Keyboard keycap dynamic control system and method based on balance rod

Abstract

The invention relates to the technical field of keyboard keycap control, and particularly discloses a dynamic keyboard keycap control system and method based on a balance rod. 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 abnormity diagnosis module. The stability and the mechanical suitability of the keyboard keycaps are evaluated through the keycap motion state and action mechanical data detection module, then the keyboard keycap management control coefficient is obtained through analysis, the intelligent management control and abnormity diagnosis module can dynamically adjust keyboard settings according to the evaluation result, potential problems are found and early warned in time, and the management control efficiency is improved. The system stability and the user operation efficiency are ensured; the keyboard performance is improved, the user experience is enhanced, and the keyboard is easy to maintain and upgrade and has a wide application prospect.

Description

Technical Field

[0001] The present invention relates to the technical field of keyboard keycap control, and particularly to a dynamic control system and method for keyboard keycaps based on a balance bar. Background Art

[0002] With the rapid development of information technology, the keyboard, as an important tool for human-computer interaction, plays an indispensable role in daily life and work. In order to improve the user's typing experience, especially for the needs of different application scenarios, the exploration of a dynamic control system for keyboard keycaps has become particularly important. Especially in professional fields such as game competition, high-speed typing, and precision programming, the response speed, stability, and personalized customization ability of the keyboard have become the key indicators for measuring the quality of the keyboard.

[0003] Traditional dynamic control systems for keyboard keycaps mainly rely on the connection between the shaft body or rubber bowl and the base. For example, mechanical keyboards trigger signals through the mechanical structure of the shaft body, while membrane keyboards rely on the deformation of the rubber bowl to contact the circuit. Although large keycaps are assisted by balance bars or satellite axes, the structure is simple and lacks precise dynamic adjustment. These systems are based on the principle of electrical switches and only recognize the "pressed" and "released" states, and cannot real-time monitor dynamic parameters such as key pressure, speed, and rebound.

[0004] Disadvantages of traditional dynamic control systems for keyboard keycaps: First, the analysis of the movement state of keyboard keycaps by traditional systems is usually based on simple trigger signals or displacement measurements, lacking in-depth analysis of movement state data. This results in the system being unable to accurately evaluate the stability of the keycaps and unable to detect potential key loosening or failures in a timely manner. Second, traditional systems have limited means in management and control, usually only being able to implement simple functions such as key locking and disabling. They lack the ability to conduct comprehensive analysis based on the stability and mechanical adaptability of the keycaps. In addition, traditional systems also have deficiencies in abnormal diagnosis. They can usually only detect simple key failures or incorrect inputs, and cannot accurately diagnose complex control anomalies. Summary of the Invention

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

[0006] To achieve the above object, the present invention provides the following technical solution: A dynamic control system for keyboard keycaps based on a balance bar, including a keycap data acquisition node division module, a keycap movement state data acquisition module, a keycap movement 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 anomaly diagnosis module.

[0007] Keycap data acquisition node division module: used to determine the keyboard keycaps as the target monitoring objects, and divide the target keyboard keycap data acquisition nodes into n monitoring sub-regions, where i = 1, 2, 3,..., n, and i is the number of each monitoring sub-region; Keycap motion state data acquisition module: used to collect and analyze the motion states of each monitoring sub-region of the target keyboard keycaps to obtain the motion state data of each monitoring sub-region of the target keyboard keycaps; Keycap motion state data analysis module: based on the motion state data of each monitoring sub-region of the target keyboard keycaps, analyze the motion state of the target keyboard keycaps to obtain the keycap stability evaluation index; Keycap action mechanics data detection module: used to detect and analyze the action mechanics data of each monitoring sub-region of the target keyboard keycaps to obtain the action mechanics data of each monitoring sub-region of the target keyboard keycaps; Keycap action mechanics data analysis module: based on the action mechanics data of each monitoring sub-region of the target keyboard keycaps, analyze the action mechanics of the target keyboard keycaps to obtain the keycap mechanics adaptability index; Keyboard keycap management control analysis module: used to comprehensively analyze according to the keycap stability evaluation index and the keycap mechanics adaptability index to obtain the keycap management control coefficient, evaluate the keycap management control coefficient, and manage and control the keyboard keycaps according to the evaluation results; Keyboard keycap control anomaly diagnosis module: based on the keycap management control coefficient, diagnose and analyze the keyboard keycap control anomaly to obtain the keyboard keycap control anomaly coefficient, and judge whether it is abnormal according to the keyboard keycap control anomaly coefficient, and send a warning message for the data with the judgment result of abnormality.

[0008] Preferably, the specific execution method of the keycap data acquisition node division module is as follows: Determine the keyboard keycaps as the target monitoring objects, and divide the target keyboard keycap data acquisition nodes. According to the division method of the target keyboard keycap motion time nodes, divide the target keyboard keycap data acquisition nodes into n monitoring sub-regions, where i = 1, 2, 3,..., n, and i is the number of each monitoring sub-region.

[0009] Preferably, the specific execution method of the keycap motion state data acquisition module is as follows: First step, install a micro camera inside the keyboard to take pictures of the balance bar, obtain the balance bar image, perform grayscale processing on the balance bar image, then remove the noise in the image through the Gaussian filtering method, use the edge detection algorithm to identify the edge of the balance bar, and obtain the edge pixel points of the balance bar; use the contour extraction algorithm to connect the edge pixel points into the contour of the balance bar, extract the two end points of the balance bar contour in each monitoring sub-region as feature points, and mark the coordinates of the two end points of the balance bar contour in the image in each monitoring sub-region as and , substitute them into the formula , and obtain the tilt angle of the balance bar in the i-th monitoring sub-region, where represents the correction factor; Second step, obtain the friction force between the keycap and the balance bar through the strain gauge friction sensor, and obtain the bridge output voltage U 1 i in each monitoring sub-region and the bridge supply voltage U 2 i in each monitoring sub-region, substitute them into the formula , and obtain the friction force between the keycap and the balance bar in the i-th monitoring sub-region, where K represents the strain gauge sensitivity coefficient, m represents the sensor calibration coefficient; Third step, install an acceleration sensor at the bottom of the keycap to measure the keycap vibration frequency Vf i ; Fourth step, record the tilt angle of the balance bar, the friction force 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 , where i is the number of each monitoring sub-region.

[0010] Preferably, the specific execution method of the keycap motion state data analysis module is as follows: First step, extract the keycap vibration frequency Vf i of the i-th monitoring sub-region, and at the same time extract the standard keycap vibration frequency Vf 0 corresponding to the target keyboard keycap from the management database, substitute them into the formula respectively, and obtain the keycap vibration frequency deviation Vfd i of the i-th monitoring sub-region, In the second step, establish a data extraction relationship between the keycap motion state data analysis module and the management database, and extract the maximum allowable tilt angle of the balance bar corresponding to the target keyboard keycap and the standard friction force between the keycap and the balance bar corresponding to the target keyboard keycap ; In the third step, calculate the keyboard keycap stability evaluation index SAI , and the calculation model is as follows: , where represents the tilt angle of the balance bar in the i-th monitoring sub-region, Vfd max represents the preset maximum keycap vibration frequency deviation, e represents the natural constant, represents the friction force between the keycap and the balance bar in the i-th monitoring sub-region, n represents the total number of monitoring sub-regions, i represents the number of the i-th monitoring sub-region.

[0011] Preferably, the specific execution method of the keycap motion mechanics data detection module is as follows: In the first step, install a linear variable differential transformer sensor under the keycap, connect the iron core to the bottom of the keycap, and obtain the keycap displacement of each monitoring sub-region when the keycap rebounds , and use a timer to record the keycap rebound reset time of each monitoring sub-region t i , that is, the time interval from the start of keycap rebound to the complete return to the initial position, and substitute them into the formula respectively to obtain the keycap rebound speed of the i-th monitoring sub-region; In the second step, install a pressure sensor at the bottom of the keycap to measure the key pressure of each monitoring sub-region ; In the third step, record the keycap rebound speed and key pressure as the motion mechanics data of each monitoring sub-region of the target keyboard keycap, and mark them as and respectively, where i is the number of each monitoring sub-region.

[0012] Preferably, the specific execution method of the keycap motion mechanics data analysis module is as follows: In the first step, extract the keycap rebound speed of the i-th monitoring sub-region, and at the same time extract the standard keycap rebound speed corresponding to the target keyboard keycap from the management database, and substitute them into the formula respectively to obtain the keycap rebound speed deviation Rsd i of the i-th monitoring sub-region; Step 2: Extract the key pressing force of the i-th monitored sub-region , and at the same time, extract the standard key pressing force corresponding to the target keyboard keycap from the management database , and substitute them into the formula respectively to obtain the key pressing force deviation coefficient of the i-th monitored sub-region Pdc i ; Step 3: Calculate the mechanical adaptability index of the keyboard keycap MAI , and the calculation model is as follows: , where represents the preset maximum keycap rebound speed deviation n represents the total number of monitored sub-regions i represents the number of each monitored sub-region

[0013] Preferably, the specific execution method of the keyboard keycap management and control analysis module is as follows: Read the keyboard keycap stability evaluation index SAI and the mechanical adaptability index of the keyboard keycap MAI , calculate the keyboard keycap management and control coefficient, and the calculation model is: , where MCC represents the keyboard keycap management and control coefficient; Evaluate the keyboard keycap management and control coefficient, compare and analyze the keyboard keycap management and control coefficient with the 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 determined 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 determined that the state of the target keyboard keycap is abnormal. Record the abnormal state of the target keyboard keycap as the evaluation result of the target keyboard keycap, screen the standard management and control method corresponding to the target keyboard keycap according to the keyboard keycap management and control coefficient corresponding to the target keyboard keycap, and perform management and control on the target keyboard keycap according to the standard management and control method corresponding to the target keyboard keycap

[0014] Preferably, the specific execution method of the keyboard keycap control anomaly diagnosis module is as follows: Step 1: Calculate the keyboard keycap control anomaly coefficient CAC , and the calculation model is as follows: , where MCC represents the keyboard keycap management and control coefficient represents the average value of the keyboard keycap management and control coefficient; In the second step, extract the abnormal coefficient of keyboard keycap control, and compare it with the preset abnormal coefficient threshold of control. If the abnormal coefficient of keyboard keycap control is greater than the preset abnormal coefficient threshold of control, it is determined that there is an abnormality in the management control of the target keyboard keycap, trigger the abnormal diagnosis process of management control, and notify the management personnel to perform abnormal management control on the target keyboard, and send a warning message for the data with the judgment result of abnormality; otherwise, it is determined that there is no abnormality in the management control of the target keyboard keycap.

[0015] To achieve the above object, the present invention provides the following technical solutions: A dynamic control method for keyboard keycaps based on a balance bar. Implementing the above dynamic control system for keyboard keycaps based on a balance bar includes the following steps: S1: Division of keycap data acquisition nodes: Determine the keyboard keycaps as the target monitoring objects, and divide the target keyboard keycap data acquisition nodes into n monitoring sub-regions, where i = 1, 2, 3,..., n, and i is the number of each monitoring sub-region; S2: Acquisition of keycap motion state data: Collect and analyze the motion states of each monitoring sub-region of the target keyboard keycaps to obtain the motion state data of each monitoring sub-region of the target keyboard keycaps; S3: Analysis of keycap motion state data: Analyze the motion states of the target keyboard keycaps based on the motion state data of each monitoring sub-region of the target keyboard keycaps to obtain the keycap stability evaluation index; S4: Detection of keycap action mechanics data: Detect and analyze the action mechanics data of each monitoring sub-region of the target keyboard keycaps to obtain the action mechanics data of each monitoring sub-region of the target keyboard keycaps; S5: Analysis of keycap action mechanics data: Analyze the keycap action mechanics based on the action mechanics data of each monitoring sub-region of the target keyboard keycaps to obtain the keycap mechanics adaptability index; S6: Analysis of keyboard keycap management control: Perform comprehensive analysis according to the keycap stability evaluation index and the keycap mechanics adaptability index to obtain the keyboard keycap management control coefficient, and evaluate the keyboard keycap management control coefficient, and perform management control on the keyboard keycaps according to the evaluation result; S7: Diagnosis of keyboard keycap control abnormality: Based on the keyboard keycap management control coefficient, diagnose and analyze the keyboard keycap control abnormality to obtain the keyboard keycap control abnormality coefficient, and determine whether it is abnormal according to the keyboard keycap control abnormality coefficient, and send a warning message for the data with the judgment result of abnormality.

[0016] The technical effects and advantages of the present invention: 1. The present invention uses a keycap motion state data analysis module and a keycap action mechanics data detection and analysis module to calculate the stability evaluation index and the mechanical adaptability index of the keyboard keycaps respectively. These two indexes jointly reflect the performance and user experience of the keyboard keycaps in actual use. Through the evaluation of these two indexes, the system can timely detect potential key problems and make personalized adjustments and optimizations according to the user's key pressing habits and needs, thereby improving the stability and comfort of the keyboard, as well as the user's operation efficiency and accuracy. 2. The present invention can perform comprehensive analysis through the keyboard keycap management control analysis module according to the stability evaluation index and the mechanical adaptability index to obtain the keyboard keycap management control coefficient, which not only reflects the current state of the keyboard keycaps, but also provides a basis for the intelligent management and control of the system. At the same time, the keyboard keycap control anomaly diagnosis module can accurately diagnose the keyboard keycap control anomaly based on the management control coefficient, timely detect and warn potential problems, and ensure the reliability and security of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The present invention will be further described with reference to the accompanying drawings. However, the embodiments in the drawings do not constitute any limitation to the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the following drawings.

[0018] Figure 1 It is a schematic structural diagram of a dynamic control system for keyboard keycaps based on a balance bar according to the present invention.

[0019] Figure 2 It is a schematic flow diagram of a dynamic control method for keyboard keycaps based on a balance bar according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0020] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0021] Embodiment 1 Please refer to Figure 1 As shown, the present invention provides a dynamic control system for keyboard keycaps based on a balance bar, including 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 anomaly diagnosis module. Keycap data acquisition node division module: used to determine the keyboard keycaps as the target monitoring objects, and divide the target keyboard keycap data acquisition nodes into n monitoring sub-regions, where i = 1, 2, 3,..., n, and i is the number of each monitoring sub-region; In this embodiment, it should be specifically noted that the specific implementation method of the keycap data acquisition node division module is as follows: Determine the keyboard keycaps as the target monitoring objects, and divide the target keyboard keycap data acquisition nodes. According to the division method of the target keyboard keycap movement time nodes, divide the target keyboard keycap data acquisition nodes into n monitoring sub-regions, where i = 1, 2, 3,..., n, and i is the number of each monitoring sub-region.

[0022] Keycap movement state data acquisition module: used to collect and analyze the movement states of each monitoring sub-region of the target keyboard keycaps to obtain the movement state data of each monitoring sub-region of the target keyboard keycaps; In this embodiment, it should be specifically noted that the specific implementation method of the keycap movement state data acquisition module is as follows: First step, install a micro camera inside the keyboard to take pictures of the balance bar to obtain the balance bar image. Perform grayscale processing on the balance bar image, then remove the noise in the image through the Gaussian filtering method, use an edge detection algorithm (such as Canny edge detection) to identify the edges of the balance bar to obtain the edge pixel points of the balance bar; use a contour extraction algorithm (such as an algorithm based on boundary tracking) to connect the edge pixel points into the contour of the balance bar, 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 , substitute them into the formula , to obtain the tilt angle of the balance bar in the i-th monitoring sub-region, where represents the correction factor; Second step, obtain the friction force between the keycap and the balance bar through a strain gauge friction sensor, obtain the bridge output voltage U 1 i of each monitoring sub-region and the bridge supply voltage U 2 i of each monitoring sub-region, substitute them into the formula , to obtain the friction force between the keycap and the balance bar in the i-th monitoring sub-region, where K represents the strain gauge sensitivity coefficient, m represents the sensor calibration coefficient; In this embodiment, it should be specifically noted that the output voltage of the bridge refers to the voltage difference between the two ends of the bridge when the bridge circuit is unbalanced. The bridge circuit is a circuit composed of four resistors (or inductors, etc.), where two components serve as bridge arms, and the other two components also serve as bridge arms but are usually related to the component to be measured.

[0023] The supply voltage of the bridge refers to the voltage that provides the working power supply for the bridge. In the bridge circuit, the supply voltage is a necessary condition for the normal operation of the bridge. It is generally provided by a power supply and is used to drive each component in the bridge to work.

[0024] Thirdly, install an acceleration sensor (such as a piezoelectric acceleration sensor) at the bottom of the keycap to measure the vibration frequency of the keycap in each monitored sub-region. Vf i ; Fourthly, record the tilt angle of the balance bar, the friction force between the keycap and the balance bar, and the vibration frequency of the keycap as the motion state data of each monitored sub-region of the target keyboard keycap, and mark them respectively as , , Vf i , where i is the number of each monitored sub-region.

[0025] Keycap motion state data analysis module: Analyze the motion state of the target keyboard keycap based on the motion state data of each monitored sub-region of the target keyboard keycap to obtain the keyboard keycap stability evaluation index; In this embodiment, it should be specifically noted that the specific execution method of the keycap motion state data analysis module is as follows: Firstly, extract the vibration frequency of the keycap in the i-th monitored sub-region Vf i , and at the same time extract the standard vibration frequency of the target keyboard keycap corresponding to the keycap from the management database Vf 0, and substitute them into the formula respectively to obtain the vibration frequency deviation of the keycap in the i-th monitored sub-region Vfd i , Secondly, establish a data extraction relationship between the keycap motion state data analysis module and the management database, and extract the maximum allowable tilt angle of the balance bar corresponding to the target keyboard keycap , and the standard friction force between the keycap and the balance bar corresponding to the target keyboard keycap ; Thirdly, calculate the keyboard keycap stability evaluation index SAI , and the calculation model is as follows: , where represents the tilt angle of the balance bar in the i-th monitored sub-region,Vfd max represents the preset maximum keycap vibration frequency deviation e represents the natural constant represents the frictional force between the keycap and the balance bar in the i-th monitored sub-region n represents the total number of monitored sub-regions i represents the number of each monitored sub-region

[0026] Keycap kinematic data detection module: used to detect and analyze the kinematic data of each monitored sub-region of the target keyboard keycap, and obtain the kinematic data of each monitored sub-region of the target keyboard keycap In this embodiment, it should be specifically noted that the specific execution method of the keycap kinematic data detection module is as follows First step, install a linear variable differential transformer sensor under the keycap, connect the iron core to the bottom of the keycap, and when the keycap rebounds, obtain the keycap displacement of each monitored sub-region and use a timer to record the keycap rebound reset time of each monitored sub-region t i , that is, the time interval from the start of the keycap rebound to the complete return to the initial position, and substitute them into the formula respectively to obtain the keycap rebound speed of the i-th monitored sub-region ; Second step, install a pressure sensor at the bottom of the keycap to measure the key pressure of each monitored sub-region ; Third step, record the keycap rebound speed and key pressure as the kinematic data of each monitored sub-region of the target keyboard keycap, and mark them as 、 respectively, where i is the number of each monitored sub-region

[0027] Keycap kinematic data analysis module: analyze the keycap kinematics based on the kinematic data of each monitored sub-region of the target keyboard keycap, and obtain the keycap mechanical adaptability index In this embodiment, it should be specifically noted that the specific execution method of the keycap kinematic data analysis module is as follows First step, extract the keycap rebound speed of the i-th monitored sub-region , and at the same time extract the standard keycap rebound speed corresponding to the target keyboard keycap from the management database , and substitute them into the formula respectively to obtain the keycap rebound speed deviation of the i-th monitored sub-region Rsd i ; Second step, extract the key pressure of the i-th monitored sub-region , simultaneously extract the standard key pressure corresponding to the target keyboard keycap from the management database , substitute them into the formula respectively , and obtain the key pressure deviation coefficient of the i-th monitoring sub-region Pdc i ; Thirdly, calculate the mechanical adaptability index of the keyboard keycap MAI , and the calculation model is as follows: , where represents the preset maximum keycap rebound speed deviation, n represents the total number of each monitoring sub-region, i represents the number of each monitoring sub-region.

[0028] Keyboard keycap management and control analysis module: used to comprehensively analyze according to the keyboard keycap stability evaluation index and the keyboard keycap mechanical adaptability index, obtain the keyboard keycap management and control coefficient, evaluate the keyboard keycap management and control coefficient, and manage and control the keyboard keycap according to the evaluation result; In this embodiment, it should be specifically noted that the specific execution method of the keyboard keycap management and control analysis module is as follows: Read the keyboard keycap stability evaluation index SAI and the keyboard keycap mechanical adaptability index MAI , calculate the keyboard keycap management and control coefficient, and the calculation model is: , where MCC represents the keyboard keycap management and control coefficient; Evaluate the keyboard keycap management and control coefficient, compare and analyze the keyboard keycap management and control coefficient with the 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. Record the abnormal state of the target keyboard keycap as the evaluation result of the target keyboard keycap. Screen the standard management and control method corresponding to the target keyboard keycap according to the keyboard keycap management and control coefficient corresponding to the target keyboard keycap, and manage and control the target keyboard keycap according to the standard management and control method corresponding to the target keyboard keycap.

[0029] In this embodiment, it should be specifically noted that the larger the keyboard keycap stability evaluation index SAI in the formula and the larger the keyboard keycap mechanical adaptability index MAI , the smaller the keyboard keycap management and control coefficient MCC , and the smaller the management and control requirement of the target keyboard keycap.

[0030] In this embodiment, it should be specifically noted that the keyboard keycap stability evaluation index in the formula SAI and the keyboard keycap mechanical adaptability index MAI do not affect each other.

[0031] Keyboard keycap control anomaly diagnosis module: Based on the keyboard keycap management control coefficient, diagnose and analyze the keyboard keycap control anomaly to obtain the keyboard keycap control anomaly coefficient, and determine whether there is an anomaly according to the keyboard keycap control anomaly coefficient, and send a warning message for the data with the judgment result of anomaly.

[0032] In this embodiment, it should be specifically noted that the specific execution method of the keyboard keycap control anomaly diagnosis module is as follows: The first step is to calculate the keyboard keycap control anomaly coefficient CAC , and the calculation model is as follows: , where MCC represents the keyboard keycap management control coefficient, represents the average value of the keyboard keycap management control coefficient; When the ratio of the keyboard keycap management control coefficient to the average value of the keyboard keycap management control coefficient is larger, the keyboard keycap control anomaly coefficient is smaller, indicating that there is no anomaly in the target keyboard keycap management control. When the ratio of the keyboard keycap management control coefficient to the average value of the keyboard keycap management control coefficient is smaller, the keyboard keycap control anomaly coefficient is larger, indicating that the target keyboard keycap management control is abnormal; The second step is to extract the keyboard keycap control anomaly coefficient and compare it with the preset control anomaly coefficient threshold. If the keyboard keycap control anomaly coefficient is greater than the preset control anomaly coefficient threshold, it is determined that there is an anomaly in the target keyboard keycap management control, trigger the management control anomaly diagnosis process, and notify the management personnel to perform abnormal management control on the target keyboard, and send a warning message for the data with the judgment result of anomaly; otherwise, it is determined that there is no anomaly in the target keyboard keycap management control.

[0033] Embodiment 2 Please refer to Figure 2 as shown. The present invention provides a dynamic control method for keyboard keycaps based on a balance bar, including the following steps: S1: Division of keycap data acquisition nodes: Determine the keyboard keycaps as the target monitoring objects, and divide the target keyboard keycap data acquisition nodes into n monitoring sub-regions, i = 1, 2, 3,..., n, and i is the number of each monitoring sub-region; S2: Acquisition of keycap motion state data: Collect and analyze the motion states of each monitoring sub-region of the target keyboard keycaps to obtain the motion state data of each monitoring sub-region of the target keyboard keycaps; S3: Analysis of the movement state data of the keycap: Analyze the movement state of the target keyboard keycap based on the movement state data of each monitored sub-region of the target keyboard keycap to obtain the keycap stability evaluation index; S4: Detection of the action mechanics data of the keycap: Detect and analyze the action mechanics data of each monitored sub-region of the target keyboard keycap to obtain the action mechanics data of each monitored sub-region of the target keyboard keycap; S5: Analysis of the action mechanics data of the keycap: Analyze the action mechanics of the target keyboard keycap based on the action mechanics data of each monitored sub-region of the target keyboard keycap to obtain the keycap mechanical adaptability index; S6: Analysis of the keycap management and control: Conduct a comprehensive analysis based on the keycap stability evaluation index and the keycap mechanical adaptability index to obtain the keycap management and control coefficient, evaluate the keycap management and control coefficient, and manage and control the keycap according to the evaluation result; S7: Diagnosis of the keycap control anomaly: Diagnose and analyze the keycap control anomaly based on the keycap management and control coefficient to obtain the keycap control anomaly coefficient, and determine whether it is abnormal based on the keycap control anomaly coefficient, and send a warning message for the data with an abnormal judgment result.

[0034] Finally: The above is only the preferred embodiment of the present invention and is not used to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

[0035] The above is only the specific implementation manner of this application, but the protection scope of this application is not limited thereto. Any person skilled in the art can easily think of changes or replacements within the technical scope disclosed in this application, and all should be covered by the protection scope of this application. Therefore, the protection scope of this application shall be subject to the protection scope of the claimed rights.

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; 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 a keyboard keycap stability evaluation index; 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 monitoring sub-area of ​​the target keyboard keycap to obtain the keyboard keycap mechanics adaptability index; 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, and evaluate the keyboard keycap management control coefficient, and manage and control the keyboard keycap according to the evaluation result; 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.

2. A 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 key cap 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, and the balance bar image is grayed. Then, the noise in the image is removed by the Gaussian filtering method, and 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, and the two endpoints of the balance bar outline of each monitoring sub-area are extracted as feature points. The coordinates of the two endpoints of the balance bar outline of each monitoring sub-area in the image are marked as and , substituting 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 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 , substituting 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 acceleration sensor at the bottom of the keycap to measure the vibration frequency of the keycap in each monitoring sub-area. V i ; In the fourth step, the tilt angle of the balance bar, the friction between the key cap and the balance bar, and the vibration frequency of the key cap are recorded as the motion state data of each monitoring sub-area of ​​the target keyboard key cap, and are marked as , , V i , 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 implementation 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 V i , and extract the standard keycap vibration frequency corresponding to the target keyboard keycap from the management database V 0, and 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 each monitoring sub-area, i Indicates the number of each monitoring sub-area.

5. The keyboard keycap dynamic control system based on a balance bar according to claim 1, characterized in that: The specific implementation method of the key cap action mechanical 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 keycap displacement of each monitoring sub-area is obtained. , use a timer to record the keycap rebound reset time of each monitoring sub-area t i , which is the time interval from the keycap starting to rebound to the keycap returning 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. ; In the third step, the keycap rebound speed and key pressure are recorded as the action mechanics data of each monitoring sub-area of ​​the target keyboard keycap, and are marked as , , i is the number of each monitoring sub-area.

6. 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 analysis module is as follows: The first step is to extract the keycap rebound speed of the i-th monitoring sub-area , and at the same time extract the standard keycap rebound speed corresponding to the target keyboard keycap 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 keycaps MAI , the calculation model is as follows: ,in, Indicates the preset maximum keycap rebound speed deviation, n Indicates the total number of each monitoring sub-area, i Indicates the number of each monitoring sub-area.

7. The keyboard keycap dynamic control system based on a balance bar according to claim 1, characterized in that: The specific implementation method of the keyboard keycap management control analysis module is as follows: Read the keyboard keycap stability evaluation index SAI Mechanical compatibility index with keyboard keycaps MAI , calculate the keyboard keycap management control coefficient, the calculation model is: ,in, MCC Indicates the keyboard keycap management control coefficient; Evaluate the keyboard keycap management and control coefficient, compare and analyze the keyboard keycap management and control coefficient 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, then determine 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, then determine that the state of the target keyboard keycap is abnormal; record the abnormal state of the target keyboard keycap as the evaluation result of the target keyboard keycap; obtain the standard management and control method corresponding to the target keyboard keycap based on the keyboard keycap management and control coefficient corresponding to the target keyboard keycap; and manage and control the target keyboard keycap based on the standard management and control method corresponding to the target keyboard keycap.

8. The keyboard keycap dynamic control system based on a balance bar according to claim 1, characterized in that: 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 keycaps, 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 early warning information for data judged to be abnormal; otherwise, it is judged that there is no abnormality in the management and control of the target keyboard keycaps.

9. A keyboard keycap dynamic control method based on a balance bar, used for using a keyboard keycap dynamic control system based on a balance bar as claimed in any one of claims 1 to 8, characterized in that: The following steps are involved: S1: keycap data collection node division: 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; 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: analyzing 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 action mechanics data detection: detecting and analyzing the action mechanics data of each monitoring sub-area of ​​the target keyboard keycap, and obtaining the action mechanics data of each monitoring sub-area of ​​the target keyboard keycap; S5: keycap action mechanics data analysis: based on the action mechanics data of each monitoring sub-area of ​​the target keyboard keycap, the action mechanics of the target keyboard keycap is analyzed to obtain the keyboard keycap mechanics adaptability index; S6: Keyboard keycap management and control analysis: perform 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, evaluate the keyboard keycap management and control coefficient, and manage and control the keyboard keycap based on the evaluation result; 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 judged to be abnormal.

Images