Ultrasonic water meter bubble analysis method and system based on echo energy statistics

Abstract

The invention relates to an ultrasonic water meter bubble analysis method and system based on echo energy statistics. The method comprises the following steps: firstly, transmitting an ultrasonic signal in a water meter pipeline and receiving an echo signal propagated by fluid, then collecting multiple groups of continuous echo signals by adopting a sliding window method, calculating an energy value of each group of echo signals, carrying out normalization processing on the energy values, calculating an energy mean value and a variance value based on the normalized echo energy values, and calculating the energy mean value and the variance value. Judging whether bubble influence exists in the water meter pipeline or not according to the energy mean value and the variance value, if so, dividing the normalized echo energy value into different energy intervals, and calculating the echo signal distribution proportion in each energy interval; and finally, on the basis of the judgment, the influence of the bubbles in the ultrasonic water meter pipeline on the echo signal and the measurement precision of the ultrasonic water meter is respectively output as an analysis result, and compared with the prior art, the method has the advantages of low complexity, high feasibility and the like.

Description

Technical Field

[0001] The present invention relates to the field of ultrasonic technology, and in particular to an ultrasonic water meter bubble analysis method and system based on echo energy statistics. Background Art

[0002] With the acceleration of the urbanization process, the scale of the water supply pipe network continues to expand, and the demand for refined management of urban water resources is becoming increasingly urgent. As the core device for measuring residential water consumption, the measurement accuracy of household water meters is directly related to the operation efficiency of water supply enterprises and the rights and interests of users. Ultrasonic water meters, with advantages such as non-invasive measurement and wide range ratio, are gradually replacing traditional mechanical water meters and becoming important data acquisition terminals in smart water systems. However, in actual applications, the problem of bubble interference in pipelines has long existed, resulting in attenuation of ultrasonic echo signals and an increase in time difference measurement deviation, severely restricting its promotion value in urban water supply scenarios.

[0003] Regarding the problem of bubble interference, existing research has mostly focused on industrial large-diameter flow detection scenarios, using complex technical solutions such as the capacitance method and the optical method. However, due to the limitations of installation space and cost constraints for household ultrasonic water meters, there is still an urgent need for a low-complexity and highly feasible embedded bubble detection method. Summary of the Invention

[0004] The purpose of the present invention is to overcome the above-mentioned defects existing in the prior art and provide an ultrasonic water meter bubble analysis method and system based on echo energy statistics.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] According to one aspect of the present invention, a method is provided, and the steps include:

[0007] S1. Transmit ultrasonic signals in the water meter pipeline and receive the echo signals after propagation through the fluid;

[0008] S2. Adopt the sliding window method to collect multiple groups of continuous echo signals and calculate the energy values of each group of echo signals;

[0009] S3. Normalize the energy values of each group of echo signals, and calculate the energy mean and variance values of each group of echo signals based on the normalized echo energy values;

[0010] S4. According to the energy mean and variance values of each group of echo signals, determine whether there is bubble influence in the water meter pipeline; if so, perform S5; if not, directly output no bubbles as the analysis result of bubbles in the ultrasonic water meter pipeline;

[0011] S5. Divide the normalized echo energy values into different energy intervals and calculate the distribution ratio of echo signals in each energy interval;

[0012] S6. Based on the distribution ratio of the echo signals in each energy interval, judge the influence of bubbles on the measurement accuracy of the ultrasonic water meter, and output the analysis result of the bubbles in the ultrasonic water meter pipeline.

[0013] As an optimal technical solution, the specific formula for calculating the energy value of each group of echo signals in S2 is:

[0014]

[0015] where E i is the energy value of the i-th group of echo signals, x[m] is the voltage value of the m-th discrete sampling point, and N is the total number of sampling points.

[0016] As an optimal technical solution, the specific formula for normalizing the energy value of each group of echo signals in S3 is:

[0017]

[0018] where E norm is the normalized echo energy value, E i is the energy value of the i-th group of echo signals, and E max is the maximum echo energy value under the condition of no bubbles.

[0019] As an optimal technical solution, the specific formula for calculating the energy mean value of each group of echo signals based on the normalized echo energy value in S3 is:

[0020]

[0021] where μ is the energy mean value, σ 2 is the variance value, W is the number of groups of echo signals in the sliding window, and E norm,i is the normalized echo energy value of the i-th group.

[0022] As an optimal technical solution, the judgment condition for judging whether there are bubbles affecting in the water meter pipeline in S4 is: if the energy mean value is greater than the preset energy mean value and the variance is less than the preset variance threshold, it is determined that there is no bubble influence; otherwise, it is determined that there is bubble influence.

[0023] As an optimal technical solution, the divided energy intervals in S5 include a high energy interval, a medium energy interval, and a low energy interval; among them, the high energy interval is set to [0.8, 1.0], the medium energy interval is set to (0.2, 0.8), and the low energy interval is set to [0.0, 0.2].

[0024] As an optimal technical solution, the specific formula for calculating the distribution ratio of the echo signals in each energy interval in S5 is:

[0025]

[0026] Among them, P [0.8,1.0] represents the proportion of echo signals in the corresponding energy range, and I [0.8,1.0] represents the number of echo signals within the energy of the corresponding range, and W is the number of groups of echo signals within the sliding window.

[0027] As a preferred technical solution, the specific process of judging the influence of bubbles on the echo signal based on the distribution ratio of echo signals in each energy range in S6 is as follows:

[0028] If the proportion of echo signals in the low energy range increases, it indicates that the bubble content in the pipeline increases, and it is judged that the attenuation effect of bubbles on the echo signal is enhanced;

[0029] If the proportion of echo signals in the high energy range increases, it indicates that the bubble content in the pipeline decreases, and it is judged that the attenuation effect of bubbles on the echo signal is weakened.

[0030] As a preferred technical solution, the specific process of judging the influence of bubbles on the measurement accuracy of the ultrasonic water meter based on the distribution ratio of echo signals in each energy range in S6 includes:

[0031] When the proportion of echo signals in the low energy range exceeds the preset threshold, output: Bubbles have an impact on the measurement accuracy of the ultrasonic water meter, and bubble removal or calibration operations need to be performed, and this is used as the analysis result of bubbles in the ultrasonic water meter pipeline;

[0032] When the proportion of echo signals in the low energy range is lower than the preset threshold, output: Bubbles have no impact on the measurement accuracy of the ultrasonic water meter, and no additional processing is required, and this is used as the analysis result of bubbles in the ultrasonic water meter pipeline.

[0033] According to another aspect of the present invention, there is provided an ultrasonic water meter bubble analysis system based on echo energy statistics. This system operates using an ultrasonic water meter bubble analysis method based on echo energy statistics as described above. The system includes a signal transceiver module, a signal processing module, a bubble judgment module, and an influence evaluation module;

[0034] The signal transceiver module is used to transmit ultrasonic signals in the water meter pipeline and receive the echo signals after propagation through the fluid;

[0035] The signal processing module is used to adopt the sliding window method to collect multiple groups of continuous echo signals, calculate the energy values of each group of echo signals, perform normalization processing on the energy values, and calculate the energy mean and variance values;

[0036] The bubble judgment module is used to judge whether there is an influence of bubbles in the water meter pipeline according to the energy mean and variance values of each group of echo signals;

[0037] The impact assessment module is used to divide the normalized echo energy values into different energy intervals, calculate the distribution ratio of echo signals in each interval, and based on this, judge and respectively output the impacts of bubbles in the ultrasonic water meter pipeline on the echo signal and the measurement accuracy of the ultrasonic water meter as the analysis result.

[0038] Compared with the prior art, the present invention has the following beneficial effects:

[0039] 1. In the present invention, the energy distribution of the echo signal is collected and analyzed in real time by the sliding window method, and combined with the calculation of the energy mean value, variance value and the proportion of the energy interval, the distribution and content of bubbles in the pipeline are evaluated, and then the impacts of bubbles in the ultrasonic water meter pipeline on the echo signal and the measurement accuracy of the ultrasonic water meter are judged and respectively output as the analysis result, which can effectively monitor and evaluate the impact of bubbles during the use of the water meter; and this method only depends on signal acquisition and simple mathematical calculations, without complex equipment and high-cost investment, with low complexity and high feasibility, simple and easy to implement, low cost, suitable for bubble detection and calibration of household ultrasonic water meters, and suitable for popularization and use.

[0040] 2. In the present invention, the divided energy intervals include a high energy interval, a medium energy interval and a low energy interval. The high energy interval is set as [0.8, 1.0], the medium energy interval is set as (0.2, 0.8), and the low energy interval is set as [0.0, 0.2]. By dividing the energy interval and analyzing the change of its proportion, the water meter can adapt to various complex fluid environments. Whether in the state of low bubble content or high bubble content, the water meter can accurately evaluate the impact of bubbles based on the energy interval analysis, realize the effective quantification of the impact of bubbles on the ultrasonic echo signal, and monitor the impact of bubbles on the measurement accuracy of the water meter in real time, so as to ensure the stability and reliability of the bubble analysis in the water meter pipeline, and further improve the measurement accuracy and reliability of the water meter.

[0041] 3. In the present invention, the specific process of judging and respectively outputting the impacts of bubbles in the ultrasonic water meter pipeline on the echo signal and the measurement accuracy of the ultrasonic water meter based on the distribution ratio of echo signals in each energy interval is provided, so that this method can accurately evaluate the impact of bubbles on the measurement accuracy of the ultrasonic water meter according to the distribution ratio of echo signals in different energy intervals, and output the corresponding analysis result, providing a basis for subsequent treatment measures. Description of the Drawings

[0042] Figure 1 It is an ultrasonic water meter bubble analysis method based on echo energy statistics in the present invention;

[0043] Figure 2 It is a schematic diagram of the experimental device in the embodiment;

[0044] Figure 3It is the change diagram of the echo signal energy at each flow point without bubble interference in the embodiment;

[0045] Figure 4 It is the change diagram of the echo signal energy at each flow point with bubble interference in the embodiment;

[0046] Figure 5 It is the schematic diagram of the change of the proportion of the echo signal in the high - energy interval in the embodiment;

[0047] Figure 6 It is the schematic diagram of the change of the proportion of the echo signal in the medium - energy interval in the embodiment;

[0048] Figure 7 It is the schematic diagram of the change of the proportion of the echo signal in the low - energy interval in the embodiment;

[0049] In the figure, 1 is the liquid flow control valve, 2 is the liquid flowmeter, 3 is the one - way check valve, 4 is the bubble injection pipe section, 5 is the transparent observation pipe section, 6 is the gas cylinder detection pipe section, 7 is the water storage tank, 8 is the water pump, 9 is the pressure - stabilizing pipe, 10 is the air compressor, 11 is the gas flowmeter, 12 is the gas flow control valve, 13 is the signal acquisition and transducer drive board, and 14 is the signal processing terminal. Specific implementation mode

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0051] With the acceleration of the urbanization process, the scale of the water supply network continues to expand, and the demand for refined management of urban water resources is becoming increasingly urgent. As the core device for measuring residential water consumption, the measurement accuracy of household water meters is directly related to the operation efficiency of water supply enterprises and the rights and interests of users. Ultrasonic water meters, with advantages such as non - invasive measurement and wide range ratio, are gradually replacing traditional mechanical water meters and becoming important data acquisition terminals in intelligent water service systems. However, in actual applications, the problem of bubble interference in pipelines has long existed, resulting in the attenuation of ultrasonic echo signals and an increase in the deviation of time - difference measurement, which seriously restricts its promotion value in urban water supply scenarios.

[0052] Regarding the problem of bubble interference, existing research has mostly focused on the industrial large-diameter flow detection scenario, adopting complex technical solutions such as the capacitance method and the optical method. However, due to the constraints of installation space and cost, household ultrasonic water meters urgently need a low-complexity and high-reliability embedded bubble detection method. Based on the requirements of the urban water supply scenario, this application proposes an echo energy distribution analysis method for household ultrasonic water meters. By analyzing the energy attenuation law of bubbles on the echo signal, a dynamic evaluation model of bubble interference is constructed, providing technical support for the leakage monitoring of urban water supply networks and accurate metering at the user end, and facilitating the efficient operation of the intelligent water service system.

[0053] Embodiment 1

[0054] In this embodiment, an ultrasonic water meter bubble detection method based on echo energy distribution is adopted, and the steps of this method are as Figure 1 shown, specifically including:

[0055] S1: Transmit ultrasonic signals in the pipeline through an ultrasonic transducer and receive the echo signals after propagation through the fluid;

[0056] S2: Adopt the sliding window method to collect a fixed number of consecutive echo signals and calculate the energy value of each echo signal;

[0057] S3: Normalize the energy values of the echo signals to obtain the normalized echo energy values; and calculate the energy mean and variance values of multiple groups of echo signals within the sliding window based on the normalized echo energy values;

[0058] S4: Based on the energy mean and variance values, preliminarily judge whether there is bubble influence in the pipeline;

[0059] S5: In the case of determining that there is bubble influence, further analyze the energy interval distribution of the echo signals, divide the normalized echo energy values into different energy intervals, and the energy intervals include high-energy intervals, medium-energy intervals, and low-energy intervals;

[0060] S6: Statistically analyze the proportion of echo signals in each energy interval and evaluate the distribution and content of bubbles in the pipeline according to the proportion.

[0061] In this embodiment, first build an experimental device to simulate the gas-liquid two-phase flow field under different gas flow rates, collect multiple groups of echo signal samples; then adopt the sliding window method to collect a fixed number of consecutive echo signals, calculate the energy value of each echo signal and perform normalization processing; and calculate the energy mean and variance values of multiple groups of echo signals within the sliding window to preliminarily judge the bubble influence situation;

[0062] When the energy mean is greater than the preset energy mean and the variance is less than the preset variance threshold, it is determined that there is no bubble influence; otherwise, it is determined that there is bubble influence. In the case where it is determined that there is bubble influence, the energy interval is divided and the proportion of echo signals in each interval is statistically analyzed to evaluate the bubble distribution and content; in the case where it is determined that there is bubble influence, the energy interval distribution of the echo signals is further analyzed. The normalized echo energy values are divided into different energy intervals, including a high energy interval [0.8, 1.0], a medium energy interval (0.2, 0.8), and a low energy interval [0.0, 0.2]. And the proportion of echo signals in each energy interval is calculated by the following formula to evaluate the bubble distribution and content in the pipeline:

[0063]

[0064] In the formula, P [0.8,1.0] represents the proportion of echo signals in the corresponding energy interval, I [0.8,1.0] represents the number of echo signals in the corresponding interval energy, and W is the number of groups of echo signals in the sliding window.

[0065] Then, based on the bubble distribution and content, the influence of bubbles on the measurement accuracy of the ultrasonic water meter is judged. By statistically analyzing the proportion of echo signals in each energy interval, the influence degree of bubbles on the echo signals is evaluated. Specifically: when the proportion of echo signals in the low energy interval increases, it indicates that the bubble content in the pipeline increases and the attenuation effect of bubbles on the echo signals is enhanced; when the proportion of echo signals in the high energy interval increases, it indicates that the bubble content in the pipeline decreases and the attenuation effect of bubbles on the echo signals is weakened.

[0066] Finally, the analysis result is output, and the corresponding calibration or exclusion operation of the water meter can be performed according to the analysis result.

[0067] Based on the proportion distribution and size of the energy interval, judge the influence of bubbles on the measurement accuracy of the ultrasonic water meter:

[0068] 1) When the proportion of echo signals in the low energy interval exceeds the preset threshold, it is determined that the bubbles have a significant impact on the measurement accuracy of the ultrasonic water meter, and bubble exclusion or calibration operations need to be performed;

[0069] 2) When the proportion of echo signals in the low energy interval is lower than the preset threshold, it is determined that the influence of bubbles on the measurement accuracy of the ultrasonic water meter is small, and no additional treatment is required

[0070] In this embodiment, in step two, the energy value of the echo signal is calculated by the following formula:

[0071]

[0072] Among them, E i$E_i$ is the energy value of the $i$-th group of echo signals, $x[m]$ is the voltage value of the $m$-th discrete sampling point, and $N$ is the total number of sampling points.

[0073] In this embodiment, in step two, the normalization process is carried out by the following formula:

[0074]

[0075] where $E$ norm is the normalized echo energy value, $E_i$ i is the energy value of the $i$-th group of echo signals, and $E_{max}$ max is the maximum echo energy value under the bubble-free condition.

[0076] In this embodiment, in step three, the energy mean and variance values of multiple groups of echo signals within the sliding window are calculated by the following formula:

[0077]

[0078] where $\mu$ is the energy mean, $\sigma$ 2 is the variance value, $W$ is the number of groups of echo signals within the sliding window, and $E_i$ norm,i is the normalized echo energy value of the $i$-th group.

[0079] In this embodiment, in step four, the energy interval is divided as follows: high energy interval [0.8, 1.0], medium energy interval (0.2, 0.8), and low energy interval [0.0, 0.2].

[0080] To sum up, in the present invention, the energy distribution of echo signals is collected and analyzed in real time by the sliding window method, and combined with the calculation of the energy mean, variance value, and energy interval ratio, the distribution and content of bubbles in the pipeline are evaluated, and then the influence of bubbles on the measurement accuracy of the ultrasonic water meter is judged. Finally, the analysis result of bubbles in the ultrasonic water meter pipeline is output, which can effectively monitor and evaluate the influence of bubbles during the use of the water meter; and this method only depends on signal acquisition and simple mathematical calculations, without the need for complex equipment and high-cost investment, with low complexity and high feasibility, simple and easy to implement, low cost, suitable for bubble detection and calibration of household ultrasonic water meters, and suitable for popularization and use.

[0081] Embodiment 2

[0082] In this embodiment, an ultrasonic water meter bubble analysis system based on echo energy statistics is adopted. The system includes a signal transceiver module, a signal processing module, a bubble judgment module, and an influence evaluation module;

[0083] The signal transceiver module is used to transmit ultrasonic signals in the water meter pipeline and receive the echo signals after being propagated through the fluid;

[0084] The signal processing module is used to collect multiple groups of continuous echo signals by using the sliding window method, calculate the energy values of each group of echo signals, normalize the energy values, and calculate the energy mean and variance values.

[0085] The bubble judgment module is used to judge whether there is an influence of bubbles in the water meter pipeline according to the energy mean and variance values of each group of echo signals.

[0086] The influence evaluation module is used to divide the normalized echo energy values into different energy intervals, calculate the distribution ratio of echo signals in each interval, and based on this, judge and respectively output the influence of bubbles in the ultrasonic water meter pipeline on the echo signals and the measurement accuracy of the ultrasonic water meter as the analysis result.

[0087] In this embodiment, the system is integrated into the processing terminal 14, and the experimental device shown in Figure 2 is built for testing; the experimental device is divided into:

[0088] 1) The flow control sub-device is used to adjust the liquid flow rate and gas flow rate.

[0089] 2) The pressure stabilization and mixing sub-device is used to ensure the stability of the flow field parameters and perform gas-liquid mixing.

[0090] 3) The signal acquisition sub-device is used to drive the ultrasonic transducer and collect echo signals.

[0091] Figure 2 The liquid flow control valve 1 in is used to control the flow rate of the liquid in the pipeline and adjust the liquid flow rate; the liquid flow meter 2 is used to measure the flow rate of the liquid in the pipeline and obtain real-time flow data; the one-way check valve 3 is used to prevent the liquid from flowing back, ensure that the liquid can only flow in the specified direction, and protect the system equipment; the bubble injection pipe section 4 is used to inject bubbles into the liquid in the pipeline; the transparent observation pipe section 5 is used to facilitate the operator to directly observe the gas-liquid flow state in the pipe, such as bubble distribution, flow pattern, etc.; the bubble detection pipe section 6 is used to detect the relevant parameters of the bubbles in the pipe, such as bubble size, quantity, speed, etc.; the water storage tank 7 is used to store the liquid, and the water pump 8 is used to provide power for the liquid to circulate in the system, so that the liquid flows from the water storage tank to other components; the pressure stabilizing tank 9 is used to stabilize the liquid pressure, reduce the pressure fluctuation in the system, and ensure the stability of the system operation; the air compressor 10 is used to compress air and provide the gas source for bubble injection. The gas flow meter 11 is used to measure the flow rate of the injected gas and accurately control the bubble injection amount; the gas flow control valve 12 is used to adjust the flow rate of the injected gas; the signal acquisition and transducer drive board 13 is used to collect various sensor signals in the system, such as bubble detection signals, etc., and drive the transducer to work; the signal processing terminal 14 is used to receive and process the collected signals and perform operations such as data analysis, storage, and display.

[0092] The water pump 8 pumps water from the water storage tank 7 and enters the pipeline through the liquid flow control valve 1, the liquid flowmeter 2, and the one-way check valve 3. The air compressor 10 generates compressed air, which enters the bubble injection pipe section 4 through the gas flow control valve 12 and the gas flowmeter 11 to be mixed with the liquid. The mixed gas-liquid two-phase flow passes through the transparent observation pipe section 5 and then is tested and the bubbles are detected through the bubble detection pipe section 6. The relevant signals are collected by the signal acquisition and transducer drive board 13 and transmitted to the signal processing terminal 14 for analysis and processing. During the test process, the pressure stabilizing tank 9 maintains the liquid pressure stable.

[0093] The test steps include:

[0094] 1) Simulate the gas-liquid two-phase flow field under different gas flow rates through the experimental device and collect multiple groups of echo signal samples;

[0095] 2) Conduct statistical analysis on the echo signal samples under different bubble distributions and summarize the relationship between the energy interval ratio distribution of the echo signals and the bubble distribution.

[0096] During this measurement process, the distribution and content of bubbles in the pipeline are monitored in real time, and the measurement parameters of the ultrasonic water meter are dynamically adjusted according to the monitoring results to improve the measurement accuracy.

[0097] The specific test steps are as follows:

[0098] Step 1: Ensure the liquid flow rate is stable and record the forward and reverse flow echo signal data at the following 4 gas flow rate points. These 12 flow rate points are:

[0099] 0, 20, 50, 70, 100, 140, 175, 210, 245, 270, 300, 350 mL / min;

[0100] Test 3 times at each flow rate point, and statistically analyze 250 groups of echo signal energy values each time;

[0101] Step 2: Calculate the energy value of each group of echo signals;

[0102]

[0103] Among them, E i is the energy value of the i-th group of echo signals, x[m] is the voltage value of the m-th discrete sampling point, and N is the total number of sampling points.

[0104] Step 3: Calculate the normalized echo signal energy;

[0105]

[0106] Among them, E norm is the normalized echo energy value, E i is the energy value of the i-th group of echo signals, Emax is the maximum echo energy value under the bubble-free condition.

[0107] Step 4: Calculate the mean and variance of the normalized energies of 250 groups of echo signals;

[0108]

[0109]

[0110] where μ is the energy mean, σ 2 is the variance value, W is the number of echo signal groups within the sliding window, and E norm,i is the normalized echo energy value of the i-th group.

[0111] Step 5: According to the division of the normalized energy interval, count the number of echo signals in the corresponding interval, and calculate the signal ratio in each energy interval.

[0112] Set the high energy interval as [0.8, 1.0], the medium energy interval as (0.2, 0.8), and the low energy interval as [0.0, 0.2];

[0113] The specific formula for the distribution ratio of echo signals in each energy interval is:

[0114]

[0115] where P [0.8,1.0] represents the echo signal ratio in the corresponding energy interval, I [0.8,1.0] represents the number of echo signals in the corresponding interval energy, and W is the number of echo signal groups within the sliding window.

[0116] In this embodiment, the echo signal energy magnitudes and statistical characteristics under the influence of no bubbles and with bubbles are studied and analyzed. As Figure 3 shown, under the condition that no bubbles flow through the pipeline, the energy change of each group of echoes is small, the mean of the normalized energy is large, and the variance is small. After introducing bubbles, the energy change of the echo signal is obvious. As Figure 4 shown, the energy of some echoes has a significant attenuation, the mean of the normalized energy decreases, and the variance increases.

[0117] In this embodiment, the data of gas content, energy mean, and variance are shown in Table 1.

[0118] Table 1 Normalized energy mean and variance of echo signals under different bubble contents

[0119]

[0120]

[0121] The differences in the means and variances with and without the influence of air bubbles are relatively large, which can be used as a basis for a preliminary judgment on whether there is an influence of air bubbles. The normalized echo energy is divided into three intervals: [0.8, 1.0], (0.2, 0.8), [0.0, 0.2]. The proportions of echo signals in each interval are statistically analyzed, and based on this, a graph showing the changing trends of the proportions of echo signals in different energy intervals with the increase in air bubble content in the four experiments is plotted, as shown in Figure 5 , 6 , and Figure 7; among them, Figure 5 is a schematic diagram showing the change in the proportion of echo signals in the high-energy interval; Figure 6 is a schematic diagram showing the change in the proportion of echo signals in the medium-energy interval; Figure 7 is a schematic diagram showing the change in the proportion of echo signals in the low-energy interval. In Figure 3 , 6 , and Figure 7, the blue line represents the first set of echo data, the orange line represents the second set of data, the green line represents the third set of data, and the red line represents the fourth set of data. From Figure 5 , Figure 6 , and Figure 7 , it can be seen that the changing trends of the energy interval proportions in the four experiments are obvious and consistent. It can be seen that there is a correlation between the energy interval proportion and the air bubble content, which can be used as a basis for evaluating the air bubble state.

[0122] As described above, it is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of various equivalent modifications or substitutions, and these modifications or substitutions should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. An ultrasonic water meter bubble analysis method based on echo energy statistics, characterized in that: The method steps include: S1. Transmit ultrasonic signals in the water meter pipe and receive echo signals after propagation through the fluid; S2, using the sliding window method to collect multiple groups of continuous echo signals and calculate the energy value of each group of echo signals; S3, normalizing the energy values ​​of each group of echo signals, and calculating the energy mean and variance value of each group of echo signals based on the normalized echo energy values; S4, judging whether there is bubble influence in the water meter pipe according to the energy mean and variance value of each group of echo signals; if so, proceed to S5; if not, directly outputting no bubble as the bubble analysis result in the ultrasonic water meter pipe; S5, dividing the normalized echo energy value into different energy intervals, and calculating the echo signal distribution ratio in each energy interval; S6. Based on the echo signal distribution ratio in each energy interval, determine and output the influence of the bubbles in the ultrasonic water meter pipeline on the echo signal and the ultrasonic water meter measurement accuracy as analysis results.

2. The ultrasonic water meter bubble analysis method based on echo energy statistics according to claim 1 is characterized in that: The specific formula for calculating the energy value of each group of echo signals in S2 is: Among them, E i is the energy value of the i-th group of echo signals, x[m] is the voltage value of the m-th discrete sampling point, and N is the total number of sampling points.

3. The ultrasonic water meter bubble analysis method based on echo energy statistics according to claim 1 is characterized in that: The specific formula for normalizing the energy value of each group of echo signals in S3 is: Among them, E norm is the normalized echo energy value, E i is the energy value of the i-th group of echo signals, E max It is the maximum echo energy value under the condition of no bubbles.

4. The ultrasonic water meter bubble analysis method based on echo energy statistics according to claim 3 is characterized in that: The specific formula for calculating the energy mean and variance value of each group of echo signals based on the normalized echo energy value in S3 is: Among them, μ is the mean energy, σ 2 is the variance value, W is the number of echo signal groups in the sliding window, E norm,i is the normalized echo energy value of the i-th group.

5. The ultrasonic water meter bubble analysis method based on echo energy statistics according to claim 4 is characterized in that: The judgment condition for judging whether there is bubble influence in the water meter pipe in S4 is: if the energy mean is greater than the preset energy mean and the variance is less than the preset variance threshold, it is judged that there is no bubble influence; otherwise, it is judged that there is bubble influence.

6. The ultrasonic water meter bubble analysis method based on echo energy statistics according to claim 1 is characterized in that: The energy intervals divided in S5 include a high energy interval, a medium energy interval and a low energy interval; wherein the high energy interval is set to [0.8, 1.0], the medium energy interval is set to (0.2, 0.8) and the low energy interval is set to [0.0, 0.2].

7. The ultrasonic water meter bubble analysis method based on echo energy statistics according to claim 6 is characterized in that: The specific formula for calculating the echo signal distribution ratio in each energy interval in S5 is: Among them, P [0.8,1.0] Represents the echo signal ratio in the corresponding energy interval, I [0.8,1.0] represents the number of echo signals in the corresponding interval energy, and W is the number of echo signal groups in the sliding window.

8. The ultrasonic water meter bubble analysis method based on echo energy statistics according to claim 7 is characterized in that: The specific process of determining the influence of bubbles on the echo signal based on the echo signal distribution ratio in each energy interval in S6 is as follows: If the proportion of echo signals in the low energy interval increases, it indicates that the bubble content in the pipeline increases, and it is judged that the attenuation effect of bubbles on echo signals increases; If the proportion of echo signals in the high-energy interval increases, it indicates that the bubble content in the pipeline decreases, and it is judged that the attenuation effect of bubbles on the echo signal is weakened.

9. The ultrasonic water meter bubble analysis method based on echo energy statistics according to claim 8, characterized in that: The specific process of determining the influence of bubbles on the ultrasonic water meter measurement accuracy based on the echo signal distribution ratio in each energy interval in S6 includes: When the echo signal ratio in the low energy interval exceeds the preset threshold, the output is: bubbles affect the measurement accuracy of the ultrasonic water meter, and bubble removal or calibration operations are required, which is used as the bubble analysis result in the ultrasonic water meter pipeline; When the echo signal ratio in the low energy interval is lower than the preset threshold, the output is: the bubbles have no effect on the measurement accuracy of the ultrasonic water meter and no additional processing is required, which is used as the bubble analysis result in the ultrasonic water meter pipeline.

10. An ultrasonic water meter bubble analysis system based on echo energy statistics, characterized in that: The system works by applying an ultrasonic water meter bubble analysis method based on echo energy statistics as described in any one of claims 1 to 9, and the system includes a signal transceiver module, a signal processing module, a bubble judgment module and an impact assessment module; The signal transceiver module is used to transmit ultrasonic signals in the water meter pipe and receive echo signals after being propagated through the fluid; The signal processing module is used to collect multiple groups of continuous echo signals by using a sliding window method, calculate the energy value of each group of echo signals, normalize the energy value, and calculate the energy mean and variance value; The bubble judgment module is used to judge whether there is bubble influence in the water meter pipe according to the energy mean and variance value of each group of echo signals; The impact assessment module is used to divide the normalized echo energy value into different energy intervals, calculate the echo signal distribution ratio in each interval, and based on this, judge and output the impact of bubbles in the ultrasonic water meter pipeline on the echo signal and the ultrasonic water meter measurement accuracy as analysis results.

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