CN117074181B - Pressure testing method, device and equipment for curved flexible screen and storage medium - Google Patents

Pressure testing method, device and equipment for curved flexible screen and storage medium Download PDF

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CN117074181B
CN117074181B CN202311339223.6A CN202311339223A CN117074181B CN 117074181 B CN117074181 B CN 117074181B CN 202311339223 A CN202311339223 A CN 202311339223A CN 117074181 B CN117074181 B CN 117074181B
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flexible screen
pressure
curved flexible
data
curved
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CN117074181A (en
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陈文泰
宋高升
李家伟
陈浩壮
许诗彤
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Shenzhen Kanglingyuan Technology Co ltd
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Abstract

The invention relates to the technical field of data processing, and discloses a pressure testing method, device and equipment for a curved flexible screen and a storage medium. The pressure testing method of the curved flexible screen comprises the following steps: acquiring first characteristic data and second characteristic data of a curved flexible screen through a preset three-dimensional laser scanner; monitoring the response of the curved flexible screen in the first state and the second state through a preset multi-mode sensor network to obtain response data; taking the first characteristic data and the second characteristic data of the curved flexible screen and the response data as the first data of the curved flexible screen; according to the invention, through the sensing technology, the simulation technology and the deep learning model, an accurate method is provided for performance test and prediction of the curved flexible screen, research and development and production efficiency of the curved flexible screen are improved, and meanwhile, higher-quality product experience is provided for consumers.

Description

Pressure testing method, device and equipment for curved flexible screen and storage medium
Technical Field
The present invention relates to the field of data processing technologies, and in particular, to a pressure testing method, apparatus, device, and storage medium for a curved flexible screen.
Background
Curved flexible screen technology has evolved significantly in recent years and is widely used in smartphones, wearable devices and other consumer electronics. Such screens are known for their flexibility and ability to accommodate a variety of modalities. However, evaluating and predicting the performance of curved flexible screens under different environmental and usage conditions remains a technical challenge. Complex testing and analysis is required to achieve accurate, reliable performance predictions to ensure that the screen maintains good display quality and functional integrity at different temperatures, pressures and bending conditions.
The existing performance test and prediction of the curved flexible screen mainly depend on the traditional laboratory test method and a simple analysis model. These methods typically involve performing a series of physical tests under fixed environmental conditions, lacking in-depth knowledge of the performance of the screen in dynamic and varying environments. In addition, the existing test method often cannot fully consider the performance of the screen in different bending states, and cannot effectively simulate and analyze the influence of temperature and pressure on the performance of the screen. This results in inaccurate and unreliable performance predictions, limiting the application and development of curved flexible screens.
Therefore, a new method for testing and predicting the performance of the curved flexible screen is urgently needed, and the performance of the screen under different environments and using conditions can be comprehensively and accurately estimated.
Disclosure of Invention
The invention provides a pressure testing method, device and equipment for a curved flexible screen and a storage medium, which are used for solving the technical problem of how to comprehensively and accurately evaluate the performance of the screen under different environments and use conditions.
The first aspect of the invention provides a pressure testing method of a curved flexible screen, which comprises the following steps:
acquiring first characteristic data and second characteristic data of a curved flexible screen through a preset three-dimensional laser scanner; monitoring the response of the curved flexible screen in the first state and the second state through a preset multi-mode sensor network to obtain response data; taking the first characteristic data and the second characteristic data of the curved flexible screen and the response data as the first data of the curved flexible screen; wherein the first state and the second state are states of the curved flexible screen under different bending degrees;
based on the acquired first data, adjusting the temperature and pressure of the simulation environment through a preset temperature simulator and a preset pressure simulator; in the adjusted simulation environment, monitoring and recording second data of the curved flexible screen through the multi-mode sensor network, and performing comparative analysis with the first data to obtain difference data of the curved flexible screen;
Acquiring test parameter information from a preset database, correcting the difference data based on the test parameter information, and generating target test data;
inputting the target test data into a trained performance prediction model to perform performance prediction to obtain performance prediction information of the curved flexible screen; the performance prediction model is obtained based on training of a deep learning model.
Optionally, in a first implementation manner of the first aspect of the present invention, the acquiring, by a preset three-dimensional laser scanner, the first feature data and the second feature data of the curved flexible screen includes:
placing the curved surface flexible screen in the scanning range of the three-dimensional laser scanner, selecting one point on the surface of the curved surface flexible screen as an initial measuring point, and measuring the distance between the rotatable measuring head and the initial measuring point through the rotatable measuring head of the three-dimensional laser scanner;
acquiring a first measured value corresponding to an axial angle measuring device of a three-dimensional laser scanner and a second measured value of a radial angle measuring device, and calculating three-dimensional space coordinates of an initial measuring point based on the first measured value and the second measured value to obtain first characteristic data of a curved flexible screen;
According to a preset angle increment, rotating a rotatable measuring head of the three-dimensional laser scanner, and measuring the distance between the next measuring point and the rotatable measuring head along the axial direction or the radial direction or along the axial direction and the radial direction simultaneously;
acquiring a third measured value and a fourth measured value of a radial angle measuring device, which correspond to an axial angle measuring device of the three-dimensional laser scanner, and calculating three-dimensional space coordinates of other measuring points in an area near an initial measuring point based on the third measured value and the fourth measured value; and performing smoothing processing based on the three-dimensional space coordinates of other measuring points to obtain second characteristic data of the curved flexible screen.
Optionally, in a second implementation manner of the first aspect of the present invention, the correcting the difference data based on the test parameter information to generate target test data includes:
constructing a first pressure test strip matched with the test parameter information; wherein the first pressure test strip is generated based on the test parameter information;
inquiring a second pressure test strip matched with the curved flexible screen in a preset database according to the first pressure test strip;
performing first correction on the second pressure test strip based on a preset curve flexible screen matching pressure difference value to obtain a third pressure test strip; the preset pressure difference value matched with the curved flexible screen is the difference value between the actual pressure value and the standard pressure value of the curved flexible screen;
Performing second correction on the third pressure test strip through a preset curved flexible screen pressure coefficient to obtain a fourth pressure test strip; the fourth pressure test strip is corrected based on the pressure coefficient of the curved flexible screen;
and fusing the fourth pressure test strip with the first test pressure strip to obtain target test data of the curved flexible screen.
Optionally, in a third implementation manner of the first aspect of the present invention, the training process of the performance prediction model includes:
acquiring pressure data of a curved flexible screen; inputting the pressure data of the curved flexible screen to a primary deep learning network; the primary deep learning network comprises a pressure identification model, a transformation trend prediction model and a pressure distribution analysis model;
predicting a pressure position identification value according to the pressure identification model through pressure data of the curved flexible screen; the pressure position identification value is used for indicating a specific position for pressing on the curved flexible screen;
according to the transformation trend prediction model, predicting a dynamic value of pressure adjustment through pressure data of the curved flexible screen; wherein the dynamic value is used for predicting a change pattern of the pressing force;
According to the pressure distribution analysis model, analyzing the distribution mode value of the pressure in the pressure data of the curved flexible screen; the distribution mode of the pressure is used for predicting the distribution of the pressure applying positions;
acquiring an actual pressure identification value of pressure data of the curved flexible screen; the actual pressure identification value comprises a real pressure position identification value, a real dynamic pressure value and a real distribution mode value;
calculating the proximity degree of the predicted pressure position value and the real pressure position value as a positioning error; calculating the approaching degree of the predicted dynamic pressure value and the real dynamic pressure value to be used as a dynamic error; calculating the proximity degree of the predicted distribution mode value and the real distribution mode value as a distribution error;
according to a preset error optimization algorithm, the parameters of the primary deep learning network are adjusted in an iterative mode, positioning errors, dynamic errors and distribution errors are minimized, and a performance prediction model is obtained through training.
Optionally, in a fourth implementation manner of the first aspect of the present invention, the first state refers to a case that the curved flexible screen is flat; the second state refers to the situation that the curved flexible screen is in a bent or deformed state.
The second aspect of the present invention provides a pressure testing device for a curved flexible screen, the pressure testing device for a curved flexible screen comprising:
the acquisition module is used for acquiring first characteristic data and second characteristic data of the curved flexible screen through a preset three-dimensional laser scanner; monitoring the response of the curved flexible screen in the first state and the second state through a preset multi-mode sensor network to obtain response data; taking the first characteristic data and the second characteristic data of the curved flexible screen and the response data as the first data of the curved flexible screen; wherein the first state and the second state are states of the curved flexible screen under different bending degrees;
the comparison module is used for adjusting the temperature and the pressure of the simulation environment through a preset temperature simulator and a preset pressure simulator based on the acquired first data; in the adjusted simulation environment, monitoring and recording second data of the curved flexible screen through the multi-mode sensor network, and performing comparative analysis with the first data to obtain difference data of the curved flexible screen;
the correction module is used for acquiring test parameter information from a preset database, correcting the difference data based on the test parameter information and generating target test data;
The prediction module is used for inputting the target test data into the trained performance prediction model to perform performance prediction, so as to obtain performance prediction information of the curved flexible screen; the performance prediction model is obtained based on training of a deep learning model.
A third aspect of the present invention provides a pressure testing apparatus for a curved flexible screen, comprising: a memory and at least one processor, the memory having instructions stored therein; and the at least one processor calls the instructions in the memory to enable the pressure testing equipment of the curved flexible screen to execute the pressure testing method of the curved flexible screen.
A fourth aspect of the present invention provides a computer readable storage medium having instructions stored therein which, when run on a computer, cause the computer to perform the method of pressure testing a curved flexible screen described above.
In the technical scheme provided by the invention, the beneficial effects are as follows: the invention provides a pressure testing method, a device, equipment and a storage medium for a curved flexible screen, wherein first characteristic data and second characteristic data of the curved flexible screen are obtained through a preset three-dimensional laser scanner; monitoring the response of the curved flexible screen in the first state and the second state through a preset multi-mode sensor network to obtain response data; taking the first characteristic data and the second characteristic data of the curved flexible screen and the response data as the first data of the curved flexible screen; based on the acquired first data, adjusting the temperature and pressure of the simulation environment through a preset temperature simulator and a preset pressure simulator; in the adjusted simulation environment, monitoring and recording second data of the curved flexible screen through the multi-mode sensor network, and performing comparative analysis with the first data to obtain difference data of the curved flexible screen; acquiring test parameter information from a preset database, correcting the difference data based on the test parameter information, and generating target test data; and inputting the target test data into the trained performance prediction model to perform performance prediction, so as to obtain the performance prediction information of the curved flexible screen. The invention can comprehensively capture the fine characteristics of the curved flexible screen, such as bending, wrinkling and other physical characteristics by using the preset three-dimensional laser scanner, thereby providing detailed and accurate first characteristic data and second characteristic data for subsequent analysis. And then, the response of the curved flexible screen in different bending states is monitored by utilizing the multi-mode sensor network, and different states possibly encountered by the screen in actual application can be captured in real time, so that more real and dynamic response data are obtained. The real use environment can be simulated through the preset temperature and pressure simulator, such as the use condition under the temperature and pressure conditions possibly of a user, so that the practical application value of the test result is ensured. The second data acquired in the simulation environment can be compared with the original first data, so that the analysis result is ensured to be more detailed and accurate, and the real difference data are obtained. By acquiring the test parameter information from a preset database, the difference data can be corrected, so that the difference data is more close to the real situation, and more accurate target test data is generated. And the performance prediction model obtained based on the deep learning model training can be used for highly accurately predicting the performance of the curved flexible screen, so that the prediction is accurate and reliable, and precious feedback can be provided for users and manufacturers. Finally, the invention provides an accurate method for performance test and prediction of the curved flexible screen through the sensing technology, the simulation technology and the deep learning model, improves the research and development efficiency and the production efficiency of the curved flexible screen, and simultaneously provides higher-quality product experience for consumers.
Drawings
FIG. 1 is a schematic diagram of an embodiment of a method for testing pressure of a curved flexible screen according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an embodiment of a pressure testing apparatus for a curved flexible screen according to an embodiment of the present invention.
Detailed Description
The embodiment of the invention provides a pressure testing method, device and equipment for a curved flexible screen and a storage medium. The terms "first," "second," "third," "fourth" and the like in the description and in the claims and in the above drawings, if any, are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used may be interchanged where appropriate such that the embodiments described herein may be implemented in other sequences than those illustrated or otherwise described herein. Furthermore, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed or inherent to such process, method, article, or apparatus.
For ease of understanding, a specific flow of an embodiment of the present invention is described below, referring to fig. 1, and an embodiment of a method for testing pressure of a curved flexible screen according to an embodiment of the present invention includes:
step 101, acquiring first characteristic data and second characteristic data of a curved flexible screen through a preset three-dimensional laser scanner; monitoring the response of the curved flexible screen in the first state and the second state through a preset multi-mode sensor network to obtain response data; taking the first characteristic data and the second characteristic data of the curved flexible screen and the response data as the first data of the curved flexible screen; wherein the first state and the second state are states of the curved flexible screen under different bending degrees;
it can be understood that the execution body of the invention may be a pressure testing device of a curved flexible screen, and may also be a terminal or a server, which is not limited herein. The embodiment of the invention is described by taking a server as an execution main body as an example.
Specifically, the implementation steps of acquiring the first characteristic data and the second characteristic data of the curved flexible screen through a preset three-dimensional laser scanner are as follows:
and scanning the curved flexible screen by using a preset three-dimensional laser scanner.
During the scanning process, the laser scanner generates a point cloud model containing the shape of the curved flexible screen surface.
And extracting first characteristic data of the curved surface flexible screen from the point cloud model. This may include information about the shape, curvature, normal direction, etc. of the curved surface.
And repeating the steps under different bending degrees to obtain the point cloud model under different conditions.
And extracting corresponding second characteristic data from each point cloud model, wherein the data can comprise deformation, curvature and other information of the curved surface.
The response of the curved flexible screen in the first state and the second state is monitored through a preset multi-mode sensor network, and the implementation steps for obtaining response data are as follows:
monitoring is performed using a preset multi-modal sensor network in a first state (e.g., an initial state) and a second state (e.g., a curved state) of the curved flexible screen.
The multimodal sensor network may include pressure sensors, light sensors, accelerometers, and other different types of sensors.
In each state of the curved flexible screen, the sensor network will record relevant response data, such as pressure, deformation, light sensitivity, etc.
By analyzing and processing the response data, information associated with the physical response of the curved flexible screen in different states can be obtained.
The method for realizing the first characteristic data, the second characteristic data and the response data of the curved flexible screen as the first data of the curved flexible screen comprises the following steps:
and combining the first characteristic data and the second characteristic data to obtain a data set containing the curved surface shape and the characteristic information.
The response data is combined with the combined feature data set to form a complete data set.
The formed data set is used for describing the characteristics and response information of the curved flexible screen in different states.
102, adjusting the temperature and the pressure of a simulation environment through a preset temperature simulator and a preset pressure simulator based on the acquired first data; in the adjusted simulation environment, monitoring and recording second data of the curved flexible screen through the multi-mode sensor network, and performing comparative analysis with the first data to obtain difference data of the curved flexible screen;
specifically, based on the acquired first data, the temperature and pressure of the simulation environment are adjusted through a preset temperature simulator and a preset pressure simulator, and the realization method for monitoring and recording the curved flexible screen by using the multi-mode sensor network is as follows:
the temperature and pressure of the simulated environment can be adjusted by using a preset temperature simulator and pressure simulator.
And after the simulation environment is adjusted, connecting the multi-mode sensor network with the curved flexible screen.
The multi-modal sensor network may include temperature sensors, pressure sensors, humidity sensors, and other different types of sensors for monitoring environmental parameters and the physical response of the curved flexible screen.
In the simulation environment, the curved flexible screen is monitored in real time through the multi-mode sensor network, and second data are recorded.
The second data may include physical response information of the curved flexible screen for temperature changes, pressure changes, deformation, etc.
And comparing and analyzing the acquired first data and second data to obtain difference data of the curved flexible screen under different environmental conditions.
Step 103, acquiring test parameter information from a preset database, and correcting the difference data based on the test parameter information to generate target test data;
specifically, step 103 is a realization step of acquiring test parameter information from a preset database, and correcting the difference data based on the information to generate target test data, wherein the realization step is as follows:
a preset database is created for storing the test parameter information. The database may contain various parameters related to the test, such as temperature, pressure, humidity, etc.
A series of test parameters and corresponding correction values are preset in a database. These correction values are obtained from past test experience or simulation results and are used to correct the difference data.
And acquiring corresponding test parameter information from a preset database according to the current test requirement.
And correcting the difference data according to a preset correction rule by using the acquired test parameter information. The manner of correction may be case-specific, such as by using linear interpolation, polynomial fitting, and the like.
And generating target test data from the corrected difference data. The target test data is corrected data which more accurately reflects the actual response of the curved flexible screen under the given test parameters.
104, inputting the target test data into a trained performance prediction model to perform performance prediction, so as to obtain performance prediction information of the curved flexible screen; the performance prediction model is obtained based on training of a deep learning model.
Specifically, step 104 is to input the target test data into the trained performance prediction model to perform performance prediction, so as to obtain performance prediction information of the curved flexible screen. The performance prediction model is obtained based on deep learning model training. The following implementation steps are as follows:
Aiming at the performance prediction requirement of the curved surface flexible screen, a performance prediction model based on deep learning is established. The model may be a Convolutional Neural Network (CNN), a Recurrent Neural Network (RNN), or other suitable deep learning model.
A large scale training data set is used, including known test parameters and corresponding measured performance data. These data will be used to train the performance prediction model.
In the training stage, the performance of the curved flexible screen under given test parameters can be accurately predicted by inputting training data into a performance prediction model and optimizing the model.
After training, target test data is used as input and is input into a trained performance prediction model.
The performance prediction model processes and analyzes the target test data and predicts the performance information of the curved flexible screen under the given test parameters.
The obtained performance prediction information can comprise indexes related to performance, such as bending degree, curvature characteristic, response speed and the like of the curved flexible screen.
Another embodiment of the pressure testing method for the curved flexible screen in the embodiment of the invention comprises the following steps:
the method for acquiring the first characteristic data and the second characteristic data of the curved flexible screen through the preset three-dimensional laser scanner comprises the following steps:
Placing the curved surface flexible screen in the scanning range of the three-dimensional laser scanner, selecting one point on the surface of the curved surface flexible screen as an initial measuring point, and measuring the distance between the rotatable measuring head and the initial measuring point through the rotatable measuring head of the three-dimensional laser scanner;
acquiring a first measured value corresponding to an axial angle measuring device of a three-dimensional laser scanner and a second measured value of a radial angle measuring device, and calculating three-dimensional space coordinates of an initial measuring point based on the first measured value and the second measured value to obtain first characteristic data of a curved flexible screen;
according to a preset angle increment, rotating a rotatable measuring head of the three-dimensional laser scanner, and measuring the distance between the next measuring point and the rotatable measuring head along the axial direction or the radial direction or along the axial direction and the radial direction simultaneously;
acquiring a third measured value and a fourth measured value of a radial angle measuring device, which correspond to an axial angle measuring device of the three-dimensional laser scanner, and calculating three-dimensional space coordinates of other measuring points in an area near an initial measuring point based on the third measured value and the fourth measured value; and performing smoothing processing based on the three-dimensional space coordinates of other measuring points to obtain second characteristic data of the curved flexible screen.
Specifically, the method can be implemented according to the following steps:
and placing the curved flexible screen in the scanning range of the three-dimensional laser scanner. The scan range may be defined to cover the entire curved flexible screen or a specific area to meet specific application requirements.
And selecting one point of the surface of the curved flexible screen as an initial measurement point. The distance between the rotatable measuring head and the initial measuring point is measured using the rotatable measuring head of the three-dimensional laser scanner. This can be achieved by rotating the measuring head and recording the distance between the measuring head and the initial measuring point.
A first measured value corresponding to an axial angle measuring device of the three-dimensional laser scanner and a second measured value of a radial angle measuring device are obtained. Based on the measured values and the distance between the rotatable measuring head and the initial measuring point, three-dimensional space coordinates of the initial measuring point can be calculated, and first characteristic data of the curved flexible screen can be obtained.
The rotatable measuring head of the three-dimensional laser scanner is rotated according to a preset angular increment, and the distance between the next measuring point and the rotatable measuring head is measured in the axial direction, the radial direction or in both the axial direction and the radial direction.
And acquiring a third measured value corresponding to the axial angle measuring device of the three-dimensional laser scanner and a fourth measured value of the radial angle measuring device. Based on these measurements, three-dimensional spatial coordinates of other measurement points in the vicinity of the initial measurement point can be calculated.
And carrying out smoothing processing by combining the three-dimensional space coordinates of other measuring points to obtain second characteristic data of the curved flexible screen. The smoothing process may employ interpolation, filtering, or other suitable methods to ensure the accuracy and continuity of the feature data.
In the embodiment of the invention, the beneficial effects are as follows:
high-precision measurement: high accuracy data can be obtained using a three-dimensional laser scanner for measurements. By measuring a large number of points and performing smoothing, detailed geometric information of the surface of the curved flexible screen, including characteristics such as shape and curvature, can be obtained. Such high precision measurements are very beneficial for design, manufacturing, quality control, etc.
High efficiency measurement: three-dimensional laser scanners are capable of acquiring a large amount of measurement data in a relatively short time. By rotating the rotatable measuring head and measuring a plurality of points, the characteristic data of each region of the curved flexible screen can be obtained quickly. Such high efficiency measurements help to improve production efficiency and reduce costs.
Comprehensive measurement: the three-dimensional laser scanner can cover the whole surface or a specific area of the curved flexible screen, so that comprehensive measurement is realized. This global measurement helps capture various characteristics of the curved flexible screen, including local irregularities, morphological irregularities, and the like. Thus, more comprehensive and accurate data support can be provided in design, manufacturing, and quality control.
Non-contact measurement: the measurement process of the three-dimensional laser scanner is non-contact, and does not need to be in physical contact with the curved flexible screen surface. Such non-contact measurement avoids possible surface damage or shape deformation, and ensures accuracy of measurement results.
Another embodiment of the pressure testing method for the curved flexible screen in the embodiment of the invention comprises the following steps:
the step of correcting the difference data based on the test parameter information to generate target test data includes:
constructing a first pressure test strip matched with the test parameter information; wherein the first pressure test strip is generated based on the test parameter information;
inquiring a second pressure test strip matched with the curved flexible screen in a preset database according to the first pressure test strip;
performing first correction on the second pressure test strip based on a preset curve flexible screen matching pressure difference value to obtain a third pressure test strip; the preset pressure difference value matched with the curved flexible screen is the difference value between the actual pressure value and the standard pressure value of the curved flexible screen;
performing second correction on the third pressure test strip through a preset curved flexible screen pressure coefficient to obtain a fourth pressure test strip; the fourth pressure test strip is corrected based on the pressure coefficient of the curved flexible screen;
And fusing the fourth pressure test strip with the first test pressure strip to obtain target test data of the curved flexible screen.
Specifically, the method can be implemented according to the following steps:
a first pressure test strip is constructed that matches the test parameter information. The pressure test strip is generated according to the test parameter information and is matched with the curved flexible screen to be tested. This includes requirements in terms of location, shape, size, material, etc. in the test parameter information.
And inquiring a second pressure test strip matched with the curved flexible screen in a preset database. The second pressure test strip matched with the parameters related to the curved flexible screen to be tested, such as size, material, stress distribution and the like, is found from the database. This database may contain test data of previous experiments or simulations and their corresponding pressure bars.
And carrying out first correction on the second pressure test strip based on a preset curve flexible screen matching pressure difference value to obtain a third pressure test strip. The preset matching pressure difference value refers to the difference between the actual pressure value and the standard pressure value of the curved flexible screen. And generating a third pressure test strip by properly adjusting the second pressure test strip to be matched with the pressure difference value of the actual curved flexible screen.
And carrying out second correction on the third pressure test strip through a preset curved flexible screen pressure coefficient to obtain a fourth pressure test strip. The pressure coefficient of a curved flexible screen refers to the proportional relationship of the strain or pressure produced by the curved flexible screen under a given stress. And generating a fourth pressure test strip by properly correcting the third pressure test strip according to the pressure coefficient of the curved surface flexible screen to be tested.
And fusing the fourth pressure test strip with the first pressure test strip to obtain target test data of the curved flexible screen. This fusion process may be based on weights or other suitable methods to preserve some of the characteristics of the first pressure test strip and combine with the correction information of the fourth pressure test strip to generate complete target test data.
In the embodiment of the invention, the beneficial effects are as follows:
accurate test data: and generating target test data through correction and fusion of the difference data. These data may provide an accurate description of the actual characteristics and performance of a curved flexible screen. This therefore helps provide reliable, repeatable test results in design, manufacturing, and quality control.
And (3) accurate matching: and constructing the pressure test strip matched with the curved surface flexible screen to be tested by utilizing preset test parameter information and database query. Through the correction of the pressure difference and the pressure coefficient, the characteristics of flexible screens with different curved surfaces can be better adapted. Such precise matching helps to improve the accuracy and reliability of the test.
And quickly generating target test data: with this method, the target test data can be generated quickly. The target test data of the curved flexible screen can be obtained in a short time by inquiring the database and correcting. This efficiency contributes to an improvement in production efficiency and a reduction in test costs.
And (3) comprehensively testing: by integrating the information of the first and fourth pressure test strips, the generated target test data encompasses more surface characteristics. Thus, the performance of the curved flexible screen can be more fully evaluated and more detailed data support provided.
Another embodiment of the pressure testing method for the curved flexible screen in the embodiment of the invention comprises the following steps:
the training process of the performance prediction model comprises the following steps:
acquiring pressure data of a curved flexible screen; inputting the pressure data of the curved flexible screen to a primary deep learning network; the primary deep learning network comprises a pressure identification model, a transformation trend prediction model and a pressure distribution analysis model;
predicting a pressure position identification value according to the pressure identification model through pressure data of the curved flexible screen; the pressure position identification value is used for indicating a specific position for pressing on the curved flexible screen;
According to the transformation trend prediction model, predicting a dynamic value of pressure adjustment through pressure data of the curved flexible screen; wherein the dynamic value is used for predicting a change pattern of the pressing force;
according to the pressure distribution analysis model, analyzing the distribution mode value of the pressure in the pressure data of the curved flexible screen; the distribution mode of the pressure is used for predicting the distribution of the pressure applying positions;
acquiring an actual pressure identification value of pressure data of the curved flexible screen; the actual pressure identification value comprises a real pressure position identification value, a real dynamic pressure value and a real distribution mode value;
calculating the proximity degree of the predicted pressure position value and the real pressure position value as a positioning error; calculating the approaching degree of the predicted dynamic pressure value and the real dynamic pressure value to be used as a dynamic error; calculating the proximity degree of the predicted distribution mode value and the real distribution mode value as a distribution error;
according to a preset error optimization algorithm, the parameters of the primary deep learning network are adjusted in an iterative mode, positioning errors, dynamic errors and distribution errors are minimized, and a performance prediction model is obtained through training.
Specifically, the training process of the performance prediction model includes the following steps:
And acquiring pressure data of the curved flexible screen. By arranging a sensor or strain gauge or the like on a curved flexible screen, data on the pressure applied to the screen can be acquired. These pressure data are recorded in digital form for use in subsequent training.
And inputting pressure data of the curved flexible screen into a primary deep learning network. The primary deep learning network includes three modules: a pressure identification model, a transformation trend prediction model and a pressure distribution analysis model. The pressure identification model is used for identifying position information in the pressure data and determining a specific position of the pressing force. The pressure change trend prediction model is used for predicting the change trend of the pressure, namely the dynamic characteristic of the pressure. The pressure distribution analysis model is used to analyze the distribution pattern of the applied pressure, i.e. the spatial distribution of the pressure on the screen.
And predicting a pressure position identification value according to the pressure identification model through the pressure data of the curved flexible screen. These pressure location identifiers represent the specific locations where pressure is applied to the curved flexible screen.
And predicting a dynamic value of pressure adjustment through pressure data of the curved flexible screen according to the transformation trend prediction model. These dynamic values are used to predict the pattern of change in the applied pressure.
And analyzing the distribution mode value of the pressing force in the pressure data of the curved flexible screen according to the pressure distribution analysis model. The distribution pattern of these pressing forces is used to predict the distribution of the pressing positions.
And acquiring an actual pressure identification value of the curved flexible screen pressure data. These actual pressure identification values include a true pressure location identification value, a true dynamic pressure value, and a true distribution pattern value.
The proximity of the predicted pressure position value to the actual pressure position value is calculated as a positioning error. And calculating the approaching degree of the predicted dynamic pressure value and the real dynamic pressure value as a dynamic error. And calculating the proximity degree of the predicted distribution mode value and the real distribution mode value as the distribution error.
And (3) carrying out iterative adjustment on parameters of the primary deep learning network according to a preset error optimization algorithm, and minimizing positioning errors, dynamic errors and distribution errors. The network parameters are updated by using back propagation algorithm, gradient descent and other technologies so as to improve the accuracy of model prediction.
In the embodiment of the invention, the beneficial effects are as follows:
accurate performance prediction: by training the primary deep learning network, performance indexes of the curved flexible screen, such as pressure position identification, dynamic pressure adjustment, pressure distribution and the like, can be accurately predicted. These predictions can provide an accurate description of the performance of the curved flexible screen, providing an important reference for design and optimization.
High-precision positioning and adjustment: the pressure position and the dynamic change of the predicted pressure adjustment can be accurately identified through the pressure identification model and the pressure transformation trend prediction model. This helps to achieve accurate position sensing and immediate pressure adjustment in actual use, providing a better user experience.
Comprehensive analysis: the distribution mode of the pressure applied on the curved flexible screen can be analyzed through the pressure distribution analysis model. Such analysis can reveal the mechanical properties and performance profile of the curved flexible screen, thereby providing a more comprehensive performance assessment and optimization direction.
The production efficiency is improved: by training the performance prediction model, the performance characteristics of the curved flexible screen can be quickly obtained in the production link. This helps to find potential problems early, improves manufacturing flow, and improves production efficiency and product quality.
Cost and risk are reduced: by accurately predicting the performance of the curved flexible screen, unnecessary trial and error and repetition in the product design and manufacturing process can be avoided. This will reduce development and manufacturing costs and reduce the risk of market emergence.
Another embodiment of the pressure testing method for the curved flexible screen in the embodiment of the invention comprises the following steps:
The first state refers to the condition that the curved flexible screen is flat; the second state refers to the situation that the curved flexible screen is in a bent or deformed state.
The method for testing the pressure of the curved flexible screen in the embodiment of the present invention is described above, and the device for testing the pressure of the curved flexible screen in the embodiment of the present invention is described below, referring to fig. 2, one embodiment of the device for testing the pressure of the curved flexible screen in the embodiment of the present invention includes:
the pressure testing device of the curved flexible screen comprises:
the acquisition module is used for acquiring first characteristic data and second characteristic data of the curved flexible screen through a preset three-dimensional laser scanner; monitoring the response of the curved flexible screen in the first state and the second state through a preset multi-mode sensor network to obtain response data; taking the first characteristic data and the second characteristic data of the curved flexible screen and the response data as the first data of the curved flexible screen; wherein the first state and the second state are states of the curved flexible screen under different bending degrees;
the comparison module is used for adjusting the temperature and the pressure of the simulation environment through a preset temperature simulator and a preset pressure simulator based on the acquired first data; in the adjusted simulation environment, monitoring and recording second data of the curved flexible screen through the multi-mode sensor network, and performing comparative analysis with the first data to obtain difference data of the curved flexible screen;
The correction module is used for acquiring test parameter information from a preset database, correcting the difference data based on the test parameter information and generating target test data;
the prediction module is used for inputting the target test data into the trained performance prediction model to perform performance prediction, so as to obtain performance prediction information of the curved flexible screen; the performance prediction model is obtained based on training of a deep learning model.
The invention also provides a pressure testing device of the curved flexible screen, which comprises a memory and a processor, wherein the memory stores computer readable instructions, and when the computer readable instructions are executed by the processor, the processor executes the steps of the pressure testing method of the curved flexible screen in the above embodiments.
The present invention also provides a computer readable storage medium, which may be a non-volatile computer readable storage medium, and may also be a volatile computer readable storage medium, where instructions are stored in the computer readable storage medium, where the instructions when executed on a computer cause the computer to perform the steps of the method for testing the pressure of the curved flexible screen.
It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, which are not repeated herein.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied essentially or in part or all of the technical solution or in part in the form of a software product stored in a storage medium, including instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a read-only memory (ROM), a random access memory (random access memory, RAM), a magnetic disk, or an optical disk, or other various media capable of storing program codes.
The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims (5)

1. The pressure testing method of the curved flexible screen is characterized by comprising the following steps of:
acquiring first characteristic data and second characteristic data of a curved flexible screen through a preset three-dimensional laser scanner; monitoring the response of the curved flexible screen in the first state and the second state through a preset multi-mode sensor network to obtain response data; taking the first characteristic data and the second characteristic data of the curved flexible screen and the response data as the first data of the curved flexible screen; wherein the first state and the second state are states of the curved flexible screen under different bending degrees;
based on the acquired first data, adjusting the temperature and pressure of the simulation environment through a preset temperature simulator and a preset pressure simulator; in the adjusted simulation environment, monitoring and recording second data of the curved flexible screen through the multi-mode sensor network, and performing comparative analysis with the first data to obtain difference data of the curved flexible screen;
Acquiring test parameter information from a preset database, correcting the difference data based on the test parameter information, and generating target test data;
inputting the target test data into a trained performance prediction model to perform performance prediction to obtain performance prediction information of the curved flexible screen; wherein the performance prediction model is obtained based on training of a deep learning model;
the method for acquiring the first characteristic data and the second characteristic data of the curved flexible screen through the preset three-dimensional laser scanner comprises the following steps:
placing the curved surface flexible screen in the scanning range of the three-dimensional laser scanner, selecting one point on the surface of the curved surface flexible screen as an initial measuring point, and measuring the distance between the rotatable measuring head and the initial measuring point through the rotatable measuring head of the three-dimensional laser scanner;
acquiring a first measured value corresponding to an axial angle measuring device of a three-dimensional laser scanner and a second measured value of a radial angle measuring device, and calculating three-dimensional space coordinates of an initial measuring point based on the first measured value and the second measured value to obtain first characteristic data of a curved flexible screen;
according to a preset angle increment, rotating a rotatable measuring head of the three-dimensional laser scanner, and measuring the distance between the next measuring point and the rotatable measuring head along the axial direction or the radial direction or along the axial direction and the radial direction simultaneously;
Acquiring a third measured value and a fourth measured value of a radial angle measuring device, which correspond to an axial angle measuring device of the three-dimensional laser scanner, and calculating three-dimensional space coordinates of other measuring points in an area near an initial measuring point based on the third measured value and the fourth measured value; smoothing based on three-dimensional space coordinates of other measuring points to obtain second characteristic data of the curved flexible screen;
the step of correcting the difference data based on the test parameter information to generate target test data includes:
constructing a first pressure test strip matched with the test parameter information; wherein the first pressure test strip is generated based on the test parameter information;
inquiring a second pressure test strip matched with the curved flexible screen in a preset database according to the first pressure test strip;
performing first correction on the second pressure test strip based on a preset curve flexible screen matching pressure difference value to obtain a third pressure test strip; the preset pressure difference value matched with the curved flexible screen is the difference value between the actual pressure value and the standard pressure value of the curved flexible screen;
performing second correction on the third pressure test strip through a preset curved flexible screen pressure coefficient to obtain a fourth pressure test strip; the fourth pressure test strip is corrected based on the pressure coefficient of the curved flexible screen;
Fusing the fourth pressure test strip with the first test pressure strip to obtain target test data of the curved flexible screen;
the first state refers to the condition that the curved flexible screen is flat; the second state refers to the situation that the curved flexible screen is in a bent or deformed state.
2. The method of claim 1, wherein the training process of the performance prediction model comprises:
acquiring pressure data of a curved flexible screen; inputting the pressure data of the curved flexible screen to a primary deep learning network; the primary deep learning network comprises a pressure identification model, a transformation trend prediction model and a pressure distribution analysis model;
predicting a pressure position identification value according to the pressure identification model through pressure data of the curved flexible screen; the pressure position identification value is used for indicating a specific position for pressing on the curved flexible screen;
according to the transformation trend prediction model, predicting a dynamic value of pressure adjustment through pressure data of the curved flexible screen; wherein the dynamic value is used for predicting a change pattern of the pressing force;
according to the pressure distribution analysis model, analyzing the distribution mode value of the pressure in the pressure data of the curved flexible screen; the distribution mode of the pressure is used for predicting the distribution of the pressure applying positions;
Acquiring an actual pressure identification value of pressure data of the curved flexible screen; the actual pressure identification value comprises a real pressure position identification value, a real dynamic pressure value and a real distribution mode value;
calculating the proximity degree of the predicted pressure position value and the real pressure position value as a positioning error; calculating the approaching degree of the predicted dynamic pressure value and the real dynamic pressure value to be used as a dynamic error; calculating the proximity degree of the predicted distribution mode value and the real distribution mode value as a distribution error;
according to a preset error optimization algorithm, the parameters of the primary deep learning network are adjusted in an iterative mode, positioning errors, dynamic errors and distribution errors are minimized, and a performance prediction model is obtained through training.
3. The utility model provides a pressure testing arrangement of curved surface flexible screen which characterized in that, pressure testing arrangement of curved surface flexible screen includes:
the acquisition module is used for acquiring first characteristic data and second characteristic data of the curved flexible screen through a preset three-dimensional laser scanner; monitoring the response of the curved flexible screen in the first state and the second state through a preset multi-mode sensor network to obtain response data; taking the first characteristic data and the second characteristic data of the curved flexible screen and the response data as the first data of the curved flexible screen; wherein the first state and the second state are states of the curved flexible screen under different bending degrees;
The comparison module is used for adjusting the temperature and the pressure of the simulation environment through a preset temperature simulator and a preset pressure simulator based on the acquired first data; in the adjusted simulation environment, monitoring and recording second data of the curved flexible screen through the multi-mode sensor network, and performing comparative analysis with the first data to obtain difference data of the curved flexible screen;
the correction module is used for acquiring test parameter information from a preset database, correcting the difference data based on the test parameter information and generating target test data;
the prediction module is used for inputting the target test data into the trained performance prediction model to perform performance prediction, so as to obtain performance prediction information of the curved flexible screen; wherein the performance prediction model is obtained based on training of a deep learning model;
the acquisition module is specifically configured to:
placing the curved surface flexible screen in the scanning range of the three-dimensional laser scanner, selecting one point on the surface of the curved surface flexible screen as an initial measuring point, and measuring the distance between the rotatable measuring head and the initial measuring point through the rotatable measuring head of the three-dimensional laser scanner;
acquiring a first measured value corresponding to an axial angle measuring device of a three-dimensional laser scanner and a second measured value of a radial angle measuring device, and calculating three-dimensional space coordinates of an initial measuring point based on the first measured value and the second measured value to obtain first characteristic data of a curved flexible screen;
According to a preset angle increment, rotating a rotatable measuring head of the three-dimensional laser scanner, and measuring the distance between the next measuring point and the rotatable measuring head along the axial direction or the radial direction or along the axial direction and the radial direction simultaneously;
acquiring a third measured value and a fourth measured value of a radial angle measuring device, which correspond to an axial angle measuring device of the three-dimensional laser scanner, and calculating three-dimensional space coordinates of other measuring points in an area near an initial measuring point based on the third measured value and the fourth measured value; smoothing based on three-dimensional space coordinates of other measuring points to obtain second characteristic data of the curved flexible screen;
the correction module is specifically used for:
constructing a first pressure test strip matched with the test parameter information; wherein the first pressure test strip is generated based on the test parameter information;
inquiring a second pressure test strip matched with the curved flexible screen in a preset database according to the first pressure test strip;
performing first correction on the second pressure test strip based on a preset curve flexible screen matching pressure difference value to obtain a third pressure test strip; the preset pressure difference value matched with the curved flexible screen is the difference value between the actual pressure value and the standard pressure value of the curved flexible screen;
Performing second correction on the third pressure test strip through a preset curved flexible screen pressure coefficient to obtain a fourth pressure test strip; the fourth pressure test strip is corrected based on the pressure coefficient of the curved flexible screen;
fusing the fourth pressure test strip with the first test pressure strip to obtain target test data of the curved flexible screen;
the first state refers to the condition that the curved flexible screen is flat; the second state refers to the situation that the curved flexible screen is in a bent or deformed state.
4. The utility model provides a pressure test equipment of curved surface flexible screen which characterized in that, pressure test equipment of curved surface flexible screen includes: a memory and at least one processor, the memory having instructions stored therein;
the at least one processor invokes the instructions in the memory to cause the pressure testing apparatus of the curved flexible screen to perform the pressure testing method of the curved flexible screen of any of claims 1-2.
5. A computer readable storage medium having instructions stored thereon, which when executed by a processor, implement a method of pressure testing a curved flexible screen according to any of claims 1-2.
CN202311339223.6A 2023-10-17 2023-10-17 Pressure testing method, device and equipment for curved flexible screen and storage medium Active CN117074181B (en)

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WO2018088610A1 (en) * 2016-11-09 2018-05-17 (주)안세기술 3d laser scanner system capable of real-time dynamic positioning of target object by using laser scanner
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WO2018088610A1 (en) * 2016-11-09 2018-05-17 (주)안세기술 3d laser scanner system capable of real-time dynamic positioning of target object by using laser scanner
CN115561568A (en) * 2022-09-23 2023-01-03 深圳市康凌源科技有限公司 Test equipment for mobile phone display screen detection

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