OLED (Organic Light Emitting Diode) nozzle driving waveform regulation and control method, device and equipment and storage medium

Abstract

The invention belongs to the technical field of OLED ink-jet printing, and discloses an OLED nozzle driving waveform regulation and control method, device and equipment and a storage medium, and the method comprises the steps: obtaining the structure parameters of an OLED nozzle and the physical and chemical parameters of ink, constructing a theoretical dynamic model about the driving voltage and the ink droplet jet volume based on the electroacoustic analogy theory, and calculating the driving waveform of the OLED nozzle according to the theoretical dynamic model; and constructing a voltage duration influence function, an ink droplet volume correction coefficient and an ink droplet steady-state speed function to optimize the theoretical dynamic model to obtain an ink droplet ejection theory-data hybrid model, and calculating to obtain a predicted ink droplet ejection volume according to a real-time driving waveform. Establishing a corresponding model prediction algorithm cost function and a driving waveform constraint condition so as to regulate and control the real-time driving waveform in real time; the driving waveform of the OLED nozzle is regulated and controlled through the ink droplet jetting theory-data mixing model, the model prediction algorithm cost function and the driving waveform constraint condition, and the printing precision and efficiency are improved.

Description

Technical Field

[0001] The present application relates to the technical field of OLED inkjet printing, and more specifically, to an OLED nozzle drive waveform control method, device, equipment and storage medium. Background Art

[0002] When printing OLED (Organic Light-Emitting Diode), whether the OLED nozzle can spray micro-ink droplets of a specific volume and speed directly determines the overall accuracy of the OLED printing equipment and the final quality of the display device. Whether the spraying state of the macro-micro-ink droplets meets the index requirements and can remain stable is mainly determined by the driving waveform of the OLED nozzle.

[0003] At present, the existing printing drive waveform debugging methods lack the support of automated debugging means, and have problems such as poor stability of debugging results, difficulty in achieving optimal accuracy, and low efficiency. In addition, the entire waveform debugging process cannot achieve online feedback and dynamic parameter adjustment, and is in a completely open-loop state, that is, the ink drop state change information during the printing process is not automatically associated with the regulation rules of the waveform parameters, which makes it difficult to automatically and accurately fine-tune the key printing control parameters, and ultimately cannot meet the needs of efficient and high-precision OLED printing.

[0004] Therefore, in order to solve the technical problems of poor stability of debugging results, difficulty in achieving optimal accuracy and low efficiency in the existing printing drive waveform debugging method, an OLED nozzle drive waveform control method, device, equipment and storage medium are urgently needed. Summary of the invention

[0005] The purpose of the present application is to provide an OLED nozzle drive waveform control method, device, equipment and storage medium, which can calculate the predicted ink droplet ejection volume based on the ink droplet ejection theory-data hybrid model optimized based on the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function, establish a corresponding model prediction algorithm cost function and drive waveform constraint conditions to control the real-time drive waveform, solve the problems of poor stability of debugging results, difficulty in achieving optimal accuracy and low efficiency in existing inkjet drive waveform debugging methods, and can associate the ink droplet state with the drive waveform to maintain the stable inkjet state of the OLED nozzle by adjusting the drive waveform. It can be suitable for different printing needs and improves printing accuracy and efficiency.

[0006] In a first aspect, the present application provides an OLED nozzle driving waveform control method, comprising: Obtain the structural parameters of the OLED nozzle and the physical and chemical parameters of the ink; Based on the electroacoustic analogy theory, the theoretical dynamic model of the driving voltage and the ink droplet ejection volume is constructed in combination with the structural parameters and the physicochemical parameters; Acquire historical ink drop volume data and historical ink drop velocity data during stable ink jetting to construct a voltage duration influence function, an ink drop volume correction coefficient, and an ink drop steady-state velocity function, and optimize the theoretical dynamic model according to the voltage duration influence function, the ink drop volume correction coefficient, and the ink drop steady-state velocity function to obtain an ink drop jetting theory-data hybrid model; Inputting the acquired real-time driving waveform of the OLED nozzle into the discretization equation corresponding to the ink droplet ejection theory-data hybrid model to calculate the predicted ink droplet ejection volume; A model prediction algorithm cost function and a driving waveform constraint condition corresponding to the predicted ink droplet ejection volume are established to perform real-time regulation on the real-time driving waveform.

[0007] The OLED nozzle driving waveform control method provided in the present application can realize the control of the driving waveform of the OLED nozzle. The predicted ink droplet ejection volume is calculated by the ink droplet ejection theory-data hybrid model obtained by optimizing the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function, and the corresponding model prediction algorithm cost function and driving waveform constraint conditions are established to control the real-time driving waveform, so as to solve the problems of poor stability of debugging results, difficulty in achieving optimal accuracy and low efficiency in the existing inkjet driving waveform debugging method. The ink droplet state and the driving waveform can be associated to maintain the stable inkjet state of the OLED nozzle by adjusting the driving waveform. The method can be suitable for different printing needs and improve the printing accuracy and efficiency.

[0008] Optionally, historical ink drop volume data and historical ink drop velocity data during stable ink jetting are obtained to construct a voltage duration influence function, an ink drop volume correction coefficient, and an ink drop steady-state velocity function, and the theoretical dynamic model is optimized according to the voltage duration influence function, the ink drop volume correction coefficient, and the ink drop steady-state velocity function to obtain an ink drop jetting theory-data hybrid model, including: Acquire voltage duration parameters and historical ink drop volume data of multiple groups of historical driving waveform data during stable ink jetting to construct a voltage duration influence function; Using a frequency domain identification method, substituting the voltage duration influence function into the theoretical dynamic model to determine the ink drop volume correction coefficient; Acquire multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting to construct an ink drop steady-state velocity function; The theoretical dynamic model is optimized according to the voltage duration influence function, the ink drop volume correction coefficient and the ink drop steady-state velocity function to obtain an ink drop ejection theory-data hybrid model.

[0009] The OLED nozzle driving waveform control method provided in the present application can realize the control of the driving waveform of the OLED nozzle. By stabilizing the voltage duration parameters of the historical driving waveform data during inkjet and the historical ink droplet volume data and the corresponding historical ink droplet velocity data, as well as the theoretical dynamic model, a voltage duration influence function, an ink droplet volume correction coefficient and an ink droplet steady-state velocity function are constructed to optimize the ink droplet ejection theory-data hybrid model. The ink droplet ejection theory-data hybrid model can predict the ink droplet ejection volume. The real-time driving waveform can be controlled by the predicted ink droplet ejection volume, which is beneficial to improving the control efficiency of the driving waveform.

[0010] Optionally, a voltage duration parameter and historical ink drop volume data of multiple sets of historical driving waveform data during stable inkjet are obtained to construct a voltage duration influence function, including: Acquire multiple groups of voltage duration parameters of historical driving waveform data that put the OLED nozzle in a stable inkjet state, and acquire corresponding historical ink drop volume data; A voltage duration effect function is obtained by performing quadratic surface fitting on the voltage duration parameters of the multiple groups of the historical drive waveform data and the corresponding historical ink drop volume data.

[0011] Optionally, a frequency domain identification method is used to substitute the voltage duration influence function into the theoretical dynamic model to determine the ink drop volume correction coefficient, including: Adding an ink drop volume correction coefficient term to the theoretical dynamic model, and improving the theoretical dynamic model through the voltage duration influence function to obtain an improved ink drop volume hybrid dynamic model; By using the frequency domain identification method, the voltage duration parameters of each group of the historical driving waveform data in the voltage duration influence function and the corresponding historical ink droplet volume data are input into the improved ink droplet volume hybrid dynamic model in turn, and the specific value of the ink droplet volume correction coefficient item is calculated to determine the ink droplet volume correction coefficient.

[0012] Optionally, acquiring multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting to construct an ink drop steady-state velocity function includes: Acquire multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting; A polynomial fitting is performed on the historical ink drop volume data and the corresponding historical ink drop velocity data to obtain an ink drop steady-state velocity function.

[0013] Optionally, the obtained real-time driving waveform of the OLED nozzle is input into a discretized equation corresponding to the ink droplet ejection theory-data hybrid model to calculate the predicted ink droplet ejection volume, including: Converting the ink drop ejection theory-data hybrid model into a corresponding discretized equation; Acquire the real-time driving waveform of the OLED nozzle; The real-time driving waveform is input into the discretization equation to calculate the predicted ink drop ejection volume.

[0014] Optionally, a model prediction algorithm cost function and a driving waveform constraint condition corresponding to the predicted ink droplet ejection volume are established to perform real-time control on the real-time driving waveform, including: Determining the cost function of the model prediction algorithm according to the difference between the predicted ink droplet ejection volume and the preset target ink droplet ejection volume; The driving waveform corresponding to ensuring that the OLED nozzle is in a stable inkjet state is the driving waveform constraint condition; According to the minimum value of the objective function for calculating the optimal parameters of the driving waveform constructed by the cost function of the model prediction algorithm and the driving waveform constraint condition, the real-time driving waveform is regulated in real time so that the real-time driving waveform tends to the optimal driving waveform corresponding to the minimum value of the objective function.

[0015] The OLED nozzle driving waveform control method provided in the present application can realize the control of the driving waveform of the OLED nozzle. The objective function for calculating the optimal parameters of the driving waveform is constructed by determining the cost function of the model prediction algorithm based on the difference between the predicted ink droplet ejection volume and the preset target ink droplet ejection volume, and the driving waveform constraint condition determined based on the driving waveform corresponding to the stable inkjet state of the OLED nozzle. The real-time driving waveform is controlled in real time to make the objective function approach the minimum value, so that the OLED nozzle is in a stable inkjet state, which is beneficial to improving the control efficiency of the driving waveform.

[0016] In a second aspect, the present application provides an OLED nozzle driving waveform control device, comprising: An acquisition module is used to acquire the structural parameters of the OLED nozzle and the physical and chemical parameters of the ink; A construction module, for constructing a theoretical dynamic model of driving voltage and ink droplet ejection volume based on electroacoustic analogy theory and in combination with the structural parameters and the physicochemical parameters; an optimization module, for obtaining historical ink drop volume data and historical ink drop velocity data during stable ink jetting, so as to construct a voltage duration influence function, an ink drop volume correction coefficient and an ink drop steady-state velocity function, and optimizing the theoretical dynamic model according to the voltage duration influence function, the ink drop volume correction coefficient and the ink drop steady-state velocity function, so as to obtain an ink drop jetting theory-data hybrid model; A calculation module, used for inputting the acquired real-time driving waveform of the OLED nozzle into the discretization equation corresponding to the ink droplet ejection theory-data hybrid model, and calculating and obtaining the predicted ink droplet ejection volume; The control module is used to establish a model prediction algorithm cost function and a driving waveform constraint condition corresponding to the predicted ink droplet ejection volume, so as to perform real-time control on the real-time driving waveform.

[0017] The OLED nozzle driving waveform control device establishes a corresponding model prediction algorithm cost function and driving waveform constraint conditions to control the real-time driving waveform through the predicted ink droplet ejection volume calculated based on the ink droplet ejection theory-data hybrid model optimized based on the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function, so as to solve the problems of poor stability of debugging results, difficulty in achieving optimal accuracy and low efficiency in the existing inkjet printing driving waveform debugging method, and can associate the ink droplet state with the driving waveform to maintain the stable inkjet state of the OLED nozzle by adjusting the driving waveform, which can be suitable for different printing requirements and improves the printing accuracy and efficiency.

[0018] In a third aspect, the present application provides an electronic device, including a processor and a memory, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, it runs the steps in the OLED nozzle drive waveform control method described above.

[0019] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps in the OLED nozzle driving waveform control method described above are executed.

[0020] Beneficial effects: The OLED nozzle drive waveform control method, device, equipment and storage medium provided in the present application, through the predicted ink droplet ejection volume calculated by the ink droplet ejection theory-data hybrid model optimized based on the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function, establishes the corresponding model prediction algorithm cost function and drive waveform constraint conditions to control the real-time drive waveform, solves the problems of poor stability of debugging results, difficulty in achieving optimal accuracy and low efficiency in the existing inkjet drive waveform debugging method, can associate the ink droplet state with the drive waveform, so as to maintain the stable inkjet state of the OLED nozzle by adjusting the drive waveform, can be suitable for different printing needs, and improves the printing accuracy and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 This is a flow chart of the OLED nozzle drive waveform control method provided in an embodiment of the present application.

[0022] Figure 2 This is a schematic diagram of the structure of the OLED nozzle driving waveform control device provided in an embodiment of the present application.

[0023] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0024] Explanation of reference numerals: 1. Acquisition module; 2. Construction module; 3. Optimization module; 4. Calculation module; 5. Control module; 301. Processor; 302. Memory; 303. Communication bus. DETAILED DESCRIPTION

[0025] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present application.

[0026] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0027] Please refer to Figure 1 , Figure 1 A method for controlling an OLED nozzle driving waveform in some embodiments of the present application is used to control the driving waveform of an OLED nozzle, comprising the steps of: Step S101, obtaining structural parameters of the OLED nozzle and physicochemical parameters of the ink; Step S102, based on the electroacoustic analogy theory, combined with the structural parameters and the physicochemical parameters, a theoretical dynamic model of the driving voltage and the ink droplet ejection volume is constructed; Step S103, obtaining historical ink drop volume data and historical ink drop velocity data during stable ink jetting to construct a voltage duration influence function, an ink drop volume correction coefficient, and an ink drop steady-state velocity function, and optimizing the theoretical dynamic model according to the voltage duration influence function, the ink drop volume correction coefficient, and the ink drop steady-state velocity function to obtain an ink drop jetting theory-data hybrid model; Step S104, inputting the acquired real-time driving waveform of the OLED nozzle into the discretization equation corresponding to the ink droplet ejection theory-data hybrid model to calculate and obtain the predicted ink droplet ejection volume; Step S105 , establishing a model prediction algorithm cost function and a driving waveform constraint condition corresponding to the predicted ink droplet ejection volume, so as to perform real-time control on the real-time driving waveform.

[0028] The OLED nozzle driving waveform control method calculates the predicted ink droplet ejection volume based on the ink droplet ejection theory-data hybrid model optimized based on the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function, establishes a corresponding model prediction algorithm cost function and driving waveform constraint conditions to control the real-time driving waveform, solves the problems of poor stability of debugging results, difficulty in achieving optimal accuracy and low efficiency in the existing inkjet driving waveform debugging method, can associate the ink droplet state with the driving waveform, and maintain the stable inkjet state of the OLED nozzle by adjusting the driving waveform, can be suitable for different printing needs, and improves the printing accuracy and efficiency.

[0029] Specifically, in step S101, the structural parameters of the OLED nozzle and the physicochemical parameters of the ink are obtained, wherein the structural parameters of the OLED nozzle include the structure of each part of the OLED nozzle and its material, model and size data, such as the size and angle of the nozzle; the physicochemical parameters of the ink include the surface tension, viscosity and density of the ink; and the structural parameters of the OLED nozzle and the physicochemical parameters of the ink can be obtained from the product manual.

[0030] Specifically, in step S102, based on the electroacoustic analogy theory, combined with structural parameters and physicochemical parameters, a theoretical dynamic model of driving voltage and ink droplet ejection volume is constructed. The theoretical dynamic model describes the dynamic change process inside the OLED nozzle from the deformation of the piezoelectric material caused by the applied voltage to the ejection of ink droplets. The theoretical dynamic model is specifically: ; Where s is the Laplace operator; is the ink drop ejection volume, is the voltage amplitude of the driving waveform of the OLED nozzle; is the coupling coefficient of the piezoelectric material converting deformation mechanical energy into acoustic energy, is the equivalent compressibility coefficient of the piezoelectric material of the OLED nozzle; is the equivalent dynamic coefficient related to the size of each structural part of the OLED nozzle and the surface tension of the ink; is the equivalent dynamic coefficient related to the size of each structural part of the OLED nozzle and the viscosity of the ink; is the equivalent dynamic coefficient related to the size of each part of the OLED nozzle structure and the ink density, It is an equivalent dynamic coefficient related to the size of each structural part of the OLED nozzle and the speed of sound; wherein the above multiple equivalent dynamic coefficients can be consulted and calculated from the product manuals of the OLED nozzle and the ink. For example, each equivalent dynamic coefficient can directly use the equivalent dynamic coefficient of the nozzle size and the corresponding parameter, or use the sum of the equivalent dynamic coefficients of the size of each structural part of the OLED nozzle and the corresponding parameter, or use the mean or weighted average of the equivalent dynamic coefficients of the size of each structural part of the OLED nozzle and the corresponding parameter.

[0031] Specifically, in step S103, historical ink drop volume data and historical ink drop velocity data during stable ink jetting are obtained to construct a voltage duration influence function, an ink drop volume correction coefficient, and an ink drop steady-state velocity function, and the theoretical dynamic model is optimized according to the voltage duration influence function, the ink drop volume correction coefficient, and the ink drop steady-state velocity function to obtain an ink drop jetting theory-data hybrid model, including: Acquire voltage duration parameters and historical ink drop volume data of multiple groups of historical driving waveform data during stable ink jetting to construct a voltage duration influence function; The frequency domain identification method is used to substitute the voltage duration influence function into the theoretical dynamic model to determine the ink drop volume correction coefficient. Acquire multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting to construct an ink drop steady-state velocity function; According to the voltage duration influence function, ink drop volume correction coefficient and ink drop steady-state velocity function, the theoretical dynamic model is optimized to obtain the ink drop ejection theory-data hybrid model.

[0032] Specifically, in step S103, voltage duration parameters and historical ink drop volume data of multiple groups of historical driving waveform data during stable ink jetting are obtained to construct a voltage duration influence function, including: Acquire multiple sets of voltage duration parameters of historical driving waveform data that put the OLED nozzle in a stable inkjet state, and acquire corresponding historical ink drop volume data; The voltage duration parameters and historical ink drop volume data of multiple groups of historical driving waveform data during stable inkjet are fitted with a quadratic surface to obtain the voltage duration influence function.

[0033] In step S103, historical driving waveform data is obtained (the historical driving waveform data includes historical records corresponding to the voltage amplitude of the driving waveform and historical records corresponding to the voltage duration of the driving waveform, etc.), and multiple sets of voltage duration parameters that make the OLED nozzle in a stable inkjet state are extracted from the historical driving waveform data, and the corresponding historical ink drop volume data are obtained. Among them, the historical inkjet image, historical ink drop volume data or historical inkjet flight speed corresponding to the voltage duration parameter of each historical driving waveform data is obtained, and the inkjet condition of the historical inkjet image is identified through image recognition technology or preset judgment criteria (which will not be described in detail here) to determine whether the OLED nozzle is in a stable inkjet state, thereby extracting multiple sets of voltage duration parameters of the historical driving waveform data that make the OLED nozzle in a stable inkjet state, and obtaining the corresponding historical ink drop volume data.

[0034] The voltage duration parameters and historical ink drop volume data of multiple sets of historical driving waveform data during stable inkjet are fitted with quadratic surfaces to obtain the voltage duration influence function. The voltage duration influence function is specifically: ; in, is the voltage duration effect function value, d is the driving waveform duration (voltage duration parameter of historical driving waveform data), are the fitting polynomial coefficients of the driving waveform duration; is the number of polynomials (i.e., the degree of the polynomial); n is the order of the polynomial; m is the number of terms in the polynomial; where The order n of each polynomial is determined by the nonlinearity of the collected data (voltage duration parameters of the historical driving waveform data during stable inkjet and the historical ink drop volume data). Generally, there are 3 or 4 of them, and the polynomial order n generally does not exceed 7.

[0035] Specifically, in step S103, the frequency domain identification method is used to substitute the voltage duration influence function into the theoretical dynamic model to determine the ink drop volume correction coefficient, including: Adding the ink drop volume correction coefficient term to the theoretical dynamic model and improving the theoretical dynamic model through the voltage duration influence function, the improved ink drop volume hybrid dynamic model is obtained; Using the frequency domain identification method, the voltage duration parameters of each group of historical driving waveform data in the voltage duration influence function and the corresponding historical ink droplet volume data are input into the improved ink droplet volume hybrid dynamic model in turn, and the specific value of the ink droplet volume correction coefficient term is calculated to determine the ink droplet volume correction coefficient.

[0036] In step S103, the ink drop volume correction coefficient term is added to the theoretical dynamic model, and after fitting to obtain the voltage duration influence function, the voltage duration influence function is substituted into the theoretical dynamic model provided with the ink drop volume correction coefficient term to improve it, and an improved ink drop volume hybrid dynamic model is obtained. The improved ink drop volume hybrid dynamic model is specifically: ; in, is the ink drop volume correction factor, The steady-state parameter group representing the duration of the driving waveform corresponding to the OLED nozzle in a stable inkjet state is used to correct the voltage duration parameter of the driving waveform corresponding to the OLED nozzle in a stable inkjet state.

[0037] Using the frequency domain identification method, the voltage duration parameters of each group of historical driving waveform data in the voltage duration influence function and the corresponding historical ink droplet volume data are input into the improved ink droplet volume hybrid dynamic model in turn, and the specific value of the ink droplet volume correction coefficient term is calculated to determine the specific ink droplet volume correction coefficient.

[0038] Specifically, in step S103, multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting are obtained to construct an ink drop steady-state velocity function, including: Acquire multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting; The historical ink drop volume data and the corresponding historical ink drop velocity data are fitted with a polynomial to obtain the ink drop steady-state velocity function.

[0039] In step S103, the ink droplet steady-state velocity function is used to describe the variation law of the average velocity of ink droplet jetting. Considering that the ink droplet jetting volume and the ink droplet jetting velocity are highly correlated, it is only necessary to consider whether the average velocity meets the target velocity during the printing process. Therefore, a polynomial fitting is performed on the historical ink droplet volume data and the corresponding historical ink droplet velocity data during stable ink jetting to obtain the ink droplet steady-state velocity function, which is specifically: ; in, is the ink drop velocity data; is the ink drop volume data (historical ink drop volume data, the number of historical ink drop volume data corresponds to the voltage duration parameter of the above-mentioned historical driving waveform data), are the coefficients of the fitted polynomial for the drop volume data.

[0040] Through the ink droplet steady-state velocity function, the ink droplet velocity data corresponding to the ink droplet volume interval can be calculated based on the ink droplet volume data during stable ink jetting.

[0041] In step S103, the theoretical dynamic model is optimized according to the voltage duration influence function, the ink drop volume correction coefficient and the ink drop steady-state velocity function to obtain the ink drop ejection theory-data hybrid model. Through the ink drop ejection theory-data hybrid model, the ink drop ejection volume and ink drop steady-state velocity corresponding to different driving waveforms can be calculated. In summary, the ink drop ejection theory-data hybrid model is specifically: ; ; in, is the steady-state velocity of the ink drop; t is the time; is the ink droplet steady-state velocity function (i.e., the ink droplet velocity mixed steady-state model), Indicated in Substitution The calculation result of the actual value; is the limit symbol, It means that time t tends to infinity.

[0042] Specifically, in step S104, the acquired real-time driving waveform of the OLED nozzle is input into the discretization equation corresponding to the ink droplet ejection theory-data hybrid model to calculate the predicted ink droplet ejection volume, including: Convert the droplet ejection theory-data hybrid model into a discretized equation; Get the real-time driving waveform of the OLED nozzle; The real-time driving waveform is input into the discretized equation and the predicted droplet ejection volume (predicted droplet ejection volume) is calculated.

[0043] In step S104, the real-time driving waveform of the OLED nozzle is obtained (the real-time driving waveform includes the voltage amplitude of the real-time driving waveform and the voltage duration of the real-time driving waveform), and the ink droplet ejection theory-data hybrid model is converted into an expression form that is convenient for the design of the prediction algorithm to obtain a discretized equation. The discretized equation is specifically: ; in, is the state of the injection process at time k (current time), , is the volume flow rate flowing through the OLED nozzle restrictor and nozzle at time k, is the volume flow rate through the nozzle at time k, is the pressure difference across the throttle of the OLED nozzle at time k, is the pressure difference at both ends of the nozzle at time k; is the state of the injection process at time k+1 (the next moment); is the system state matrix, is the system input matrix, Determined by the OLED nozzle structure parameters and ink characteristic parameters, Determined by the piezoelectric material parameters, namely and For parameters ,parameter ,parameter and parameters Related functions; is the output matrix, ; represents the ink droplet ejection volume ejected by the OLED nozzle at time k, that is, the predicted ink droplet ejection volume; Represents the control input at time k, that is, the real-time driving waveform.

[0044] The inkjet process status of the next N cycles can be calculated The iterative calculation is as follows: ; in, is the inkjet process state quantity, is the inkjet cycle, To control the time domain, ,exist In the time domain, That is, from the end of the control time domain to the end of the inkjet cycle, the input real-time driving waveform is considered to be 0.

[0045] In summary, by combining the discretized equation and the state quantity of the inkjet process, the predicted ink droplet ejection volume for the next N cycles can be obtained as follows: ; in, is the predicted ink drop ejection volume in the next N cycles; is the system state matrix in the next N cycles, ; is the impact matrix in the next N cycles, ; is the control input at the initial moment, that is, the input initial value of the real-time drive waveform, . is the predicted control input sequence optimized in the next N cycles, that is, the predicted driving waveform sequence, ; The superscript T is the transposition symbol.

[0046] In summary, the real-time driving waveform is input into the discretization equation, and the corresponding predicted ink droplet ejection volume is calculated.

[0047] Specifically, in step S105, a model prediction algorithm cost function and a driving waveform constraint condition corresponding to the predicted ink droplet ejection volume are established to perform real-time control on the real-time driving waveform, including: Determining a model prediction algorithm cost function according to a difference between a predicted ink droplet ejection volume and a preset target ink droplet ejection volume; The driving waveform constraint condition is to ensure that the driving waveform corresponding to the OLED nozzle is in a stable inkjet state; According to the minimum value of the objective function for calculating the optimal parameters of the driving waveform constructed based on the cost function of the model prediction algorithm and the driving waveform constraints, the real-time driving waveform is regulated in real time so that the real-time driving waveform tends to the optimal driving waveform corresponding to the minimum value of the objective function, thereby obtaining the optimal driving waveform.

[0048] In step S105, a model prediction algorithm cost function is determined based on the difference between the predicted ink droplet ejection volume and the preset target ink droplet ejection volume. The model prediction algorithm cost function is specifically: ; Among them, J is the cost function value of the model prediction algorithm; H is the first constant matrix, , R is the diagonal matrix of the system input matrix, and its dimension is , Q is the diagonal matrix of the system state matrix, with dimension N; G is the second constant matrix, , , is the error matrix, is the target ink droplet ejection volume; P is the third constant matrix, ; Among them, Q, R and It can be set according to actual needs; Q and R determine the feasibility of the cost function of the model prediction algorithm and the final ink drop control accuracy.

[0049] The driving waveform constraint condition is to ensure that the driving waveform corresponding to the OLED nozzle is in a stable inkjet state, wherein the interval of the driving waveform corresponding to the OLED nozzle in a stable inkjet state is set to .

[0050] According to the cost function of the model prediction algorithm and the driving waveform constraints, an objective function for calculating the optimal parameters of the driving waveform is constructed. The specific objective function is: ; in, is the target value of the driving waveform; is a constraint condition.

[0051] While the real-time driving waveform is being regulated in real time, the objective function is iterated through the regulated real-time driving waveform, so that the objective function tends to the minimum value and the real-time driving waveform tends to the optimum.

[0052] During the control process, the objective function is iteratively calculated to obtain the target value of the driving waveform. The control input (drive waveform) is at its minimum value. When it is at its minimum, the corresponding ink droplet ejection volume has reached the target ink droplet ejection volume. At the same time, the ink droplet velocity closely related to the volume must also meet the requirements. The control input at this time is the optimal driving waveform.

[0053] As can be seen from the above, the OLED nozzle driving waveform control method obtains the structural parameters of the OLED nozzle and the physicochemical parameters of the ink, and based on the electroacoustic analogy theory, combines the structural parameters and the physicochemical parameters to construct a theoretical dynamic model about the driving voltage and the ink droplet ejection volume, obtains the historical ink droplet volume data and the historical ink droplet velocity data during stable ink jetting, so as to construct the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function, and optimizes the theoretical dynamic model according to the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function to obtain the ink droplet ejection theory-data hybrid model, and inputs the obtained real-time driving waveform of the OLED nozzle into the discretized equation corresponding to the ink droplet ejection theory-data hybrid model to calculate and obtain the predicted ink droplet ejection volume. A model prediction algorithm cost function and driving waveform constraint conditions corresponding to the predicted ink droplet ejection volume are established to perform real-time regulation of the real-time driving waveform; thereby, the predicted ink droplet ejection volume is calculated by the ink droplet ejection theory-data hybrid model optimized based on the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function, and the corresponding model prediction algorithm cost function and driving waveform constraint conditions are established to regulate the real-time driving waveform, so as to solve the problems of poor stability of debugging results, difficulty in achieving optimal accuracy and low efficiency in the existing inkjet driving waveform debugging method, and to associate the ink droplet state with the driving waveform to maintain the stable inkjet state of the OLED nozzle by regulating the driving waveform, so as to be suitable for different printing needs and improve the printing accuracy and efficiency.

[0054] refer to Figure 2 The present application provides an OLED nozzle driving waveform control device, which is used to control the driving waveform of the OLED nozzle, including: Acquisition module 1, used to acquire structural parameters of the OLED nozzle and physical and chemical parameters of the ink; Building module 2, for building a theoretical dynamic model of driving voltage and ink droplet ejection volume based on electroacoustic analogy theory and combining structural parameters and physicochemical parameters; Optimization module 3 is used to obtain historical ink drop volume data and historical ink drop velocity data during stable ink jetting, so as to construct a voltage duration influence function, an ink drop volume correction coefficient and an ink drop steady-state velocity function, and optimize the theoretical dynamic model according to the voltage duration influence function, the ink drop volume correction coefficient and the ink drop steady-state velocity function to obtain an ink drop jetting theory-data hybrid model; A calculation module 4 is used to input the acquired real-time driving waveform of the OLED nozzle into the discretization equation corresponding to the ink droplet ejection theory-data hybrid model to calculate and obtain the predicted ink droplet ejection volume; The control module 5 is used to establish a model prediction algorithm cost function and a driving waveform constraint condition corresponding to the predicted ink droplet ejection volume, so as to perform real-time control on the real-time driving waveform.

[0055] The OLED nozzle driving waveform control device establishes a corresponding model prediction algorithm cost function and driving waveform constraint conditions to control the real-time driving waveform through the predicted ink droplet ejection volume calculated based on the ink droplet ejection theory-data hybrid model optimized based on the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function, so as to solve the problems of poor stability of debugging results, difficulty in achieving optimal accuracy and low efficiency in the existing inkjet printing driving waveform debugging method, and can associate the ink droplet state with the driving waveform to maintain the stable inkjet state of the OLED nozzle by adjusting the driving waveform, which can be suitable for different printing requirements and improves the printing accuracy and efficiency.

[0056] Specifically, when the acquisition module 1 is executed, the structural parameters of the OLED nozzle and the physicochemical parameters of the ink are acquired, wherein the structural parameters of the OLED nozzle include the structure of each part of the OLED nozzle and its material, model and size data, such as the size and angle of the nozzle; the physicochemical parameters of the ink include the surface tension, viscosity and density of the ink; and the structural parameters of the OLED nozzle and the physicochemical parameters of the ink can be obtained from the product manual.

[0057] Specifically, when building module 2 is executed, based on the electroacoustic analogy theory, combined with structural parameters and physicochemical parameters, a theoretical dynamic model of driving voltage and ink droplet ejection volume is constructed. The theoretical dynamic model describes the dynamic change process inside the OLED nozzle from the deformation of the piezoelectric material caused by the applied voltage to the ejection of ink droplets. The theoretical dynamic model is specifically: ; Where s is the Laplace operator; is the ink drop ejection volume, is the voltage amplitude of the driving waveform of the OLED nozzle; is the coupling coefficient of the piezoelectric material converting deformation mechanical energy into acoustic energy, is the equivalent compressibility coefficient of the piezoelectric material of the OLED nozzle; is the equivalent dynamic coefficient related to the size of each structural part of the OLED nozzle and the surface tension of the ink; is the equivalent dynamic coefficient related to the size of each structural part of the OLED nozzle and the viscosity of the ink; is the equivalent dynamic coefficient related to the size of each part of the OLED nozzle structure and the ink density, It is an equivalent dynamic coefficient related to the size of each structural part of the OLED nozzle and the speed of sound; wherein the above multiple equivalent dynamic coefficients can be consulted and calculated from the product manuals of the OLED nozzle and the ink. For example, each equivalent dynamic coefficient can directly use the equivalent dynamic coefficient of the nozzle size and the corresponding parameter, or use the sum of the equivalent dynamic coefficients of the size of each structural part of the OLED nozzle and the corresponding parameter, or use the mean or weighted average of the equivalent dynamic coefficients of the size of each structural part of the OLED nozzle and the corresponding parameter.

[0058] Specifically, when the optimization module 3 obtains the historical ink drop volume data and the historical ink drop velocity data during stable ink jetting to construct the voltage duration influence function, the ink drop volume correction coefficient and the ink drop steady-state velocity function, and optimizes the theoretical dynamic model according to the voltage duration influence function, the ink drop volume correction coefficient and the ink drop steady-state velocity function to obtain the ink drop jetting theory-data hybrid model, the following is executed: Acquire voltage duration parameters and historical ink drop volume data of multiple groups of historical driving waveform data during stable ink jetting to construct a voltage duration influence function; The frequency domain identification method is used to substitute the voltage duration influence function into the theoretical dynamic model to determine the ink drop volume correction coefficient. According to the voltage duration influence function, ink drop volume correction coefficient and ink drop steady-state velocity function, the theoretical dynamic model is optimized to obtain the ink drop ejection theory-data hybrid model.

[0059] Specifically, when the optimization module 3 obtains the voltage duration parameters and the historical ink drop volume data of multiple groups of historical driving waveform data during stable ink jetting to construct the voltage duration influence function, it executes: Acquire multiple sets of voltage duration parameters of historical driving waveform data that put the OLED nozzle in a stable inkjet state, and acquire corresponding historical ink drop volume data; The voltage duration parameters and historical ink drop volume data of multiple groups of historical driving waveform data during stable inkjet are fitted with a quadratic surface to obtain the voltage duration influence function.

[0060] When the optimization module 3 is executed, multiple groups of voltage duration parameters that make the OLED nozzle in a stable inkjet state are extracted from the historical driving waveform data, and the corresponding historical ink drop volume data are obtained. Among them, the historical inkjet image, historical ink drop volume data or historical inkjet flight speed corresponding to the voltage duration parameters of each historical driving waveform data is obtained, and the inkjet condition of the historical inkjet image is identified through image recognition technology or preset judgment criteria (which will not be described in detail here) to determine whether the OLED nozzle is in a stable inkjet state, thereby extracting multiple groups of voltage duration parameters of the historical driving waveform data that make the OLED nozzle in a stable inkjet state, and obtaining the corresponding historical ink drop volume data).

[0061] The voltage duration parameters and historical ink drop volume data of multiple sets of historical driving waveform data during stable inkjet are fitted with quadratic surfaces to obtain the voltage duration influence function. The voltage duration influence function is specifically: ; in, is the voltage duration effect function value, d is the driving waveform duration (voltage duration parameter of historical driving waveform data), are the fitting polynomial coefficients of the driving waveform duration; is the number of polynomials (i.e., the degree of the polynomial); n is the order of the polynomial; m is the number of terms in the polynomial; where The order n of each polynomial is determined by the nonlinearity of the collected data (voltage duration parameters of the historical driving waveform data during stable inkjet and the historical ink drop volume data). Generally, there are 3 or 4 of them, and the polynomial order n generally does not exceed 7.

[0062] Specifically, when the optimization module 3 adopts the frequency domain identification method and substitutes the voltage duration influence function into the theoretical dynamic model to determine the ink drop volume correction coefficient, the following is performed: Adding the ink drop volume correction coefficient term to the theoretical dynamic model and improving the theoretical dynamic model through the voltage duration influence function, the improved ink drop volume hybrid dynamic model is obtained; Using the frequency domain identification method, the voltage duration parameters of each group of historical driving waveform data in the voltage duration influence function and the corresponding historical ink droplet volume data are input into the improved ink droplet volume hybrid dynamic model in turn, and the specific value of the ink droplet volume correction coefficient term is calculated to determine the ink droplet volume correction coefficient.

[0063] When the optimization module 3 is executed, the ink drop volume correction coefficient term is added to the theoretical dynamic model, and after fitting the voltage duration influence function, the voltage duration influence function is substituted into the theoretical dynamic model with the ink drop volume correction coefficient term for improvement, and an improved ink drop volume mixed dynamic model is obtained. The improved ink drop volume mixed dynamic model is specifically: ; in, is the ink drop volume correction factor, The steady-state parameter group representing the duration of the driving waveform corresponding to the OLED nozzle in a stable inkjet state is used to correct the voltage duration parameter of the driving waveform corresponding to the OLED nozzle in a stable inkjet state.

[0064] Using the frequency domain identification method, the voltage duration parameters of each group of historical driving waveform data in the voltage duration influence function and the corresponding historical ink droplet volume data are input into the improved ink droplet volume hybrid dynamic model in turn, and the specific value of the ink droplet volume correction coefficient term is calculated to determine the specific ink droplet volume correction coefficient.

[0065] Specifically, when the optimization module 3 obtains multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting to construct an ink drop steady-state velocity function, now: Acquire multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting; The historical ink drop volume data and the corresponding historical ink drop velocity data are fitted with a polynomial to obtain the ink drop steady-state velocity function.

[0066] When the optimization module 3 is executed, the ink droplet steady-state velocity function is used to describe the variation law of the average velocity of ink droplet jetting. Considering that the ink droplet jetting volume and the ink droplet jetting velocity are highly correlated, it is only necessary to consider whether the average velocity meets the target velocity during the printing process. Therefore, a polynomial fitting is performed on the historical ink droplet volume data and the corresponding historical ink droplet velocity data during stable ink jetting to obtain the ink droplet steady-state velocity function, which is specifically: ; in, is the ink drop velocity data; is the ink drop volume data (historical ink drop volume data, the number of historical ink drop volume data corresponds to the voltage duration parameter of the above-mentioned historical driving waveform data), are the coefficients of the fitted polynomial for the drop volume data.

[0067] Through the ink droplet steady-state velocity function, the ink droplet velocity data corresponding to the ink droplet volume interval can be calculated based on the ink droplet volume data during stable ink jetting.

[0068] When the optimization module 3 is executed, the theoretical dynamic model is optimized according to the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function to obtain the ink droplet ejection theory-data hybrid model. Through the ink droplet ejection theory-data hybrid model, the ink droplet ejection volume and ink droplet steady-state velocity corresponding to different driving waveforms can be calculated. In summary, the ink droplet ejection theory-data hybrid model is specifically: ; ; in, is the steady-state velocity of the ink drop; t is the time; is the ink droplet steady-state velocity function (i.e., the ink droplet velocity mixed steady-state model), Indicated in Substitution The calculation result of the actual value; is the limit symbol, It means that time t tends to infinity.

[0069] Specifically, when the calculation module 4 inputs the acquired real-time driving waveform of the OLED nozzle into the discretization equation corresponding to the ink droplet ejection theory-data hybrid model and calculates the predicted ink droplet ejection volume, it executes: Convert the droplet ejection theory-data hybrid model into a discretized equation; Get the real-time driving waveform of the OLED nozzle; The real-time driving waveform is input into the discretized equation and the predicted droplet ejection volume (predicted droplet ejection volume) is calculated.

[0070] When the calculation module 4 is executed, the ink droplet ejection theory-data hybrid model is converted into an expression form that is convenient for the design of the prediction algorithm to obtain a discretized equation. The discretized equation is specifically: ; in, is the state of the injection process at time k (current time), , is the volume flow rate flowing through the OLED nozzle restrictor and nozzle at time k, is the volume flow rate through the nozzle at time k, is the pressure difference across the throttle of the OLED nozzle at time k, is the pressure difference at both ends of the nozzle at time k; is the state of the injection process at time k+1 (the next moment); is the system state matrix, is the system input matrix, Determined by the OLED nozzle structure parameters and ink characteristic parameters, Determined by the piezoelectric material parameters, namely and For parameters ,parameter ,parameter and parameters Related functions; is the output matrix, ; represents the ink droplet ejection volume ejected by the OLED nozzle at time k, that is, the predicted ink droplet ejection volume; Represents the control input at time k, that is, the real-time driving waveform.

[0071] The inkjet process status of the next N cycles can be calculated The iterative calculation is as follows: ; in, is the inkjet process state quantity, is the inkjet cycle, To control the time domain, ,exist In the time domain, That is, from the end of the control time domain to the end of the inkjet cycle, the input real-time driving waveform is considered to be 0.

[0072] In summary, by combining the discretized equation and the state quantity of the inkjet process, the predicted ink droplet ejection volume for the next N cycles can be obtained as follows: ; in, is the predicted ink drop ejection volume in the next N cycles; is the system state matrix in the next N cycles, ; is the impact matrix in the next N cycles, ; is the control input at the initial moment, that is, the input initial value of the real-time drive waveform, . is the predicted control input sequence optimized in the next N cycles, that is, the predicted driving waveform sequence, ; The superscript T is the transposition symbol.

[0073] In summary, the real-time driving waveform is input into the discretization equation, and the corresponding predicted ink droplet ejection volume is calculated.

[0074] Specifically, when the control module 5 establishes the model prediction algorithm cost function and the driving waveform constraint condition corresponding to the predicted ink droplet ejection volume for real-time control of the real-time driving waveform, it executes: Determining a model prediction algorithm cost function according to a difference between a predicted ink droplet ejection volume and a preset target ink droplet ejection volume; The driving waveform constraint condition is to ensure that the driving waveform corresponding to the OLED nozzle is in a stable inkjet state; According to the minimum value of the objective function for calculating the optimal parameters of the driving waveform constructed based on the cost function of the model prediction algorithm and the driving waveform constraints, the real-time driving waveform is regulated in real time so that the real-time driving waveform tends to the optimal driving waveform corresponding to the minimum value of the objective function.

[0075] When the control module 5 is executed, the model prediction algorithm cost function is determined according to the difference between the predicted ink droplet ejection volume and the preset target ink droplet ejection volume. The model prediction algorithm cost function is specifically: ; Among them, J is the cost function value of the model prediction algorithm; H is the first constant matrix, , R is the diagonal matrix of the system input matrix, and its dimension is , Q is the diagonal matrix of the system state matrix, with dimension N; G is the second constant matrix, , , is the error matrix, is the target ink droplet ejection volume; P is the third constant matrix, ; Among them, Q, R and It can be set according to actual needs; Q and R determine the feasibility of the cost function of the model prediction algorithm and the final ink drop control accuracy.

[0076] The driving waveform constraint condition is to ensure that the driving waveform corresponding to the OLED nozzle is in a stable inkjet state, wherein the interval of the driving waveform corresponding to the OLED nozzle in a stable inkjet state is set to .

[0077] When the control module 5 is executed, it constructs an objective function for calculating the optimal parameters of the driving waveform according to the cost function of the model prediction algorithm and the driving waveform constraints. The objective function is specifically: ; in, is the target value of the driving waveform; is a constraint condition.

[0078] While the real-time driving waveform is being regulated in real time, the objective function is iterated through the regulated real-time driving waveform, so that the objective function tends to the minimum value and the real-time driving waveform tends to the optimum.

[0079] During the control process, the objective function is iteratively calculated to obtain the target value of the driving waveform. The control input (drive waveform) is at its minimum value. When it is at its minimum, the corresponding ink droplet ejection volume has reached the target ink droplet ejection volume. At the same time, the ink droplet velocity closely related to the volume must also meet the requirements. The control input at this time is the optimal driving waveform.

[0080] As can be seen from the above, the OLED nozzle driving waveform control device obtains the structural parameters of the OLED nozzle and the physicochemical parameters of the ink, and based on the electroacoustic analogy theory, combines the structural parameters and the physicochemical parameters to construct a theoretical dynamic model about the driving voltage and the ink droplet ejection volume, obtains the historical ink droplet volume data and the historical speed data during stable ink jetting, so as to construct the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state speed function, and optimizes the theoretical dynamic model according to the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state speed function to obtain the ink droplet ejection theory-data hybrid model, inputs the obtained real-time driving waveform of the OLED nozzle into the discretized equation corresponding to the ink droplet ejection theory-data hybrid model, calculates the predicted ink droplet ejection volume, and constructs A model prediction algorithm cost function and driving waveform constraint conditions corresponding to the predicted ink droplet ejection volume are established to adjust the real-time driving waveform in real time; thereby, the predicted ink droplet ejection volume is calculated by the ink droplet ejection theory-data hybrid model optimized based on the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state velocity function, and the corresponding model prediction algorithm cost function and driving waveform constraint conditions are established to adjust the real-time driving waveform, so as to solve the problems of poor stability of debugging results, difficulty in achieving optimal accuracy and low efficiency in the existing inkjet driving waveform debugging method, and to associate the ink droplet state with the driving waveform to maintain the stable inkjet state of the OLED nozzle by adjusting the driving waveform, so as to be suitable for different printing needs and improve the printing accuracy and efficiency.

[0081] Please refer to Figure 3 , Figure 3The present application provides a structural schematic diagram of an electronic device provided in an embodiment of the present application. The present application provides an electronic device, including: a processor 301 and a memory 302. The processor 301 and the memory 302 are interconnected and communicate with each other through a communication bus 303 and / or other forms of connection mechanisms (not shown). The memory 302 stores a computer program executable by the processor 301. When the electronic device is running, the processor 301 executes the computer program to execute the OLED nozzle driving waveform control method in any optional implementation of the above embodiment to achieve the following functions: obtain the structural parameters of the OLED nozzle and the physicochemical parameters of the ink, and construct a waveform control method for driving the OLED nozzle based on the electroacoustic analogy theory in combination with the structural parameters and the physicochemical parameters. A theoretical dynamic model of dynamic voltage and ink droplet ejection volume is established, and historical ink droplet volume data and historical speed data during stable ink jetting are obtained to construct a voltage duration influence function, an ink droplet volume correction coefficient and an ink droplet steady-state speed function. The theoretical dynamic model is optimized according to the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state speed function to obtain an ink droplet ejection theory-data hybrid model. The obtained real-time driving waveform of the OLED nozzle is input into the discretized equation corresponding to the ink droplet ejection theory-data hybrid model to calculate the predicted ink droplet ejection volume, and the model prediction algorithm cost function and driving waveform constraint conditions corresponding to the predicted ink droplet ejection volume are established to control the real-time driving waveform in real time.

[0082] The embodiment of the present application provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the OLED nozzle driving waveform control method in any optional implementation of the above embodiment is executed to achieve the following functions: obtaining structural parameters of the OLED nozzle and physicochemical parameters of the ink, constructing a theoretical dynamic model about the driving voltage and the ink droplet ejection volume based on the electroacoustic analogy theory and in combination with the structural parameters and the physicochemical parameters, obtaining historical ink droplet volume data and historical speed data during stable ink ejection to construct a voltage duration influence function, an ink droplet volume correction coefficient and an ink droplet steady-state speed function, and optimizing the theoretical dynamic model according to the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady-state speed function to obtain an ink droplet ejection theory-data hybrid model, inputting the obtained real-time driving waveform of the OLED nozzle into the discretized equation corresponding to the ink droplet ejection theory-data hybrid model, calculating the predicted ink droplet ejection volume, establishing a model prediction algorithm cost function and driving waveform constraint conditions corresponding to the predicted ink droplet ejection volume, so as to perform real-time control on the real-time driving waveform. Among them, the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0083] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.

[0084] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, and may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0085] Furthermore, the functional modules in the various embodiments of the present application may be integrated together to form an independent part, or each module may exist separately, or two or more modules may be integrated to form an independent part.

[0086] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0087] The above description is only an embodiment of the present application and is not intended to limit the protection scope of the present application. For those skilled in the art, the present application may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for controlling an OLED nozzle driving waveform, for controlling an OLED nozzle driving waveform, characterized in that: Includes steps: Obtain the structural parameters of the OLED nozzle and the physical and chemical parameters of the ink; Based on the electroacoustic analogy theory, the theoretical dynamic model of the driving voltage and the ink droplet ejection volume is constructed in combination with the structural parameters and the physicochemical parameters; Acquiring historical ink drop volume data and historical speed data during stable ink jetting to construct a voltage duration influence function, an ink drop volume correction coefficient, and an ink drop steady-state speed function, and optimizing the theoretical dynamic model according to the voltage duration influence function, the ink drop volume correction coefficient, and the ink drop steady-state speed function to obtain an ink drop jetting theory-data hybrid model; Inputting the acquired real-time driving waveform of the OLED nozzle into the discretization equation corresponding to the ink droplet ejection theory-data hybrid model to calculate the predicted ink droplet ejection volume; A model prediction algorithm cost function and a driving waveform constraint condition corresponding to the predicted ink droplet ejection volume are established to perform real-time regulation on the real-time driving waveform.

2. The OLED nozzle driving waveform control method according to claim 1, characterized in that: The historical ink drop volume data and the historical speed data during stable ink jetting are obtained to construct a voltage duration influence function, an ink drop volume correction coefficient and an ink drop steady-state speed function, and the theoretical dynamic model is optimized according to the voltage duration influence function, the ink drop volume correction coefficient and the ink drop steady-state speed function to obtain an ink drop jetting theory-data hybrid model, including: Acquire voltage duration parameters and historical ink drop volume data of multiple groups of historical driving waveform data during stable ink jetting to construct a voltage duration influence function; Using a frequency domain identification method, substituting the voltage duration influence function into the theoretical dynamic model to determine the ink drop volume correction coefficient; Acquire multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting to construct an ink drop steady-state velocity function; The theoretical dynamic model is optimized according to the voltage duration influence function, the ink drop volume correction coefficient and the ink drop steady-state velocity function to obtain an ink drop ejection theory-data hybrid model.

3. The OLED nozzle driving waveform control method according to claim 2, characterized in that: The voltage duration parameters and historical ink drop volume data of multiple sets of historical driving waveform data during stable ink jetting are obtained to construct a voltage duration influence function, including: Acquire multiple groups of voltage duration parameters of historical driving waveform data that put the OLED nozzle in a stable inkjet state, and acquire corresponding historical ink drop volume data; A voltage duration effect function is obtained by performing quadratic surface fitting on the voltage duration parameters of the multiple groups of the historical drive waveform data and the corresponding historical ink drop volume data.

4. The OLED nozzle driving waveform control method according to claim 2, characterized in that: The frequency domain identification method is used to substitute the voltage duration influence function into the theoretical dynamic model to determine the ink drop volume correction coefficient, including: Adding an ink drop volume correction coefficient term to the theoretical dynamic model, and improving the theoretical dynamic model through the voltage duration influence function to obtain an improved ink drop volume hybrid dynamic model; By using the frequency domain identification method, the voltage duration parameters of each group of the historical driving waveform data in the voltage duration influence function and the corresponding historical ink droplet volume data are input into the improved ink droplet volume hybrid dynamic model in turn, and the specific value of the ink droplet volume correction coefficient item is calculated to determine the ink droplet volume correction coefficient.

5. The OLED nozzle driving waveform control method according to claim 2, characterized in that: Acquiring multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting to construct an ink drop steady-state velocity function, including: Acquire multiple sets of historical ink drop volume data and corresponding historical ink drop velocity data during stable ink jetting; A polynomial fitting is performed on the historical ink drop volume data and the corresponding historical ink drop velocity data to obtain an ink drop steady-state velocity function.

6. The OLED nozzle driving waveform control method according to claim 1, characterized in that: The obtained real-time driving waveform of the OLED nozzle is input into the discretization equation corresponding to the ink droplet ejection theory-data hybrid model to calculate the predicted ink droplet ejection volume, including: Converting the ink drop ejection theory-data hybrid model into a corresponding discretized equation; Acquire the real-time driving waveform of the OLED nozzle; The real-time driving waveform is input into the discretization equation to calculate the predicted ink drop ejection volume.

7. The OLED nozzle driving waveform control method according to claim 1, characterized in that: Establishing a model prediction algorithm cost function and a driving waveform constraint condition corresponding to the predicted ink droplet ejection volume to perform real-time control on the real-time driving waveform, including: Determining the cost function of the model prediction algorithm according to the difference between the predicted ink droplet ejection volume and the preset target ink droplet ejection volume; The driving waveform corresponding to ensuring that the OLED nozzle is in a stable inkjet state is the driving waveform constraint condition; According to the minimum value of the objective function for calculating the optimal parameters of the driving waveform constructed by the cost function of the model prediction algorithm and the driving waveform constraint condition, the real-time driving waveform is regulated in real time so that the real-time driving waveform tends to the optimal driving waveform corresponding to the minimum value of the objective function.

8. An OLED nozzle driving waveform control device, used to control the driving waveform of an OLED nozzle, characterized in that: include: An acquisition module is used to acquire the structural parameters of the OLED nozzle and the physical and chemical parameters of the ink; A construction module, for constructing a theoretical dynamic model of driving voltage and ink droplet ejection volume based on electroacoustic analogy theory and in combination with the structural parameters and the physicochemical parameters; an optimization module, for obtaining historical ink drop volume data and historical ink drop velocity data during stable ink jetting, so as to construct a voltage duration influence function, an ink drop volume correction coefficient and an ink drop steady-state velocity function, and optimizing the theoretical dynamic model according to the voltage duration influence function, the ink drop volume correction coefficient and the ink drop steady-state velocity function, so as to obtain an ink drop jetting theory-data hybrid model; A calculation module, used for inputting the acquired real-time driving waveform of the OLED nozzle into the discretization equation corresponding to the ink droplet ejection theory-data hybrid model, and calculating and obtaining the predicted ink droplet ejection volume; The control module is used to establish a model prediction algorithm cost function and a driving waveform constraint condition corresponding to the predicted ink droplet ejection volume, so as to perform real-time control on the real-time driving waveform.

9. An electronic device, characterized in that: It comprises a processor and a memory, wherein the memory stores a computer program executable by the processor, and when the processor executes the computer program, it runs the steps in the OLED nozzle driving waveform control method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the OLED nozzle driving waveform control method according to any one of claims 1 to 7 are executed.

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