Intelligent clothing cutting and discharging system and process based on digital twinning and machine vision

Abstract

The invention discloses an intelligent clothing cutting and discharging system and process based on digital twinning and machine vision, and relates to the technical field of intelligent clothing manufacturing. The system comprises a quantum-level dynamic sensing module which excites quantum dots of cloth through ultraviolet rays to generate dual-band fluorescence, and micro-strain distribution is captured through a hyperspectral camera; establishing a stress-spectrum mapping model; the light field real-time twinning module is combined with a stress-spectrum model and a machine vision image to construct a cloth real-time twinning model; the biological intelligent discharging module adopts a mucus foraging model to determine an optimal arrangement scheme of cutting pieces; the metamaterial active cloth stabilizing module detects vibration through a laser vibration meter at the moment that the cutter is in contact with the cloth, calculates and emits offset waves in real time, and stabilizes the cloth; and the intelligent tailoring execution module completes tailoring according to the arrangement scheme and the cloth stabilizing effect. According to the system, high precision, intelligence and high efficiency of tailoring and arrangement are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent clothing manufacturing, and more specifically, to an intelligent clothing cutting and nesting system and process based on digital twins and machine vision. Background Art

[0002] In the field of clothing manufacturing, cutting and nesting has always been a key bottleneck in production efficiency and quality. Traditional methods mainly rely on manual experience and simple automated equipment, and have many limitations. First, the fabric is easily affected by external forces and produces micro-strain during the cutting process, and traditional methods are difficult to perceive and feedback these tiny changes in real time, resulting in reduced cutting accuracy; secondly, most of the existing nesting algorithms are based on fixed rules, and fail to fully consider the actual physical properties of the fabric, such as texture, elastic modulus, etc., as well as the complex relationship between the pieces, resulting in low fabric utilization and poor nesting efficiency; in addition, the vibration problem of the fabric during the cutting process has not been effectively solved, which not only affects the cutting quality, but may also shorten the service life of the equipment. More importantly, there is a lack of real-time dynamic monitoring and optimization of the cutting process, making it difficult to adapt to complex and changing production needs. With the advancement of technology, With continuous progress, cutting-edge technologies such as digital twins, machine vision, quantum technology and metamaterials have gradually matured, providing new ideas and methods for solving these problems. Digital twin technology can construct virtual mappings of physical entities and realize real-time monitoring and optimization of entities; machine vision plays an important role in industrial inspection and automated production with its high-precision image acquisition and analysis capabilities; quantum technology shows unique advantages at the microscopic perception level, and the fluorescent properties of quantum dot materials can be used for high-sensitivity strain detection; the emergence of metamaterials provides a new way to regulate the mechanical properties of structures, and its special acoustic properties can be used for vibration control. The integration of these technologies into the intelligent cutting and nesting system for clothing is expected to improve the traditional cutting and nesting mode, realize intelligent, high-precision and efficient cutting and nesting, and promote technological upgrading in the clothing manufacturing industry.

[0003] Therefore, the existing cutting and laying-out methods have problems such as low cutting accuracy, poor laying-out efficiency, and insufficient fabric stability. Summary of the Invention

[0004] In order to overcome the problems of low cutting accuracy, poor nesting efficiency, and insufficient fabric stability in existing cutting and nesting methods, the present invention discloses an intelligent clothing cutting and nesting system and process based on digital twins and machine vision, which can effectively solve the above technical problems.

[0005] In order to solve the above technical problems, the technical solutions of the present invention are as follows:

[0006] The intelligent clothing cutting and marking system based on digital twin and machine vision is characterized by including:

[0007] A quantum-level dynamic sensing module is used to use ultraviolet light to excite quantum dots in fabrics to emit dual-band fluorescence, capture microstrain distribution through a hyperspectral camera, and establish a stress-spectrum mapping model λ = f(σ, E, v);

[0008] The light field real-time twin module is used to build a light field real-time twin model of fabric based on the stress-spectrum mapping model and fabric images collected by machine vision;

[0009] A bio-intelligent nesting module, which uses the mathematical representation of the slime mold foraging model to perform bio-intelligent nesting of garment pieces and determine the optimal arrangement of the pieces on the fabric;

[0010] The metamaterial active fabric stabilization module is used to detect the amplitude through a laser vibrometer when the piezoelectric cutter contacts the fabric, and calculate the anti-phase acoustic wave field p in real time. anti (x,y)=-p0e i(ωt-k·r) H(ω), and controlling the acoustic metasurface array to emit cancelling waves;

[0011] The intelligent cutting execution module is used to intelligently cut the fabric according to the optimal arrangement plan and the active stabilization effect of the metamaterial.

[0012] Preferably, the quantum-level dynamic perception module includes:

[0013] The quantum dot excitation unit is used to control the ultraviolet light source to irradiate the quantum dot material on the surface of the fabric at a preset intensity and angle, thereby exciting the quantum dots to emit dual-band fluorescence signals;

[0014] The micro-strain acquisition unit is used to image the fabric surface with a millisecond sampling frequency using a hyperspectral camera to obtain a hyperspectral image sequence containing dual-band fluorescence information, and obtain the micro-strain distribution data on the fabric surface through spectral unmixing and strain inversion calculation;

[0015] The model building unit is used to establish a stress-spectrum mapping model λ=f(σ,E,v) according to the microstrain distribution data, wherein λ represents the spectral characteristics, σ represents the stress, E represents the elastic modulus, and ν represents the Poisson's ratio.

[0016] Preferably, the light field real-time twin module includes:

[0017] An image acquisition unit, used for acquiring surface feature images of texture, color and wrinkles of the fabric through a machine vision system;

[0018] A data fusion unit is used to align the internal stress distribution data of the fabric calculated by the stress-spectrum mapping model with the surface feature image collected by machine vision in time and space;

[0019] The twin model construction unit is used to construct a real-time twin model of the light field of the cloth based on the data after time and space alignment using three-dimensional modeling technology. The model can be updated in real time and present the dynamic changes of the cloth during the cutting process.

[0020] Preferably, the biological intelligent discharge module includes:

[0021] The piece abstraction unit is used to abstract clothing pieces into nodes in the slime mold's foraging path and the cuttable areas of the fabric into the foraging environment.

[0022] The weight calculation unit is used to establish the connection weight function between nodes according to the shape, size, texture and defect information of the cut piece;

[0023] The solution generation unit is used to iteratively calculate the arrangement path of the pieces based on the mathematical model of mycelium growth and nutrient absorption during the slime mold foraging process until the optimal arrangement plan of the pieces on the fabric is obtained.

[0024] Preferably, the metamaterial active stabilization module includes:

[0025] A vibration detection unit is used to install a laser vibrometer on the piezoelectric cutter head to collect vibration displacement, velocity and acceleration data of the fabric surface in real time when the cutter contacts the fabric;

[0026] The acoustic wave calculation unit is used to calculate the inverse acoustic wave field p in real time through the wave equation solver based on the collected vibration data, combined with the material parameters and boundary conditions of the fabric. anti (x,y);

[0027] The acoustic wave emission unit is used to transmit the calculated anti-phase acoustic wave field parameters to the acoustic metasurface array controller, control the acoustic metasurface array to emit a cancellation wave that offsets the acoustic wave generated by the vibration of the fabric, and suppress the vibration of the fabric.

[0028] Preferably, the intelligent cutting execution module includes:

[0029] An instruction generation unit, used to convert the optimal arrangement plan into a cutting path instruction and send it to the intelligent cutting device;

[0030] The fabric stabilization monitoring unit is used to monitor the active fabric stabilization effect of the metamaterial in real time during the cutting process. When the vibration of the fabric is detected to exceed the preset threshold, the acoustic metasurface array's acoustic wave emission parameters are dynamically adjusted;

[0031] The cutting execution unit is used for intelligent cutting equipment to complete high-precision cutting of fabrics according to cutting path instructions and real-time fabric stabilization status.

[0032] Preferably, the intelligent clothing cutting and marking process based on digital twin and machine vision includes the following steps:

[0033] Ultraviolet light is used to excite quantum dots in fabric to emit dual-band fluorescence, and a hyperspectral camera is used to capture the microstrain distribution. A stress-spectrum mapping model λ = f(σ, E, v) is then established.

[0034] Based on the stress-spectrum mapping model and fabric images collected by machine vision, a real-time twin model of the fabric's light field is constructed;

[0035] Using the mathematical representation of the slime mold foraging model, we perform bio-intelligent nesting of garment pieces and determine the optimal arrangement of the pieces on the fabric.

[0036] When the piezoelectric cutter contacts the fabric, the amplitude is detected by a laser vibrometer and the anti-phase acoustic wave field is calculated in real time. And control the acoustic metasurface array to emit cancellation waves, where p anti (x,y) represents the offset wave, p0 represents the initial amplitude, ω represents the angular frequency, k represents the wave number, r represents the position, and H(ω) represents the frequency response function;

[0037] The fabric is intelligently cut based on the optimal arrangement plan and the active stabilization effect of the metamaterial.

[0038] Preferably, the establishing of the stress-spectrum mapping model includes:

[0039] Control the ultraviolet light source to irradiate the quantum dot material on the surface of the fabric at a preset intensity and angle, exciting the quantum dots to emit dual-band fluorescence signals;

[0040] A hyperspectral camera is used to image the fabric surface at a millisecond sampling frequency to obtain a hyperspectral image sequence containing dual-band fluorescence information. Spectral unmixing and strain inversion calculations are then performed to obtain the microstrain distribution data on the fabric surface.

[0041] A stress-spectrum mapping model λ=f(σ, E, v) is established based on the microstrain distribution data.

[0042] Preferably, the step of constructing a light field real-time twin model of the cloth includes:

[0043] Capture images of the texture, color, and wrinkle surface features of the fabric through a machine vision system;

[0044] The internal stress distribution data of the fabric calculated by the stress-spectrum mapping model is spatially and temporally aligned with the surface feature image acquired by machine vision;

[0045] Based on the time-space aligned data, 3D modeling technology is used to construct a real-time light field twin model of the cloth. The model can update in real time and present the dynamic changes of the cloth during the cutting process.

[0046] Preferably, the real-time calculation of the anti-phase acoustic wave field and the control of the acoustic metasurface array to emit the cancellation wave include:

[0047] A laser vibrometer is installed on the piezoelectric cutter head to collect the vibration displacement, velocity and acceleration data of the fabric surface in real time when the cutter contacts the fabric.

[0048] According to the collected vibration data, combined with the material parameters and boundary conditions of the fabric, the antiphase acoustic wave field p is calculated in real time through the wave equation solver. anti (x,y);

[0049] The calculated anti-phase acoustic wave field parameters are transmitted to the acoustic metasurface array controller, which controls the acoustic metasurface array to emit cancellation waves that offset the sound waves generated by the vibration of the fabric, thereby suppressing the vibration of the fabric.

[0050] Compared with the existing technology, the beneficial effects of the present invention are as follows: the intelligent clothing cutting and nesting system of the present invention uses ultraviolet rays to excite fabric quantum dots to emit dual-band fluorescence through the quantum-level dynamic perception module, and the hyperspectral camera captures the micro-strain distribution and establishes a stress-spectrum mapping model, thereby realizing accurate monitoring of the stress state of the fabric, providing accurate data for cutting, improving cutting accuracy, reducing cutting errors and scrap rates; the light field real-time twin module constructs a real-time twin model of the fabric based on the model and the images collected by machine vision, realizing visualization and real-time monitoring of the cutting process, enabling operators to promptly discover and adjust abnormal situations, and further improving cutting quality and efficiency; the biological intelligent nesting module adopts slime mold foraging The model abstracts the cutting pieces and fabric areas into nodes and foraging environments respectively, establishes a weight function based on the cutting piece characteristics and fabric information, and iteratively calculates the optimal layout plan, effectively improving fabric utilization and reducing production costs; the metamaterial active fabric stabilization module collects fabric vibration data through a laser vibrometer at the moment of cutting, calculates and emits offset waves in real time, suppresses fabric vibration, enhances fabric stability, reduces cutting deviations caused by vibration, and extends equipment life; the intelligent cutting execution module accurately executes cutting tasks based on the optimal layout plan and fabric stabilization effect to achieve high-precision cutting. The modules work closely together, and the highly intelligent system improves the degree of production automation, reduces labor costs, and enhances production stability and consistency. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the implementation methods of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the implementation methods or the description of the prior art. Obviously, the drawings described below are merely exemplary. For ordinary technicians in this field, other implementation drawings can be derived based on the provided drawings without any creative work.

[0052] Figure 1 This is a system structure diagram of the present invention;

[0053] Figure 2 It is a process flow chart of the present invention. DETAILED DESCRIPTION

[0054] The accompanying drawings are for illustrative purposes only and are not to be construed as limiting this patent;

[0055] In order to better illustrate this embodiment, some parts in the drawings may be omitted, enlarged, or reduced, and do not represent the actual product size;

[0056] It is understandable to those skilled in the art that some well-known structures and descriptions thereof may be omitted in the drawings.

[0057] The technical solution of the present invention is further described below with reference to the accompanying drawings and embodiments.

[0058] Example 1

[0059] See also Figure 1 , a clothing intelligent cutting and marking system based on digital twin and machine vision, including:

[0060] A quantum-level dynamic sensing module is used to use ultraviolet light to excite quantum dots in fabrics to emit dual-band fluorescence, capture microstrain distribution through a hyperspectral camera, and establish a stress-spectrum mapping model λ = f(σ, E, v);

[0061] The light field real-time twin module is used to build a light field real-time twin model of fabric based on the stress-spectrum mapping model and fabric images collected by machine vision;

[0062] A bio-intelligent nesting module, which uses the mathematical representation of the slime mold foraging model to perform bio-intelligent nesting of garment pieces and determine the optimal arrangement of the pieces on the fabric;

[0063] The metamaterial active fabric stabilization module is used to detect the amplitude through a laser vibrometer when the piezoelectric cutter contacts the fabric, and calculate the anti-phase acoustic wave field p in real time. anti (x,y)=-p0e i(ωt-k·r) H(ω), and controlling the acoustic metasurface array to emit cancelling waves;

[0064] The intelligent cutting execution module is used to intelligently cut the fabric according to the optimal arrangement plan and the active stabilization effect of the metamaterial.

[0065] The quantum level dynamic perception module includes:

[0066] The quantum dot excitation unit is used to control the ultraviolet light source to irradiate the quantum dot material on the surface of the fabric at a preset intensity and angle, thereby exciting the quantum dots to emit dual-band fluorescence signals;

[0067] The micro-strain acquisition unit is used to image the fabric surface with a millisecond sampling frequency using a hyperspectral camera to obtain a hyperspectral image sequence containing dual-band fluorescence information, and obtain the micro-strain distribution data on the fabric surface through spectral unmixing and strain inversion calculation;

[0068] The model building unit is used to establish a stress-spectrum mapping model λ=f(σ,E,v) according to the microstrain distribution data, wherein λ represents the spectral characteristics, σ represents the stress, E represents the elastic modulus, and ν represents the Poisson's ratio.

[0069] The light field real-time twin module includes:

[0070] An image acquisition unit, used for acquiring surface feature images of texture, color and wrinkles of the fabric through a machine vision system;

[0071] A data fusion unit is used to align the internal stress distribution data of the fabric calculated by the stress-spectrum mapping model with the surface feature image collected by machine vision in time and space;

[0072] The twin model construction unit is used to construct a real-time twin model of the light field of the cloth based on the data after time and space alignment using three-dimensional modeling technology. The model can be updated in real time and present the dynamic changes of the cloth during the cutting process.

[0073] The biological intelligent discharge module includes:

[0074] The piece abstraction unit is used to abstract clothing pieces into nodes in the slime mold's foraging path and the cuttable areas of the fabric into the foraging environment.

[0075] The weight calculation unit is used to establish the connection weight function between nodes according to the shape, size, texture and defect information of the cut piece;

[0076] The solution generation unit is used to iteratively calculate the arrangement path of the pieces based on the mathematical model of mycelium growth and nutrient absorption during the slime mold foraging process until the optimal arrangement plan of the pieces on the fabric is obtained.

[0077] The metamaterial active stabilization module includes:

[0078] A vibration detection unit is used to install a laser vibrometer on the piezoelectric cutter head to collect vibration displacement, velocity and acceleration data of the fabric surface in real time when the cutter contacts the fabric;

[0079] The acoustic wave calculation unit is used to calculate the inverse acoustic wave field p in real time through the wave equation solver based on the collected vibration data, combined with the material parameters and boundary conditions of the fabric. anti (x,y);

[0080] The acoustic wave emission unit is used to transmit the calculated anti-phase acoustic wave field parameters to the acoustic metasurface array controller, control the acoustic metasurface array to emit a cancellation wave that offsets the acoustic wave generated by the vibration of the fabric, and suppress the vibration of the fabric.

[0081] The intelligent cutting execution module includes:

[0082] An instruction generation unit, used to convert the optimal arrangement plan into a cutting path instruction and send it to the intelligent cutting device;

[0083] The fabric stabilization monitoring unit is used to monitor the active fabric stabilization effect of the metamaterial in real time during the cutting process. When the vibration of the fabric is detected to exceed the preset threshold, the acoustic metasurface array's acoustic wave emission parameters are dynamically adjusted;

[0084] The cutting execution unit is used for intelligent cutting equipment to complete high-precision cutting of fabrics according to cutting path instructions and real-time fabric stabilization status.

[0085] The quantum-level dynamic sensing module uses ultraviolet light to excite the quantum dot material in the fabric, causing it to emit dual-band fluorescence signals. These signals are captured by a hyperspectral camera to obtain micro-strain distribution data on the fabric surface. The specific steps are as follows:

[0086] The quantum dot excitation unit uses a control unit to operate an ultraviolet light source to irradiate the quantum dot material on the surface of the fabric at a preset intensity and angle, exciting the quantum dots to emit dual-band fluorescence signals.

[0087] The micro-strain acquisition unit uses a hyperspectral camera to image the fabric surface and obtains a hyperspectral image sequence containing dual-band fluorescence information at a millisecond sampling frequency.

[0088] The model building unit uses spectral unmixing and strain inversion calculation techniques to obtain microstrain distribution data on the fabric surface from the hyperspectral image sequence, and based on this, establishes a stress-spectrum mapping model λ = f(σ, E, v). This model correlates spectral characteristics (λ), stress (σ), elastic modulus (E) and Poisson's ratio (ν) to provide accurate stress data for subsequent cutting operations.

[0089] The light field real-time twin module builds a light field real-time twin model of the fabric based on the stress-spectrum mapping model and fabric images collected by machine vision. The specific steps are as follows:

[0090] The image acquisition unit acquires surface feature images of the texture, color and wrinkles of the cloth through a machine vision system.

[0091] The data fusion unit performs spatiotemporal alignment between the internal stress distribution data of the fabric calculated by the stress-spectrum mapping model and the surface feature image acquired by machine vision.

[0092] The twin model construction unit uses three-dimensional modeling technology to build a real-time twin model of the light field of the fabric based on the data aligned in time and space. This model can update and present the dynamic changes of the fabric during the cutting process in real time, providing the operator with a visual interface for the cutting process.

[0093] The bio-intelligent nesting module uses the mathematical representation of the slime mold foraging model to perform bio-intelligent nesting on garment pieces and determine the optimal arrangement of the pieces on the fabric. The specific steps are as follows:

[0094] The piece abstraction unit abstracts clothing pieces as nodes in the slime mold's foraging path and abstracts the cuttable area of ​​the fabric as the foraging environment.

[0095] The weight calculation unit establishes a connection weight function between nodes according to the shape, size, fabric texture and defect information of the pieces.

[0096] The solution generation unit iteratively calculates the arrangement path of the pieces based on the mathematical model of mycelium growth and nutrient absorption during the slime mold's foraging process until the optimal arrangement plan of the pieces on the fabric is obtained.

[0097] The metamaterial active fabric stabilization module detects the amplitude of the piezoelectric cutter using a laser vibrometer at the moment it contacts the fabric, calculates the anti-phase acoustic wave field in real time, and controls the acoustic metasurface array to emit a canceling wave. The specific steps are as follows:

[0098] The vibration detection unit installs a laser vibrometer on the piezoelectric cutter head to collect the vibration displacement, velocity and acceleration data of the fabric surface in real time at the moment the cutter contacts the fabric.

[0099] The acoustic wave calculation unit calculates the antiphase acoustic wave field in real time through a wave equation solver based on the collected vibration data and combined with the material parameters and boundary conditions of the fabric.

[0100] The acoustic wave emission unit transmits the calculated anti-phase acoustic wave field parameters to the acoustic metasurface array controller, controlling the acoustic metasurface array to emit a cancellation wave that offsets the acoustic wave generated by the vibration of the fabric, thereby suppressing the vibration of the fabric.

[0101] The intelligent cutting execution module performs intelligent cutting of the fabric based on the optimal arrangement plan and the active stabilization effect of the metamaterial. The specific steps are as follows:

[0102] The instruction generation unit converts the optimal arrangement plan into a cutting path instruction and sends it to the intelligent cutting device.

[0103] During the cutting process, the fabric stabilization monitoring unit monitors the active fabric stabilization effect of the metamaterial in real time. When it detects that the fabric vibration exceeds the preset threshold, it dynamically adjusts the sound wave emission parameters of the acoustic metasurface array.

[0104] The intelligent cutting equipment of the cutting execution unit completes high-precision cutting of the fabric according to the cutting path instructions and the real-time stable fabric status.

[0105] Example 2

[0106] See also Figure 2 The intelligent clothing cutting and nesting process based on digital twins and machine vision includes the following steps:

[0107] Ultraviolet light is used to excite quantum dots in fabric to emit dual-band fluorescence, and a hyperspectral camera is used to capture the microstrain distribution. A stress-spectrum mapping model λ = f(σ, E, v) is then established.

[0108] Based on the stress-spectrum mapping model and fabric images collected by machine vision, a real-time twin model of the fabric's light field is constructed;

[0109] Using the mathematical representation of the slime mold foraging model, we perform bio-intelligent nesting of garment pieces and determine the optimal arrangement of the pieces on the fabric.

[0110] When the piezoelectric cutter contacts the fabric, the amplitude is detected by a laser vibrometer and the anti-phase acoustic wave field is calculated in real time. And control the acoustic metasurface array to emit cancellation waves, where p anti (x,y) represents the offset wave, p0 represents the initial amplitude, ω represents the angular frequency, k represents the wave number, r represents the position, and H(ω) represents the frequency response function;

[0111] The fabric is intelligently cut based on the optimal arrangement plan and the active stabilization effect of the metamaterial.

[0112] The establishment of the stress-spectrum mapping model comprises:

[0113] Control the ultraviolet light source to irradiate the quantum dot material on the surface of the fabric at a preset intensity and angle, exciting the quantum dots to emit dual-band fluorescence signals;

[0114] A hyperspectral camera is used to image the fabric surface at a millisecond sampling frequency to obtain a hyperspectral image sequence containing dual-band fluorescence information. Spectral unmixing and strain inversion calculations are then performed to obtain the microstrain distribution data on the fabric surface.

[0115] A stress-spectrum mapping model λ=f(σ, E, v) is established based on the microstrain distribution data.

[0116] The construction of the real-time light field twin model of the cloth includes:

[0117] Capture images of the texture, color, and wrinkle surface features of the fabric through a machine vision system;

[0118] The internal stress distribution data of the fabric calculated by the stress-spectrum mapping model is spatially and temporally aligned with the surface feature image acquired by machine vision;

[0119] Based on the time-space aligned data, 3D modeling technology is used to construct a real-time light field twin model of the cloth. The model can update in real time and present the dynamic changes of the cloth during the cutting process.

[0120] The real-time calculation of the anti-phase acoustic wave field and the control of the acoustic metasurface array to emit the cancellation wave include:

[0121] A laser vibrometer is installed on the piezoelectric cutter head to collect the vibration displacement, velocity and acceleration data of the fabric surface in real time when the cutter contacts the fabric.

[0122] According to the collected vibration data, combined with the material parameters and boundary conditions of the fabric, the antiphase acoustic wave field p is calculated in real time through the wave equation solver. anti (x,y);

[0123] The calculated anti-phase acoustic wave field parameters are transmitted to the acoustic metasurface array controller, which controls the acoustic metasurface array to emit cancellation waves that offset the sound waves generated by the vibration of the fabric, thereby suppressing the vibration of the fabric.

[0124] Ultraviolet light is used to excite quantum dots in fabric to emit dual-band fluorescence, and a hyperspectral camera is used to capture the microstrain distribution, and a stress-spectrum mapping model is established.

[0125] Based on the stress-spectrum mapping model and fabric images collected by machine vision, a real-time light field twin model of the fabric is constructed.

[0126] The mathematical representation of the slime mold foraging model is used to perform bio-intelligent nesting of clothing pieces and determine the optimal arrangement of the pieces on the fabric.

[0127] At the moment when the piezoelectric cutter touches the fabric, the amplitude is detected by the laser vibrometer, the anti-phase acoustic wave field is calculated in real time, and the acoustic metasurface array is controlled to emit a cancellation wave p anti (x,y)=-p0e i(ω tk·r ) H(ω), where p anti (x, y) represents the cancellation wave, p0 represents the initial amplitude, ω represents the angular frequency, k represents the wave number, r represents the position, and H(ω) represents the frequency response function.

[0128] The fabric is intelligently cut based on the optimal arrangement plan and the active stabilization effect of the metamaterial.

[0129] In the specific process, a UV light source is used to irradiate the quantum dot material on the surface of the fabric to stimulate the quantum dots to emit dual-band fluorescence signals.

[0130] A hyperspectral camera is used to image the fabric surface at a millisecond sampling frequency to obtain a hyperspectral image sequence containing dual-band fluorescence information.

[0131] Through spectral unmixing and strain inversion calculation, the micro-strain distribution data of the cloth surface is obtained from the hyperspectral image sequence.

[0132] A stress-spectrum mapping model is established based on the microstrain distribution data, where λ represents the spectral feature λ = f(σ, E, v), σ represents stress, E represents elastic modulus, and ν represents Poisson's ratio.

[0133] The surface feature images of the fabric’s texture, color, and wrinkles are captured by a machine vision system.

[0134] The internal stress distribution data of the fabric calculated by the stress-spectrum mapping model is temporally and spatially aligned with the surface feature image acquired by machine vision.

[0135] Based on the time-space aligned data, 3D modeling technology is used to construct a real-time light field twin model of the fabric. This model can update and present the dynamic changes of the fabric during the cutting process in real time.

[0136] The clothing pieces are abstracted as nodes in the slime mold's foraging path, and the cuttable areas of the fabric are abstracted as the foraging environment.

[0137] The connection weight function between nodes is established based on the shape, size, fabric texture and defect information of the pieces.

[0138] Based on the mathematical model of mycelial growth and nutrient absorption during the slime mold's foraging process, the arrangement path of the pieces is iteratively calculated until the optimal arrangement plan of the pieces on the fabric is obtained.

[0139] Based on the calculated layout path, the optimal layout plan for the pieces on the fabric is generated.

[0140] A laser vibrometer is installed on the piezoelectric cutter head to collect the vibration displacement, velocity and acceleration data of the fabric surface in real time at the moment the cutter contacts the fabric.

[0141] Based on the collected vibration data, combined with the material parameters and boundary conditions of the fabric, the antiphase acoustic wave field is calculated in real time through the wave equation solver.

[0142] The calculated anti-phase acoustic wave field parameters are transmitted to the acoustic metasurface array controller, which controls the acoustic metasurface array to emit cancellation waves that offset the sound waves generated by the vibration of the fabric, thereby suppressing the vibration of the fabric.

[0143] The optimal arrangement plan is converted into cutting path instructions and sent to the intelligent cutting device.

[0144] During the cutting process, the effect of active stabilization of the metamaterial is monitored in real time. When the vibration of the fabric is detected to exceed the preset threshold, the sound wave emission parameters of the acoustic metasurface array are dynamically adjusted.

[0145] Intelligent cutting equipment completes high-precision cutting of fabrics based on cutting path instructions and real-time fabric stability status. During the cutting process, high-precision control and feedback mechanisms are used to ensure cutting accuracy and efficiency.

[0146] Through the above embodiments, this system and process can realize intelligent clothing cutting and laying out based on digital twins and machine vision, with the characteristics of high precision, high efficiency and intelligence.

[0147] The same or similar reference numerals correspond to the same or similar components;

[0148] The terms used in the drawings to describe positional relationships are for illustrative purposes only and should not be construed as limiting this patent;

[0149] Obviously, the above embodiments of the present invention are merely examples for clearly illustrating the present invention, and are not limitations on the implementation methods of the present invention. For ordinary technicians in the field, other different forms of changes or modifications can be made based on the above description. It is not necessary and impossible to enumerate all the implementation methods here. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present invention should be included in the scope of protection of the claims of the present invention.

Claims

1. The intelligent clothing cutting and marking system based on digital twin and machine vision is characterized by: include: A quantum-level dynamic sensing module is used to use ultraviolet light to excite quantum dots in fabrics to emit dual-band fluorescence, capture microstrain distribution through a hyperspectral camera, and establish a stress-spectrum mapping model λ = f(σ, E, v); The light field real-time twin module is used to build a light field real-time twin model of fabric based on the stress-spectrum mapping model and fabric images collected by machine vision; A bio-intelligent nesting module, which uses the mathematical representation of the slime mold foraging model to perform bio-intelligent nesting of garment pieces and determine the optimal arrangement of the pieces on the fabric; The metamaterial active fabric stabilization module is used to detect the amplitude through a laser vibrometer when the piezoelectric cutter contacts the fabric, and calculate the anti-phase acoustic wave field p in real time. anti (x,y)=-p0e i(ωt-k·r) H(ω), and controlling the acoustic metasurface array to emit cancelling waves; The intelligent cutting execution module is used to intelligently cut the fabric according to the optimal arrangement plan and the active stabilization effect of the metamaterial.

2. The system according to claim 1, wherein: The quantum level dynamic perception module includes: The quantum dot excitation unit is used to control the ultraviolet light source to irradiate the quantum dot material on the surface of the fabric at a preset intensity and angle, thereby exciting the quantum dots to emit dual-band fluorescence signals; The micro-strain acquisition unit is used to image the fabric surface with a millisecond sampling frequency using a hyperspectral camera to obtain a hyperspectral image sequence containing dual-band fluorescence information, and obtain the micro-strain distribution data on the fabric surface through spectral unmixing and strain inversion calculation; The model building unit is used to establish a stress-spectrum mapping model λ=f(σ,E,v) according to the microstrain distribution data, wherein λ represents the spectral characteristics, σ represents the stress, E represents the elastic modulus, and ν represents the Poisson's ratio.

3. The system according to claim 1, wherein: The light field real-time twin module includes: An image acquisition unit, used for acquiring surface feature images of texture, color and wrinkles of the fabric through a machine vision system; A data fusion unit is used to align the internal stress distribution data of the fabric calculated by the stress-spectrum mapping model with the surface feature image collected by machine vision in time and space; The twin model construction unit is used to construct a real-time twin model of the light field of the cloth based on the data after time and space alignment using three-dimensional modeling technology. The model can be updated in real time and present the dynamic changes of the cloth during the cutting process.

4. The system according to claim 1, wherein: The biological intelligent discharge module includes: The piece abstraction unit is used to abstract clothing pieces into nodes in the slime mold's foraging path and the cuttable areas of the fabric into the foraging environment. The weight calculation unit is used to establish the connection weight function between nodes according to the shape, size, texture and defect information of the cut piece; The solution generation unit is used to iteratively calculate the arrangement path of the pieces based on the mathematical model of mycelium growth and nutrient absorption during the slime mold foraging process until the optimal arrangement plan of the pieces on the fabric is obtained.

5. The system according to claim 1, wherein: The metamaterial active stabilization module includes: A vibration detection unit is used to install a laser vibrometer on the piezoelectric cutter head to collect vibration displacement, velocity and acceleration data of the fabric surface in real time when the cutter contacts the fabric; The acoustic wave calculation unit is used to calculate the inverse acoustic wave field p in real time through the wave equation solver based on the collected vibration data, combined with the material parameters and boundary conditions of the fabric. anti (x,y); The acoustic wave emission unit is used to transmit the calculated anti-phase acoustic wave field parameters to the acoustic metasurface array controller, control the acoustic metasurface array to emit a cancellation wave that offsets the acoustic wave generated by the vibration of the fabric, and suppress the vibration of the fabric.

6. The system according to claim 1, wherein: The intelligent cutting execution module includes: An instruction generation unit, used to convert the optimal arrangement plan into a cutting path instruction and send it to the intelligent cutting device; The fabric stabilization monitoring unit is used to monitor the active fabric stabilization effect of the metamaterial in real time during the cutting process. When the vibration of the fabric is detected to exceed the preset threshold, the acoustic metasurface array's acoustic wave emission parameters are dynamically adjusted; The cutting execution unit is used for intelligent cutting equipment to complete high-precision cutting of fabrics according to cutting path instructions and real-time fabric stabilization status.

7. A garment intelligent cutting and nesting process based on digital twins and machine vision, used to implement the system according to any one of claims 1 to 6, characterized in that: The following steps are involved: Ultraviolet light is used to excite quantum dots in fabric to emit dual-band fluorescence, and a hyperspectral camera is used to capture the microstrain distribution. A stress-spectrum mapping model λ = f(σ, E, v) is then established. Based on the stress-spectrum mapping model and fabric images collected by machine vision, a real-time twin model of the fabric's light field is constructed; Using the mathematical representation of the slime mold foraging model, we perform bio-intelligent nesting of garment pieces and determine the optimal arrangement of the pieces on the fabric. At the moment when the piezoelectric cutter touches the fabric, the amplitude is detected by the laser vibrometer and the antiphase acoustic wave field p is calculated in real time. anti (x,y)=-p0e i(ω tk·r ) ·H(ω), and control the acoustic metasurface array to emit cancellation waves, where p anti (x,y) represents the offset wave, p0 represents the initial amplitude, ω represents the angular frequency, k represents the wave number, r represents the position, and H(ω) represents the frequency response function; The fabric is intelligently cut based on the optimal arrangement plan and the active stabilization effect of the metamaterial.

8. The process according to claim 7, characterized in that The establishment of the stress-spectrum mapping model comprises: Control the ultraviolet light source to irradiate the quantum dot material on the surface of the fabric at a preset intensity and angle, exciting the quantum dots to emit dual-band fluorescence signals; A hyperspectral camera is used to image the fabric surface at a millisecond sampling frequency to obtain a hyperspectral image sequence containing dual-band fluorescence information. Spectral unmixing and strain inversion calculations are then performed to obtain the microstrain distribution data on the fabric surface. A stress-spectrum mapping model λ=f(σ, E, v) is established based on the microstrain distribution data.

9. The process according to claim 7, characterized in that The construction of the real-time light field twin model of the cloth includes: Capture images of the texture, color, and wrinkle surface features of the fabric through a machine vision system; The internal stress distribution data of the fabric calculated by the stress-spectrum mapping model is spatially and temporally aligned with the surface feature image acquired by machine vision; Based on the time-space aligned data, 3D modeling technology is used to construct a real-time light field twin model of the cloth. The model can update in real time and present the dynamic changes of the cloth during the cutting process.

10. The process according to claim 7, characterized in that The real-time calculation of the anti-phase acoustic wave field and the control of the acoustic metasurface array to emit the cancellation wave include: A laser vibrometer is installed on the piezoelectric cutter head to collect the vibration displacement, velocity and acceleration data of the fabric surface in real time when the cutter contacts the fabric. According to the collected vibration data, combined with the material parameters and boundary conditions of the fabric, the antiphase acoustic wave field p is calculated in real time through the wave equation solver. anti (x,y); The calculated anti-phase acoustic wave field parameters are transmitted to the acoustic metasurface array controller, which controls the acoustic metasurface array to emit cancellation waves that offset the sound waves generated by the vibration of the fabric, thereby suppressing the vibration of the fabric.

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