and flow fluctuation calculation. At the same time, the periodic fluctuation of water flow parameters is further analyzed through water flow state analysis, and the frequency and amplitude of water flow change are calculated; S3, based on the comparison of the extracted water flow parameters with the set dripping event detection threshold, the dripping event is identified, the threshold setting includes amplitude threshold setting and frequency threshold setting, and the identification of the dripping event includes comparison of flow fluctuation amplitude and flow fluctuation frequency, which is used for further confirmation and identification of the dripping event; S4, after the dripping event is identified, the flow fluctuation difference in the water flow parameter is calculated to reflect the change amplitude of the water flow, and this difference is compared with the detection threshold in S3 to determine the occurrence of the dripping behavior; S5. When the dripping behavior is determined, the detailed information of the dripping event is recorded, including the start time, end time, duration and cumulative dripping amount of the event, and this information is stored in the memory of the water meter for subsequent query and analysis.

2. The ultrasonic water meter dripping measurement method according to claim 1, characterized in that: The water flow signal processing includes noise removal, signal gain adjustment and waveform amplitude detection, wherein the noise filtering module is used to remove external interference in the water flow signal, the gain adjustment module is used to adjust the amplitude of the water flow signal, and the waveform analysis module is used to analyze the signal waveform.

3. The ultrasonic water meter dripping measurement method according to claim 1, characterized in that: The water flow velocity in the water flow parameter is calculated by the time difference Δt of the ultrasonic signal propagation, and the calculation formula is: Among them, v is the flow velocity of the water, c is the propagation speed of ultrasound in water, Δt is the time difference of signal propagation, and d is the distance from the sensor to the water.

4. The ultrasonic water meter dripping measurement method according to claim 3 is characterized in that: The flow fluctuation in the water flow parameter is calculated by the change in water flow velocity, and there is the following relationship between the flow rate Q and the flow velocity v of the water flow: ΔQ=A·Δv Among them, ΔQ is the fluctuation of flow rate, A is the cross-sectional area of ​​the water pipe, and Δv is the change of flow velocity.

5. The ultrasonic water meter dripping measurement method according to claim 1, characterized in that: The periodic fluctuation analysis in S2 quantifies the water flow signal by three methods: RMS calculation, Fourier transform and autocorrelation function; RMS calculation is used to quantify the amplitude change of water flow signal, and the calculation formula is: Among them, RMS is the root mean square value of the water flow signal, x i is the value of each sampling point of the water flow signal, and N is the total number of sampling points of the water flow signal; Fourier transform analyzes the frequency components of periodic fluctuations by converting time domain signals to frequency domain. The calculation formula is: Among them, F freq (ω) is the frequency domain representation of the water flow signal, f(t) is the time domain representation of the water flow signal, and ω is the angular frequency of the water flow signal; The autocorrelation function is used to detect periodic fluctuations in water flow signals. The calculation formula is: Among them, R(τ) is the autocorrelation function of the water flow signal, τ is the delay time, and x i and x i+τ are two sampling points of the time domain signal.

6. The ultrasonic water meter dripping measurement method according to claim 1, characterized in that: The water flow variation in S4 can be reflected by calculating the difference between the maximum and minimum flow fluctuations in the water flow parameters. The calculation formula is: ΔQ=Q max -Q min Among them, ΔQ is the flow fluctuation difference, Q max is the maximum value of flow fluctuation, Q min is the minimum value in the flow fluctuation.

7. The ultrasonic water meter dripping measurement method according to claim 1, characterized in that: The cumulative dripping amount in S5 refers to the cumulative flow fluctuation of the water flow during the dripping event, which is calculated by combining the amplitude of the flow fluctuation and the duration of the event. By calculating the cumulative amount of flow fluctuation during the dripping event, the system is provided with detailed data on the impact of the dripping event on water consumption. The calculation formula is: Among them, Q total is the cumulative dripping amount, Q(t) is the instantaneous flow rate during the event, and t1 and t2 are the start and end times of the event, respectively.

8. The ultrasonic water meter dripping measurement method according to claim 1, characterized in that: The information storage in S5 is generally stored in the form of data fields, and specific data storage fields include: 1) eventid: unique identifier of the drip event; 2) starttime: the start time of the dripping event, recorded as a timestamp; 3)endtime: the end time of the dripping event, recorded as a timestamp; 4) duration: the duration of the dripping event; 5) totaldripvolume: the accumulated drip volume during the drip event; 6) additional data: additional information.

9. The ultrasonic water meter dripping measurement method according to claim 1, characterized in that: The data transmission mode in S1 is divided into wired transmission and wireless transmission, wherein wired transmission means that data is transmitted to the signal processing module through a wired connection, and wireless transmission means that when flexible arrangement or remote monitoring is required, the collected water flow signal data can be transmitted to the remote signal processing module through the wireless communication module.

10. The ultrasonic water meter dripping measurement method according to claim 1, characterized in that: The water meter supports fast retrieval of drip event data, and query methods include querying by time interval, event type, and cumulative drip volume.

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