Hydraulic stability-based mixer intelligent speed regulation method, system and medium

Abstract

The application provides a mixer intelligent speed regulation method and system based on hydraulic stability, and a medium, and relates to the technical field of hydraulic stability control.The method comprises the following steps: real-time monitoring of fluid at the inlet of a mixer, obtaining a real-time fluid parameter set, introducing real-time rotating speed of the mixer to perform load calculation on the mixer, determining a real-time load torque parameter, setting a target mixing quality index to determine a target mixing efficiency, performing speed regulation calculation according to the real-time load torque parameter in combination with the target mixing efficiency, generating a speed regulation control signal, obtaining a speed regulation control result, performing rotating speed verification on the real-time fluid parameter set in the reverse direction, and formulating a dynamic speed regulation instruction to perform adaptive speed regulation on the mixer.The technical problem that the prior art cannot dynamically adjust the rotating speed of the mixer according to real-time characteristics of fluid, resulting in unstable product mixing quality, is solved.The technical effect of accurate adaptive regulation and control of the rotating speed of the mixer, improvement of product mixing quality and production efficiency, and guarantee of hydraulic stability is achieved.

Description

Technical Field

[0001] This invention relates to the field of hydraulic stability control technology, specifically to a method, system, and medium for intelligent speed regulation of mixers based on hydraulic stability. Background Technology

[0002] In industrial production, mixers are widely used in chemical, pharmaceutical, and food processing industries to mix fluids with different components. The accuracy of mixer speed control directly affects the uniformity of fluid mixing, reaction efficiency, and final product quality. Traditional mixer speed control methods mainly rely on fixed speed settings or simple manual adjustment. On the one hand, fixed speed settings cannot be dynamically adjusted according to the real-time characteristics of the fluid, resulting in unstable mixing quality and difficulty in achieving the expected mixing effect. On the other hand, manual speed adjustment is not only inefficient but also difficult to control precisely, and improper operation can easily affect mixing quality and production efficiency.

[0003] Existing technologies have technical problems such as the inability to dynamically adjust the mixer speed according to the real-time characteristics of the fluid, low efficiency and inaccuracy of manual adjustment, resulting in unstable mixing quality. Summary of the Invention

[0004] The purpose of this application is to provide a method, system and medium for intelligent speed regulation of mixers based on hydraulic stability, in order to solve the technical problems of existing technologies that cannot dynamically adjust the mixer speed according to the real-time characteristics of the fluid, and that manual adjustment is inefficient and inaccurate, resulting in unstable mixing quality.

[0005] In view of the above problems, this application provides a method, system and medium for intelligent speed regulation of mixers based on hydraulic stability.

[0006] The first aspect of this application provides an intelligent speed regulation method for a hydraulically stable mixer. The method includes: real-time monitoring of the fluid at the mixer inlet to obtain a real-time fluid parameter set; incorporating the real-time rotational speed of the mixer to perform load calculations on the mixer and determine real-time load torque parameters; setting a target mixing quality index; performing mixing analysis on the real-time fluid parameter set to determine a target mixing efficiency; performing speed regulation calculations based on the real-time load torque parameters and the target mixing efficiency to generate a speed regulation control signal, the speed regulation control signal including a target rotational speed value; executing the target rotational speed value to drive the mixer to adjust its speed; obtaining the speed regulation control result to verify the rotational speed against the real-time fluid parameter set; and formulating a dynamic speed regulation command to adaptively regulate the speed of the mixer.

[0007] Optionally, a pressure transmitter installed on the mixer inlet pipe continuously acquires fluid pressure fluctuation signals, performs mean filtering on the fluid pressure fluctuation signals to obtain fluid pressure values; a temperature sensor installed on the mixer inlet pipe continuously acquires fluid temperature fluctuation signals, performs calibration and compensation on the fluid temperature fluctuation signals to obtain fluid temperature values; fluid physical properties are analyzed based on the fluid temperature values ​​to calculate fluid viscosity values; the mixer's drive shaft is sensed in real time to obtain the mixer's real-time rotational speed, and load calculations are performed based on the mixer's real-time rotational speed combined with the fluid pressure values, fluid temperature values, and fluid viscosity values ​​to obtain the real-time load torque parameters.

[0008] Optionally, the real-time rotational speed of the mixer is cross-fused with the fluid pressure, fluid temperature, and fluid viscosity values ​​to construct a multi-dimensional operating condition feature vector based on the fusion result; historical multi-dimensional operating condition parameter sets are introduced to perform multi-condition load calculations to obtain a calibration dataset; operating condition identification is performed based on the multi-dimensional operating condition feature vector to determine the target operating condition category data; the target operating condition category data is used as an index to retrieve the calibration dataset to obtain the real-time load torque parameter.

[0009] Optionally, a target mixing quality index is set, which is the component uniformity or particle size distribution of the fluid at the mixer outlet; pressure and temperature fluctuation analysis is performed according to the component uniformity, and pressure uniform fluctuation threshold and temperature uniform fluctuation threshold are set; viscosity analysis is performed according to the particle size distribution, and fluid viscosity threshold is set; the fluid pressure value is compared with the pressure uniform fluctuation threshold to calculate the pressure fluctuation amplitude; the fluid temperature value is compared with the temperature uniform fluctuation threshold to calculate the temperature fluctuation amplitude; the fluid viscosity value is compared with the fluid viscosity threshold to calculate the fluid viscosity state parameter; mixing analysis is performed based on the pressure fluctuation amplitude, the temperature fluctuation amplitude, and the fluid viscosity state parameter to obtain the mixing difficulty analysis result; the mixing difficulty analysis result is used to traverse the mixer performance spectrum for matching to determine the target mixing efficiency.

[0010] Optionally, a speed regulation strategy database is constructed. The real-time load torque parameter and the target mixing efficiency are used as input conditions and synchronized to the speed regulation strategy database for multi-condition matching queries to generate a recommended speed value. The recommended speed value is converted into a standard electrical signal, and the mixer is speed-regulated using the standard electrical signal to generate an initial speed regulation signal. Based on the initial speed regulation signal, historical speed values ​​of adjacent cycles are retrieved according to the speed cycle. The difference between the recommended speed value and the historical speed value is compared to verify whether the speed difference exceeds a preset speed limit. When the speed difference exceeds the preset speed limit, the recommended speed value is restricted to within the historical speed value to generate a target speed value. When the speed difference does not exceed the preset speed limit, the recommended speed value is used as the target speed value.

[0011] Optionally, multiple load torque parameters and multiple mixing efficiencies of the mixer under different operating conditions are retrieved. Operational tests are conducted based on these parameters to extract stable operating speed points. The load torque parameters and mixing efficiencies are then integrated based on these stable operating speed points to construct raw data pairs. These raw data pairs are cleaned and categorized, and the load torque parameters and mixing efficiencies are used as a joint primary key to construct a speed control strategy database. The real-time load torque parameters and the target mixing efficiency are used as input conditions to form a query vector. The speed control strategy database is traversed according to the query vector, and the joint primary key is compared to obtain the comparison results. Euclidean distance is calculated based on the comparison results, and the recommended speed value is determined according to the distance parameter.

[0012] Optionally, the target speed value is used to drive the mixer to adjust its speed. Data is collected at the mixer inlet based on the speed control result to obtain a set of speed-adjusting fluid parameters. The set of speed-adjusting fluid parameters is then compared with the real-time fluid parameter set. Speed ​​verification is performed based on the comparison results to generate speed adjustment effect data. The effectiveness of the target speed value is evaluated based on the speed adjustment effect data. Scheduling analysis is performed based on the evaluation results to set a recommended speed adjustment step size. Speed ​​adjustment reciprocating analysis is performed according to the recommended speed adjustment step size to determine the speed adjustment cycle. The target speed value is decomposed according to the speed adjustment cycle and the recommended speed adjustment step size to obtain a continuous speed adjustment command. The continuous speed adjustment commands are correlated and integrated to formulate the dynamic speed adjustment command.

[0013] Optionally, the speed-regulating fluid pressure, temperature, and viscosity values ​​are retrieved based on the speed-regulating fluid parameter set; the fluid pressure, temperature, and viscosity values ​​are retrieved based on the real-time fluid parameter set; the absolute value of the change is obtained by comparing the speed-regulating fluid pressure, temperature, and viscosity values ​​with the fluid pressure, temperature, and viscosity values; a change expectation threshold is set, and the absolute value of the change is compared with the change expectation threshold. If the absolute value of the change is less than or equal to the change expectation threshold, the speed regulation control result is determined to meet the expected parameters, and the speed-regulating fluid parameter set is verified for stability to generate the speed regulation effect data; if the absolute value of the change is greater than the change expectation threshold, the speed regulation control result is determined to have failed to meet the expected parameters, and the speed regulation fluid parameter set is verified for abnormal fluctuations to generate the speed regulation effect data.

[0014] A second aspect of this application provides an intelligent speed control system for a hydraulically stable mixer. The system includes: a data calculation module for real-time monitoring of the fluid at the mixer inlet, obtaining a real-time fluid parameter set, incorporating the real-time speed of the mixer to perform load calculations, and determining real-time load torque parameters; a data analysis module for setting a target mixing quality index, performing mixing analysis on the real-time fluid parameter set, and determining a target mixing efficiency; a control signal generation module for performing speed control calculations based on the real-time load torque parameters and the target mixing efficiency, generating a speed control signal containing a target speed value; and a speed control module for executing the target speed value to drive the mixer to adjust its speed, obtaining the speed control result to verify the speed of the real-time fluid parameter set, and formulating dynamic speed control commands to adaptively adjust the speed of the mixer.

[0015] A third aspect of this application provides a computer-readable storage medium storing a computer program that, when executed, implements the steps of the hydraulically stable mixer intelligent speed regulation method described in any one of the first aspects above.

[0016] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0017] The method provided in this application embodiment obtains a real-time fluid parameter set by real-time monitoring of the fluid at the mixer inlet. It then uses the real-time speed of the mixer to calculate the load and determine the real-time load torque parameter. A target mixing quality index is set, and the real-time fluid parameter set is analyzed to determine the target mixing efficiency. Based on the real-time load torque parameter and the target mixing efficiency, speed regulation calculations are performed to generate a speed control signal, which includes the target speed value. The target speed value is then executed to drive the mixer to adjust its speed. The speed control result is used to verify the speed of the real-time fluid parameter set, and a dynamic speed regulation command is formulated to adaptively adjust the speed of the mixer. This achieves precise adaptive control of the mixer speed, improving product mixing quality and production efficiency while ensuring hydraulic stability.

[0018] The above description is merely an overview of the technical solution of this application. To enable a clearer understanding of the technical means of this application and to facilitate its implementation according to the description, and to make the above and other objects, features, and advantages of this application more apparent, specific embodiments of this application are described below. It should be understood that the content described in this section is not intended to identify key or important features of the embodiments of this application, nor is it intended to limit the scope of this application. Other features of this application will become readily apparent through the following description. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are merely exemplary. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 A flowchart illustrating the intelligent speed regulation method for a hydraulically stable mixer provided in this application.

[0021] Figure 2 A schematic diagram of the intelligent speed control system for a hydraulically stabilized mixer provided in this application.

[0022] Explanation of reference numerals in the attached diagram: Data calculation module 11, data analysis module 12, control signal generation module 13, speed control module 14. Detailed Implementation

[0023] This application provides a method, system, and medium for intelligent speed control of mixers based on hydraulic stability. It addresses the technical problems of existing technologies, such as the inability to dynamically adjust mixer speed according to real-time fluid characteristics, and the low efficiency and inaccuracy of manual adjustment, leading to unstable mixing quality. The method achieves precise adaptive control of mixer speed, improving product mixing quality and production efficiency while ensuring hydraulic stability.

[0024] The technical solutions of the present invention will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, and not all of them. It should be understood that the present invention is not limited to the exemplary embodiments described herein. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention. It should also be noted that, for ease of description, only the parts related to the present invention are shown in the accompanying drawings, not all of them.

[0025] Example 1, as Figure 1 As shown, this application provides a hydraulically stable intelligent speed control method for mixers, which includes:

[0026] The fluid at the mixer inlet is monitored in real time to obtain a set of real-time fluid parameters. The real-time rotational speed of the mixer is then used to calculate the load on the mixer and determine the real-time load torque parameters.

[0027] Furthermore, the fluid at the mixer inlet is monitored in real time to obtain a real-time fluid parameter set. The real-time rotational speed of the mixer is then used to calculate the load on the mixer to determine the real-time load torque parameter. The method includes: continuously acquiring fluid pressure fluctuation signals through a pressure transmitter installed on the mixer inlet pipeline; performing mean filtering on the fluid pressure fluctuation signals to obtain the fluid pressure value; continuously acquiring fluid temperature fluctuation signals through a temperature sensor installed on the mixer inlet pipeline; calibrating and compensating the fluid temperature fluctuation signals to obtain the fluid temperature value; performing fluid physical property analysis based on the fluid temperature value to calculate the fluid viscosity value; and real-time sensing of the mixer's drive shaft to obtain the real-time rotational speed of the mixer. The load is then calculated based on the real-time rotational speed of the mixer combined with the fluid pressure value, the fluid temperature value, and the fluid viscosity value to obtain the real-time load torque parameter.

[0028] Specifically, a mixer typically consists of three parts: an inlet pipe, a mixing chamber, and an outlet pipe. Its working principle is based on fluid mechanics and mass and heat transfer principles. The rotation of the impeller generates shear force and turbulence, achieving thorough mixing of different fluid components. A pressure transmitter is installed at the mixer inlet pipe. This pressure transmitter is a sensor that converts fluid pressure signals into electrical signals. It continuously acquires fluid pressure fluctuation signals, obtaining real-time information on fluid pressure changes. The acquired fluid pressure fluctuation signals are then subjected to mean filtering. Mean filtering is a common signal processing technique that calculates the average value of the fluid pressure fluctuation signal within a certain time window to remove noise and interference, resulting in a more stable and accurate fluid pressure value. For example, the arithmetic mean of fluid pressure fluctuation signals acquired from 10 consecutive sampling points can effectively suppress periodic noise. After mean filtering, the obtained fluid pressure value accurately reflects the pressure state of the fluid at the mixer inlet. Simultaneously, a temperature sensor installed in the mixer inlet pipe continuously acquires the fluid temperature in the inlet pipe, obtaining fluid temperature fluctuation signals. Because temperature sensors are affected by changes in ambient temperature during actual use, leading to deviations in measurement results, calibration and compensation are performed on the collected fluid temperature fluctuation signals. For example, a high-precision ambient temperature reference sensor can be added near the temperature sensor's installation location to collect ambient temperature data in real time. Simultaneously, a temperature-error mapping table for the fluid temperature sensor is established using historical data. The measurement error correction amount for the fluid temperature in the current inlet pipe is then retrieved based on the real-time ambient temperature value and, combined with the fluid temperature fluctuation signal, is calculated using formula T. 校准 =T 原始 −ΔT(T 环境), where ΔT is the correction amount obtained from the lookup table, achieving dynamic compensation to obtain the final fluid pressure value. A standardized physical property database of common fluids, such as water, oil, and polymer solutions, is pre-constructed, storing viscosity-temperature experimental data of each fluid within a specific temperature range. By inputting the fluid medium in the current mixer inlet pipe, based on the fluid temperature value as input, the corresponding viscosity benchmark value is queried from the standardized physical property database. If the fluid is a non-Newtonian fluid, such as a shear-thinning fluid, a shear rate correction term calculated based on the real-time rotational speed is further superimposed. By analyzing the fluid physical properties of the corrected fluid temperature value, the corresponding fluid viscosity value is calculated, reflecting the magnitude of the fluid's internal resistance. The collected and calculated fluid pressure data, fluid temperature data, and fluid viscosity value are integrated to obtain a real-time fluid parameter set. The rotational speed of the mixer drive shaft is collected in real time by a speed sensor installed on the drive shaft to obtain the real-time mixer rotational speed. Then, the obtained real-time mixer rotational speed is combined with the fluid pressure value, fluid temperature value, and fluid viscosity value to perform load calculation, thereby determining the real-time load torque parameter. By monitoring the inlet fluid and calculating the load in real time, the current operating status and load of the mixer can be accurately obtained, thus providing accurate and reliable data support for the adaptive speed regulation of the mixer and improving mixing quality and production efficiency.

[0029] Furthermore, the real-time load torque parameter is obtained by calculating the load based on the real-time rotational speed of the mixer combined with the fluid pressure, fluid temperature, and fluid viscosity values. The method includes: cross-fusion of the real-time rotational speed of the mixer with the fluid pressure, fluid temperature, and fluid viscosity values; constructing a multi-dimensional operating condition feature vector based on the fusion result; introducing a historical multi-dimensional operating condition parameter set for multi-condition load calculation to obtain a calibration dataset; identifying the operating condition based on the multi-dimensional operating condition feature vector to determine the target operating condition category data; and using the target operating condition category data as an index to retrieve the calibration dataset to obtain the real-time load torque parameter.

[0030] Specifically, a data fusion algorithm is employed to cross-fuse the real-time mixer speed, fluid pressure, fluid temperature, and fluid viscosity values ​​obtained from the collected calculations. For example, by using a synchronization signal, the sampling timestamps of the real-time mixer speed, fluid pressure, fluid temperature, and fluid viscosity values ​​are aligned to the same time baseline. Then, fusion algorithms such as Kalman filtering and particle filtering are used to integrate multiple data of different types to obtain the fusion result. The fused dataset is represented as a vector form, forming a multi-dimensional operating condition feature vector. This multi-dimensional operating condition feature vector contains information from multiple dimensions, such as the real-time mixer speed, fluid pressure, fluid temperature, and fluid viscosity values, which can comprehensively reflect the operating status of the mixer under the current operating conditions. Historical multi-dimensional data of the mixer under different operating conditions is collected to form a historical multi-dimensional operating condition parameter set. This historical multi-dimensional operating condition parameter set includes mixer speed, fluid pressure, fluid temperature, and fluid viscosity values. Through experimental or simulation methods, the mixer is run under different operating conditions, and the corresponding load torque data is calculated to form a calibration dataset. Historical feature data is divided into multiple typical operating condition categories using K-means clustering, such as high viscosity-high speed and low pressure-variable temperature. Based on the constructed multi-dimensional operating condition feature vector, the Mahalanobis distance between the multi-dimensional operating condition feature vector and the center of each operating condition cluster is calculated in real time to determine the target operating condition category data. Then, using the target operating condition category as an index, the most similar historical feature vector is found by searching and matching from the calibration dataset using a nearest neighbor search algorithm. The corresponding operating condition load is directly output as the real-time load torque parameter, enabling fast and accurate acquisition of the real-time load torque parameter corresponding to the current operating condition category, thereby improving the accuracy and effectiveness of the mixer's adaptive speed control.

[0031] Set a target mixing quality index, perform mixing analysis on the real-time fluid parameter set, and determine the target mixing efficiency.

[0032] Furthermore, a target mixing quality index is set, and a mixing analysis is performed on the real-time fluid parameter set to determine the target mixing efficiency. The method includes: setting a target mixing quality index, where the target mixing quality index is the component uniformity or particle size distribution of the fluid at the mixer outlet; performing pressure and temperature fluctuation analysis based on the component uniformity, and setting pressure uniform fluctuation thresholds and temperature uniform fluctuation thresholds; performing viscosity analysis based on the particle size distribution, and setting a fluid viscosity threshold; comparing the fluid pressure value with the pressure uniform fluctuation threshold to calculate the pressure fluctuation amplitude; comparing the fluid temperature value with the temperature uniform fluctuation threshold to calculate the temperature fluctuation amplitude; comparing the fluid viscosity value with the fluid viscosity threshold to calculate the fluid viscosity state parameter; performing a mixing analysis based on the pressure fluctuation amplitude, the temperature fluctuation amplitude, and the fluid viscosity state parameter to obtain a mixing difficulty analysis result; and matching the mixer performance spectrum according to the mixing difficulty analysis result to determine the target mixing efficiency.

[0033] Specifically, based on the mixing process requirements, target mixing quality indicators are set. These indicators refer to the mixing quality standards that the fluid exiting the mixer should achieve, including component uniformity or particle size distribution. Component uniformity reflects the evenness of the distribution of each component in the mixed fluid, while particle size distribution reflects the size distribution of particles in the mixed fluid. When using component uniformity as the target mixing quality indicator, pressure fluctuations can cause changes in fluid turbulence intensity, thus affecting the component diffusion rate. Temperature fluctuations can change fluid density and surface tension, indirectly interfering with mixing uniformity. Therefore, pressure and temperature fluctuations are analyzed, and based on historical data analysis results and the mixer's process requirements, pressure uniformity fluctuation thresholds and temperature uniformity fluctuation thresholds are set as boundary conditions for stable operation. When using particle size distribution as the target mixing quality indicator, fluid viscosity analysis is performed. Since fluid viscosity affects particle dispersion, excessively high viscosity can hinder particle movement and lead to agglomeration. Therefore, a fluid viscosity threshold is set to ensure effective particle dispersion. The fluid pressure, temperature, and viscosity values ​​are then compared with preset pressure uniform fluctuation thresholds, temperature uniform fluctuation thresholds, and viscosity thresholds, respectively, to calculate the pressure fluctuation amplitude, temperature fluctuation amplitude, and fluid viscosity parameters. A mixing analysis is then performed based on these parameters to assess the difficulty encountered during mixing, yielding a mixing difficulty analysis result. This result reflects the ease with which the mixer achieves the target mixing quality under current operating conditions. For example, the pressure fluctuation amplitude, temperature fluctuation amplitude, and fluid viscosity parameters are normalized and mapped to a unified numerical range. Then, weighting coefficients are assigned based on the influence of each parameter on the mixing difficulty. The normalized parameters are multiplied by their corresponding weights and summed to obtain the mixing difficulty analysis result. A result closer to 1 indicates higher mixing difficulty, while a result closer to 0 indicates ideal mixing conditions, meaning that multiple parameters do not exceed the thresholds. Using real-time fluid parameter sets and mixing difficulty analysis results as query criteria, a matching search is performed in a pre-built mixer performance map database. By calculating the Euclidean distance or cosine similarity between the real-time fluid parameters and mixing difficulty and the historical operating condition records in the mixer performance map database, all historical mixing efficiency values ​​that can achieve the target mixing quality index under the same or similar fluid parameters and mixing difficulty are found. From all historical mixing efficiency values ​​that meet the conditions, the efficiency value with the smallest value is selected and determined as the target mixing efficiency. The mixer performance map is a collection of mixer performance data under different operating conditions, reflecting the mixing efficiency of the mixer under different operating conditions.By setting target mixing quality indicators and conducting mixing analysis, the degree of difficulty encountered in the mixing process can be accurately assessed, thereby determining the target mixing efficiency. This provides an accurate and reliable basis for the speed control of the mixer, enabling the mixer to automatically adjust to the optimal operating state under different working conditions in order to achieve or approach the target mixing efficiency.

[0034] Speed ​​regulation calculations are performed based on the real-time load torque parameters and the target mixing efficiency to generate a speed regulation control signal, which includes the target speed value.

[0035] Furthermore, a speed regulation strategy database is constructed. The real-time load torque parameter and the target mixing efficiency are used as input conditions and synchronized to the speed regulation strategy database for multi-condition matching queries to generate a recommended speed value. The recommended speed value is converted into a standard electrical signal, and the mixer is speed-regulated using the standard electrical signal to generate an initial speed regulation signal. Based on the initial speed regulation signal, historical speed values ​​of adjacent cycles are retrieved according to the speed cycle. The difference between the recommended speed value and the historical speed value is compared to verify whether the speed difference exceeds a preset speed limit. When the speed difference exceeds the preset speed limit, the recommended speed value is restricted to within the historical speed value to generate a target speed value. When the speed difference does not exceed the preset speed limit, the recommended speed value is used as the target speed value.

[0036] Specifically, the mixer is operated under various operating conditions, collecting multiple load torque parameters and mixing efficiency values, and recording the stable operating speed point for each condition. The load torque parameters and target mixing efficiency are used as a joint primary key to construct raw data pairs. After cleaning and classification, a speed control strategy database is built. This database contains a set of data on the mixer's load torque parameters, target mixing efficiency, and corresponding speed values ​​under different operating conditions. Real-time load torque parameters and the target mixing efficiency are used as input conditions and synchronized to the speed control strategy database for multi-condition matching queries to obtain recommended speed values. These recommended speed values ​​are then converted into standard electrical signals according to the PWM duty cycle versus speed calibration curve. These standard electrical signals are signals that can be recognized and executed by the mixer's speed control driver, and are either voltage or current signals. The standard electrical signals are input to the mixer's speed control driver to adjust the mixer's speed, generating an initial speed control signal. Based on this initial speed control signal, historical speed values ​​from adjacent cycles are retrieved according to the speed cycle, where the speed cycle refers to the time interval for adjusting the mixer's speed, for example, recording a speed value once per minute. Then, the difference between the recommended speed value and the historical speed value is compared. The calculation results verify whether the speed difference exceeds the preset speed limit. The preset speed limit is the maximum allowable speed variation range set according to the mechanical characteristics and process requirements of the mixer, used to prevent damage to the mixer caused by excessively rapid speed changes. When the difference does not exceed the preset speed limit, the recommended speed value is directly output as the target speed value. When the speed difference exceeds the preset speed limit, speed limiting processing is used to restrict the recommended speed value to within the historical speed value, generating the target speed value. For example, if the preset speed limit is 2 rad / s, the historical speed value is 9 rad / s, the recommended speed value is 10 rad / s, and the speed difference is 1 rad / s, which does not exceed the preset speed limit. The recommended speed value is directly set as the target speed value, and the target speed value is 10 rad / s. If the recommended speed value is 12 rad / s, the historical speed value is 8 rad / s, and the preset speed limit is 2 rad / s, then the target speed value should be limited to 10 rad / s.

[0037] By constructing a speed regulation strategy database and using multi-condition matching queries, suitable recommended speed values ​​can be found quickly and accurately. By retrieving historical speed values ​​and comparing the differences, it is ensured that speed changes are within a safe range, preventing damage to the mixer. Furthermore, the generated target speed value can drive the mixer to perform precise speed regulation, ensuring that the mixer achieves the target mixing efficiency under different operating conditions, thereby improving mixing quality and production efficiency.

[0038] Furthermore, the method for constructing the speed regulation strategy database, using the real-time load torque parameters and the target mixing efficiency as input conditions, and synchronizing them to the speed regulation strategy database for multi-condition matching queries to generate recommended speed values, includes: retrieving multiple load torque parameters and multiple mixing efficiencies of the mixer under different operating conditions; conducting operational tests based on the multiple load torque parameters and multiple mixing efficiencies to extract stable operating speed points; integrating the multiple load torque parameters and multiple mixing efficiencies according to the stable operating speed points to construct original data pairs; cleaning and classifying the original data pairs, using the multiple load torque parameters and multiple mixing efficiencies as joint primary keys to construct the speed regulation strategy database; using the real-time load torque parameters and the target mixing efficiency as input conditions to form a query vector; traversing the speed regulation strategy database according to the query vector to compare the joint primary keys and obtain comparison results; calculating Euclidean distance based on the comparison results, and determining the recommended speed value based on the distance parameter.

[0039] Specifically, the mixer is operated under various operating conditions to collect multiple load torque parameters and mixing efficiency values. The stable operating speed point for each operating condition is recorded. The stable operating speed refers to the speed at which the mixer can operate stably and achieve the target mixing efficiency under a specific operating condition. Based on the collected data, the stable operating speed point, load torque parameters, and mixing efficiency are integrated to construct raw data pairs. Each data pair contains a load torque value, a mixing efficiency value, and a corresponding stable operating speed value. The raw data pairs are cleaned to remove outliers, ensuring data accuracy and consistency. Then, the K-means clustering algorithm is used to merge and classify the cleaned data according to similar operating conditions. The load torque parameters and mixing efficiency are used as a joint primary key to construct a speed regulation strategy database. The joint primary key ensures that each combination of load torque and mixing efficiency corresponds to a recommended speed value. After the speed regulation strategy database is constructed, real-time load torque parameters and target mixing efficiency are used as input conditions to form a query vector. This query vector contains the load torque parameters and mixing efficiency under the current operating condition and is used to query the speed regulation strategy database. The speed regulation strategy database is traversed according to the query vector, and the composite primary key is compared to obtain the comparison results. If a record in the database completely matches the query vector, the corresponding recommended speed value is directly obtained. If no record completely matches, Euclidean distance is calculated based on the comparison results. Euclidean distance is a method used to measure the distance between two points and can be used to evaluate the similarity between the query vector and the records in the database. By calculating the Euclidean distance between the query vector and each record, the record with the closest distance is found, thereby determining the recommended speed value.

[0040] By constructing a speed regulation strategy database and using multi-condition matching queries, suitable recommended speed values ​​can be found quickly and accurately. Simultaneously, through Euclidean distance calculation, the closest recommended speed value can be found even when no perfectly matching record exists. This allows the mixer to automatically adjust to its optimal operating state under different working conditions, improving the accuracy and reliability of the mixer's speed control, thereby enhancing mixing quality and production efficiency.

[0041] The target speed value is executed to drive the mixer to adjust its speed. The speed control result is then used to verify the speed of the real-time fluid parameter set. Dynamic speed control commands are then formulated to adaptively adjust the speed of the mixer.

[0042] Furthermore, the target speed value is used to drive the mixer to adjust its speed, and the speed control result is used to verify the speed of the real-time fluid parameter set. A dynamic speed control command is then formulated. The method includes: executing the target speed value to drive the mixer to adjust its speed; collecting data at the mixer inlet based on the speed control result to obtain a speed-adjusting fluid parameter set; comparing the speed-adjusting fluid parameter set with the real-time fluid parameter set, verifying the speed based on the comparison result, and generating speed adjustment effect data; evaluating the effectiveness of the target speed value based on the speed adjustment effect data, performing scheduling analysis based on the evaluation result, and setting a recommended speed adjustment step size; performing a reciprocating speed adjustment analysis according to the recommended speed adjustment step size to determine the speed adjustment cycle; decomposing the target speed value and the recommended speed adjustment step size according to the speed adjustment cycle to obtain a continuous speed adjustment command; and associating and integrating the continuous speed adjustment commands to formulate the dynamic speed control command.

[0043] Specifically, the target rotational speed is converted into a corresponding electrical signal by a speed-regulating driver. The speed-regulating driver adjusts the motor speed according to the target rotational speed to ensure the mixer operates at the target speed. After the target rotational speed is achieved, parameters such as fluid pressure, fluid temperature, and fluid viscosity are monitored and collected in real time in the mixer inlet pipeline to obtain a speed-regulating fluid parameter set. This set refers to the real-time parameter set of the fluid in the mixer inlet pipeline at the target rotational speed, reflecting the mixer's operating state at that speed. Then, the speed-regulating fluid parameter set is compared and analyzed with the real-time fluid parameter set to calculate the changes in fluid pressure, temperature, and viscosity, obtaining a comparison result. The mixer's rotational speed is verified based on the comparison result, generating speed regulation effect data. This data reflects the changes in fluid parameters after speed regulation. Based on the parameter changes in the speed regulation effect data, a weighted scoring algorithm is used to quantitatively evaluate the effectiveness of the target rotational speed. In the weighted scoring algorithm, different weights are assigned to each parameter according to their importance to the mixing effect; for example, if fluid pressure has a greater impact on mixing quality, it is given a higher weight. By calculating the deviations of each parameter's change from a preset threshold and multiplying them by their respective weights, a comprehensive score is obtained. If the comprehensive score exceeds the preset threshold, the speed regulation is deemed effective, and the current speed is maintained. If the score is below the preset threshold, it indicates that the speed regulation effect has not met expectations. Using a fuzzy inference engine, based on the evaluation results and considering factors such as the mixer's operating status, historical data, and process requirements, a recommended speed regulation step size is dynamically set. The recommended speed regulation step size refers to the suggested speed adjustment range under the current operating conditions. The fuzzy inference engine handles uncertainty and fuzziness through fuzzy logic, enabling flexible adjustment of the recommended speed regulation step size according to different operating conditions. This achieves adaptive speed regulation of the mixer, ensuring efficient and stable operation of the mixer under various conditions. Speed ​​regulation reciprocating analysis is performed according to the recommended speed regulation step size. By simulating the speed regulation process under different step sizes, the mixer response is analyzed, including the smoothness of speed change, the time required to reach the target speed, and the vibration of the mixer during the speed regulation process. A comprehensive analysis of the speed regulation response speed and mixer stability is conducted to determine an optimal speed regulation cycle. The speed regulation cycle refers to the time interval for speed regulation verification at different speeds, used to control the frequency of the speed regulation process and prevent parameter fluctuations due to an excessively short cycle. After determining the speed regulation cycle, the target speed value is decomposed into continuous speed regulation commands according to the recommended step size. For example, if the speed regulation cycle is 1 second, the target speed is 10 rad / s, the current speed is 9 rad / s, and the recommended speed regulation step size is 0.5 rad / s, then the speed regulation process can be decomposed into the following steps: 1st second: Adjust the speed from 9 rad / s to 9.5 rad / s. 2nd second: Adjust the speed from 9.5 rad / s to 10 rad / s. After each adjustment, wait 1 second to ensure speed stability. Continuous speed control commands refer to a sequence of commands that gradually adjust the speed within a speed control cycle.By integrating various instructions through timestamp association, a dynamic speed control command containing rotational speed, execution time, and step size is generated to guide the mixer's speed adjustment process. This dynamic speed control command enables adaptive speed regulation of the mixer, achieving precise matching between the mixer's rotational speed and the fluid state.

[0044] By executing target speed values ​​to drive the mixer through speed regulation and verifying the speed regulation effect, it is possible to evaluate in real time whether the speed regulation has achieved the expected mixing effect. Based on the speed regulation effect data, effectiveness evaluation and scheduling analysis can be performed to dynamically adjust the speed regulation step size and speed regulation cycle, ensuring that the mixer achieves optimal operating conditions under different operating conditions. By generating continuous speed regulation commands and formulating dynamic speed regulation commands, smooth adaptive speed regulation of the mixer can be achieved, thereby improving the mixing quality and production efficiency of the mixer.

[0045] Furthermore, the speed-regulating fluid parameter set is compared and analyzed against the real-time fluid parameter set in reverse. Speed ​​verification is performed based on the comparison results to generate speed regulation effect data. The method includes: retrieving the speed-regulating fluid pressure, temperature, and viscosity values ​​based on the speed-regulating fluid parameter set; retrieving the fluid pressure, temperature, and viscosity values ​​based on the real-time fluid parameter set; calculating the absolute value of the change by comparing the speed-regulating fluid pressure, temperature, and viscosity values ​​with the fluid pressure, temperature, and viscosity values; setting an expected threshold for the change; comparing the absolute value of the change with the expected threshold; if the absolute value of the change is less than or equal to the expected threshold, the speed regulation control result is determined to meet the expected parameters, and the speed-regulating fluid parameter set is verified for stability to generate the speed regulation effect data; if the absolute value of the change is greater than the expected threshold, the speed regulation control result is determined to have failed to meet the expected parameters, and the speed-regulating fluid parameter set is verified for abnormal fluctuations to generate the speed regulation effect data.

[0046] Specifically, after setting the target speed, data is collected at the mixer inlet to obtain a set of speed-regulating fluid parameters. Based on this set, the speed-regulating fluid pressure, temperature, and viscosity values ​​are retrieved. Simultaneously, the fluid pressure, temperature, and viscosity values ​​from the real-time fluid parameter set are retrieved. These values ​​are then compared with those from the real-time set, and the absolute value of the change in each parameter is calculated—the absolute difference between the parameter value after speed regulation and the parameter value before speed regulation. For example, the absolute value of the difference between the speed-regulating fluid pressure and the real-time fluid pressure is represented as |ΔP|, the absolute value of the difference between the speed-regulating fluid temperature and the real-time fluid temperature is represented as |ΔT|, and the absolute value of the difference between the speed-regulating fluid viscosity and the real-time fluid viscosity is represented as |Δη|. Based on the mixer's process requirements and speed regulation target, the expected threshold for the change in each parameter is determined. For example, set the pressure change threshold to P. th The threshold for temperature change is T. th The viscosity change threshold is η th The expected threshold for the change in parameters is used to determine whether the parameter changes after speed regulation are within the allowable range. The absolute value of the change is compared with the expected threshold. If the absolute value of the change in all parameters is less than or equal to the corresponding expected threshold, the speed regulation control result is determined to meet the expected parameters. Simultaneously, the stability of the speed regulation fluid parameter set is verified by continuously monitoring changes in fluid parameters to ensure that the fluid parameters remain stable over a period of time, generating speed regulation effect data. If the absolute value of the change in any parameter is greater than the corresponding expected threshold, the speed regulation control result is determined to have failed to meet the expected parameters. Statistical analysis methods, such as moving average and standard deviation, are used to verify abnormal fluctuations in the speed regulation fluid parameter set, analyze whether abnormal fluctuations exist, and generate speed regulation effect data. This data includes information such as the parameter changes after speed regulation, whether they meet the expected parameters, and whether abnormal fluctuations exist.

[0047] By comparing the fluid parameters before and after speed regulation, calculating the absolute value of the change, and comparing it with the expected threshold of the change, we can accurately assess whether the speed regulation has achieved the expected mixing effect, thereby improving the accuracy and reliability of mixer speed regulation control, ensuring that the mixer can achieve the best operating state under different working conditions, improving mixing quality and production efficiency, while ensuring hydraulic stability.

[0048] Example 2, based on the same inventive concept as the hydraulically stable intelligent speed regulation method for mixers in the foregoing examples, such as... Figure 2 As shown, this application provides a hydraulically stable intelligent speed control system for mixers, wherein the hydraulically stable intelligent speed control system for mixers includes:

[0049] The data calculation module 11 is used to monitor the fluid at the mixer inlet in real time, obtain a real-time fluid parameter set, and use the real-time speed of the mixer to calculate the load on the mixer and determine the real-time load torque parameter. The data analysis module 12 is used to set a target mixing quality index, perform mixing analysis on the real-time fluid parameter set, and determine the target mixing efficiency. The control signal generation module 13 is used to perform speed regulation calculation based on the real-time load torque parameter and the target mixing efficiency, and generate a speed regulation control signal, which includes a target speed value. The speed regulation control module 14 is used to execute the target speed value to drive the mixer to regulate its speed, obtain the speed regulation control result, verify the speed of the real-time fluid parameter set, and formulate a dynamic speed regulation command to adaptively regulate the speed of the mixer.

[0050] Furthermore, the data calculation module 11 in the hydraulically stable mixer intelligent speed control system is also used for: continuously acquiring fluid pressure fluctuation signals through a pressure transmitter installed in the mixer inlet pipeline, performing mean filtering on the fluid pressure fluctuation signals to obtain fluid pressure values; continuously acquiring fluid temperature fluctuation signals through a temperature sensor installed in the mixer inlet pipeline, performing calibration and compensation on the fluid temperature fluctuation signals to obtain fluid temperature values; performing fluid physical property analysis based on the fluid temperature values ​​to calculate fluid viscosity values; and real-time sensing of the mixer's drive shaft to obtain the mixer's real-time rotational speed, performing load calculation based on the mixer's real-time rotational speed combined with the fluid pressure values, fluid temperature values, and fluid viscosity values ​​to obtain the real-time load torque parameters.

[0051] Furthermore, the data calculation module 11 in the hydraulically stable mixer intelligent speed regulation system is also used to: perform cross-fusion of the real-time speed of the mixer with the fluid pressure value, the fluid temperature value, and the fluid viscosity value, and construct a multi-dimensional working condition feature vector based on the fusion result; introduce historical multi-dimensional working condition parameter sets to perform multi-working condition load calculations to obtain a calibration dataset; perform working condition identification based on the multi-dimensional working condition feature vector to determine the target working condition category data; and use the target working condition category data as an index to retrieve the calibration dataset to obtain the real-time load torque parameter.

[0052] Furthermore, the data analysis module 12 in the hydraulically stable mixer intelligent speed regulation system is also used for: setting a target mixing quality index, wherein the target mixing quality index is the component uniformity or particle size distribution of the fluid at the mixer outlet; performing pressure and temperature fluctuation analysis according to the component uniformity, and setting pressure uniform fluctuation threshold and temperature uniform fluctuation threshold; performing viscosity analysis according to the particle size distribution, and setting a fluid viscosity threshold; comparing the fluid pressure value with the pressure uniform fluctuation threshold to calculate the pressure fluctuation amplitude; comparing the fluid temperature value with the temperature uniform fluctuation threshold to calculate the temperature fluctuation amplitude; comparing the fluid viscosity value with the fluid viscosity threshold to calculate the fluid viscosity state parameter; performing mixing analysis based on the pressure fluctuation amplitude, the temperature fluctuation amplitude, and the fluid viscosity state parameter to obtain the mixing difficulty analysis result; and matching the mixer performance spectrum according to the mixing difficulty analysis result to determine the target mixing efficiency.

[0053] Furthermore, the control signal generation module 13 in the hydraulically stable mixer intelligent speed regulation system is also used to: construct a speed regulation strategy database, take the real-time load torque parameter and the target mixing efficiency as input conditions, synchronize them to the speed regulation strategy database for multi-condition matching query, and generate a recommended speed value; convert the recommended speed value into a standard electrical signal, and use the standard electrical signal to regulate the speed of the mixer to generate an initial speed regulation signal; retrieve historical speed values ​​of adjacent cycles according to the initial speed regulation signal; compare the difference between the recommended speed value and the historical speed value to verify whether the speed difference exceeds a preset speed limit; when the speed difference exceeds the preset speed limit, the recommended speed value is limited to the historical speed value to generate a target speed value; when the speed difference does not exceed the preset speed limit, the recommended speed value is used as the target speed value.

[0054] Furthermore, the control signal generation module 13 in the hydraulically stable mixer intelligent speed regulation system is also used for: retrieving multiple load torque parameters and multiple mixing efficiencies of the mixer under different operating conditions; performing operational tests based on the multiple load torque parameters and multiple mixing efficiencies to extract stable operating speed points; integrating the multiple load torque parameters and multiple mixing efficiencies according to the stable operating speed points to construct raw data pairs; cleaning and classifying the raw data pairs, using the multiple load torque parameters and multiple mixing efficiencies as joint primary keys to construct a speed regulation strategy database; using the real-time load torque parameters and the target mixing efficiency as input conditions to form a query vector; traversing the speed regulation strategy database according to the query vector to compare the joint primary keys and obtain comparison results; calculating Euclidean distance based on the comparison results, and determining the recommended speed value based on the distance parameters.

[0055] Furthermore, the speed control module 14 in the hydraulically stable mixer intelligent speed control system is also used for: executing the target speed value to drive the mixer to adjust its speed; collecting data from the mixer inlet based on the speed control result to obtain a speed-adjusting fluid parameter set; comparing the speed-adjusting fluid parameter set with the real-time fluid parameter set in reverse; verifying the speed based on the comparison result to generate speed adjustment effect data; evaluating the effectiveness of the target speed value based on the speed adjustment effect data; performing scheduling analysis based on the evaluation result to set a recommended speed adjustment step size; performing speed adjustment reciprocating analysis according to the recommended speed adjustment step size to determine the speed adjustment cycle; decomposing the target speed value and the recommended speed adjustment step size according to the speed adjustment cycle to obtain a continuous speed adjustment command; and associating and integrating the continuous speed adjustment command to formulate the dynamic speed adjustment command.

[0056] Furthermore, the speed control module 14 in the hydraulically stable mixer intelligent speed control system is also used for: retrieving the speed control fluid pressure value, speed control fluid temperature value, and speed control fluid viscosity value based on the speed control fluid parameter set; retrieving the fluid pressure value, fluid temperature value, and fluid viscosity value based on the real-time fluid parameter set; calculating the absolute value of the change by comparing the speed control fluid pressure value, speed control fluid temperature value, and speed control fluid viscosity value with the fluid pressure value, fluid temperature value, and fluid viscosity value; setting a change expectation threshold; comparing the absolute value of the change with the change expectation threshold; if the absolute value of the change is less than or equal to the change expectation threshold, it is determined that the speed control result meets the expected parameters, and the speed control fluid parameter set is stabilized to generate the speed control effect data; if the absolute value of the change is greater than the change expectation threshold, it is determined that the speed control result does not meet the expected parameters, and the speed control fluid parameter set is abnormally fluctuated to generate the speed control effect data.

[0057] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Figure 1 The intelligent speed regulation method and specific examples of the mixer based on hydraulic stability in Example 1 are also applicable to the intelligent speed regulation system of the mixer based on hydraulic stability in this embodiment. Through the foregoing detailed description of the intelligent speed regulation method of the mixer based on hydraulic stability, those skilled in the art can clearly understand the intelligent speed regulation system of the mixer based on hydraulic stability in this embodiment. Therefore, for the sake of brevity, it will not be described in detail here.

[0058] In Embodiment 3, based on the same inventive concept as the hydraulically stable intelligent speed regulation method for mixers in the foregoing embodiments, this application also provides a computer-readable storage medium storing a computer program, which, when executed, implements the steps of the hydraulically stable intelligent speed regulation method for mixers described in any one of Embodiment 1.

[0059] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0060] Obviously, those skilled in the art can make several improvements and modifications to this application without departing from the principles of this application, and these improvements and modifications also fall within the protection scope of this application.

Claims

1. A mixer intelligent speed regulation method based on hydraulic stability, characterized in that, The method comprises: Real-time monitoring of the fluid at the mixer inlet to obtain a real-time fluid parameter set, introducing a real-time rotational speed of the mixer to perform load calculation on the mixer to determine a real-time load torque parameter; Setting a target mixing quality index, performing mixing analysis on the real-time fluid parameter set to determine a target mixing efficiency; According to the real-time load torque parameter combined with the target mixing efficiency, a speed regulation calculation is performed to generate a speed regulation control signal, and the speed regulation control signal contains a target rotational speed value; Performing speed regulation driven by the target rotational speed value to drive the mixer to perform speed regulation, obtaining a speed regulation control result, and performing rotational speed verification on the real-time fluid parameter set in the reverse direction to formulate a dynamic speed regulation instruction to adaptively regulate the mixer; Real-time monitoring of the fluid at the mixer inlet to obtain a real-time fluid parameter set, introducing a real-time rotational speed of the mixer to perform load calculation on the mixer to determine a real-time load torque parameter, the method comprising: Continuous acquisition by a pressure transmitter installed on the mixer inlet pipeline to obtain a fluid pressure fluctuation signal, and mean filtering processing on the fluid pressure fluctuation signal to obtain a fluid pressure value; Continuous acquisition by a temperature sensor installed on the mixer inlet pipeline to obtain a fluid temperature fluctuation signal, and calibration compensation on the fluid temperature fluctuation signal to obtain a fluid temperature value; Based on the fluid temperature value, fluid physical property analysis is performed to calculate and obtain a fluid viscosity value; Real-time sensing of the transmission shaft of the mixer to obtain a real-time rotational speed of the mixer, and performing load calculation according to the real-time rotational speed of the mixer combined with the fluid pressure value, the fluid temperature value and the fluid viscosity value to obtain the real-time load torque parameter; According to the real-time rotational speed of the mixer combined with the fluid pressure value, the fluid temperature value and the fluid viscosity value, a load calculation is performed to obtain the real-time load torque parameter, the method comprising: Cross-fusion of the real-time rotational speed of the mixer combined with the fluid pressure value, the fluid temperature value and the fluid viscosity value, and construction of a multi-dimensional working condition feature vector according to the fusion result; Introducing a historical multi-dimensional working condition parameter set to perform multi-working condition load calculation to obtain a calibration data set; Based on the multi-dimensional working condition feature vector, working condition recognition is performed to determine target working condition category data; Taking the target working condition category data as an index to search the calibration data set to obtain the real-time load torque parameter.

2. The method of claim 1, wherein the mixer intelligent speed control is based on hydraulic stabilization. Setting a target mixing quality index, performing mixing analysis on the real-time fluid parameter set to determine a target mixing efficiency, the method comprising: Setting a target mixing quality index, the target mixing quality index being the uniformity of components or the particle size distribution of the fluid at the mixer outlet; According to the uniformity of components, fluctuation analysis of pressure and temperature is performed to set a pressure uniform fluctuation threshold and a temperature uniform fluctuation threshold; According to the particle size distribution, viscosity analysis is performed to set a fluid viscosity threshold; Comparing the fluid pressure value with the pressure uniform fluctuation threshold to calculate a pressure fluctuation amplitude; Comparing the fluid temperature value with the temperature uniform fluctuation threshold to calculate a temperature fluctuation amplitude; Comparing the fluid viscosity value with the fluid viscosity threshold to calculate a fluid viscosity state parameter; According to the pressure fluctuation amplitude, the temperature fluctuation amplitude, and the fluid viscosity state parameter, a mixed analysis is performed to obtain a mixed difficulty analysis result; According to the mixed difficulty analysis result, a mixer performance map is traversed for matching to determine the target mixing efficiency.

3. The method of claim 1, wherein the mixer intelligent speed control is based on hydraulic stabilization. According to the real-time load torque parameter and the target mixing efficiency, a speed regulation calculation is performed to generate a speed regulation control signal, and the method comprises: A speed regulation strategy database is constructed, the real-time load torque parameter and the target mixing efficiency are taken as input conditions, and the speed regulation strategy database is synchronously matched for multi-condition matching query to generate a recommended rotating speed value; The recommended rotating speed value is converted into a standard electrical signal, the mixer is regulated by the standard electrical signal to generate an initial speed regulation signal; Based on the initial speed regulation signal, a historical rotating speed value of an adjacent period is called according to a rotating speed period; The recommended rotating speed value is compared with the historical rotating speed value by difference, and it is verified whether a rotating speed difference value exceeds a preset rotating speed extreme value, when the rotating speed difference value exceeds the preset rotating speed extreme value, the recommended rotating speed value is limited within the historical rotating speed value to generate a target rotating speed value; When the rotating speed difference value does not exceed the preset rotating speed extreme value, the recommended rotating speed value is taken as the target rotating speed value.

4. The intelligent speed regulation method for a mixer based on hydraulic stability as described in claim 3, characterized in that, The method for constructing the speed regulation strategy database, taking the real-time load torque parameter and the target mixing efficiency as input conditions, synchronously matching the speed regulation strategy database for multi-condition matching query to generate a recommended rotating speed value, comprises: A plurality of load torque parameters and a plurality of mixing efficiencies of the mixer under different working conditions are called, running tests are performed based on the plurality of load torque parameters and the plurality of mixing efficiencies, and stable running rotating speed points are extracted; According to the stable running rotating speed points, the plurality of load torque parameters and the plurality of mixing efficiencies are integrated to construct an original data pair; The original data pair is cleaned and classified, the plurality of load torque parameters and the plurality of mixing efficiencies are taken as joint primary keys, and a speed regulation strategy database is constructed; The real-time load torque parameter and the target mixing efficiency are taken as input conditions to form a query vector; According to the query vector, the joint primary keys are compared in the speed regulation strategy database to obtain a comparison result; Based on the comparison result, an Euclidean distance calculation is performed, and the recommended rotating speed value is determined according to a distance parameter.

5. The method of claim 1, wherein the mixer intelligent speed control is based on hydraulic stabilization. The mixer is driven by the target rotating speed value to perform speed regulation, the real-time fluid parameter set is verified by a speed regulation control result, dynamic speed regulation instructions are formulated, and the method comprises: The mixer is driven by the target rotating speed value to perform speed regulation, data of a mixer inlet is collected according to a speed regulation control result to obtain a speed regulation fluid parameter set; The speed regulation fluid parameter set is compared with the real-time fluid parameter set in reverse to perform comparative analysis, a rotating speed verification is performed according to a comparison result to generate speed regulation effect data; Based on the speed regulation effect data, the target rotating speed value is evaluated for effectiveness, a recommended speed regulation step is set according to an evaluation result; According to the recommended speed regulation step, speed regulation is analyzed reciprocally to determine a speed regulation period; The target rotating speed value is decomposed according to the speed regulation period combined with the recommended speed regulation step to obtain a continuous speed regulation instruction; The continuous speed regulation instruction is associated and integrated to formulate the dynamic speed regulation instruction.

6. The method of claim 5, wherein the mixer intelligent speed control is based on hydraulic stabilization. The set of speed regulation fluid parameters is reversely compared with the set of real-time fluid parameters, speed verification is performed according to the comparison result, and speed regulation effect data is generated, the method comprising: The speed regulation fluid pressure value, the speed regulation fluid temperature value, and the speed regulation fluid viscosity value are called based on the set of speed regulation fluid parameters; The fluid pressure value, the fluid temperature value, and the fluid viscosity value are called based on the set of real-time fluid parameters; The change absolute value is obtained by comparing the speed regulation fluid pressure value, the speed regulation fluid temperature value, the speed regulation fluid viscosity value, the fluid pressure value, the fluid temperature value, and the fluid viscosity value; The change absolute value is compared with the change expected threshold value, when the change absolute value is less than or equal to the change expected threshold value, it is determined that the speed regulation control result meets the expected parameter, and the set of speed regulation fluid parameters is stably verified to generate the speed regulation effect data; When the change absolute value is greater than the change expected threshold value, it is determined that the speed regulation control result does not meet the expected parameter, and the set of speed regulation fluid parameters is abnormally verified to generate the speed regulation effect data.

7. A mixer intelligent speed control system based on hydraulic stability, characterized by, The steps of the method for implementing the intelligent speed regulation of the mixer based on hydraulic stability according to any one of claims 1 to 6, the intelligent speed regulation system of the mixer based on hydraulic stability comprising: A data calculation module for real-time monitoring of fluid at the inlet of the mixer to obtain a set of real-time fluid parameters, and introducing the real-time rotating speed of the mixer to calculate the load of the mixer to determine a real-time load torque parameter; A data analysis module for setting a target mixing quality index, and performing mixing analysis on the set of real-time fluid parameters to determine a target mixing efficiency; A control signal generation module for performing speed regulation calculation based on the real-time load torque parameter combined with the target mixing efficiency to generate a speed regulation control signal, the speed regulation control signal including a target rotating speed value; A speed regulation control module for driving the mixer to regulate speed by the target rotating speed value to obtain a speed regulation control result, reversely verifying the set of real-time fluid parameters, formulating a dynamic speed regulation instruction, and adaptively regulating the speed of the mixer.

8. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program implements the steps of the method for implementing the intelligent speed regulation of the mixer based on hydraulic stability according to any one of claims 1 to 6 when executed.

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