Method and system for measuring flow velocity of plant liquid flow, computer equipment and medium

Abstract

The invention provides a plant liquid flow velocity measurement method and system, computer equipment and a medium, and belongs to the field of liquid flow velocity detection in phytophysiology, the method comprises the following steps: collecting upstream and downstream discrete sequences of a target plant branch liquid flow to construct a cross-correlation function; calculating a sampling point interval by using an initial window, substituting all sampling points into a cross-correlation function to calculate a cross-correlation value, and counting a maximum value and a mean value; determining the transit time based on the sampling point corresponding to the maximum value, and adaptively adjusting the window size according to the standard deviation of the transit time and the maximum peak value and mean value of the cross-correlation value until the stability and correlation constraint conditions are met; according to the method, self-adaptive adjustment of the window length is achieved, the measurement problem caused by long signal delay time at the plant liquid flow velocity is effectively solved, the reliability and efficiency of plant liquid flow velocity measurement are remarkably improved, and an effective technical means is provided for plant physiology and ecology research.

Description

Technical Field

[0001] This invention belongs to the field of sap flow velocity detection in plant physiology, specifically relating to a method, system, computer equipment, and medium for measuring plant sap flow velocity. Background Technology

[0002] Measuring fluid velocity enables better analysis, application, and management of fluids. Velocity not only describes the speed of fluid movement but is also a crucial prerequisite for accurately measuring other fluid parameters. Measuring sap flow within plants allows for effective research into the relationship between whole-plant transpiration and plant water. Water is vital for plant physiology and ecology. Plant roots continuously absorb water from the soil and transport it to various parts of the plant to meet the needs of normal life activities. Measuring plant sap flow velocity is of great significance for further research on plant transpiration water consumption assessment, water stress studies, and the exploration of water use strategies.

[0003] Common flow velocity measurement methods include differential pressure measurement, particle image analysis (PIV), ultrasonic Doppler ultrasound, and cross-correlation methods. However, these methods are mainly for measuring conventional flow velocities above 1 cm / s. In practical applications and scientific research, there are fluids with flow velocities far below 1 cm / s, such as plant stem flow, colloid electrophoresis, multi-media osmosis, and microreactors, which are mostly concentrated between 0.01 and 0.5 mm / s. The flow velocity of sap within plants is generally between 0.02 and 0.05 mm / s, which is 2-3 orders of magnitude smaller than the flow velocity measurement range of conventional methods. In this case, conventional flow velocity measurement methods will be ineffective.

[0004] In practical engineering measurements, it is often necessary to study the relationship between two signal variables. However, signals are often randomly changing or subject to interference, exhibiting uncertainty. The cross-correlation function is used to describe the similarity between two random signals, reflecting their correlation information, and is helpful for signal calculation and analysis.

[0005] Currently, the cross-correlation time delay estimation method has been widely recognized in the application of flow velocity measurement. By installing sensors upstream and downstream of the fluid, the changes in the measured signal are converted into changes in the electrical signal. After a series of conversions including amplification, filtering, and A / D conversion circuits, the signal is sent to a cross-correlation circuit for processing. The cross-correlation function of the signal is calculated, and the cross-correlation information within the measurement window is extracted to find the peak coordinates. The transit time of the fluid from upstream to downstream is obtained. By combining the transit time with the distance between upstream and downstream, the flow velocity can be calculated.

[0006] Compared to traditional velocity measurement methods, cross-correlation velocity measurement has the following advantages: traditional methods require separating the fluid phase components and measuring their velocities separately, while cross-correlation methods only require installing sensors and data acquisition circuits upstream and downstream of the flow, simplifying equipment and operation; it uses the correlation between upstream and downstream signals for calculation, avoiding the influence of uncorrelated noise; and the calculated cross-correlation coefficient can be used as an indicator to measure flow stability.

[0007] When the fluid flow rate is extremely slow, cross-correlation calculations over a relatively long time interval (i.e., the measurement window) are required to achieve effective flow rate measurement. The determination of this time interval depends on the flow rate and varies over a large range. If a fixed measurement window is used, it cannot be applied to the measurement of different flow rates. Therefore, it is urgent to find a new method to optimize and improve the traditional cross-correlation algorithm to solve the problem of measuring the flow rate of plant sap. Summary of the Invention

[0008] To address the problem that the fixed window of the cross-correlation algorithm fails when calculating the velocity of extremely slow-flowing fluids, this invention provides a method, system, computer device, and medium for measuring the velocity of plant sap flow, which can automatically select an appropriate measurement window for different flow velocities.

[0009] To achieve the above objectives, the present invention provides a method for measuring the flow rate of plant sap, comprising: During the preset time period t Inside, the distance between the target plant branches and trunks was simultaneously collected. L upstream fluid flow signal x ( t ) and downstream fluid flow signal y ( t ).

[0010] Will x ( t )and y ( t Convert each to an initial window length of ) N upstream discrete sequence x ( k and downstream discrete sequences y ( k );set up y ( k Relative to x ( k The acquisition delay time is the offset of the number of sampling points. m And collect downstream discrete sequences under delay time. y ( k+m ); the m The range of values ​​is determined by N It is confirmed that the k This is the index of the sampling points after the fluid flow signal is discretized.

[0011] By traversal m ,right x ( k )and y ( k+m Perform cross-correlation calculations to obtain a cross-correlation value array; calculate the mean of the current cross-correlation value array. and maximum value Record the above Corresponding maximum sampling point offset From the current Calculate the estimated crossing time of the target plant, and then calculate the standard deviation of the estimated crossing time. .

[0012] like , and Window length when preset conditions are not met N Increment; and update the sampling point offset. m The range of values, calculate the updated m Corresponding , and ;like , and Stop when preset conditions are met. An incrementing loop; let's record the value at this point. Corresponding sampling point offset This represents the offset of the final number of sampling points.

[0013] The flow rate of the target plant sap is obtained by using the offset of the final sampling point number.

[0014] Preferably, the step of traversing m right x ( k )and y ( k+m Perform cross-correlation calculations to obtain an array of cross-correlation values. The expression for the cross-correlation calculation is as follows: ; In the formula, It is a cross-correlation function. m [- ].

[0015] Preferably, the step of determining the target plant sap flow velocity using the final sampling point offset includes: The upstream fluid flow signal x ( t ) and downstream fluid flow signal y (t The sampling frequency is Using the final sampling point offset and sampling frequency The ratio is used to calculate the transit time; using L The target plant flow velocity is obtained by comparing the flow velocity with the transit time.

[0016] Preferably, the if , and Stop when preset conditions are met. The incrementing loop includes: like Less than the preset standard deviation, and in the current loop and Stop when the difference is greater than the preset cross-correlation value. N An incrementing loop.

[0017] The present invention also provides a system for measuring the flow rate of plant sap, comprising: The signal acquisition module is used to acquire signals within a preset time period. t Inside, the distance between the target plant branches and trunks was simultaneously collected. L upstream fluid flow signal x ( t ) and downstream fluid flow signal y ( t );Will x ( t )and y ( t Convert each to an initial window length of ) N upstream discrete sequence x ( k and downstream discrete sequences y ( k );set up y ( k Relative to x ( k The acquisition delay time is the offset of the number of sampling points. m And collect downstream discrete sequences under delay time. y ( k+m ); the m The range of values ​​is determined by N It is confirmed that the k This is the index of the sampling points after the fluid flow signal is discretized.

[0018] The window determination module is used to determine the window through traversal. m ,right x ( k )and y ( k+m Perform cross-correlation calculations to obtain a cross-correlation value array; calculate the mean of the current cross-correlation value array. and maximum value Record the above Corresponding maximum sampling point offset From the current Calculate the estimated crossing time of the target plant, and then calculate the standard deviation of the estimated crossing time. ;like , and When the preset conditions are not met, the window N Increment; and update the sampling point offset. m The range of values, calculate the updated m Corresponding , and ;like , and Stop when preset conditions are met. An incrementing loop; let's record the value at this point. Corresponding sampling point offset This represents the offset of the final number of sampling points.

[0019] The flow velocity calculation module is used to determine the flow velocity of the target plant using the offset of the final sampling point count.

[0020] The present invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of any one of the methods for measuring the flow rate of plant sap.

[0021] The present invention also provides a computer-readable storage medium storing a computer program that, when loaded by a processor, is capable of executing any of the steps in the method for measuring the flow rate of plant sap.

[0022] The method for measuring the flow rate of plant sap provided by this invention has the following beneficial effects: The adaptive optimal window finding method proposed in this invention is applicable to fluids with extremely slow flow rates. The cyclic self-adding sampling point method provided by this invention allows the measurement window to dynamically and adaptively adjust its size and shape according to the characteristics of the measured object or measurement requirements, offering significant advantages in improving measurement accuracy and efficiency; [The last sentence appears to be incomplete and requires further context.] , and The decision criteria improve the reliability and stability of the algorithm, increase the utilization rate of sample data and the accuracy of the estimation algorithm; by realizing the adaptive adjustment of the window length, the problem of not being able to measure the velocity of slow fluids in conventional velocity measurement methods is solved. Attached Figure Description

[0023] To more clearly illustrate the embodiments and design schemes of the present invention, the accompanying drawings required for this embodiment will be briefly described below. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0024] Figure 1 This is a flowchart of a method for measuring the flow rate of plant sap according to an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the principle of cross-correlation velocity measurement according to an embodiment of the present invention. Figure 3 This is a flowchart illustrating the implementation of the adaptive window in an embodiment of the present invention. Figure 4 This is a comparative experimental diagram of the conventional method in an embodiment of the present invention; Figure 4 (a) shows the upstream and downstream signal waveforms. Figure 4 (b) is a graph showing the results of the cross-correlation calculation; Figure 5 This is an experimental comparison diagram of the adaptive window algorithm in an embodiment of the present invention; Figure 5 (a) is the original signal waveform. Figure 5 (b) is a schematic diagram of upstream and downstream signals; Figure 6 This is a comparative experimental diagram of the denoised signal according to an embodiment of the present invention; Figure 6 (a) is a schematic diagram of upstream and downstream signals. Figure 6 (b) is a graph showing the results of the cross-correlation calculation. Figure 6 (c) is a graph showing the change in transit time. Detailed Implementation

[0025] To enable those skilled in the art to better understand and implement the technical solutions of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and should not be construed as limiting the scope of protection of the present invention.

[0026] This invention provides a method for measuring the flow rate of plant sap, specifically as follows: Figure 1 As shown, it includes: S1, within the preset time period t Inside, the distance between the target plant branches and trunks was simultaneously collected. L upstream fluid flow signal x ( t ) and downstream fluid flow signal y ( t );Will x ( t )and y (t Convert each to an initial window length of ) N upstream discrete sequence x ( k and downstream discrete sequences y ( k );set up y ( k Relative to x ( k The acquisition delay time is the offset of the number of sampling points. m And collect downstream discrete sequences under delay time. y ( k+m ); the m The range of values ​​is determined by N It is confirmed that the k This is the index of the sampling points after the fluid flow signal is discretized.

[0027] The plant sap flow velocity range studied in this invention is 0.01-0.5 mm / s. Two identical sensors are installed at a certain distance L between the upstream and downstream sides of the fluid flow path, with the fluid flow direction being consistent. The upstream sap flow signal reflecting the flow information of the fluid under test is obtained. x ( t ) and downstream fluid flow signal y ( t Discretize the two signals in the time domain to obtain the corresponding upstream discrete sequences. x ( k and downstream discrete sequences y ( k ).

[0028] S2, used for traversal m ,right x ( k )and y ( k+m Perform cross-correlation calculations to obtain a cross-correlation value array; calculate the mean of the current cross-correlation value array. and maximum value Record the above Corresponding maximum sampling point offset From the current Calculate the estimated crossing time of the target plant, and then calculate the standard deviation of the estimated crossing time. ;like , and When the preset conditions are not met, the window N Increment; and update the sampling point offset. m The range of values, calculate the updated m Corresponding , and ;like , and Stop when preset conditions are met. An incrementing loop; let's record the value at this point. Corresponding sampling point offset This represents the offset of the final number of sampling points.

[0029] Based on the upstream discrete sequence x ( k and downstream discrete sequences y ( k Construct a cross-correlation function, with the following expression: ; In the formula, For cross-correlation function, by N Determine the offset of the number of sampling points m The range of values ​​for , .

[0030] Cross-correlation calculations are performed on the fluid flow signals measured by upstream and downstream sensors to obtain the cross-correlation function. The time delay corresponding to the peak value is the transit time. This refers to the time it takes for the measured fluid to flow through the upstream and downstream sensors. For example... Figure 2 As shown, the signal waveforms collected by the sensor and discretized are cross-correlation calculated, and the time delay value obtained after each cross-correlation calculation is stored.

[0031] Selecting an appropriate measurement window is crucial for accurate measurement. This requires clearly defining the measurement window for cross-correlation calculations. Furthermore, when the fluid flow rate is extremely slow, the selected measurement window should be increased accordingly. For example... Figure 3 As shown, the adaptive window adjusts the length of the selected window by iteratively calculating cross-correlation. It judges the stability and correlation of the signal relationship based on the set loop conditions, and exits the loop calculation when the conditions are met. At this point, the position of the optimal peak in the cross-correlation results can be obtained, i.e., the time delay corresponding to the maximum cross-correlation value. The time delay corresponding to the peak is recorded, i.e., the transit time. .

[0032] S3. Calculate the target plant flow velocity using the final sampling point offset.

[0033] Using the final sampling point With sampling frequency The ratio of the two values ​​is used to calculate the transit time. This algorithm enables the velocity measurement system to adjust the measurement window for different flow velocities, obtain more accurate transit times, and thus calculate the constantly changing velocity.

[0034] use L and The ratio of the two values ​​is used to determine the plant flow velocity. V , will different m Substituting the values ​​into the calculation yields the cross-correlation function value, and the time corresponding to the peak of the function is the transit time. The fluid velocity can be determined by using the transit time and the distance between the sensors. V .

[0035] ; The cross-correlation is calculated iteratively, and the signal length is adjusted accordingly. When the fluid flow rate is extremely slow, the measurement window should be increased accordingly. The cross-correlation function of the two signals is calculated, and the position of the peak value in the cross-correlation result is found. That is, the time delay corresponding to the maximum cross-correlation value is calculated, and the time delay corresponding to the peak value is recorded, which is the transit time. Store the time delay value obtained after each cross-correlation calculation.

[0036] After measuring six time delays, calculate the standard deviation of the most recent six time delays. If the standard deviation of the most recent six time delays is less than 6, it indicates that the time delays between the signals tend to stabilize. Calculate the difference between the maximum and mean of the cross-correlation result. If the difference is greater than 1000, it indicates that the cross-correlation function has a significant peak, suggesting a strong correlation between the signals. Exit the loop calculation when the condition is met. After confirming the stability and correlation of the signals, exit the loop calculation; if the condition is not met, continue to increase the window length and recalculate the cross-correlation.

[0037] By identifying the maximum cross-correlation points corresponding to different measurement windows of varying lengths in plant sap flow velocity measurement, and using the time offset corresponding to these maximum points, the flow velocity corresponding to different measurement windows can be calculated. Furthermore, by observing the waveform delay and flow velocity error obtained from the cross-correlation calculation, the optimal measurement window for that flow velocity can be selected.

[0038] The following simulation experiments will verify the feasibility and accuracy of the algorithm. A set of simulation control experiments will be set up to illustrate the superiority of using this algorithm.

[0039] Control group Experiment 1: Simulation experiments were conducted without using the adaptive window algorithm.

[0040] A noisy signal is randomly generated using simulation software. The waveforms of its upstream and downstream signals after normalization are shown below. Figure 4 As shown in (a) the “Upstream and Downstream Signals” image, the blue solid line represents the upstream waveform, and the red solid line represents the downstream waveform with a time delay superimposed. Since this control group experiment does not perform iterative window optimization, the selected window length is fixed, and cross-correlation calculations are performed only within the fixed-length window. The resulting image is shown below. Figure 4As shown in image (b) "Cross-correlation Results", it is observed that there is no obvious peak in the cross-correlation results image. The cross-correlation result has two large peaks, while an effective cross-correlation calculation should yield a relatively obvious maximum peak, making it impossible to determine the corresponding transit time. This is because the measurement window length is improperly selected, being much smaller than the actual transit time of the signal.

[0041] Experiment 2 of Experimental Group: Simulation experiment using the adaptive window algorithm proposed in this invention.

[0042] Random signals generated using simulation software, such as Figure 5 As shown in (a) the “original signal” image, the upstream and downstream signal waveforms are as follows: Figure 5 As shown in image (b), "Upstream and Downstream Signals," the blue solid line represents the upstream waveform, and the red solid line represents the downstream waveform superimposed with a time delay. After signal normalization, as shown... Figure 6 The topmost “Upstream and Downstream Signals” image (a) shows the upstream waveform, where the blue solid line represents the upstream waveform and the red solid line represents the downstream waveform with a time delay superimposed.

[0043] The cross-correlation between upstream and downstream signals is calculated to find the time delay corresponding to the maximum correlation between the two signals. This experimental group uses an adaptive window algorithm for iterative optimization, which allows for dynamic adjustment of the selected window length until the optimal window length is found.

[0044] Each time a cross-correlation calculation is performed, the corresponding time delay value is recorded. The stability and correlation of the signal relationship are judged. When the judgment condition is met, the loop calculation is terminated, and the obtained window length is the optimal solution. Otherwise, the loop calculation continues, and the measurement window length is gradually increased until the following stopping conditions are met: the variance of the most recent 6 time delays is <6, indicating signal stability; the difference between the peak value and the mean of the cross-correlation is >1000, indicating signal correlation.

[0045] Figure 6 The image for (b) cross-correlation results shows the results of the cross-correlation calculation. Figure 6 The transit time variation image (c) records the change in delay time during the iteration process. The cross-correlation calculation result corresponds one-to-one with the delay time. Observing the two images together, it is found that the cross-correlation result has a significant maximum peak, indicating that the cross-correlation calculation result is effective and can be used to obtain the actual transit time of the signal. Locating the peak position of the cross-correlation result image at the position corresponding to the transit time variation image, it is found that the transit time also tends to a stable value at this time, indicating that the time delay is very close to the actual transit time of the signal. The experiment confirms the feasibility and reliability of using the adaptive window algorithm. Using this algorithm, the problem of the failure of conventional methods in measuring extremely slowly changing signals can be solved.

[0046] Through the above comparative experiments, the following conclusions were drawn: Without using the adaptive window algorithm proposed in this invention, conventional algorithms may fail in slow signal measurement, making it impossible to determine the optimal measurement window length. This results in the calculated cross-correlation result having multiple peak positions without a clear maximum peak, thus making it impossible to calculate the corresponding transit time. Using the adaptive window algorithm proposed in this invention, the measurement window length can be automatically adjusted. Calculating the cross-correlation under the optimal measurement window can produce a clear maximum peak, and the delay time corresponding to the peak position basically matches the actual transit time, thereby obtaining the time delay corresponding to the maximum cross-correlation value.

[0047] Based on the same inventive concept, the present invention also provides a system for measuring the flow rate of plant sap, comprising: The signal acquisition module is used to acquire signals within a preset time period. t Inside, the distance between the target plant branches and trunks was simultaneously collected. L upstream fluid flow signal x ( t ) and downstream fluid flow signal y ( t );Will x ( t )and y ( t Convert each to an initial window length of ) N upstream discrete sequence x ( k and downstream discrete sequences y ( k );set up y ( k Relative to x ( k The acquisition delay time is the offset of the number of sampling points. m And collect downstream discrete sequences under delay time. y ( k+m ); the m The range of values ​​is determined by N It is confirmed that the k This is the index of the sampling points after the fluid flow signal is discretized.

[0048] The window determination module is used to determine the window through traversal. m ,right x ( k )and y ( k+m Perform cross-correlation calculations to obtain a cross-correlation value array; calculate the mean of the current cross-correlation value array. and maximum value Record the above Corresponding maximum sampling point offset From the current Calculate the estimated crossing time of the target plant, and then calculate the standard deviation of the estimated crossing time. ;like , , When the preset conditions are not met, the window N Increment; and update the sampling point offset. m The range of values, calculate the updated m Corresponding , and ;like , and Stop when preset conditions are met. An incrementing loop; let's record the value at this point. Corresponding sampling point offset This represents the offset of the final number of sampling points.

[0049] The flow velocity calculation module is used to determine the flow velocity of the target plant using the offset of the final sampling point count.

[0050] This invention also provides a computer device, which, at the hardware level, includes a processor, an internal bus, a network interface, memory, and non-volatile memory, and may also include other hardware required for business operations. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to implement the above-mentioned method for measuring the flow rate of plant sap.

[0051] The present invention also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described method for measuring the flow rate of plant sap.

[0052] Specific limitations regarding the calculation system for measuring plant sap flow velocity can be found in the limitations section above, and will not be repeated here. Each module in the aforementioned plant sap flow velocity measurement system can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, allowing the processor to call and execute the corresponding operations of each module.

[0053] The technical features of the above embodiments can be combined arbitrarily. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as the combination of these technical features does not contradict each other, it should be considered within the scope of this specification. Furthermore, the above embodiments only illustrate several implementation methods of this application, and their descriptions are relatively specific and detailed, but they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

[0054] It should be noted that the specific embodiments described above enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although the present invention has been described in detail in this specification and embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the present invention; and all technical solutions and improvements that do not depart from the spirit and scope of the present invention are covered within the protection scope of the patent of the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. A method for measuring the flow rate of plant sap, characterized in that, The method includes: During the preset time period t Inside, the distance between the target plant branches and trunks was simultaneously collected. L upstream fluid flow signal x ( t ) and downstream fluid flow signal y ( t ); Will x ( t )and y ( t Convert each to an initial window length of ) N upstream discrete sequence x ( k and downstream discrete sequences y ( k );set up y ( k Relative to x ( k The acquisition delay time is the offset of the number of sampling points. m And collect downstream discrete sequences under delay time. y ( k+m ); the m The range of values ​​is determined by N It is confirmed that the k This is the index of the sampling points after discretization of the fluid flow signal; By traversal m ,right x ( k )and y ( k+m Perform cross-correlation calculations to obtain a cross-correlation value array; calculate the mean of the current cross-correlation value array. and maximum value Record the above Corresponding maximum sampling point offset From the current Calculate the estimated crossing time of the target plant, and then calculate the standard deviation of the estimated crossing time. ; like , and Window length when preset conditions are not met N Increment; and update the sampling point offset. m The range of values, calculate the updated m Corresponding , and ;like , and Stop when preset conditions are met. An incrementing loop; let's record the value at this point. Corresponding sampling point offset This is the offset of the final number of sampling points; The flow rate of the target plant sap is obtained by using the offset of the final sampling point number.

2. The method for measuring the flow rate of plant sap according to claim 1, characterized in that, The traversal m ,right x ( k )and y ( k+m Perform cross-correlation calculations to obtain an array of cross-correlation values. The expression for the cross-correlation calculation is as follows: ； In the formula, It is a cross-correlation function. m [- ].

3. The method for measuring the flow rate of plant sap according to claim 1, characterized in that, The method of determining the target plant sap flow velocity using the final sampling point offset includes: The upstream fluid flow signal x ( t ) and downstream fluid flow signal y ( t The sampling frequency is Using the final sampling point offset and sampling frequency The ratio is used to calculate the transit time; using L The target plant flow velocity is obtained by comparing the flow velocity with the transit time.

4. The method for measuring the flow rate of plant sap according to claim 1, characterized in that, If , and Stop when preset conditions are met. The incrementing loop includes: like Less than the preset standard deviation, and in the current loop and Stop when the difference is greater than the preset cross-correlation value. N An incrementing loop.

5. A system for measuring the flow rate of plant sap, characterized in that, include: The signal acquisition module is used to acquire signals within a preset time period. t Inside, the distance between the target plant branches and trunks was simultaneously collected. L upstream fluid flow signal x ( t ) and downstream fluid flow signal y ( t );Will x ( t )and y ( t Convert each to an initial window length of ) N upstream discrete sequence x ( k and downstream discrete sequences y ( k );set up y ( k Relative to x ( k The acquisition delay time is the offset of the number of sampling points. m And collect downstream discrete sequences under delay time. y ( k+m ); the m The range of values ​​is determined by N It is confirmed that the k This is the index of the sampling points after discretization of the fluid flow signal; The window determination module is used to determine the window through traversal. m ,right x ( k )and y ( k+m Perform cross-correlation calculations to obtain a cross-correlation value array; calculate the mean of the current cross-correlation value array. and maximum value Record the above Corresponding maximum sampling point offset From the current Calculate the estimated crossing time of the target plant, and then calculate the standard deviation of the estimated crossing time. ;like , and When the preset conditions are not met, the window N self-added; And update the sampling point offset. m The range of values, calculate the updated m Corresponding , and ;like , and Stop when preset conditions are met. An incrementing loop; let's record the value at this point. Corresponding sampling point offset This is the offset of the final number of sampling points; The flow velocity calculation module is used to determine the flow velocity of the target plant using the offset of the final sampling point count.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, When the processor executes the computer program, it implements the method of any one of claims 1 to 4.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1 to 4.

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