Method, device, electronic device and storage medium for generating pump characteristic curve

Abstract

The present invention discloses a method, device, electronic device and storage medium for generating a characteristic curve of a water pump. Among them, the method includes: obtaining multiple sets of water pump operation data of a water pump to be tested at multiple different vane angles; determining a reference characteristic function according to multiple sets of water pump operation data corresponding to a target vane angle among the multiple vane angles; for at least one other vane angle among the multiple vane angles except the target vane angle, determining a characteristic function corresponding to the other vane angle according to a pre-determined target transformation parameter corresponding to the other vane angle and the reference characteristic function; determining a pump characteristic curve corresponding to the water pump to be tested according to the reference characteristic function and at least one characteristic function. This technical solution achieves the effect of generating smooth characteristic curves corresponding to different vane angles that conform to physical laws when the amount of water pump operation data corresponding to different vane angles is small.

Description

Technical Field

[0001] The present invention relates to the technical field of water pump performance detection, and particularly to a method, device, electronic device and storage medium for generating a water pump characteristic curve. Background Art

[0002] Currently, large water pumps are widely used in industries, agriculture and municipal engineering. The performance of water pumps directly affects the operation efficiency of the system. Especially in water pumps with adjustable vane angles, the change of vane angles has a significant impact on the flow-head or flow-mechanical efficiency characteristic curves.

[0003] In related technologies, the performance analysis of water pumps mainly relies on experimental data for curve fitting. However, for water pumps with adjustable vane angles, it is difficult to collect experimental data during their operation, and the amount of experimental data obtained is small. Using the existing interpolation fitting method is likely to result in large fitting errors, and even generate curves that do not conform to physical laws, thereby leading to a low accuracy rate of water pump performance evaluation and affecting the optimization and application of water pumps. Summary of the Invention

[0004] The present invention provides a method, device, electronic device and storage medium for generating a water pump characteristic curve, so as to achieve the effect of generating smooth characteristic curves corresponding to different vane angles that conform to physical laws under the condition of a small amount of water pump operation data corresponding to different vane angles.

[0005] According to one aspect of the present invention, a method for generating a water pump characteristic curve is provided, and the method includes:

[0006] Obtain multiple sets of water pump operation data of a to-be-detected water pump at multiple different vane angles; wherein, the water pump operation data is used to indicate the data generated during the operation of the to-be-detected water pump at the corresponding vane angle; the multiple sets of water pump operation data include different water pump flows and water pump performance data corresponding to the water pump flows; the amount of data of each set of water pump operation data at each vane angle is less than a preset data amount threshold;

[0007] Determine a reference characteristic function according to multiple sets of the water pump operation data corresponding to a target vane angle among the multiple vane angles;

[0008] For at least one other vane angle among the multiple vane angles except the target vane angle, determine a characteristic function corresponding to the other vane angle according to a pre-determined target transformation parameter corresponding to the other vane angle and the reference characteristic function; wherein, the target transformation parameter is determined based on multiple sets of the water pump operation data corresponding to the other vane angle;

[0009] Determine the pump characteristic curve corresponding to the water pump to be measured according to the reference characteristic function and at least one of the characteristic functions.

[0010] According to another aspect of the present invention, there is provided a device for generating a water pump characteristic curve, the device comprising:

[0011] A data acquisition module, configured to acquire multiple sets of water pump operation data of the water pump to be measured at multiple different blade angles; wherein, the water pump operation data is used to indicate the data generated during the operation of the water pump to be measured at the corresponding blade angle; the multiple sets of water pump operation data include different water pump flows and water pump performance data corresponding to the water pump flows; the data volume of the multiple sets of water pump operation data at each blade angle is less than a preset data volume threshold;

[0012] A reference function determination module, configured to determine a reference characteristic function according to multiple sets of the water pump operation data corresponding to the target blade angle among the multiple blade angles;

[0013] A characteristic function determination module, configured to, for at least one other blade angle among the multiple blade angles except the target blade angle, determine a characteristic function corresponding to the other blade angle according to a pre-determined target transformation parameter corresponding to the other blade angle and the reference characteristic function; wherein, the target transformation parameter is determined based on multiple sets of the water pump operation data corresponding to the other blade angle;

[0014] A curve generation module, configured to determine the pump characteristic curve corresponding to the water pump to be measured according to the reference characteristic function and at least one of the characteristic functions.

[0015] According to another aspect of the present invention, there is provided an electronic device, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program executable by the at least one processor, and when the computer program is executed by the at least one processor, the at least one processor is enabled to execute the water pump characteristic curve generation method according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, there is provided a computer-readable storage medium, the computer-readable storage medium storing computer instructions, and when the computer instructions are executed by a processor, the water pump characteristic curve generation method according to any embodiment of the present invention is implemented.

[0020] The technical solution of the embodiment of the present invention obtains multiple groups of pump operation data of the pump to be measured at multiple different blade angles. Further, according to the multiple groups of pump operation data corresponding to the target blade angle among the multiple blade angles, a reference characteristic function is determined. Further, for at least one other blade angle among the multiple blade angles except the target blade angle, according to the pre-determined target transformation parameter corresponding to the other blade angle and the reference characteristic function, a characteristic function corresponding to the other blade angle is determined. Further, according to the reference characteristic function and at least one pump characteristic function, a pump characteristic curve corresponding to the pump to be measured is determined, which solves the problem that the characteristic curve generation method in the related art is likely to cause a large fitting error and even generate a curve that does not conform to the physical law. It realizes the effect of generating smooth characteristic curves corresponding to different blade angles that conform to the physical law under the condition of a small amount of pump operation data corresponding to different blade angles, improves the accuracy of curve fitting, and further improves the accuracy of pump performance analysis.

[0021] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present invention, nor is it used to limit the scope of the present invention. Other features of the present invention will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0023] Figure 1 is a flowchart of a method for generating a pump characteristic curve according to Embodiment 1 of the present invention;

[0024] Figure 2 is a flowchart of a method for generating a pump characteristic curve according to Embodiment 2 of the present invention;

[0025] Figure 3 is a schematic structural diagram of a device for generating a pump characteristic curve according to Embodiment 3 of the present invention;

[0026] Figure 4 is a schematic structural diagram of an electronic device for implementing the method for generating a pump characteristic curve of the embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] To enable those skilled in the art to better understand the solution of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0028] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged under appropriate circumstances so that the embodiments of the present invention described here can be implemented in an order different from those illustrated or described here. In addition, the terms "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0029] Embodiment 1

[0030] Figure 1 is a flowchart of a method for generating a pump characteristic curve provided in Embodiment 1 of the present invention. This embodiment is applicable to the situation of performing performance analysis on a pump with adjustable vane angles. This method can be executed by a pump characteristic curve generation device, which can be implemented in the form of hardware and / or software, and the pump characteristic curve generation device can be configured in a terminal and / or a server. As Figure 1 shown, the method includes:

[0031] S110. Obtain multiple sets of pump operation data of the pump to be tested at multiple vane angles.

[0032] Among them, the water pump to be tested can be a water pump to be subjected to performance testing. The water pump to be tested can be any type of water pump. Optionally, it is a large adjustable vane angle water pump. It can be understood that the vane angle can be the included angle between the vane and the axis of the water pump, also known as the vane installation angle or vane inclination angle. The water pump operation data can be used to indicate the data generated during the operation of the water pump to be tested at the corresponding vane angle. The water pump operation data can include multiple data associated with the operation performance of the water pump. In this embodiment, multiple sets of water pump operation data can include different water pump flows and the corresponding water pump performance data. In other words, multiple sets of water pump operation data can be data constructed by sampling the water pump performance data corresponding to multiple water pump flows. The water pump flow refers to the amount of liquid (liquid volume or liquid weight) delivered by the water pump per unit time. The water pump performance data can be understood as important parameters characterizing the performance of the water pump. Optionally, the water pump performance data includes the water pump head and / or the water pump mechanical efficiency. The water pump head refers to the height that the water pump can lift water, and its unit is meters (m). The water pump mechanical efficiency refers to the efficiency that the water pump can convert during operation. Generally, when the vane angle is determined, the water pump to be tested can operate at this vane angle. Further, the water pump flow and the water pump performance data generated during the operation of the water pump to be tested can be detected, and the water pump flow and the water pump performance data can be collected to obtain the water pump performance data corresponding to multiple different water pump flows. Furthermore, the collected data can be used as multiple sets of water pump operation data corresponding to the water pump to be tested at this vane angle, and each set of water pump operation data includes a water pump flow and the corresponding water pump performance data. It should be noted that multiple sets of water pump operation data corresponding to each vane angle can include key data points within the working range of the water pump to be tested. For example, the maximum water pump flow, the maximum water pump head, and / or the maximum water pump mechanical efficiency, etc.

[0033] It should be noted that in this embodiment, the data volume of multiple sets of water pump operation data at each vane angle can be less than a preset data volume threshold. Furthermore, the water pump performance of the water pump to be tested can be analyzed based on the water pump operation data less than the preset data volume threshold. The preset data volume threshold can be any value. Optionally, it is 5 sets, 6 sets, 8 sets, or 10 sets, etc.

[0034] In this embodiment, multiple different blade angles can be determined. Further, for each blade angle, the blades in the impeller of the water pump to be tested can be set based on this blade angle, and the water pump to be tested can be controlled to operate at this blade angle. Further, during the operation of the water pump to be tested, the water pump flow rate and the water pump performance data are detected, and data collection is performed on the water pump flow rate and the corresponding water pump performance data at the corresponding water pump flow rate. Furthermore, the collected data can be used as multiple sets of water pump operation data corresponding to the water pump to be tested at this blade angle. Further, when the water pump to be tested operates at each blade angle respectively, multiple sets of water pump operation data corresponding to the water pump to be tested at multiple different blade angles can be obtained.

[0035] Exemplarily, for multiple blade angles, 8 water pump flow rates of the water pump to be tested at this blade angle and the corresponding water pump performance data for each water pump flow rate can be collected. Furthermore, the water pump flow rate and its corresponding water pump performance data can be used as a set of water pump operation data, and 8 sets of water pump operation data corresponding to the water pump to be tested at this blade angle can be obtained.

[0036] S120. Determine a reference characteristic function according to multiple sets of water pump operation data corresponding to the target blade angle among multiple blade angles.

[0037] Among them, the target blade angle is one of the multiple blade angles. The reference characteristic function can be a pump characteristic function determined based on multiple sets of water pump operation data corresponding to the target blade angle. It can be understood that the pump characteristic function is used to describe the functional relationship between important performance parameter values such as the head, power, efficiency, and flow rate of the pump when it operates at a certain rotational speed. Usually, the independent variable represents the water pump flow rate, and the dependent variable can represent the water pump head, the water pump mechanical efficiency, or the water pump shaft power, etc. In this embodiment, the reference characteristic function can include a flow-head function and / or a flow-efficiency function, that is, it reflects the functional relationship between the water pump flow rate and the water pump head; and / or, it reflects the functional relationship between the water pump flow rate and the water pump mechanical efficiency.

[0038] In this embodiment, when multiple sets of water pump operation data corresponding to the water pump to be tested at multiple blade angles are obtained, the target blade angle can be determined from multiple blade angles. Further, a reference characteristic function can be generated according to multiple sets of water pump operation data corresponding to the target blade angle.

[0039] Optionally, determining a reference characteristic curve according to multiple sets of water pump operation data corresponding to the target blade angle among multiple blade angles includes: randomly determining a blade angle from multiple blade angles as the target blade angle; processing multiple sets of water pump operation data corresponding to the target blade angle according to a preset spline interpolation method to obtain a reference characteristic function.

[0040] Among them, the spline interpolation method is a mathematical method used to construct a smooth curve through a series of points, and it is a way to construct a smooth curve passing through a series of points with variable splines. The spline interpolation method can include various spline interpolation types. Optionally, it includes linear spline interpolation method, quadratic spline interpolation method, cubic spline interpolation method, etc. In this embodiment, the cubic spline interpolation method can be used to determine the reference characteristic function. It can be understood that the cubic spline interpolation method uses a cubic polynomial as the spline function for interpolation. The cubic spline interpolation method can ensure that the function curve is both continuous and smooth at the connection points.

[0041] As an optional implementation manner of this embodiment, in the case of obtaining multiple sets of pump operation data corresponding to a water pump to be measured at multiple vane angles, a vane angle can be randomly determined from the multiple vane angles, and this vane angle is used as the target vane angle. Further, interpolation fitting processing is performed on the multiple sets of pump operation data corresponding to the target vane angle according to the preset cubic spline interpolation method to obtain a fitting function, and this fitting function is used as the reference characteristic function.

[0042] It should be noted that the determination method of the target vane angle can also be other methods. For example, the multiple sets of pump operation data corresponding to each vane angle are analyzed respectively, and the target vane angle is determined from the multiple vane angles according to the data analysis results. This embodiment does not make specific limitations on this.

[0043] S130. For at least one other vane angle among the multiple vane angles except the target vane angle, determine the characteristic function corresponding to the other vane angle according to the pre-determined target transformation parameter corresponding to the other vane angle and the reference characteristic function.

[0044] Among them, the other vane angle is the vane angle among the multiple vane angles except the target vane angle. The target transformation parameter can be understood as a parameter that can perform transformation processing on the function to change the position and / or shape of the function curve. Optionally, the target transformation parameter can at least include a translation parameter and a scaling parameter. The translation parameter can be used to perform translation processing on the function curve to change the position of the function curve. The scaling parameter can be used to perform scaling processing on the function curve to change the shape of the function curve. In this embodiment, for the other vane angles among the multiple vane angles except the target vane angle, the target transformation parameter corresponding to the other vane angle can be determined based on the multiple sets of pump operation data corresponding to the other vane angle and the reference characteristic function.

[0045] In practical applications, when the amount of data of multiple groups of pump operation data corresponding to multiple different blade angles of the pump to be measured is small, if multiple groups of pump operation data are respectively subjected to fitting interpolation based on conventional fitting interpolation methods to generate multiple characteristic curves, there may be a situation where curves that do not conform to physical laws (such as multiple curves crossing or discontinuous points appearing) are generated.

[0046] In view of the above situation, in this embodiment, for other blade angles except the target blade angle among multiple blade angles, the target transformation parameters corresponding to other blade angles can be determined according to those corresponding to other blade angles. Further, the reference characteristic curve and multiple groups of pump operation data corresponding to this other blade angle can be processed according to the determined target transformation parameters to obtain a characteristic function corresponding to this blade angle. The advantage of such a setting is that it can ensure that the characteristic curves of the pump to be measured at different blade angles do not cross, so that the finally generated pump characteristic curve is a smooth curve that conforms to physical laws, improving the accuracy of curve fitting. Furthermore, the accuracy of pump performance analysis is improved.

[0047] Optionally, determining the characteristic function corresponding to other blade angles according to the pre-determined target transformation parameters and reference characteristic function corresponding to other blade angles includes: performing a translation process on the reference characteristic function according to the translation parameter to obtain a characteristic function to be processed; performing a scaling process on the characteristic function to be processed according to the scaling parameter to obtain a characteristic function corresponding to other blade angles.

[0048] As an optional implementation manner of this embodiment, when the target transformation parameters corresponding to other blade angles are determined, the reference characteristic function can be translated according to the translation parameter in the target transformation parameters to obtain a translated reference characteristic function, and the translated reference characteristic function is used as the characteristic function to be processed. Further, the characteristic function to be processed can be scaled according to the scaling parameter in the target transformation parameters to obtain a scaled characteristic function to be processed, and the scaled characteristic function to be processed is used as the characteristic function corresponding to other blade angles.

[0049] Exemplarily, the determination method of the characteristic function can be expressed based on the following formula:

[0050] y2(x) = b · y1(x - a)

[0051] Where, y2(x) represents the characteristic function; b represents the scaling parameter; y1(x) represents the reference characteristic function; a represents the translation parameter; x represents the pump flow rate; y1 and y2 represent pump performance data.

[0052] S140. Determine the pump characteristic curve corresponding to the pump to be measured according to the reference characteristic function and at least one characteristic function.

[0053] In this embodiment, when the reference characteristic function corresponding to the target blade angle and the characteristic functions corresponding to other blade angles are obtained, the pump characteristic curve corresponding to the water pump to be measured can be determined according to the reference characteristic function and each characteristic function.

[0054] Optionally, determining the pump characteristic curve corresponding to the water pump to be measured according to the reference characteristic function and at least one characteristic function includes: generating a reference characteristic curve according to the reference characteristic function; and generating characteristic curves according to each characteristic function; using the reference characteristic curve and at least one characteristic curve as the pump characteristic curve corresponding to the water pump to be measured.

[0055] As an optional implementation manner of this embodiment, a curve can be generated according to the reference characteristic function and used as the reference characteristic curve. And for the characteristic functions corresponding to other blade angles, a curve can be generated according to the characteristic functions corresponding to other blade angles and used as the characteristic curve corresponding to the other blade angle. Further, the reference characteristic curve and the characteristic curves corresponding to other blade angles can be used as the pump characteristic curve corresponding to the water pump to be measured.

[0056] In this embodiment, in order to more clearly and intuitively analyze the performance of the water pump to be measured based on the pump characteristic curve, this embodiment further includes: generating a pump characteristic analysis diagram based on the pump characteristic curve and visually displaying the pump characteristic analysis diagram.

[0057] Among them, the pump characteristic analysis diagram can be understood as a schematic diagram for reflecting the change trend of the water pump performance of the water pump to be measured. Optionally, the pump characteristic analysis diagram can be a line chart, a bar chart or a pie chart, etc.

[0058] As an optional implementation manner of this embodiment, when the pump characteristic curve corresponding to the water pump to be measured is obtained, a pump characteristic analysis diagram corresponding to the water pump to be measured can be generated according to the pump characteristic curve and visually displayed, so that relevant staff can understand the change trend of the water pump performance of the water pump to be measured according to the pump characteristic analysis diagram, in order to timely discover potential problems in the water pump to be measured and ensure that the water pump to be measured always maintains the best working state.

[0059] In the technical solution of the embodiment of the present invention, by obtaining multiple sets of pump operation data of the pump to be measured at multiple different blade angles, further, according to the multiple sets of pump operation data corresponding to the target blade angle among the multiple blade angles, a reference characteristic function is determined. Further, for at least one other blade angle among the multiple blade angles except the target blade angle, according to the pre-determined target transformation parameter corresponding to the other blade angle and the reference characteristic function, a characteristic function corresponding to the other blade angle is determined. Further, according to the reference characteristic function and at least one pump characteristic function, a pump characteristic curve corresponding to the pump to be measured is determined, which solves the problem that the characteristic curve generation method in the related art is prone to large fitting errors and even generates curves that do not conform to physical laws. The effect of generating smooth characteristic curves corresponding to different blade angles that conform to physical laws is achieved under the condition of a small amount of pump operation data corresponding to different blade angles, the accuracy of curve fitting is improved, and further, the accuracy of pump performance analysis is improved.

[0060] Embodiment 2

[0061] Figure 2 FIG. is a flowchart of a method for generating a pump characteristic curve provided by Embodiment 2 of the present invention. On the basis of the foregoing embodiment, the target transformation parameter corresponding to the other blade angle can be determined according to the multiple sets of pump operation data corresponding to the other blade angle and the reference characteristic function, so as to determine the characteristic function corresponding to the other blade angle based on the target transformation parameter. The specific implementation manner thereof can refer to the technical solution of this embodiment. Among them, the same or similar technical terms as those in the above embodiment will not be specifically described herein.

[0062] As Figure 2 shown, the method includes:

[0063] S210. Obtain multiple sets of pump operation data of the pump to be measured at multiple different blade angles.

[0064] S220. Determine a reference characteristic function according to the multiple sets of pump operation data corresponding to the target blade angle among the multiple blade angles.

[0065] S230. For at least one other blade angle among the multiple blade angles except the target blade angle, determine the parameter to be optimized corresponding to the other blade angle.

[0066] Among them, the parameter to be optimized can be understood as a transformation parameter to be optimized for parameter optimization. Optionally, the parameter to be optimized includes a translation parameter and a scaling parameter. It should be noted that before iterative update, the parameter value of the parameter to be optimized can be an initial value or a default value, and the parameter value of the parameter to be optimized can be set manually or randomly selected. Optionally, the parameter value of the parameter to be optimized can be 0 or any other value.

[0067] S240 iteratively updates the parameters to be optimized based on the gradient descent algorithm and a preset loss function, so as to determine the target transformation parameters corresponding to other blade angles when the loss function reaches the preset convergence condition.

[0068] Among them, the gradient descent algorithm is an algorithm for optimization and finding the minimum value of a function. The gradient descent algorithm adjusts the parameter values iteratively, making the value of the objective function (loss function or cost function) gradually decrease until finally reaching a local minimum. In this embodiment, the loss function is constructed based on multiple sets of pump operation data corresponding to other blade angles and a benchmark characteristic function. The loss function can be used to measure the difference or error between the output obtained based on the benchmark characteristic function and the pump performance data in multiple sets of pump operation data. The loss function can be any loss function, and optionally, it is a mean squared error function. The preset convergence condition can include that the function value of the loss function is less than a preset error value, the change trend of the function value tends to be stable, or the number of iterative updates reaches a preset number threshold, etc.

[0069] Exemplarily, the loss function can be expressed based on the following formula:

[0070]

[0071] where i represents the number of groups of pump operation data; x i represents the pump flow rate in the i-th group of pump operation data; y i represents the pump performance data in the i-th group of pump operation data; b0 represents the scaling parameter to be optimized; y1 represents the dependent variable value of the benchmark characteristic function when the independent variable is x i ; a0 represents the translation parameter to be optimized.

[0072] In this embodiment, when determining the parameters to be optimized corresponding to other blade angles, a loss function can be constructed according to the benchmark characteristic function and multiple sets of pump operation data corresponding to other blade angles. Further, the parameters to be optimized can be iteratively updated according to the gradient descent algorithm and the pre-constructed loss function. Furthermore, when the loss function reaches the preset convergence condition, the target transformation parameters corresponding to other blade angles are determined.

[0073] Optionally, the parameters to be optimized are iteratively updated according to the gradient descent algorithm and a preset loss function, so as to determine the target transformation parameters corresponding to other blade angles when the loss function reaches the preset convergence condition, including: for multiple iteration processes, determining the partial derivative of the loss function corresponding to the current iteration process with respect to the parameters to be optimized corresponding to the current iteration process, so as to obtain the gradient corresponding to the current iteration process; updating the parameters to be optimized corresponding to the current iteration process according to the gradient, so as to obtain the parameters to be optimized corresponding to the next iteration update process, and determining the loss function corresponding to the next iteration process according to the parameters to be optimized corresponding to the next iteration process, the benchmark characteristic function, and multiple groups of pump operation data; in the case that it is determined that the loss function corresponding to the next iteration process does not meet the preset convergence condition, taking the next iteration process as the current iteration process, and repeating the steps of determining the gradient and updating the parameters until the loss function corresponding to the next iteration process meets the preset convergence condition, and taking the parameters to be optimized corresponding to the next iteration process as the target transformation parameters corresponding to other blade angles.

[0074] As an optional implementation manner of this Embodiment 1, for multiple iteration processes, the parameters to be optimized corresponding to the current iteration process can be obtained, and the parameters to be optimized are input into the loss function to obtain the loss function corresponding to the current iteration process. Further, the partial derivative of the loss function with respect to the parameters to be optimized can be determined to obtain the gradient corresponding to the current iteration process. Further, the product between the gradient and the preset learning rate can be determined, and the difference between the parameters to be optimized corresponding to the current iteration process and the product can be determined, and the difference is used as the parameters to be optimized corresponding to the next iteration process. Further, the parameters to be optimized in the loss function corresponding to the current iteration process can be replaced based on the parameters to be optimized corresponding to the next iteration process, and the loss function after the parameter replacement is used as the loss function corresponding to the next iteration process. Further, it is determined whether the loss function corresponding to the next iteration process meets the preset convergence condition. Furthermore, in the case that it is determined that the loss function corresponding to the next iteration process does not meet the preset convergence condition, taking the next iteration process as the current iteration process, and repeating the steps of determining the gradient and updating the parameters until the loss function corresponding to the next iteration process meets the preset convergence condition, and taking the parameters to be optimized corresponding to the next iteration process as the target transformation parameters corresponding to other blade angles.

[0075] Exemplarily, the process of taking the partial derivative of the parameters to be optimized can be expressed based on the following formula:

[0076]

[0077] where represents the gradient corresponding to the translation parameter; represents the gradient corresponding to the scaling parameter.

[0078] The update process of the parameter to be optimized can be expressed based on the following formula:

[0079]

[0080] where a new represents the updated translation parameter; α represents a preset learning rate; a old represents the translation parameter before update; b new represents the updated scaling parameter; b old represents the scaling parameter before update.

[0081] S250. For at least one other blade angle among multiple blade angles except the target blade angle, according to the target transformation parameter and the reference characteristic function corresponding to the other blade angle determined in advance, determine the characteristic function corresponding to the other blade angle.

[0082] S260. According to the reference characteristic function and at least one characteristic function, determine the pump characteristic curve corresponding to the water pump to be measured.

[0083] The technical solution of the embodiment of the present invention, by determining the parameter to be optimized corresponding to at least one other blade angle among multiple blade angles except the target blade angle; further, iteratively updating the parameter to be optimized according to the gradient descent algorithm and the preset loss function, to determine the target transformation parameter corresponding to the other blade angle when the loss function reaches the preset convergence condition, realizes the effect of quickly determining the target transformation parameter corresponding to each blade angle, and further improves the generation efficiency and generation effect of the pump characteristic curve.

[0084] Embodiment III

[0085] Figure 3 is a schematic structural diagram of a pump characteristic curve generation device provided in Embodiment III of the present invention. As Figure 3 shown, the device includes: a data acquisition module 310, a reference function determination module 320, a characteristic function determination module 330, and a curve generation module 340.

[0086] Among them, the data acquisition module 310 is configured to acquire multiple sets of pump operation data of the pump to be measured at multiple different blade angles. Among them, the pump operation data is used to indicate the data generated during the operation of the pump to be measured at the corresponding blade angle. The multiple sets of pump operation data include different pump flows and pump performance data corresponding to the pump flows. The data volume of the multiple sets of pump operation data at each blade angle is less than a preset data volume threshold. The reference function determination module 320 is configured to determine a reference characteristic function according to the multiple sets of pump operation data corresponding to the target blade angle among the multiple blade angles. The characteristic function determination module 330 is configured to, for at least one other blade angle among the multiple blade angles except the target blade angle, determine a characteristic function corresponding to the other blade angle according to a pre-determined target transformation parameter corresponding to the other blade angle and the reference characteristic function. Among them, the target transformation parameter is determined based on the multiple sets of pump operation data corresponding to the other blade angle. The curve generation module 340 is configured to determine a pump characteristic curve corresponding to the pump to be measured according to the reference characteristic function and at least one of the characteristic functions.

[0087] The technical solution of the embodiment of the present invention solves the problem that the characteristic curve generation method in the related art is prone to large fitting errors and even generates curves that do not conform to physical laws by acquiring multiple sets of pump operation data of the pump to be measured at multiple different blade angles. Further, a reference characteristic function is determined according to the multiple sets of pump operation data corresponding to the target blade angle among the multiple blade angles. Further, for at least one other blade angle among the multiple blade angles except the target blade angle, a characteristic function corresponding to the other blade angle is determined according to a pre-determined target transformation parameter corresponding to the other blade angle and the reference characteristic function. Further, a pump characteristic curve corresponding to the pump to be measured is determined according to the reference characteristic function and at least one pump characteristic function. The effect of generating smooth characteristic curves corresponding to different blade angles that conform to physical laws is achieved under the condition that the data volume of the pump operation data corresponding to different blade angles is small, the accuracy of curve fitting is improved, and further, the accuracy of pump performance analysis is improved.

[0088] Optionally, the device further includes: a parameter to be optimized determination module and a target transformation parameter determination module.

[0089] The parameter to be optimized determination module is configured to determine a parameter to be optimized corresponding to the other blade angle for at least one other blade angle among the multiple blade angles except the target blade angle.

[0090] A target transformation parameter determination module, which is used to iteratively update the parameter to be optimized according to the gradient descent algorithm and a preset loss function, so as to determine the target transformation parameter corresponding to the other blade angles when the loss function reaches the preset convergence condition; wherein, the loss function is constructed based on multiple sets of the pump operation data corresponding to the other blade angles and the reference characteristic function.

[0091] Optionally, the target transformation parameter determination module includes: a gradient determination unit, a parameter update unit, and a target transformation parameter determination unit.

[0092] The gradient determination unit is used to, for multiple iterative processes, determine the partial derivative of the loss function corresponding to the current iterative process with respect to the parameter to be optimized corresponding to the current iterative process, so as to obtain the gradient corresponding to the current iterative process;

[0093] The parameter update unit is used to update the parameter to be optimized corresponding to the current iterative process according to the gradient, so as to obtain the parameter to be optimized corresponding to the next iterative update process, and determine the loss function corresponding to the next iterative process according to the parameter to be optimized corresponding to the next iterative process and the loss function corresponding to the current iterative process;

[0094] The target transformation parameter determination unit is used to, when it is determined that the loss function corresponding to the next iterative process does not meet the preset convergence condition, use the next iterative process as the current iterative process, and repeat the steps of determining the gradient and updating the parameter until the loss function corresponding to the next iterative process meets the preset convergence condition, and use the parameter to be optimized corresponding to the next iterative process as the target transformation parameter corresponding to the other blade angles.

[0095] Optionally, the reference function determination module 320 includes: a target blade angle determination unit and a reference function determination unit.

[0096] The target blade angle determination unit is used to randomly determine one of the blade angles from multiple blade angles as the target blade angle;

[0097] The reference function determination unit is used to process the multiple sets of pump operation data corresponding to the target blade angle according to a preset spline interpolation method to obtain a reference characteristic function.

[0098] Optionally, the characteristic function determination module 330 includes: a function translation unit and a function scaling unit.

[0099] The function translation unit is used to translate the reference characteristic function according to the translation parameter to obtain a to-be-processed characteristic function;

[0100] A function scaling unit for scaling the to-be-processed characteristic function according to the scaling parameter to obtain a characteristic function corresponding to the other blade angles.

[0101] Optionally, the curve generation module 340 includes: a curve generation unit and a characteristic curve determination unit.

[0102] The curve generation unit is configured to generate a reference characteristic curve according to the reference characteristic function; and generate characteristic curves according to each of the characteristic functions;

[0103] The characteristic curve determination unit is configured to use the reference characteristic curve and at least one of the characteristic curves as the pump characteristic curve corresponding to the to-be-tested water pump.

[0104] Optionally, the device further includes: an analysis graph display module.

[0105] The analysis graph display module is configured to generate a pump characteristic analysis graph based on the pump characteristic curve and visually display the pump characteristic analysis graph.

[0106] The water pump characteristic curve generation device provided by the embodiments of the present invention can execute the water pump characteristic curve generation method provided by any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the method.

[0107] Embodiment 4

[0108] Figure 4 FIG. shows a schematic structural diagram of an electronic device 10 that can be used to implement the embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as, laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0109] As Figure 4As shown, the electronic device 10 includes at least one processor 11 and a memory communicatively connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc. Among them, the memory stores a computer program executable by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. The input / output (I / O) interface 15 is also connected to the bus 14.

[0110] Multiple components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disc, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0111] The processor 11 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the processor 11 include but are not limited to a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the water pump characteristic curve generation method.

[0112] In some embodiments, the water pump characteristic curve generation method can be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as the storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the water pump characteristic curve generation method described above can be executed. Alternatively, in other embodiments, the processor 11 can be configured to execute the water pump characteristic curve generation method by any other appropriate means (such as by means of firmware).

[0113] The various embodiments of the systems and techniques described above in this specification can be implemented in digital electronic circuitry, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems-on-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor that receives data and instructions from, and transmits data and instructions to, a storage system, at least one input device, and at least one output device.

[0114] The computer programs for implementing the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the computer programs, when executed by the processor, cause the functions / operations specified in the flowchart and / or block diagram to be implemented. The computer programs can be executed entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

[0115] In the context of the present invention, a computer-readable storage medium can be a tangible medium that can contain or store a computer program for use by or in connection with an instruction execution system, apparatus, or device. The computer-readable storage medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. Alternatively, the computer-readable storage medium can be a machine-readable signal medium. More specific examples of the machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0116] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the electronic device. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0117] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected to each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), blockchain network, and the Internet.

[0118] A computing system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The relationship between the client and the server is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system and solves the defects of difficult management and weak business scalability existing in traditional physical hosts and VPS services.

[0119] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in the present invention can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved, and no limitation is made herein.

[0120] The above specific embodiments do not constitute a limitation on the protection scope of the present invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A method for generating a water pump characteristic curve, characterized in that: include: Acquire multiple groups of water pump operation data of the water pump to be tested at multiple different blade angles; wherein the water pump operation data is used to indicate data generated during the operation of the water pump to be tested at the corresponding blade angle; the multiple groups of water pump operation data include different water pump flow rates and water pump performance data corresponding to the water pump flow rates; the data volume of the multiple groups of water pump operation data at each of the blade angles is less than a preset data volume threshold; determining a reference characteristic function according to a plurality of groups of the water pump operation data corresponding to a target blade angle among the plurality of blade angles; For at least one other blade angle among the plurality of blade angles except the target blade angle, determining a characteristic function corresponding to the other blade angle according to a predetermined target transformation parameter corresponding to the other blade angle and the reference characteristic function; wherein the target transformation parameter is determined based on a plurality of groups of the water pump operation data corresponding to the other blade angle; Determining a pump characteristic curve corresponding to the water pump to be tested according to the reference characteristic function and at least one of the characteristic functions; The method of determining the pump characteristic curve corresponding to the water pump to be tested based on the benchmark characteristic function and at least one of the characteristic functions includes: generating a benchmark characteristic curve based on the benchmark characteristic function; and generating a characteristic curve based on each of the characteristic functions; and using the benchmark characteristic curve and at least one of the characteristic curves as the pump characteristic curves corresponding to the water pump to be tested.

2. The method for generating a water pump characteristic curve according to claim 1, characterized in that: Also includes: For other blade angles among the plurality of blade angles except the target blade angle, determining parameters to be optimized corresponding to the other blade angles; The parameters to be optimized are iteratively updated according to the gradient descent algorithm and the preset loss function to determine the target transformation parameters corresponding to the other blade angles when the loss function reaches the preset convergence conditions; wherein the loss function is constructed based on multiple groups of the water pump operation data corresponding to the other blade angles and the benchmark characteristic function.

3. The method for generating a water pump characteristic curve according to claim 2, characterized in that: The iterative updating of the parameters to be optimized according to the gradient descent algorithm and the preset loss function, so as to determine the target transformation parameters corresponding to the other blade angles when the loss function reaches a preset convergence condition, includes: For multiple iterations, determine the partial derivative of the loss function corresponding to the current iteration with respect to the parameter to be optimized corresponding to the current iteration to obtain the gradient corresponding to the current iteration; Performing parameter updating on the parameter to be optimized corresponding to the current iterative process according to the gradient to obtain the parameter to be optimized corresponding to the next iterative process, and determining the loss function corresponding to the next iterative process according to the parameter to be optimized corresponding to the next iterative process and the loss function corresponding to the current iterative process; When it is determined that the loss function corresponding to the next iterative process does not meet the preset convergence conditions, the next iterative process is used as the current iterative process, and the steps of determining the gradient and updating the parameters are repeated until the loss function corresponding to the next iterative process meets the preset convergence conditions, and the parameters to be optimized corresponding to the next iterative process are used as the target transformation parameters corresponding to the other blade angles.

4. The method for generating a water pump characteristic curve according to claim 1, characterized in that: Determining the reference characteristic function according to the plurality of groups of the water pump operation data corresponding to the target blade angle among the plurality of blade angles includes: Randomly determine one of the blade angles as a target blade angle; The plurality of groups of the water pump operation data corresponding to the target blade angles are processed according to a preset spline interpolation method to obtain a reference characteristic function.

5. The method for generating a water pump characteristic curve according to claim 1, characterized in that: The target transformation parameters include translation parameters and scaling parameters; and determining the characteristic function corresponding to the other blade angles according to the predetermined target transformation parameters corresponding to the other blade angles and the reference characteristic function includes: Performing translation processing on the reference characteristic function according to the translation parameter to obtain a characteristic function to be processed; The characteristic function to be processed is scaled according to the scaling parameter to obtain a characteristic function corresponding to the other blade angles.

6. The method for generating a water pump characteristic curve according to claim 1, characterized in that: Also includes: A pump characteristic analysis diagram is generated based on the pump characteristic curve, and the pump characteristic analysis diagram is visualized.

7. A water pump characteristic curve generating device, characterized in that: include: A data acquisition module, used to acquire multiple groups of water pump operation data of the water pump to be tested at multiple different blade angles; wherein the water pump operation data is used to indicate data generated during the operation of the water pump to be tested at the corresponding blade angle; the multiple groups of water pump operation data include different water pump flow rates and water pump performance data corresponding to the water pump flow rates; the data volume of the multiple groups of water pump operation data at each of the blade angles is less than a preset data volume threshold; A reference function determination module, used to determine a reference characteristic function according to a plurality of groups of the water pump operation data corresponding to a target blade angle among the plurality of blade angles; a characteristic function determination module, configured to determine, for at least one other blade angle among the plurality of blade angles except the target blade angle, a characteristic function corresponding to the other blade angle according to a predetermined target transformation parameter corresponding to the other blade angle and the reference characteristic function; wherein the target transformation parameter is determined based on a plurality of groups of the water pump operation data corresponding to the other blade angle; A curve generating module, used for determining a pump characteristic curve corresponding to the water pump to be tested according to the reference characteristic function and at least one of the characteristic functions; Wherein, the curve generation module comprises: a curve generation unit and a characteristic curve determination unit; The curve generating unit is used to generate a reference characteristic curve according to the reference characteristic function; and to generate a characteristic curve according to each of the characteristic functions; The characteristic curve determination unit is used to use the reference characteristic curve and at least one of the characteristic curves as pump characteristic curves corresponding to the water pump to be tested.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the water pump characteristic curve generating method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for generating a water pump characteristic curve according to any one of claims 1 to 6 when executed.

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