OLED shower head driving waveform regulation method, device, equipment and storage medium

Abstract

The application belongs to the technical field of OLED inkjet printing, and discloses an OLED nozzle driving waveform regulation method, device, equipment and storage medium, the method comprises the following steps: obtaining the structure parameters of the OLED nozzle and the physicochemical parameters of the ink, based on electroacoustic analogy theory, constructing a theoretical dynamic model about driving voltage and ink droplet ejection volume, 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, obtaining an ink droplet ejection theoretical-data hybrid model, calculating the predicted ink droplet ejection volume according to the real-time driving waveform, establishing the corresponding model prediction algorithm cost function and driving waveform constraint condition to regulate the real-time driving waveform in real time; the driving waveform of the OLED nozzle is regulated through the ink droplet ejection theoretical-data hybrid 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, in particular to an OLED nozzle driving waveform regulation method, device, equipment and storage medium. BACKGROUND

[0002] When performing OLED (Organic Light-Emitting Diode) printing, whether the OLED nozzle can eject micro-droplets of a specific volume and speed directly determines the overall precision of the OLED printing equipment and the final quality of the display device. Whether the ejection state of macro micro-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 driving waveform debugging methods all lack the support of automatic debugging means, have poor debugging result stability, low precision, and low efficiency, and the entire waveform debugging process cannot realize online feedback and dynamic adjustment of parameters, and is in a completely open-loop state, that is, the change information of the droplet state in the printing process and the regulation law of the waveform parameters are not automatically associated, which further leads to difficulty in automatic precise fine-tuning of key printing control parameters, and finally cannot meet the needs of efficient and high-precision OLED printing.

[0004] Therefore, in order to solve the technical problems of poor debugging result stability, low precision and low efficiency of the existing printing driving waveform debugging method, an OLED nozzle driving waveform regulation method, device, equipment and storage medium are urgently needed. SUMMARY

[0005] The purpose of the present application is to provide an OLED nozzle driving waveform regulation method, device, equipment and storage medium, to establish the corresponding model prediction algorithm cost function and driving waveform constraint condition by calculating the predicted droplet ejection volume obtained by the droplet ejection theory-data hybrid model based on the voltage duration influence function, the droplet volume correction coefficient and the droplet steady-state speed function optimization, to regulate the real-time driving waveform, to solve the problems of poor debugging result stability, low precision and low efficiency of the existing printing driving waveform debugging method, to associate the droplet state and the driving waveform, to maintain the stable ink ejection state of the OLED nozzle by regulating the driving waveform, to be applicable to different printing needs, and to improve the printing precision and efficiency.

[0006] In a first aspect, the present application provides an OLED nozzle driving waveform regulation method, comprising:

[0007] Obtaining the structure parameters of the OLED nozzle and the physicochemical parameters of the ink;

[0008] constructing a theoretical dynamic model about driving voltage and ink droplet ejection volume based on electroacoustic analogy theory, in combination with the structural parameters and the physicochemical parameters;

[0009] acquiring historical ink droplet volume data and historical ink droplet velocity data at stable ink ejection to construct a voltage duration influence function, an ink droplet volume correction coefficient and an ink droplet steady-state velocity 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 velocity function to obtain an ink droplet ejection theoretical-data hybrid model;

[0010] inputting the acquired real-time driving waveform of the OLED printhead into a discretization equation corresponding to the ink droplet ejection theoretical-data hybrid model to calculate a predicted ink droplet ejection volume;

[0011] establishing a model prediction algorithm cost function and a driving waveform constraint condition corresponding to the predicted ink droplet ejection volume to real-time regulate the real-time driving waveform.

[0012] The OLED printhead driving waveform regulation method provided in the application can regulate the driving waveform of the OLED printhead, and the predicted ink droplet ejection volume calculated by the ink droplet ejection theoretical-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 is used to establish a corresponding model prediction algorithm cost function and a driving waveform constraint condition to regulate the real-time driving waveform, thereby solving the problems of poor stability of the debugging result, difficulty in achieving optimal precision and low efficiency of the existing printing driving waveform debugging method, and enabling the ink droplet state to be associated with the driving waveform to maintain the stable ink ejection state of the OLED printhead by regulating the driving waveform, and being applicable to different printing requirements to improve the printing precision and efficiency.

[0013] Optionally, the historical ink droplet volume data and the historical ink droplet velocity data at stable ink ejection are acquired to construct a voltage duration influence function, an ink droplet volume correction coefficient and an ink droplet steady-state velocity function, and 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 an ink droplet ejection theoretical-data hybrid model, including:

[0014] acquiring voltage duration parameters of historical driving waveform data and historical ink droplet volume data at stable ink ejection to construct a voltage duration influence function;

[0015] the voltage duration influence function is substituted into the theoretical dynamic model by using a frequency domain identification method to determine the ink droplet volume correction coefficient;

[0016] acquire a plurality of sets of historical drop volume data and corresponding historical drop velocity data in stable inkjetting to build a drop steady velocity function;

[0017] optimize the theoretical dynamic model according to the voltage duration influence function, the drop volume correction coefficient and the drop steady velocity function to obtain a drop ejection theoretical-data hybrid model.

[0018] The OLED jet drive waveform regulation method provided in the application can regulate the drive waveform of the OLED jet. The voltage duration parameter of historical drive waveform data, historical drop volume data and corresponding historical drop velocity data in stable inkjetting, and a theoretical dynamic model are used to build a voltage duration influence function, a drop volume correction coefficient and a drop steady velocity function, so as to optimize a drop ejection theoretical-data hybrid model. The drop ejection theoretical-data hybrid model can predict the drop ejection volume, and the real-time drive waveform can be regulated by the predicted drop ejection volume, which is conducive to improving the regulation efficiency of the drive waveform.

[0019] Optionally, the voltage duration parameter of historical drive waveform data and historical drop volume data in stable inkjetting are acquired to build a voltage duration influence function, which comprises:

[0020] The voltage duration parameter of a plurality of sets of historical drive waveform data in stable inkjetting of the OLED jet is acquired, and corresponding historical drop volume data is acquired.

[0021] The voltage duration parameter of a plurality of sets of historical drive waveform data and the corresponding historical drop volume data are subjected to quadratic surface fitting to obtain a voltage duration influence function.

[0022] Optionally, the frequency domain identification method is adopted to substitute the voltage duration influence function into the theoretical dynamic model to determine the drop volume correction coefficient, which comprises:

[0023] A drop volume correction coefficient term is added to the theoretical dynamic model, and the theoretical dynamic model is improved by the voltage duration influence function to obtain an improved drop volume hybrid dynamic model.

[0024] The frequency domain identification method is adopted to sequentially input the voltage duration parameter of a plurality of sets of historical drive waveform data and corresponding historical drop volume data in the voltage duration influence function into the improved drop volume hybrid dynamic model to calculate the specific value of the drop volume correction coefficient term, so as to determine the drop volume correction coefficient.

[0025] Optionally, a plurality of sets of historical ink drop volume data and corresponding historical ink drop velocity data in stable inkjet are acquired to construct an ink drop steady velocity function, including:

[0026] A plurality of sets of historical ink drop volume data and corresponding historical ink drop velocity data in stable inkjet are acquired;

[0027] The historical ink drop volume data and the corresponding historical ink drop velocity data are polynomial fitted to obtain an ink drop steady velocity function.

[0028] Optionally, the real-time driving waveform of the OLED jet is input into the corresponding discretization equation of the ink drop jetting theory-data hybrid model to calculate a predicted ink drop jetting volume, including:

[0029] The ink drop jetting theory-data hybrid model is converted into a corresponding discretization equation;

[0030] The real-time driving waveform of the OLED jet is acquired;

[0031] The real-time driving waveform is input into the discretization equation to calculate a predicted ink drop jetting volume.

[0032] Optionally, a model prediction algorithm cost function corresponding to the predicted ink drop jetting volume and a driving waveform constraint condition are established to real-time regulate the real-time driving waveform, including:

[0033] The model prediction algorithm cost function is determined according to a difference between the predicted ink drop jetting volume and a preset target ink drop jetting volume;

[0034] The driving waveform constraint condition is a driving waveform corresponding to a stable inkjet state of the OLED jet;

[0035] The real-time driving waveform is real-time regulated according to a minimum value of a target function for calculating optimal parameters of the driving waveform constructed according to the model prediction algorithm cost function and the driving waveform constraint condition, so that the real-time driving waveform tends to an optimal driving waveform corresponding to the minimum value of the target function.

[0036] The OLED jet head driving waveform regulation method provided by the application can regulate the driving waveform of the OLED jet head, determine the model prediction algorithm cost function based on the difference between the predicted ink drop ejection volume and the preset target ink drop ejection volume, and determine the driving waveform constraint condition based on the driving waveform corresponding to the stable ink ejection state of the OLED jet head, construct a target function for calculating the optimal parameters of the driving waveform, and regulate the real-time driving waveform in real time to make the target function tend to a minimum value, so that the OLED jet head is in a stable ink ejection state, which is beneficial to improving the regulation efficiency of the driving waveform.

[0037] In a second aspect, the application provides an OLED jet head driving waveform regulation device, comprising:

[0038] An acquisition module is configured to acquire the structural parameters of the OLED jet head and the physicochemical parameters of the ink.

[0039] A construction module is configured to construct a theoretical dynamic model about the driving voltage and the ink drop ejection volume based on the electroacoustic analogy theory and in combination with the structural parameters and the physicochemical parameters.

[0040] An optimization module is configured to acquire the historical ink drop volume data and the historical ink drop speed data in the stable ink ejection state, construct a voltage duration influence function, an ink drop volume correction coefficient, and an ink drop steady-state speed 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 speed function to obtain an ink drop ejection theoretical-data hybrid model.

[0041] A calculation module is configured to input the real-time driving waveform of the OLED jet head acquired by the acquisition module into a discretization equation corresponding to the ink drop ejection theoretical-data hybrid model to calculate a predicted ink drop ejection volume.

[0042] A regulation module is configured to establish a model prediction algorithm cost function corresponding to the predicted ink drop ejection volume and a driving waveform constraint condition to regulate the real-time driving waveform in real time.

[0043] The OLED jet head driving waveform regulation device can calculate the predicted ink drop ejection volume based on the ink drop ejection theoretical-data hybrid model optimized by the voltage duration influence function, the ink drop volume correction coefficient, and the ink drop steady-state speed function, establish the corresponding model prediction algorithm cost function and the driving waveform constraint condition to regulate the real-time driving waveform, solve the problems of poor stability, difficult optimal precision, and low efficiency of the existing printing driving waveform debugging method, correlate the ink drop state with the driving waveform, maintain the stable ink ejection state of the OLED jet head by regulating the driving waveform, and be applicable to different printing requirements to improve the printing precision and efficiency.

[0044] In a third aspect, the present application provides an electronic device comprising 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.

[0045] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, runs the steps of the OLED nozzle drive waveform control method as described above.

[0046] Beneficial effects: The OLED nozzle drive waveform control method, device, equipment and storage medium provided in the present application 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, and solve the problems of poor debugging result stability, difficulty in achieving optimal accuracy and low efficiency in the existing inkjet drive waveform debugging method. It can associate the ink droplet state with the drive waveform to maintain the stable inkjet state of the OLED nozzle by regulating the drive waveform. It can be applied to different printing requirements and improves printing accuracy and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 This is a flow chart of the OLED nozzle drive waveform control method provided in an embodiment of the present application.

[0048] Figure 2 This is a structural diagram of the OLED nozzle drive waveform control device provided in an embodiment of the present application.

[0049] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0050] 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

[0051] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments of the present application. The components of the embodiments of the present application described and shown in the drawings herein 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 claimed present application, but only represents 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 creative work fall within the scope of the present application.

[0052] It should be noted that: similar reference numbers and letters represent similar items in the following drawings, therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. Meanwhile, in the description of the present application, the terms "first", "second", etc. are only used for differentiation, and cannot be understood as indicating or implying relative importance.

[0053] Please refer to Figure 1 , Figure 1 is an OLED nozzle driving waveform regulation method in some embodiments of the present application, which is used for regulating the driving waveform of an OLED nozzle, comprising the steps of:

[0054] Step S101, obtaining the structural parameters of the OLED nozzle and the physicochemical parameters of the ink;

[0055] Step S102, based on electroacoustic analogy theory, combining the structural parameters and the physicochemical parameters, constructing a theoretical dynamic model about the driving voltage and the ink droplet ejection volume;

[0056] Step S103, obtaining the historical ink droplet volume data and the historical ink droplet speed data at the time of stable ink ejection, to construct a voltage duration influence function, an ink droplet volume correction coefficient and an ink droplet steady speed function, and according to the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function, optimizing the theoretical dynamic model to obtain an ink droplet ejection theoretical-data hybrid model;

[0057] Step S104, inputting the obtained real-time driving waveform of the OLED nozzle into the discretization equation corresponding to the ink droplet ejection theoretical-data hybrid model, to calculate the predicted ink droplet ejection volume;

[0058] Step S105, establishing a model prediction algorithm cost function corresponding to the predicted ink droplet ejection volume and a driving waveform constraint condition, to regulate the real-time driving waveform in real time.

[0059] The OLED nozzle driving waveform regulation method solves the problems of poor stability of the debugging result, difficulty in achieving optimal precision, and low efficiency of the existing printing driving waveform debugging method, can associate the ink drop state with the driving waveform, maintain the stable inkjet state of the OLED nozzle by regulating the driving waveform, can be suitable for different printing requirements, and improves the printing precision and efficiency.

[0060] Specifically, in step S101, the structure parameters of the OLED nozzle and the physicochemical parameters of the ink are obtained, wherein the structure parameters of the OLED nozzle include the data of the structure of each part of the OLED nozzle, the material, the model, and the size, etc., such as the size and angle of the nozzle; the physicochemical parameters of the ink include the data of the surface tension, the viscosity, and the density of the ink, etc.; and the structure parameters of the OLED nozzle and the physicochemical parameters of the ink can be obtained from the product manual.

[0061] Specifically, in step S102, based on the electroacoustic analogy theory, the theoretical dynamic model about the driving voltage and the ink drop ejection volume is constructed by combining the structure parameters and the physicochemical parameters, the theoretical dynamic model describes the dynamic change process from the deformation of the piezoelectric material caused by the applied voltage to the ejection of the ink drop inside the OLED nozzle, and the theoretical dynamic model is specifically:

[0062] ;

[0063] wherein 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 for converting the 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 part of the OLED nozzle and the surface tension of the ink; is the equivalent dynamic coefficient related to the size of each 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 and the density of the ink, The equivalent dynamic coefficients of the size of each part structure of the OLED jet head and the sound velocity are related; wherein, the above-mentioned multiple equivalent dynamic coefficients can be obtained from the product specification of the OLED jet head and the ink, for example, each equivalent dynamic coefficient can directly use the size of the nozzle and the equivalent dynamic coefficient of the corresponding parameter, or use the sum of the size of each part structure of the OLED jet head and the equivalent dynamic coefficient of the corresponding parameter, or use the mean or weighted average of the size of each part structure of the OLED jet head and the equivalent dynamic coefficient of the corresponding parameter.

[0064] Specifically, in step S103, historical drop volume data and historical drop velocity data during stable inkjet are obtained to construct a voltage duration influence function, a drop volume correction coefficient, and a drop steady-state velocity function, and a theoretical dynamic model is optimized according to the voltage duration influence function, the drop volume correction coefficient, and the drop steady-state velocity function to obtain a drop ejection theoretical-data hybrid model, including:

[0065] The voltage duration parameters of the historical driving waveform data and the historical drop volume data during stable inkjet are obtained to construct a voltage duration influence function;

[0066] The voltage duration influence function is substituted into a theoretical dynamic model by using a frequency domain identification method to determine a drop volume correction coefficient;

[0067] The historical drop volume data and the corresponding historical drop velocity data during stable inkjet are obtained to construct a drop steady-state velocity function;

[0068] The theoretical dynamic model is optimized according to the voltage duration influence function, the drop volume correction coefficient, and the drop steady-state velocity function to obtain a drop ejection theoretical-data hybrid model.

[0069] Specifically, in step S103, the voltage duration parameters of the historical driving waveform data and the historical drop volume data during stable inkjet are obtained to construct a voltage duration influence function, including:

[0070] The voltage duration parameters of the historical driving waveform data during stable inkjet of the OLED jet head are obtained, and the corresponding historical drop volume data are obtained;

[0071] The voltage duration parameters of the historical driving waveform data and the historical drop volume data during stable inkjet are subjected to quadratic surface fitting to obtain a voltage duration influence function.

[0072] In step S103, historical driving waveform data is acquired (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). Multiple sets of voltage duration parameters that maintain the OLED printhead in a stable inkjet state are extracted from the historical driving waveform data, and corresponding historical ink droplet volume data is obtained. Specifically, historical inkjet images, historical ink droplet volume data, or historical inkjet flight speeds corresponding to the voltage duration parameters of each historical driving waveform data are acquired. The inkjet conditions of the historical inkjet images are identified using image recognition technology or a preset judgment criterion (not described in detail herein) to determine whether the OLED printhead is in a stable inkjet state. This results in extracting multiple sets of voltage duration parameters that maintain the OLED printhead in a stable inkjet state and obtaining the corresponding historical ink droplet volume data.

[0073] The voltage duration parameters and historical ink drop volume data of multiple sets of stable inkjet historical driving waveform data are fitted with a quadratic surface to obtain the voltage duration influence function. The voltage duration influence function is specifically:

[0074] ;

[0075] 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 number of polynomials is 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). The number of polynomials is Generally, there are 3 or 4 of them, and the polynomial order n generally does not exceed 7.

[0076] 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:

[0077] The ink drop volume correction coefficient term is added to the theoretical dynamic model, and the theoretical dynamic model is improved by using the voltage duration influence function to obtain an improved ink drop volume hybrid dynamic model.

[0078] The voltage duration parameter of each group of historical driving waveform data in the voltage duration influence function and the corresponding historical drop volume data are input into the improved drop volume hybrid dynamic model in sequence by using the frequency domain identification method, and the specific value of the drop volume correction coefficient term is calculated to determine the drop volume correction coefficient.

[0079] In step S103, the 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 provided with the drop volume correction coefficient term to improve it, and an improved drop volume hybrid dynamic model is obtained. The improved drop volume hybrid dynamic model is specifically:

[0080] ;

[0081] Wherein, is the drop volume correction coefficient, represents the duration steady-state parameter group of the corresponding driving waveform when the OLED nozzle is in a stable inkjet state, and is used to correct the voltage duration parameter of the corresponding driving waveform when the OLED nozzle is in a stable inkjet state.

[0082] The voltage duration parameter of each group of historical driving waveform data in the voltage duration influence function and the corresponding historical drop volume data are input into the improved drop volume hybrid dynamic model in sequence by using the frequency domain identification method, and the specific value of the drop volume correction coefficient term is calculated to determine the specific drop volume correction coefficient.

[0083] Specifically, in step S103, a plurality of groups of historical drop volume data and corresponding historical drop velocity data during stable inkjet are obtained to construct a drop steady-state velocity function, including:

[0084] A plurality of groups of historical drop volume data and corresponding historical drop velocity data during stable inkjet are obtained;

[0085] The historical drop volume data and the corresponding historical drop velocity data are polynomial fitted to obtain a drop steady-state velocity function.

[0086] In step S103, the drop steady-state velocity function is used to describe the change rule of the average speed of drop ejection. Considering that the drop ejection volume and the drop ejection speed have a strong correlation, only the average speed needs to be considered during printing to meet the target speed. Therefore, the historical drop volume data and the corresponding historical drop velocity data during stable inkjet are polynomial fitted to obtain a drop steady-state velocity function, and the drop steady-state velocity function is specifically:

[0087] ;

[0088] 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.

[0089] By using 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.

[0090] In step S103, the theoretical dynamic model is optimized based on the voltage duration influence function, the ink droplet volume correction coefficient, and the ink droplet steady-state velocity function to obtain an 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:

[0091] ;

[0092] ;

[0093] 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), Indicates Substitution Calculation results of actual values; is the limit symbol, It means that time t tends to infinity.

[0094] Specifically, in step S104, 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, including:

[0095] Convert the droplet ejection theory-data hybrid model into a discretized equation;

[0096] Get the real-time driving waveform of the OLED nozzle;

[0097] The real-time driving waveform is input into the discretized equation and the predicted droplet ejection volume (predicted droplet ejection volume) is calculated.

[0098] In step S104, the real-time driving waveform of the OLED nozzle is obtained (the real-time driving waveform includes the voltage amplitude and 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:

[0099] ;

[0100] in, is the state of the injection process at time k (the current moment), , is the volume flow rate flowing through the OLED nozzle restrictor and nozzle at time k, is the volume flow rate flowing through the nozzle at time k, is the pressure difference across the throttle of the OLED nozzle at time k, is the pressure difference across 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 the parameters ,parameter ,parameter and parameters Related functions; is the output matrix, ; represents the ink droplet ejection volume ejected by the OLED printhead 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.

[0101] The inkjet process status of the next N cycles can be calculated The iterative calculation is as follows:

[0102] ;

[0103] 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.

[0104] In summary, the predicted ink droplet ejection volume in the future N periods can be obtained as follows by combining the discretized equation and the inkjet process state quantity:

[0105] ;

[0106] wherein, is the predicted ink droplet ejection volume in the future N periods; is the system state matrix in the future N periods, ; is the influence matrix in the future N periods, ; is the control input at the initial time, that is, the input initial value of the real-time driving waveform, . is the optimized predicted control input sequence in the future N periods, that is, the predicted driving waveform sequence, ; the superscript T is the transpose symbol.

[0107] In summary, the real-time driving waveform is input into the discretized equation, and the corresponding predicted ink droplet ejection volume is calculated.

[0108] Specifically, in step S105, a model predictive algorithm cost function corresponding to the predicted ink droplet ejection volume and a driving waveform constraint condition are established to perform real-time regulation and control on the real-time driving waveform, including:

[0109] The model predictive algorithm cost function is determined according to the difference between the predicted ink droplet ejection volume and the preset target ink droplet ejection volume;

[0110] The driving waveform constraint condition is the driving waveform corresponding to the stable inkjet state of the OLED nozzle;

[0111] The real-time driving waveform is regulated and controlled in real time according to the minimum value of the objective function for calculating the optimal parameters of the driving waveform constructed according to the model predictive algorithm cost function and the driving waveform constraint condition, so that the real-time driving waveform tends to the optimal driving waveform corresponding to the minimum value of the objective function, and the optimal driving waveform is obtained.

[0112] In step S105, the model predictive algorithm cost function is determined according to the difference between the predicted ink droplet ejection volume and the preset target ink droplet ejection volume, and the model predictive algorithm cost function is specifically:

[0113] ;

[0114] wherein, J is the model predictive algorithm cost function value; H is a first constant matrix, , R is a diagonal matrix of the system input matrix, and the dimension is , Q is a diagonal matrix of the system state matrix, and the dimension is N; G is a second constant matrix, , , is an error matrix, is a target ink drop ejection volume; P is a third constant matrix, ; wherein Q, R and can be set according to actual needs; Q and R determine the feasibility of the model prediction algorithm cost function and the final ink drop control accuracy.

[0115] The driving waveform corresponding to the stable ink ejection state of the OLED nozzle is taken as a driving waveform constraint condition, wherein the interval of the driving waveform corresponding to the stable ink ejection state of the OLED nozzle is set as .

[0116] According to the model prediction algorithm cost function and the driving waveform constraint condition, a target function for calculating the optimal parameters of the driving waveform is constructed, and the target function is specifically:

[0117] ;

[0118] wherein, is a driving waveform target value; is a constraint condition.

[0119] While the real-time driving waveform is controlled in real time, the target function is iterated through the real-time driving waveform after the control, so that the target function tends to a minimum value while the real-time driving waveform tends to be optimal.

[0120] In the control process, the target function is iterated and calculated, and the control input (driving waveform) of the driving waveform target value is calculated when the target function is at a minimum value. When the driving waveform target value is at a minimum value, the ink drop ejection volume has reached the target ink drop ejection volume, and the ink drop speed closely related to the volume also necessarily meets the requirements, and the control input at this time is the optimal driving waveform.

[0121] According to the above, the OLED jet head driving waveform regulation method, by acquiring the structure parameters of the OLED jet head and the physicochemical parameters of the ink, based on the electroacoustic analogy theory, combining the structure parameters and the physicochemical parameters, a theoretical dynamic model about the driving voltage and the ink droplet ejection volume is constructed, the historical ink droplet volume data and the historical ink droplet speed data at the time of stable ink ejection are acquired to construct the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function, and the theoretical dynamic model is optimized according to the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function, to obtain an ink droplet ejection theoretical-data hybrid model, the real-time driving waveform of the OLED jet head acquired is input into the discretization equation corresponding to the ink droplet ejection theoretical-data hybrid model, the predicted ink droplet ejection volume is calculated, and the model prediction algorithm cost function and the driving waveform constraint condition corresponding to the predicted ink droplet ejection volume are established to regulate the real-time driving waveform in real time. Thus, by the predicted ink droplet ejection volume calculated by the ink droplet ejection theoretical-data hybrid model obtained by optimizing the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function, the corresponding model prediction algorithm cost function and the driving waveform constraint condition are established to regulate the real-time driving waveform, the problems of poor stability of the debugging result, difficult to achieve optimal precision and low efficiency of the existing printing driving waveform debugging method are solved, the ink droplet state and the driving waveform can be associated to maintain the stable ink ejection state of the OLED jet head by regulating the driving waveform, and the method can be suitable for different printing requirements, and the printing precision and efficiency are improved.

[0122] Reference Figure 2 The present application provides an OLED jet head driving waveform regulation device for regulating the driving waveform of an OLED jet head, comprising:

[0123] The acquisition module 1 is configured to acquire the structure parameters of the OLED jet head and the physicochemical parameters of the ink.

[0124] The construction module 2 is configured to construct a theoretical dynamic model about the driving voltage and the ink droplet ejection volume based on the electroacoustic analogy theory and combining the structure parameters and the physicochemical parameters.

[0125] The optimization module 3 is configured to acquire the historical ink droplet volume data and the historical ink droplet speed data at the time of stable ink ejection to construct the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function, and optimize the theoretical dynamic model according to the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function to obtain an ink droplet ejection theoretical-data hybrid model.

[0126] The calculation module 4 is configured to input the real-time driving waveform of the OLED jet head acquired into the discretization equation corresponding to the ink droplet ejection theoretical-data hybrid model to calculate the predicted ink droplet ejection volume.

[0127] The regulation module 5 is configured 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 regulate the real-time driving waveform.

[0128] The OLED nozzle driving waveform regulation device can solve the problems of poor stability of the debugging result, difficulty in achieving optimal precision, and low efficiency of the existing printing driving waveform debugging method, can associate the ink droplet state with the driving waveform, can maintain the stable ink ejection state of the OLED nozzle by regulating the driving waveform, can be suitable for different printing requirements, and improves the printing precision and efficiency.

[0129] Specifically, the acquisition module 1, when executed, acquires the structure parameters of the OLED nozzle and the physicochemical parameters of the ink, wherein the structure parameters of the OLED nozzle include the data of the structure of each part of the OLED nozzle and the material, model, and size thereof, such as the size and angle of the nozzle; and the physicochemical parameters of the ink include the data of the surface tension, viscosity, and density of the ink; and the structure parameters of the OLED nozzle and the physicochemical parameters of the ink can be obtained from the product manual.

[0130] Specifically, the construction module 2, when executed, constructs 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 structure parameters and the physicochemical parameters, the theoretical dynamic model describes the dynamic change process from the deformation of the piezoelectric material caused by the applied voltage to the ejection of the ink droplet inside the OLED nozzle, and the theoretical dynamic model is specifically as follows:

[0131] ;

[0132] wherein s is the Laplace operator; is the ink droplet ejection volume, is the voltage amplitude of the driving waveform of the OLED nozzle; is the coupling coefficient of the piezoelectric material for converting the 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 part of the OLED nozzle and the surface tension of the ink; is the equivalent dynamic coefficient related to the size of each 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 and the density of the ink, The equivalent dynamic coefficients of the size of each part structure of the OLED jet head and the sound velocity are related; wherein, the above-mentioned multiple equivalent dynamic coefficients can be obtained from the product specification of the OLED jet head and the ink, for example, each equivalent dynamic coefficient can directly use the size of the nozzle and the equivalent dynamic coefficient of the corresponding parameter, or use the sum of the size of each part structure of the OLED jet head and the equivalent dynamic coefficient of the corresponding parameter, or use the mean or weighted average of the size of each part structure of the OLED jet head and the equivalent dynamic coefficient of the corresponding parameter.

[0133] Specifically, the optimization module 3 executes the following when obtaining the historical droplet volume data and the historical droplet velocity data in stable inkjet to construct the voltage duration influence function, the droplet volume correction coefficient and the droplet steady-state velocity function, and optimize the theoretical dynamic model according to the voltage duration influence function, the droplet volume correction coefficient and the droplet steady-state velocity function to obtain the droplet ejection theoretical-data hybrid model:

[0134] Obtain the voltage duration parameter of the historical driving waveform data and the historical droplet volume data in stable inkjet to construct the voltage duration influence function;

[0135] Using frequency domain identification method, the voltage duration influence function is substituted into the theoretical dynamic model to determine the droplet volume correction coefficient;

[0136] According to the voltage duration influence function, the droplet volume correction coefficient and the droplet steady-state velocity function, the theoretical dynamic model is optimized to obtain the droplet ejection theoretical-data hybrid model.

[0137] Specifically, the optimization module 3 executes the following when obtaining the voltage duration parameter of the historical driving waveform data and the historical droplet volume data in stable inkjet to construct the voltage duration influence function:

[0138] Obtain the voltage duration parameter of the historical driving waveform data and the historical droplet volume data in stable inkjet to construct the voltage duration influence function;

[0139] The voltage duration parameter of the historical driving waveform data and the historical droplet volume data in stable inkjet are subjected to quadratic surface fitting to obtain the voltage duration influence function.

[0140] During execution, Optimization Module 3 extracts multiple sets of voltage duration parameters that maintain the OLED printhead in a stable inkjet state from the historical drive waveform data and obtains corresponding historical ink droplet volume data. This involves obtaining historical inkjet images, historical ink droplet volume data, or historical inkjet flight speeds corresponding to the voltage duration parameters of each historical drive waveform data. Using image recognition technology or a pre-set judgment criterion (not described in detail here), the inkjet status of the historical inkjet images is identified to determine whether the OLED printhead is in a stable inkjet state. This results in extracting multiple sets of voltage duration parameters of the historical drive waveform data that maintain the OLED printhead in a stable inkjet state and obtaining the corresponding historical ink droplet volume data.

[0141] The voltage duration parameters and historical ink drop volume data of multiple sets of stable inkjet historical driving waveform data are fitted with a quadratic surface to obtain the voltage duration influence function. The voltage duration influence function is specifically:

[0142] ;

[0143] 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 number of polynomials is 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). The number of polynomials is Generally, there are 3 or 4 of them, and the polynomial order n generally does not exceed 7.

[0144] 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, it executes:

[0145] The ink drop volume correction coefficient term is added to the theoretical dynamic model, and the theoretical dynamic model is improved by using the voltage duration influence function to obtain an improved ink drop volume hybrid dynamic model.

[0146] Using the frequency domain identification method, the voltage duration parameters of each set 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.

[0147] The optimization module 3, when executed, adds a droplet volume correction coefficient term in the theoretical dynamic model, substitutes the voltage duration influence function into the theoretical dynamic model provided with the droplet volume correction coefficient term after fitting the voltage duration influence function, and obtains an improved droplet volume hybrid dynamic model, and the improved droplet volume hybrid dynamic model is specifically:

[0148] ;

[0149] wherein, is a droplet volume correction coefficient, represents a duration steady-state parameter group of the corresponding driving waveform when the OLED nozzle is in a stable inkjet state, and is used to correct the voltage duration parameter of the corresponding driving waveform when the OLED nozzle is in a stable inkjet state.

[0150] The frequency domain identification method is adopted, the voltage duration parameter of each group of historical driving waveform data in the voltage duration influence function and the corresponding historical droplet volume data are sequentially input into the improved droplet volume hybrid dynamic model, the specific value of the droplet volume correction coefficient term is calculated, and the specific droplet volume correction coefficient is determined.

[0151] Specifically, when the optimization module 3 obtains a plurality of groups of historical droplet volume data and corresponding historical droplet velocity data in a stable inkjet state to construct a droplet steady-state velocity function, now:

[0152] a plurality of groups of historical droplet volume data and corresponding historical droplet velocity data in a stable inkjet state are obtained;

[0153] The historical droplet volume data and the corresponding historical droplet velocity data are polynomial fitted to obtain a droplet steady-state velocity function.

[0154] The optimization module 3, when executed, is used to describe the change rule of the average speed of the droplet ejection, and considering that the droplet ejection volume and the droplet ejection speed have a strong correlation, only the average speed needs to be considered whether it meets the target speed in the printing process. Therefore, the historical droplet volume data and the corresponding historical droplet velocity data in a stable inkjet state are polynomial fitted to obtain a droplet steady-state velocity function, and the droplet steady-state velocity function is specifically:

[0155] ;

[0156] wherein, is droplet velocity data; is droplet volume data (historical droplet volume data, the number of historical droplet volume data corresponds to the voltage duration parameter of the historical driving waveform data described above), is a fitting polynomial coefficient of the droplet volume data.

[0157] By using 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.

[0158] When the optimization module 3 is executed, it 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. 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:

[0159] ;

[0160] ;

[0161] 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), Indicates Substitution Calculation results of actual values; is the limit symbol, It means that time t tends to infinity.

[0162] Specifically, when the calculation module 4 inputs the acquired real-time driving waveform of the OLED nozzle into the discretized equation corresponding to the ink droplet ejection theory-data hybrid model and calculates the predicted ink droplet ejection volume, it executes:

[0163] Convert the droplet ejection theory-data hybrid model into a discretized equation;

[0164] Get the real-time driving waveform of the OLED nozzle;

[0165] The real-time driving waveform is input into the discretized equation and the predicted droplet ejection volume (predicted droplet ejection volume) is calculated.

[0166] When the calculation module 4 is executed, it converts the ink droplet ejection theory-data hybrid model into an expression form that is convenient for the design of the prediction algorithm, and obtains a discretized equation. The discretized equation is specifically:

[0167] ;

[0168] in, is the state of the injection process at time k (the current moment), , is the volume flow rate flowing through the OLED nozzle restrictor and nozzle at time k, the volume flow rate through the nozzle at time k, the pressure difference across the OLED jet restrictor at time k, the pressure difference across the nozzle at time k; the state of the jetting process at time k+1 (next time); the system state matrix, the system input matrix, determined from the OLED jet structure parameters and ink property parameters, determined from the piezoelectric material parameters, i.e. and are functions related to the parameters , the parameter , the parameter and the parameter ; the output matrix, ; represents the ejected drop volume at time k, i.e. the predicted drop ejection volume; represents the control input at time k, i.e. the real-time driving waveform.

[0169] The future N-period inkjet process state quantities can be iteratively calculated as follows:

[0170] ;

[0171] where, is the inkjet process state quantity, is the inkjet period, is the control time domain, , in the time domain, i.e. from the end of the control time domain to the end of the inkjet period, the input real-time driving waveform is considered to be 0.

[0172] In summary, the predicted drop ejection volume for the future N periods can be obtained as follows, in combination with the discretized equations and the inkjet process state quantities:

[0173] ;

[0174] where, is the predicted drop ejection volume for the future N periods; is the system state matrix for the future N periods, ; is the influence matrix for the future N periods, ; is the control input at the initial time, i.e. the input initial value of the real-time driving waveform, . a predicted control input sequence for optimization in the future N periods, i.e. a predicted drive waveform sequence, ; T is a transpose symbol.

[0175] In summary, the real-time drive waveform is input into the discretized equation, and the corresponding predicted ink droplet ejection volume is calculated.

[0176] Specifically, when regulating the real-time drive waveform by establishing a model prediction algorithm cost function corresponding to the predicted ink droplet ejection volume and drive waveform constraint conditions, the regulating module 5 performs:

[0177] determining the model prediction algorithm cost function according to the difference between the predicted ink droplet ejection volume and the preset target ink droplet ejection volume;

[0178] using the drive waveform corresponding to the stable ink ejection state of the OLED nozzle as the drive waveform constraint condition;

[0179] regulating the real-time drive waveform in real time according to the minimum value of the objective function for calculating the optimal parameters of the drive waveform constructed according to the model prediction algorithm cost function and the drive waveform constraint condition, so that the real-time drive waveform tends to the optimal drive waveform corresponding to the minimum value of the objective function.

[0180] When the regulating 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, and the model prediction algorithm cost function is specifically:

[0181] ;

[0182] wherein J is the model prediction algorithm cost function value; H is a first constant matrix, , R is a diagonal matrix of the system input matrix, with a dimension of , Q is a diagonal matrix of the system state matrix, with a dimension of N; G is a second constant matrix, , , is an error matrix, is the target ink droplet ejection volume; P is a third constant matrix, ; wherein Q, R and can be set according to actual needs; Q and R determine the feasibility of the model prediction algorithm cost function and the final ink droplet control accuracy.

[0183] using the drive waveform corresponding to the stable ink ejection state of the OLED nozzle as the drive waveform constraint condition, wherein the interval of the drive waveform corresponding to the stable ink ejection state of the OLED nozzle is set as .

[0184] The control module 5, when executed, constructs a target function for calculating the optimal parameters of the drive waveform according to the model prediction algorithm cost function and the drive waveform constraint condition, and the target function is specifically:

[0185] ;

[0186] Wherein, is the target value of the drive waveform; is the constraint condition.

[0187] While the real-time drive waveform is being real-time controlled, the target function is iterated through the real-time drive waveform after control, so that the target function tends to the minimum value while the real-time drive waveform tends to the optimal.

[0188] In the control process, the target function is iterated to calculate the control input (drive waveform) of the drive waveform target value at the minimum value. When the drive waveform target value is at the minimum, the corresponding ink droplet ejection volume has reached the target ink droplet ejection volume, and the ink droplet speed closely related to the volume also necessarily meets the requirements, and the control input at this time is the optimal drive waveform.

[0189] As can be seen from the above, the OLED nozzle drive waveform control device, by obtaining the structural parameters of the OLED nozzle and the physicochemical parameters of the ink, based on the electroacoustic analogy theory, combining the structural parameters and the physicochemical parameters, a theoretical dynamic model about the drive voltage and the ink droplet ejection volume is constructed, the historical ink droplet volume data and the historical speed data at the time of stable inkjet are obtained to construct the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function, and according to the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function, the theoretical dynamic model is optimized to obtain the ink droplet ejection theoretical-data hybrid model, the real-time drive waveform of the OLED nozzle is input to the corresponding discretization equation of the ink droplet ejection theoretical-data hybrid model, the predicted ink droplet ejection volume is calculated, the model prediction algorithm cost function and the drive waveform constraint condition corresponding to the predicted ink droplet ejection volume are established to real-time control the real-time drive waveform; thereby, the predicted ink droplet ejection volume calculated by the ink droplet ejection theoretical-data hybrid model obtained by optimization based on the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function, the corresponding model prediction algorithm cost function and the drive waveform constraint condition are established to control the real-time drive waveform, solve the problems of poor stability of the debugging result, difficult to achieve optimal precision and low efficiency of the existing printing drive waveform debugging method, can associate the ink droplet state with the drive waveform to maintain the stable inkjet state of the OLED nozzle by controlling the drive waveform, can be suitable for different printing needs, and improve the printing precision and efficiency.

[0190] Please refer to Figure 3 , Figure 3 A structural schematic diagram of an electronic device provided by an embodiment of the present application, the present application provides an electronic device, comprising: 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 mechanism (not marked), the memory 302 stores a computer program executable by the processor 301, when the electronic device runs, the processor 301 executes the computer program to execute the OLED nozzle drive waveform regulation method in any optional implementation manner of the above-mentioned embodiments, to realize the following functions: obtaining the structure parameters of the OLED nozzle and the physicochemical parameters of the ink, based on the electroacoustic analogy theory, combining the structure parameters and the physicochemical parameters, constructing the theoretical dynamic model about the driving voltage and the ink droplet ejection volume, obtaining the historical ink droplet volume data and the historical speed data at the stable ink ejection, to construct the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function, and according to the voltage duration influence function, the ink droplet volume correction coefficient and the ink droplet steady speed function, optimizing the theoretical dynamic model, obtaining the ink droplet ejection theoretical-data hybrid model, inputting the real-time driving waveform of the OLED nozzle obtained to the discretization equation corresponding to the ink droplet ejection theoretical-data hybrid model, calculating to obtain the predicted ink droplet ejection volume, establishing the model prediction algorithm cost function corresponding to the predicted ink droplet ejection volume and the driving waveform constraint condition, to regulate the real-time driving waveform in real time.

[0191] The embodiment of the present application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to execute the OLED jet head driving waveform regulation method in any optional implementation manner of the above embodiment, so as to realize the following functions: obtaining structure parameters of an OLED jet head and physicochemical parameters of ink, constructing a theoretical dynamic model about driving voltage and ink drop ejection volume based on electroacoustic analogy theory, combining the structure parameters and the physicochemical parameters, obtaining historical ink drop volume data and historical speed data in stable ink ejection, so as to construct a voltage duration influence function, an ink drop volume correction coefficient and an ink drop steady 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 speed function, obtaining an ink drop ejection theoretical-data hybrid model, inputting the obtained real-time driving waveform of the OLED jet head into a discretization equation corresponding to the ink drop ejection theoretical-data hybrid model, calculating to obtain a predicted ink drop ejection volume, and establishing a model prediction algorithm cost function corresponding to the predicted ink drop ejection volume and a driving waveform constraint condition, so as to perform real-time regulation on the real-time driving waveform. The storage medium can be realized by any type of volatile or non-volatile storage device or a combination thereof, such as a static random access memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic disk or an optical disk.

[0192] In the embodiments of the present application, it should be understood that the disclosed device and method can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. In actual implementation, another division mode can be used. For example, a plurality of units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some communication interfaces. The coupling or communication connection can be electrical, mechanical or in other forms.

[0193] In addition, the units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, and may be located in one place, or distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment scheme.

[0194] Furthermore, the functional modules in various embodiments of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0195] In this paper, the relationship terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between the entities or operations.

[0196] The above is only an embodiment of the present application and is not used to limit the protection scope of the present application. For those skilled in the art, the present application can have various changes and variations. Any modification, equivalent replacement, improvement, etc. 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: Including steps: Obtain the structural parameters of the OLED printhead and the physical and chemical parameters of the ink; Based on the electroacoustic analogy theory and in combination with the structural parameters and the physicochemical parameters, a theoretical dynamic model of the driving voltage and the ejection volume of the ink droplets is constructed; Acquiring historical ink droplet volume data and historical velocity data during stable ink jetting to construct a voltage duration influence function, an ink droplet volume correction coefficient, and an ink droplet steady-state velocity function; and optimizing the theoretical dynamic model based on the voltage duration influence function, the ink droplet volume correction coefficient, and the ink droplet steady-state velocity function to obtain an ink droplet ejection theory-data hybrid model; Inputting the acquired real-time driving waveform of the OLED nozzle into the discretized equation corresponding to the ink droplet ejection theory-data hybrid model to calculate 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 to perform real-time control on the real-time driving waveform; 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 that converts deformation mechanical energy into acoustic energy, is the equivalent compressibility coefficient of the piezoelectric material of the OLED printhead; is the equivalent dynamic coefficient related to the size of each structural part of the OLED printhead and the surface tension of the ink; is the equivalent dynamic coefficient related to the size of each structural part of the OLED printhead 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, is the equivalent dynamic coefficient related to the size of each structural part of the OLED nozzle and the speed of sound; The ink drop ejection theory-data hybrid model is specifically: ； ； in, is the steady-state velocity of the ink droplet; t is the time; is the ink droplet steady-state velocity function, Indicates Substitution Calculation results of actual values; is the limit symbol, Indicates that time t tends to infinity; is the ink drop volume correction factor; is the voltage duration effect function value.

2. The OLED nozzle driving waveform control method according to claim 1, characterized in that: Historical ink droplet volume data and historical velocity 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 velocity function. The theoretical dynamic model is optimized based on the voltage duration influence function, the ink droplet volume correction coefficient, and the ink droplet steady-state velocity function to obtain an ink droplet ejection theory-data hybrid model, including: Acquire voltage duration parameters and historical ink drop volume data of multiple sets of historical driving waveform data during stable inkjet 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 inkjet 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; A quadratic surface fitting is performed on the voltage duration parameters of the multiple groups of the historical driving waveform data and the corresponding historical ink drop volume data to obtain a voltage duration influence function.

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; Using the frequency domain identification method, the voltage duration parameters of each group of the historical driving waveform data and the corresponding historical ink droplet volume data in the voltage duration influence function 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 discretized equation corresponding to the ink droplet ejection theory-data hybrid model to calculate the predicted ink droplet ejection volume, including: Converting the ink droplet ejection theory-data hybrid model into corresponding discretized equations; Acquire a 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 a cost function of the model prediction algorithm according to a difference between the predicted ink droplet ejection volume and a preset target ink droplet ejection volume; The driving waveform constraint condition is to ensure that 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 by the cost function of the model prediction algorithm and the driving waveform constraint conditions, 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 drive waveform control device for controlling the drive waveform of an OLED nozzle, characterized in that: include: An acquisition module is used to obtain the structural parameters of the OLED printhead and the physical and chemical parameters of the ink; A construction module is used to construct 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 acquiring 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 based on 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, configured to input the acquired real-time driving waveform of the OLED nozzle into a discretized equation corresponding to the ink droplet ejection theory-data hybrid model to calculate a predicted ink droplet ejection volume; a control module, configured 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 control the real-time driving waveform in real time; 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 that converts deformation mechanical energy into acoustic energy, is the equivalent compressibility coefficient of the piezoelectric material of the OLED printhead; is the equivalent dynamic coefficient related to the size of each structural part of the OLED printhead and the surface tension of the ink; is the equivalent dynamic coefficient related to the size of each structural part of the OLED printhead 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, is the equivalent dynamic coefficient related to the size of each structural part of the OLED nozzle and the speed of sound; The ink drop ejection theory-data hybrid model is specifically: ； ； in, is the steady-state velocity of the ink droplet; t is the time; is the ink droplet steady-state velocity function, Indicates Substitution Calculation results of actual values; is the limit symbol, Indicates that time t tends to infinity; is the ink drop volume correction factor; is the voltage duration effect function value.

9. An electronic device, characterized in that: The method 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, the method runs the steps of 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 a processor, the steps of the OLED nozzle driving waveform control method according to any one of claims 1 to 7 are executed.

Images