Display Screen Material Identification and Cutting Parameter Regulation System Based on Multi-Source Sensing Fusion

Abstract

The present invention provides a display screen material identification and cutting parameter regulation system based on multi-source sensing fusion, which relates to the technical field of display screen cutting, and includes: a data input module, a data acquisition module, a calculation and processing module, and an execution control module; by pre-inputting the type of the display screen, the corresponding cutting equipment and cutting parameters are called according to the type, and then the cutting parameters are fine-tuned according to the material differences of the display screen to be applicable to the rapid call and rapid cutting of different material display screens. The present invention pre-constructs a database, collects cutting data of different display screen material types to construct an identification model; manually inputs the material type of the display screen and adjusts the initial cutting parameters; then identifies the material to be cut; optimizes on the basis of the initial cutting parameters to provide more accurate cutting parameter data, thereby improving the cutting efficiency and reducing the damage rate.

Description

Technical Field

[0001] The present invention relates to the technical field of display screen cutting, and more specifically, to a display screen material identification and cutting parameter regulation system based on multi-source sensing fusion. Background Art

[0002] A display screen is a display device commonly used as an interactive interface on various electronic devices. In the prior art, for display screens, such as in the production and manufacturing of liquid crystal displays and touch screens, in order to improve production efficiency, reduce manufacturing costs, and achieve large-scale mass production, multiple liquid crystal displays or touch screens are often fabricated on a larger glass substrate. After screen printing into a cell, there are multiple groups of liquid crystal display or touch screen units on the glass. These small units need to be separated before liquid crystal filling. The cutting process is to split the whole cell of glass into individual liquid crystal displays or touch screens. Currently, the more common cutting processes include dicing wheel cutting, laser cutting, and water jet cutting.

[0003] Generally, display screens are divided into two major categories: LCD and OLED. Traditional LCD uses glass as the substrate and needs to be paired with a backlight module, such as an LED backlight, a light guide plate, etc. to achieve the display function. At the same time, its structure also includes functional layers such as a liquid crystal layer, a color filter, and a polarizer. OLED is divided into rigid OLED and flexible OLED. Rigid OLED is similar to LCD and both use glass material as the substrate; a transparent resin protective film needs to be covered on the surface, and its structure includes an organic light-emitting layer, an anode / cathode layer, and a packaging layer, etc. Flexible OLED usually uses polyimide (PI) film or flexible polymer as the substrate, and the packaging material is a flexible barrier film (such as an antistatic adhesive coating), supporting bending and folding functions.

[0004] Constrained by the different structures of liquid crystal display screens, different cutting processes need to be used for different types of liquid crystal display screens. For example, for LCD and rigid OLED: due to the brittle characteristics of the glass substrate, diamond dicing wheels are usually used for cutting, and precise cutting is achieved through mechanical stress. For flexible OLED: since the plastic substrate cannot withstand the stress of mechanical cutting, laser cutting technology (such as CO2 laser) needs to be used to precisely peel off the support film or cut the substrate through thermal effects to avoid material deformation.

[0005] However, even for the same type of display screen, such as LCD or OLED, different structures of display screens are required due to their different application fields; different substrate thicknesses and the combination and composition of various functional films and the thickness components of ITO glue will affect the overall strength, resulting in the need to specifically adjust the cutting parameters (such as the pressure, angle, cutting speed, etc. of the cutting tool) to avoid the breakage of the glass substrate or the melting of the PI substrate. In the prior art, for newly developed display screens, it is usually necessary to test cut multiple times and adjust the cutting parameters multiple times to find the most suitable control parameters to reduce the scrap rate.

[0006] Therefore, a display screen material recognition and cutting parameter control system based on multi-source sensor fusion is needed to adaptively adjust the cutting parameters, improve the cutting effect, and reduce the scrap rate. Summary of the invention

[0007] In order to solve the above technical problems, the present invention provides a display screen material recognition and cutting parameter control system based on multi-source sensor fusion.

[0008] According to one aspect of the present invention, a display screen material recognition and cutting parameter control system based on multi-source sensor fusion is provided, comprising:

[0009] Data input module, data acquisition module, calculation processing module and execution control module;

[0010] The data input module includes an interactive touch screen, through which the type of display screen to be cut is input to the execution control module;

[0011] Data acquisition module, used for data acquisition of materials to be cut;

[0012] The calculation processing module classifies the information collected by the data acquisition module, generates characteristic parameters for identifying the material type, and adjusts the cutting parameters according to the characteristic parameters;

[0013] The execution control module calls the corresponding cutting equipment according to the cutting parameters and controls its operation, and saves the cutting data at the same time;

[0014] By inputting the type of display screen in advance, calling the corresponding cutting equipment and cutting parameters according to the type, and then fine-tuning the cutting parameters according to the material difference of the display screen, it is possible to quickly call parameters and quickly cut display screens of different materials.

[0015] Preferably, the data acquisition module includes a hyperspectral imaging sensor, a laser confocal sensor, an acoustic wave surface sensor and a temperature sensor;

[0016] The hyperspectral imaging sensor is used to detect the reflection spectrum of the display screen to be processed;

[0017] The laser confocal sensor is used to detect the three-dimensional topography and thickness of the display screen to be processed;

[0018] The surface acoustic wave sensor is used to detect the hardness and density of the display screen to be processed;

[0019] The temperature sensor is used to detect the surface temperature data of the display screen to be processed;

[0020] The data acquisition module further includes a communication port, and the data collected in real time is sent to the calculation and processing module through the communication port.

[0021] Preferably, the calculation and processing module preprocesses the collected raw data and performs feature extraction;

[0022] The steps of preprocessing include: data cleaning and normalization; data cleaning is used to remove noise; normalization is used to unify the dimension of various types of data;

[0023] For the reflection spectrum obtained by the hyperspectral imaging sensor, feature extraction is performed, and the position of the characteristic peak, slope and polarization light transmittance of the reflection spectrum are analyzed to determine the material characteristics of the display screen to be measured:

[0024] For the three-dimensional topography and thickness data obtained by the laser confocal sensor, feature extraction is performed to determine the interlayer thickness characteristics of the display screen to be measured;

[0025] For the hardness and density data obtained by the surface acoustic wave sensor, feature extraction is performed to determine the auxiliary material characteristics of the display screen;

[0026] For the temperature data obtained by the temperature sensor, feature extraction is performed to determine the real-time temperature of the display screen;

[0027] The calculation and processing module performs spatio-temporal alignment on the extracted features.

[0028] Preferably, the calculation and processing module is built-in with a trained recognition model based on deep learning; after preprocessing the raw data collected by the data acquisition module, the feature vector is sent as input to the recognition model;

[0029] The appropriate cutting parameter data is output through the feature fusion and decision fusion steps of the recognition model.

[0030] Preferably, the recognition model adopts a convolutional neural network-random forest joint architecture;

[0031] Deep learning is performed through the convolutional neural network model to process hyperspectral images and confocal topography maps;

[0032] The acoustic wave data and temperature data are processed through the random forest model.

[0033] Preferably, the influence function between the characteristic parameters and the cutting parameters is determined through experiments, and a relationship library of characteristic parameters - cutting parameters is established.

[0034] Preferably, decision fusion is performed on the results output by the recognition model; the characteristic parameters output by the model are weighted and summed according to the confidence theory, and the final control parameter data is output.

[0035] The second aspect of the present invention provides a method for identifying the display screen material and dynamically regulating the cutting parameters based on multi-source sensing fusion, which is applied to the above system, and includes the following specific steps:

[0036] S1: Manually input the type and basic parameters of the display screen;

[0037] S2: Collect data on the material to be cut;

[0038] S3: Preprocess and extract features from the collected data;

[0039] S4: Use the recognition model to process the extracted features and output the cutting parameters;

[0040] S5: Call the cutting device to process according to the output cutting parameters;

[0041] S6: Detect and record the quality of the cut product; feedback the cutting quality data to the recognition model to optimize the accuracy of the recognition model.

[0042] Preferably, after manually inputting the display screen type, the recognition model immediately calls the corresponding cutting parameters; and based on the current cutting parameters, the cutting parameters are fine-tuned according to the output results to output the final cutting parameters.

[0043] The third aspect of the present invention provides a computer device, including a memory and a processor, the memory stores a computer program, and when the processor executes the computer program, it implements the steps of the above method for identifying the display screen material and dynamically regulating the cutting parameters based on multi-source sensing fusion.

[0044] Compared with the prior art, the present invention pre-constructs a database, collects cutting data of different display screen material types to build a recognition model; manually inputs the material type of the display screen to adjust the initial cutting parameters; then identifies the material to be cut; and optimizes based on the initial cutting parameters to provide more accurate cutting parameter data, thereby improving the cutting efficiency and reducing the damage rate. Description of the Drawings

[0045] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work. In the drawings:

[0046] Figure 1 4 is a system block diagram of a display screen material recognition and cutting parameter control system based on multi-source sensor fusion according to an embodiment of the present invention.

[0047] Figure 2 The present invention is a flowchart of a method for display screen material identification and cutting parameter control based on multi-source sensor fusion according to an embodiment of the present invention.

[0048] Figure 3 A schematic diagram of the structure of a computer system of an electronic device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] Below, the exemplary embodiments according to the present invention will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments of the present invention, and it should be understood that the present invention is not limited to the exemplary embodiments described here.

[0050] As mentioned in the above background technology, in order to solve the problem that the same type of display screens, such as LCD or OLED, require display screens with different structures due to their different practical application fields; since the thickness of different substrates and the combination and composition of various functional films and the thickness components of ITO glue will affect the overall strength, it is necessary to adjust the cutting parameters (such as the pressure, angle, cutting speed, etc. of the cutting tool) in a targeted manner to avoid the problem of glass substrate fragmentation or PI substrate melting, the following solutions are proposed:

[0051] Example 1

[0052] like Figure 1 The present invention provides a display screen material recognition and cutting parameter control system based on multi-source sensor fusion, including:

[0053] Data input module, data acquisition module, calculation processing module and execution control module;

[0054] In this embodiment, the data input module includes an interactive touch screen. Through the touch screen, the type of display screen to be cut is input to the execution control module; by pre-inputting the type of display screen, the relevant parameter data can be called; for example, if the input display screen type is LCD, the diamond cutter wheel cutting device is preferably called for cutting, and the standard LCD display screen cutting data in the cutting device database is called as the basic cutting parameters.

[0055] In this embodiment, the data acquisition module is used to acquire data of the material to be cut; the specific data acquisition module includes a hyperspectral imaging sensor, a laser confocal sensor, a surface acoustic wave sensor, and a temperature sensor;

[0056] Among them, the hyperspectral imaging sensor is used to detect the reflection spectrum of the display screen to be processed;

[0057] The laser confocal sensor is used to detect the three-dimensional topography and thickness of the display screen to be processed;

[0058] The surface acoustic wave sensor is used to detect the hardness and density of the display screen to be processed;

[0059] The temperature sensor is used to detect the surface temperature data of the display screen to be processed;

[0060] The data acquisition module also includes a communication port, and the data collected in real time is sent to the calculation and processing module through the communication port.

[0061] In this embodiment, the calculation and processing module classifies the information collected by the data acquisition module, generates characteristic parameters for identifying the material type, and adjusts the cutting parameters according to the characteristic parameters;

[0062] The calculation and processing module preprocesses the collected raw data and performs feature extraction;

[0063] The steps of preprocessing include: data cleaning and normalization; data cleaning is used to remove noise; normalization is used to unify the dimension of each type of data; the calculation and processing module performs spatio-temporal alignment on the extracted features to improve the correlation between features.

[0064] Feature extraction is performed on the reflection spectrum obtained by the hyperspectral imaging sensor, and the characteristic peak position, slope, and polarized light transmittance of the reflection spectrum are analyzed to determine the material characteristics of the display screen to be measured. For example, whether the glass substrate is a soda-lime glass substrate or a sodium-free borosilicate glass substrate. For the physical properties of different materials, the appropriate cutting method and cutting parameters can be further selected;

[0065] Feature extraction is performed on the three-dimensional topography and thickness data obtained by the laser confocal sensor to determine the interlayer thickness characteristics of the display screen to be measured; through the measured thickness data, the brittleness of the substrate can be analyzed to adaptively adjust the cutting angle and cutting direction of the cutting tool during cutting;

[0066] Feature extraction is performed on the hardness and density data obtained by the surface acoustic wave sensor to assist in judging the material characteristics of the auxiliary materials of the display screen to be cut, and further optimize the pressure during cutting to avoid brittle cracking of the substrate.

[0067] Feature extraction is performed on the temperature data obtained by the temperature sensor to determine the real-time temperature of the display screen; by controlling the power of the heat dissipation device and the power of the laser cutting device, the temperature on the surface of the display screen during cutting is dynamically adjusted to avoid damage to the display screen caused by high temperature.

[0068] The calculation and processing module incorporates a trained recognition model based on deep learning; after preprocessing the raw data collected by the data acquisition module, the feature vector is sent as input to the recognition model;

[0069] Appropriate cutting parameter data is output through the feature fusion and decision fusion steps of the recognition model. The recognition model adopts a convolutional neural network-random forest joint architecture; through deep learning using the convolutional neural network model, hyperspectral images and confocal topography maps are processed. Based on the deep learning-based recognition model architecture, hyperspectral images and confocal topography maps can be quickly processed to facilitate the rapid determination of the substrate material, three-dimensional topography, and thickness data of the display screen to be processed;

[0070] Subsequently, the acoustic wave data and temperature data are processed by the random forest model to facilitate the rapid determination of the auxiliary material material and surface temperature data of the display screen to be processed.

[0071] The influence function between the feature parameters and the cutting parameters is determined through experiments, and a feature parameter-cutting parameter relationship library is established; for example, the greater the thickness, the stronger the pressure-bearing capacity; the pressure applied during cutting can be increased. Then, decision fusion is performed on the results output by the recognition model; the feature parameters output by the model are weighted and summed according to the confidence theory to determine the final control parameter data output. Additionally, constraint conditions can be set, and by establishing a cutting energy equation with the goal of minimizing the output energy, the optimal control strategy is output to reduce energy consumption; the cutting energy equation is as follows:

[0072]

[0073] In the formula, E is the total effective cutting energy, P(t) is the instantaneous laser power, v(t) is the cutting head movement speed; η is the material's absorption rate function of laser energy; λ is the laser wavelength; T is the material surface temperature.

[0074] In this embodiment, the execution control module calls the corresponding cutting device according to the cutting parameters and controls its operation, while saving the cutting data; a corresponding database is established through the accumulation of data to optimize the accuracy of the recognition model and improve the accuracy of the output cutting parameters.

[0075] In the present invention, by pre-inputting the type of the display screen, the corresponding cutting device and cutting parameters are called according to the type, and then the cutting parameters are finely adjusted according to the material difference of the display screen to be applicable to the rapid parameter call of display screens of different materials, and the cutting operation is carried out quickly, forming cutting marks on the surface of the display screen, facilitating subsequent cracking by a dicing machine, and dividing the whole display screen into specified sizes, facilitating subsequent processing steps.

[0076] Embodiment 2

[0077] This embodiment takes an LCD display screen as an example to introduce the solution in Embodiment 1 in detail;

[0078] Common LCD screens include a glass substrate, a liquid crystal layer, polarizers, and functional film layers; the glass substrate is divided into upper and lower substrates; usually, an indium tin oxide (ITO) conductive layer is plated on the lower substrate to form an electric field and control the arrangement of liquid crystal molecules; and the upper substrate is usually called a cover plate, and its surface is covered with a color filter for displaying colors and a black light-shielding adhesive for preventing light leakage; the cover plate is combined with the common electrode ITO layer; the liquid crystal layer is usually filled between the lower substrate and the cover plate; therefore, during the processing of the display screen, it is necessary to first clean the glass substrate and plate an ITO conductive layer; after waiting for the steps of screen printing and cell formation, cutting is carried out to separate the units of multiple liquid crystal displays or touch screens on the glass before liquid crystal perfusion can be carried out; therefore, for LCD display screens, when carrying out cutting operations, it is necessary to first consider the thickness, composition of the glass substrate, and the thickness and physical properties of the ITO conductive layer.

[0079] Use the system in Embodiment 1 to adjust the cutting parameters of this LCD display screen; first, input the basic information of the LCD display screen through an interactive touch screen, that is, the data input module, and divide the complete glass substrate into smaller display units according to actual processing needs; the cutting parameters call the standard cutting data of this type of LCD display screen in the database as the basic cutting parameters; for example, select a diamond knife wheel cutting machine for cutting, with a rotation speed of 9000 rpm and a feed speed of 0.3 m / s. Then use the data acquisition module to collect data on the material to be cut; the specific data acquisition module includes a hyperspectral imaging sensor, a laser confocal sensor, a surface acoustic wave sensor, and a temperature sensor;

[0080] Among them, the hyperspectral imaging sensor is used to detect the reflection spectrum of the display screen to be processed;

[0081] A laser confocal sensor is used to detect the three-dimensional topography and thickness of the display screen to be processed;

[0082] A surface acoustic wave sensor is used to detect the hardness and density of the display screen to be processed;

[0083] A temperature sensor is used to detect the surface temperature data of the display screen to be processed;

[0084] The calculation and processing module classifies the information collected by the data acquisition module, generates characteristic parameters for identifying the material type, and adjusts the cutting parameters according to the characteristic parameters;

[0085] The calculation and processing module preprocesses the collected raw data and performs feature extraction;

[0086] The steps of preprocessing include: data cleaning and normalization; data cleaning is used to remove noise; normalization is used to unify the dimensions of various types of data; the calculation and processing module performs spatio-temporal alignment on the extracted features to improve the correlation between features.

[0087] Feature extraction is performed on the reflection spectrum obtained by the hyperspectral imaging sensor, and the characteristic peak position, slope, and polarization light transmittance of the reflection spectrum are analyzed to determine the material characteristics of the display screen to be measured; feature extraction is performed on the three-dimensional topography and thickness data obtained by the laser confocal sensor to determine the interlayer thickness characteristics of the display screen to be measured; through the measured thickness data, the brittleness of the substrate can be analyzed to adaptively adjust the cutting angle and cutting direction of the cutting tool during cutting; feature extraction is performed on the hardness and density data obtained by the surface acoustic wave sensor to assist in judging the material characteristics of the auxiliary material of the display screen to be cut, and further optimize the cutting pressure to avoid substrate cracking. Feature extraction is performed on the temperature data obtained by the temperature sensor to determine the real-time temperature of the display screen.

[0088] The calculation and processing module incorporates a trained deep learning-based recognition model; after preprocessing the raw data collected by the data acquisition module, the feature vector is sent as input to the recognition model;

[0089] The appropriate cutting parameter data is output through the feature fusion and decision fusion steps of the recognition model. The recognition model adopts a convolutional neural network-random forest joint architecture; through the convolutional neural network model for deep learning, hyperspectral images and confocal topography maps are processed. Based on the deep learning-based recognition model architecture, hyperspectral images and confocal topography maps can be quickly processed to facilitate the rapid determination of the substrate material, three-dimensional topography, and thickness data of the display screen to be processed;

[0090] After that, the acoustic wave data and temperature data are processed by a random forest model to quickly determine the auxiliary material of the display screen to be processed and the surface temperature data. Then, decision fusion is performed on the results output by the recognition model; the characteristic parameters output by the model are weighted and summed according to the confidence theory to determine the final output control parameter data. For example, the hyperspectral image and the confocal topography map data have high accuracy, while the acoustic wave data and temperature data are greatly affected by the external environment. Therefore, the initial weight a of the convolutional neural network model is set to 0.6, and the weight b of the random forest model is set to 0.4; through actual testing of a large amount of data, the weights a and b are adaptively adjusted according to the accuracy of the measured data and the predicted data, but still need to satisfy a + b = 1.

[0091] In this embodiment, it is assumed that the following results are recognized according to the recognition model: the glass substrate to be measured is a soda-lime glass substrate; the thickness is 0.5 mm, the ITO film layer is 0.1 mm, and the current surface temperature of the glass substrate is 20 degrees Celsius; compared with the manually input data, the thickness of the glass substrate increases by 0.1 mm, and based on the previous basic cutting parameters, the cutting parameters are adjusted.

[0092] Here, due to the increase in the thickness of the glass substrate, according to the established relationship library of characteristic parameters - cutting parameters, the bearing pressure increases with the increase in thickness. Therefore, the rotation speed in the cutting parameters is adjusted to 10,000 rpm.

[0093] After that, the execution control module calls the corresponding cutting device according to the cutting parameters and controls its operation, and at the same time saves the cutting data; a corresponding database is established through the accumulation of data to optimize the accuracy of the recognition model and improve the accuracy of the output cutting parameters. When the characteristic parameters similar to the display screen structure and material are detected again, the cutting parameters of this time are preferentially used as the output to control the cutting device for cutting.

[0094] When the recognition result output by the recognition model of the calculation module has a large deviation from the manually input result; a warning prompt is given through the interactive display touch screen to avoid waste of raw materials caused by misoperation.

[0095] For example: the material of the glass substrate manually input is soda-lime glass, the thickness is 0.4 mm, and the ITO film layer is 0.1 mm; in this embodiment, it is assumed that the following results are recognized according to the recognition model: the glass substrate to be measured is sodium-free borosilicate glass; the thickness is 0.3 mm, the ITO film layer is 0.1 mm, and the current surface temperature of the glass substrate is 10 degrees Celsius; there are obvious large differences compared with the manually input data.

[0096] Due to the high brittleness of soda-lime glass, a cutter head with higher precision and faster rotation speed is required to reduce chipping; while for non-sodium borosilicate glass, due to its higher hardness, wear-resistant cutting tools need to be used to reduce the wear of the cutting equipment; for ultra-thin LCD substrates with a thickness less than 0.35 mm, due to their greater brittleness, diamond cutter wheel cutting equipment is not suitable; therefore, warning prompts are given through an interactive display touch screen; assuming a manual data input error here, after the manual data is corrected, the processing is carried out again; at this time, a laser cutting equipment is preferably used for cutting; and the cutting power is adjusted within the range of 20-200 w according to the type of glass, and the cutting speed is less than 0.6 m / min; the laser cutting equipment is sensitive to temperature, so it is necessary to adjust the laser cutting power in combination with the surface temperature of the initial glass substrate to avoid deformation and failure of the glass substrate caused by thermal effects.

[0097] In the present invention, by pre-inputting the type of the display screen, the corresponding cutting equipment and cutting parameters are called according to the type, and then the cutting parameters are finely adjusted according to the material difference of the display screen to enable rapid parameter calling for different material display screens and rapid cutting operations, forming cutting knife marks on the surface of the display screen, facilitating subsequent breaking by a splitting machine, and dividing the whole display screen into specified sizes for subsequent processing steps.

[0098] Embodiment 3

[0099] As Figure 2 shown, the present invention provides a method for identifying the material of a display screen and dynamically regulating cutting parameters based on multi-source sensing fusion, which is applied to the system in Embodiment 1 and includes the following specific steps:

[0100] S1: Manually input the type and basic parameters of the display screen;

[0101] S2: Collect data on the material to be cut;

[0102] S3: Preprocess and extract features from the collected data;

[0103] S4: Use the recognition model to process the extracted features and output cutting parameters;

[0104] S5: Call the cutting equipment to process according to the output cutting parameters;

[0105] S6: Detect the quality of the cut product and record it; feed the cutting quality data back to the recognition model to optimize the accuracy of the recognition model.

[0106] Preferably, after the type of the display screen is manually input, the recognition model immediately calls the corresponding cutting parameters; and based on the current cutting parameters and according to the output results, the cutting parameters are finely adjusted to output the final cutting parameters.

[0107] Embodiment 4

[0108] Figure 3 The structural schematic diagram of a computer system of an electronic device suitable for implementing the embodiments of the present invention is shown.

[0109] It should be noted that the computer system of the electronic device in this embodiment is only an example and should not impose any limitations on the functions and usage scope of the embodiments of the present invention.

[0110] In this embodiment, the computer system includes a central processing unit 401, which can perform various appropriate actions and processes according to the program stored in the read-only memory 402 or the program loaded from the storage section 408 into the random access memory 403, such as executing the system and method for identifying the display screen material and regulating the cutting parameters based on multi-source sensing fusion described in the above embodiments. In the random access memory 403, various programs and data required for system operation are also stored. The central processing unit 401, the read-only memory 402, and the random access memory 403 are connected to each other via a bus 404. The input / output interface 405 is also connected to the bus 404.

[0111] The following components are connected to the input / output interface 405: an input section 406 including a keyboard, a mouse, etc.; an output section 407 including, for example, a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A driver 410 is also connected to the input / output interface 405 as needed. A removable medium 411, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the driver 410 as needed so that a computer program read from it can be installed into the storage section 408 as needed.

[0112] Particularly, according to the embodiments of the present invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, the embodiments of the present invention include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication section 409 and / or installed from the removable medium 411. When the computer program is executed by the central processing unit 401, various functions defined in the system of the present invention are executed.

[0113] It should be noted that the computer-readable medium shown in the embodiments of the present invention can be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of a computer-readable storage medium can include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium can be any tangible medium that contains or stores a program, and this program can be used by or in combination with an instruction execution system, apparatus, or device. In the present invention, a computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, and this computer-readable medium can send, propagate, or transmit a program for use by or in combination with an instruction execution system, apparatus, or device. The computer program contained on a computer-readable medium can be transmitted using any appropriate medium, including but not limited to: wireless, wired, etc., or any suitable combination of the above.

[0114] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present invention. Among them, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and the above module, program segment, or part of code contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0115] The units involved in the embodiments of the present invention can be implemented in software or in hardware, and the described units can also be provided in a processor. Among them, the names of these units do not, in some cases, constitute a limitation on the unit itself.

[0116] According to one aspect of the present invention, there is provided a computer program product or a computer program, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the methods provided in the above various alternative implementation manners.

[0117] As another aspect, the present invention further provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or may exist alone without being assembled into the electronic device. The above computer-readable medium carries one or more programs, and when the one or more programs are executed by an electronic device, the electronic device implements the system and method for identifying the display screen material and regulating the cutting parameters based on multi-source sensing fusion described in the above embodiments.

[0118] It should be noted that although several modules or units of a device for action execution are mentioned in the above detailed description, such a division is not mandatory. In fact, according to the embodiments of the present invention, the features and functions of two or more of the above-described modules or units can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.

[0119] Through the description of the above embodiments, those skilled in the art can easily understand that the example embodiments described herein can be implemented by software or by a combination of software and necessary hardware. Therefore, the technical solutions according to the embodiments of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (such as a personal computer, a server, a touch terminal, or a network device, etc.) to execute the methods according to the embodiments of the present invention.

[0120] Here, those skilled in the art can understand that the specific operations of each step in the above method for dynamically regulating the display screen material recognition and cutting parameters based on multi-source sensing fusion have been described above with reference to Figure 1has been introduced in detail in the description of the display screen material recognition and cutting parameter regulation system based on multi-source sensor fusion, and therefore, its repeated description will be omitted.

[0121] In summary, the display screen material recognition and cutting parameter regulation system based on multi-source sensor fusion according to the embodiments of the present invention is clarified, which inputs cutting parameters in advance and then recognizes the material to be cut; optimizes on the basis of the initial cutting parameters to improve the cutting efficiency and reduce the damage rate.

Claims

1. A display screen material recognition and cutting parameter regulation system based on multi-source sensing fusion, characterized in that Including: A data input module, a data acquisition module, a calculation and processing module, and an execution control module; The data input module includes an interactive touch screen, and inputs the type of display screen to be cut to the execution control module through the touch screen; The data acquisition module is used for data acquisition of the material to be cut; The data acquisition module includes a hyperspectral imaging sensor, a laser confocal sensor, a surface acoustic wave sensor, and a temperature sensor; Among them, the hyperspectral imaging sensor is used to detect the reflection spectrum of the display screen to be processed; The laser confocal sensor is used to detect the three-dimensional morphology and thickness of the display screen to be processed; The surface acoustic wave sensor is used to detect the hardness and density of the display screen to be processed; The temperature sensor is used to detect the surface temperature data of the display screen to be processed; The data acquisition module also includes a communication port, and sends the real-time acquired data to the calculation and processing module through the communication port; The calculation and processing module classifies and processes the information acquired by the data acquisition module, generates characteristic parameters for identifying the material type, and adjusts the cutting parameters according to the characteristic parameters; The calculation and processing module preprocesses the acquired raw data and performs feature extraction; The steps of preprocessing include: data cleaning and normalization; data cleaning is used to remove noise; normalization is used to unify the dimension of various types of data; Perform feature extraction on the reflection spectrum obtained by the hyperspectral imaging sensor, analyze the characteristic peak position, slope, and polarization light transmittance of the reflection spectrum to determine the material characteristics of the display screen to be measured: select appropriate cutting methods and cutting parameters according to the physical characteristics of different materials; Perform feature extraction on the three-dimensional morphology and thickness data obtained by the laser confocal sensor to determine the interlayer thickness characteristics of the display screen to be measured; analyze the brittleness of the substrate through the measured thickness data to adaptively adjust the cutting angle and cutting direction when the cutting tool cuts; Perform feature extraction on the hardness and density data obtained by the surface acoustic wave sensor to determine the auxiliary material characteristics of the display screen; optimize the pressure during cutting to avoid brittle fracture of the substrate; Perform feature extraction on the temperature data obtained by the temperature sensor to determine the real-time temperature of the display screen; dynamically adjust the temperature of the display screen surface during cutting by controlling the power of the heat dissipation device and the power of the laser cutting device to avoid damage to the display screen caused by high temperature; The calculation and processing module performs spatio-temporal alignment on the extracted features; The execution control module calls the corresponding cutting device according to the cutting parameters and controls its operation, and saves the cutting data at the same time; By pre-inputting the type of the display screen, call the corresponding cutting device and cutting parameters according to the type, and then fine-tune the cutting parameters according to the material difference of the display screen to be suitable for rapid parameter calling and rapid cutting of display screens of different materials.

2. The system for identifying display screen materials and regulating cutting parameters based on multi-source sensing fusion according to claim 1, wherein, The calculation and processing module internally has a trained recognition model based on deep learning; after preprocessing the raw data collected by the data acquisition module, the calculation and processing module sends the feature vector as input to the recognition model; Output the adapted cutting parameter data through the feature fusion and decision fusion steps of the recognition model.

3. The system for identifying the display screen material and regulating the cutting parameters based on multi-source sensing fusion according to claim 2, wherein The recognition model adopts a convolutional neural network-random forest joint architecture; Perform deep learning through a convolutional neural network model to process hyperspectral images and confocal topography maps; Process acoustic wave data and temperature data through a random forest model.

4. The system for identifying the display screen material and regulating the cutting parameters based on multi-source sensing fusion according to claim 2 or 3, wherein Determine the influence function of feature parameters and cutting parameters through experiments, and establish a feature parameter-cutting parameter relationship library.

5. The system for identifying the display screen material and regulating the cutting parameters based on multi-source sensing fusion according to claim 4, wherein Perform decision fusion on the results output by the recognition model; perform weighted summation on the feature parameters output by the model according to the confidence theory, and output the final control parameter data; set constraint conditions, establish a cutting energy equation, and take the lowest output energy as the optimization goal to output the optimal control strategy and reduce energy consumption; the cutting energy equation is as follows: In the formula, E is the total effective cutting energy, P(t) is the instantaneous laser power, v(t) is the cutting head movement speed; η is the material's absorption rate function of laser energy; λ is the laser wavelength; T is the material surface temperature.

6. A method for identifying the material of a display screen and dynamically adjusting cutting parameters based on multi-source sensing fusion, which is applied to the system described in any one of claims 1-5, and is characterized in that, It includes the following specific steps: S1: Manually input the type and basic parameters of the display screen; S2: Collect data on the material to be cut; S3: Preprocess and extract features from the collected data; S4: Use the recognition model to process the extracted features and output cutting parameters; S5: Call the cutting equipment to process according to the output cutting parameters; S6: Detect and record the quality of the cut product; feedback the cutting quality data to the recognition model to optimize the accuracy of the recognition model.

7. The method for dynamically regulating the identification of display screen materials and cutting parameters based on multi-source sensing fusion according to claim 6, wherein After manually inputting the display screen type, the recognition model immediately calls the corresponding cutting parameters; and fine-tunes the cutting parameters based on the output results on the basis of the current cutting parameters to output the final cutting parameters.

8. A computer device, comprising a memory and a processor, the memory storing a computer program, characterized in that: When the processor executes the computer program, it implements the steps of the method for identifying the display screen material and dynamically regulating the cutting parameters based on multi-source sensing fusion according to any one of claims 6-7.

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