A keyboard keycap dynamic control system and method based on a balance bar

Abstract

The application relates to the technical field of keyboard keycap control, and particularly discloses a keyboard keycap dynamic control system and method based on a balance bar, which comprises a keycap data acquisition node division module, a keycap motion state data acquisition module, a keycap motion state data analysis module, a keycap action mechanics data detection module, a keycap action mechanics data analysis module, a keyboard keycap management control analysis module and a keyboard keycap control abnormality diagnosis module; through the keycap motion state and action mechanics data detection module, the stability and mechanical adaptability of the keyboard keycap are evaluated, and then a keyboard keycap management control coefficient is obtained through analysis; the intelligent management control and abnormality diagnosis module can dynamically adjust the keyboard setting according to the evaluation result, potential problems can be found and warned in time, and the system stability and user operation efficiency are ensured; the application not only improves the keyboard performance, but also enhances the user experience, is easy to maintain and upgrade, and has a wide application prospect.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of keyboard keycap control, and in particular to a keyboard keycap dynamic control system and method based on a balance bar. BACKGROUND

[0002] With the rapid development of information technology, keyboards play an indispensable role in daily life and work as an important tool for human-computer interaction. In order to improve the typing experience of users, especially for the needs of different application scenarios, the exploration of keyboard keycap dynamic control systems becomes particularly important. In particular, in professional fields such as game competition, high-speed typing, and precision programming, the response speed, stability, and individual customization capability of keyboards become key indicators of keyboard quality.

[0003] Traditional keyboard keycap dynamic control systems mainly rely on shafts or rubber bowls to connect with the base. For example, mechanical keyboards trigger signals through shaft mechanical structures, and membrane keyboards rely on rubber bowl deformation to contact circuits. Large keycaps have balance bars or satellite shafts for assistance, but the structure is simple and lacks precise dynamic adjustment. These systems are based on electrical switch principles and can only identify "press down" and "release" states, and cannot monitor dynamic parameters such as key pressure, speed, and rebound in real time.

[0004] The disadvantages of traditional keyboard keycap dynamic control systems are as follows: first, the traditional system's analysis of the motion state of the keyboard keycap is usually based on simple trigger signals or displacement measurements, lacking in-depth analysis of motion state data. This results in the system being unable to accurately assess the stability of the keycap and unable to promptly detect potential key looseness or faults. Second, the traditional system has limited means of management control and can only achieve simple key locking, disabling, and other functions. It lacks the ability to comprehensively analyze keycap stability and mechanical adaptability. In addition, the traditional system also has deficiencies in anomaly diagnosis. They can only detect simple key faults or incorrect inputs, and cannot accurately diagnose complex control abnormalities. SUMMARY

[0005] To overcome the above-mentioned defects of the prior art, embodiments of the present application provide a keyboard keycap dynamic control system and method based on a balance bar to solve the problems raised in the background art.

[0006] To achieve the above-mentioned purpose, the present application provides the following technical solution: a keyboard keycap dynamic control system based on a balance bar, comprising a keycap data acquisition node division module, a keycap motion state data acquisition module, a keycap motion state data analysis module, a keycap motion mechanics data detection module, a keycap motion mechanics data analysis module, a keyboard keycap management control analysis module, and a keyboard keycap control anomaly diagnosis module.

[0007] The keycap data acquisition node division module is configured to determine the keyboard keycap as a target monitoring object, and divide the target keyboard keycap data acquisition node into n monitoring sub-regions, i=1, 2, 3, …, n, where i is the number of each monitoring sub-region.

[0008] The keycap motion state data acquisition module is configured to acquire and analyze the motion state of each monitoring sub-region of the target keyboard keycap, and obtain motion state data of each monitoring sub-region of the target keyboard keycap.

[0009] The keycap motion state data analysis module is configured to analyze the motion state of the target keyboard keycap based on the motion state data of each monitoring sub-region of the target keyboard keycap, and obtain a keyboard keycap stability evaluation index.

[0010] The keycap motion state data analysis module is configured to analyze the motion state of the target keyboard keycap based on the motion state data of each monitoring sub-region of the target keyboard keycap, and obtain a keyboard keycap stability evaluation index.

[0011] The keycap motion state data analysis module is configured to analyze the motion state of the target keyboard keycap based on the motion state data of each monitoring sub-region of the target keyboard keycap, and obtain a keyboard keycap stability evaluation index.

[0012] The keyboard keycap management control analysis module is configured to comprehensively analyze the keyboard keycap stability evaluation index and the keyboard keycap mechanical adaptability index, obtain a keyboard keycap management control coefficient, evaluate the keyboard keycap management control coefficient, and manage and control the keyboard keycap according to the evaluation result.

[0013] The keyboard keycap control abnormality diagnosis module is configured to diagnose and analyze the keyboard keycap control abnormality based on the keyboard keycap management control coefficient, obtain a keyboard keycap control abnormality coefficient, and determine whether there is an abnormality according to the keyboard keycap control abnormality coefficient, and issue a warning information for data that is determined to be abnormal.

[0014] Preferably, the keycap data acquisition node division module has the following specific implementation manner:

[0015] The keycap data acquisition node division module is configured to determine the keyboard keycap as a target monitoring object, and divide the target keyboard keycap data acquisition node into n monitoring sub-regions, i=1, 2, 3, …, n, where i is the number of each monitoring sub-region.

[0016] Preferably, the keycap motion state data acquisition module has the following specific implementation manner:

[0017] The first step is to install a miniature camera inside the keyboard to take pictures of the balance bar, get the balance bar image, and then process the image to grayscale. Then, remove the noise in the image by using the Gaussian filter method, identify the edge of the balance bar by using the edge detection algorithm, and get the edge pixel points of the balance bar. Then, connect the edge pixel points to the contour of the balance bar by using the contour extraction algorithm, extract the two end points of the balance bar contour of each monitoring sub-region as feature points, and mark the coordinates of the two end points of the balance bar contour of each monitoring sub-region in the image as and respectively. Substitute the above into the formula to get the inclination angle of the balance bar of the ith monitoring sub-region , wherein represents the correction factor.

[0018] The second step is to obtain the friction between the keycap and the balance bar by using the strain gauge friction sensor, obtain the bridge output voltage of each monitoring sub-region U 1 i , and the bridge power supply voltage of each monitoring sub-region U 2 i , and substitute them into the formula to get the friction between the keycap and the balance bar of the ith monitoring sub-region , wherein K represents the strain gauge sensitivity coefficient, and m represents the sensor calibration coefficient.

[0019] The third step is to install an acceleration sensor at the bottom of the keycap to measure the keycap vibration frequency of each monitoring sub-region Vf i .

[0020] The fourth step is to record the inclination angle of the balance bar, the friction between the keycap and the balance bar, and the keycap vibration frequency as the motion state data of each monitoring sub-region of the target keyboard keycap, and mark them as , , Vf i respectively, wherein i is the number of each monitoring sub-region.

[0021] Preferably, the specific execution mode of the keycap motion state data analysis module is as follows:

[0022] The first step is to extract the keycap vibration frequency of the ith monitoring sub-region Vf i , and extract the standard keycap vibration frequency corresponding to the target keyboard keycap from the management database Vf 0 , and substitute them into the formula to get the keycap vibration frequency deviation of the ith monitoring sub-region Vfd i ,

[0023] Second, the establishment of key movement state data analysis module and the management database between the data extraction relationship, extraction of the target keyboard key corresponding to the maximum allowable balance bar tilt angle 、 target keyboard key corresponding to the key and the standard friction between the balance bar ;

[0024] Third, the calculation of keyboard key stability evaluation index SAI , the calculation model is as follows:

[0025] , wherein, represents the balance bar tilt angle of the i-th monitoring sub-area, Vfd max represents the preset maximum key vibration frequency deviation, e represents the natural constant, represents the friction between the key and the balance bar of the i-th monitoring sub-area, n represents the total number of each monitoring sub-area, i represents the number of each monitoring sub-area.

[0026] Preferably, the specific execution mode of the key action dynamics data detection module is as follows:

[0027] First, install a linear variable differential transformer sensor under the key, connect the core to the bottom of the key, and when the key rebounds, get the key displacement of each monitoring sub-area , use a timer to record the key rebound reset time of each monitoring sub-area t i , that is, the time interval from the start of the key rebound to the complete return to the initial position, respectively, into the formula , the key rebound speed of the i-th monitoring sub-area is obtained ;

[0028] Second, install a pressure sensor at the bottom of the key to measure the key pressure of each monitoring sub-area ;

[0029] Third, the key rebound speed and the key pressure are recorded as the action dynamics data of each monitoring sub-area of the target keyboard key, and they are respectively marked as 、 , i is the number of each monitoring sub-area.

[0030] Preferably, the specific execution mode of the key action dynamics data analysis module is as follows:

[0031] First, extract the key rebound speed of the i-th monitoring sub-area extracting the standard keycap rebound speed corresponding to the target keyboard keycap from the management database , respectively, into the formula , to obtain the keycap rebound speed deviation of the i-th monitoring sub-region Rsd i ;

[0032] Secondly, the key pressing force of the i-th monitoring sub-region is extracted , and the standard key pressing force corresponding to the target keyboard keycap is extracted from the management database , respectively, into the formula , to obtain the key pressing force deviation coefficient of the i-th monitoring sub-region Pdc i ;

[0033] Thirdly, the keyboard keycap mechanical adaptability index is calculated MAI , and the calculation model is as follows:

[0034] , wherein represents the preset maximum keycap rebound speed deviation, n represents the total number of monitoring sub-regions, i represents the number of each monitoring sub-region.

[0035] Preferably, the specific execution mode of the keyboard keycap management control analysis module is as follows:

[0036] The keyboard keycap stability evaluation index SAI and the keyboard keycap mechanical adaptability index MAI are read, and the keyboard keycap management control coefficient is calculated, and the calculation model is as follows: , wherein MCC represents the keyboard keycap management control coefficient;

[0037] The keyboard keycap management control coefficient is evaluated, and the keyboard keycap management control coefficient is compared and analyzed with the preset management control coefficient threshold value. If the keyboard keycap management control coefficient is less than or equal to the preset management control coefficient threshold value, it is judged that the state of the target keyboard keycap is normal, and if the keyboard keycap management control coefficient is greater than the preset management control coefficient threshold value, it is judged that the state of the target keyboard keycap is abnormal. The state of the target keyboard keycap is recorded as the evaluation result of the target keyboard keycap. The standard management control mode corresponding to the target keyboard keycap is obtained according to the keyboard keycap management control coefficient corresponding to the target keyboard keycap, and the target keyboard keycap is managed and controlled according to the standard management control mode corresponding to the target keyboard keycap.

[0038] Preferably, the specific execution mode of the keyboard keycap control abnormality diagnosis module is as follows:

[0039] First step, calculate the keyboard key cap control abnormality coefficient CAC The calculation model is as follows:

[0040] Wherein, MCC Indicates the keyboard key cap management control coefficient, Indicates the average value of the keyboard key cap management control coefficient;

[0041] Second step, extract the keyboard key cap control abnormality coefficient, compare it with the preset control abnormality coefficient threshold value, if the keyboard key cap control abnormality coefficient is greater than the preset control abnormality coefficient threshold value, it is judged that the target keyboard key cap management control is abnormal, the management control abnormality diagnosis process is triggered, and the management personnel is informed to perform abnormal management control on the target keyboard. Warning information is issued for the data of the abnormal judgment result; otherwise, it is judged that the target keyboard key cap management control is normal.

[0042] To achieve the above purpose, the present application provides the following technical scheme: a keyboard key cap dynamic control method based on a balance bar, which implements the above-mentioned keyboard key cap dynamic control system based on a balance bar, comprising the following steps:

[0043] S1: key cap data acquisition node division: the keyboard key cap is determined as the target monitoring object, and the target keyboard key cap data acquisition node is divided into n monitoring sub-regions, i=1, 2, 3,..., n, i is the number of each monitoring sub-region;

[0044] S2: key cap motion state data acquisition: the motion state of each monitoring sub-region of the target keyboard key cap is collected and analyzed to obtain the motion state data of each monitoring sub-region of the target keyboard key cap;

[0045] S3: key cap motion state data analysis: based on the motion state data of each monitoring sub-region of the target keyboard key cap, the motion state of the target keyboard key cap is analyzed to obtain a key cap stability evaluation index;

[0046] S4: key cap motion mechanics data detection: the motion mechanics data of each monitoring sub-region of the target keyboard key cap is detected and analyzed to obtain the motion mechanics data of each monitoring sub-region of the target keyboard key cap;

[0047] S5: key cap motion mechanics data analysis: based on the motion mechanics data of each monitoring sub-region of the target keyboard key cap, the motion mechanics of the target keyboard key cap is analyzed to obtain a key cap mechanics adaptability index;

[0048] S6: keyboard key cap management control analysis: based on the key cap stability evaluation index and the key cap mechanics adaptability index, the keyboard key cap management control coefficient is obtained, and the keyboard key cap management control coefficient is evaluated, and the keyboard key cap is managed and controlled according to the evaluation result;

[0049] S7: Keyboard keycap control abnormality diagnosis: based on the keyboard keycap management control coefficient, the keyboard keycap control abnormality is diagnosed and analyzed, the keyboard keycap control abnormality coefficient is obtained, and whether it is abnormal is judged according to the keyboard keycap control abnormality coefficient, and a warning information is sent for the data of the judgment result being abnormal.

[0050] The technical effects and advantages of the present application are as follows:

[0051] 1. The present application utilizes the keycap motion state data analysis module and the keycap motion mechanics data detection and analysis module to calculate the stability evaluation index and the mechanics adaptability index of the keyboard keycap respectively, which together reflect the performance and user experience of the keyboard keycap in actual use; through the evaluation of the two indexes, the system can timely find potential key problems and make personalized adjustment and optimization according to the user's key habits and needs, thereby improving the stability and comfort of the keyboard and the operation efficiency and accuracy of the user;

[0052] 2. The present application can comprehensively analyze the stability evaluation index and the mechanics adaptability index through the keyboard keycap management control analysis module to obtain the keyboard keycap management control coefficient, which not only reflects the current state of the keyboard keycap, but also provides a basis for the intelligent management control of the system; at the same time, the keyboard keycap control abnormality diagnosis module can accurately diagnose the keyboard keycap control abnormality based on the management control coefficient, timely find and warn potential problems, and ensure the reliability and safety of the system. BRIEF DESCRIPTION OF DRAWINGS

[0053] The present application is further illustrated by the accompanying drawings, but the embodiments in the drawings do not constitute any limitation on the present application. For ordinary skilled persons in the art, other drawings can be obtained without creative labor on the basis of the following drawings.

[0054] Figure 1 The present application is a structure schematic diagram of a keyboard keycap dynamic control system based on a balance bar.

[0055] Figure 2 The present application is a flowchart of a keyboard keycap dynamic control method based on a balance bar. DETAILED DESCRIPTION

[0056] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary skilled persons in the art without creative labor are within the scope of protection of the present application.

[0057] Example 1

[0058] Referring to Figure 1 As shown in the drawings, the application provides a keyboard keycap dynamic control system based on a balance bar, comprising a keycap data acquisition node division module, a keycap motion state data acquisition module, a keycap motion state data analysis module, a keycap motion kinetics data detection module, a keycap motion kinetics data analysis module, a keyboard keycap management control analysis module, and a keyboard keycap control abnormality diagnosis module.

[0059] The keycap data acquisition node division module is configured to determine the keyboard keycap as a target monitoring object, and divide the target keyboard keycap data acquisition node into n monitoring sub-regions, i = 1, 2, 3,..., n, i being the number of each monitoring sub-region.

[0060] In this embodiment, it needs to be specifically explained that the specific execution mode of the keycap data acquisition node division module is as follows:

[0061] The keyboard keycap is determined as a target monitoring object, and the target keyboard keycap data acquisition node is divided. According to the division mode of the target keyboard keycap motion time node, the target keyboard keycap data acquisition node is divided into n monitoring sub-regions, i = 1, 2, 3,..., n, wherein i is the number of each monitoring sub-region.

[0062] The keycap motion state data acquisition module is configured to collect and analyze the motion state of each monitoring sub-region of the target keyboard keycap, and obtain the motion state data of each monitoring sub-region of the target keyboard keycap.

[0063] In this embodiment, it needs to be specifically explained that the specific execution mode of the keycap motion state data acquisition module is as follows:

[0064] Firstly, a miniature camera is installed inside the keyboard to take pictures of the balance bar, and the balance bar image is subjected to grayscale processing. Then, the noise in the image is removed by a Gaussian filtering method, and the edge detection algorithm (such as Canny edge detection) is used to identify the edge of the balance bar to obtain the edge pixel points of the balance bar. The contour extraction algorithm (such as the algorithm based on boundary tracking) is used to connect the edge pixel points into the contour of the balance bar, and the two end points of the balance bar contour of each monitoring sub-region are extracted as feature points. The coordinates of the two end points of the balance bar contour of each monitoring sub-region in the image are marked as and , respectively. They are substituted into the formula to obtain the inclination angle of the balance bar of the i-th monitoring sub-region , wherein represents a correction factor.

[0065] The second step is to obtain the friction force between the keycap and the balance bar through the strain gauge friction sensor, and obtain the bridge output voltage of each monitoring sub-area. U 1 i and the bridge supply voltage of each monitoring sub-area U 2 i , substitute it into the formula , get the friction force between the keycap and the balance bar in the i-th monitoring sub-area ,in, K represents the strain gauge sensitivity coefficient, m Indicates the sensor calibration coefficient;

[0066] In this embodiment, it should be noted that the bridge output voltage refers to the voltage difference across the bridge circuit when the bridge is unbalanced. A bridge circuit is a circuit consisting of four resistors (or inductors, etc.), two of which serve as bridge arms, and the other two also serve as bridge arms but are typically associated with the device under test.

[0067] The bridge supply voltage is the voltage that provides the bridge with operating power. In a bridge circuit, the supply voltage is essential for the bridge to function properly. It is typically provided by a power supply and is used to drive the various components in the bridge.

[0068] The third step is to install an accelerometer (such as a piezoelectric accelerometer) at the bottom of the keycap to measure the vibration frequency of the keycap in each monitoring sub-area. Vf i ;

[0069] The fourth step is to record the tilt angle of the balance bar, the friction between the keycap and the balance bar, and the vibration frequency of the keycap as the motion state data of each monitoring sub-area of ​​the target keyboard keycap, and mark them as 、 、 Vf i , i is the number of each monitoring sub-area.

[0070] Keycap motion state data analysis module: analyzes the motion state of the target keyboard keycap based on the motion state data of each monitoring sub-area of ​​the target keyboard keycap to obtain the keyboard keycap stability evaluation index;

[0071] In this embodiment, it should be specifically explained that the specific execution method of the keycap motion state data analysis module is as follows:

[0072] The first step is to extract the keycap vibration frequency of the i-th monitoring sub-area Vf i , and at the same time extract the standard keycap vibration frequency corresponding to the target keyboard keycap from the management database Vf 0, and substitute them into the formula , get the keycap vibration frequency deviation of the i-th monitoring sub-area Vfd i ,

[0073] The second step is to establish a data extraction relationship between the keycap motion state data analysis module and the management database to extract the maximum allowable balance bar tilt angle corresponding to the target keyboard keycap. , the standard friction between the keycap corresponding to the target keyboard keycap and the balance bar ;

[0074] The third step is to calculate the keyboard keycap stability evaluation index SAI , the calculation model is as follows:

[0075] ,in, represents the tilt angle of the balance bar in the ith monitoring sub-area, Vfd max Indicates the preset maximum keycap vibration frequency deviation, e represents a natural constant, represents the friction force between the keycap and the balance bar in the i-th monitoring sub-area, n Indicates the total number of monitoring sub-areas, i Indicates the number of each monitoring sub-area.

[0076] Keycap action mechanics data detection module: used to detect and analyze the action mechanics data of each monitoring sub-area of ​​the target keyboard keycap, and obtain the action mechanics data of each monitoring sub-area of ​​the target keyboard keycap;

[0077] In this embodiment, it should be specifically explained that the specific execution method of the keycap action mechanics data detection module is as follows:

[0078] The first step is to install the linear variable differential transformer sensor under the keycap so that the iron core is connected to the bottom of the keycap. When the keycap rebounds, the displacement of the keycap in each monitoring sub-area is obtained. , use a timer to record the keycap rebound reset time of each monitoring sub-area t i , that is, the time interval from the keycap starting to rebound to the time it returns to its initial position, and substitute it into the formula , get the keycap rebound speed of the i-th monitoring sub-area ;

[0079] The second step is to install a pressure sensor at the bottom of the keycap to measure the key pressure of each monitoring sub-area. ;

[0080] The third step is to record the keycap rebound speed and key pressure as the action mechanics data of each monitoring sub-area of ​​the target keyboard keycap, and mark them as 、 , i is the number of each monitoring sub-area.

[0081] Keycap action mechanics data analysis module: analyzes the action mechanics of the target keyboard keycap based on the action mechanics data of each monitored sub-area of ​​the target keyboard keycap to obtain the keyboard keycap mechanical adaptability index;

[0082] In this embodiment, it should be specifically explained that the specific execution method of the keycap action mechanics data analysis module is as follows:

[0083] The first step is to extract the keycap rebound speed of the i-th monitoring sub-area At the same time, the standard keycap rebound speed corresponding to the target keyboard keycap is extracted from the management database , respectively substitute them into the formula , get the keycap rebound speed deviation of the i-th monitoring sub-area Rsd i ;

[0084] The second step is to extract the key pressure of the i-th monitoring sub-area , and extract the standard key pressure corresponding to the target keyboard keycap from the management database , respectively substitute them into the formula , get the key pressure deviation coefficient of the i-th monitoring sub-area Pdc i ;

[0085] The third step is to calculate the mechanical adaptability index of the keyboard keycap MAI , the calculation model is as follows:

[0086] ,in, Indicates the preset maximum keycap rebound speed deviation, n Indicates the total number of monitoring sub-areas, i Indicates the number of each monitoring sub-area.

[0087] Keyboard keycap management control analysis module: used to conduct a comprehensive analysis based on the keyboard keycap stability evaluation index and the keyboard keycap mechanical adaptability index to obtain the keyboard keycap management control coefficient, evaluate the keyboard keycap management control coefficient, and manage and control the keyboard keycap according to the evaluation results;

[0088] In this embodiment, it should be specifically explained that the specific execution method of the keyboard keycap management, control and analysis module is as follows:

[0089] Read the keyboard keycap stability evaluation index SAI And keyboard keycap mechanical adaptability index MAI , calculate the keyboard keycap management control coefficient, the calculation model is: ,in, MCC Indicates the keyboard keycap management control coefficient;

[0090] The keyboard keycap management and control coefficient is evaluated, and the keyboard keycap management and control coefficient is compared and analyzed with a preset management and control coefficient threshold. If the keyboard keycap management and control coefficient is less than or equal to the preset management and control coefficient threshold, it is judged that the state of the target keyboard keycap is normal. If the keyboard keycap management and control coefficient is greater than the preset management and control coefficient threshold, it is judged that the state of the target keyboard keycap is abnormal. The abnormal state of the target keyboard keycap is recorded as the evaluation result of the target keyboard keycap. The standard management and control method corresponding to the target keyboard keycap is obtained by screening the keyboard keycap management and control coefficient corresponding to the target keyboard keycap, and the target keyboard keycap is managed and controlled according to the standard management and control method corresponding to the target keyboard keycap.

[0091] In this embodiment, it should be specifically explained that the keyboard keycap stability evaluation index in the formula is SAI The larger the keyboard keycap mechanical adaptability index MAI The larger the value, the better the keyboard keycap management control coefficient MCC The smaller it is, the less control is required for the target keyboard keycap.

[0092] In this embodiment, it should be specifically explained that the keyboard keycap stability evaluation index in the formula is SAI And keyboard keycap mechanical adaptability index MAI There will be no mutual impact between them.

[0093] Keyboard keycap control abnormality diagnosis module: diagnose and analyze keyboard keycap control abnormality based on keyboard keycap management control coefficient, obtain keyboard keycap control abnormality coefficient, and judge whether it is abnormal based on the keyboard keycap control abnormality coefficient, and issue warning information for data judged to be abnormal.

[0094] In this embodiment, it should be specifically explained that the specific execution method of the keyboard keycap control abnormality diagnosis module is as follows:

[0095] The first step is to calculate the keyboard keycap control abnormality coefficient CAC , the calculation model is as follows:

[0096] ,in, MCC Indicates the keyboard keycap management control coefficient, It represents the mean value of keyboard keycap management control coefficient;

[0097] When the ratio of the keyboard keycap management control coefficient to the average keyboard keycap management control coefficient is larger, the keyboard keycap control abnormality coefficient is smaller, indicating that the target keyboard keycap management control is normal, and when the ratio of the keyboard keycap management control coefficient to the average keyboard keycap management control coefficient is smaller, the keyboard keycap control abnormality coefficient is larger, indicating that the target keyboard keycap management control is abnormal.

[0098] Second step, extract the keyboard keycap control abnormality coefficient, compare it with the preset control abnormality coefficient threshold value, if the keyboard keycap control abnormality coefficient is greater than the preset control abnormality coefficient threshold value, it is judged that the target keyboard keycap management control is abnormal, the management control abnormality diagnosis process is triggered, and the management personnel is informed to perform abnormal management control on the target keyboard. Warning information is issued for the data of the abnormal judgment result; otherwise, it is judged that the target keyboard keycap management control is normal.

[0099] Embodiment 2

[0100] Please refer to Figure 2 The application provides a keyboard keycap dynamic control method based on a balance bar, which comprises the following steps:

[0101] S1: Keycap data acquisition node division: the keyboard keycap is determined as a target monitoring object, and the target keyboard keycap data acquisition node is divided into n monitoring sub-regions, i=1, 2, 3,..., n, i is the number of each monitoring sub-region;

[0102] S2: Keycap motion state data acquisition: the motion state of each monitoring sub-region of the target keyboard keycap is collected and analyzed to obtain the motion state data of each monitoring sub-region of the target keyboard keycap;

[0103] S3: Keycap motion state data analysis: the motion state of the target keyboard keycap is analyzed based on the motion state data of each monitoring sub-region of the target keyboard keycap to obtain a keyboard keycap stability evaluation index;

[0104] S4: Keycap motion mechanics data detection: the motion mechanics data of each monitoring sub-region of the target keyboard keycap is detected and analyzed to obtain the motion mechanics data of each monitoring sub-region of the target keyboard keycap;

[0105] S5: Keycap motion mechanics data analysis: the motion mechanics of the target keyboard keycap is analyzed based on the motion mechanics data of each monitoring sub-region of the target keyboard keycap to obtain a keyboard keycap mechanics adaptability index;

[0106] S6: Keyboard keycap management control analysis: the keyboard keycap management control coefficient is obtained by comprehensively analyzing the keyboard keycap stability evaluation index and the keyboard keycap mechanics adaptability index, and the keyboard keycap management control coefficient is evaluated, and the keyboard keycap is managed and controlled according to the evaluation result;

[0107] S7: Keyboard key cap control abnormality diagnosis: based on the keyboard key cap management control coefficient, the keyboard key cap control abnormality is diagnosed and analyzed, the keyboard key cap control abnormality coefficient is obtained, and whether it is abnormal is judged according to the keyboard key cap control abnormality coefficient, and a warning information is sent for the data of the judgment result being abnormal.

[0108] Finally: the above only for the preferred embodiments of the present application, and not for limiting the present application, any modification, equivalent replacement, improvement, etc. within the spirit and principles of the present application, should be included in the protection scope of the present application.

[0109] The above is only a specific embodiment of the present application, but the protection scope of the present application is not limited to this. Any person skilled in the art can easily think of changes or replacements within the technical range disclosed by the present application, which should be covered within the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.

Claims

1. A keyboard keycap dynamic control system based on a balance bar, characterized in that: include: Keycap data collection node division module: used to determine the keyboard keycap as the target monitoring object, and divide the target keyboard keycap data collection node into n monitoring sub-areas, i=1, 2, 3, ..., n, i is the number of each monitoring sub-area; Keycap motion state data acquisition module: used to collect and analyze the motion state of each monitoring sub-area of ​​the target keyboard keycap, and obtain the motion state data of each monitoring sub-area of ​​the target keyboard keycap; The specific implementation of the keycap motion state data acquisition module is as follows: In the first step, a micro camera is installed inside the keyboard to shoot the balance bar to obtain a balance bar image. The balance bar image is grayscaled, and then the noise in the image is removed by the Gaussian filter method. The edge detection algorithm is used to identify the edge of the balance bar to obtain the edge pixel points of the balance bar. The edge pixel points are connected into the outline of the balance bar using the contour extraction algorithm. The two endpoints of the balance bar outline of each monitoring sub-area are extracted as feature points, and the coordinates of the two endpoints of the balance bar outline of each monitoring sub-area in the image are marked as and , substitute it into the formula , get the tilt angle of the balance bar in the i-th monitoring sub-area ,in, represents the correction factor; The second step is to obtain the friction force between the keycap and the balance bar through the strain gauge friction sensor, and obtain the bridge output voltage of each monitoring sub-area. U 1 i and the bridge supply voltage of each monitoring sub-area U 2 i , substitute it into the formula , get the friction force between the keycap and the balance bar in the i-th monitoring sub-area ,in, K represents the strain gauge sensitivity coefficient, m Indicates the sensor calibration coefficient; The third step is to install an accelerometer at the bottom of the keycap to measure the vibration frequency of the keycap in each monitoring sub-area. Vf i ; The fourth step is to record the tilt angle of the balance bar, the friction between the keycap and the balance bar, and the vibration frequency of the keycap as the motion state data of each monitoring sub-area of ​​the target keyboard keycap, and mark them as 、 、 Vf i , i is the number of each monitoring sub-area; Keycap motion state data analysis module: analyzes the motion state of the target keyboard keycap based on the motion state data of each monitoring sub-area of ​​the target keyboard keycap to obtain the keyboard keycap stability evaluation index; The specific execution method of the keycap motion state data analysis module is as follows: The first step is to extract the keycap vibration frequency of the i-th monitoring sub-area Vf i , and at the same time extract the standard keycap vibration frequency corresponding to the target keyboard keycap from the management database Vf 0 , respectively substitute them into the formula , get the keycap vibration frequency deviation of the i-th monitoring sub-area VfD i , The second step is to establish a data extraction relationship between the keycap motion state data analysis module and the management database to extract the maximum allowable balance bar tilt angle corresponding to the target keyboard keycap. , the standard friction between the keycap corresponding to the target keyboard keycap and the balance bar ; The third step is to calculate the keyboard keycap stability evaluation index SAI , the calculation model is as follows: ,in, represents the tilt angle of the balance bar in the ith monitoring sub-area, VfD max Indicates the preset maximum keycap vibration frequency deviation, e represents a natural constant, represents the friction force between the keycap and the balance bar in the i-th monitoring sub-area, n Indicates the total number of monitoring sub-areas, i Indicates the number of each monitoring sub-area; Keycap action mechanics data detection module: used to detect and analyze the action mechanics data of each monitoring sub-area of ​​the target keyboard keycap, and obtain the action mechanics data of each monitoring sub-area of ​​the target keyboard keycap; Keycap action mechanics data analysis module: analyzes the action mechanics of the target keyboard keycap based on the action mechanics data of each monitored sub-area of ​​the target keyboard keycap to obtain the keyboard keycap mechanical adaptability index; The specific execution method of the keycap action mechanics data analysis module is as follows: The first step is to extract the keycap rebound speed of the i-th monitoring sub-area At the same time, the standard keycap rebound speed corresponding to the target keyboard keycap is extracted from the management database , respectively substitute them into the formula , get the keycap rebound speed deviation of the i-th monitoring sub-area Rsd i ; The second step is to extract the key pressure of the i-th monitoring sub-area , and extract the standard key pressure corresponding to the target keyboard keycap from the management database , respectively substitute them into the formula , get the key pressure deviation coefficient of the i-th monitoring sub-area Pdc i ; The third step is to calculate the mechanical adaptability index of the keyboard keycap MAI , the calculation model is as follows: ,in, Indicates the preset maximum keycap rebound speed deviation, n Indicates the total number of monitoring sub-areas, i Indicates the number of each monitoring sub-area; Keyboard keycap management control analysis module: used to conduct a comprehensive analysis based on the keyboard keycap stability evaluation index and the keyboard keycap mechanical adaptability index to obtain the keyboard keycap management control coefficient, evaluate the keyboard keycap management control coefficient, and manage and control the keyboard keycap according to the evaluation results; The specific execution method of the keyboard keycap management control analysis module is as follows: Read the keyboard keycap stability evaluation index SAI And keyboard keycap mechanical adaptability index MAI , calculate the keyboard keycap management control coefficient, the calculation model is: ,in, MCC Indicates the keyboard keycap management control coefficient; Keyboard keycap control abnormality diagnosis module: diagnoses and analyzes keyboard keycap control abnormalities based on the keyboard keycap management control coefficient, obtains the keyboard keycap control abnormality coefficient, and determines whether it is abnormal based on the keyboard keycap control abnormality coefficient, and issues warning information for data with abnormal judgment results; The specific implementation method of the keyboard keycap control abnormality diagnosis module is as follows: The first step is to calculate the keyboard keycap control abnormality coefficient CAC , the calculation model is as follows: ,in, MCC Indicates the keyboard keycap management control coefficient, It represents the mean value of keyboard keycap management control coefficient; The second step is to extract the keyboard keycap control abnormality coefficient and compare it with the preset control abnormality coefficient threshold. If the keyboard keycap control abnormality coefficient is greater than the preset control abnormality coefficient threshold, it is judged that there is an abnormality in the management and control of the target keyboard keycap, triggering the management and control abnormality diagnosis process, and notifying the management personnel to perform abnormal management and control on the target keyboard, and issuing an early warning message for the data judged to be abnormal; otherwise, it is judged that there is no abnormality in the management and control of the target keyboard keycap.

2. The keyboard keycap dynamic control system based on a balance bar according to claim 1, characterized in that: The specific implementation method of the keycap data acquisition node division module is as follows: The keyboard keycaps are determined as target monitoring objects, and the target keyboard keycap data collection nodes are divided. According to the division method of the target keyboard keycap movement time nodes, the target keyboard keycap data collection nodes are divided into n monitoring sub-areas, i=1, 2, 3, ..., n, where i is the number of each monitoring sub-area.

3. The keyboard keycap dynamic control system based on a balance bar according to claim 1, characterized in that: The specific implementation method of the keycap action mechanics data detection module is as follows: The first step is to install the linear variable differential transformer sensor under the keycap so that the iron core is connected to the bottom of the keycap. When the keycap rebounds, the displacement of the keycap in each monitoring sub-area is obtained. , use a timer to record the keycap rebound reset time of each monitoring sub-area t i , that is, the time interval from the keycap starting to rebound to the time it returns to its initial position, and substitute it into the formula , get the keycap rebound speed of the i-th monitoring sub-area ; The second step is to install a pressure sensor at the bottom of the keycap to measure the key pressure of each monitoring sub-area. ; The third step is to record the keycap rebound speed and key pressure as the action mechanics data of each monitoring sub-area of ​​the target keyboard keycap, and mark them as 、 , i is the number of each monitoring sub-area.

4. The keyboard keycap dynamic control system based on a balance bar according to claim 1, characterized in that: The specific execution method of the keyboard keycap management control analysis module is as follows: The keyboard keycap management and control coefficient is evaluated, and the keyboard keycap management and control coefficient is compared and analyzed with a preset management and control coefficient threshold. If the keyboard keycap management and control coefficient is less than or equal to the preset management and control coefficient threshold, it is judged that the state of the target keyboard keycap is normal. If the keyboard keycap management and control coefficient is greater than the preset management and control coefficient threshold, it is judged that the state of the target keyboard keycap is abnormal. The abnormal state of the target keyboard keycap is recorded as the evaluation result of the target keyboard keycap. The standard management and control method corresponding to the target keyboard keycap is obtained by screening the keyboard keycap management and control coefficient corresponding to the target keyboard keycap, and the target keyboard keycap is managed and controlled according to the standard management and control method corresponding to the target keyboard keycap.

5. A keyboard keycap dynamic control method based on a balance bar, used for using the keyboard keycap dynamic control system based on a balance bar according to any one of claims 1 to 4, characterized in that: The following steps are involved: S1: Keycap data collection node division: The keyboard keycap is determined as the target monitoring object, and the target keyboard keycap data collection node is divided into n monitoring sub-areas, i=1, 2, 3, ..., n, i is the number of each monitoring sub-area; S2: keycap motion state data collection: collect and analyze the motion state of each monitoring sub-area of ​​the target keyboard keycap to obtain the motion state data of each monitoring sub-area of ​​the target keyboard keycap; S3: Keycap motion state data analysis: Analyze the motion state of the target keyboard keycap based on the motion state data of each monitoring sub-area of ​​the target keyboard keycap to obtain a keyboard keycap stability evaluation index; S4: keycap motion mechanics data detection: detecting and analyzing the motion mechanics data of each monitoring sub-area of ​​the target keyboard keycap to obtain the motion mechanics data of each monitoring sub-area of ​​the target keyboard keycap; S5: Keycap action mechanics data analysis: Analyze the action mechanics of the target keyboard keycap based on the action mechanics data of each monitored sub-area of ​​the target keyboard keycap to obtain the keyboard keycap mechanical adaptability index; S6: Keyboard keycap management and control analysis: performing a comprehensive analysis based on the keyboard keycap stability evaluation index and the keyboard keycap mechanical adaptability index to obtain a keyboard keycap management and control coefficient, and evaluating the keyboard keycap management and control coefficient, and managing and controlling the keyboard keycaps based on the evaluation results; S7: Keyboard keycap control abnormality diagnosis: diagnose and analyze the keyboard keycap control abnormality based on the keyboard keycap management control coefficient, obtain the keyboard keycap control abnormality coefficient, and judge whether it is abnormal based on the keyboard keycap control abnormality coefficient, and issue a warning message for data with abnormal judgment results.

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