Lubricating material online quality closed-loop control method and system

Abstract

The invention discloses an online quality closed-loop control method and system for a lubricating material, and belongs to the technical field of production control. The optimal heating temperature estimated by equipment is estimated according to the initial kinematic viscosity and the preset target kinematic viscosity of the lubricating material at the standard temperature; the final target kinematic viscosity at the equipment estimation optimal heating temperature is analyzed according to the preset target kinematic viscosity at the standard temperature, so that the control target is aligned with the actual working condition, the accuracy of end point control is improved, the equipment estimation optimal stirring speed is estimated according to the initial kinematic viscosity and the final target kinematic viscosity, and the control accuracy is improved. The optimal stirring speed is estimated according to the real-time kinematic viscosity updating equipment, so that the adjustment of the stirring speed fits the production working condition, and the production efficiency and the product quality are improved.

Description

Technical Field

[0001] This invention relates to the field of production control technology, and in particular to a method and system for online closed-loop quality control of lubricating materials. Background Technology

[0002] In the production process of lubricating materials, the blending process is one of the key steps. It usually requires heating and stirring the materials to make their viscosity reach the preset target value. Kinematic viscosity is an important indicator for measuring the quality of lubricating materials and directly affects the performance of the products.

[0003] Currently, existing technologies mostly use fixed parameters or rely on manual experience to set and control the heating temperature and stirring speed during the blending process, resulting in insufficient production efficiency and quality in the blending stage. Summary of the Invention

[0004] To address the technical problems existing in the prior art, this invention provides an online closed-loop quality control method for lubricating materials, comprising the following steps: S1. Before heating and stirring in the mixing process, obtain the initial kinematic viscosity and the preset target kinematic viscosity of the lubricating material at the standard temperature, and estimate the optimal heating temperature of the equipment based on the initial kinematic viscosity and the preset target kinematic viscosity. S2. Analyze the final target kinematic viscosity at the equipment's estimated optimal heating temperature based on the preset target kinematic viscosity at standard temperature; estimate the equipment's estimated optimal stirring speed based on the initial kinematic viscosity and the final target kinematic viscosity; S3. The production equipment is controlled to heat and stir the lubricating material based on the equipment's estimated optimal heating temperature and the equipment's estimated optimal stirring speed, and the real-time kinematic viscosity is obtained at preset time intervals during the stirring process; S4. Update the equipment to estimate the optimal stirring speed based on the real-time kinematic viscosity, and stir the lubricating material at the updated equipment-estimated optimal stirring speed until the real-time kinematic viscosity reaches the final target kinematic viscosity.

[0005] Furthermore, both the initial kinematic viscosity obtained in step S1 and the real-time kinematic viscosity obtained in step S3 are acquired through monitoring by an online kinematic viscosity sensor.

[0006] Furthermore, the step of estimating the optimal heating temperature of the device based on the initial kinematic viscosity and the preset target kinematic viscosity specifically involves: S11. Obtain the estimated optimal heating temperature of the first device using a preset empirical formula. The preset empirical formula is specifically expressed as follows:

[0007] T_1 is the estimated optimal heating temperature of the first device, T_0 is the standard temperature, ND_0 is the initial kinematic viscosity, and ND_Y is the preset target kinematic viscosity. It is the viscosity-temperature characteristic constant, reflecting the rate at which viscosity decreases with increasing temperature; S12. The preliminary equipment's estimated optimal heating temperature is corrected to obtain the second equipment's estimated optimal heating temperature, specifically as follows: ;

[0008] T_2 is the estimated optimal heating temperature of the second device, Kr is the thermal response correction coefficient, and N1 is the preset number of historical samples. Set the heating temperature for the nth historical device. This represents the actual temperature reached by the nth historical lubricating material. S13. Compare the estimated optimal heating temperature of the second equipment with the safe upper limit to determine the estimated optimal heating temperature of the equipment, specifically as follows: Obtain the current safe upper temperature limit of the lubricating material and the current set upper temperature limit of the production equipment, and select the minimum value as the final safe upper temperature limit T_safe; If T_2≤T_safe, then T_3=T_2; if T_2>T_safe, then T_3=T_safe; T_3 is the estimated optimal heating temperature of the equipment.

[0009] Furthermore, the analysis of the final target kinematic viscosity at the equipment's estimated optimal heating temperature based on the preset target kinematic viscosity at standard temperature is specifically obtained through a viscosity conversion model, which is expressed as follows:

[0010] ND_Z is the final target kinematic viscosity, and e is the natural constant.

[0011] Furthermore, the step of analyzing the preset target kinematic viscosity at a standard temperature to estimate the final target kinematic viscosity at the optimal heating temperature is specifically achieved through the following steps: Sa21. Obtain a pre-established process mapping table, wherein the process mapping table takes the preset target kinematic viscosity at standard temperature and the equipment estimated optimal heating temperature as two input dimensions, and outputs the corresponding final target kinematic viscosity. Sa22. If there is a record in the process mapping table that perfectly matches the current preset target kinematic viscosity and the equipment's estimated optimal heating temperature, then directly read the final target kinematic viscosity corresponding to that record. If not, then execute steps Sa23 to Sa24. Sa23. From the process mapping table, with the current preset target kinematic viscosity unchanged, find the two heating temperature values ​​with the smallest deviation from the current equipment estimated optimal heating temperature, and thus match the two corresponding kinematic viscosities, which are denoted as the first viscosity ND1 and the second viscosity ND2 respectively. From the process mapping table, based on the current equipment estimated optimal heating temperature remaining unchanged, find the two kinematic viscosity values ​​with the smallest deviation from the current preset target kinematic viscosity, and thus match the corresponding two kinematic viscosities, which are denoted as the third viscosity ND3 and the fourth viscosity ND4 respectively. Sa24. Calculate the final target kinematic viscosity ND_Z based on the first viscosity ND1, the second viscosity ND2, the third viscosity ND3, and the fourth viscosity ND4: ND_Z = [(ND1 + ND2) / 2 + (ND3 + ND4) / 2] / 2.

[0012] Furthermore, the process of estimating the optimal stirring speed based on the initial kinematic viscosity and the final target kinematic viscosity specifically involves: Sb21, Estimate the total shear force Q required to reach the final target kinematic viscosity:

[0013] The preset shear sensitivity coefficient is ND_Z, and the final target kinematic viscosity is ND_Z. Sb22. Estimate the first stirring speed V1 based on the total shear force Q:

[0014] Ks is the equipment shear constant, and t is the preset stirring time; Sb23. If V_min≤V1≤V_safe, then V=V1, where V is the estimated optimal stirring speed of the equipment, V_min is the minimum stirring speed of the equipment, and V_safe is the maximum safe stirring speed of the equipment. If V1 < V_min, then V = V_min, and the preset stirring time t is updated at the same time, t = Q / (V_min × Ks); If V1 > V_safe, then V = V_safe, and the preset stirring time t is updated simultaneously, t = Q / (V_safe × Ks).

[0015] Furthermore, the step of updating the optimal stirring speed based on real-time kinematic viscosity specifically involves: S41. Analyze the current viscosity deviation E and viscosity change rate R: E=ND_S-ND_Z; R=(ND_S-ND_P) / Δt; ND_S is the real-time kinematic viscosity, ND_P is the kinematic viscosity obtained from the previous sampling node, and Δt is the preset time interval; S42. If E≤0, then stop stirring; If E>0 and |E|≤E1, where E1 is the preset convergence threshold, then the convergence phase begins, and the equipment's estimated optimal stirring speed is updated as follows: V_new = V_s × Kj, where V_new is the estimated optimal stirring speed of the updated equipment, V_s is the estimated optimal stirring speed of the current equipment, and Kj is the preset speed decay coefficient; If E > 0 and |E| > E1, then continue executing steps S43 to S44; S43. Based on the current viscosity deviation E, calculate the expected viscosity decrease rate R_d: R_d = -Kp × E, where Kp is the preset proportional gain coefficient of the PID controller. S44. Calculate the required stirring speed adjustment ΔV, and update the equipment estimate of the optimal stirring speed based on the required stirring speed adjustment ΔV: V_new=V_s+ΔV; ΔV=(R_d-R) / η; η=β×Ks×ND_S; η is the shear efficiency coefficient.

[0016] Furthermore, after updating the equipment to estimate the optimal stirring speed, it also includes: S45. Estimate the required real-time shear force Q1:

[0017] The preset shear sensitivity coefficient is ND_Z, and the final target kinematic viscosity is ND_Z. S46. If V_min≤V_new≤V_safe, then V_new=V_new, update the preset stirring time t, t=Q1 / (V_new×Ks); V_min is the minimum stirring speed of the equipment, and V_safe is the maximum safe stirring speed of the equipment. If V_new < V_min, then V_new = V_min, update the preset stirring time t, t = Q1 / (V_min × Ks); If V_new > V_safe, then V_new = V_safe, and update the preset stirring time t, t = Q1 / (V_safe × Ks).

[0018] Furthermore, after step S46, when the stirring time at the currently updated equipment estimated optimal stirring speed reaches the corresponding updated preset stirring time, the real-time kinematic viscosity is directly updated and step S4 is re-executed.

[0019] This invention also provides an online quality closed-loop control system for lubricating materials, employing any of the above-described online quality closed-loop control methods for lubricating materials, including: The first estimation module obtains the initial kinematic viscosity and the preset target kinematic viscosity of the lubricating material at the standard temperature before heating and stirring in the mixing process, and estimates the optimal heating temperature of the equipment based on the initial kinematic viscosity and the preset target kinematic viscosity. The second estimation module analyzes the preset target kinematic viscosity at the standard temperature to estimate the final target kinematic viscosity at the optimal heating temperature of the equipment; and estimates the optimal stirring speed of the equipment based on the initial kinematic viscosity and the final target kinematic viscosity. The control module is updated to control the production equipment to heat and stir the lubricating material based on the equipment's estimated optimal heating temperature and estimated optimal stirring speed. During the stirring process, the real-time kinematic viscosity is obtained at preset time intervals, and the equipment's estimated optimal stirring speed is updated based on the real-time kinematic viscosity. The lubricating material is then stirred using the updated equipment's estimated optimal stirring speed.

[0020] Compared with the prior art, the beneficial effects of the present invention are as follows: This invention estimates the optimal heating temperature of the equipment based on the initial kinematic viscosity and the preset target kinematic viscosity of the lubricating material at standard temperature. Then, it analyzes the final target kinematic viscosity at the estimated optimal heating temperature based on the preset target kinematic viscosity at standard temperature, thus aligning the control target with the actual working conditions and improving the accuracy of endpoint control. Furthermore, it estimates the optimal stirring speed of the equipment based on the initial and final target kinematic viscosities and updates the estimated optimal stirring speed based on the real-time kinematic viscosity, ensuring that the stirring speed adjustment fits the production conditions and improves production efficiency and product quality. This invention employs a three-tiered approach: "theoretical calculation using preset empirical formulas + historical correction + safety constraints." This ensures that the final output of the device's estimated optimal heating temperature not only aligns with the material characteristics of the current batch but also adapts to the actual thermal response capability of the specific device, while always remaining within safe boundaries. This invention proposes a method for obtaining the final target viscosity based on a process mapping table, which is suitable for scenarios that lack accurate mathematical models or have nonlinear characteristics. By matching and interpolating historical data, it ensures that a reasonable target viscosity value can still be obtained when there is no direct matching data, thereby enhancing the robustness and applicability of the method. This invention, by real-time monitoring of viscosity deviation and rate of change, and by using proportional control to plan the desired rate of decrease, can quickly adjust when the deviation is large, significantly shortening the mixing time and improving production efficiency. Through low-speed stirring during the convergence phase, unnecessary long-term high-speed stirring is avoided, reducing damage to the material structure and equipment wear caused by excessive shearing. Attached Figure Description

[0021] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0023] Figure 1 This is a flowchart of an online quality closed-loop control method for lubricating materials according to the present invention; Figure 2 This is a structural block diagram of an online quality closed-loop control system for lubricating materials according to the present invention. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below 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. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0025] It should be noted that all directional indications (such as up, down, left, right, front, back, etc.) in the embodiments of the present invention are only used to explain the relative positional relationship and movement of each component in a certain specific posture (as shown in the figure). If the specific posture changes, the directional indication will also change accordingly.

[0026] Furthermore, the use of terms such as "first" and "second" in this invention is 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" and "second" may explicitly or implicitly include at least one of those features. Additionally, the technical solutions of the various embodiments can be combined with each other, but only on the basis of being achievable by those skilled in the art. When the combination of technical solutions is contradictory or impossible to implement, such a combination of technical solutions should be considered non-existent and not within the scope of protection claimed by this invention.

[0027] Example 1 See Figure 1 As shown, the present invention provides an online quality closed-loop control method for lubricating materials, which specifically includes the following steps: S1. Before heating and stirring in the mixing process, obtain the initial kinematic viscosity and the preset target kinematic viscosity of the lubricating material at the standard temperature, and estimate the optimal heating temperature of the equipment based on the initial kinematic viscosity and the preset target kinematic viscosity. S2. Analyze the final target kinematic viscosity at the equipment's estimated optimal heating temperature based on the preset target kinematic viscosity at standard temperature; estimate the equipment's estimated optimal stirring speed based on the initial kinematic viscosity and the final target kinematic viscosity; S3. The production equipment is controlled to heat and stir the lubricating material based on the equipment's estimated optimal heating temperature and the equipment's estimated optimal stirring speed, and the real-time kinematic viscosity is analyzed at preset time intervals during the stirring process. S4. Update the equipment to estimate the optimal stirring speed based on the real-time kinematic viscosity, and stir the lubricating material using the updated equipment to estimate the optimal stirring speed.

[0028] The following provides a detailed explanation of each step: S1. Before heating and stirring in the mixing process, obtain the initial kinematic viscosity of the lubricating material at the standard temperature, and estimate the optimal heating temperature of the equipment based on the initial kinematic viscosity and the preset target kinematic viscosity at the standard temperature.

[0029] In step S1, the process of estimating the optimal heating temperature of the device based on the initial kinematic viscosity and the preset target kinematic viscosity specifically involves: S11. Obtain the estimated optimal heating temperature of the first device using a preset empirical formula. The preset empirical formula is specifically expressed as follows:

[0030] T_1 is the estimated optimal heating temperature of the first device, T_0 is the standard temperature, ND_0 is the initial kinematic viscosity, and ND_Y is the preset target kinematic viscosity. It is the viscosity-temperature characteristic constant, reflecting the rate at which viscosity decreases with increasing temperature; S12. The preliminary equipment's estimated optimal heating temperature is corrected to obtain the second equipment's estimated optimal heating temperature, specifically as follows: ;

[0031] T_2 is the estimated optimal heating temperature of the second device, Kr is the thermal response correction coefficient, and N1 is the preset number of historical samples. Set the heating temperature for the nth historical device. This represents the actual temperature reached by the nth historical lubricating material. S13. Compare the estimated optimal heating temperature of the second equipment with the safe upper limit to determine the estimated optimal heating temperature of the equipment, specifically as follows: Obtain the current safe upper temperature limit of the lubricating material and the current set upper temperature limit of the production equipment, and select the minimum value as the final safe upper temperature limit T_safe; If T_2≤T_safe, then T_3=T_2; if T_2>T_safe, then T_3=T_safe; T_3 is the estimated optimal heating temperature of the equipment.

[0032] The viscosity-temperature characteristic constant is obtained through prior experimental calibration, specifically as follows: Multiple test temperature points were set according to the actual application temperature range and blending process temperature range of the lubricating material; The kinematic viscosity of each test temperature point is tested repeatedly a preset number of times to obtain the average test viscosity of each test temperature point. Using the Arrhenius viscosity-temperature relationship model, multiple first model constants A and multiple second model constants B are obtained by using every two sets of test kinematic viscosity and the mean of test viscosity. Then, the mean values ​​are calculated to obtain the first final model constant Az and the second final model constant Bz. The Arrhenius viscosity-temperature relationship model is expressed as: ln(ND_c)=A+B / (T_c+273.15), where T_c is the test temperature point and ND_c is the corresponding test kinematic viscosity. Analysis of viscosity-temperature characteristic constants: .

[0033] S2. Analyze the final target kinematic viscosity at the equipment's estimated optimal heating temperature based on the preset target kinematic viscosity at the standard temperature; estimate the equipment's estimated optimal stirring speed based on the initial kinematic viscosity and the final target kinematic viscosity.

[0034] In some embodiments, in step S2, the final target kinematic viscosity at the optimal heating temperature estimated by the device based on the preset target kinematic viscosity at standard temperature is specifically calculated using a viscosity conversion model, which is expressed as follows:

[0035] ND_Z is the final target kinematic viscosity, and e is the natural constant.

[0036] In another embodiment, the step of estimating the final target kinematic viscosity at the optimal heating temperature based on the preset target kinematic viscosity at a standard temperature can be further achieved through the following steps: Sa21. Obtain a pre-established process mapping table, wherein the process mapping table takes the preset target kinematic viscosity at standard temperature and the equipment estimated optimal heating temperature as two input dimensions, and outputs the corresponding final target kinematic viscosity. Sa22. If there is a record in the process mapping table that perfectly matches the current preset target kinematic viscosity and the equipment's estimated optimal heating temperature, then directly read the final target kinematic viscosity corresponding to that record. If not, then execute steps Sa23 to Sa24. Sa23. From the process mapping table, with the current preset target kinematic viscosity unchanged, find the two heating temperature values ​​with the smallest deviation from the current equipment estimated optimal heating temperature, and thus match the two corresponding kinematic viscosities, which are denoted as the first viscosity ND1 and the second viscosity ND2 respectively. From the process mapping table, based on the current equipment estimated optimal heating temperature remaining unchanged, find the two kinematic viscosity values ​​with the smallest deviation from the current preset target kinematic viscosity, and thus match the corresponding two kinematic viscosities, which are denoted as the third viscosity ND3 and the fourth viscosity ND4 respectively. (For example, if the current preset target kinematic viscosity is a0, and the current estimated optimal heating temperature of the equipment is t0, and a0 remains unchanged in the process mapping table, the records are (a0, t1, v1), (a0, t2, v2), and (a0, t3, v3). If t1 and t2 have the smallest deviation from t0, then the corresponding two kinematic viscosities v1 and v2 are matched and output.) Sa24. Calculate the final target kinematic viscosity based on the first viscosity ND1, the second viscosity ND2, the third viscosity ND3, and the fourth viscosity ND4: ND_Z=[(ND1+ND2) / 2+(ND3+ND4) / 2] / 2.

[0037] In step Sa21, the data sources for the process mapping table include: production records of historical successful batches, including the target viscosity at standard temperature, the actual heating temperature used, and the final kinematic viscosity of the batch that was measured and verified to be qualified at the heating temperature.

[0038] In step S2, the process of estimating the optimal stirring speed based on the initial kinematic viscosity and the final target kinematic viscosity specifically involves: Sb21, Estimate the total shear force Q required to reach the final target kinematic viscosity:

[0039] The preset shear sensitivity coefficient; Sb22. Estimate the first stirring speed V1 based on the total shear force Q:

[0040] Ks is the equipment shear constant, and t is the preset stirring time; Sb23. If V_min≤V1≤V_safe, then V=V1, where V is the estimated optimal stirring speed of the equipment, V_min is the minimum stirring speed of the equipment, and V_safe is the maximum safe stirring speed of the equipment. If V1 < V_min, then V = V_min, and the preset stirring time t is updated at the same time, t = Q / (V_min × Ks); If V1 > V_safe, then V = V_safe, and the preset stirring time t is updated simultaneously, t = Q / (V_safe × Ks).

[0041] The shear sensitivity coefficient represents the relative rate of change of viscosity of a lubricating material at a unit shear rate. It is obtained by fitting previous experimental data and reflects the sensitivity of the material to stirring shear. The larger the value, the faster the viscosity decreases under the same stirring action.

[0042] The equipment shear constant represents the average shear rate generated in the material per revolution of the agitator.

[0043] Both the initial kinematic viscosity obtained in step S1 and the real-time kinematic viscosity obtained in step S3 are acquired through online kinematic viscosity sensor monitoring.

[0044] S4. Update the equipment to estimate the optimal stirring speed based on the real-time kinematic viscosity, and stir the lubricating material using the updated equipment to estimate the optimal stirring speed.

[0045] In step S4, the step of updating the optimal stirring speed based on real-time kinematic viscosity specifically involves: S41. Analyze the current viscosity deviation E and viscosity change rate R: E=ND_S-ND_Z; R=(ND_S-ND_P) / Δt; ND_S is the real-time kinematic viscosity, ND_P is the kinematic viscosity obtained from the previous sampling node, and Δt is the preset time interval; S42. If E≤0, then stop stirring; If E>0 and |E|≤E1, where E1 is the preset convergence threshold, then the convergence phase begins, and the equipment's estimated optimal stirring speed is updated as follows: V_new = V_s × Kj, where V_new is the estimated optimal stirring speed of the updated equipment, V_s is the estimated optimal stirring speed of the current equipment, and Kj is the preset speed decay coefficient; If E > 0 and |E| > E1, then continue executing steps S43 to S44; S43. Based on the current viscosity deviation E, calculate the expected viscosity decrease rate R_d: R_d = -Kp × E, where Kp is the preset proportional gain coefficient of the PID controller. S44. Calculate the required stirring speed adjustment ΔV, and update the equipment estimate of the optimal stirring speed based on the required stirring speed adjustment ΔV: V_new=V_s+ΔV; ΔV=(R_d-R) / η; η=β×Ks×ND_S; η is the shear efficiency coefficient.

[0046] For step S4, after updating the equipment estimate of the optimal stirring speed, the following is also included: S45. Estimate the required real-time shear force Q1:

[0047] S46. If V_min≤V_new≤V_safe, then V_new=V_new, update the preset stirring time t, t=Q1 / (V_new×Ks); If V_new < V_min, then V_new = V_min, update the preset stirring time t, t = Q1 / (V_min × Ks); If V_new > V_safe, then V_new = V_safe, and update the preset stirring time t, t = Q1 / (V_safe × Ks).

[0048] Current viscosity deviation; a positive value indicates that the current viscosity is still higher than the target value, and stirring needs to continue.

[0049] The rate of viscosity change; a positive value indicates that the viscosity is increasing, and a negative value indicates that the viscosity is decreasing.

[0050] The shear efficiency coefficient reflects the rate of change of viscosity caused by a unit increase in stirring speed at the current viscosity level.

[0051] Step S4 also includes: When the stirring time at the estimated optimal stirring speed using the currently updated equipment reaches the corresponding updated preset stirring time, the real-time kinematic viscosity is directly updated and step S4 is executed again.

[0052] Example 2 See Figure 2 As shown, the present invention also provides an online quality closed-loop control system for lubricating materials, specifically comprising: The first estimation module obtains the initial kinematic viscosity and the preset target kinematic viscosity of the lubricating material at the standard temperature before heating and stirring in the mixing process, and estimates the optimal heating temperature of the equipment based on the initial kinematic viscosity and the preset target kinematic viscosity. The second estimation module analyzes the preset target kinematic viscosity at the standard temperature to estimate the final target kinematic viscosity at the optimal heating temperature of the equipment; and estimates the optimal stirring speed of the equipment based on the initial kinematic viscosity and the final target kinematic viscosity. The control module is updated to control the production equipment to heat and stir the lubricating material based on the equipment's estimated optimal heating temperature and estimated optimal stirring speed. During the stirring process, the real-time kinematic viscosity is obtained at preset time intervals, and the equipment's estimated optimal stirring speed is updated based on the real-time kinematic viscosity. The lubricating material is then stirred using the updated equipment's estimated optimal stirring speed.

[0053] Example 3

[0054] The present invention also provides an electronic device, including: a processor, a transmitting device, an input device, an output device, and a memory. The processor may be implemented using a general-purpose CPU (Central Processing Unit), a microprocessor, an application-specific integrated circuit, or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory may be implemented using a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM), and is used to store computer program code. The computer program code includes computer instructions. When the processor executes the computer instructions, the electronic device executes a method as described in any of the above possible implementation methods.

[0055] Example 4 The present invention also provides a computer-readable storage medium storing a computer program, the computer program including program instructions, which, when executed by a processor of an electronic device, cause the processor to perform a method as described in any of the above possible implementations.

[0056] The beneficial effects of this invention are as follows: This invention estimates the optimal heating temperature of the equipment based on the initial kinematic viscosity and the preset target kinematic viscosity of the lubricating material at standard temperature. Then, it analyzes the final target kinematic viscosity at the estimated optimal heating temperature based on the preset target kinematic viscosity at standard temperature, thus aligning the control target with the actual working conditions and improving the accuracy of endpoint control. Furthermore, it estimates the optimal stirring speed of the equipment based on the initial and final target kinematic viscosities and updates the estimated optimal stirring speed based on the real-time kinematic viscosity, ensuring that the stirring speed adjustment fits the production conditions and improves production efficiency and product quality. This invention employs a three-tiered approach: "theoretical calculation using preset empirical formulas + historical correction + safety constraints." This ensures that the final output of the device's estimated optimal heating temperature not only aligns with the material characteristics of the current batch but also adapts to the actual thermal response capability of the specific device, while always remaining within safe boundaries. This invention proposes a method for obtaining the final target viscosity based on a process mapping table, which is suitable for scenarios that lack accurate mathematical models or have nonlinear characteristics. By matching and interpolating historical data, it ensures that a reasonable target viscosity value can still be obtained when there is no direct matching data, thereby enhancing the robustness and applicability of the method.

[0057] This invention, by real-time monitoring of viscosity deviation and rate of change, and by using proportional control to plan the desired rate of decrease, can quickly adjust when the deviation is large, significantly shortening the mixing time and improving production efficiency. Through low-speed stirring during the convergence phase, unnecessary long-term high-speed stirring is avoided, reducing damage to the material structure and equipment wear caused by excessive shearing.

[0058] In the description of this specification, the references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0059] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0060] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. 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 the invention. Therefore, the present invention 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 claimed herein.

Claims

1. A method for online closed-loop quality control of lubricating materials, characterized in that, Includes the following steps: S1. Before heating and stirring in the mixing process, obtain the initial kinematic viscosity and the preset target kinematic viscosity of the lubricating material at the standard temperature, and estimate the optimal heating temperature of the equipment based on the initial kinematic viscosity and the preset target kinematic viscosity. S2. Analyze the final target kinematic viscosity at the equipment's estimated optimal heating temperature based on the preset target kinematic viscosity at standard temperature; estimate the equipment's estimated optimal stirring speed based on the initial kinematic viscosity and the final target kinematic viscosity; S3. The production equipment is controlled to heat and stir the lubricating material based on the equipment's estimated optimal heating temperature and the equipment's estimated optimal stirring speed, and the real-time kinematic viscosity is obtained at preset time intervals during the stirring process; S4. Update the equipment to estimate the optimal stirring speed based on the real-time kinematic viscosity, and stir the lubricating material at the updated equipment-estimated optimal stirring speed until the real-time kinematic viscosity reaches the final target kinematic viscosity.

2. The online quality closed-loop control method for lubricating materials according to claim 1, characterized in that, Both the initial kinematic viscosity obtained in step S1 and the real-time kinematic viscosity obtained in step S3 are acquired through online kinematic viscosity sensor monitoring.

3. The online quality closed-loop control method for lubricating materials according to claim 1, characterized in that, The process of estimating the optimal heating temperature of the equipment based on the initial kinematic viscosity and the preset target kinematic viscosity specifically involves: S11. Obtain the estimated optimal heating temperature of the first device using a preset empirical formula. The preset empirical formula is specifically expressed as follows: ； T_1 is the estimated optimal heating temperature of the first device, T_0 is the standard temperature, ND_0 is the initial kinematic viscosity, and ND_Y is the preset target kinematic viscosity. It is the viscosity-temperature characteristic constant, reflecting the rate at which viscosity decreases with increasing temperature; S12. The preliminary equipment's estimated optimal heating temperature is corrected to obtain the second equipment's estimated optimal heating temperature, specifically as follows: ； T_2 is the estimated optimal heating temperature of the second device, Kr is the thermal response correction coefficient, and N1 is the preset number of historical samples. Set the heating temperature for the nth historical device. This represents the actual temperature reached by the nth historical lubricating material. S13. Compare the estimated optimal heating temperature of the second equipment with the safe upper limit to determine the estimated optimal heating temperature of the equipment, specifically as follows: Obtain the current safe upper temperature limit of the lubricating material and the current set upper temperature limit of the production equipment, and select the minimum value as the final safe upper temperature limit T_safe; If T_2≤T_safe, then T_3=T_2; if T_2>T_safe, then T_3=T_safe; T_3 is the estimated optimal heating temperature of the equipment.

4. The online quality closed-loop control method for lubricating materials according to claim 3, characterized in that, The final target kinematic viscosity at the estimated optimal heating temperature is obtained by analyzing the preset target kinematic viscosity at standard temperature. Specifically, this is calculated using a viscosity conversion model, which is expressed as follows: ； ND_Z is the final target kinematic viscosity, and e is the natural constant.

5. The online quality closed-loop control method for lubricating materials according to claim 3, characterized in that, The step of estimating the final target kinematic viscosity at the optimal heating temperature based on the preset target kinematic viscosity at standard temperature is further achieved through the following steps: Sa21. Obtain a pre-established process mapping table, wherein the process mapping table takes the preset target kinematic viscosity at standard temperature and the equipment estimated optimal heating temperature as two input dimensions, and outputs the corresponding final target kinematic viscosity. Sa22. If there is a record in the process mapping table that perfectly matches the current preset target kinematic viscosity and the equipment's estimated optimal heating temperature, then directly read the final target kinematic viscosity corresponding to that record. If not, then execute steps Sa23 to Sa24. Sa23. From the process mapping table, with the current preset target kinematic viscosity unchanged, find the two heating temperature values ​​with the smallest deviation from the current equipment estimated optimal heating temperature, and thus match the two corresponding kinematic viscosities, which are denoted as the first viscosity ND1 and the second viscosity ND2 respectively. From the process mapping table, based on the current equipment estimated optimal heating temperature remaining unchanged, find the two kinematic viscosity values ​​with the smallest deviation from the current preset target kinematic viscosity, and thus match the corresponding two kinematic viscosities, which are denoted as the third viscosity ND3 and the fourth viscosity ND4 respectively. Sa24. Calculate the final target kinematic viscosity ND_Z based on the first viscosity ND1, the second viscosity ND2, the third viscosity ND3, and the fourth viscosity ND4: ND_Z = [(ND1 + ND2) / 2 + (ND3 + ND4) / 2] / 2.

6. The online quality closed-loop control method for lubricating materials according to claim 3, characterized in that, The process of estimating the optimal stirring speed based on the initial kinematic viscosity and the final target kinematic viscosity is as follows: Sb21, Estimate the total shear force Q required to reach the final target kinematic viscosity: ； The preset shear sensitivity coefficient is ND_Z, and the final target kinematic viscosity is ND_Z. Sb22. Estimate the first stirring speed V1 based on the total shear force Q: ； Ks is the equipment shear constant, and t is the preset stirring time; Sb23. If V_min≤V1≤V_safe, then V=V1, where V is the estimated optimal stirring speed of the equipment, V_min is the minimum stirring speed of the equipment, and V_safe is the maximum safe stirring speed of the equipment. If V1 < V_min, then V = V_min, and the preset stirring time t is updated at the same time, t = Q / (V_min × Ks); If V1 > V_safe, then V = V_safe, and the preset stirring time t is updated simultaneously, t = Q / (V_safe × Ks).

7. The online quality closed-loop control method for lubricating materials according to claim 3, characterized in that, The process of updating the optimal stirring speed based on real-time kinematic viscosity is specifically as follows: S41. Analyze the current viscosity deviation E and viscosity change rate R: E=ND_S-ND_Z; R=(ND_S-ND_P) / Δt; ND_S is the real-time kinematic viscosity, ND_P is the kinematic viscosity obtained from the previous sampling node, and Δt is the preset time interval; S42. If E≤0, then stop stirring; If E>0 and |E|≤E1, where E1 is the preset convergence threshold, then the convergence phase begins, and the equipment's estimated optimal stirring speed is updated as follows: V_new = V_s × Kj, where V_new is the estimated optimal stirring speed of the updated equipment, V_s is the estimated optimal stirring speed of the current equipment, and Kj is the preset speed decay coefficient; If E>0 and |E|>E1, then continue with steps S43 to S44. S43. Based on the current viscosity deviation E, calculate the expected viscosity decrease rate R_d: R_d = -Kp × E, where Kp is the preset proportional gain coefficient of the PID controller. S44. Calculate the required stirring speed adjustment ΔV, and update the equipment estimate of the optimal stirring speed based on the required stirring speed adjustment ΔV: V_new=V_s+ΔV; ΔV=(R_d-R) / η; η=β×Ks×ND_S; η is the shear efficiency coefficient.

8. The online quality closed-loop control method for lubricating materials according to claim 7, characterized in that, After updating the equipment to estimate the optimal mixing speed, the following is also included: S45. Estimate the required real-time shear force Q1: ； The preset shear sensitivity coefficient is ND_Z, and the final target kinematic viscosity is ND_Z. S46. If V_min≤V_new≤V_safe, then V_new=V_new, update the preset stirring time t, t=Q1 / (V_new×Ks); V_min is the minimum stirring speed of the equipment, and V_safe is the maximum safe stirring speed of the equipment. If V_new < V_min, then V_new = V_min, update the preset stirring time t, t = Q1 / (V_min × Ks); If V_new > V_safe, then V_new = V_safe, and update the preset stirring time t, t = Q1 / (V_safe × Ks).

9. The online quality closed-loop control method for lubricating materials according to claim 8, characterized in that, After step S46, the process further includes updating the real-time kinematic viscosity and re-executing step S4 when the duration of stirring at the currently updated equipment estimated optimal stirring speed reaches the corresponding updated preset stirring duration.

10. An online quality closed-loop control system for lubricating materials, employing the online quality closed-loop control method for lubricating materials as described in any one of claims 1 to 9, characterized in that, include: The first estimation module obtains the initial kinematic viscosity and the preset target kinematic viscosity of the lubricating material at the standard temperature before heating and stirring in the mixing process, and estimates the optimal heating temperature of the equipment based on the initial kinematic viscosity and the preset target kinematic viscosity. The second estimation module estimates the final target kinematic viscosity at the optimal heating temperature based on the preset target kinematic viscosity analysis at the standard temperature. The optimal stirring speed of the equipment is estimated based on the initial kinematic viscosity and the final target kinematic viscosity. The control module is updated to control the production equipment to heat and stir the lubricating material based on the equipment's estimated optimal heating temperature and estimated optimal stirring speed. During the stirring process, the real-time kinematic viscosity is obtained at preset time intervals, and the equipment's estimated optimal stirring speed is updated based on the real-time kinematic viscosity. The lubricating material is then stirred using the updated equipment's estimated optimal stirring speed.

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