Data processing system and method based on calibration board of foot tester

Abstract

The invention relates to the technical field of data processing, in particular to a data processing system and method based on a calibration board of a foot testing instrument, and the method specifically comprises the steps: carrying out the initial data calibration processing of the foot testing instrument through the calibration board; a historical calibration data log is constructed, and first-round state approval is carried out; multiple groups of individual foot original data of the user are obtained through a foot testing instrument, and an individual foot original data sequence is formed; calculating a data accuracy coefficient of the original foot data of each group of individuals in real time; effective foot original data in the individual foot original data sequence are screened, and a foot scanning strategy is dynamically adjusted according to the effective foot original data. The problems that in the prior art, due to the fact that the precision of a foot testing instrument is reduced in the long-time using process, the foot scanning accuracy is difficult to guarantee, and the foot scanning strategy cannot be quantitatively adjusted are solved.

Description

Technical Field

[0001] The invention relates to the technical field of data processing, and is a data processing system and method based on a foot tester calibration board. Background Art

[0002] In the field of foot health assessment and diagnosis, foot testers, as a key device, are widely used in foot geometric parameter measurement, plantar pressure distribution analysis, foot morphology assessment, etc. However, in the initial data calibration process, the existing foot testers lack a systematic calibration plate and an accurate initial data calibration processing method, and mostly rely on manual calibration, which is not only time-consuming but also easy to introduce human errors, resulting in the long-term accuracy and stability of the measurement data being difficult to guarantee; at the same time, during the foot scanning process, due to the user's actions or the accuracy of the equipment, the scanning data may be inconsistent or erroneous, affecting the accuracy of subsequent analysis and diagnosis. When processing multiple groups of personal foot raw data, the existing technology lacks an effective data verification strategy, and cannot calculate the accuracy coefficient of each group of data in real time, and then screen out high-quality valid data, which hinders the subsequent data mining and utilization. Therefore, a new data processing system and method are urgently needed to improve the measurement accuracy and data processing capabilities of the foot tester equipment and ensure the consistency and reliability of the data. Summary of the invention

[0003] The purpose of this section is to summarize some aspects of embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0004] The technical problem to be solved by the present invention is that in the prior art, the accuracy of a foot tester decreases during long-term use, resulting in difficulty in ensuring the accuracy of foot scanning and the inability to quantify and adjust the foot scanning strategy. A data processing system and method based on a foot tester calibration board are proposed.

[0005] In order to achieve the above object, the technical solution of a data processing method based on a foot tester calibration plate of the present invention comprises the following steps:

[0006] S1: Start the foot tester and perform initial data calibration on the foot tester through the calibration board;

[0007] S2: Based on the initial data calibration processing results, a historical calibration data log is constructed, and the mechanical wear factor is calculated based on the historical calibration data log, and the first round of status verification of the working status of the foot detector is performed based on the mechanical wear factor;

[0008] S3: Debugging the foot detector to the foot scanning mode, scanning the user's feet multiple times within a standard scanning period, obtaining multiple groups of the user's personal foot raw data, and forming a personal foot raw data sequence;

[0009] S4: extracting the multiple sets of original foot data of individuals, importing the multiple sets of original foot data of individuals into the second round of data verification strategy, and calculating the data accuracy coefficient of each set of original foot data of individuals in real time;

[0010] S5: Filter valid foot raw data in the individual foot raw data sequence according to the data accuracy coefficient of each group of individual foot raw data, and dynamically adjust the foot scanning strategy according to the valid foot raw data.

[0011] Specifically, in S1, the calibration plate includes: 8 cubic blocks and an aluminum alloy middle plate, wherein 4 cubic blocks are adhered to the 4 vertex corners of the upper surface and the lower surface of the aluminum alloy middle plate; the four sides of each cubic block on the upper surface of the aluminum alloy middle plate are parallel to the four sides of the aluminum alloy middle plate; the four sides of each cubic block on the lower surface of the aluminum alloy middle plate are at an angle of 45 degrees to the four sides of the aluminum alloy middle plate;

[0012] The workbench of the foot inspection instrument includes: two rectangular glass panels of equal area and four cameras.

[0013] The rectangular glass panel is a foot measurement area, and a scanning device is arranged below it.

[0014] Specifically, in S1, the initial data calibration process specifically includes:

[0015] S11: placing the calibration plate on the workbench of the foot tester, and adjusting the four top corners of the alloy middle plate of the calibration plate to be parallel to the scales of the glass panels on the left and right sides of the workbench of the foot tester, and starting the initial data calibration process;

[0016] S12: Control the measurement reference lines of the two rectangular glass panels to move left and right, so that the two adjusted measurement reference lines coincide with the sharp corners of the four cube blocks on the lower surface of the aluminum alloy middle plate, wherein the measurement reference lines are parallel to the length of the rectangular glass panels and the length of the measurement reference lines is equal to the length of the rectangular glass panels;

[0017] S13: Control the viewpoint of the camera to move up and down, so that the adjusted viewpoint coincides with the center of the upper surface of the four cube blocks on the upper surface of the aluminum alloy middle plate.

[0018] Specifically, S2 includes the following specific steps:

[0019] S21: constructing a historical calibration data log according to the initial data calibration processing result, wherein the initial data calibration processing result includes: the distance movement of the measurement reference line and the angle movement of the viewpoint of the camera;

[0020] S22: Calculate the mechanical wear factor according to the initial data calibration processing result. The calculation strategy of the mechanical wear factor ms is:

[0021]

[0022] Among them, α 1 ,α 2 The mechanical wear contribution proportional coefficients are the distance movement and the angle movement respectively;

[0023] i is a subscript, indicating the i-th measurement reference line, l i is the distance movement of the i-th measurement baseline; is the mean distance movement in the historical calibration data log; L min ,L max They are the minimum and maximum distance movement values ​​in the historical calibration data log respectively;

[0024] j is the subscript, indicating the viewpoint of the jth camera; θ j is the angular movement of the viewpoint of the jth camera; is the average angular movement in the historical calibration data log; θ min ,θ max They are the minimum and maximum angular movement values ​​in the historical calibration data log respectively;

[0025] S23: Perform a first round of status verification on the working status of the foot tester according to the mechanical wear factor, the first round of status verification includes: presetting the maximum tolerable mechanical wear factor of the foot tester, comparing the mechanical wear factor of the initial data calibration processing result with the maximum tolerable mechanical wear factor of the foot tester, when the mechanical wear factor of the initial data calibration processing result is less than the maximum tolerable mechanical wear factor of the foot tester, it is judged that the foot tester has working conditions, and the foot tester is adjusted to the working mode, otherwise, the foot tester is manually calibrated by the staff.

[0026] Specifically, S3 includes the following specific steps:

[0027] S31: Debugging the foot detector to the foot scanning mode, scanning the user's foot multiple times within a standard scanning period, wherein the standard scanning period includes multiple data collection unit periods, and the duration of the data collection unit period is ten seconds;

[0028] S32: obtaining multiple groups of the user's personal foot raw data to form a personal foot raw data sequence, wherein the personal foot raw data includes: foot geometric parameter data, foot surface image data, foot temperature data and foot humidity data.

[0029] Specifically, in S4, the secondary round data verification strategy includes: a pressure fluctuation frequency verification strategy and an image pixel distortion verification strategy;

[0030] The pressure fluctuation frequency approval strategy specifically includes:

[0031] S41: evenly divide the measurement area of ​​the rectangular glass panel into pressure monitoring grids with an area of ​​1 cm×1 cm, wherein the total number of the pressure monitoring grids is U;

[0032] S42: extracting the pressure data on each pressure detection grid in the measurement area of ​​the rectangular glass panel within a single data acquisition unit period, and calculating the pressure fluctuation frequency value according to the pressure data. The pressure fluctuation frequency value p r,yl The calculation strategy is:

[0033]

[0034] Wherein, u is a subscript, indicating the u-th pressure monitoring grid;

[0035] r is a subscript, yl r (u),yl r-1 (u),yl r-2 (u) represents the pressure data of the u-th pressure monitoring grid in the r-th, r-1-th and r-2-th data collection unit time periods respectively.

[0036] Specifically, the image pixel distortion probability approval strategy includes:

[0037] S43: Capturing foot surface image data through various cameras, and obtaining a foot surface edge curve through an edge detection algorithm;

[0038] S44: Draw a tangent line and a perpendicular line to the tangent line for each pixel point on the foot surface edge curve, wherein the intersection point between the tangent line and the perpendicular line to the tangent line is the pixel point itself;

[0039] S45: extracting pixel values ​​of each pixel point on the foot edge curve, and calculating pixel distortion probability values ​​according to the pixel values, wherein the pixel distortion probability value q r,xs The calculation strategy is:

[0040]

[0041] Among them, h is a subscript, indicating the h-th frame of the foot surface image, and H is the total number of foot surface images captured by the camera during the r-th data acquisition unit period;

[0042] In the rth data collection unit period, xs r (h g ) represents the pixel value of the g-th pixel point on the foot surface edge curve of the foot surface image of the h-th frame;

[0043] h g,up1 Indicates the pixel point on the outside of the foot edge curve, in the area above the perpendicular line of the tangent line of the g-th pixel point, which is closest to the pixel value of the g-th pixel point; xs r (h g,up1 ) represents the pixel value of the pixel;

[0044] h g,down1 xs represents the pixel point closest to the pixel value of the g-th pixel in the area below the perpendicular line of the tangent line of the g-th pixel on the outside of the foot surface edge curve; r (h g,down1 ) represents the pixel value of the pixel;

[0045] h g,up2 Indicates the pixel point on the inner side of the edge curve of the foot surface, which is the pixel point closest to the pixel value of the g-th pixel point in the area above the perpendicular line of the tangent line of the g-th pixel point; xs r (h g,up2 ) represents the pixel value of the pixel;

[0046] h g,down2 Indicates the pixel point closest to the pixel value of the g-th pixel in the area below the perpendicular line of the tangent line of the g-th pixel point on the inner side of the edge curve of the foot surface; xs r (h g,down2 ) represents the pixel value of the pixel.

[0047] Specifically, in S4, the calculation strategy of the data accuracy coefficient K of each set of individual foot raw data includes:

[0048]

[0049] Where, e is the natural logarithm;

[0050] p0 and q0 are the standard values ​​of pressure fluctuation frequency and pixel distortion probability respectively.

[0051] Specifically, S5 includes the following specific steps:

[0052] S51: extracting the data accuracy coefficient of each group of individual foot raw data and presetting the data accuracy threshold;

[0053] S52: Filtering the individual foot raw data sequence, the individual foot raw data whose data accuracy coefficient is greater than the data accuracy threshold, to obtain valid foot raw data;

[0054] S53: dynamically adjusting the foot scanning strategy according to the valid foot raw data, specifically including: extracting the number of data groups of valid foot raw data in real time within a standard scanning period, when the number of data groups of valid foot raw data obtained within a standard scanning period is greater than or equal to 3, completing the foot scanning, otherwise, executing step S54:

[0055] S54: when the number of data sets of valid foot raw data acquired within a standard scanning period is less than 3, the duration of the current foot scanning is automatically extended by half of the standard scanning duration, and the process returns to step S52, and steps S52-S53 are re-executed;

[0056] If the number of data sets of valid raw foot data obtained after the foot scanning strategy is dynamically adjusted is greater than or equal to 3, the foot scan is completed. Otherwise, the staff is notified to manually guide the user to re-scan the foot.

[0057] In addition, the data processing system based on the foot tester calibration board of the present invention includes the following modules:

[0058] Initial data calibration module, first round status verification module, scanning data acquisition module, second round data verification module and scanning strategy adjustment module;

[0059] The initial data calibration module is used to start the foot tester and perform initial data calibration on the foot tester through the calibration board;

[0060] The first-round status verification module constructs a historical calibration data log according to the initial data calibration processing result, calculates the mechanical wear factor according to the historical calibration data log, and performs a first-round status verification on the working status of the foot detector according to the mechanical wear factor;

[0061] The scanning data acquisition module is used to adjust the foot detector to the foot scanning mode, scan the user's feet multiple times within a standard scanning period, obtain multiple groups of the user's personal foot raw data, and form a personal foot raw data sequence;

[0062] The secondary round data verification module is used to extract the multiple sets of personal foot raw data, import the multiple sets of personal foot raw data into the secondary round data verification strategy, and calculate the data accuracy coefficient of each set of personal foot raw data in real time;

[0063] The scanning strategy adjustment module screens valid foot raw data in the individual foot raw data sequence according to the data accuracy coefficient of each group of individual foot raw data, and dynamically adjusts the foot scanning strategy according to the valid foot raw data.

[0064] Compared with the prior art, the technical effects of the present invention are as follows:

[0065] 1. The present invention significantly improves the accuracy and stability of data calibration by introducing a dedicated systematic calibration board and combining it with an accurate initial data calibration processing method, reduces the frequency and human errors of traditional manual calibration, ensures the initial accuracy of the data, and can monitor and adjust the calibration data in real time after the equipment has been used for a long time, maintains the consistency of measurement accuracy, and thus improves the long-term stability of the data.

[0066] 2. By introducing an effective data verification strategy, the present invention can calculate the accuracy coefficient of each group of individual foot raw data in real time and screen out high-quality valid data, which greatly improves the accuracy and reliability of data processing and helps to improve the accuracy of subsequent analysis and diagnosis.

[0067] 3. The present invention realizes the automation of the whole process from data collection, processing to strategy adjustment. This highly automated mechanism not only improves the availability of the equipment and the user experience, but also reduces manual operation and human intervention, reduces the complexity and error rate of operation, and realizes efficient, accurate and reliable data processing.

[0068] 4. The present invention introduces real-time monitoring and adaptive adjustment mechanisms, so that the equipment can maintain the best state during long-term use, reducing the downtime for maintenance and upgrading. BRIEF DESCRIPTION OF THE DRAWINGS

[0069] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative labor.

[0070] in:

[0071] Figure 1 It is a flow chart of a data processing method based on a foot tester calibration board of the present invention;

[0072] Figure 2 It is a structural schematic diagram of a data processing system based on a foot tester calibration board of the present invention;

[0073] Figure 3 A schematic top view of a calibration plate of the present invention;

[0074] Figure 4 A schematic side view of a calibration plate of the present invention;

[0075] Figure 5 This is an exemplary diagram of a workbench of a foot testing instrument of the present invention. DETAILED DESCRIPTION

[0076] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0077] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0078] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0079] Embodiment 1:

[0080] like Figure 1 As shown, a data processing method based on a foot tester calibration board according to an embodiment of the present invention is as follows: Figure 1 As shown, the specific steps are as follows:

[0081] S1: Start the foot tester and perform initial data calibration on the foot tester through the calibration board;

[0082] like Figure 3 and Figure 4 As shown, in S1, the calibration plate includes: 8 cubic blocks and an aluminum alloy middle plate, wherein 4 cubic blocks are adhered to the 4 vertex corners of the upper surface and the lower surface of the aluminum alloy middle plate; the four sides of each cubic block on the upper surface of the aluminum alloy middle plate are parallel to the four sides of the aluminum alloy middle plate; the four sides of each cubic block on the lower surface of the aluminum alloy middle plate are at an angle of 45 degrees to the four sides of the aluminum alloy middle plate;

[0083] like Figure 5 As shown, the workbench of the foot inspection instrument includes: two rectangular glass panels of equal area and four cameras.

[0084] The rectangular glass panel is a foot measurement area, and a scanning device is arranged below it.

[0085] In S1, the initial data calibration process specifically includes:

[0086] S11: placing the calibration plate on the workbench of the foot tester, and adjusting the four top corners of the alloy middle plate of the calibration plate to be parallel to the scales of the glass panels on the left and right sides of the workbench of the foot tester, and starting the initial data calibration process;

[0087] S12: Control the measurement reference lines of the two rectangular glass panels to move left and right, so that the two adjusted measurement reference lines coincide with the sharp corners of the four cube blocks on the lower surface of the aluminum alloy middle plate, wherein the measurement reference lines are parallel to the length of the rectangular glass panels and the length of the measurement reference lines is equal to the length of the rectangular glass panels;

[0088] S13: Control the viewpoint of the camera to move up and down, so that the adjusted viewpoint coincides with the center of the upper surface of the four cube blocks on the upper surface of the aluminum alloy middle plate.

[0089] S2: Based on the initial data calibration processing results, a historical calibration data log is constructed, and the mechanical wear factor is calculated based on the historical calibration data log, and the first round of status verification of the working status of the foot detector is performed based on the mechanical wear factor;

[0090] S2 includes the following specific steps:

[0091] S21: constructing a historical calibration data log according to the initial data calibration processing result, wherein the initial data calibration processing result includes: the distance movement of the measurement reference line and the angle movement of the viewpoint of the camera;

[0092] S22: Calculate the mechanical wear factor according to the initial data calibration processing result. The calculation strategy of the mechanical wear factor ms is:

[0093]

[0094] Among them, α 1 ,α 2 The mechanical wear contribution proportional coefficients are the distance movement and the angle movement respectively;

[0095] i is a subscript, indicating the i-th measurement reference line, l i is the distance movement of the i-th measurement baseline; is the mean distance movement in the historical calibration data log; L min ,L max They are the minimum and maximum distance movement values ​​in the historical calibration data log respectively;

[0096] j is the subscript, indicating the viewpoint of the jth camera; θ j is the angular movement of the viewpoint of the jth camera; is the average angular movement in the historical calibration data log; θ min ,θ max They are the minimum and maximum angular movement values ​​in the historical calibration data log respectively;

[0097] S23: Perform a first round of status verification on the working status of the foot tester according to the mechanical wear factor, the first round of status verification includes: presetting the maximum tolerable mechanical wear factor of the foot tester, comparing the mechanical wear factor of the initial data calibration processing result with the maximum tolerable mechanical wear factor of the foot tester, when the mechanical wear factor of the initial data calibration processing result is less than the maximum tolerable mechanical wear factor of the foot tester, it is judged that the foot tester has working conditions, and the foot tester is adjusted to the working mode, otherwise, the foot tester is manually calibrated by the staff.

[0098] S3: Debugging the foot detector to the foot scanning mode, scanning the user's feet multiple times within a standard scanning period, obtaining multiple groups of the user's personal foot raw data, and forming a personal foot raw data sequence;

[0099] S3 includes the following specific steps:

[0100] S31: Debugging the foot detector to the foot scanning mode, scanning the user's foot multiple times within a standard scanning period, wherein the standard scanning period includes multiple data collection unit periods, and the duration of the data collection unit period is ten seconds;

[0101] S32: obtaining multiple groups of the user's personal foot raw data to form a personal foot raw data sequence, wherein the personal foot raw data includes: foot geometric parameter data, foot surface image data, foot temperature data and foot humidity data.

[0102] Exemplarily, in this embodiment, the foot geometric parameter data includes: foot length, foot width, arch height, toe length and toe width.

[0103] S4: extracting the multiple sets of original foot data of individuals, importing the multiple sets of original foot data of individuals into the second round of data verification strategy, and calculating the data accuracy coefficient of each set of original foot data of individuals in real time;

[0104] In S4, the secondary round data verification strategy includes: a pressure fluctuation frequency verification strategy and an image pixel distortion verification strategy;

[0105] The pressure fluctuation frequency approval strategy specifically includes:

[0106] S41: evenly divide the measurement area of ​​the rectangular glass panel into pressure monitoring grids with an area of ​​1 cm×1 cm, wherein the total number of the pressure monitoring grids is U;

[0107] S42: extracting the pressure data on each pressure detection grid in the measurement area of ​​the rectangular glass panel within a single data acquisition unit period, and calculating the pressure fluctuation frequency value according to the pressure data. The pressure fluctuation frequency value p r,yl The calculation strategy is:

[0108]

[0109] Wherein, u is a subscript, indicating the u-th pressure monitoring grid;

[0110] r is a subscript, yl r (u),yl r-1 (u),yl r-2 (u) represents the pressure data of the u-th pressure monitoring grid in the r-th, r-1-th and r-2-th data collection unit time periods respectively.

[0111] The image pixel distortion probability approval strategy includes:

[0112] S43: Capturing foot surface image data through various cameras, and obtaining a foot surface edge curve through an edge detection algorithm;

[0113] S44: Draw a tangent line and a perpendicular line to the tangent line for each pixel point on the foot surface edge curve, wherein the intersection point between the tangent line and the perpendicular line to the tangent line is the pixel point itself;

[0114] S45: extracting pixel values ​​of each pixel point on the foot edge curve, and calculating pixel distortion probability values ​​according to the pixel values, wherein the pixel distortion probability value q r,xs The calculation strategy is:

[0115]

[0116] Among them, h is a subscript, indicating the h-th frame of the foot surface image, and H is the total number of foot surface images captured by the camera during the r-th data acquisition unit period;

[0117] In the rth data collection unit period, xs r (h g ) represents the pixel value of the g-th pixel point on the foot surface edge curve of the foot surface image of the h-th frame;

[0118] h g,up1 Indicates the pixel point on the outside of the foot edge curve, in the area above the perpendicular line of the tangent line of the g-th pixel point, which is closest to the pixel value of the g-th pixel point; xs r (h g,up1 ) represents the pixel value of the pixel;

[0119] h g,down1xs represents the pixel point closest to the pixel value of the g-th pixel in the area below the perpendicular line of the tangent line of the g-th pixel on the outside of the foot surface edge curve; r (h g,down1 ) represents the pixel value of the pixel;

[0120] h g,up2 Indicates the pixel point on the inner side of the edge curve of the foot surface, which is the pixel point closest to the pixel value of the g-th pixel point in the area above the perpendicular line of the tangent line of the g-th pixel point; xs r (h g,up2 ) represents the pixel value of the pixel;

[0121] h g,down2 Indicates the pixel point closest to the pixel value of the g-th pixel in the area below the perpendicular line of the tangent line of the g-th pixel point on the inner side of the edge curve of the foot surface; xs r (h g,down2 ) represents the pixel value of the pixel.

[0122] In S4, the calculation strategy of the data accuracy coefficient K of each set of individual foot raw data includes:

[0123]

[0124] Where, e is the natural logarithm;

[0125] p0 and q0 are the standard values ​​of pressure fluctuation frequency and pixel distortion probability respectively.

[0126] S5: Filter valid foot raw data in the individual foot raw data sequence according to the data accuracy coefficient of each group of individual foot raw data, and dynamically adjust the foot scanning strategy according to the valid foot raw data.

[0127] S5 includes the following specific steps:

[0128] S51: extracting the data accuracy coefficient of each group of individual foot raw data and presetting the data accuracy threshold;

[0129] S52: Filtering the individual foot raw data sequence, the individual foot raw data whose data accuracy coefficient is greater than the data accuracy threshold, to obtain valid foot raw data;

[0130] S53: dynamically adjusting the foot scanning strategy according to the valid foot raw data, specifically including: extracting the number of data groups of valid foot raw data in real time within a standard scanning period, when the number of data groups of valid foot raw data obtained within a standard scanning period is greater than or equal to 3, completing the foot scanning, otherwise, executing step S54:

[0131] S54: when the number of data sets of valid foot raw data acquired within a standard scanning period is less than 3, the duration of the current foot scanning is automatically extended by half of the standard scanning duration, and the process returns to step S52, and steps S52-S53 are re-executed;

[0132] If the number of data sets of valid raw foot data obtained after the foot scanning strategy is dynamically adjusted is greater than or equal to 3, the foot scan is completed. Otherwise, the staff is notified to manually guide the user to re-scan the foot.

[0133] Embodiment 2:

[0134] like Figure 2 As shown, a data processing system based on a foot tester calibration board according to an embodiment of the present invention is as follows: Figure 2 As shown, it includes the following modules:

[0135] Initial data calibration module, first round status verification module, scanning data acquisition module, second round data verification module and scanning strategy adjustment module;

[0136] The initial data calibration module is used to start the foot tester and perform initial data calibration on the foot tester through the calibration board;

[0137] The first-round status verification module constructs a historical calibration data log according to the initial data calibration processing result, calculates the mechanical wear factor according to the historical calibration data log, and performs a first-round status verification on the working status of the foot detector according to the mechanical wear factor;

[0138] The scanning data acquisition module is used to adjust the foot detector to the foot scanning mode, scan the user's feet multiple times within a standard scanning period, obtain multiple groups of the user's personal foot raw data, and form a personal foot raw data sequence;

[0139] The secondary round data verification module is used to extract the multiple sets of personal foot raw data, import the multiple sets of personal foot raw data into the secondary round data verification strategy, and calculate the data accuracy coefficient of each set of personal foot raw data in real time;

[0140] The scanning strategy adjustment module screens valid foot raw data in the individual foot raw data sequence according to the data accuracy coefficient of each group of individual foot raw data, and dynamically adjusts the foot scanning strategy according to the valid foot raw data.

[0141] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present invention can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0142] In summary, compared with the prior art, the technical effects of the present invention are as follows:

[0143] 1. The present invention significantly improves the accuracy and stability of data calibration by introducing a dedicated systematic calibration board and combining it with an accurate initial data calibration processing method, reduces the frequency and human errors of traditional manual calibration, ensures the initial accuracy of the data, and can monitor and adjust the calibration data in real time after the equipment has been used for a long time, maintains the consistency of measurement accuracy, and thus improves the long-term stability of the data.

[0144] 2. By introducing an effective data verification strategy, the present invention can calculate the accuracy coefficient of each group of individual foot raw data in real time and screen out high-quality valid data, which greatly improves the accuracy and reliability of data processing and helps to improve the accuracy of subsequent analysis and diagnosis.

[0145] 3. The present invention realizes the automation of the whole process from data collection, processing to strategy adjustment. This highly automated mechanism not only improves the availability of the equipment and the user experience, but also reduces manual operation and human intervention, reduces the complexity and error rate of operation, and realizes efficient, accurate and reliable data processing.

[0146] 4. The present invention introduces real-time monitoring and adaptive adjustment mechanisms, so that the equipment can maintain the best state during long-term use, reducing the downtime for maintenance and upgrading.

[0147] The above shows and describes the basic principles and main features of the present invention and the advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention to be protected. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A data processing method based on a foot tester calibration plate, characterized in that: The method comprises the following specific steps: S1: Start the foot tester and perform initial data calibration on the foot tester through the calibration board; S2: Based on the initial data calibration processing results, a historical calibration data log is constructed, and the mechanical wear factor is calculated based on the historical calibration data log, and the first round of status verification of the working status of the foot detector is performed based on the mechanical wear factor; S3: Debugging the foot detector to the foot scanning mode, scanning the user's feet multiple times within a standard scanning period, obtaining multiple groups of the user's personal foot raw data, and forming a personal foot raw data sequence; S4: extracting the multiple sets of original foot data of individuals, importing the multiple sets of original foot data of individuals into the second round of data verification strategy, and calculating the data accuracy coefficient of each set of original foot data of individuals in real time; S5: Filter valid foot raw data in the individual foot raw data sequence according to the data accuracy coefficient of each group of individual foot raw data, and dynamically adjust the foot scanning strategy according to the valid foot raw data.

2. The data processing method based on the foot tester calibration plate according to claim 1 is characterized in that: In S1, the calibration plate includes: 8 cubic blocks and an aluminum alloy middle plate, wherein 4 cubic blocks are adhered to the 4 vertex corners of the upper surface and the lower surface of the aluminum alloy middle plate; the four sides of each cubic block on the upper surface of the aluminum alloy middle plate are parallel to the four sides of the aluminum alloy middle plate; the four sides of each cubic block on the lower surface of the aluminum alloy middle plate are at an angle of 45 degrees to the four sides of the aluminum alloy middle plate; The workbench of the foot inspection instrument includes: two rectangular glass panels of equal area and four cameras.

3. The data processing method based on the foot tester calibration plate according to claim 2 is characterized in that: In S1, the initial data calibration process specifically includes: S11: placing the calibration plate on the workbench of the foot tester, and adjusting the four top corners of the alloy middle plate of the calibration plate to be parallel to the scales of the glass panels on the left and right sides of the workbench of the foot tester, and starting the initial data calibration process; S12: Control the measurement reference lines of the two rectangular glass panels to move left and right, so that the two adjusted measurement reference lines coincide with the sharp corners of the four cube blocks on the lower surface of the aluminum alloy middle plate, wherein the measurement reference lines are parallel to the length of the rectangular glass panels and the length of the measurement reference lines is equal to the length of the rectangular glass panels; S13: Control the viewpoint of the camera to move up and down, so that the adjusted viewpoint coincides with the center of the upper surface of the four cube blocks on the upper surface of the aluminum alloy middle plate.

4. The data processing method based on the foot tester calibration plate according to claim 3 is characterized in that: S2 includes the following specific steps: S21: constructing a historical calibration data log according to the initial data calibration processing result, wherein the initial data calibration processing result includes: the distance movement of the measurement reference line and the angle movement of the viewpoint of the camera; S22: Calculate the mechanical wear factor according to the initial data calibration processing result. The calculation strategy of the mechanical wear factor ms is: Among them, α1 and α2 are the mechanical wear contribution coefficients of distance movement and angle movement respectively; i is a subscript, indicating the i-th measurement reference line, l i is the distance movement of the i-th measurement baseline; L is the mean distance movement in the historical calibration data log; L min ,L max They are the minimum and maximum distance movement values ​​in the historical calibration data log respectively; j is the subscript, indicating the viewpoint of the jth camera; θ j is the angular movement of the viewpoint of the jth camera; θ is the mean angular movement in the historical calibration data log; θ min ,θ max They are the minimum and maximum angular movement values ​​in the historical calibration data log respectively; S23: Perform a first round of status verification on the working status of the foot tester according to the mechanical wear factor, the first round of status verification includes: presetting the maximum tolerable mechanical wear factor of the foot tester, comparing the mechanical wear factor of the initial data calibration processing result with the maximum tolerable mechanical wear factor of the foot tester, when the mechanical wear factor of the initial data calibration processing result is less than the maximum tolerable mechanical wear factor of the foot tester, it is judged that the foot tester has working conditions, and the foot tester is adjusted to the working mode, otherwise, the foot tester is manually calibrated by the staff.

5. The data processing method based on the foot tester calibration plate according to claim 4 is characterized in that: S3 includes the following specific steps: S31: Debugging the foot detector to the foot scanning mode, scanning the user's foot multiple times within a standard scanning period, wherein the standard scanning period includes multiple data collection unit periods, and the duration of the data collection unit period is ten seconds; S32: obtaining multiple sets of the user's personal foot raw data to form a personal foot raw data sequence, wherein the personal foot raw data includes: foot geometric parameter data, foot surface image data, foot temperature data and foot humidity data.

6. The data processing method based on the foot tester calibration plate according to claim 5 is characterized in that: In S4, the secondary round data verification strategy includes: a pressure fluctuation frequency verification strategy and an image pixel distortion verification strategy; The pressure fluctuation frequency approval strategy specifically includes: S41: evenly divide the measurement area of ​​the rectangular glass panel into pressure monitoring grids with an area of ​​1 cm×1 cm, wherein the total number of the pressure monitoring grids is U; S42: extracting the pressure data on each pressure detection grid in the measurement area of ​​the rectangular glass panel within a single data acquisition unit period, and calculating the pressure fluctuation frequency value according to the pressure data. The pressure fluctuation frequency value p r,yl The calculation strategy is: Wherein, u is a subscript, indicating the u-th pressure monitoring grid; r is a subscript, yl r (u),yl r-1 (u),yl r-2 (u) represents the pressure data of the u-th pressure monitoring grid in the r-th, r-1-th and r-2-th data collection unit time periods respectively.

7. The data processing method based on the foot tester calibration plate according to claim 6 is characterized in that: The image pixel distortion probability approval strategy includes: S43: Capturing foot surface image data through various cameras, and obtaining a foot surface edge curve through an edge detection algorithm; S44: Draw a tangent line and a perpendicular line to the tangent line for each pixel point on the foot surface edge curve, wherein the intersection point between the tangent line and the perpendicular line to the tangent line is the pixel point itself; S45: extracting pixel values ​​of each pixel point on the foot edge curve, and calculating pixel distortion probability values ​​according to the pixel values, wherein the pixel distortion probability value q r,xs The calculation strategy is: Among them, h is a subscript, indicating the h-th frame of the foot surface image, and H is the total number of foot surface images captured by the camera during the r-th data acquisition unit period; In the rth data collection unit period, xs r (h g ) represents the pixel value of the g-th pixel on the foot surface edge curve of the foot surface image of the h-th frame; h g,up1 Indicates the pixel point on the outside of the foot edge curve, in the area above the perpendicular line of the tangent line of the g-th pixel point, which is closest to the pixel value of the g-th pixel point; xs r (h g,up1 ) represents the pixel value of the pixel; h g,down1 xs represents the pixel point closest to the pixel value of the g-th pixel in the area below the perpendicular line of the tangent line of the g-th pixel on the outside of the foot surface edge curve; r (h g,down1 ) represents the pixel value of the pixel; h g,up2 Indicates the pixel point on the inner side of the edge curve of the foot surface, which is the pixel point closest to the pixel value of the g-th pixel point in the area above the perpendicular line of the tangent line of the g-th pixel point; xs r (h g,up2 ) represents the pixel value of the pixel; h g,down2 Indicates the pixel point closest to the pixel value of the g-th pixel in the area below the perpendicular line of the tangent line of the g-th pixel point on the inner side of the edge curve of the foot surface; xs r (h g,down2 ) represents the pixel value of the pixel.

8. The data processing method based on the foot tester calibration plate according to claim 7 is characterized in that: In S4, the calculation strategy of the data accuracy coefficient K of each set of individual foot raw data includes: Where, e is the natural logarithm; p0 and q0 are the standard values ​​of pressure fluctuation frequency and pixel distortion probability respectively.

9. The data processing method based on the foot tester calibration plate according to claim 8 is characterized in that: S5 includes the following specific steps: S51: extracting the data accuracy coefficient of each group of individual foot raw data and presetting the data accuracy threshold; S52: Filtering the individual foot raw data sequence, the individual foot raw data whose data accuracy coefficient is greater than the data accuracy threshold, to obtain valid foot raw data; S53: dynamically adjusting the foot scanning strategy according to the valid foot raw data, specifically including: extracting the number of data groups of valid foot raw data in real time within a standard scanning period, when the number of data groups of valid foot raw data obtained within a standard scanning period is greater than or equal to 3, completing the foot scanning, otherwise, executing step S54: S54: when the number of data sets of valid foot raw data acquired within a standard scanning period is less than 3, the duration of the current foot scanning is automatically extended by half of the standard scanning duration, and the process returns to step S52, and steps S52-S53 are re-executed; If the number of data sets of valid raw foot data obtained after the foot scanning strategy is dynamically adjusted is greater than or equal to 3, the foot scan is completed. Otherwise, the staff is notified to manually guide the user to re-scan the foot.

10. A data processing system based on a foot tester calibration board, used to implement a data processing method based on a foot tester calibration board as claimed in any one of claims 1 to 9, characterized in that: The system includes the following modules: Initial data calibration module, first round status verification module, scanning data acquisition module, second round data verification module and scanning strategy adjustment module; The initial data calibration module is used to start the foot tester and perform initial data calibration on the foot tester through the calibration board; The first-round status verification module constructs a historical calibration data log according to the initial data calibration processing result, calculates the mechanical wear factor according to the historical calibration data log, and performs a first-round status verification on the working status of the foot detector according to the mechanical wear factor; The scanning data acquisition module is used to adjust the foot detector to the foot scanning mode, scan the user's feet multiple times within a standard scanning period, obtain multiple groups of the user's personal foot raw data, and form a personal foot raw data sequence; The secondary round data verification module is used to extract the multiple sets of personal foot raw data, import the multiple sets of personal foot raw data into the secondary round data verification strategy, and calculate the data accuracy coefficient of each set of personal foot raw data in real time; The scanning strategy adjustment module screens valid foot raw data in the individual foot raw data sequence according to the data accuracy coefficient of each group of individual foot raw data, and dynamically adjusts the foot scanning strategy according to the valid foot raw data.

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