Lithium battery homogenizing equipment state monitoring method and system

Abstract

The invention belongs to the technical field of data processing, and particularly relates to a lithium battery homogenizing equipment state monitoring method and system.The method comprises the steps that a torque signal and an angular speed of a stirring shaft, a strain signal of a slurry tank wall and a slurry solid content set value are collected, and the effective viscosity of slurry and the equivalent rigidity of equipment are calculated; constructing a stirring system kinetic equation containing a fluid damping item and a structural rigidity item, decoupling to obtain a fluid resistance component and a mechanical resistance component, performing kernel smoothing regression modeling on standard working condition data under different operation stages and solid content conditions, and matching a corresponding model according to a current working condition to obtain a dynamic state of the stirring system; a mechanical resistance reference value is obtained by combining the real-time fluid resistance component, and a mechanical resistance residual error is calculated; by comparing the difference between the residual error and historical normal distribution, the health index of the equipment is determined, and graded monitoring and fault early warning of the homogenate equipment state are achieved. According to the invention, process fluctuation and mechanical abnormity can be effectively separated, and monitoring accuracy and reliability are improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of data processing. More particularly, the present application relates to a lithium battery homogenate equipment state monitoring method and system. BACKGROUND

[0002] As the core power source in the current new energy vehicle, energy storage system and consumer electronics field, the preparation quality of electrode slurry of lithium battery is directly related to the energy density, cycle life and safety of the battery. In the pre-production process of lithium battery, homogenization is one of the key links, and the goal is to uniformly mix active material, conductive agent, binder and solvent to form a stable and uniform suspension slurry. This process is usually completed in a sealed stirring tank, and high shear stirring equipment is used to realize powder wetting, particle dispersion and system homogenization. Due to the non-Newtonian fluid characteristics of the slurry, and the high solid content and large viscosity, the equipment is subjected to complex alternating loads for a long time during stirring, and mechanical failures such as bearing wear, transmission loosening and paddle deformation are prone to occur. At the same time, process parameter deviations such as incorrect feeding, solvent evaporation and abnormal temperature control can also cause abnormal rheological properties of the slurry. Therefore, real-time and accurate monitoring of the running state of the homogenization equipment has become an urgent need to ensure the consistency of the slurry and the reliability of the equipment.

[0003] Currently, the state monitoring of the homogenization equipment in the industrial field mainly relies on traditional motor current monitoring, vibration signal analysis or periodic manual inspection. Some enterprises collect the current signals of the main shaft driving motor to indirectly reflect the load changes, which are used to judge whether it is overloaded or stuck; some other systems install vibration sensors on the equipment shell to identify the bearing fault characteristic frequency by using frequency spectrum analysis.

[0004] The existing methods can find serious faults to some extent, but due to the multi-stage dynamic change characteristics of the homogenization process itself, the slurry viscosity fluctuates sharply with the mixing process, resulting in significant natural changes in motor load and vibration level, and it is difficult for traditional monitoring methods to distinguish between normal process evolution and equipment abnormal degradation. For example, the rapid rise of slurry viscosity in the wetting period is often misjudged as equipment overload, while the slight resistance increase caused by early bearing wear may be masked by process fluctuations, resulting in missed reports. SUMMARY

[0005] To solve the technical problems that the existing homogenization equipment state monitoring method cannot effectively distinguish between process parameter fluctuations and load changes caused by mechanical faults, resulting in misjudgment and missed reports, the present application provides solutions in the following aspects.

[0006] In a first aspect, the present application provides a lithium battery homogenization equipment state monitoring method, comprising: The torque signal, the angular velocity, the strain signal of the slurry tank wall and the slurry solid content setting value of the stirring shaft during the operation of the homogenizing equipment are collected; the effective viscosity of the slurry is calculated based on the torque signal and the angular velocity, and the equivalent stiffness of the equipment is calculated in combination with the contact force converted from the strain signal and the torque signal; the stirring system dynamics equation containing the fluid damping term and the structural stiffness term is constructed according to the effective viscosity of the slurry and the equivalent stiffness of the equipment, and the fluid resistance component and the mechanical resistance component are decoupled; under different operating stages and slurry solid content conditions, the fluid resistance component and the mechanical resistance component under the standard working condition are subjected to kernel smoothing regression modeling, and a standard relationship library is established; the mechanical resistance reference value is obtained based on the real-time fluid resistance component according to the kernel regression model corresponding to the standard relationship library under the current working condition, and the mechanical resistance residual is obtained according to the difference between the real-time mechanical resistance component and the mechanical resistance reference value; the equipment health index is determined according to the distribution difference between the real-time mechanical resistance residual and the mechanical resistance residual under the historical standard working condition, and the homogenizing equipment state monitoring is performed according to the equipment health index.

[0007] The present application can simultaneously obtain the mechanical response of the equipment and the rheological properties of the slurry by collecting the torque signal, the angular velocity, the strain signal of the slurry tank wall and the slurry solid content setting value during the operation of the homogenizing equipment, and then calculating the effective viscosity reflecting the mixing state of the slurry based on the torque and the rotational speed, and evaluating the equivalent stiffness of the equipment structure in combination with the contact force converted from the tank wall strain and the torque, realizing the dual characterization of the process state and the mechanical state; on this basis, the stirring system dynamics model containing the fluid damping and the structural stiffness is constructed, the total torque is decoupled into the fluid resistance component dominated by the slurry properties and the mechanical resistance component dominated by the equipment state, and the coupling effect of process fluctuations and mechanical abnormalities is effectively separated; the kernel smoothing regression model library is established under different operating stages and solid content conditions according to the standard working condition data, so that the system can adaptively match the optimal reference relationship according to the current working condition, the mechanical resistance residual is obtained by comparing the deviation between the measured mechanical resistance component and the model predicted value, and the degree of deviation of the equipment from the normal state is accurately reflected; finally, the equipment health index is generated by analyzing the statistical difference between the residual sequence and the historical normal distribution, realizing the evaluation of the health status of the homogenizing equipment, improving the early fault identification ability and the state monitoring precision, avoiding the false alarm caused by the process fluctuation masking the equipment failure or the process fluctuation masking the mechanical degradation, and thus ensuring the stability of the lithium battery slurry preparation process and the reliability of the equipment operation.

[0008] Preferably, the effective viscosity of the slurry satisfies the expression: ; in the formula, is the effective viscosity of the slurry; is the torque signal; is the stirring paddle geometric coefficient; is the real-time angular velocity of the stirring shaft; is the blade diameter.

[0009] Preferably, the device equivalent stiffness satisfies the expression: ; in the expression, is the device equivalent stiffness; is the contact force of the slurry to the tank wall, which is converted from the torque signal by the lever principle , is the tank body radius; is the slurry tank wall strain signal; is the tank body characteristic length.

[0010] Preferably, the stirring system dynamics equation is: ; in the expression, is the system moment of inertia; is the angular displacement; is the fluid damping coefficient; is the device equivalent stiffness; is the torque signal; represents the angle first-order derivative with respect to time; represents the angle second-order derivative with respect to time; represents the inertial moment; represents the fluid damping moment; represents the elastic restoring moment.

[0011] The present application establishes the dynamics equation of the stirring system, comprehensively considers the inertial moment, fluid damping moment and elastic restoring moment in the system rotation process, and contains various mechanical actions on the stirring shaft in operation. The inertial moment reflects the resistance characteristics of the device rotating part to acceleration change, the fluid damping moment embodies the resistance of the slurry viscosity to stirring movement, and the elastic restoring moment represents the stiffness characteristics of the device structure after deformation under force to restore to the original state, thereby providing a basis for decoupling the process load and the device body state.

[0012] Preferably, the decoupling obtains the fluid resistance component and the mechanical resistance component, including: the fluid resistance component satisfies the expression: , in the expression, is the fluid damping coefficient; is the real-time angular velocity of the stirring shaft; the mechanical resistance component satisfies the expression: , in the expression, is the torque signal.

[0013] The present application can effectively separate the load caused by the rheological properties of the slurry and the resistance caused by the mechanical structure state of the equipment by decomposing the total torque measured during stirring into a fluid resistance component and a mechanical resistance component, wherein the fluid resistance component is calculated according to the damping characteristics corresponding to the effective viscosity of the slurry and the real-time rotational speed of the stirring shaft, and truly reflects the viscous resistance level of the slurry under the current process conditions, and the mechanical resistance component is obtained by deducting the fluid contribution from the total torque, and reflects the mechanical loss state of the bearing friction, transmission component wear, structural looseness and other equipment bodies. The mechanical resistance component extracted can be used as an independent health feature for subsequent modeling and analysis, significantly improving the robustness of state monitoring and providing reliable technical support for realizing process-independent early warning of equipment failure.

[0014] Preferably, the standard working condition refers to the operating condition of the equipment under the condition of no mechanical failure and stable ambient temperature, and qualified slurry is prepared.

[0015] Preferably, the mechanical resistance reference value satisfies the expression: ; wherein, is the current time, is the mechanical resistance reference value at the current time; is the fluid resistance component at the current time; is the kernel regression model corresponding to the current operating stage of the slurry solid content set value under the current working condition.

[0016] Preferably, the determination of the equipment health index comprises: constructing a reference window at the current time; obtaining the mean and standard deviation of the mechanical resistance residual of the historical standard working condition with the same slurry solid content set value and the same operating stage as the current working condition, is the preset number of standard working condition samples; the equipment health index at the current time satisfies the expression: , wherein, is the mean of all mechanical resistance residuals in the reference window corresponding to the current time; is the mean of the mechanical resistance residual under the historical standard working condition; is the standard deviation of the mechanical resistance residual under the historical standard working condition; is the maximum function, is the exponential function with the natural constant as the base; is the attenuation coefficient.

[0017] The application realizes adaptive evaluation of the health state of the equipment by constructing a sliding reference window of the current moment, combining historical standard working condition data matched with the current process condition and operation stage, obtaining statistical distribution characteristics of mechanical resistance residuals in a normal state, reflecting the fluctuation range of the typical mechanical resistance residuals of the equipment in the fault-free case by using the mean value and standard deviation of the historical data, and obtaining the equipment health index by calculating the offset of the current mechanical resistance residual mean value relative to the historical normal distribution, effectively improving the sensitivity and reliability of the monitoring system, enabling the operation and maintenance personnel to accurately judge the equipment degradation degree and take graded response measures according to the change trend of the health index, and ensuring the stability of the homogenization process and the safety of the equipment operation.

[0018] Preferably, the homogenization equipment state monitoring according to the equipment health index comprises: marking the current homogenization equipment state as normal; in response to triggering a warning to notify the equipment maintenance personnel to perform preliminary inspection and record the operation parameters; in response to triggering an alarm to notify the equipment maintenance personnel to perform detailed inspection and arrange preventive maintenance; and in response to notifying the equipment maintenance personnel to immediately shut down for maintenance, wherein, is the equipment health index at the current moment.

[0019] The application realizes graded monitoring of the homogenization equipment operation state by dividing the equipment health index into multiple intervals and corresponding different state determination and response strategies, improves the timeliness and accuracy of fault response, avoids the problems of excessive maintenance or insufficient maintenance, and significantly improves the reliability, safety and operation and maintenance efficiency of the lithium battery homogenization process.

[0020] In a second aspect, the application provides a lithium battery homogenization equipment state monitoring system, comprising a processor and a memory, and the memory stores computer program instructions, which realize the above-mentioned lithium battery homogenization equipment state monitoring method when executed by the processor.

[0021] By adopting the above technical solution, the above-mentioned lithium battery homogenization equipment state monitoring method is generated into a computer program and stored in the memory to be loaded and executed by the processor, so that a terminal equipment is made according to the memory and the processor, and convenient use is achieved.

[0022] The beneficial effects of the present invention are as follows: the present invention realizes the coordinated perception of the dynamic response of the mechanical system and the rheological characteristics of the slurry by synchronously collecting the torque, angular velocity, tank wall strain and process setting parameters of the stirring shaft during the operation of the homogenizing equipment, and extracts the effective viscosity of the slurry reflecting the mixing state and the mechanical equivalent stiffness characterizing the structural integrity of the equipment based on the physical mechanism, which provides a basis for distinguishing process fluctuations from mechanical anomalies; the present invention constructs a dynamic model of the stirring system including inertia, fluid damping and structural elastic effects, and decouples the total load into a fluid resistance component dominated by the slurry characteristics and a mechanical resistance component dominated by the equipment state, which effectively removes the interference of process changes on equipment monitoring; The invention establishes a phased and process-based kernel smoothing regression model library for different operating stages and slurry solid content conditions, forming an adaptive mechanical resistance benchmark prediction capability. By comparing the residuals between the measured values ​​and the expected values, the trend of the equipment deviating from the normal state can be accurately identified; combining the sliding window statistics with the distribution comparison of historical standard operating conditions, the equipment health index is obtained, and multi-level thresholds are set to trigger corresponding operation and maintenance responses. This not only improves the sensitivity to early mechanical failures such as bearing wear and structural looseness, but also avoids misjudgments caused by process factors such as feeding deviation and viscosity fluctuations, significantly enhancing the accuracy and robustness of lithium battery slurry process status monitoring, and providing reliable technical support for preventive maintenance. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 is a flow chart schematically illustrating a method for monitoring the state of a lithium battery homogenization device in the present invention; Figure 2 is a schematic diagram showing the torque signal of the stirring shaft; Figure 3 is a line graph schematically showing the mechanical resistance residual; Figure 4 It is a line graph schematically showing the device health indicator. DETAILED DESCRIPTION

[0024] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work shall fall within the scope of protection of the present invention.

[0025] The specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0026] The embodiment of the present invention discloses a method for monitoring the state of a lithium battery homogenization device, referring to Figure 1 , including steps S1 to S5: S1, collect the torque signal of the stirring shaft, the angular velocity, the strain signal of the slurry tank wall and the solid content setting value in the running process of the homogenizing equipment, calculate the effective viscosity of the slurry based on the torque signal and the angular velocity, and calculate the equivalent stiffness of the equipment in combination with the contact force converted from the strain signal and the torque signal.

[0027] S101, collect the torque signal of the stirring shaft, the angular velocity, the strain signal of the slurry tank wall and the solid content setting value in the running process of the homogenizing equipment.

[0028] It should be noted that the running of the homogenizing equipment is essentially the interaction process of the stirring system and the non-Newtonian slurry. In order to accurately capture the dynamic changes of the equipment state and the process execution, the fluid characteristics and the mechanical response need to be captured synchronously.

[0029] Specifically, the torque signal of the stirring shaft , the angular velocity , the strain signal of the slurry tank wall , the ambient temperature , and the solid content setting value of the slurry are collected.

[0030] Among them, the torque signal of the stirring shaft is the output torque of the main shaft monitored in real time through a strain torque sensor, and the unit is The strain signal of the slurry tank wall is the radial strain value obtained by real-time monitoring through the resistance strain gauges pasted on the key positions of the tank body. The torque signal of the stirring shaft and the strain signal of the slurry tank wall need to be collected synchronously to ensure phase alignment. In this embodiment, the collection frequency is 200 Hz. In other embodiments, the implementer can set it according to the actual implementation situation, but it should be noted that the strain signal of the slurry tank wall directly reflects the fluid pressure distribution of the slurry on the tank wall, which is the key input for analyzing the rheological characteristics. Its sampling frequency needs to be higher than the flow characteristic frequency of the slurry to avoid aliasing effect, and it should be at least 2 times or more than the flow characteristic frequency of the slurry.

[0031] Exemplarily, Figure 2 is the torque signal of the stirring shaft.

[0032] S102, calculate the effective viscosity of the slurry based on the torque signal and the angular velocity, and calculate the equivalent stiffness of the equipment in combination with the contact force converted from the strain signal and the torque signal.

[0033] It should be noted that the change of the slurry viscosity reflects the change of the rheological property of the slurry, the effective viscosity of the slurry is dominated by the process parameters, and is a key index for characterizing the process conditions such as the feeding ratio and the solid content; the equipment stiffness attenuation reflects the change of the structural integrity of the stirring system, the equivalent stiffness of the equipment is dominated by the equipment state, and is a core parameter for characterizing mechanical faults such as bearing wear and structural looseness, therefore, obtaining accurate effective viscosity of the slurry and equivalent stiffness of the equipment is the physical basis for distinguishing process deviation and mechanical fault, and the effective viscosity of the slurry and the equivalent stiffness of the equipment are obtained based on the principles of fluid mechanics and structural mechanics.

[0034] Specifically, the effective viscosity of the slurry is calculated according to Newton internal friction law :

[0035] In the formula, the effective viscosity of the slurry is ; the torque signal is ; the geometric coefficient of the stirring paddle is ; the real-time angular velocity of the stirring shaft is ; the diameter of the paddle is . Wherein, is obtained by calibrating the geometric shape of the stirring paddle and the flow field distribution, and the value is determined by calculating fluid dynamics simulation, when simulating, a three-dimensional flow field model with a 1:1 ratio of the actual equipment is constructed, the mapping relationship between the torque and the viscosity is fitted by changing the paddle speed and the slurry viscosity, and finally is back calculated, the coefficient essentially reflects the effective contact efficiency of the paddle surface area and the fluid, the greater the paddle pitch and the more the number of blades, the greater the value.

[0036] Further, the equivalent stiffness of the equipment is calculated according to the slurry tank wall strain signal :

[0037] In the formula, the equivalent stiffness of the equipment is ; the contact force of the slurry on the tank wall is , which is obtained by converting the torque signal by the lever principle , the radius of the tank body; the slurry tank wall strain signal; the characteristic length of the tank body is , represents the equivalent distance from the installation position of the resistance strain gauge to the center of the tank. The equivalent stiffness of the equipment The structural integrity of the stirring system can be characterized, and the attenuation directly indicates the degree of bearing wear.

[0038] S2, according to the effective viscosity of the slurry and the equivalent stiffness of the equipment, a stirring system dynamics equation containing a fluid damping term and a structural stiffness term is constructed, and a fluid resistance component and a mechanical resistance component are obtained by decoupling.

[0039] It should be noted that the homogenization process has a coupling effect of fluid resistance and mechanical resistance, and the torque signal contains the rheological properties of the slurry and the mechanical state of the equipment. If decoupling is not performed, the physical root cause of process deviation and equipment failure cannot be distinguished, therefore, the stirring system dynamics equation is established based on the classical mechanics principle to decouple the torque signal, and the fluid resistance component and the mechanical resistance component are obtained.

[0040] Specifically, the stirring system dynamics equation is established as follows:

[0041] In the formula, is the moment of inertia of the system, and the unit is ; is the angular displacement, and the unit is ; is the fluid damping coefficient, and the unit is ; is the equivalent stiffness of the equipment, and the unit is ; is the driving torque, that is, the torque signal of the stirring shaft, and the unit is ; represents the first order derivative of the angle with respect to time, that is, the angular velocity ; represents the second order derivative of the angle with respect to time, that is, the angular acceleration; represents the inertial torque, which reflects the resistance of the moment of inertia of the system to the angular acceleration; represents the fluid damping torque, which reflects the resistance of the fluid viscous resistance to the angular velocity; represents the elastic recovery torque, which reflects the restoring force of the structural stiffness of the equipment to the angular displacement.

[0042] Among them, the fluid damping coefficient is linearly related to the effective viscosity of the slurry, and the specific expression is as follows:

[0043] In the formula, is the damping proportionality coefficient, and the unit is ; is the effective viscosity of the slurry, unit Among them, the damping proportional coefficient The geometric parameters of the stirring blade are obtained by calibrating the flow field simulation, which reflects the effective contact area between the fluid and the stirring structure. The geometric parameters of the stirring blade include the surface area of ​​the blade and the gap between the blade and the tank. The larger the surface area of ​​the blade, the smaller the gap between the blade and the tank. The bigger.

[0044] Furthermore, the dynamic equation of the stirring system is decoupled to obtain the fluid resistance component and mechanical resistance component .

[0045] Among them, the fluid resistance component Satisfies the expression:

[0046] Where, is the fluid resistance component, in units of ; is the fluid damping coefficient, unit ; is the real-time angular velocity of the stirring shaft, in units of .

[0047] The mechanical resistance component Satisfies the expression:

[0048] Where, is the mechanical resistance component, in units of , including equipment body resistance such as bearing friction and structural vibration; is the torque signal of the stirring shaft, in units of , is the fluid resistance component, in units of .

[0049] It should be noted that Mainly affected by the rheological properties of the slurry, It is mainly affected by the mechanical state of the equipment, and the two constitute an orthogonal feature space.

[0050] S3. Under different operating stages and slurry solid content conditions, kernel smoothing regression modeling is performed on the fluid resistance component and mechanical resistance component under standard working conditions to establish a standard relationship library divided by stage and process.

[0051] It should be noted that the homogenization process has obvious stage characteristics, for example, the feeding period, the slurry is in a non-uniform state, the torque signal fluctuates violently and irregularly, and the slurry viscosity has not yet formed a stable value; the wetting period, the liquid and powder are preliminarily mixed, the slurry gradually forms a viscoelastic body, the torque signal shows a clear upward trend, and the slurry viscosity increases rapidly; the dispersion period, the particle dispersion stage under the action of high shear force, the torque signal tends to be stable but still has small fluctuations, the slurry viscosity reaches the process requirement range, the homogenization period, the slurry reaches the uniform state stage, the torque signal fluctuates smoothly, and the slurry viscosity is stable near the target value. In different stages, the coupling mechanism of the fluid and the mechanical system is significantly different, the solid particle collision is mainly in the feeding period, the liquid-solid interface formation is mainly in the wetting period, the particle depolymerization is mainly in the dispersion period, and the uniform dispersion is mainly in the homogenization period. Therefore, the present application adopts a staged local kernel regression modeling method to construct an adaptive mechanical resistance reference value calculation model to accurately reflect the coupling mechanism of the fluid and the mechanical system in different stages.

[0052] Specifically, different slurry solid content set values Next, the history of different stages of homogenization The fluid resistance component and the mechanical resistance component under the standard working condition of the group, the standard working condition refers to the working condition of the equipment without mechanical failure (the bearing wear is less than 0.01 mm), the stable environment temperature is Under the condition, qualified slurry (the viscosity is in the standard range ) is prepared. Among them, is the preset number of standard working condition samples, which is set to 100 in the embodiment, and in other embodiments, the implementer can set it according to the actual implementation, but needs to ensure that the number of samples in each stage and each solid content interval is not less than 50 groups, so as to ensure the statistical reliability of the model.

[0053] The mechanical resistance component of each stage under the standard working condition is taken as the dependent variable, and the fluid resistance component is taken as the independent variable. The mechanical resistance component and the fluid resistance component under the standard working condition are kernel smoothing regression modeled to obtain the kernel regression model of each stage.

[0054] Different slurry solid content set values The kernel regression model in different stages is constructed to build a standard relationship library. In the standard relationship library, the kernel regression model of the four stages corresponds to every 0.5% slurry solid content interval, covering the conventional slurry solid content range of 55%-65%, so that the corresponding model can be matched under different process conditions. For the current working condition between two solid content intervals, a linear interpolation method is used to obtain the kernel regression model parameters corresponding to the current running stage of the slurry solid content set value under the current working condition.

[0055] S4. According to the kernel regression model corresponding to the current working condition in the standard relationship library, a mechanical resistance reference value is obtained based on the real-time fluid resistance component, and a mechanical resistance residual is obtained based on the difference between the real-time mechanical resistance component and the mechanical resistance reference value.

[0056] Specifically, the mechanical resistance reference value satisfies the expression:

[0057] in, For the current moment, The current mechanical resistance reference value, in units of ; is the fluid resistance component at the current moment; It is the kernel regression model corresponding to the set value of slurry solid content under the current working conditions at the current operating stage.

[0058] Furthermore, the mechanical resistance residual at the current moment is determined based on the difference between the mechanical resistance component at the current moment and the mechanical resistance reference value:

[0059] Where, For the current moment; is the mechanical resistance residual at the current moment; is the mechanical resistance component at the current moment; It is the mechanical resistance reference value at the current moment.

[0060] For example, Figure 3 It is a line graph of the mechanical resistance residual.

[0061] S5. Determine the equipment health index based on the distribution difference between the real-time mechanical resistance residual and the mechanical resistance residual under historical standard working conditions, and monitor the homogenization equipment status based on the equipment health index.

[0062] It should be noted that abnormal device status is manifested as The statistical characteristics of the residual between the measured value and the expected value deviate. Therefore, the present invention obtains the device health index at the current moment by constructing the difference between the statistical characteristics of the residual within the dynamic window and the historical normal distribution.

[0063] Specifically, the mechanical resistance residuals at all moments in the current operation phase constitute a mechanical resistance residual sequence, and the length of the mechanical resistance residual sequence is obtained: The length of the residual sequence in response to mechanical resistance Greater than or equal to , taking the mechanical resistance residual at the current moment as the last data in the window, construct The size of the reference window; the length of the residual sequence in response to mechanical resistance Less than , taking the mechanical resistance residual at the current moment as the last data in the window, construct The reference window of size. is the sliding window size, which is set to 60 in this embodiment. In other embodiments, the implementer can set it according to the actual implementation situation.

[0064] Get the history of the same slurry solid content setting value and the same operation stage as the current working condition The mean and standard deviation of the mechanical resistance residuals under the group standard working conditions, is the number of preset standard working condition samples.

[0065] Furthermore, the equipment health index at the current moment is obtained based on the distribution difference between the mechanical resistance residual in the reference window corresponding to the current moment and the mechanical resistance residual under the historical standard working conditions:

[0066] Where, The device health index at the current moment; is the mean of all mechanical resistance residuals in the reference window corresponding to the current moment; is the mean value of the mechanical resistance residual under historical standard working conditions; is the standard deviation of the mechanical resistance residual under historical standard working conditions; is the maximum value function, is an exponential function with a natural constant as its base; is the attenuation coefficient, which is used to control the sensitivity of the health index to abnormalities. The empirical value is , the implementation personnel can set according to the actual implementation situation EHI reflects the overall health status of the equipment's mechanical system, with a value range of 0-100. A larger value indicates a healthier equipment status.

[0067] Further, in response to , mark the current homogenization equipment status as normal; in response to , triggering an early warning, notifying equipment maintenance personnel to conduct preliminary inspections and record operating parameters; in response to , triggering an alarm to notify equipment maintenance personnel to conduct a detailed inspection and arrange preventive maintenance; in response to , notify the equipment maintenance personnel to immediately shut down the machine for maintenance to avoid production interruption or safety accidents caused by equipment failure.

[0068] For example, Figure 4 A line chart showing device health indicators.

[0069] In one embodiment, in response to The mechanical resistance component corresponding to the current moment is taken as the dependent variable, and the fluid resistance component increment is added to the solid content and the core regression model of the corresponding stage to update the model parameters.

[0070] The embodiment of the present application also discloses a lithium battery homogenate equipment state monitoring system, comprising a processor and a memory, the memory stores computer program instructions, when the computer program instructions are executed by the processor, a lithium battery homogenate equipment state monitoring method according to the present application is realized.

[0071] The above system also includes a communication bus and a communication interface and other components well known to those skilled in the art, the setting and function of which are known in the art, and therefore will not be repeated here.

Claims

1. A method for monitoring the status of a lithium battery homogenization device, characterized in that: include: Collect the torque signal, angular velocity of the stirring shaft, the strain signal of the slurry tank wall and the set value of the slurry solid content during the operation of the homogenization equipment; The effective viscosity of the slurry is calculated based on the torque signal and angular velocity, and the equivalent stiffness of the equipment is calculated by combining the contact force converted from the strain signal and the torque signal. The dynamic equation of the stirring system containing the fluid damping term and the structural stiffness term is constructed based on the effective viscosity of the slurry and the equivalent stiffness of the equipment, and the fluid resistance component and the mechanical resistance component are obtained by decoupling. Under different operating stages and slurry solid content conditions, the fluid resistance component and mechanical resistance component under standard working conditions are modeled by kernel smoothing regression to establish a standard relationship library; According to the kernel regression model corresponding to the current working condition in the standard relationship library, the mechanical resistance baseline value is obtained based on the real-time fluid resistance component, and the mechanical resistance residual is obtained based on the difference between the real-time mechanical resistance component and the mechanical resistance baseline value; According to the distribution difference between the real-time mechanical resistance residual and the mechanical resistance residual under historical standard working conditions, the equipment health index is determined, and the homogenization equipment status is monitored based on the equipment health index.

2. The method for monitoring the state of a lithium battery homogenization device according to claim 1, wherein: The effective viscosity of the slurry satisfies the expression: ； Where, is the effective viscosity of the slurry; is the torque signal; is the geometric coefficient of the stirring paddle; is the real-time angular velocity of the stirring shaft; is the blade diameter.

3. The method for monitoring the state of a lithium battery homogenization device according to claim 1, wherein: The equivalent stiffness of the equipment satisfies the expression: ； Where, is the equivalent stiffness of the equipment; is the contact force of the slurry on the tank wall, which is determined by the torque signal Calculated by lever principle , is the tank radius; is the strain signal of the slurry tank wall; is the characteristic length of the tank.

4. The method for monitoring the state of a lithium battery homogenization device according to claim 1, wherein: The dynamic equation of the stirring system is: ； Where, is the system moment of inertia; is the angular displacement; is the fluid damping coefficient; is the equivalent stiffness of the equipment; is the torque signal; Indicates angle First derivative with respect to time; Indicates angle Second derivative with respect to time; represents the moment of inertia; represents the fluid damping torque; represents the elastic restoring moment.

5. The method for monitoring the state of a lithium battery homogenization device according to claim 1, wherein: The decoupling to obtain the fluid resistance component and the mechanical resistance component includes: Fluid resistance component Satisfies the expression: , where is the fluid damping coefficient; is the real-time angular velocity of the stirring shaft; Mechanical resistance component Satisfies the expression: , where is the torque signal.

6. The method for monitoring the state of a lithium battery homogenization device according to claim 1, wherein: The standard operating conditions refer to the operating conditions under which the equipment produces qualified slurry without mechanical failure and stable ambient temperature.

7. The method for monitoring the state of a lithium battery homogenization device according to claim 1, wherein: The mechanical resistance reference value satisfies the expression: ； in, For the current moment, is the mechanical resistance baseline value at the current moment; is the fluid resistance component at the current moment; It is the kernel regression model corresponding to the set value of slurry solid content under the current working conditions at the current operating stage.

8. The method for monitoring the state of a lithium battery homogenization device according to claim 1, wherein: Determining the device health index includes: Build a reference window for the current moment; obtain historical data with the same slurry solid content setting value and the same operating stage as the current working condition The mean and standard deviation of the mechanical resistance residuals under the group standard working conditions, The number of preset standard working condition samples; the equipment health index at the current moment Satisfies the expression: , where is the mean of all mechanical resistance residuals in the reference window corresponding to the current moment; is the mean value of the mechanical resistance residual under historical standard working conditions; is the standard deviation of the mechanical resistance residual under historical standard working conditions; is the maximum value function, is an exponential function with a natural constant as its base; is the attenuation coefficient.

9. The method for monitoring the state of a lithium battery homogenization device according to claim 1, characterized in that: The homogenization equipment status monitoring according to the equipment health index includes: In response to , mark the current homogenization equipment status as normal; in response to , triggering an early warning, notifying equipment maintenance personnel to conduct preliminary inspections and record operating parameters; in response to , triggering an alarm to notify equipment maintenance personnel to conduct a detailed inspection and arrange preventive maintenance; in response to , notify the equipment maintenance personnel to immediately shut down the machine for maintenance, including: The device health index at the current moment.

10. A lithium battery homogenization equipment status monitoring system, characterized in that: include: A processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, a lithium battery homogenization equipment status monitoring method according to any one of claims 1 to 9 is implemented.

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