Method, apparatus, and machine readable storage medium for controlling a pumping power system

Abstract

The application discloses a method, device and machine readable storage medium for controlling a pumping power system. The method comprises: determining a rotational speed characteristic area of a pumping device during operation of the pumping device; determining a state of a rotational speed characteristic of the pumping device according to the rotational speed characteristic area; obtaining working condition data of the pumping device in the case that the state of the rotational speed characteristic is an abnormal state; inputting the working condition data into a target pumping speed prediction model to obtain a predicted pumping speed; determining an operation state of the pumping device according to the predicted pumping speed and an actual pumping speed of the pumping device; determining an abnormality level of the pumping device in the case that the operation state is an abnormal operation state; and executing a corresponding control strategy according to the abnormality level. The application determines the abnormality of the pumping device by combining the rotational speed and the pumping speed, so that the judgment result is more accurate, and the targeted control is performed according to the abnormality, which is beneficial to improving the system performance and the user experience.

Description

Technical Field

[0001] This application relates to the field of engineering machinery technology, and more specifically to a method, apparatus and machine-readable storage medium for controlling a pumping power system. Background Technology

[0002] The power system of concrete pumping equipment is mainly driven by a fuel engine, an electric motor, or a fuel engine + electric motor hybrid system. The power system outputs torque and speed to the hydraulic system, which then acts on the load through the actuators. If the load changes and suddenly increases, the torque demand of the hydraulic system will increase accordingly. When this torque exceeds the output torque of the power system, the power system will experience insufficient power, speed drop, or even shutdown, affecting the normal operation of the equipment.

[0003] Currently, the industry primarily uses two methods to prevent power system speed drops: reducing the torque demanded by the hydraulic system or increasing the power output. Reducing the torque demanded by the hydraulic system involves using constant power control of the oil pump. This means that once the oil pump pressure rises to a preset value, the pump displacement is reduced, thereby decreasing the torque demanded by the pump and preventing insufficient power from causing speed drops. Increasing the power output of the power system involves increasing the throttle or motor current. This means that once the actual speed falls below a preset value, the throttle or current is increased to boost power and prevent speed drops and shutdowns. Both methods can also be used simultaneously.

[0004] However, besides load changes causing a drop in power system speed, equipment power system malfunctions or aging and performance degradation due to increased service life can also lead to decreased power system responsiveness. In such cases, if the hydraulic system is not adjusted accordingly and continues to operate according to previous settings, abnormal speed will occur, resulting in unstable equipment operation and decreased work efficiency.

[0005] Existing technology compares the current actual engine speed with a preset speed. When the engine is operating at different speeds, if the difference between the actual speed and the preset speed is greater than a first given value corresponding to that speed, it is determined that the engine is slowing down. At this time, the target engine speed is increased and the oil pump displacement is reduced. If the difference is less than a second given value corresponding to that speed, it is determined that the engine has excess power, the target engine speed is reduced, and the oil pump displacement is increased.

[0006] However, different engines have different power characteristics. Some engines, although experiencing a large speed drop, can quickly recover within a short time, and this speed drop has no impact on the actual operation of the equipment. Other engines, although experiencing a small speed drop, take a long time to recover to the target speed after the speed drop, and this speed drop directly affects the operation of the equipment. Therefore, using the speed drop value at a single moment as a judgment criterion cannot accurately identify the impact on the equipment's operation. In addition, due to the differences in the responsiveness of different equipment's engines, hydraulic systems, and actuators, and the varying years of use and intensity of use of different equipment, the degree of performance degradation of each system varies, making a preset fixed speed value no longer suitable as a judgment condition.

[0007] Therefore, the pumping control methods used in the prior art have the problems of low accuracy in anomaly detection and limited applicability. Summary of the Invention

[0008] The purpose of this application is to provide a method, apparatus, and machine-readable storage medium for controlling a pumping power system, in order to solve the problems of low accuracy and limited applicability of pumping control methods used in the prior art.

[0009] To achieve the above objectives, the first aspect of this application provides a method for controlling a pumping power system, the method comprising:

[0010] During the operation of the pumping equipment, determine the area representing the pumping equipment's rotational speed;

[0011] The state of the pumping equipment's rotational speed characteristics is determined based on the area representing the rotational speed.

[0012] When the speed characteristic is in an abnormal state, obtain the operating condition data of the pumping equipment;

[0013] Input the operating data into the target pumping speed prediction model to obtain the predicted pumping speed of the pumping equipment;

[0014] The operating status of the pumping equipment is determined based on the predicted pumping speed and the actual pumping speed of the pumping equipment.

[0015] When the pumping equipment is in an abnormal operating state, determine the abnormality level of the pumping equipment;

[0016] The corresponding control strategy is executed based on the anomaly level.

[0017] In this embodiment of the application, determining the area representing the rotational speed of the pumping equipment includes:

[0018] Obtain the actual rotational speed dataset of the pumping equipment from the first time point to the second time point;

[0019] Obtain the gear position information of the pumping equipment;

[0020] Determine the target speed of the pumping equipment based on the gear information;

[0021] The rotational speed characterization area of ​​the pumping equipment is determined based on the actual rotational speed dataset and the target rotational speed.

[0022] The first moment is the moment when the difference between the actual speed and the target speed of the pumping equipment is negative for the first time after the previous reversing signal is issued, and the second moment is the moment when the difference between the actual speed and the target speed of the pumping equipment is negative for the last time before the next reversing signal is issued.

[0023] In this embodiment of the application, determining the rotational speed characteristics of the pumping equipment based on the rotational speed characterization area includes:

[0024] Compare the area represented by the rotational speed with the area threshold;

[0025] If the area representing the rotational speed is less than the area threshold, the rotational speed characteristic is determined to be in a normal state.

[0026] If the area representing the rotational speed is greater than or equal to the area threshold, the rotational speed characteristic is determined to be in an abnormal state.

[0027] In this embodiment of the application, determining the operating status of the pumping equipment based on the predicted pumping speed and the actual pumping speed of the pumping equipment includes:

[0028] Determine the speed difference between the predicted pumping speed and the actual pumping speed;

[0029] Compare the speed difference with a first threshold;

[0030] If the speed difference is less than the first threshold, the pumping equipment is determined to be in normal operating condition.

[0031] If the speed difference is greater than or equal to the first threshold, the operating status of the pumping equipment is determined to be abnormal.

[0032] In this embodiment of the application, when the pumping equipment is in an abnormal operating state, determining the abnormality level of the pumping equipment includes:

[0033] The speed difference is compared with the second threshold and the third threshold, respectively;

[0034] If the speed difference is less than the second threshold, the abnormality level of the pumping equipment is determined to be the first level;

[0035] If the speed difference is greater than or equal to the second threshold and less than the third threshold, the abnormality level of the pumping equipment is determined to be the second level.

[0036] If the speed difference is greater than or equal to the third threshold, the abnormality level of the pumping equipment is determined to be the third level;

[0037] Among them, the first threshold is less than the second threshold, and the second threshold is less than the third threshold.

[0038] In this embodiment of the application, executing the corresponding control strategy according to the anomaly level includes:

[0039] When the pumping equipment is classified as having an anomaly level of Level 1, monitor the changes in the pumping equipment's rotational speed characteristics.

[0040] If the change in rotational speed characteristics meets the set criteria, the rate of change of pumping speed is determined based on the predicted pumping speed and the actual pumping speed.

[0041] The rate of change of the output pumping speed.

[0042] In this embodiment of the application, executing the corresponding control strategy according to the anomaly level includes:

[0043] When the abnormality level of the pumping equipment is the second level, the output can be selected as a control mode, which includes controlling the oil pump displacement and controlling the output power.

[0044] Acquire target control method;

[0045] When the target control method is to control the oil pump displacement, reduce the oil pump displacement of the pumping equipment;

[0046] When the target control mode is to control the output power, increase the output power of the pumping equipment's engine.

[0047] In this embodiment of the application, executing the corresponding control strategy according to the anomaly level includes:

[0048] When the abnormality level of the pumping equipment is level three, reduce the oil pump displacement of the pumping equipment, or reduce the oil pump displacement of the pumping equipment while increasing the output power of the pumping equipment's engine.

[0049] Determine whether the speed characteristics of the pumping equipment have returned to normal after control;

[0050] If the speed characteristics have not returned to normal, increase the control intensity;

[0051] Once the speed characteristics return to normal, maintain the current control strength.

[0052] In this embodiment of the application, the method further includes:

[0053] Obtain historical operating data sets of the pumping equipment;

[0054] Filter out the feature datasets corresponding to multiple features related to pumping speed from the historical operating condition dataset;

[0055] An initial pumping speed prediction model is constructed based on a linear regression algorithm and multiple features.

[0056] The initial pumping speed prediction model is trained using the feature dataset to obtain the trained pumping speed prediction model.

[0057] The accuracy of the trained pumping speed prediction model was evaluated.

[0058] If the trained pumping speed prediction model meets the accuracy requirements, the trained pumping speed prediction model will be determined as the target pumping speed prediction model.

[0059] A second aspect of this application provides an apparatus for controlling a pumping power system, comprising:

[0060] The memory is configured to store instructions; and

[0061] The processor is configured to retrieve instructions from memory and, when executing the instructions, to implement the aforementioned method for controlling the pumping power system.

[0062] A third aspect of this application provides a machine-readable storage medium storing instructions for causing a machine to perform the aforementioned method for controlling a pumping power system.

[0063] Through the above technical solution, during the operation of the pumping equipment, the rotational speed characterization area of ​​the pumping equipment is determined, and the state of the rotational speed characteristic of the pumping equipment is determined based on the rotational speed characterization area. When the rotational speed characteristic state is abnormal, the operating condition data of the pumping equipment is acquired. Then, the operating condition data is input into the target pumping speed prediction model to obtain the predicted pumping speed of the pumping equipment. The operating state of the pumping equipment is determined based on the predicted pumping speed and the actual pumping speed. When the operating state of the pumping equipment is abnormal, the abnormality level of the pumping equipment is determined. Finally, the corresponding control strategy is executed according to the abnormality level. This application determines the abnormal situation of the pumping equipment by combining two parameters, rotational speed and pumping speed, making the judgment result more accurate. Furthermore, targeted control based on the abnormal situation is beneficial to improving system performance and user experience.

[0064] Other features and advantages of the embodiments of this application will be described in detail in the following detailed description section. Attached Figure Description

[0065] The accompanying drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the following detailed description to explain the embodiments of this application, but do not constitute a limitation on the embodiments of this application. In the drawings:

[0066] Figure 1 A flowchart illustrating a method for controlling a pumping power system, provided as an embodiment of this application;

[0067] Figure 2 A graph showing the relationship between rotational speed and time during the operation of a pumping device provided in a specific embodiment of this application;

[0068] Figure 3 A flowchart illustrating a method for constructing a target pumping speed prediction model, provided in a specific embodiment of this application;

[0069] Figure 4 This is a structural block diagram of a device for controlling a pumping power system, provided as an embodiment of this application. Detailed Implementation

[0070] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only for illustration and explanation of the embodiments of this application and are not intended to limit the embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0071] It should be noted that if the embodiments of this application involve directional indicators (such as up, down, left, right, front, back, etc.), the directional indicators are only used to explain the relative positional relationship and movement of the components in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indicators will also change accordingly.

[0072] Furthermore, if the embodiments of this application involve descriptions such as "first" or "second," these descriptions are for descriptive purposes only and should not be construed as indicating or implying their relative importance or implicitly specifying the number of technical features indicated. Therefore, features defined with "first" or "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. If the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0073] Figure 1 This is a flowchart illustrating a method for controlling a pumping power system, provided as an embodiment of this application. Figure 1 As shown in the figure, this application provides a method for controlling a pumping power system, which may include the following steps:

[0074] Step 101: During the operation of the pumping equipment, determine the area representing the rotational speed of the pumping equipment;

[0075] Step 102: Determine the state of the pumping equipment's rotational speed characteristics based on the rotational speed characterization area;

[0076] Step 103: When the speed characteristic is in an abnormal state, obtain the operating condition data of the pumping equipment;

[0077] Step 104: Input the operating data into the target pumping speed prediction model to obtain the predicted pumping speed of the pumping equipment;

[0078] Step 105: Determine the operating status of the pumping equipment based on the predicted pumping speed and the actual pumping speed of the pumping equipment;

[0079] Step 106: If the pumping equipment is in an abnormal operating state, determine the abnormality level of the pumping equipment;

[0080] Step 107: Execute the corresponding control strategy according to the anomaly level.

[0081] In this embodiment, during pumping, fluctuations in load pressure, engine malfunctions, or decreased performance of the pumping equipment can cause the actual rotational speed to deviate from the target speed, i.e., engine speed fluctuations. To monitor the operating status of the pumping equipment, the engine speed can be used as a preliminary criterion for judging the operating status of the pumping equipment. In this embodiment, the rotational speed characteristic is determined by the rotational speed characterization area. The rotational speed characterization area of ​​the pumping equipment refers to the area enclosed by the curves of the actual rotational speed and the target rotational speed of the pumping equipment within a set time period. This area characterizes the combined effect of the depth and breadth of the speed drop. Once the rotational speed characterization area of ​​the pumping equipment is determined, the rotational speed characteristic of the pumping equipment can be determined based on this area.

[0082] In this embodiment, the actuator of the concrete pumping equipment is a pumping cylinder, which is used to output thrust and speed. The thrust of the cylinder is determined by the size of the concrete load, and the speed of the cylinder affects the pumping efficiency and stability. The ideal pumping speed is to immediately increase to the target speed after completing the reversal within one pumping cycle, and then maintain a uniform speed.

[0083] The pumping speed satisfies formula (1):

[0084]

[0085] Where v is the pumping speed, Q is the flow rate of the oil pump, M is the area of ​​the oil pressure chamber of the oil cylinder, and M is a constant.

[0086] The flow rate of the oil pump satisfies formula (2):

[0087] Q = V × n × i; (2)

[0088] Where V is the oil pump displacement, n is the engine speed, i is the transmission system speed ratio, and is a constant.

[0089] Therefore, the functional relationship between pumping speed, rotational speed, and pump displacement is established as shown in formula (3):

[0090] v = f(V, n); (3)

[0091] Therefore, when a change in the rotational speed characteristic causes a decrease or fluctuation in the cylinder speed, it can be considered that the equipment's performance is affected. In this embodiment, if the rotational speed characteristic is detected to be in an abnormal state based on the area of ​​the rotational speed characterization, the change in pumping speed can be further determined, thereby identifying the impact on the equipment's performance. In another example, if the rotational speed characteristic of the pumping equipment is in an abnormal state, it indicates that the pumping equipment's performance is not affected. In this case, the rotational speed characteristic of the pumping equipment can be continuously monitored until the equipment stops operating.

[0092] In this embodiment, when an abnormal state is detected in the rotational speed characteristic, the operating condition data of the pumping equipment at that moment is acquired. In one example, the operating condition data of the pumping equipment may include pumping pressure, actual engine speed, hydraulic system main pump displacement current, hydraulic system oil temperature, ambient temperature, and atmospheric pressure. Further, the operating condition parameters are input into a pre-constructed target pumping speed prediction model to obtain the predicted pumping speed of the pumping equipment. The target pumping equipment prediction model is a model used to predict the current ideal pumping speed of the pumping equipment; the predicted pumping speed is the ideal pumping speed of the pumping equipment under the current operating conditions. Since the pumping speed directly affects the working performance of the pumping equipment, the operating state of the pumping equipment can be determined based on the predicted pumping speed and the actual pumping speed; the actual pumping speed is the actual pumping speed of the pumping equipment at that moment acquired by the controller.

[0093] Furthermore, in order to achieve targeted control of the pumping equipment, when the pumping equipment is in an abnormal operating state, the abnormality level of the pumping equipment can be determined, and then the corresponding control strategy can be executed according to the specific abnormality level to restore the pumping equipment to normal operating state.

[0094] Through the above technical solution, during the operation of the pumping equipment, the rotational speed characterization area of ​​the pumping equipment is determined, and the state of the rotational speed characteristic of the pumping equipment is determined based on the rotational speed characterization area. When the rotational speed characteristic state is abnormal, the operating condition data of the pumping equipment is acquired. Then, the operating condition data is input into the target pumping speed prediction model to obtain the predicted pumping speed of the pumping equipment. The operating state of the pumping equipment is determined based on the predicted pumping speed and the actual pumping speed. When the operating state of the pumping equipment is abnormal, the abnormality level of the pumping equipment is determined. Finally, the corresponding control strategy is executed according to the abnormality level. This application determines the abnormal situation of the pumping equipment by combining two parameters, rotational speed and pumping speed, making the judgment result more accurate. Furthermore, targeted control based on the abnormal situation is beneficial to improving system performance and user experience.

[0095] In this embodiment of the application, step 101, determining the rotational speed characterization area of ​​the pumping equipment, may include:

[0096] Obtain the actual rotational speed dataset of the pumping equipment from the first time point to the second time point;

[0097] Obtain the gear position information of the pumping equipment;

[0098] Determine the target speed of the pumping equipment based on the gear information;

[0099] The rotational speed characterization area of ​​the pumping equipment is determined based on the actual rotational speed dataset and the target rotational speed.

[0100] The first moment is the moment when the difference between the actual speed and the target speed of the pumping equipment is negative for the first time after the previous reversing signal is issued, and the second moment is the moment when the difference between the actual speed and the target speed of the pumping equipment is negative for the last time before the next reversing signal is issued.

[0101] In this embodiment, the target speed refers to the ideal value that the engine speed of the pumping equipment should reach in the current gear, while the actual speed refers to the actual measured value of the engine speed of the pumping equipment. During pumping, due to load pressure fluctuations, engine malfunctions, or decreased performance of the pumping equipment, the actual speed may deviate from the target speed, i.e., the engine speed may fluctuate. Fluctuations in engine speed can affect the normal operation of the equipment. Depending on the fluctuation, severe fluctuations may cause the engine to shut down, interrupting the equipment's operation; smaller fluctuations may not immediately cause the engine to shut down, but they will still affect the normal operation of the equipment, causing changes in the equipment's operating speed, i.e., changes in the pumping speed. Changes in pumping speed can lead to fluctuations in load pressure, which in turn can affect the displacement of the hydraulic system's oil pump under constant power control, resulting in mutual interference. Therefore, the operating status of the pumping equipment can be preliminarily judged based on the engine speed of the pumping equipment, thereby determining whether the equipment is malfunctioning.

[0102] In this embodiment, to reduce the probability of misjudgment, the state of the rotational speed characteristic can be determined based on the rotational speed representation area. Specifically, the target rotational speed corresponding to the current gear is first determined based on the gear information of the pumping equipment. Then, the following steps are executed repeatedly: the actual rotational speed dataset of the pumping equipment from the first moment to the second moment is obtained; the rotational speed representation area is calculated based on the actual rotational speed dataset and the target rotational speed; and the rotational speed characteristic is judged to be abnormal based on the representation area. If abnormal, corresponding processing is performed. This process is repeated until the pumping equipment stops operating.

[0103] Figure 2 This is a graph showing the relationship between rotational speed and time during the operation of a pumping device provided in a specific embodiment of this application. Figure 2 As shown in the figure, the circled area represents the area representing the rotational speed of the pumping equipment at different times. In one example, the area representing the rotational speed of the pumping equipment can satisfy formula (4):

[0104]

[0105] Where A is the area representing the rotational speed, and R i Let R be the actual rotational speed at point i, and R be the target rotational speed. The time corresponding to point i = 1 is the first time, which is the moment when the actual rotational speed and the target rotational speed are negative for the first time after the commutation signal occurs and the set time has elapsed. The time corresponding to point i = n is the second time, which is the moment when the actual rotational speed and the target rotational speed are negative for the last time before the commutation signal occurs and the set time has elapsed. In one example, the set time can be 0.1 s.

[0106] Therefore, judging whether the speed characteristics are abnormal by measuring the area of ​​the speed characterization during the operation of the pumping equipment helps to reduce the false judgment rate and improve the accuracy of the judgment results.

[0107] In this embodiment of the application, step 102, determining the state of the pumping equipment's rotational speed characteristics based on the rotational speed characterization area, may include:

[0108] Compare the area represented by the rotational speed with the area threshold;

[0109] If the area representing the rotational speed is less than the area threshold, the rotational speed characteristic is determined to be in a normal state.

[0110] If the area representing the rotational speed is greater than or equal to the area threshold, the rotational speed characteristic is determined to be in an abnormal state.

[0111] Specifically, the area threshold refers to the optimal threshold for distinguishing between the normal and abnormal states of a rotational speed characteristic. The state of the rotational speed characteristic can be determined by comparing the calculated area of ​​the rotational speed representation with the area threshold. If the area of ​​the rotational speed representation is less than the area threshold, it is determined that the area of ​​the rotational speed representation is within the normal range, and the corresponding state of the rotational speed characteristic is normal. Otherwise, the corresponding state of the rotational speed characteristic is abnormal.

[0112] In one example, the area threshold can be determined as follows.

[0113] Table 1 shows the confusion matrix of the classification results. The evaluation criterion for determining the area threshold is the F1 score, which is calculated as follows:

[0114] Table 1

[0115]

[0116] Based on Table 1, we can obtain formulas (5) and (6):

[0117]

[0118]

[0119] Then, F1 can satisfy formula (7):

[0120]

[0121] Where P is the recall rate, R is the precision rate, and N is the total number of samples.

[0122] The specific steps for determining the area threshold are as follows:

[0123] 1) First, sort the rotational speed characterization areas A from smallest to largest, and then sample the characterization areas A using an equal-frequency sampling method to obtain sampling points K1, K, ... K. n The number of sampling points n should be less than 10. Calculate the F1 score of each sampling point sequentially, identify the point with the largest F1 score, and extract its corresponding value K. i ;

[0124] 2) Then in K i-1 To K i+1 Within the interval, equal-frequency sampling is performed on the area A, with n sampling points. The F1 score of each sampling point is calculated sequentially, and the point with the largest F1 score is identified, and its corresponding value K is extracted. j ;

[0125] 3) Repeat step 2) until the total number of data points in the m-th interval is less than N, then take K. m This is the final threshold, used to obtain the area threshold.

[0126] Thus, the above method can be used to automatically optimize the area threshold, thereby improving the accuracy of the area criterion.

[0127] In this embodiment of the application, the method may further include:

[0128] Obtain historical operating data sets of the pumping equipment;

[0129] Filter out the feature datasets corresponding to multiple features related to pumping speed from the historical operating condition dataset;

[0130] An initial pumping speed prediction model is constructed based on a linear regression algorithm and multiple features.

[0131] The initial pumping speed prediction model is trained using the feature dataset to obtain the trained pumping speed prediction model.

[0132] The accuracy of the trained pumping speed prediction model was evaluated.

[0133] If the trained pumping speed prediction model meets the accuracy requirements, the trained pumping speed prediction model will be determined as the target pumping speed prediction model.

[0134] In this embodiment, the historical operating condition dataset of the pumping equipment can be collected by an industrial IoT edge computing box installed on the pumping equipment, and the collected operating condition data is sent to a cloud big data platform for storage to obtain the historical operating condition dataset, which is used to construct a target pumping speed prediction model. In one example, the historical operating condition dataset of the pumping equipment includes multiple operating condition data points. Each operating condition data point may include the operating gear of the pumping equipment, the main pump pressure of the pumping hydraulic system, the pumping speed, the displacement current of the main pump of the hydraulic system, the hydraulic system oil temperature, the target speed of the engine, the actual speed of the engine, the ambient temperature, the atmospheric pressure, and the latitude and longitude of the pumping equipment's location. Among them, the ambient temperature, atmospheric pressure, and the latitude and longitude of the pumping equipment's location are used to identify the working environment of the equipment; the operating gear of the pumping equipment, the main pump pressure of the pumping hydraulic system, the pumping speed, the displacement current of the main pump of the hydraulic system, the hydraulic system oil temperature, the target speed of the engine, and the actual speed of the engine are used to identify the operating condition of the pumping equipment.

[0135] Furthermore, since the historical operating condition dataset of the pumping equipment contains various operating condition parameters, it is necessary to filter the historical operating condition dataset to identify multiple features related to pumping speed and their corresponding feature datasets in order to construct a target pumping speed prediction model. These multiple features refer to several different operating condition parameters related to pumping speed. In one example, these multiple features may include pumping pressure, actual engine speed, hydraulic system main pump displacement current, hydraulic system oil temperature, ambient temperature, and atmospheric pressure. Then, based on a linear regression algorithm, an initial pumping speed prediction model is constructed according to the selected multiple features, and this initial model is trained using the feature datasets corresponding to these features to obtain a trained pumping speed prediction model. To ensure the accuracy of the model's predictions, the accuracy of the trained pumping speed prediction model needs to be evaluated. Once the accuracy requirements are met, the target pumping speed prediction model can be obtained.

[0136] Figure 3 This is a flowchart illustrating a method for constructing a target pumping speed prediction model, provided as a specific embodiment of this application. Figure 3 As shown in the figure, a specific embodiment of this application provides a method for constructing a target pumping speed prediction model. Taking a concrete pump truck as an example, the method may include the following steps:

[0137] Step 1: Data Collection

[0138] Historical operating condition data is collected by an industrial IoT edge computing box installed on a concrete pump truck and uploaded to a cloud big data platform for storage to obtain a historical operating condition dataset, which is used to build a standard model for pumping speed.

[0139] Step 2: Polynomial Characteristic Construction

[0140] First, starting from the mechanism, several features related to pumping speed are selected, i.e., features that may affect pumping speed. Examples include: pumping pressure, actual engine speed, oil pump displacement current, hydraulic system oil temperature, ambient temperature, and atmospheric pressure. Then, a regression fitting model is established based on a linear regression algorithm to obtain an initial pumping speed prediction model. When establishing the regression fitting model, there may be higher-order relationships between the features; therefore, it is necessary to first construct polynomial features. A specific example is shown below:

[0141] If there are two features x1 and x2 that are related to the fitted target y, then the constructed second-order polynomial features will be expanded to x1, x1, x1 2 x1x2, x2 2 Five terms, and so on for an nth-order polynomial.

[0142] When constructing a polynomial, you can use the preprocessing.PolynomialFeatures library in Python's sklearn library to construct features, and directly construct an nth-order polynomial using the parameter degree=n.

[0143] Step 3: Feature Selection and Target Fitting

[0144] After constructing high-order features, the feature dimensions can expand dramatically, a phenomenon commonly known as the "curse of dimensionality." Therefore, dimensionality reduction is necessary, such as using the Lasso algorithm. Lasso can perform dimensionality reduction and fitting simultaneously. Because it employs L1 regularization, it compresses the coefficients of features, reducing initially small coefficients to zero, thus discarding features corresponding to these coefficients as insignificant. Simultaneously, feature selection and fitting are performed on the target, resulting in a standard pumping speed fitting curve that meets accuracy requirements, thus yielding the trained pumping speed prediction model.

[0145] Step 4: Model Accuracy Evaluation

[0146] To ensure the accuracy of model predictions, it is necessary to evaluate the model's accuracy. According to industry standards, the effectiveness of a standard model can only be guaranteed if the mean absolute error of the model prediction is less than or equal to 1. The mean absolute error satisfies formula (8):

[0147]

[0148] in, S is the mean absolute error. i For the i-th predicted pumping speed, y i Let be the actual pumping speed for the i-th pumping cycle.

[0149] The mean absolute error of the trained pumping speed prediction model is calculated using the above method. If the calculated mean absolute error is less than or equal to 1, it indicates that the trained pumping speed prediction model meets the accuracy requirements, and thus the target pumping speed prediction model is obtained.

[0150] In this embodiment of the application, step 105, determining the operating status of the pumping equipment based on the predicted pumping speed and the actual pumping speed of the pumping equipment, may include:

[0151] Determine the speed difference between the predicted pumping speed and the actual pumping speed;

[0152] Compare the speed difference with a first threshold;

[0153] If the speed difference is less than the first threshold, the pumping equipment is determined to be in normal operating condition.

[0154] If the speed difference is greater than or equal to the first threshold, the operating status of the pumping equipment is determined to be abnormal.

[0155] In this embodiment, the first threshold is a critical value for distinguishing between the normal operating state and the abnormal operating state of the pumping equipment. First, the difference between the predicted pumping speed and the actual pumping speed, i.e., the speed difference, is determined. Then, the speed difference is compared with the first threshold, and the operating state of the pumping speed is determined based on the comparison result. In this embodiment, if the speed difference is less than the first threshold, the operating state of the pumping speed is determined to be the normal operating state; otherwise, it is determined to be the abnormal operating state. Thus, after determining an abnormal state based on the rotational speed characteristic, to further improve the accuracy of judging the operating state of the pumping equipment, the judgment is further combined with the pumping speed, which helps to reduce the false judgment rate.

[0156] In this embodiment of the application, step 106, determining the abnormality level of the pumping equipment when the pumping equipment is in an abnormal operating state, may include:

[0157] The speed difference is compared with the second threshold and the third threshold, respectively;

[0158] If the speed difference is less than the second threshold, the abnormality level of the pumping equipment is determined to be the first level;

[0159] If the speed difference is greater than or equal to the second threshold and less than the third threshold, the abnormality level of the pumping equipment is determined to be the second level.

[0160] If the speed difference is greater than or equal to the third threshold, the abnormality level of the pumping equipment is determined to be the third level;

[0161] Among them, the first threshold is less than the second threshold, and the second threshold is less than the third threshold.

[0162] Specifically, both the first and second thresholds are critical values ​​for distinguishing the abnormality levels of pumping equipment. Level 1 indicates a mild abnormality, Level 2 indicates a moderate abnormality, and Level 3 indicates a severe abnormality. Specifically, when the pumping equipment is operating abnormally, the speed difference between the predicted and actual pumping speeds is compared with the second and third thresholds. If the speed difference is less than the second threshold, it indicates a mild abnormality (Level 1). If the speed difference is greater than or equal to the second threshold but less than the third threshold, it indicates a moderate abnormality (Level 2). If the speed difference is greater than or equal to the third threshold, it indicates a severe abnormality (Level 3). The first threshold is less than the second threshold, and the second threshold is less than the third threshold. In one example, the specific values ​​of the first, second, and third thresholds can be obtained experimentally. This method of determining the abnormality level of the pumping equipment facilitates subsequent targeted control.

[0163] In this embodiment, a corresponding control strategy can be executed according to the abnormality level of the pumping equipment, mainly including two methods: emergency active control and reminder control.

[0164] In this embodiment of the application, step 107, executing the corresponding control strategy according to the anomaly level, may include:

[0165] When the pumping equipment is classified as having an anomaly level of Level 1, monitor the changes in the pumping equipment's rotational speed characteristics.

[0166] If the change in rotational speed characteristics meets the set criteria, the rate of change of pumping speed is determined based on the predicted pumping speed and the actual pumping speed.

[0167] The rate of change of the output pumping speed.

[0168] Specifically, if the pumping equipment's anomaly level is Level 1, it indicates a low risk of shutdown and minimal impact on the equipment; therefore, no control measures are necessary. However, to allow technicians a clearer understanding of the pumping equipment's operation, continuous monitoring of its rotational speed characteristics is recommended. If the rotational speed characteristics meet set criteria, the rate of change of the pumping speed is determined based on the predicted and actual pumping speeds. This rate of change is the percentage decrease in pumping speed, calculated as the ratio of the difference between the predicted and actual pumping speeds to the actual pumping speed. This rate of change is then output for real-time monitoring by the user. In one example, the set criteria refer to the change in rotational speed characteristics obtained in a later calculation compared to a previous calculation falling within a set range. This set range can be determined based on actual conditions.

[0169] In this embodiment of the application, step 107, executing the corresponding control strategy according to the anomaly level, may include:

[0170] When the abnormality level of the pumping equipment is the second level, the output can be selected as a control mode, which includes controlling the oil pump displacement and controlling the output power.

[0171] Acquire target control method;

[0172] When the target control method is to control the oil pump displacement, reduce the oil pump displacement of the pumping equipment;

[0173] When the target control mode is to control the output power, increase the output power of the pumping equipment's engine.

[0174] In this embodiment, the target control method refers to the control method ultimately selected by the customer from the optional control methods according to their needs. When the detected abnormality level of the pumping equipment is Level 2, meaning the pumping equipment is in a moderate abnormal state, it indicates that the risk of the pumping equipment stopping is also moderate. In this case, no active control is performed on the pumping equipment; instead, multiple optional control methods are provided for the user to select. These optional control methods may include controlling the oil pump displacement and controlling the output power, etc.

[0175] Furthermore, after the user selects the corresponding control method according to their needs, the controller obtains the user's selected target control method and then executes the corresponding control measures. In one example, if the user selects controlling the oil pump displacement, the controller achieves this control by reducing the oil pump displacement and decreasing the system's required power. This reduces the equipment's performance, decreases the engine load rate, and lowers the risk of equipment downtime. In another example, if the user selects controlling the output power, the controller increases the engine output power by increasing the throttle and speed to ensure that the equipment performance does not degrade, but this will increase energy consumption. In yet another example, if the user does not make a selection within the specified time, the default is the previous selection result. If this is the first selection event, the judgment program continues to execute, and the available control methods are continuously output to continuously remind the user to operate.

[0176] In this embodiment, to enable users to promptly grasp the equipment's risk status, when the equipment is in a moderate abnormal state, it can alert the user to the abnormality by outputting audible, visual, or vibration signals, while reducing the frequency of the interval between alerts. Furthermore, depending on the user's selection, the degree of performance degradation or fuel consumption increase can be displayed. This allows users to promptly understand the equipment's abnormality and take timely action.

[0177] In this embodiment of the application, step 107, executing the corresponding control strategy according to the anomaly level, may include:

[0178] When the abnormality level of the pumping equipment is level three, reduce the oil pump displacement of the pumping equipment, or reduce the oil pump displacement of the pumping equipment while increasing the output power of the pumping equipment's engine.

[0179] Determine whether the speed characteristics of the pumping equipment have returned to normal after control;

[0180] If the speed characteristics have not returned to normal, increase the control intensity;

[0181] Once the speed characteristics return to normal, maintain the current control strength.

[0182] In this embodiment, when the pumping equipment is detected to be at level three, indicating a highly abnormal state, it signifies a high risk of equipment shutdown. In this case, active control of the pumping equipment is necessary. In one example, the controller can reduce the pump displacement to increase engine speed. In another example, the controller can simultaneously reduce the pump displacement and increase the engine output power to further increase engine speed. Further, based on feedback from the pumping equipment's speed characteristics after control, it is determined whether to maintain the existing control or strengthen it further until the speed characteristics return to normal. In one example, if the pumping equipment's speed characteristics do not return to normal after control, the controller increases the control intensity. In another example, if the pumping equipment returns to normal, the controller maintains the current control intensity and continues to control the pumping equipment.

[0183] In this embodiment, to enable users to promptly grasp the risk status of the equipment, when the equipment is in a highly abnormal state, intermittent sound, light, or vibration warning signals can be issued, suggesting immediate repair. This allows users to understand the abnormal situation of the equipment in a timely manner and take appropriate action, improving system security.

[0184] Figure 4 This is a structural block diagram of a device for controlling a pumping power system, provided as an embodiment of this application. Figure 4 As shown in the figure, this application provides an apparatus for controlling a pumping power system, which may include:

[0185] Memory 410 is configured to store instructions; and

[0186] The processor 420 is configured to retrieve instructions from the memory 410 and, when executing the instructions, to implement the aforementioned method for controlling the pumping power system.

[0187] Specifically, in this embodiment of the application, the processor 420 can be configured to:

[0188] During the operation of the pumping equipment, determine the area representing the pumping equipment's rotational speed;

[0189] The state of the pumping equipment's rotational speed characteristics is determined based on the area representing the rotational speed.

[0190] When the speed characteristic is in an abnormal state, obtain the operating condition data of the pumping equipment;

[0191] Input the operating data into the target pumping speed prediction model to obtain the predicted pumping speed of the pumping equipment;

[0192] The operating status of the pumping equipment is determined based on the predicted pumping speed and the actual pumping speed of the pumping equipment.

[0193] When the pumping equipment is in an abnormal operating state, determine the abnormality level of the pumping equipment;

[0194] The corresponding control strategy is executed based on the anomaly level.

[0195] Furthermore, the processor 420 can also be configured as follows:

[0196] Obtain the actual rotational speed dataset of the pumping equipment from the first time point to the second time point;

[0197] Obtain the gear position information of the pumping equipment;

[0198] Determine the target speed of the pumping equipment based on the gear information;

[0199] The rotational speed characterization area of ​​the pumping equipment is determined based on the actual rotational speed dataset and the target rotational speed.

[0200] The first moment is the moment when the difference between the actual speed and the target speed of the pumping equipment is negative for the first time after the previous reversing signal is issued, and the second moment is the moment when the difference between the actual speed and the target speed of the pumping equipment is negative for the last time before the next reversing signal is issued.

[0201] Furthermore, the processor 420 can also be configured as follows:

[0202] Compare the area represented by the rotational speed with the area threshold;

[0203] If the area representing the rotational speed is less than the area threshold, the rotational speed characteristic is determined to be in a normal state.

[0204] If the area representing the rotational speed is greater than or equal to the area threshold, the rotational speed characteristic is determined to be in an abnormal state.

[0205] Furthermore, the processor 420 can also be configured as follows:

[0206] Determine the speed difference between the predicted pumping speed and the actual pumping speed;

[0207] Compare the speed difference with a first threshold;

[0208] If the speed difference is less than the first threshold, the pumping equipment is determined to be in normal operating condition.

[0209] If the speed difference is greater than or equal to the first threshold, the operating status of the pumping equipment is determined to be abnormal.

[0210] Furthermore, the X20 processor can also be configured as follows:

[0211] The speed difference is compared with the second threshold and the third threshold, respectively;

[0212] If the speed difference is less than the second threshold, the abnormality level of the pumping equipment is determined to be the first level;

[0213] If the speed difference is greater than or equal to the second threshold and less than the third threshold, the abnormality level of the pumping equipment is determined to be the second level.

[0214] If the speed difference is greater than or equal to the third threshold, the abnormality level of the pumping equipment is determined to be the third level;

[0215] Among them, the first threshold is less than the second threshold, and the second threshold is less than the third threshold.

[0216] Furthermore, the processor 420 can also be configured as follows:

[0217] When the pumping equipment is classified as having an anomaly level of Level 1, monitor the changes in the pumping equipment's rotational speed characteristics.

[0218] If the change in rotational speed characteristics meets the set criteria, the rate of change of pumping speed is determined based on the predicted pumping speed and the actual pumping speed.

[0219] The rate of change of the output pumping speed.

[0220] Furthermore, the processor 420 can also be configured as follows:

[0221] When the abnormality level of the pumping equipment is the second level, the output can be selected as a control mode, which includes controlling the oil pump displacement and controlling the output power.

[0222] Acquire target control method;

[0223] When the target control method is to control the oil pump displacement, reduce the oil pump displacement of the pumping equipment;

[0224] When the target control mode is to control the output power, increase the output power of the pumping equipment's engine.

[0225] Furthermore, the processor 420 can also be configured as follows:

[0226] When the abnormality level of the pumping equipment is level three, reduce the oil pump displacement of the pumping equipment, or reduce the oil pump displacement of the pumping equipment while increasing the output power of the pumping equipment's engine.

[0227] Determine whether the speed characteristics of the pumping equipment have returned to normal after control;

[0228] If the speed characteristics have not returned to normal, increase the control intensity;

[0229] Once the speed characteristics return to normal, maintain the current control strength.

[0230] Furthermore, the processor 420 can also be configured as follows:

[0231] Obtain historical operating data sets of the pumping equipment;

[0232] Filter out the feature datasets corresponding to multiple features related to pumping speed from the historical operating condition dataset;

[0233] An initial pumping speed prediction model is constructed based on a linear regression algorithm and multiple features.

[0234] The initial pumping speed prediction model is trained using the feature dataset to obtain the trained pumping speed prediction model.

[0235] The accuracy of the trained pumping speed prediction model was evaluated.

[0236] If the trained pumping speed prediction model meets the accuracy requirements, the trained pumping speed prediction model will be determined as the target pumping speed prediction model.

[0237] Through the above technical solution, during the operation of the pumping equipment, the rotational speed characterization area of ​​the pumping equipment is determined, and the state of the rotational speed characteristic of the pumping equipment is determined based on the rotational speed characterization area. When the rotational speed characteristic state is abnormal, the operating condition data of the pumping equipment is acquired. Then, the operating condition data is input into the target pumping speed prediction model to obtain the predicted pumping speed of the pumping equipment. The operating state of the pumping equipment is determined based on the predicted pumping speed and the actual pumping speed. When the operating state of the pumping equipment is abnormal, the abnormality level of the pumping equipment is determined. Finally, the corresponding control strategy is executed according to the abnormality level. This application determines the abnormal situation of the pumping equipment by combining two parameters, rotational speed and pumping speed, making the judgment result more accurate. Furthermore, targeted control based on the abnormal situation is beneficial to improving system performance and user experience.

[0238] This application also provides a machine-readable storage medium storing instructions that cause a machine to perform the above-described method for controlling a pumping power system.

[0239] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0240] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create a machine for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0241] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0242] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0243] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0244] Memory may include non-persistent memory in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0245] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0246] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0247] The above are merely embodiments of this application and are not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

Claims

1. A method for controlling a pumping power system, characterized in that, include: During the operation of the pumping equipment, the rotational speed characterization area of ​​the pumping equipment is determined. The rotational speed characterization area refers to the area enclosed by the curves of the actual rotational speed and the target rotational speed of the pumping equipment within a set time. The state of the rotational speed characteristics of the pumping equipment is determined based on the area representing the rotational speed. When the speed characteristic is in an abnormal state, the operating condition data of the pumping equipment is acquired; The operating condition data is input into the target pumping speed prediction model to obtain the predicted pumping speed of the pumping equipment; The operating status of the pumping equipment is determined based on the predicted pumping speed and the actual pumping speed of the pumping equipment. When the pumping equipment is in an abnormal operating state, the abnormality level of the pumping equipment is determined. The corresponding control strategy is executed based on the anomaly level.

2. The method according to claim 1, characterized in that, The determination of the rotational speed characterization area of ​​the pumping equipment includes: Obtain the actual rotational speed dataset of the pumping equipment during the period from the first time point to the second time point; Obtain the gear position information of the pumping equipment; The target rotational speed of the pumping equipment is determined based on the gear information. The rotational speed characterization area of ​​the pumping equipment is determined based on the actual rotational speed dataset and the target rotational speed. Wherein, the first moment is the moment when the difference between the actual speed of the pumping equipment and the target speed is negative for the first time after the previous reversing signal occurs, and the second moment is the moment when the difference between the actual speed of the pumping equipment and the target speed is negative for the last time before the next reversing signal occurs.

3. The method according to claim 1, characterized in that, The state of determining the rotational speed characteristics of the pumping equipment based on the rotational speed characterization area includes: The area representing the rotational speed is compared with an area threshold. If the area representing the rotational speed is less than the area threshold, the state of the rotational speed feature is determined to be normal. If the area representing the rotational speed is greater than or equal to the area threshold, the state of the rotational speed feature is determined to be an abnormal state.

4. The method according to claim 1, characterized in that, Determining the operating status of the pumping equipment based on the predicted pumping speed and the actual pumping speed of the pumping equipment includes: Determine the speed difference between the predicted pumping speed and the actual pumping speed; The speed difference is compared with a first threshold. If the speed difference is less than the first threshold, the pumping equipment is determined to be in normal operating condition. If the speed difference is greater than or equal to the first threshold, the operating state of the pumping equipment is determined to be an abnormal operating state.

5. The method according to claim 4, characterized in that, When the pumping equipment is in an abnormal operating state, determining the abnormality level of the pumping equipment includes: The speed difference is compared with the second threshold and the third threshold, respectively; If the speed difference is less than the second threshold, the abnormality level of the pumping equipment is determined to be the first level; If the speed difference is greater than or equal to the second threshold and less than the third threshold, the abnormality level of the pumping equipment is determined to be the second level. If the speed difference is greater than or equal to the third threshold, the abnormality level of the pumping equipment is determined to be the third level. Wherein, the first threshold is less than the second threshold, and the second threshold is less than the third threshold.

6. The method according to claim 5, characterized in that, The step of executing the corresponding control strategy based on the anomaly level includes: When the abnormality level of the pumping equipment is the first level, the change in the rotational speed characteristics of the pumping equipment is detected; If the change in the rotational speed characteristic meets the set criteria, the rate of change of the pumping speed is determined based on the predicted pumping speed and the actual pumping speed. Output the rate of change of the pumping speed.

7. The method according to claim 5, characterized in that, The step of executing the corresponding control strategy based on the anomaly level includes: When the abnormality level of the pumping equipment is the second level, an optional control mode is output, which includes controlling the oil pump displacement and controlling the output power. Acquire target control method; When the target control method is to control the oil pump displacement, reduce the oil pump displacement of the pumping equipment; When the target control mode is to control the output power, the output power of the pumping equipment's engine is increased.

8. The method according to claim 5, characterized in that, The step of executing the corresponding control strategy based on the anomaly level includes: When the abnormality level of the pumping equipment is level three, reduce the oil pump displacement of the pumping equipment, or reduce the oil pump displacement of the pumping equipment while increasing the output power of the pumping equipment's engine. Determine whether the speed characteristics of the pumping equipment have returned to normal after control; If the rotational speed characteristics do not return to normal, increase the control intensity; If the rotational speed characteristics return to normal, maintain the current control strength.

9. The method according to claim 1, characterized in that, The method further includes: Obtain the historical operating data set of the pumping equipment; Filter out the feature datasets corresponding to multiple features related to pumping speed from the historical operating condition dataset; Based on the linear regression algorithm, an initial pumping speed prediction model is constructed according to the multiple features. The initial pumping speed prediction model is trained using the feature dataset to obtain the trained pumping speed prediction model. The accuracy of the trained pumping speed prediction model is evaluated. If the trained pumping speed prediction model meets the accuracy requirements, the trained pumping speed prediction model is determined as the target pumping speed prediction model.

10. A device for controlling a pumping power system, characterized in that, include: The memory is configured to store instructions; as well as The processor is configured to retrieve the instructions from the memory and, when executing the instructions, to implement the method for controlling a pumping power system according to any one of claims 1 to 9.

11. A machine-readable storage medium, characterized in that, The machine-readable storage medium stores instructions for causing the machine to perform the method for controlling the pumping power system according to any one of claims 1 to 9.

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