Ultrasonic water meter flow measurement data processing methods, devices, electronic equipment and storage media

Abstract

The present invention provides a method, device, electronic device, and storage medium for processing ultrasonic water meter flow measurement data. The method includes acquiring ultrasonic signals in the downstream and upstream directions to form a first time domain signal and a second time domain signal, respectively; performing window function windowing and framing on the two time domain signals to obtain corresponding signal frame sequences; performing Fourier transform and frequency domain filtering respectively, and then restoring the first and second time domain signal frame sequences through inverse transform; splicing the restored frame sequences, extracting the propagation time difference through cross-correlation function analysis; calculating the flow velocity based on the propagation time difference, and combining it with the pipe cross-sectional area to obtain the water flow rate. In this way, the most likely propagation time difference is extracted through the cross-correlation peak, and the signal quality is enhanced by frequency domain filtering, which can effectively improve the anti-interference and overall accuracy of the flow velocity measurement.

Description

Technical Field

[0001] This invention belongs to the field of ultrasonic measurement and signal processing technology, and in particular relates to a method, device, electronic device and storage medium for processing ultrasonic water meter flow measurement data. Background Technology

[0002] Ultrasonic flow measurement is a common non-contact fluid metering method, widely used in water meters, heat meters, and industrial process fluid monitoring. This technology typically uses ultrasonic transducers installed at both ends of the pipe to emit and receive ultrasonic signals in the forward and reverse directions, respectively. By comparing the time difference between the two propagation directions, the fluid velocity in the pipe is inferred, and the total flow rate is calculated in conjunction with the pipe's cross-sectional area.

[0003] In related technologies, ultrasonic signals are typically processed directly in the time domain after acquisition, including methods such as signal enhancement and cross-correlation analysis. However, time-domain signals are susceptible to noise interference, especially in low signal-to-noise ratio environments, making it difficult to accurately extract the propagation time difference and affecting measurement accuracy and stability.

[0004] On the other hand, the processes of preprocessing, frequency domain filtering, and frame reconstruction of ultrasonic signals in related technologies are not yet systematic enough, resulting in low signal utilization. Especially under non-ideal pipeline conditions (such as turbulence, water hammer, or multipath interference), the measurement results fluctuate greatly, and the accuracy is limited. Summary of the Invention

[0005] In view of this, the purpose of this invention is to provide a method, device, electronic device and storage medium for processing ultrasonic water meter flow measurement data. This method improves the accuracy and stability of propagation time difference extraction by introducing window function windowing, framing, frequency domain transformation and filtering, frame-level time domain restoration and cross-correlation analysis in the ultrasonic signal processing process, and enhances the anti-interference ability under complex working conditions, thereby improving the measurement reliability and application adaptability of ultrasonic water meters.

[0006] To achieve the above objectives, the technical solution created by this invention is implemented as follows:

[0007] In a first aspect, the present invention provides a method for processing ultrasonic water meter flow measurement data, the method comprising:

[0008] S1. Based on the ultrasonic transducer, ultrasonic signals in the downstream and upstream directions are acquired respectively, thereby forming a first time-domain signal and a second time-domain signal;

[0009] S2. Window the first time-domain signal and the second time-domain signal respectively using window functions, and divide them into frames according to a predetermined frame length to obtain the first signal frame sequence and the second signal frame sequence.

[0010] S3. Perform Fourier transform on the first signal frame sequence and the second signal frame sequence respectively to obtain the corresponding frequency domain signal frame sequence. Perform frequency domain filtering on the frequency domain signal frame sequence to remove noise and interference. Then perform inverse Fourier transform on the filtered frequency domain signal frame sequence to obtain the first time domain signal frame sequence and the second time domain signal frame sequence.

[0011] S4. The first time-domain signal frame sequence and the second time-domain signal frame sequence are spliced ​​together in time, and the ultrasonic propagation time difference is extracted by cross-correlation analysis.

[0012] S5. Calculate the flow velocity based on the propagation time difference, and calculate the water flow rate in combination with the pipe cross-sectional area.

[0013] Furthermore, in step S2, the window function windowing process involves applying window functions to the first time-domain signal and the second time-domain signal respectively to reduce boundary effects and leakage. The window function includes any one of Hamming window, Hanning window, or Blackman window.

[0014] Furthermore, in step S2, the framing process divides the windowed first time-domain signal and the second time-domain signal into frames based on a preset frame length N and frame shift M, thereby forming the first signal frame sequence and the second signal frame sequence.

[0015] Furthermore, in step S3, the frequency domain filtering employs a bandpass filter to filter out noise and interference components outside the target frequency band. The bandpass filter includes a Gaussian or rectangular window frequency domain filter.

[0016] Furthermore, in step S4, the first time-domain signal frame sequence and the second time-domain signal frame sequence are time-sequentially concatenated to form a first time-domain signal and a second time-domain signal. The ultrasonic wave propagation time difference is extracted through cross-correlation analysis, wherein the cross-correlation function for performing the cross-correlation analysis is defined as:

[0017] ;

[0018] The propagation time difference is t, , The sampling period is [period], and the first time-domain signal is [signal]. The second time-domain signal is , for and Between delays The cross-correlation function values ​​under the following conditions For delay amount, This refers to the number of sampling points contained in a single frame. for Delay amount of the maximum value , This is the index of the current intra-frame sampling point.

[0019] Furthermore, in step S5, the flow rate is calculated using the following formula:

[0020] ;

[0021] Where L is the distance between the ultrasonic transducers; and Represent the propagation time in the downstream and upstream directions, respectively, satisfying t;

[0022] The water flow rate is denoted as Q, and is calculated using the following formula:

[0023] ;

[0024] Where A is the cross-sectional area of ​​the pipe. This represents the average flow velocity of water in the pipe.

[0025] In a second aspect, the present invention provides a flow measurement data processing apparatus, comprising:

[0026] The acquisition module acquires ultrasonic signals in the downstream and upstream directions through an ultrasonic transducer, thereby forming a first time-domain signal and a second time-domain signal.

[0027] The processing module performs windowing processing on the first time-domain signal and the second time-domain signal respectively, and divides them into frames according to a predetermined frame length to obtain the first signal frame sequence and the second signal frame sequence.

[0028] The filtering module performs Fourier transform on the first signal frame sequence and the second signal frame sequence respectively to obtain the corresponding frequency domain signal frame sequence. It then performs frequency domain filtering on the frequency domain signal frame sequence to remove noise and interference. Finally, it performs inverse Fourier transform on the filtered frequency domain signal frame sequence to obtain the first time domain signal frame sequence and the second time domain signal frame sequence.

[0029] The extraction module performs time-series splicing of the first time-domain signal frame sequence and the second time-domain signal frame sequence, and extracts the ultrasonic wave propagation time difference through cross-correlation analysis.

[0030] The calculation module calculates the flow velocity based on the propagation time difference and calculates the water flow rate by combining the cross-sectional area of ​​the pipe.

[0031] Thirdly, the present invention provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0032] The memory stores computer-executed instructions;

[0033] When the processor executes the computer execution instructions stored in the memory, it is used to implement the ultrasonic water meter flow measurement data processing method of the first aspect of the invention.

[0034] Fourthly, the present invention provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement an ultrasonic water meter flow measurement data processing method according to the first aspect of the invention.

[0035] The above technical solution employs independent preprocessing steps to window and frame the raw ultrasonic signals in both the downstream and upstream directions using window functions. This results in signals with good temporal boundary characteristics and local stationarity, effectively suppressing spectral spread and interference caused by initial boundary discontinuities. Subsequently, in the frequency domain processing stage, frame-by-frame Fourier transform is used to map the framed signals to the frequency domain, and frequency domain filtering strategies are combined to effectively remove noise and interference components. This frequency domain filtering process can specifically suppress interference in non-target frequency bands and enhance the spectral concentration of the main signal. After filtering, the signal is restored to the time domain via inverse Fourier transform. A continuous sequence of first and second time-domain signal frames is then constructed using frame-level time-series splicing. This preserves the frequency domain enhancement effect while ensuring the coherence and integrity of the final time-domain signal, providing a high-quality signal foundation for time difference analysis. Furthermore, in the crucial propagation time difference extraction stage, a cross-correlation analysis method is introduced. By measuring the similarity between two signals at different time offsets, the delay corresponding to the best-matching moment is identified. This cross-correlation strategy exhibits good noise resistance, especially in multi-path or complex background interference scenarios, accurately extracting the time delay information of the main propagation path. Finally, based on the extracted time difference, combined with known structural parameters and a physical model, the flow velocity is calculated, and ultimately, the volumetric flow rate within the pipe is determined.

[0036] In summary, this invention focuses on core aspects such as signal quality improvement, interference suppression, and enhanced time difference recognition accuracy. It constructs a complete data processing chain from signal acquisition, frame filtering, reconstruction and splicing, time difference extraction to flow output, which can significantly improve the robustness, accuracy, and engineering practicality of the flow measurement system under complex operating conditions. Attached Figure Description

[0037] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments and descriptions of the invention are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings:

[0038] Figure 1A flowchart illustrating the ultrasonic water meter flow measurement data processing method provided in Embodiment 1 of the present invention. Figure 1 ;

[0039] Figure 2 A flowchart illustrating the ultrasonic water meter flow measurement data processing method provided in Embodiment 2 of the present invention. Figure 2 ;

[0040] Figure 3 This is a schematic diagram of the flow measurement data processing device provided in Embodiment 3 of the present invention;

[0041] Figure 4 This is a schematic diagram of the hardware structure of the electronic device provided in Embodiment 4 of the present invention. Detailed Implementation

[0042] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0043] In the embodiments of this application, the terms "first" and "second" are used to distinguish identical or similar items with substantially the same function and effect. Those skilled in the art will understand that the terms "first" and "second" do not limit the quantity or execution order, nor do they necessarily imply difference. It should be noted that in the embodiments of this application, words such as "exemplary" or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design scheme described as "exemplary" or "for example" in this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of words such as "exemplary" or "for example" is intended to present the relevant concepts in a concrete manner. In the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more.

[0044] It should be noted that the phrase "at...time" in the embodiments of this application can refer to the instant at which a certain situation occurs, or to a period of time after the occurrence of a certain situation; the embodiments of this application do not specifically limit this. Furthermore, the training method for lateral control of autonomous driving provided in the embodiments of this application is merely an example; the training method for lateral control of autonomous driving may also include more or less content.

[0045] To facilitate a clear description of the technical solutions in the embodiments of this application, some terms and technologies involved in the embodiments of this application will be briefly introduced below:

[0046] Ultrasonic transducer: refers to an acoustic device installed on the wall of a pipe for transmitting or receiving ultrasonic signals. They are usually arranged in pairs, transmitting and receiving ultrasonic pulse signals in the direction of flow and in the direction of counterflow, respectively.

[0047] With-flow direction / against-flow direction: With-flow direction refers to the path in which the ultrasonic wave propagates in the same direction as the fluid flow, while against-flow direction refers to the reverse path. The time difference between the two propagation directions reflects the influence of fluid velocity.

[0048] Sampling signal: refers to the discrete time sequence formed after the ultrasonic analog signal is digitized by an analog-to-digital converter (ADC), which serves as the basis for subsequent processing.

[0049] First time-domain signal / Second time-domain signal: These refer to the original sampled signals obtained in the downstream and upstream directions, respectively, representing the time-domain response of the ultrasonic waves propagating in the two directions after transmission through the medium.

[0050] Windowing with window functions: Before signal framing, window functions (such as rectangular windows, Hanning windows, etc.) are used to weight each frame of signal to reduce spectral leakage caused by edge abrupt changes and improve transform stability.

[0051] Framing refers to dividing a long, continuous signal into several segments (frames) of fixed length to facilitate subsequent frame-by-frame analysis and processing.

[0052] Frame sequence: refers to a set of equal-length signal segments obtained after windowing and framing, which facilitates batch processing operations at the frame level.

[0053] Fourier Transform / Inverse Fourier Transform: The Fourier Transform converts a time-domain signal into a frequency-domain signal to reveal the characteristics of its frequency components; the Inverse Transform restores the frequency-domain signal to a time-domain waveform.

[0054] Frequency domain signal frame sequence: refers to the set of frequency domain data obtained after the signal is framed and subjected to Fourier transform, which is used for frequency domain processing (such as filtering).

[0055] Frequency domain filtering: Applying filters (such as bandpass, low-pass, high-pass, etc.) to a signal in the frequency domain to remove noise or retain specific frequency bands and improve the quality of the target signal.

[0056] Time-domain signal frame reconstruction: refers to the process of restoring a clearer time-domain signal frame by performing an inverse transform on the frequency-domain filtered spectrum.

[0057] Timing splicing: Connecting multiple frame-level signals sequentially to form a continuous time sequence, maintaining the integrity on the time axis, and ensuring consistency with the physical order of the original signals.

[0058] Cross-correlation analysis: used to detect the similarity between two signals at different time offsets. The propagation delay between signals is identified by finding the position of the maximum value of the cross-correlation function.

[0059] Propagation time difference: This represents the time difference between the transmission of ultrasonic signals in the downstream and upstream directions due to the influence of fluid velocity. It is a core parameter for calculating flow velocity.

[0060] Maximum correlation delay point: refers to the delay position corresponding to the peak value in the cross-correlation function curve, indicating the most likely time alignment point between two signals.

[0061] Sampling period: The time interval at which the ADC digitizes the signal, often used to convert the number of discrete delay points into real time.

[0062] Flow velocity calculation: Based on the propagation time difference and structural parameters such as the distance between sensors, the actual flow velocity of the medium in the pipe is calculated using the sound velocity difference principle.

[0063] Pipe cross-sectional area: refers to the cross-sectional area parameter inside the pipe being measured. It is usually a fixed value and is used to convert flow velocity into volumetric flow rate.

[0064] Flow output: The volumetric flow rate through the pipeline per unit time, calculated by combining the flow velocity and cross-sectional area, can be used as a basis for measurement or control.

[0065] Complex operating conditions, including unstable flow rates, air bubbles or impurities in the water, multipath reflection of signals, and strong noise interference, pose challenges to traditional methods.

[0066] Anti-interference capability / robustness: refers to the ability of this method to maintain the stability of the data processing flow, the accuracy of time difference extraction, and the reliability of flow calculation under the above-mentioned complex working conditions.

[0067] In existing technologies, flow measurement methods based on ultrasonic transducers are widely used for velocity and flow detection of pipeline media, especially due to their advantages such as non-contact operation, fast response, and adaptability to various media, making them highly practical in industrial flow measurement scenarios. However, current ultrasonic flow measurement systems still face many challenges in practical applications, mainly focusing on signal processing accuracy, anti-interference capabilities, and adaptability to complex environments.

[0068] First, current technologies for preprocessing raw ultrasound signals are rather crude, lacking targeted data windowing and framing operations. They often directly analyze the entire signal as a whole, resulting in significant edge effects and severe spectral leakage, which affects the quality of subsequent frequency domain processing. Furthermore, some schemes do not introduce effective filtering mechanisms during frequency domain analysis, or only use fixed-threshold filtering, which is insufficient to effectively remove high-frequency noise, impulse interference, or background stray signals, causing aliasing of frequency domain features and reducing the accuracy of time difference calculations.

[0069] Secondly, the propagation time difference, as a key intermediate quantity for flow velocity calculation, is often roughly estimated in traditional methods through peak positions, zero-crossing points, and correlation accumulation. This is highly susceptible to noise or multipath interference, especially in scenarios with low flow velocities, small signal amplitudes, or complex water quality. The time difference identification is unstable and the accuracy fluctuates greatly, further amplifying the error in flow velocity calculation.

[0070] Furthermore, some existing methods suffer from loose links and a lack of systematic design in their data processing workflows. The processing steps between signal acquisition and output do not form an efficient closed loop, resulting in slow overall system response and poor robustness, which is not conducive to deployment and operation in industrial real-world conditions such as high dynamics and high disturbances.

[0071] In summary, there is an urgent need for an ultrasonic water meter flow measurement data processing method that can improve signal quality, enhance the stability of time difference extraction, and construct a complete processing flow, in order to solve the above-mentioned shortcomings of the existing technology and meet the higher requirements for measurement accuracy, response speed and system stability under complex working conditions.

[0072] Based on this, embodiments of this application provide an ultrasonic water meter flow measurement data processing method, apparatus, device, and storage medium, which can be used in the field of ultrasonic measurement and signal processing technology, and aims to solve the above-mentioned technical problems of the prior art.

[0073] Example 1

[0074] Figure 1 A flowchart illustrating the ultrasonic water meter flow measurement data processing method provided in Embodiment 1 of the present invention. Figure 1 ,like Figure 1 As shown, the method includes:

[0075] S1. Based on the ultrasonic transducer, ultrasonic signals in the downstream and upstream directions are acquired respectively, thereby forming a first time-domain signal and a second time-domain signal;

[0076] Specifically, in step S1, a pair of ultrasonic transducers are configured to emit and receive ultrasonic signals in the co-current and counter-current directions, respectively, and the time response of the signals propagating in the fluid is acquired to generate a first time-domain signal and a second time-domain signal, forming a complete bidirectional acoustic measurement channel. That is, step S1 achieves accurate acquisition of bidirectional propagation information, effectively reflects the influence of fluid motion on the sound velocity propagation path, and ensures that accurate flow velocity calculation can be carried out based on the propagation time difference in the two directions in subsequent processing. By distinguishing between co-current and counter-current propagation signals, the adaptability to asymmetric flow or disturbance conditions can be enhanced, and the overall environmental adaptability of the measurement system can be improved.

[0077] S2. Window the first time-domain signal and the second time-domain signal respectively using window functions, and divide them into frames according to a predetermined frame length to obtain the first signal frame sequence and the second signal frame sequence.

[0078] Specifically, in step S2, a window function is introduced before the signal is framed. The sampled signal is usually weighted using a Hanning window or a Hamming window. Then, it is divided into multiple independent frames according to a set frame length, forming a first signal frame sequence and a second signal frame sequence. That is, the window function can effectively suppress the spectral leakage caused by abrupt changes in frame boundaries and improve the energy focusing of frequency domain analysis. The framed processing can keep the signal stable in a local time period, which is more conducive to fine frequency domain analysis and time sequence reconstruction. Through step S2, the system signal processing link obtains good time and frequency resolution capability, providing high-quality input data for subsequent processing.

[0079] S3. Perform Fourier transform on the first signal frame sequence and the second signal frame sequence respectively to obtain the corresponding frequency domain signal frame sequence. Perform frequency domain filtering on the frequency domain signal frame sequence to remove noise and interference. Then perform inverse Fourier transform on the filtered frequency domain signal frame sequence to obtain the first time domain signal frame sequence and the second time domain signal frame sequence.

[0080] Specifically, in step S3, Fourier transforms are performed frame by frame on the first and second signal frame sequences to obtain frequency domain signal frame sequences. Then, frequency domain filtering is used to remove high-frequency noise, background interference, and spurious components. Finally, an inverse Fourier transform is performed on the filtered frequency domain data to reconstruct the purified first and second time domain signal frame sequences. Frequency domain filtering improves the purity of the signal and the ability to express effective signal components, effectively eliminating interference components caused by pipe impurities, transducer aging, or environmental noise. Simultaneously, the time domain signal restored by the inverse transform has stronger stability and boundary continuity, laying a solid foundation for time difference analysis.

[0081] S4. The first time-domain signal frame sequence and the second time-domain signal frame sequence are spliced ​​together in time, and the ultrasonic propagation time difference is extracted by cross-correlation analysis.

[0082] Specifically, in step S4, the filtered and reconstructed frame sequence is spliced ​​together in chronological order to form complete continuous time-domain signals in the first and second directions. Subsequently, based on the cross-correlation analysis method, a sliding comparison is performed on the two signals to extract the most probable propagation time difference. That is, the complete signal trajectory is restored through time-series splicing, avoiding the problem of signal continuity being affected by frame structure fragmentation. The cross-correlation algorithm for delay detection has strong noise robustness and positioning accuracy, and can accurately identify the time delay of the real propagation path under complex conditions such as echo interference, nonlinear distortion, or signal envelope overlap.

[0083] S5. Calculate the flow velocity based on the propagation time difference, and calculate the water flow rate by combining the pipe cross-sectional area.

[0084] Specifically, in step S5, the extracted propagation time difference is used as the core parameter. Combined with structural information such as transducer spacing, the instantaneous flow velocity of the medium in the pipe is calculated. Then, the volumetric flow rate output is calculated by combining the known pipe cross-sectional area. That is, the flow velocity estimation method based on propagation time difference is highly accurate and has a fast response. At the same time, by combining actual pipe size data, the water flow rate result can be output in real time, completing the closed-loop process from signal acquisition to metering output.

[0085] Therefore, the ultrasonic water meter flow measurement data processing method provided by this invention systematically solves the technical problems existing in current ultrasonic flow measurement technology, such as poor signal quality, weak anti-interference ability, and unstable time difference identification, by constructing a complete signal acquisition, preprocessing, frequency domain enhancement, time difference extraction, and flow calculation chain. It has the following significant advantages:

[0086] First, in the signal acquisition and preprocessing stage, this invention employs a bidirectional ultrasonic signal synchronous acquisition mechanism, combined with windowing using window functions and fixed-length framing, to ensure the time-frequency locality and boundary continuity of the signal from the source. This design effectively suppresses the spectral leakage problem caused by signal truncation in traditional methods, providing a high-quality time-frequency analysis foundation for subsequent processing.

[0087] Secondly, in the signal enhancement stage, this invention employs a processing architecture combining frame-by-frame Fourier transform with frequency domain filtering. Frequency-selective filtering effectively eliminates various noise interferences, while inverse transform reconstructs a clean time-domain signal. Compared to traditional time-domain filtering or overall frequency-domain processing methods, this approach significantly improves the signal-to-noise ratio and feature preservation capability.

[0088] In the critical time difference extraction stage, this invention restores signal continuity through time-series splicing and accurately identifies propagation delay using cross-correlation analysis. This method fully utilizes the overall waveform characteristics of the signal and, compared to traditional peak detection or zero-crossing detection methods, has stronger anti-interference capabilities and sub-sampling level time resolution.

[0089] Finally, in the flow calculation stage, this invention uses high-precision time difference measurement results combined with pipeline structural parameters for integrated calculation, achieving a complete closed-loop processing from the raw signal to the flow output. This end-to-end processing flow ensures the consistency and reliability of the measurement results, making it particularly suitable for long-term stable operation under complex industrial conditions.

[0090] In some embodiments, for the signal preprocessing process of step S2, windowing with a window function is performed as follows: applying a window function to the first time-domain signal and the second time-domain signal respectively for windowing, so as to reduce the sudden change effect at the signal frame boundary and the resulting spectral leakage problem. Specifically, the window function used can be any one of a Hamming window, a Hanning window, or a Blackman window.

[0091] In some embodiments, for step S2, the framing process is based on a preset frame length N and a frame shift amount M, and the windowed first time-domain signal and second time-domain signal are framed to form a first signal frame sequence and a second signal frame sequence. Here, the frame length N refers to the number of sampling points included in each frame, and the frame shift amount M refers to the starting position offset between adjacent frames; when M < N, there is an overlap between adjacent frames, which is commonly used to improve the temporal continuity and frequency-domain smoothness. By setting reasonable N and M parameters in the present invention, while the signal is divided into multiple short time periods, the necessary time continuity and spectral integrity are still retained.

[0092] Specifically, after framing with the window function, a soft transition is formed between frame segments through overlap (determined by M < N), effectively alleviating the energy jump problem caused by hard cutting, further suppressing spectral leakage, and enhancing spectral smoothness and energy focusing ability.

[0093] At the same time, since the frame length N and the frame shift amount M are adjustable parameters, they can be dynamically configured according to the signal-to-noise ratio characteristics, waveform structure, and computing resources of different application scenarios, enhancing the adaptability of the system under different working conditions; for example, in a high-noise scenario, a longer frame length can be selected in combination with a smaller frame shift to improve spectral clarity and time tracking ability.

[0094] In some embodiments, for the frequency-domain filtering operation in step S3, a band-pass filter is used for frequency-domain filtering to suppress noise and interference components in non-target frequency bands, thereby retaining the effective information consistent with the frequency of the ultrasonic main signal. Specifically, the band-pass filter includes a Gaussian-type frequency-domain filter or a rectangular-window-type frequency-domain filter.

[0095] Among them, a band-pass filter is a filtering structure that allows a specific frequency interval (i.e., the target frequency band) to pass through while suppressing all frequency components outside this frequency band. In the present invention, based on the characteristics that the signal emitted by the ultrasonic transducer has a stable center frequency and a limited bandwidth, the band-pass filter can be accurately designed around this main frequency range to shield irrelevant noise and abnormal spectral fluctuations.

[0096] In some implementations, for step S4, the first time-domain signal frame sequence and the second time-domain signal frame sequence are time-sequentially concatenated to form a first time-domain signal and a second time-domain signal. The ultrasonic wave propagation time difference is extracted through cross-correlation analysis, wherein the cross-correlation function for performing the cross-correlation analysis is defined as:

[0097] ;

[0098] The time difference of propagation is t, , The sampling period is [period], and the first time-domain signal is [signal]. The second time-domain signal is , for and Between delays The cross-correlation function values ​​under the following conditions For delay amount, This refers to the number of sampling points contained in a single frame. for Delay amount of the maximum value , This is the index of the current intra-frame sampling point.

[0099] For example, the time difference of propagation This represents the difference in propagation time of ultrasonic waves in the forward and reverse flow directions. It is a core input variable for subsequent calculations of flow velocity and volumetric flow rate. (The last sentence appears to be incomplete and possibly refers to a different variable.) It has stronger physical accuracy and signal consistency, providing a high-quality data foundation for the entire measurement system.

[0100] In some implementations, for step S5, the flow rate is calculated using the following formula:

[0101] ;

[0102] Where L is the distance between the ultrasonic transducers; and Represent the propagation time in the downstream and upstream directions, respectively, satisfying t;

[0103] Let the water flow rate be Q, and it is calculated using the following formula:

[0104] ;

[0105] Where A is the cross-sectional area of ​​the pipe. This represents the average flow velocity of water in the pipe.

[0106] In some implementations, the propagation time difference between the ultrasonic waves propagating in the upstream and downstream directions is extracted by acquiring the time-domain signals and performing cross-correlation analysis. t, the t represents the downstream propagation time. With the time of reverse propagation The difference between them, and satisfying t;

[0107] It should be noted that the downstream propagation time is not directly measured in the ultrasonic water meter flow measurement data processing method. With the time of reverse propagation Instead of determining the specific numerical value, the analysis uses a cross-correlation function to analyze the received signals from both directions and identify the number of time delay points corresponding to the cross-correlation peak. Then multiply by the sampling period The propagation time difference was calculated. t: ;

[0108] The cross-correlation function measures the similarity between two waveforms at different time delays, enabling stable and accurate extraction of the time difference between waveforms. It achieves reliable matching even in noisy backgrounds or with signal amplitude distortion. It is the difference between the propagation time with and against the current; therefore, as long as the average propagation time is known further... (For example, based on a preliminary estimate using the speed of sound and the transducer spacing L), the following formula can be used to deduce:

[0109] , ;

[0110] For example, when the flow rate is low, The values ​​are relatively small, and conventional methods are prone to instability in estimating time differences due to signal ambiguity. However, cross-correlation methods can be enhanced by increasing the sampling rate or using interpolation. The time resolution enables effective sensing of flow velocities below 0.05 m / s.

[0111] Example 2

[0112] Figure 2 A flowchart illustrating the ultrasonic water meter flow measurement data processing method provided in Embodiment 2 of the present invention. Figure 2 In this embodiment, Figure 1 Based on the embodiments, the data processing method for ultrasonic water meter flow measurement is described in detail, such as... Figure 2 As shown, the method includes:

[0113] S11. Ultrasonic transducers are installed at both ends of the pipeline. The ultrasonic transducers are used to alternately transmit and receive ultrasonic signals to form a first ultrasonic signal that propagates in the downstream direction and a second ultrasonic signal that propagates in the upstream direction in the pipeline.

[0114] Specifically, ultrasonic transducers are installed at both the upstream and downstream ends of the pipeline. These transducers alternately transmit and receive ultrasonic signals, generating a first ultrasonic signal propagating in the downstream direction and a second ultrasonic signal propagating in the upstream direction, respectively. This bidirectional signal construction mechanism not only reflects the influence of the fluid on the ultrasonic propagation velocity but also facilitates the calculation of flow velocity through time difference, thus improving measurement sensitivity and accuracy.

[0115] S12. The first ultrasonic signal and the second ultrasonic signal are sampled and processed respectively to obtain the corresponding first original time domain signal and the second original time domain signal. The first original time domain signal and the second original time domain signal are preprocessed respectively. The preprocessing includes applying a window function to both the first original time domain signal and the second original time domain signal to perform windowing operation. The windowed first original time domain signal and the second original time domain signal are framed respectively to obtain the first signal frame sequence and the second signal frame sequence.

[0116] Specifically, ultrasonic signals from two directions are sampled to obtain a first and a second original time-domain signal. To improve signal processing, windowing is applied using a window function, and framing is performed to form a frame-level signal sequence. This processing helps suppress spectral leakage, improve time resolution, and provide high-quality input for subsequent frequency domain processing.

[0117] S13. Perform Fourier transform on the first signal frame sequence and the second signal frame sequence respectively to obtain the first frequency domain signal frame sequence and the second frequency domain signal frame sequence, and perform frequency domain filtering on the first frequency domain signal frame sequence and the second frequency domain signal frame sequence to obtain the filtered third frequency domain signal frame sequence and the fourth frequency domain signal frame sequence.

[0118] Specifically, Fast Fourier Transform (FFT) is performed on the first and second signal frame sequences respectively to obtain their frequency domain representations. Then, frequency domain filtering is applied to remove interference from irrelevant frequency bands, ultimately yielding the third and fourth frequency domain signal frame sequences with high signal-to-noise ratios. This step effectively reduces the influence of power frequency, electromagnetic, or background noise, enhances the structural characteristics of the useful signal, and improves the accuracy of subsequent time difference extraction.

[0119] S14. Perform inverse Fourier transform on the third frequency domain signal frame sequence and the fourth frequency domain signal frame sequence respectively to obtain the restored first time domain signal frame sequence and second time domain signal frame sequence.

[0120] Specifically, the third and fourth frequency domain signal frame sequences are subjected to inverse Fourier transform processing to obtain the restored first and second time domain signal frame sequences, thereby enhancing signal clarity and time domain alignment, and providing higher quality input for the next step of cross-correlation analysis.

[0121] S15. Perform cross-correlation analysis on the first time-domain signal frame sequence and the second time-domain signal frame sequence to extract the propagation time difference between the first ultrasonic signal and the second ultrasonic signal.

[0122] Specifically, after the time-domain signal optimization is completed, cross-correlation analysis is performed to extract the propagation time difference between the first and second ultrasonic signals. The cross-correlation method extracts the time difference by matching the overall waveform, avoiding dependence on the starting point or instantaneous feature points, and has good anti-interference ability. Even under conditions of low flow velocity or poor signal-to-noise ratio, it can still obtain stable and reliable time difference values.

[0123] S16. Based on the propagation time difference and the preset distance between the ultrasonic transducers, calculate the velocity of the water flow in the pipe, and calculate the water flow rate according to the cross-sectional area of ​​the pipe.

[0124] Specifically, the flow velocity is calculated based on the extracted propagation time difference and the preset distance between the transducer, and the water flow rate is calculated in combination with the pipe cross-sectional area, thereby reducing the dependence on time synchronization accuracy. It is applicable to water meter structures of different sizes and flow ranges, and the output results can be directly used for flow monitoring and billing management.

[0125] Specifically, in step S12, the window function is any one of the Hanning window, Hamming window, or Blackman window, wherein the window function is set to ;

[0126] Windowing operations include: setting the first time-domain signal to... The second time-domain signal is set as follows: ,Will and Frames are divided according to a fixed frame length N and a frame shift M to form a frame sequence. and ,in, This represents the i-th frame of the first time-domain signal. This represents the i-th frame of the second time-domain signal, where the intra-frame index n ranges from 0 to n. <N;

[0127] Apply a window function to each frame The first and second signal frame sequences after windowing are obtained, wherein the windowing processing form of each frame is as follows:

[0128] ; ;

[0129] Where i represents the frame number and n represents the sampling point within the frame. Indicates the first signal frame sequence. This represents the second signal frame sequence.

[0130] Specifically, the introduction of the window function significantly suppresses spectral leakage caused by signal frame boundaries, especially providing a clearer and more reliable frequency domain representation for short-time signal segments. Furthermore, the use of frame length N and frame shift M for framing gives the system a sliding window structure, adapting to dynamic characteristics such as flow velocity fluctuations and signal periodic changes. Moreover, the signal after windowing with the window function and standard framing exhibits good waveform consistency and alignment, which helps in the accurate identification of cross-correlation peaks and propagation time differences. Stable extraction.

[0131] Specifically, in step S13, Fourier transforms are performed on the first signal frame sequence and the second signal frame sequence respectively, and the transform formula is as follows:

[0132] ;

[0133] ;

[0134] Where k represents the frequency index. The length of each frame is j, where j is the imaginary unit. This is the first frequency domain signal frame sequence. This is the second frequency domain signal frame sequence.

[0135] Specifically, in step S13, frequency domain filtering includes applying a Gaussian bandpass filter to each frame of the first frequency domain signal frame sequence and the second frequency domain signal frame sequence, wherein the filter function is defined as:

[0136] ;

[0137] After filtering, we get:

[0138] ;

[0139] ;

[0140] in, This is a sequence of signal frames in the third frequency domain. This is a fourth frequency domain signal frame sequence. For the first Filter gain coefficient at each frequency point Controlling the filter bandwidth; the smaller the value, the narrower the bandwidth. This is the index corresponding to the center frequency of the filter.

[0141] Specifically, in step S14, an inverse Fourier transform is performed on each frame of the third frequency domain signal frame sequence and the fourth frequency domain signal frame sequence to obtain the first time domain signal frame sequence and the second time domain signal frame sequence, wherein the transform formula is:

[0142] ;

[0143] ;

[0144] in, and These are the first time-domain signal frame sequence and the second time-domain signal frame sequence, respectively. is the frame length, k is the frequency index, n is the intra-frame sampling point index, and j is the imaginary unit.

[0145] Specifically, in step S15, the first time-domain signal frame sequence and the second time-domain signal frame sequence are concatenated to form a first reconstructed time-domain signal and a second reconstructed time-domain signal, respectively. The first reconstructed time-domain signal is set as... The second reconstructed time-domain signal is set as and to and Perform cross-correlation analysis;

[0146] The cross-correlation function used to perform cross-correlation analysis is defined as follows:

[0147] ;

[0148] The time difference of propagation is t, , The sampling period is [period], and the first time-domain signal is [signal]. The second time-domain signal is , for and Between delays The cross-correlation function values ​​under the following conditions For delay amount, This refers to the number of sampling points contained in a single frame. for Delay amount of the maximum value , This is the index of the current intra-frame sampling point.

[0149] Specifically, in step S16, the velocity of the water flow in the pipe is calculated as follows:

[0150] ;

[0151] Where L is the distance between the ultrasonic transducers; and Represent the propagation time in the downstream and upstream directions, respectively, satisfying t;

[0152] Let the water flow rate be Q, and it is calculated using the following formula:

[0153] ;

[0154] Where A is the cross-sectional area of ​​the pipe.

[0155] Example 3

[0156] Figure 3 This is a schematic diagram of the flow measurement data processing device provided in Embodiment 3 of the present invention. Figure 3 As shown, the flow measurement data processing device 100 provided in Embodiment 3 of the present invention includes an acquisition module 110, a processing module 120, a filtering module 130, an extraction module 140, and a calculation module 150.

[0157] The acquisition module 110 acquires ultrasonic signals in the downstream and upstream directions through an ultrasonic transducer, thereby forming a first time-domain signal and a second time-domain signal.

[0158] The processing module 120 performs windowing processing on the first time-domain signal and the second time-domain signal respectively, and divides them into frames according to a predetermined frame length to obtain a first signal frame sequence and a second signal frame sequence.

[0159] The filtering module 130 performs Fourier transform on the first signal frame sequence and the second signal frame sequence respectively to obtain the corresponding frequency domain signal frame sequence. It then performs frequency domain filtering on the frequency domain signal frame sequence to remove noise and interference. Finally, it performs inverse Fourier transform on the filtered frequency domain signal frame sequence to obtain the first time domain signal frame sequence and the second time domain signal frame sequence.

[0160] The extraction module 140 performs time-series splicing of the first time-domain signal frame sequence and the second time-domain signal frame sequence, and extracts the ultrasonic wave propagation time difference through cross-correlation analysis.

[0161] The calculation module 150 calculates the flow velocity based on the propagation time difference and calculates the water flow rate in combination with the cross-sectional area of ​​the pipe.

[0162] The flow measurement data processing device 100 provided in this embodiment can execute the ultrasonic water meter flow measurement data processing method of the above embodiment 1. Its implementation principle and technical effect are similar, and will not be described again in this embodiment 3.

[0163] In a specific implementation of the aforementioned flow measurement data processing device 100, each module can be implemented as a processor. The processor can execute computer execution instructions stored in the memory, causing the processor to execute the aforementioned ultrasonic water meter flow measurement data processing method.

[0164] Example 4

[0165] Figure 4 This is a schematic diagram of the hardware structure of the electronic device provided in Embodiment 4 of the present invention. Figure 4 A block diagram is shown of an exemplary electronic device 12 suitable for implementing embodiments of the present invention. Figure 4 The electronic device 12 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0166] like Figure 4 As shown, the electronic device 12 is represented in the form of a general-purpose computing device. The components of the electronic device 12 may include, but are not limited to: one or more processors or processing units 16, system memory 28, and bus 18 connecting different system components (including system memory 28 and processing unit 16).

[0167] Bus 18 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0168] Electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by electronic device 12, including volatile and non-volatile media, removable and non-removable media.

[0169] System memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Electronic device 12 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media. Each drive may be connected to bus 18 via one or more data media interfaces. Memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0170] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of the present invention.

[0171] Electronic device 12 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable a user to interact with the electronic device 12 / server / computer, and / or with any device that enables the electronic device 12 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed via input / output (I / O) interface 22. Furthermore, electronic device 12 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 20. As shown, network adapter 20 communicates with other modules of electronic device 12 via bus 18. It should be understood that, although not shown in the figures, other hardware and / or software modules can be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0172] The processing unit 16 executes various functional applications and data processing by running programs stored in the system memory 28, such as implementing the ultrasonic water meter flow measurement data processing method provided in the embodiments of the present invention.

[0173] Meanwhile, this embodiment of the invention also provides a storage medium containing computer-executable instructions, which, when executed by a computer processor, are used to perform the ultrasonic water meter flow measurement data processing method provided in the above embodiments.

[0174] Example 5

[0175] The computer storage medium of Embodiment 5 of the present invention can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of computer-readable storage media (a non-exhaustive list) include: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0176] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0177] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including—but not limited to—wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0178] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network—including a local area network (LAN) or a wide area network (WAN)—or can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0179] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for processing flow measurement data from an ultrasonic water meter, characterized in that, Includes the following steps: S1. Based on the ultrasonic transducer, ultrasonic signals in the downstream and upstream directions are acquired respectively, thereby forming a first time-domain signal and a second time-domain signal; S2. Window the first time-domain signal and the second time-domain signal respectively using window functions, and divide them into frames according to a predetermined frame length to obtain the first signal frame sequence and the second signal frame sequence. S3. Perform Fourier transform on the first signal frame sequence and the second signal frame sequence respectively to obtain the corresponding frequency domain signal frame sequence. Perform frequency domain filtering on the frequency domain signal frame sequence to remove noise and interference. Then perform inverse Fourier transform on the filtered frequency domain signal frame sequence to obtain the first time domain signal frame sequence and the second time domain signal frame sequence. S4. The first time-domain signal frame sequence and the second time-domain signal frame sequence are spliced ​​together in time, and the ultrasonic propagation time difference is extracted by cross-correlation analysis. S5. Calculate the flow velocity based on the propagation time difference, and calculate the water flow rate in combination with the cross-sectional area of ​​the pipe.

2. The ultrasonic water meter flow measurement data processing method according to claim 1, characterized in that, In step S2, the window function windowing process involves applying window functions to the first time-domain signal and the second time-domain signal respectively to reduce boundary effects and leakage. The window function includes any one of Hamming window, Hanning window, or Blackman window.

3. The ultrasonic water meter flow measurement data processing method according to claim 1, characterized in that, In step S2, the framing process divides the windowed first time-domain signal and the second time-domain signal into frames based on a preset frame length N and frame shift M, thereby forming the first signal frame sequence and the second signal frame sequence.

4. The ultrasonic water meter flow measurement data processing method according to claim 1, characterized in that, In step S3, the frequency domain filtering uses a bandpass filter to filter out noise and interference components in non-target frequency bands. The bandpass filter includes a Gaussian or rectangular window frequency domain filter.

5. The ultrasonic water meter flow measurement data processing method according to claim 1, characterized in that, In step S4, the first time-domain signal frame sequence and the second time-domain signal frame sequence are time-series concatenated to form a first time-domain signal and a second time-domain signal. The ultrasonic wave propagation time difference is extracted through cross-correlation analysis. The cross-correlation function for performing the cross-correlation analysis is defined as: ； The propagation time difference is t, , The sampling period is [period], and the first time-domain signal is [signal]. The second time-domain signal is , for and Between delays The cross-correlation function values ​​under the following conditions For delay amount, This refers to the number of sampling points contained in a single frame. for Delay amount of the maximum value , This is the index of the current intra-frame sampling point.

6. The ultrasonic water meter flow measurement data processing method according to claim 1, characterized in that, In step S5, the flow rate is calculated using the following formula: ； Where L is the distance between the ultrasonic transducers; and Represent the propagation time in the downstream and upstream directions, respectively, satisfying t; The water flow rate is denoted as Q, and is calculated using the following formula: ； Where A is the cross-sectional area of ​​the pipe. This represents the average flow velocity of water in the pipe.

7. A flow measurement data processing device, characterized in that, include: The acquisition module acquires ultrasonic signals in the downstream and upstream directions respectively through an ultrasonic transducer, thereby forming a first time-domain signal and a second time-domain signal; The processing module performs windowing processing on the first time-domain signal and the second time-domain signal respectively, and divides them into frames according to a predetermined frame length to obtain the first signal frame sequence and the second signal frame sequence. The filtering module performs Fourier transform on the first signal frame sequence and the second signal frame sequence respectively to obtain the corresponding frequency domain signal frame sequence. It then performs frequency domain filtering on the frequency domain signal frame sequence to remove noise and interference. Finally, it performs inverse Fourier transform on the filtered frequency domain signal frame sequence to obtain the first time domain signal frame sequence and the second time domain signal frame sequence. The extraction module performs time-series splicing of the first time-domain signal frame sequence and the second time-domain signal frame sequence, and extracts the ultrasonic wave propagation time difference through cross-correlation analysis; The calculation module calculates the flow velocity based on the propagation time difference and calculates the water flow rate by combining the cross-sectional area of ​​the pipe.

8. An electronic device, characterized in that, include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executed instructions; When the processor executes the computer execution instructions stored in the memory, it is used to implement the ultrasonic water meter flow measurement data processing method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the ultrasonic water meter flow measurement data processing method as described in any one of claims 1 to 6.

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