An automated bioceramic production monitoring system based on machine vision

Abstract

The application provides an automatic biological ceramic production monitoring system based on machine vision, compared with the prior art, the automatic biological ceramic production monitoring system comprises a camera device for acquiring images of biological ceramics in a furnace through an observation window, a monitoring module for receiving images shot by the camera device to judge the firing condition of the biological ceramics in the furnace, and a receiving module for receiving the biological ceramics fired in the furnace, the system combines image processing, automatic judgment and real-time monitoring and other technologies, effectively monitors and analyzes the change of the shape structure of the biological ceramics in the firing process, and makes the biological ceramic production process more stable and efficient.

Description

Technical Field

[0001] This invention relates to the field of production monitoring technology, and in particular to an automated bioceramic production monitoring system based on machine vision. Background Technology

[0002] Bioceramics are ceramic materials used in medical and biological applications, commonly used to create medical implants such as artificial bones and teeth. Their preparation technology involves material selection, preparation methods, and surface treatment. The ceramic green body needs to be sintered at high temperatures to achieve tighter particle bonding and obtain the desired mechanical properties and biocompatibility. The sintering temperature and duration affect the ceramic's properties. Furthermore, heat treatment can also be used to improve the mechanical properties and microstructure of the ceramic. The production process of bioceramics requires rigorous testing and quality control to ensure product performance and safety. Common testing methods include mechanical property testing, biocompatibility testing, and microstructure analysis.

[0003] Our research team has long been reviewing and studying a large amount of relevant data on bioceramic production technologies. Utilizing relevant resources and conducting numerous experiments, we discovered existing technologies such as those disclosed in CN115022379B, CN107848141B, CN113200293B, and CN112393583B. One such technology is a ceramic production management system based on a 5G cloud platform, belonging to the field of factory equipment management technology. This system includes a production monitoring module, a 5G base station, a 5G cloud platform, a data transmission module, and a remote terminal module. The 5G cloud platform is used to monitor the ceramic production process. The system analyzes and manages the data information during the process and sends the received control information to the production monitoring module. The remote terminal module is used by the user to send real-time control information to the 5G cloud platform. This invention achieves network connectivity of the data acquisition terminal unit by embedding a 5G gateway unit in the data acquisition terminal unit, which includes multiple robots, cameras installed on the production site, and multiple environmental sensors. The data is then sent to the 5G cloud platform for data management. Equipment operators can remotely obtain panoramic high-definition video images of the production site and related equipment data in real time through the 5G network, and achieve real-time and precise control of related equipment on site, effectively ensuring that control commands are executed quickly, accurately, and reliably.

[0004] This invention was made to address the common problem in the field that the sintering process of bioceramics cannot be monitored in real time to observe the quality of bioceramics. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of current practices in this field by proposing an automated bioceramic production monitoring system based on machine vision.

[0006] To overcome the shortcomings of the prior art, the present invention adopts the following technical solution:

[0007] An automated bioceramic production monitoring system based on machine vision is disclosed. The bioceramic production system includes a furnace for firing bioceramics and an observation window installed on the furnace for observing the internal combustion chamber. The monitoring system includes a camera device for acquiring images of the bioceramics inside the furnace through the observation window, a monitoring module for receiving the images captured by the camera device to determine the firing status of the bioceramics inside the furnace, and a receiving module for receiving the completed bioceramics inside the furnace.

[0008] The camera device monitors the situation inside the observation window at a preset angle via a fixed bracket. The monitoring module includes a preliminary processing unit for processing and analyzing the first image captured by the camera device during the furnace operation, and a follow-up processing unit for processing and analyzing the second image captured by the camera device during the furnace operation and subsequent acquired images.

[0009] The receiving module includes a base, a moving drive mechanism that drives the base to move on the ground along a preset path, and a gripping unit stacked on the base for gripping and transferring bioceramics inside the furnace.

[0010] Furthermore, the initial processing unit performs the task through the following steps:

[0011] S101: The first image of the bioceramics inside the furnace acquired by the camera device is used as the initial image.

[0012] S102: Perform denoising, image enhancement, and grayscale processing on the initial image to further obtain a pre-processed image of preset specifications.

[0013] S103: Identify bioceramic regions in the initial processed image:

[0014] s1031: Divide the initial processed image into L first sub-images, and calculate the mean value of the pixel gray levels in each first sub-image. Use the mean value of the pixel gray levels of the first sub-image as the representative value of the first sub-image. The first sub-images are sequentially represented as IMAGE1, IMAGE2, IMAGEx…IMAGEL, and the representative values ​​of each first sub-image are sequentially represented as REVA1, REVA2, REVAx…REVAL, x=1,2,3……L; where REVAx is the representative value of IMAGEx.

[0015] s1032: Correct the reference values ​​within each first sub-graphic in the initial processed image. Taking IMAGEx as an example, correct the reference values ​​of IMAGEx to obtain the calibration reference value CALIVx for IMAGEx.

[0016] CALIVx = INT(REVAx), where INT(REVAx) is the Gaussian integer operation on REVAx.

[0017] s1033: Obtain the first sub-graphic distribution value IDV in the initial processed image.

[0018] Where Max is the maximum value of the calibration reference value in the first sub-image of the initial processed image, Min is the maximum value of the calibration reference value in the first sub-image of the initial processed image, RE1 is the preset minimum difference reference value, and RE2 is the preset maximum difference reference value.

[0019] s1034: Obtain the image pixel grayscale value Disth: Disth = Refe + IDV × α β ,

[0020] Where Refe is a pre-set standard division value, α is the difference correction coefficient positively correlated with IDV, and β is the priority correlation parameter of the difference correction coefficient.

[0021] s1035: The initial processed image is subjected to threshold differentiation to obtain the initial differentiated image, denoted by F(x) as the pixel gray value of the x-th first sub-graphic in the initial processed image in the initial differentiated image:

[0022]

[0023] s1036: The first sub-graphics in the initial processed image are identified sequentially. The graphic with a pixel gray value of 0 is identified as a bioceramic region. The graphic in the initial differentiated image where each pixel gray value of 0 simultaneously forms a closed image is a tracking image of a bioceramic. The center pixel coordinates of each tracking image are obtained as tracking coordinates, thereby obtaining the same number of tracking coordinates as the number of bioceramics in the furnace.

[0024] Furthermore, each gripping unit includes a horizontally arranged base plate, a horizontally arranged top plate above the base plate, at least two lifting drive rods with their bottoms fixed to the base plate and their tops fixed to the top plate, a groove in the upper wall of the base plate, a rotating platform embedded in the groove, a rubber pad on the rotating platform, a robotic arm fixed to the base plate by a fixing seat, and an adaptive gripping mechanism fixed to the top of the robotic arm.

[0025] Furthermore, the adaptive clamping mechanism includes a shell with a plate-like structure and an internal cavity, a communication port on the shell, adsorption holes distributed on the bottom wall of the shell, a negative pressure motor fixed on the base plate, an adsorption tube with one end connected to the negative pressure port of the negative pressure motor and the other end connected to the communication port, multiple pipes located in the cavity of the shell, with one branch pipe connected to the communication port and the remaining branch pipes connected to the other adsorption holes in sequence, a miniature electronic control valve for controlling the closing of each adsorption hole, rubber nozzles connected in sequence to each adsorption hole, and several clamping members that are rotatably fitted to the side edge of the shell, wherein each adaptive clamping mechanism includes at least two clamping members.

[0026] Furthermore, each of the clamping components includes a drive port disposed on the side wall of the housing, a drive gear rotatably fixed inside the housing via a rotating shaft and at least partially extending through the drive port, a mating roller rotatably fixed outside the housing via a rotating shaft seat, a driven gear sleeved in the middle of the mating roller for meshing with the drive gear, an arc-shaped clamping plate, a rubber pad laid on the plate wall of the clamping plate, and at least two connecting rods, each fixed at one end to the roller wall of the mating roller and at the other end to the clamping plate.

[0027] The beneficial effects achieved by this invention are:

[0028] 1. The present invention analyzes and processes images captured by a camera device at different stages, including initial and subsequent images, thereby improving the system's adaptability and accuracy. By tracking the acquisition of coordinates, it facilitates further analysis and processing of subsequent acquisitions, enabling real-time monitoring of shape changes during the firing process of bioceramics and automatically determining the integrity of the shape and structure of bioceramics during firing, thus avoiding the tedious process of manual inspection.

[0029] 2. The system of the present invention analyzes and processes images captured by a camera device at different stages, including initial images and subsequently acquired images, thereby improving the adaptability and accuracy of the system. By acquiring tracking coordinates, it is convenient to further analyze and process the subsequently acquired images, thereby enabling real-time monitoring of shape changes during the firing process of bioceramics and automatically judging the shape and structural integrity of bioceramics during the firing process, avoiding the tedious process of manual inspection.

[0030] 3. The receiving module adopts an automated operation process. Through components such as a moving drive mechanism, robotic arm, and gripping unit, it realizes automatic gripping, transfer, and receiving of bioceramics. The gripping unit is designed with gripping, rotation, and adsorption functions, which can adapt to the gripping and receiving needs of bioceramics under different conditions. Through the overlapping and connected gripping units, the receiving module can grip and transfer multiple bioceramics at the same time, enabling the receiving module to complete the receiving and transfer of a large number of bioceramics in a short time. Automated operation reduces human intervention, reduces operational risks and errors, improves work safety, and improves the production efficiency of bioceramics. Attached Figure Description

[0031] The invention will be further understood from the following description taken in conjunction with the accompanying drawings. The components in the drawings are not necessarily drawn to scale, but rather the emphasis is on illustrating the principles of the embodiments. In different views, the same reference numerals designate corresponding parts.

[0032] Figure 1 This is a modular schematic diagram of the automated bioceramic production monitoring system based on machine vision according to the present invention.

[0033] Figure 2 This is a partial structural diagram of the receiving module of the present invention.

[0034] Figure 3 This is a schematic diagram of one part of the clamping unit of the present invention.

[0035] Figure 4 This is a schematic diagram of another part of the clamping unit of the present invention.

[0036] Figure 5 This is a partial structural schematic diagram of the adaptive clamping mechanism of the present invention.

[0037] Explanation of reference numerals: 1-Clamping unit; 2-Base; 3-Moving drive mechanism; 4-Groove; 5-Rotating table; 6-Base plate; 7-Lifting drive rod; 8-Top plate; 9-Working wall; 10-Mechanical arm; 11-Adaptive clamping mechanism; 12-Matching roller; 13-Housing shell; 14-Rotating shaft seat; 15-Connecting rod; 16-Drive gear; 17-Drive port; 18-; 19-Rotating shaft; 20-Passive gear; 21-Clamping plate. Detailed Implementation

[0038] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to its embodiments. It should be noted that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of this invention. Other systems, methods, and / or features of this embodiment will become apparent to those skilled in the art after reviewing the following detailed description. Furthermore, the terminology used to describe positional relationships in the accompanying drawings is for illustrative purposes only and should not be construed as limiting this patent. Those skilled in the art can understand the specific meaning of the above terms according to the specific circumstances.

[0039] Example 1: Combined with Appendix Figure 1 Appendix Figure 2 Appendix Figure 3 Appendix Figure 4 and attached Figure 5 This embodiment constructs an automated bioceramic production monitoring system based on machine vision. The bioceramic production system includes a furnace for firing bioceramics and an observation window installed on the furnace for observing the internal combustion chamber. The bioceramic production monitoring system includes a camera device for acquiring images of the bioceramics inside the furnace through the observation window, a monitoring module for receiving the images captured by the camera device to determine the firing status of the bioceramics inside the furnace, and a receiving module for receiving the bioceramics that have been fired in the furnace.

[0040] The camera device monitors the situation inside the observation window at a preset angle via a fixed frame. The monitoring module is used to determine the integrity of the shape and structure of the bioceramic during the firing process. The monitoring module includes a preliminary processing unit for processing and analyzing the first image captured by the camera device during the firing operation, and a follow-up processing unit for processing and analyzing the second image captured by the camera device during the firing operation and subsequent acquired images.

[0041] The initial processing unit performs the task through the following steps:

[0042] S101: The first image of the bioceramics inside the furnace acquired by the camera device is used as the initial image.

[0043] S102: Perform denoising, image enhancement, and grayscale processing on the initial image to further obtain a pre-processed image of preset specifications.

[0044] S103: Identify bioceramic regions in the initial processed image:

[0045] s1031: Divide the initial processed image into L first sub-images, and calculate the mean value of the pixel gray levels in each first sub-image. Use the mean value of the pixel gray levels of the first sub-image as the representative value of the first sub-image. The first sub-images are sequentially represented as IMAGE1, IMAGE2, IMAGEx…IMAGEL, and the representative values ​​of each first sub-image are sequentially represented as REVA1, REVA2, REVAx…REVAL, x=1,2,3……L; where REVAx is the representative value of IMAGEx.

[0046] s1032: Correct the reference values ​​within each first sub-graphic in the initial processed image. Taking IMAGEx as an example, correct the reference values ​​of IMAGEx to obtain the calibration reference value CALIVx for IMAGEx.

[0047] CALIVx = INT(REVAx), where INT(REVAx) is the Gaussian integer operation on REVAx.

[0048] s1033: Obtain the first sub-graphic distribution value IDV in the initial processed image.

[0049] Where Max is the maximum value of the calibration reference value in the first sub-image of the initial processed image, Min is the maximum value of the calibration reference value in the first sub-image of the initial processed image, RE1 is the preset minimum difference reference value, and RE2 is the preset maximum difference reference value.

[0050] s1034: Obtain the image pixel grayscale value Disth: Disth = Refe + IDV × α β ,

[0051] Where Refe is a pre-set standard division value, α is a difference correction coefficient positively correlated with IDV, and β is a priority-related parameter of the difference correction coefficient. Refe, RE1, RE2, α, and β are obtained by those skilled in the art based on historical experience, extensive repeated experimental training, and optimization training, and will not be elaborated here.

[0052] s1035: The initial processed image is subjected to threshold differentiation to obtain the initial differentiated image, denoted by F(x) as the pixel gray value of the x-th first sub-graphic in the initial processed image in the initial differentiated image:

[0053]

[0054] s1036: The first sub-graphics in the initial processed image are identified sequentially. The graphic with a pixel gray value of 0 is identified as a bioceramic region. The graphic in the initial differentiated image where each pixel gray value of 0 simultaneously forms a closed image is a tracking image of a bioceramic. The center pixel coordinates of each tracking image are obtained as tracking coordinates, and then the number of tracking coordinates is the same as the number of bioceramics in the furnace.

[0055] The present invention provides a system that analyzes images captured by a camera device and processes images acquired at different stages of the camera device, including initial images and subsequently acquired images, thereby improving the system's adaptability and accuracy. By acquiring tracking coordinates, it is convenient to further analyze and process the subsequently acquired images, thereby enabling real-time monitoring of shape changes during the firing process of bioceramics and automatically judging the shape and structural integrity of bioceramics during the firing process, avoiding the tedious process of manual inspection.

[0056] Example 2: Combined with Appendix Figure 1 Appendix Figure 2 Appendix Figure 3 Appendix Figure 4 and attached Figure 5 In addition to the content included in the above embodiments, the continuing processing unit performs the operation through the following steps:

[0057] s201: Subsequent images are those acquired by the camera device after the initial image.

[0058] s202: Subsequent images are subjected to denoising, image enhancement, and grayscale processing to obtain further processed images of preset specifications.

[0059] s203: Identify bioceramic regions in the subsequently processed image:

[0060] s2031: Divide the subsequent processed image into L second sub-images, and calculate the mean value of the pixel gray levels in each second sub-image. Use the mean value of the pixel gray levels of the second sub-image as the representative value of the second sub-image. The second sub-images are sequentially represented as PT1, PT2, PTx...PTL, and the representative values ​​of each second sub-image are sequentially represented as GY1, GY2, GYx...GYL, x = 1, 2, 3...L; where GYx is the representative value of PTx.

[0061] s2032: The subsequent processed image is subjected to threshold differentiation to obtain a further differentiated image, where f(x) represents the pixel grayscale value of the x-th second sub-graphic in the further processed image in the further differentiated image.

[0062]

[0063] s204: Identify and mark the position of each tracking coordinate in the processed image. For each tracking coordinate in the processed image, select the closed image with a grayscale value of 0 that is closest to the tracking coordinate within a preset range as the identification image, and calculate the area of ​​the identification image.

[0064] S205: From the continuously acquired processed images, the recognition images acquired sequentially under the same tracking coordinate are denoted as IDEN1, IDEN2, IDEN1…IDENn, and the acquisition times corresponding to the recognition images are T1, T2, Ti…Tn, i = 1, 2, 3…n, where n is a positive integer. Spline interpolation is used to fit the curve of the area change of the recognition images acquired sequentially under the same tracking coordinate with time, and the interpolation function Y(T) is obtained. Taking the recognition image acquired at the current time as IDENr and the current acquisition time as Tr, the area change rate Roc(Tr) of the continuously acquired recognition images under the same tracking coordinate at the current moment is calculated:

[0065] Roc(Tr)=|Y(T) / dt|,Tr-μ≤T≤Tr

[0066] Where μ is the preset monitoring time value, Y(T) / dt represents the first derivative of the interpolation function Y(T), that is, the derivative of the interpolation function with respect to time T, and Roc(Tr) represents the absolute value of the first derivative of the continuously acquired recognition images under the same tracking coordinates in the time zone [Tr-μ, Tr], and also represents the rate of area change of the continuously acquired recognition images under the same tracking coordinates at the current moment.

[0067] S206: The volume change trend of bioceramics during the furnace firing process is determined based on the real-time calculated rate of change of the recognized image area, Roc(Tr).

[0068] S207: When Roc(Tr) is greater than the preset comparison threshold, determine that the bioceramic firing in the corresponding recognition image has failed.

[0069] S208: Record the bioceramic detection results in each identified image into the database for staff to track and analyze the quality of bioceramic products;

[0070] This invention enables real-time and continuous monitoring of changes during the bioceramic firing process through continuous acquisition and analysis of subsequent images. This helps to identify potential problems earlier. By identifying and marking the tracking coordinates in the processed images, the system can determine the specific location of the bioceramic and further analyze it. Furthermore, it can promptly determine the firing failure of bioceramic by observing abnormal trends in the area changes of different bioceramic images. By recording the bioceramic detection results in each identified image into a database, this helps staff track, analyze, and review the quality of bioceramic products to further improve the production process.

[0071] Example 3: Combined with Appendix Figure 1 Appendix Figure 2 Appendix Figure 3 Appendix Figure 4 and attached Figure 5 In addition to the contents of the above embodiments, the receiving module also includes a base, a moving drive mechanism for driving the base to move on the ground along a preset path, and a gripping unit for clamping and transferring bioceramics inside the furnace, which is stacked sequentially on the base.

[0072] Each gripping unit includes a horizontally positioned base plate, a horizontally positioned top plate above the base plate, at least two lifting drive rods with their bottoms fixed to the base plate and their tops fixed to the top plate, a groove in the upper wall of the base plate, a rotating platform embedded in the groove, a rubber pad on the rotating platform, a robotic arm fixed to the base plate by a fixing seat, and an adaptive gripping mechanism fixed to the top of the robotic arm.

[0073] The adaptive clamping mechanism includes a plate-shaped shell with an internal cavity, a communication port on the shell, adsorption holes distributed on the bottom wall of the shell, a negative pressure motor fixed to the base plate, an adsorption tube with one end connected to the negative pressure port of the negative pressure motor and the other end connected to the communication port, multiple pipes located in the shell cavity, with one branch pipe connected to the communication port and the remaining branch pipes connected to the other adsorption holes in sequence, a miniature electronic control valve for controlling the closure of each adsorption hole, rubber nozzles connected to each adsorption hole in sequence, and several clamping components that are rotatably fitted to the side edge of the shell.

[0074] Each of the adaptive clamping mechanisms includes at least two clamping components. Each clamping component includes a drive port on the side wall of the housing, a drive gear rotatably fixed inside the housing via a rotating shaft and at least partially extending from the drive port, a mating rod rotatably fixed outside the housing via a rotating shaft seat, a driven gear sleeved in the middle of the mating rod for meshing with the drive gear, an arc-shaped clamping plate, a rubber pad laid on the wall of the clamping plate, and at least two connecting rods, each with one end fixed to the wall of the mating rod and the other end fixed to the clamping plate.

[0075] Using the area on the top wall of the base plate, excluding the grooved area, as the working wall, the robotic arm is fixed to the working wall. The bottom plate of one gripping unit is locked to the top plate of another gripping unit via a detachable locking mechanism, thereby enabling the two gripping units to be stacked and connected. In the stacked gripping units, the bottom plate of the lowest gripping unit is fixed to the base via a detachable locking mechanism.

[0076] After the moving drive mechanism moves to the target position, the robotic arms of each gripping unit drive the appropriate gripping mechanisms to move into the cooled electric furnace. A negative pressure motor operates to generate suction force from the rubber nozzles, and the rotation of the gripping plates clamps and fixes the bioceramics. Under the movement of the robotic arms, the bioceramics gripped by the appropriate gripping mechanisms are moved to the rotary table, and then the moving drive mechanism moves them to the bioceramic receiving point, thus completing the unified automatic receiving and transfer of the fired and cooled bioceramics.

[0077] The receiving module employs an automated operating process, utilizing components such as a moving drive mechanism, robotic arm, and gripping unit to automatically clamp, transfer, and receive bioceramics. The gripping unit is designed with clamping, rotation, and adsorption functions, adapting to the different requirements for bioceramic clamping and receiving under various conditions. Through overlapping and connected gripping units, the receiving module can simultaneously clamp and transfer multiple bioceramics, enabling it to complete the receiving and transfer of a large number of bioceramics in a short time. Automated operation reduces human intervention, lowers operational risks and errors, improves work safety, and increases the production efficiency of bioceramics.

[0078] While the invention has been described above with reference to various embodiments, it should be understood that many changes and modifications can be made without departing from the scope of the invention. That is, the methods, systems, and devices discussed above are examples. Various configurations can be appropriately omitted, substituted, or added to various processes or components. For example, in alternative configurations, methods can be performed in a different order than described, and / or various components can be added, omitted, and / or combined. Moreover, features described with respect to certain configurations can be combined in various other configurations, such as different aspects and elements of the configuration can be combined in a similar manner. Furthermore, the elements therein can be updated as the technology develops; many elements are examples and do not limit the scope of this disclosure or the claims. It should also be understood that after reading the description of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent changes and modifications also fall within the scope defined by the claims of this invention.

Claims

1. An automated bioceramic production monitoring system based on machine vision, characterized in that, The bioceramic production monitoring system includes a furnace for firing bioceramics and an observation window installed on the furnace for observing the internal combustion chamber. The system also includes a camera device for acquiring images of the bioceramics inside the furnace through the observation window, a monitoring module for receiving the images captured by the camera device to determine the firing status of the bioceramics inside the furnace, and a receiving module for receiving the finished bioceramics fired in the furnace. The camera device monitors the situation inside the observation window at a preset angle via a fixed bracket. The monitoring module includes a preliminary processing unit for processing and analyzing the first image captured by the camera device during the furnace operation, and a follow-up processing unit for processing and analyzing the second image captured by the camera device during the furnace operation and subsequent acquired images. The receiving module includes a base, a moving drive mechanism that drives the base to move on the ground along a preset path, and a gripping unit stacked on the base for gripping and transferring bioceramics inside the furnace. The initial processing unit performs the task through the following steps: S101: The first image of the bioceramics inside the furnace acquired by the camera device is used as the initial image. S102: Perform denoising, image enhancement, and grayscale processing on the initial image to further obtain a pre-processed image of preset specifications. S103: Identify bioceramic regions in the initial processed image: s1031: Divide the initial processed image into L first sub-images, and calculate the mean value of the pixel gray levels in each first sub-image. Use the mean value of the pixel gray levels of the first sub-image as the representative value of the first sub-image. The first sub-images are sequentially represented as IMAGE1, IMAGE2, IMAGEx…IMAGEL, and the representative values ​​of each first sub-image are sequentially represented as REVA1, REVA2, REVAx…REVAL, x=1,2,3…L; where REVAx is the representative value of IMAGEx. s1032: Correct the reference values ​​within each first sub-graphic in the initial processed image. Taking IMAGEx as an example, correct the reference values ​​of IMAGEx to obtain the calibration reference value CALIVx for IMAGEx. CALIVx= , s1033: Obtain the first sub-graphic distribution value IDV in the initial processed image. Where Max is the maximum value of the calibration reference value in the first sub-image of the initial processed image, Min is the minimum value of the calibration reference value in the first sub-image of the initial processed image, RE1 is the preset minimum difference reference value, and RE2 is the preset maximum difference reference value. s1034: Obtain image pixel grayscale values : , in, For the pre-set standard division values, To and The difference correction coefficient for positive correlation Priority-related parameters for the difference correction coefficient. s1035: The initial processed image is subjected to threshold differentiation to obtain the initial differentiated image, denoted by F(x) as the pixel gray value of the x-th first sub-graphic in the initial processed image in the initial differentiated image: ， s1036: The first sub-graphics in the initial processed image are identified sequentially. The graphic with a pixel gray value of 0 is identified as a bioceramic region. The graphic in the initial differentiated image where each pixel gray value of 0 simultaneously forms a closed image is a tracking image of a bioceramic. The center pixel coordinates of each tracking image are obtained as tracking coordinates, thereby obtaining the same number of tracking coordinates as the number of bioceramics in the furnace.

2. The bioceramic production monitoring system as described in claim 1, characterized in that, The follow-up processing unit performs the task through the following steps: s201: Subsequent images are those acquired by the camera device after the initial image. s202: Subsequent images are subjected to denoising, image enhancement, and grayscale processing to obtain further processed images of preset specifications. s203: Identify bioceramic regions in subsequent processed images: s2031: Divide the subsequent processed image into L second sub-images, and calculate the mean value of the pixel gray levels in each second sub-image. Use the mean value of the pixel gray levels of the second sub-image as the representative value of the second sub-image. The second sub-images are sequentially represented as PT1, PT2, PTx...PTL, and the representative values ​​of each second sub-image are sequentially represented as GY1, GY2, GYx...GYL, x=1,2,3...L; where GYx is the representative value of PTx. s2032: The subsequent processed image is subjected to threshold differentiation to obtain a further differentiated image, where f(x) represents the pixel grayscale value of the x-th second sub-graphic in the further processed image in the further differentiated image. ， s204: Identify and mark the position of each tracking coordinate in the processed image. For each tracking coordinate in the processed image, select the closed image with a grayscale value of 0 that is closest to the tracking coordinate within a preset range as the identification image, and calculate the area of ​​the identification image. S205: From the continuously acquired processed images, the recognition images acquired sequentially under the same tracking coordinate are denoted as IDEN1, IDEN2, IDEN1…IDENn, and the acquisition times corresponding to the recognition images are T1, T2, Ti…Tn, i=1, 2, 3…n, where n is a positive integer. Spline interpolation is used to fit the curve of the area change of the recognition images acquired sequentially under the same tracking coordinate with time, and the interpolation function Y(T) is obtained. Taking the recognition image acquired at the current time as IDENr and the current acquisition time as Tr, the area change rate of the continuously acquired recognition images under the same tracking coordinate at the current moment is calculated. : ； in, The preset monitoring time value, Let Y(T) represent the first derivative of the interpolation function Y(T), that is, the derivative of the interpolation function with respect to time T. This indicates that the recognition images acquired consecutively under the same tracking coordinates are in the same time zone [Tr- The absolute value of the first derivative within [Tr], which also represents the rate of change of the area of ​​the continuously acquired recognition images at the current moment under the same tracking coordinates. S206: Based on the real-time calculated rate of change of the area of ​​the recognized image To determine the volume change trend during the firing process of bioceramics in the furnace. S207: When Roc(Tr) is greater than the preset comparison threshold, determine that the bioceramic firing in the corresponding recognition image has failed. S208: Record the bioceramic detection results in each identified image into the database for staff to track and analyze the quality of bioceramic products.

3. The bioceramic production monitoring system as described in claim 2, characterized in that, Each gripping unit includes a horizontally arranged base plate, a horizontally arranged top plate above the base plate, at least two lifting drive rods with their bottoms fixed to the base plate and their tops fixed to the top plate, a groove in the upper wall of the base plate, a rotating platform embedded in the groove, a rubber pad on the rotating platform, a robotic arm fixed to the base plate by a fixing seat, and an adaptive gripping mechanism fixed to the top of the robotic arm.

4. The bioceramic production monitoring system as described in claim 3, characterized in that, The adaptive clamping mechanism includes a plate-shaped shell with an internal cavity, a communication port on the shell, adsorption holes distributed on the bottom wall of the shell, a negative pressure motor fixed on the base plate, an adsorption tube with one end connected to the negative pressure port of the negative pressure motor and the other end connected to the communication port, multiple pipes located in the shell cavity, with one branch pipe connected to the communication port and the remaining branch pipes connected to other adsorption holes in sequence, a miniature electronic control valve for controlling the closing of each adsorption hole, rubber nozzles connected to each adsorption hole in sequence, and several clamping members that are rotatably fitted to the side edge of the shell, wherein each adaptive clamping mechanism includes at least two clamping members.

5. The bioceramic production monitoring system as described in claim 4, characterized in that, Each of the clamping components includes a drive port disposed on the side wall of the housing, a drive gear rotatably fixed inside the housing via a rotating shaft and at least partially extending through the drive port, a mating rod rotatably fixed outside the housing via a rotating shaft seat, a driven gear sleeved in the middle of the mating rod for meshing with the drive gear, an arc-shaped clamping plate, a rubber pad laid on the plate wall of the clamping plate, and at least two connecting rods, each with one end fixed to the rod wall of the mating rod and the other end fixed to the clamping plate.

Images