Water permeable brick laser processing control system of self-adaptive control algorithm

Abstract

A water permeable brick laser processing control system based on an adaptive control algorithm is characterized by comprising a monitoring hardware module, a monitoring transmission module, a data storage module, an image enhancement module, an intelligent control module, a control adjustment module and a control feedback module. According to the water-permeable brick laser processing control system based on the self-adaptive control algorithm, real-time monitoring and image acquisition in the water-permeable brick laser processing process are carried out through the high-definition camera, the acquired water-permeable brick image data are enhanced through the image enhancement algorithm, and then the water-permeable brick laser processing control system based on the self-adaptive control algorithm is obtained through the self-adaptive control algorithm. And working parameters of the laser processing instrument are regulated and controlled in real time.

Description

Technical Field

[0001] The present invention relates to the field of intelligent healthcare, and particularly to a laser processing control system for permeable bricks with an adaptive control algorithm. Background Art

[0002] With the rapid advancement of urbanization, cities are facing increasingly severe drainage problems and the urban heat island effect. Traditional drainage systems are unable to effectively cope with extreme weather events such as heavy rainstorms, resulting in frequent urban waterlogging, which has had a great impact on the normal operation of cities and the lives of residents. To solve this problem, permeable bricks, as a new type of ground material, have gradually attracted attention. The design of permeable bricks is inspired by nature, and its unique water permeability can effectively infiltrate precipitation into the ground, increase groundwater recharge, reduce surface runoff, and thus effectively alleviate urban flooding problems.

[0003] In past research, the production and processing technologies of permeable bricks have undergone a series of improvements and innovations. The production of permeable bricks usually requires a certain proportion of cement, aggregates, and additives, and is fired at high temperatures to form strong bricks. However, traditional surface treatment methods for permeable bricks often rely on mechanical equipment to adjust the surface texture and roughness through physical means to enhance their water permeability. This treatment method not only has low efficiency, but also is difficult to ensure the consistency and quality of each brick in actual operation, and it is easy to have differences between batches. Therefore, there is an urgent need for a new and more advanced processing technology to improve the performance and effect of permeable bricks.

[0004] In recent years, laser processing technology has gradually been applied to the processing of permeable bricks. Laser processing technology has gradually attracted the attention of industry insiders with its advantages of high precision, high efficiency, and non-contact. By utilizing the energy of the laser beam, the surface of permeable bricks can be processed and modified at the micron level, thereby achieving precise control of important physical parameters such as surface texture and roughness. Laser processing can not only greatly improve the water permeability of permeable bricks, but also achieve some complex pattern engraving to increase their aesthetic value. Therefore, laser processing technology is considered an important means to improve the performance of permeable bricks.

[0005] Therefore, the present invention aims to develop a laser processing control system for permeable bricks with an adaptive control algorithm, which provides a feasible solution in the face of many challenges in urban drainage problems and permeable brick processing technologies, improves the performance of permeable bricks, ensures their reliability and stability under different environmental conditions, and has a positive significance for improving the urban environment. In the future, with the continuous maturity of related technologies, this system is expected to be popularized and applied in a wider range of fields to contribute to the sustainable development of cities. Summary of the Invention

[0006] The object of the present invention is to provide a laser processing control system for permeable bricks with an adaptive control algorithm, aiming to solve the problems mentioned in the above background.

[0007] To achieve the above object, the present invention proposes a laser processing control system for permeable bricks with an adaptive control algorithm, which is characterized by including a monitoring hardware module, a monitoring transmission module, a data storage module, an image enhancement module, an intelligent control module, a control adjustment module, and a control feedback module; in the monitoring hardware module, a high-definition camera is used to monitor the permeable bricks undergoing laser surface treatment in real time and collect the surface image data of the permeable bricks; the monitoring transmission module constructs a wired transmission network through a wired network protocol and transmits the collected surface data of the permeable bricks to the computing host; the data storage module receives the image data of the permeable bricks transmitted by the wired transmission network and stores it through the computing host; the image enhancement module first calculates the pixel parameters based on the permeable brick image data matrix, then enhances the permeable brick image data through an iterative function, and finally constructs a loss function using the difference degree between pixel points to optimize the iterative enhancement process; the intelligent control module adaptively regulates the laser processing instrument based on the laser processing situation of the permeable bricks using the adaptive control algorithm; the control adjustment module issues a regulation quality through the computing host based on the output result of the intelligent control module to adjust the working parameters of the laser processing instrument; the control feedback module monitors and checks the surface condition of the permeable bricks after laser processing through a high-definition camera and reworks the permeable bricks that do not meet the standards.

[0008] Further, in the monitoring hardware module, high-definition cameras are installed around the permeable bricks to achieve monitoring from four angles, and the surface of the permeable bricks undergoing laser processing is monitored in real time to collect the surface image data of the permeable bricks.

[0009] Further, the monitoring transmission module uses a wired network protocol to establish a data transmission channel and transmits data through the data transmission channel.

[0010] Further, the data storage module uses the computing host to receive the surface image data of the permeable bricks transmitted through the data transmission channel and stores the transmitted surface image data of the permeable bricks.

[0011] Further, for the image enhancement algorithm, pixel parameters are calculated based on the permeable brick image data matrix, the permeable brick image data is enhanced through an iterative function, and a loss function is constructed using the difference degree between pixel points to optimize the iterative enhancement process.

[0012] Further, the detailed process of enhancing the permeable brick image data is as follows:

[0013] For the collected pervious brick image data, a pixel matrix is constructed, and the pervious brick image data is represented through the pixel matrix as follows:

[0014]

[0015] Among them, D represents the pervious brick image data matrix, d1,1, d1,n, di,j, dn,1, and dn,n respectively represent the values of the pixel points at the first row and first column, the first row and nth column, the i-th row and j-th column, the nth row and first column, and the nth row and nth column of the pervious brick image data matrix. Based on the pervious brick image data matrix, the calculation of pixel parameters is carried out, and the calculation formula is as follows:

[0016]

[0017] Among them, gi,j represents the pixel parameter corresponding to the pixel point at the i-th row and j-th column of the pervious brick image data matrix, ωi,j represents the feature weight corresponding to the pixel point at the i-th row and j-th column of the pervious brick image data matrix. The pixel parameters form a pixel parameter matrix. Based on the pixel parameter matrix, an iterative function is constructed to enhance the pervious brick image data, and the iterative function formula is as follows:

[0018]

[0019] Among them, Dk and Dk+1 respectively represent the pervious brick image data matrix at the k-th iteration and the pervious brick image data matrix at the (k + 1)-th iteration, Gk and Gk-1 respectively represent the pixel parameter matrix at the k-th iteration and the pixel parameter matrix at the (k - 1)-th iteration, k represents the current iteration number, E(1) represents a matrix with all elements being 1. Through iteration, an image enhancement effect is generated. During the iterative enhancement of the pervious brick image data, by constructing a loss function, the uniformity of the pixel point distribution after image enhancement is improved. The difference degree between the pixel point of the pervious brick image data matrix and the surrounding adjacent N pixel points during the iteration process is defined, and the calculation formula is as follows:

[0020]

[0021] Among them, respectively represent the value of the pixel point at the i-th row and j-th column of the pervious brick image data matrix at the k-th iteration and the value of the pixel point at the l-th row and r-th column of the pervious brick image data matrix at the k-th iteration, represents the difference degree of the pixel point at the i-th row and j-th column of the pervious brick image data matrix at the k-th iteration. Based on the difference degree, a loss function is constructed, and the loss function is expressed as follows:

[0022]

[0023] Among them, F represents the loss function, represents the difference degree of the pixel at the i-th row and j-th column of the permeable brick image data matrix at the (k - 1)-th iteration. Through the loss function, the uniformity of the pixel distribution in the iterative enhancement process of the permeable brick image data is optimized. The image enhancement algorithm proposed by the present invention is based on the permeable brick image data matrix, calculates pixel parameters, constructs a pixel parameter matrix, uses an iterative function to enhance the permeable brick image data, constructs a loss function according to the difference degree between pixels. The image enhancement algorithm proposed by the present invention improves the effect of the acquired image, and the loss function optimizes the uniformity of the pixel distribution of the enhanced image.

[0024] Furthermore, for the adaptive control algorithm, a working relationship function is constructed to obtain an adjustment function, and a neural network is used to obtain the expected regulation coefficient matrix of the laser processing instrument to regulate the working parameters of the laser processing instrument.

[0025] Furthermore, the process of regulating the working parameters of the laser processing instrument is as follows:

[0026] The laser processing instrument processes the surface of the permeable brick. The acquired image data of the permeable brick surface passes through the image enhancement module to obtain the enhanced image data of the permeable brick surface. Through the image data of the permeable brick surface at different sampling times, the expected working power required by the current laser processing instrument is analyzed, and the working power of the laser processing instrument is regulated. The constructed working relationship function is expressed as follows:

[0027]

[0028] Among them, respectively represent the enhanced image data of the permeable brick surface at the h-th sampling time and the enhanced image data of the permeable brick surface at the (h - 1)-th sampling time. Δt represents the time between adjacent sampling times, β represents the relationship coefficient, μh and μh-1 respectively represent the working output of the laser processing instrument at the h-th sampling time and the working output of the laser processing instrument at the (h - 1)-th sampling time, αh and αh-1 respectively represent the working output regulation coefficient matrix of the laser processing instrument at the h-th sampling time and the working output regulation coefficient matrix of the laser processing instrument at the (h - 1)-th sampling time. Then, according to the working relationship function, an adjustment function is obtained, and the formula of the adjustment function is as follows:

[0029]

[0030] Among them, V represents the adjustment function, and μ′h represents the expected working output of the laser processing instrument at the h-th sampling moment. The adjustment function is input into the neural network, and through each fully connected layer in the neural network, the output of the neural network is obtained. Based on the output of the neural network, the expected regulation coefficient matrix of the laser processing instrument is calculated, which is expressed as:

[0031]

[0032] Among them, γout,i represents the i-th output of the output layer of the neural network, represents the i-th value of the expected regulation coefficient matrix of the laser processing instrument. Through the expected regulation coefficient matrix, the working power of the laser processing instrument is adjusted to the corresponding power. The adaptive control algorithm proposed by the present invention establishes a working relationship function based on the relationship between the working parameters of the laser processing instrument and the image data of the permeable brick. Based on the working relationship function, the adjustment function is obtained, and through the neural network, the expected regulation coefficient matrix of the laser processing instrument is calculated. The adaptive control algorithm proposed by the present invention starts from the relationship between the working parameters and the image data of the permeable brick, uses the neural network to adjust the working parameters, and improves the accuracy of adaptive adjustment.

[0033] Furthermore, the control and adjustment module, based on the output result of the control and adjustment module, calculates the host to transmit a control instruction to the laser processing instrument through the data transmission channel to adjust the working parameters of the laser processing instrument.

[0034] Furthermore, the control feedback module conducts quality inspection on the permeable bricks that have completed laser processing through a high-definition camera, and reprocesses the permeable bricks that do not meet the processing standards.

[0035] Beneficial Effects

[0036] 1. The image enhancement algorithm proposed by the present invention calculates pixel parameters based on the permeable brick image data matrix, constructs a pixel parameter matrix, and uses an iterative function to enhance the permeable brick image data. According to the difference degree between pixel points, a loss function is constructed. The image enhancement algorithm proposed by the present invention improves the effect of the acquired image, and the loss function optimizes the uniformity of the pixel point distribution of the enhanced image.

[0037] 2. The adaptive control algorithm proposed by the present invention establishes a working relationship function based on the relationship between the working parameters of the laser processing instrument and the image data of the permeable brick. Based on the working relationship function, the adjustment function is obtained, and through the neural network, the expected regulation coefficient matrix of the laser processing instrument is calculated. The adaptive control algorithm proposed by the present invention starts from the relationship between the working parameters and the image data of the permeable brick, uses the neural network to adjust the working parameters, and improves the accuracy of adaptive adjustment. Description of the Drawings

[0038] To more clearly illustrate the technical solutions in the embodiments of the present invention or in the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0039] Figure 1 is a schematic diagram of the system of the present invention; Detailed implementation manners

[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.

[0041] To achieve the above object, the present invention proposes a laser processing control system for permeable bricks with an adaptive control algorithm, which is characterized in that it includes a monitoring hardware module, a monitoring transmission module, a data storage module, an image enhancement module, an intelligent control module, a control adjustment module, and a control feedback module; in the monitoring hardware module, a high-definition camera is used to monitor the permeable bricks undergoing laser surface treatment in real time and collect the surface image data of the permeable bricks; the monitoring transmission module constructs a wired transmission network through a wired network protocol to transmit the collected surface data of the permeable bricks to a computing host; the data storage module receives the permeable brick image data transmitted by the wired transmission network and stores it through the computing host; the image enhancement module first calculates the pixel parameters based on the permeable brick image data matrix, then enhances the permeable brick image data through an iterative function, and finally constructs a loss function using the difference degree between pixel points to optimize the iterative enhancement process; the intelligent control module adaptively regulates the laser processing instrument based on the laser processing situation of the permeable bricks using an adaptive control algorithm; the control adjustment module issues a regulation quality through the computing host based on the output result of the intelligent control module to adjust the working parameters of the laser processing instrument; the control feedback module monitors and checks the surface condition of the permeable bricks after laser processing through a high-definition camera and reworks the permeable bricks that do not meet the standards.

[0042] Specifically, in the monitoring hardware module, high-definition cameras are installed around the permeable bricks to achieve monitoring from four angles, and real-time surface monitoring of the permeable bricks undergoing laser processing is carried out to collect the surface image data of the permeable bricks.

[0043] Specifically, the monitoring transmission module uses a wired network protocol to establish a data transmission channel and transmits data through the data transmission channel.

[0044] Specifically, the data storage module uses the computing host to store the surface image data of the permeable bricks transmitted.

[0045] Specifically, the image enhancement algorithm calculates the pixel parameters based on the permeable brick image data matrix, enhances the permeable brick image data through an iterative function, constructs a loss function using the difference degree between pixel points, and optimizes the iterative enhancement process. The detailed process is as follows:

[0046] For the collected permeable brick image data, a pixel matrix is constructed, and the permeable brick image data is represented through the pixel matrix as follows:

[0047]

[0048] Among them, D represents the permeable brick image data matrix, d1,1, d1,n, di,j, dn,1, and dn,n respectively represent the values of the pixel points in the first row and first column, the first row and nth column, the i-th row and j-th column, the nth row and first column, and the nth row and nth column of the permeable brick image data matrix. Based on the permeable brick image data matrix, the pixel parameters are calculated, and the calculation formula is as follows:

[0049]

[0050] Among them, gi,j represents the pixel parameter corresponding to the pixel point in the i-th row and j-th column of the permeable brick image data matrix, ωi,j represents the feature weight corresponding to the pixel point in the i-th row and j-th column of the permeable brick image data matrix. The pixel parameters form a pixel parameter matrix. Based on the pixel parameter matrix, an iterative function is constructed to enhance the permeable brick image data. The iterative function formula is as follows:

[0051]

[0052] Among them, Dk and Dk+1 respectively represent the permeable brick image data matrix at the k-th iteration and the permeable brick image data matrix at the (k + 1)-th iteration, Gk and Gk-1 respectively represent the pixel parameter matrix at the k-th iteration and the pixel parameter matrix at the (k - 1)-th iteration, k represents the current iteration number, E(1) represents a matrix with all elements being 1. Through iteration, an image enhancement effect is generated. During the iterative enhancement process of the permeable brick image data, by constructing a loss function, the uniformity of the pixel point distribution after image enhancement is improved. The difference degree between the pixel points in the permeable brick image data matrix and the surrounding N adjacent pixel points during the iterative process is defined, and the calculation formula is as follows:

[0053]

[0054] Among them, The distribution represents the value of the pixel at the i-th row and j-th column of the permeable brick image data matrix at the k-th iteration, and the value of the pixel at the l-th row and r-th column of the permeable brick image data matrix at the k-th iteration. Represents the degree of difference of the pixel at the i-th row and j-th column of the permeable brick image data matrix at the k-th iteration. Based on the degree of difference, a loss function is constructed, and the loss function is expressed as follows:

[0055]

[0056] Among them, F represents the loss function. Represents the degree of difference of the pixel at the i-th row and j-th column of the permeable brick image data matrix at the (k - 1)-th iteration. Through the loss function, the uniformity of the pixel distribution in the iterative enhancement process of the permeable brick image data is optimized.

[0057] Specifically, for the adaptive control algorithm, a working relationship function is constructed to obtain an adjustment function. Using a neural network, the expected regulation coefficient matrix of the laser processing instrument is obtained to regulate the working parameters of the laser processing instrument. The detailed process is as follows:

[0058] The laser processing instrument processes the surface of the permeable brick. The collected image data of the permeable brick surface passes through the image enhancement module to obtain the enhanced image data of the permeable brick surface. Through the image data of the permeable brick surface at different sampling times, the expected working power required by the current laser processing instrument is analyzed, and the working power of the laser processing instrument is regulated. The working relationship function is constructed and expressed as follows:

[0059]

[0060] Among them, Respectively represent the enhanced image data of the permeable brick surface at the h-th sampling time and the enhanced image data of the permeable brick surface at the (h - 1)-th sampling time. Δt represents the time between adjacent sampling times, β represents the relationship coefficient, μh and μh - 1 respectively represent the working output of the laser processing instrument at the h-th sampling time and the working output of the laser processing instrument at the (h - 1)-th sampling time, and αh and αh - 1 respectively represent the regulation coefficient matrix of the working output of the laser processing instrument at the h-th sampling time and the regulation coefficient matrix of the working output of the laser processing instrument at the (h - 1)-th sampling time. Then, according to the working relationship function, the adjustment function is obtained, and the formula of the adjustment function is as follows:

[0061]

[0062] Among them, V represents the adjustment function, and μ′h represents the expected working output of the laser processing instrument at the h-th sampling moment. The adjustment function is input into the neural network, and through each fully connected layer in the neural network, the output of the neural network is obtained. Based on the output of the neural network, the expected regulation coefficient matrix of the laser processing instrument is calculated, which is expressed as:

[0063]

[0064] Among them, γout,i represents the i-th output of the output layer of the neural network. represents the i-th value of the expected regulation coefficient matrix of the laser processing instrument. Through the expected regulation coefficient matrix, the working parameters of the laser processing instrument are adjusted.

[0065] Specifically, the control and adjustment module, based on the output result of the control and adjustment module, calculates the host to transmit a control instruction to the laser processing instrument through the data transmission channel to adjust the working parameters of the laser processing instrument.

[0066] Specifically, the control feedback module conducts quality inspection on the permeable bricks that have completed laser processing through a high-definition camera, and reprocesses the permeable bricks that do not meet the processing standards.

[0067] In a specific embodiment, the user first conducts real-time monitoring and data collection of the laser processing of the permeable bricks through the high-definition cameras installed around the permeable bricks. Then, using the wired network protocol, a data transmission channel is established, and through the data transmission channel, data transmission among the high-definition cameras, the computing host, and the laser processing instrument is carried out. Then, using the image enhancement algorithm, the collected image data of the permeable bricks is enhanced. Next, using the adaptive regulation algorithm, the working parameters of the laser processing instrument are regulated in real time, and a regulation instruction is sent to the laser processing device. Finally, for the permeable bricks that have completed laser processing, quality inspection is carried out through a high-definition camera, and the permeable bricks that do not meet the processing standards are reprocessed.

[0068] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the said element.

[0069] Each embodiment in this specification is described in a related manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and for the related parts, reference can be made to the partial description of the method embodiment.

[0070] The above description is only a preferred embodiment of the present invention and is not intended to limit the protection scope of the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention are all included in the protection scope of the present invention.

Claims

1. A laser processing control system for permeable bricks with an adaptive control algorithm, characterized in that, It includes a monitoring hardware module, a monitoring transmission module, a data storage module, an image enhancement module, an intelligent control module, a control adjustment module, and a control feedback module. In the monitoring hardware module, a high-definition camera is used to monitor the laser processing process of the permeable bricks in real time. The monitoring transmission module transmits the monitoring data to the computing host through a wired network protocol. The data storage module stores the collected image data of the permeable bricks. The image enhancement module uses an image enhancement algorithm to enhance the collected image data of the permeable bricks. The intelligent control module uses an adaptive control algorithm to adaptively regulate the laser processing instrument based on the laser processing situation of the permeable bricks. The control adjustment module adjusts the working parameters of the laser processing instrument based on the output result of the intelligent control module. The control feedback module monitors and inspects the permeable bricks after laser processing through a high-definition camera.

2. The permeable brick laser processing control system with an adaptive control algorithm according to claim 1, wherein In the monitoring hardware module, high-definition cameras are installed around the permeable bricks to achieve monitoring from four angles, and real-time surface monitoring of the laser-processed permeable bricks is carried out to collect surface image data of the permeable bricks.

3. The laser processing control system for permeable bricks of an adaptive control algorithm according to claim 1, wherein, The monitoring transmission module uses a wired network protocol to establish a data transmission channel and conducts data transmission through the data transmission channel.

4. The laser processing control system for permeable bricks with an adaptive control algorithm according to claim 1, characterized in that, The data storage module uses the computing host to store the transmitted surface image data of the permeable bricks.

5. The laser processing control system for permeable bricks with an adaptive control algorithm according to claim 1, wherein The image enhancement algorithm calculates pixel parameters based on the permeable brick image data matrix, enhances the permeable brick image data through an iterative function, constructs a loss function using the difference degree between pixel points, and optimizes the iterative enhancement process.

6. The laser processing control system for permeable bricks of an adaptive control algorithm according to claim 5, characterized in that, The detailed process of the enhancement of the permeable brick image data is as follows: For the collected permeable brick image data, a pixel matrix is constructed, and the permeable brick image data is represented through the pixel matrix, as shown below: Among them, D represents the permeable brick image data matrix, d1,1, d1,n, di,j, dn,1, and dn,n respectively represent the values of the pixel points in the first row and first column, the first row and nth column, the i-th row and j-th column, the nth row and first column, and the nth row and nth column of the permeable brick image data matrix. Based on the permeable brick image data matrix, pixel parameter calculations are carried out, and the calculation formula is as follows: Among them, gi,j represents the pixel parameter corresponding to the pixel point in the i-th row and j-th column of the permeable brick image data matrix, ωi,j represents the feature weight corresponding to the pixel point in the i-th row and j-th column of the permeable brick image data matrix. The pixel parameters form a pixel parameter matrix. Based on the pixel parameter matrix, an iterative function is constructed to enhance the permeable brick image data, and the iterative function formula is as follows: Among them, Dk and Dk+1 respectively represent the pervious brick image data matrix at the k-th iteration and the pervious brick image data matrix at the (k + 1)-th iteration, Gk and Gk-1 respectively represent the pixel parameter matrix at the k-th iteration and the pixel parameter matrix at the (k - 1)-th iteration, k represents the current iteration number, E(1) represents a matrix with all elements being 1. Through iteration, an image enhancement effect is generated. During the iterative enhancement of the pervious brick image data, by constructing a loss function, the uniformity of the pixel point distribution after image enhancement is improved. The difference degree between the pixel points of the pervious brick image data matrix and the surrounding N adjacent pixel points during the iteration process is defined, and the calculation formula is as follows: Among them, The distribution represents the value of the pixel at the i-th row and j-th column of the permeable brick image data matrix at the k-th iteration, and the value of the pixel at the l-th row and r-th column of the permeable brick image data matrix at the k-th iteration. Represents the difference degree of the pixel at the i-th row and j-th column of the permeable brick image data matrix at the k-th iteration. Based on the difference degree, a loss function is constructed, and the loss function is expressed as follows: Among them, F represents the loss function, represents the difference degree of the pixel at the i-th row and j-th column of the permeable brick image data matrix at the (k - 1)-th iteration. Through the loss function, the uniformity of the pixel distribution in the iterative enhancement process of the permeable brick image data is optimized.

7. An adaptive control algorithm-based laser processing control system for permeable bricks according to claim 1, characterized in that, For the adaptive control algorithm, a working relationship function is constructed to obtain an adjustment function. Using a neural network, the expected regulation coefficient matrix of the laser processing instrument is obtained to regulate the working parameters of the laser processing instrument.

8. An adaptive control algorithm-based laser processing control system for permeable bricks according to claim 1, characterized in that, The detailed process of regulating the working parameters of the laser processing instrument is as follows: The laser processing instrument processes the surface of the pervious brick. The collected pervious brick surface image data passes through the image enhancement module to obtain the enhanced pervious brick surface image data. Based on the pervious brick surface image data at different sampling times, the expected working power required by the current laser processing instrument is analyzed, and the working power of the laser processing instrument is regulated. The constructed working relationship function is expressed as follows: Among them, respectively represent the enhanced permeable brick surface image data at the h-th sampling moment, the enhanced permeable brick surface image data at the (h - 1)-th sampling moment, Δt represents the time between adjacent sampling moments, β represents the relationship coefficient, μh and μh-1 respectively represent the working output of the laser processing instrument at the h-th sampling moment and the working output of the laser processing instrument at the (h - 1)-th sampling moment, αh and αh-1 respectively represent the working output regulation coefficient matrix of the laser processing instrument at the h-th sampling moment and the working output regulation coefficient matrix of the laser processing instrument at the (h - 1)-th sampling moment. Then, according to the working relationship function, an adjustment function is obtained, and the adjustment function formula is as follows: Among them, V represents the adjustment function, μ′h represents the expected working output of the laser processing instrument at the h-th sampling time. Using a neural network, the adjustment function is input into the neural network. After passing through each fully connected layer in the neural network, the output of the neural network is obtained. Based on the output of the neural network, the expected regulation coefficient matrix of the laser processing instrument is calculated and expressed as: Among them, γout,i represents the i-th output of the output layer of the neural network. represents the i-th value of the expected regulation coefficient matrix of the laser processing instrument. The working power of the laser processing instrument is adjusted through the expected regulation coefficient matrix.

9. The permeable brick laser processing control system of an adaptive control algorithm according to claim 8, characterized in that, Based on the output result of the control and adjustment module, through the data transmission channel, the control adjustment module calculates and transmits a control instruction from the host to the laser processing instrument to adjust the working parameters of the laser processing instrument.

10. The permeable brick laser processing control system with an adaptive control algorithm according to claim 1, characterized in that, For the pervious brick that has completed laser processing, the control feedback module conducts quality inspection through a high-definition camera, and the pervious brick that does not meet the processing standard is reprocessed.

Images