A plant sap flow rate measurement method, system, computer device and medium

Abstract

The application provides a plant liquid flow velocity measurement method, system, computer device and medium, and belongs to the field of liquid flow velocity detection in plant physiology. The method comprises the following steps: collecting upstream and downstream discrete sequences of target plant branch sap flow to construct a cross-correlation function; calculating a sampling point interval by using an initial window, substituting all sampling points into the cross-correlation function to calculate cross-correlation values, and counting a maximum value and a mean value; determining a 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 the mean value of the cross-correlation values until the stability and correlation constraint conditions are met; the method realizes adaptive adjustment of the window length, effectively solves the measurement problem caused by long signal delay time of plant liquid flow velocity, significantly improves the reliability and efficiency of plant liquid flow velocity measurement, and provides an effective technical means for plant physiological and ecological research.

Description

TECHNICAL FIELD

[0001] The application belongs to the field of liquid flow rate detection in plant physiology, and particularly relates to a plant liquid flow rate measurement method and system, a computer device and a medium. BACKGROUND

[0002] Measuring fluid flow rate can better analyze, apply and manage fluid. Flow rate not only describes the movement speed of fluid, but also is an important prerequisite for accurately measuring other parameters of fluid. Measuring the internal liquid flow of plants can effectively study the whole plant transpiration and the relationship between plants and water. Water is crucial to plant physiology and ecology. Plants continuously absorb water from the soil through their roots and transport it to various parts of the plant body to meet the needs of normal life activities. Measuring plant liquid flow rate is of great significance for further evaluating plant transpiration water consumption, studying water stress and exploring water utilization strategies.

[0003] Common flow rate measurement methods include differential pressure method, particle image method (PIV), ultrasonic Doppler method and cross-correlation method, etc. However, these methods are mainly used for measuring conventional flow rates above 1 cm / s. In actual application and scientific research, there are also fluids with plant liquid flow rates much lower than 1 cm / s, such as plant stem flow, gel electrophoresis, multi-medium permeation, micro-reactor, etc., which are mostly concentrated in the range of 0.01-0.5 mm / s. The internal liquid flow rate of plants is generally in the range of 0.02-0.05 mm / s, which is 2-3 orders of magnitude smaller than the flow rate measurement range of conventional methods. At this time, the conventional flow rate measurement method will fail.

[0004] In actual engineering measurement, it is often necessary to study the relationship between two signal variables, and the signals often change randomly or are disturbed, with uncertainty. Cross-correlation function is used to describe the similarity of two random signals and reflects the correlation information between them, which is helpful for calculation and analysis between signals.

[0005] At present, the cross-correlation time delay estimation method has been widely recognized in the application of flow rate measurement. By installing sensors on the upstream and downstream of the fluid, the change of the signal to be measured is converted into the change of the electric signal, which is sent to the cross-correlator for processing after a series of conversion such as amplification, filtering and A / D conversion circuit. The cross-correlation function of the signal is calculated, the peak value coordinate is extracted from the cross-correlation information in the measurement window, the transit time of the fluid from the upstream to the downstream is obtained, and the flow rate can be calculated by using the transit time combined with the distance between the upstream and downstream.

[0006] Compared with the traditional velocity measurement method, the cross-correlation velocity measurement has the following advantages: the traditional method needs to separate the components of each phase of the fluid to measure the velocity, and the cross-correlation method only needs to install sensors and data acquisition circuits upstream and downstream of the flow, which simplifies the equipment and operation; the correlation of the upstream and downstream signals is used for calculation, which avoids the influence of irrelevant noise; and the cross-correlation coefficient obtained by calculation can be used as an index for measuring the stability of the flow.

[0007] When the fluid flow rate is extremely slow, a long time interval (i.e. measurement window) is required for cross-correlation calculation to realize effective flow rate measurement, and the determination of the time interval depends on the flow rate and has a large variation range, so that a fixed measurement window cannot be used for measurement of different flow rates, and it is urgent to seek a new method to optimize and improve the traditional cross-correlation algorithm and solve the measurement problem of the plant liquid flow rate. SUMMARY

[0008] In order to solve the problem that the fixed window of the cross-correlation algorithm is invalid when calculating the flow rate of extremely slow fluid, the present application provides a plant liquid flow rate measurement method, system, computer device and medium, which can automatically select a suitable measurement window for different flow rates.

[0009] In order to achieve the above-mentioned purpose, the present application provides a plant liquid flow rate measurement method, comprising:

[0010] In a preset time period t , the upstream liquid flow signal L ( x ) and the downstream liquid flow signal t ( y ) are synchronously collected. t

[0011] The upstream discrete sequence x ( t ) and the downstream discrete sequence y ( t ) are converted into the upstream discrete sequence N ( x ) and the downstream discrete sequence k ( y ) with an initial window length k ; the collection delay time of y ( k ) relative to x ( k ) is set as a sampling point number offset m , and the downstream discrete sequence y ( k+m ) under the collection delay time is collected; the value range of m is determined by N , and k ​This is the index of the sampling points after the fluid flow signal is discretized.

[0012] 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. .

[0013] 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.

[0014] The flow rate of the target plant sap is obtained by using the offset of the final sampling point number.

[0015] 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:

[0016] ;

[0017] In the formula, It is a cross-correlation function. m [- ].

[0018] Preferably, the step of determining the target plant sap flow velocity using the final sampling point offset includes:

[0019] the upstream liquid flow signal x ( t ) and the downstream liquid flow signal y ( t ) is ; the ratio of the final sampling point offset and the sampling frequency is used to obtain the transit time; the ratio of L and the transit time is used to obtain the target plant flow rate.

[0020] Preferably, when the values of , and meet preset conditions, the self-adding cycle of is stopped, including:

[0021] If is less than a preset standard deviation, and the difference between and in the current cycle is greater than a preset cross-correlation value, the self-adding cycle of N is stopped.

[0022] The application further provides a plant liquid flow rate measuring system, including:

[0023] a signal collecting module, configured to synchronously collect the upstream liquid flow signal t ( L ) and the downstream liquid flow signal x ( t ) of the target plant branch at a distance of y in a preset time period; convert t ( x ) and t ( y ) into upstream discrete sequence t ( N ) and downstream discrete sequence x ( k ) with an initial window length of y ; set the collection delay time of k ( y ) relative to k ( x ) as the sampling point offset k , and collect the downstream discrete sequence m ( y ) under the collection delay time; the value range of k+m is determined by m , and N is the sampling point index after the liquid flow signal is discretized. k

[0024] a window determining module, configured to determine the window length by traversing​m , and x ( k ) and y ( k+m ) are correlated to obtain a correlation value array; the mean value and the maximum value of the current correlation value array are calculated ; the corresponding maximum sampling point offset is recorded ; the transit time estimation value of the target plant is calculated from the current , and the standard deviation of the transit time estimation value is calculated from the transit time estimation value , and do not meet the preset conditions, the window N is added; and the value range of the sampling point offset m is updated, and the m corresponding , and are calculated; if , and meet the preset conditions, the self-adding cycle of the window is stopped; and the sampling point offset corresponding to this time is recorded as the final sampling point offset .

[0025] The flow rate calculation module is used to obtain the target plant flow rate by using the final sampling point offset.

[0026] The application also provides a computer device, which comprises a memory, a processor and a computer program stored in the memory, and the processor executes the computer program to realize the steps of any one of the plant liquid flow rate measurement methods.

[0027] The application also provides a computer readable storage medium, which stores a computer program, and the computer program can execute the steps of any one of the plant liquid flow rate measurement methods when loaded by a processor.

[0028] The plant liquid flow rate measurement method provided by the application has the following advantages:

[0029] The adaptive optimal window searching method provided by the application is suitable for extremely slow fluid. The cyclic sampling point adding method provided by the application can dynamically and adaptively adjust the size and shape of the measurement window according to the characteristics of the measured object or the measurement requirements, and has significant advantages in improving the measurement accuracy and efficiency; the , 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

[0030] 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.

[0031] 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;

[0032] Figure 2 This is a schematic diagram illustrating the principle of cross-correlation velocity measurement according to an embodiment of the present invention.

[0033] Figure 3 This is a flowchart illustrating the implementation of the adaptive window in an embodiment of the present invention.

[0034] 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;

[0035] 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;

[0036] 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

[0037] 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.

[0038] This invention provides a method for measuring the flow rate of plant sap, specifically as follows: Figure 1 As shown, it includes:

[0039] 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.

[0040] 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 ).

[0041] 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.

[0042] Based on the upstream discrete sequence x ( k and downstream discrete sequences y ( k Construct a cross-correlation function, with the following expression:

[0043] ;

[0044] In the formula, For cross-correlation function, by N Determine the offset of the number of sampling points m The range of values ​​for , .

[0045] 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.

[0046] 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. .

[0047] S3, obtaining the target plant flow rate by using the final sampling point number offset.

[0048] obtaining the final sampling point number offset and the sampling frequency , and obtaining the transit time . The algorithm enables the velocity measurement system to adjust the measurement window for different flow rates, obtain more accurate transit time, and further calculate the constantly changing velocity.

[0049] obtaining the plant flow rate L by using the ratio of and V , substituting different values into the calculation to obtain the cross-correlation function value, and taking the time corresponding to the function peak value as the transit time m . The fluid flow rate can be obtained by using the transit time and the distance between the sensors. V

[0050] ;

[0051] The cross-correlation is calculated and the signal length is adjusted. In the case of extremely slow fluid flow rate, the measurement window should be increased accordingly. The cross-correlation function of the two signals is calculated, the position of the peak value in the cross-correlation result is found, the time delay corresponding to the maximum cross-correlation value is calculated, and the time delay corresponding to the peak value, i.e. the transit time, is recorded . The time delay value obtained after each cross-correlation calculation is stored.

[0052] After measuring 6 time delays, the standard deviation of the last 6 time delays is calculated. If the standard deviation of the last 6 time delays is less than 6, it indicates that the time delay between the signals tends to be stable. The difference between the maximum value and the average value of the cross-correlation result is calculated. If the difference is greater than 1000, it indicates that there is a significant peak in the cross-correlation function, indicating that the signals have strong correlation. When the conditions are met, the loop calculation is exited. After confirming the stability and correlation of the signals, the loop calculation is exited. If the conditions are not met, the window length is increased and the cross-correlation is recalculated.

[0053] By finding the maximum value point of the cross-correlation corresponding to different lengths of the measurement window in the plant sap flow rate measurement, the flow rate corresponding to different measurement windows can be calculated through the time offset corresponding to the maximum value point. By observing the waveform delay and flow rate error obtained by the cross-correlation calculation, the best measurement window under the flow rate can be selected.

[0054] The feasibility and accuracy of the algorithm are verified through simulation experiments. A set of simulation control experiments are set up to illustrate the superiority of using the algorithm.

[0055] ​Control group experiment one: simulation experiment without using adaptive window algorithm.

[0056] A signal containing noise is randomly generated by simulation software, and the normalized waveform of the upstream and downstream signals is shown in the (a) "upstream and downstream signals" image of Figure 4 , in which the blue solid line represents the upstream waveform, and the red solid line represents the downstream waveform superimposed with time delay. Since this control group experiment does not perform window cycle iteration optimization, the selected window length is fixed, and only cross-correlation calculation is performed under the fixed length window, and the result image is shown in the (b) "cross-correlation result" image of Figure 4 . Observation shows that there is no obvious peak value on the cross-correlation result image, and the cross-correlation result has two larger peak values, while effective cross-correlation calculation should obtain a relatively obvious maximum peak value, which cannot be used to calculate the corresponding transit time. This is because the measurement window length is not properly selected, which is much smaller than the actual transit time of the signal.

[0057] Experimental group experiment two: simulation experiment using the adaptive window algorithm proposed in the present application.

[0058] The random signal generated by the simulation software is shown in the (a) "original signal" image of Figure 5 , and the upstream and downstream signal waveforms are shown in the (b) "upstream and downstream signals" image of Figure 5 , in which the blue solid line represents the upstream waveform, and the red solid line represents the downstream waveform superimposed with time delay. After normalization processing of the signal, it is shown in the (a) uppermost "upstream and downstream signals" image of Figure 6 , in which the blue solid line represents the upstream waveform, and the red solid line represents the downstream waveform superimposed with time delay.

[0059] The cross-correlation of the upstream and downstream signals is calculated to find the delay time corresponding to the maximum correlation of the two signals. This experimental group experiment uses the adaptive window algorithm for cycle iteration optimization, so that the selected window length can be dynamically adjusted until the optimal window length is found.

[0060] Each cross-correlation calculation records the time delay value corresponding to the cross-correlation result value. The stability and correlation of the signal are judged, and the cycle calculation is exited when the judgment condition is met, at which time the obtained window length is the optimal solution. Otherwise, the cycle calculation is continued, and the length of the measurement window is gradually increased until the following stopping conditions are met: the variance of the last 6 time delays <6, the signal has stability; the difference between the cross-correlation peak value and the average value >1000, the signal has correlation.

[0061] Figure 6 The (b) cross-correlation result image shows the cross-correlation calculation result, Figure 6The (c) transit time variation image records the variation of the delay time in the iteration process. The result value of the cross-correlation calculation corresponds to the delay time. It is found that there is a clear maximum peak value in the cross-correlation result by observing the two images, which indicates that the cross-correlation calculation result is effective, and the actual transit time of the signal can be obtained by using the maximum peak value result. The position of the peak value of the cross-correlation result image is found in the position corresponding to the transit time variation image, and it is found that the transit time also tends to a stable value at this time, which indicates that the time delay is very close to the actual transit time of the signal. The experiment proves the feasibility and reliability of using the adaptive window algorithm, and using the algorithm can solve the problem of the failure of the conventional method in the measurement of extremely slow signals.

[0062] Through the above contrast experiment, the following conclusions are finally drawn: without using the adaptive window algorithm proposed in the application, the problem of failure of the conventional algorithm in the measurement of slow signals may be faced, the optimal measurement window length cannot be known, the calculated cross-correlation result may have multiple peak positions without a clear maximum peak value, and the corresponding transit time cannot be calculated; using the adaptive window algorithm proposed in the application, the measurement window length can be automatically adjusted, the cross-correlation can be calculated under the optimal measurement window to produce a clear maximum peak value, the delay time corresponding to the peak position is basically consistent with the actual transit time, and the time delay corresponding to the maximum cross-correlation value is obtained.

[0063] Based on the same inventive concept, the application further provides a plant liquid flow velocity measurement system, comprising:

[0064] A signal acquisition module is configured to synchronously acquire upstream liquid flow signals t and downstream liquid flow signals L with a distance of x ( t ) between the target plant branches in a preset time period. y ( t ) and x ( t ) are converted into upstream discrete sequences y ( t ) and downstream discrete sequences N ( x ) with an initial window length of k . y ( k ) is set as a sampling point number offset y ( k ) relative to the acquisition delay time of x ( k ), and the downstream discrete sequence m ( y ) under the acquisition delay time is acquired. k+m ( m ) is in the range ofN It is confirmed that the k This is the index of the sampling points after the fluid flow signal is discretized.

[0065] 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.

[0066] 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.

[0067] 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.

[0068] 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.

[0069] The specific limitations of the plant sap flow rate measurement method calculation system can refer to the limitations of the plant sap flow rate measurement method described above, which will not be repeated here. Each module in the above plant sap flow rate measurement system can be implemented by software, hardware and their combinations. The above modules can be embedded in or independent of the processor in the computer device in hardware form, or stored in the memory of the computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0070] The technical features of the above embodiments can be combined in any way. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, but as long as the combinations of the technical features do not exist contradictions, they should be considered as the scope of the present disclosure. In addition, the above-described embodiments only express several embodiments of the present application, and the description is more specific and detailed, but it should not be interpreted as limiting the scope of the patent. It should be noted that for those skilled in the art, without departing from the concept of the present application, some modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of the patent protection of the present application should be subject to the appended claims.

[0071] It should be noted that the above specific embodiments can enable those skilled in the art to have a more comprehensive understanding of the present application, but in no way limit the present application. Therefore, although the present application has been described in detail in the specification and examples, those skilled in the art should understand that the present application can still be modified or replaced by equivalents; all technical solutions and improvements that do not deviate from the spirit and scope of the present application are covered within the scope of the patent protection of the present application. Any reference signs in the claims should not be considered as limiting the claims.

Claims

1. A method of measuring plant sap flow velocity, characterized by, The method comprises: In a preset time period t , the target plant branches are synchronously collected with a distance of L between the upstream and downstream sap flow signals x ( t ) and 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. ; If , and do not meet the preset condition, the window length N is increased by one; and the value range of the sampling point offset m is updated, the updated m corresponding , and are calculated; if , and meet the preset condition, the increasing cycle of the window length is stopped; the sampling point offset corresponding to this time is recorded as the final sampling point offset . The target plant sap flow rate is obtained by using the final sampling point number offset.

2. The method of claim 1, wherein, 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: ； wherein is the cross-correlation function, m [- ].

3. The method of claim 1, wherein the plant sap flow rate is measured by the method comprising: The target plant sap flow rate is obtained by using the final sampling point number offset. The upstream flow signal x ( t ) and the downstream flow signal y ( t ) have a sampling frequency of ; the ratio of the final sampling point offset and the sampling frequency is used to obtain the transit time; the ratio of L and the transit time is used to obtain the target plant flow rate.

4. The method of claim 1, wherein, The if , and satisfies the preset condition, stop the self-adding cycle, comprising: 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 a plant sap, characterized by, It comprises: 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 has been discretized; 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 number offset m , calculate the updated m corresponding to the value range of , and ; if , and meet the preset condition, stop self-addition cycle; record the corresponding sampling point number offset at this time as the final sampling point number offset The flow rate calculation module is configured to obtain the target plant sap flow rate by using the final sampling point number offset.

6. A computer device comprising a memory, a processor, and a computer program stored on the memory, wherein the computer program comprises instructions that, when executed by the processor, cause the processor to perform the method of any one of claims 1-5. The processor executes the computer program to implement the method in any one of claims 1 to 4.

7. A computer readable storage medium storing a computer program, wherein the computer program comprises program instructions configured to cause a processor to perform the method according to any one of claims 1 to 6. The computer program is executed by the processor to implement the method in any one of claims 1 to 4.

Images