Monitoring System for the Preparation of Solid Wood Multilayer Flooring Based on a Data Analysis Model

Abstract

The present invention discloses a monitoring system for the preparation of multi-layer solid wood floors using a data analysis model, specifically related to the fields of solid wood surface engraving and engraving machine tool monitoring, and is used to solve the problems of high energy consumption and long time consumption in the engraving of solid wood surface patterns and the monitoring of engraving machine tools. The monitoring system includes the following steps: by collecting the image feature information of the solid wood surface without engraving patterns and comparing it with the feature information of standard straight lines, oblique lines, and wavy lines, determine the type of the engraved pattern on the solid wood surface, and engrave a similar pattern on the basis of the existing patterns on the solid wood surface, thereby greatly reducing the time and energy consumption of pattern engraving. In addition, more rigorous monitoring is carried out on the engraving machine tool with a large load, which effectively improves the accuracy and safety of the monitoring system while minimizing the labor and material costs as much as possible.

Description

Technical Field

[0001] The present invention relates to the technical field of solid wood surface engraving and engraving machine tool monitoring. More specifically, the present invention relates to a monitoring system for the preparation of solid wood multi-layer floors based on a data analysis model. Background Art

[0002] The solid wood surface is an important part of the solid wood multi-layer floor. The quality of the solid wood surface directly affects the appearance, stability, wear resistance and service life of the floor. Therefore, strict monitoring of the unengraved solid wood surface is required.

[0003] The prior art has the following deficiencies:

[0004] 1. When engraving patterns on the solid wood surface by the prior art, due to various factors such as the hardness of the solid wood surface, the accuracy of the engraved pattern, and the influence of its own texture, a large amount of energy and time will be consumed during the engraving process;

[0005] 2. The monitoring of the faults of the engraving machine tool in the prior art is all based on a unified standard, without considering the influence of the number of solid wood surfaces engraved on the performance of the engraving machine tool, which will result in problems such as resource waste or untimely fault discovery. Summary of the Invention

[0006] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a signal processing method for the receiving end of a radar communication integrated system. By taking the original texture of the unengraved solid wood surface as an important consideration factor, the type of the solid wood surface engraving pattern is selected purposefully, and the monitoring scheme of the engraving machine tool is determined according to the number of solid wood surfaces engraved to solve the problems raised in the above background art.

[0007] To achieve the above object, the present invention provides the following technical solutions:

[0008] A monitoring system for the preparation of solid wood multi-layer floors based on a data analysis model, including a solid wood surface data acquisition unit, a solid wood surface data analysis unit, a texture image acquisition unit, an image feature extraction unit, a texture image comparison unit, a decision processing unit, a machine tool data acquisition unit, a machine tool data processing unit and an alarm unit;

[0009] The solid wood surface data acquisition unit is used to collect information on the moisture content, thickness, and elastic modulus of the solid wood surface, and transmit this information to the solid wood surface data analysis unit;

[0010] The solid wood surface data analysis unit performs comprehensive arithmetic processing on the received data information, generates qualified and unqualified signals for the equipment accordingly, and transmits the generated signals to the texture image acquisition unit;

[0011] The wood grain image acquisition unit acquires the qualified signal of the solid wood surface grain image information and transmits it to the image feature extraction unit;

[0012] The image feature extraction unit extracts the grain feature information of the image and transmits it to the grain image comparison unit;

[0013] The grain image comparison unit compares the extracted feature information with the three standard grain feature information of straight grain, diagonal grain, and wavy grain, generates a category parameter signal, and sends the category parameter signal to the decision processing unit;

[0014] The decision processing unit distributes the unengraved solid wood surface to the wood board engraving machines for manufacturing straight grain, diagonal grain, and wavy grain respectively according to the category parameter signal;

[0015] The machine tool data acquisition unit acquires the number of solid wood surfaces to be engraved, the internal working temperature, the integrity of the tool head, and the relative error of the spindle speed of each of the three machine tools, and transmits the information to the machine tool data processing unit;

[0016] The machine tool data processing unit divides the machine tools into the state of focusing on monitoring the wood board engraving machine for manufacturing straight grain, the state of focusing on monitoring the wood board engraving machine for manufacturing diagonal grain, the state of focusing on monitoring the wood board engraving machine for manufacturing wavy grain, and the state of not requiring key monitoring according to the number of solid wood surfaces engraved by each machine tool, divides the machine tools into the normal working state and the abnormal working state according to different standards according to different states, and transmits its state information to the alarm unit;

[0017] The alarm unit performs corresponding different processing on the machine tool according to the different received state information.

[0018] Further, the specific steps for comprehensively calculating and processing the solid wood surface data are as follows:

[0019] S1: The formula for the quality coefficient Ai of the solid wood surface is where MC represents the moisture content of the solid wood surface, H represents the thickness of the solid wood surface, E represents the elastic modulus of the solid wood surface, i=(1,2,…,n) represents the i-th unengraved solid wood surface, a1 and a2 are weighting factors, and a1>a2, a1 + a2 = 1.021;

[0020] S2: Set a reference value H1, and compare the quality coefficient A of each of the n unengraved solid wood surfaces with H1 i respectively. When A i ≥H1, it indicates that the unengraved solid wood surface is qualified, and the determination coefficient B i =1; when A i <H1, it indicates that the unengraved solid wood surface is unqualified, and the determination coefficient Bi = 0.

[0021] Furthermore, the texture image acquisition unit operates as follows:

[0022] If the acquisition is qualified, that is, determine the coefficient B i = 1 of the unpatterned solid wood surface texture image.

[0023] Furthermore, the specific steps for feature extraction of the texture image are as follows:

[0024] S1: Gray-scale the image using the formula Gray = 0.299*R + 0.587*G + 0.114*B, where R, G, and B represent the pixel values of the three primary colors red, green, and blue respectively, and Gray represents the gray-scale value obtained by converting the pixel point;

[0025] S2: Obtain the gray-scale distribution of the solid wood surface texture gray-scale image according to the distribution of the number of different gray-scale values among all pixel points

[0026] S3: Take (where ) as the Gabor filter and convolve it with the image gray-scale distribution to obtain the feature amplitude of the solid wood surface texture. Among them, convolution is a mathematical operation widely used in signal processing and image processing. It is to superimpose two signals. By gradually moving one of the signals, a new signal is obtained. This new signal describes the interaction between the two signals. Through the convolution operation, the local features of the image can be extracted;

[0027] S4: Extract the feature information of the unpatterned solid wood surface texture through the feature amplitude

[0028] Furthermore, the specific comparison method of the texture image comparison unit is as follows:

[0029] Adopt the support vector machine classification algorithm, compare the solid wood surface texture feature information with the three standard feature information of straight grain, oblique grain, and wavy grain. Through the inner product function find the optimal classification surface. Adopt three independent support vector machine classifiers. If the texture recognized by two classifiers is straight grain, it means that the unpatterned solid wood surface texture is more similar to straight grain, and set the category parameter C i = 1; if the texture recognized by two classifiers is oblique grain, it means that the unpatterned solid wood surface texture is more similar to oblique grain, and set the category parameter C i = 2; if the texture recognized by two classifiers is wavy grain, it means that the unpatterned solid wood surface texture is more similar to wavy grain, and set the category parameter C​i = 3.

[0030] Further, the decision processing unit processes as follows:

[0031] If the category parameter Ci = 1, then transfer the unpatterned solid wood skin to the wood engraving machine for making straight grains; if the category parameter Ci = 2, then transfer the unpatterned solid wood skin to the wood engraving machine for making diagonal grains; if the category parameter Ci = 3, then transfer the unpatterned solid wood skin to the wood engraving machine for making wavy grains.

[0032] Further, the specific steps for processing by the machine tool data processing unit are as follows:

[0033] S1: The number of solid wood skins to be engraved by the wood engraving machine for making straight grains is N1, the number of solid wood skins to be engraved by the wood engraving machine for making diagonal grains is N2, and the number of solid wood skins to be engraved by the wood engraving machine for making wavy grains is N 3；

[0034] S2: Set the reference value Z. If N1 ≥ Z% * (N1 + N2 + N3), then the wood engraving machine for making straight grains has a heavy workload and needs to be overhauled with priority. At this time, the overhaul type D i = 1; if N2 ≥ Z% * (N1 + N2 + N3), then the wood engraving machine for making diagonal grains has a heavy workload and needs to be overhauled with priority. At this time, the overhaul type D i = 2; if N3 ≥ Z% * (N1 + N2 + N3), then the wood engraving machine for making straight grains has a heavy workload and needs to be overhauled with priority. At this time, the overhaul type D i = 3; if none of these three situations occur, it means that the quantities of N1, N2, and N3 are relatively average. At this time, the overhaul type D i = 4;

[0035] S3: According to the formula obtain the machine tool accuracy coefficient P i , where W represents the tool tip integrity, R represents the relative error of the spindle speed, T represents the internal working temperature of the machine tool, and j = 1, 2, 3, representing the wood engraving machines for making straight grains, diagonal grains, and wavy grains respectively;

[0036] S4: Set the reference value H2. If D i = 1, then every t1 time, compare the P1 of the wood engraving machine for making straight grains with H2, and every t2 time, compare the accuracy coefficients P j of the remaining two wood engraving machines with H2 respectively; if D i = 1, then every t1 time, compare the P1 of the wood engraving machine for making straight grains with H2, and every t2 time, compare the accuracy coefficients P j of the remaining two wood engraving machines with H2 respectively; if Di If D = 2, then every t1 time, compare the wood engraving machine P2 for making twill with H2, and every t2 time, compare the accuracy coefficients P of the remaining two wood engraving machines with H2 respectively; j If D i = 3, then every t1 time, compare the wood engraving machine P3 for making wavy lines with H2, and every t2 time, compare the accuracy coefficients P of the remaining two wood engraving machines with H2 respectively; j If D i = 4, then every t2 time, compare the accuracy coefficients P of the three wood engraving machines with H2 respectively, where t1 < t2; if P j ≥ H2, it indicates that the machine tool is in normal working condition, and the status coefficient E j = 1; if P j < H2, it indicates that the accuracy of the machine tool is too low and damage may occur, which is an abnormal working condition, and the status coefficient E j = 0. j

[0037] Furthermore, the specific steps for the alarm unit to issue an alarm are as follows:

[0038] When the status coefficient E j = 1, the alarm device corresponding to the wood engraving machine does not operate; when the status coefficient E j = 0, the alarm device corresponding to the wood engraving machine operates, and at the same time, the wood engraving machine stops operating and waits for inspection and repair.

[0039] Technical effects and advantages of the present invention:

[0040] 1. This system adds the original texture of the uncarved solid wood surface as an important condition for selecting the types of carved solid wood surface patterns, making the patterns of the solid wood surface to be carved have similarities with the corresponding standard patterns. The identical parts do not need to be carved, thus greatly reducing energy consumption and time consumption;

[0041] 2. This system divides the monitoring status into different types according to the number of solid wood surfaces to be carved, so as to ensure high efficiency in detecting faults of the engraving machine tools while minimizing the monitoring cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the accompanying drawings;

[0043] Figure 1 It is a schematic structural diagram of the first embodiment of the present invention;

[0044] Figure 2 It is a schematic structural diagram of the second embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION​

[0045] Next, in combination with the accompanying drawings in the embodiments of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0046] Embodiment 1

[0047] As Figure 1 shown, a monitoring system for the preparation of multi-layer solid wood floors based on a data analysis model needs to mainly include a solid wood skin data acquisition unit, a solid wood skin data analysis unit, a texture image acquisition unit, an image feature extraction unit, a texture image comparison unit, and a decision-making processing unit.

[0048] First, the solid wood skin data acquisition unit collects data on relevant information of n un-etched solid wood skins of the same batch, including the water content of the solid wood skin, the thickness of the solid wood skin, and the elastic modulus of the solid wood skin.

[0049] It should be noted that the water content of the solid wood skin is a very important parameter, which will interact with the environmental humidity, thus affecting the material properties and aesthetics of the floor. If the water content of the un-etched solid wood skin is too high, it will cause problems such as floor swelling, deformation, and cracking. At the same time, it is also easy to cause the growth of mold and bacteria, affecting the hygiene and health of the floor. If the water content of the un-etched solid wood skin is too low, the stability of the floor will become poor, and problems such as cracking and deformation will easily occur. The greater the thickness of the solid wood skin, the better the performance of the floor and the longer the service life of the floor. The elastic modulus of the solid wood skin represents the ratio of the elastic stress to the elastic strain per unit area. The higher the elastic modulus, the better the stability and anti-torsion rate of the floor.

[0050] Send the collected data of the un-etched solid wood skin to the solid wood skin data analysis unit, and according to the formula obtain the quality coefficient A of the un-etched solid wood skin i . Among them, MC represents the water content of the solid wood skin, H represents the thickness of the solid wood skin, E represents the elastic modulus of the solid wood skin, i=(1,2,…,n) represents the i-th un-etched solid wood skin, a1 and a2 are weight factors, and a1 > a2, a1 + a2 = 1.021. The larger the quality coefficient A of the un-etched solid wood skin i , the better the performance of the un-etched solid wood skin.

[0051] Set a reference value H1, and for each of the n un-etched solid wood skins, the quality coefficient A of the un-etched solid wood skin iCompare their magnitudes with H1 respectively. When A i ≥H1, it indicates that the unpatterned solid wood surface is qualified, and the determination coefficient B i =1; when A i <H1, it indicates that the unpatterned solid wood surface is unqualified, and the determination coefficient B i =0.

[0052] The texture image acquisition unit performs texture image acquisition on the qualified unpatterned solid wood surface, that is, the unpatterned solid wood surface with B i =1, acquires the texture images of each solid wood surface and sends them to the image feature extraction unit.

[0053] The function of the texture image feature extraction unit is to extract relevant information reflecting the texture information of the unpatterned solid wood surface from the image. Since it is necessary to be very sensitive to the differences in different textures and exclude the influence of irrelevant factors such as light, two-dimensional Gabor wavelet transform is used to extract features from the image. Using (where ) as the filter, the image is converted from the time domain to the frequency domain. The specific steps are as follows:

[0054] Since color images are very sensitive to the light source and are greatly affected by light, first, the texture images of the unpatterned solid wood surface are grayscale-converted to eliminate the influence of light on subsequent judgments. The conversion formula is Gray = 0.299*R + 0.587*G + 0.114*B, where R, G, and B represent the pixel values of the three primary colors of red, green, and blue respectively, and Gray represents the grayscale value obtained by converting the pixel point, with a size of 0 - 255. According to the distribution of the number of different grayscale values among all pixel points, the grayscale distribution of the texture grayscale image of the solid wood surface can be obtained

[0055] Then, the Gabor filter is convolved with the image grayscale distribution to obtain the characteristic amplitude of the texture of the solid wood surface where convolution is a mathematical operation widely used in signal processing and image processing. It is to superimpose two signals and obtain a new signal by gradually moving one of the signals. This new signal describes the interaction between the two signals. Through the convolution operation, the local features of the image can be extracted.

[0056] Finally, the characteristic information of the texture of the unpatterned solid wood surface is extracted through the characteristic amplitude .

[0057] Through these three steps, the irrelevant information on the original solid wood surface image can be discarded, and only the important information about the texture is retained, making the extracted texture image feature information more complete, concise, and accurate.

[0058] In actual production, the textures of solid wood surfaces include straight grain, diagonal grain, and wavy grain. The texture image comparison unit compares the frequency domain signals extracted by the texture image feature extraction unit with the frequency domain signals of the three standard solid wood surface textures one by one, and analyzes which standard solid wood surface texture the unengraved solid wood surface texture is more similar to. The support vector machine classification algorithm is used to complete the classification of two categories by establishing the maximum classification surface. Through the inner product function find the optimal classification surface. Three independent support vector machine classifiers are used. If the textures recognized by two classifiers are straight grains, it means that the unengraved solid wood surface texture is more similar to the straight grain, and the category parameter C i is set to 1; if the textures recognized by two classifiers are diagonal grains, it means that the unengraved solid wood surface texture is more similar to the diagonal grain, and the category parameter C i is set to 2; if the textures recognized by two classifiers are wavy grains, it means that the unengraved solid wood surface texture is more similar to the wavy grain, and the category parameter C i is set to 3.

[0059] The texture image comparison unit transfers the obtained category parameter to the decision-making processing unit. If C i = 1, the unengraved solid wood surface is transferred to the wood board engraving machine for making straight grains; if C i = 2, the unengraved solid wood surface is transferred to the wood board engraving machine for making diagonal grains; if C i = 3, the unengraved solid wood surface is transferred to the wood board engraving machine for making wavy grains.

[0060] Embodiment 2

[0061] As Figure 2 shown, the monitoring system for preparing multi-layer solid wood floors based on the data analysis model also needs to include a machine tool data acquisition unit, a machine tool data processing unit, and an alarm unit. Since the number of solid wood surfaces to be engraved by each engraving machine is different, and the processing time of the solid wood surfaces in the same batch is fixed, the engraving rate of the engraving machine is controlled by adjusting the spindle speed of each engraving machine, while minimizing energy consumption and failure rate and ensuring engraving accuracy. At the same time, since the engraving machine may malfunction and be damaged during high-intensity operation, it needs to be detected regularly, and the probability of malfunction and damage is higher with stronger operating intensity, so the engraving machine with strong operating intensity needs to be monitored more closely.

[0062] The machine tool data acquisition unit collects the number of solid wood surfaces to be carved, the internal working temperature, the integrity of the tool head, and the relative error of the spindle speed for each of the three machine tools.

[0063] The number of solid wood surfaces to be carved by the wood engraving machine for making straight grains is N1, the number of solid wood surfaces to be carved by the wood engraving machine for making twill grains is N2, and the number of solid wood surfaces to be carved by the wood engraving machine for making wavy grains is N 3。

[0064] Set the reference value Z. If N1 ≥ Z% * (N1 + N2 + N3), then the wood engraving machine for making straight grains has a heavy workload and needs to be overhauled key, and the overhaul type D i = 1; if N2 ≥ Z% * (N1 + N2 + N3), then the wood engraving machine for making twill grains has a heavy workload and needs to be overhauled key, and the overhaul type D i = 2; if N3 ≥ Z% * (N1 + N2 + N3), then the wood engraving machine for making straight grains has a heavy workload and needs to be overhauled key, and the overhaul type D i = 3; if none of the above situations apply, it means that the quantities of N1, N2, and N3 are relatively average, and the overhaul type D i = 4.

[0065] It should be noted that the higher the internal working temperature of the machine tool, the more likely the machine tool components will deform or even be damaged, resulting in poor machine tool accuracy; the formula for the integrity of the tool head is (|actual tool head length - original tool head length| / original tool head length) * 100%, the better the tool head, the higher the machine tool accuracy; the relative error of the spindle speed; the formula for the relative error of the spindle speed is (|actual speed - rated speed| / rated speed) * 100%, the smaller the relative error, the higher the machine tool accuracy.

[0066] Transfer the collected data to the machine tool data processing unit, and according to the formula calculate the machine tool accuracy coefficient P i . Among them, W represents the integrity of the tool head, R represents the relative error of the spindle speed, T represents the internal working temperature of the machine tool, and j = 1, 2, 3, representing the wood engraving machines for making straight grains, twill grains, and wavy grains respectively. The larger P j , the higher the machine tool accuracy.

[0067] Set the reference value H2. If D i = 1, then every t1 time, compare the P1 of the wood engraving machine for making straight grains with H2, and every t2 time, compare the accuracy coefficients P of the remaining two wood engraving machines j with H2 respectively; if D i = 1, then every t1 time, compare the P1 of the wood engraving machine for making straight grains with H2, and every t2 time, compare the accuracy coefficients P of the remaining two wood engraving machines jCompare with H2 respectively; if D i = 2, then every t1 time, compare the wood engraving machine P2 for making twill with H2, and every t2 time, compare the precision coefficients P of the remaining two wood engraving machines j with H2 respectively; if D i = 3, then every t1 time, compare the wood engraving machine P3 for making wavy lines with H2, and every t2 time, compare the precision coefficients P of the remaining two wood engraving machines j with H2 respectively; if D i = 4, then every t2 time, compare the precision coefficients P of the three wood engraving machines j with H2 respectively, where t1 < t2. If P j ≥ H2, it means that the machine tool is in normal working condition, and the status coefficient E j = 1; if P j < H2, it means that the precision of the machine tool is too low and damage may occur, which is an abnormal working condition, and the status coefficient E j = 0.

[0068] Transmit the value of E j to the alarm unit. When E j = 1, the alarm device of the corresponding wood engraving machine does not operate; when E j = 0, the alarm device of the corresponding wood engraving machine operates, and at the same time, the wood engraving machine stops running and waits for inspection and repair. After the inspection and repair are completed, the alarm device stops running and the wood engraving machine starts working again.

[0069] The above formulas are all dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data and performing software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by technicians in this field according to the actual situation.

[0070] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the processes or functions described in the embodiments of the present application are generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center in a wired or wireless (such as infrared, wireless, microwave, etc.) manner. The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more collections of available media. The available medium can be a magnetic medium (such as a floppy disk, hard disk, or magnetic tape), an optical medium (such as a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state drive.

[0071] It should be understood that the term "and / or" in this document is merely a description of the association relationship between associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. Here, A and B can be singular or plural. In addition, the character " / " in this document generally represents an "or" relationship between the associated objects before and after, but it may also represent an "and / or" relationship, which can be specifically understood with reference to the context before and after.

[0072] In this application, "at least one" means one or more, and "a plurality" means two or more. "At least one of the following" or a similar expression refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can represent: a, b, c, a - b, a - c, b - c, or a - b - c, where a, b, and c can be single or multiple.

[0073] It should be understood that in various embodiments of the present application, the magnitudes of the sequence numbers of the above processes do not mean the order of execution. The order of execution of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application.

[0074] Those of ordinary skill in the art will realize that the units and algorithm steps of each example described in combination with the embodiments disclosed herein can be implemented by electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are executed in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods to implement the described functions for each specific application, but such implementation should not be considered to exceed the scope of this application.

[0075] In several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the displayed or discussed couplings or direct couplings or communication connections to each other can be through some interfaces. The indirect couplings or communication connections of devices or units can be in electrical, mechanical, or other forms.

[0076] The units described as separate components may or may not be physically separated. The components displayed as units may or may not be physical units, that is, they can be located in one place, or distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0077] In addition, the functional units in each embodiment of this application can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit.

[0078] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or this part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in each embodiment of this application. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical discs that can store program codes.

[0079] As described above, it is only the specific implementation manner of the present application. However, the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered within the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims described above.

Claims

1. A monitoring system for the preparation of multi-layer solid wood floors based on a data analysis model, characterized in that: It includes a solid wood skin data acquisition unit, a solid wood skin data analysis unit, a texture image acquisition unit, an image feature extraction unit, a texture image comparison unit, a decision-making processing unit, a machine tool data acquisition unit, a machine tool data processing unit, and an alarm unit; The solid wood skin data acquisition unit is used to collect the moisture content, thickness, and elastic modulus information of the solid wood skin, and transmit this information to the solid wood skin data analysis unit; The solid wood skin data analysis unit performs comprehensive arithmetic processing on the received data information, generates qualified and unqualified signals for the equipment accordingly, and transmits the generated signals to the texture image acquisition unit; The texture image acquisition unit collects the texture image information of the solid wood skin with a qualified signal and transmits it to the image feature extraction unit; The image feature extraction unit extracts the texture feature information of the image and transmits it to the texture image comparison unit; The texture image comparison unit compares the extracted feature information with the three standard texture feature information of straight grain, diagonal grain, and wavy grain, generates a category parameter signal, and sends the category parameter signal to the decision-making processing unit; The decision-making processing unit distributes the unengraved solid wood skin to the wood board engraving machines for manufacturing straight grain, diagonal grain, and wavy grain respectively according to the category parameter signal; The machine tool data acquisition unit collects the number of solid wood skins to be engraved, the internal working temperature, the integrity of the tool head, and the relative error of the spindle speed of each of the three machine tools, and transmits the information to the machine tool data processing unit; The machine tool data processing unit divides the machine tools into a state of key monitoring of the wood board engraving machine for manufacturing straight grain, a state of key monitoring of the wood board engraving machine for manufacturing diagonal grain, a state of key monitoring of the wood board engraving machine for manufacturing wavy grain, and a state of non-key monitoring according to the number of solid wood skins engraved by each machine tool. According to different states, the machine tools are divided into a normal working state and an abnormal working state according to different standards, and transmits their state information to the alarm unit; The alarm unit performs corresponding different treatments on the machine tools according to the different received state information.

2. The monitoring system for the preparation of solid wood multi-layer floors based on the data analysis model according to claim 1, wherein, The specific steps for performing comprehensive arithmetic processing on the solid wood skin data are as follows: S1: The solid wood skin data analysis unit calculates the quality coefficient Ai of the solid wood skin according to the moisture content, thickness, and elastic modulus information of the solid wood skin. The formula for the quality coefficient Ai of the solid wood skin is , where MC represents the moisture content of the solid wood surface, H represents the thickness of the solid wood surface, E represents the elastic modulus of the solid wood surface, i = (1, 2, …, n) represents the i-th unpatterned solid wood surface, and a1, a2 are weighting factors, and a1 > a2; S2: Set the reference value H1, and compare the quality coefficient A of each unpatterned solid wood skin among the n unpatterned solid wood skins with H1 respectively. i When A i ≥H1, it indicates that the unpatterned solid wood skin is qualified, and the judgment coefficient B i =1; when A i <H1, it indicates that the unpatterned solid wood skin is unqualified, and the judgment coefficient B i =0.

3. The monitoring system for the preparation of solid wood multi-layer floors based on the data analysis model according to claim 2, characterized in that, The operation of the texture image acquisition unit is as follows: The collection is qualified, that is, the determination coefficient B i = 1 unpatterned solid wood surface texture image.

4. The monitoring system for the preparation of solid wood multi-layer floors based on the data analysis model according to claim 3, characterized in that, The specific steps for extracting features from the texture image are as follows: S1: Use the formula to grayscale the image, where R, G, and B represent the pixel values of the three primary colors red, green, and blue respectively, and Gray represents the grayscale value obtained by converting the image pixel points; S2: Obtain the gray-scale distribution of the gray-scale image of the solid wood surface texture according to the distribution of the number of different gray-scale values among all pixel points ; S3: Take as the Gabor filter and convolve it with the grayscale distribution of the image to obtain the feature amplitude of the texture of the solid wood surface , and extract the local features of the image through the convolution operation; where is the j-th Gabor basis function, , is the j-th two-dimensional wave vector, i is the imaginary unit to ensure that the filter can capture both amplitude and phase features simultaneously, v is the direction index used to discretely rotate the Gabor kernel to cover all principal directions in the range of 0–π, and u is the scale index that determines the center frequency of the filter; S4: Through the feature amplitude Extract the feature information of the unpatterned solid wood surface texture.

5. The monitoring system for the preparation of multi-layer solid wood floors based on the data analysis model according to claim 4, characterized in that, The specific comparison method of the texture image comparison unit is as follows: Using the support vector machine classification algorithm, compare the texture feature information of the solid wood surface with the three standard feature information of straight grain, oblique grain, and wavy grain, and find the optimal classification surface through the inner product function is the decay width coefficient of the Gaussian kernel. Three independent support vector machine classifiers are used. If the texture recognized by two classifiers is straight grain, set the class parameter C If the texture recognized by two classifiers is oblique grain, set the class parameter C i = 1; if the texture recognized by two classifiers is wavy grain, set the class parameter C i = 2; if the texture recognized by two classifiers is wavy grain, set the class parameter C i = 3.

6. The monitoring system for the preparation of solid wood multi-layer floors based on the data analysis model according to claim 5, characterized in that, The processing method of the decision-making processing unit is as follows: If the category parameter Ci = 1, then transmit the unengraved solid wood skin to the wood board engraving machine for manufacturing straight grain; if the category parameter Ci = 2, then transmit the unengraved solid wood skin to the wood board engraving machine for manufacturing diagonal grain; if the category parameter Ci = 3, then transmit the unengraved solid wood skin to the wood board engraving machine for manufacturing wavy grain.

7. The monitoring system for the preparation of multi-layer solid wood floors based on the data analysis model according to claim 6, characterized in that, The specific steps for processing by the machine tool data processing unit are as follows: S1: The number of solid wood surfaces to be engraved by the straight-grain wood engraving machine is N1, the number of solid wood surfaces to be engraved by the diagonal-grain wood engraving machine is N2, and the number of solid wood surfaces to be engraved by the wavy-grain wood engraving machine is N 3； S2: Set the reference value Z. If N1 ≥ Z% * (N1 + N2 + N3), it means the working load of the wood engraving machine for making straight grains is large and requires key maintenance. At this time, the maintenance type D i = 1; If N2 ≥ Z% * (N1 + N2 + N3), it means the working load of the wood engraving machine for making twill grains is large and requires key maintenance. At this time, the maintenance type D i = 2; If N3 ≥ Z% * (N1 + N2 + N3), it means the working load of the wood engraving machine for making straight grains is large and requires key maintenance. At this time, the maintenance type D i = 3; If none of these three situations occur, it means the quantities of N1, N2, and N3 are relatively average. At this time, the maintenance type D i = 4; S3: Calculate the machine tool precision coefficient P according to the formula where W represents the tool tip integrity, R represents the relative error of the spindle speed, T represents the internal working temperature of the machine tool, and j = 1, 2, 3 represent the wood engraving machines for making straight grain, twill, and wavy grain boards respectively; i ​ S4: Set the reference value H2. If D i = 1, then every t1 time, compare the wood engraving machine P1 for making straight grain with H2, and every t2 time, compare the accuracy coefficients P j of the remaining two wood engraving machines with H2 respectively; if D i = 1, then every t1 time, compare the wood engraving machine P1 for making straight grain with H2, and every t2 time, compare the accuracy coefficients P j of the remaining two wood engraving machines with H2 respectively; if D i = 2, then every t1 time, compare the wood engraving machine P2 for making twill with H2, and every t2 time, compare the accuracy coefficients P j of the remaining two wood engraving machines with H2 respectively; if D i = 3, then every t1 time, compare the wood engraving machine P3 for making wavy grain with H2, and every t2 time, compare the accuracy coefficients P j of the remaining two wood engraving machines with H2 respectively; if D i = 4, then every t2 time, compare the accuracy coefficients P j of the three wood engraving machines with H2 respectively, where t1 < t2; if P j ≥ H2, it indicates that the machine tool is in normal working condition, and the status coefficient E j = 1; if P j < H2, it indicates that the accuracy of the machine tool is too low and it is in an abnormal working condition, and the status coefficient E j = 0.

8. The monitoring system for the preparation of multi-layer solid wood floors based on the data analysis model according to claim 7, characterized in that, The specific steps for the alarm unit to issue an alarm are as follows: When the status coefficient E j = 1, the alarm device of the wood board engraving machine does not operate; when the status coefficient E j = 0, the alarm device of the corresponding wood board engraving machine operates, and at the same time, the wood board engraving machine stops operating and waits for inspection and repair.

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