Cloth inspecting system capable of automatically controlling dryness and humidity in garment processing

Abstract

The invention discloses a cloth inspecting system capable of automatically controlling dryness and humidity in garment processing, and relates to the field of cloth inspecting. Comprising a data acquisition module, and the data acquisition module comprises a temperature sensor, a humidity sensor and a material identification module; the data preprocessing module is used for preprocessing the data acquired by the sensor; the central processing module is used for analyzing and identifying the preprocessed data and generating control logic; the control module is used for generating a control instruction according to the control logic; and the execution module comprises a humidifying unit and a drying unit, and the humidifying unit or the drying unit performs corresponding execution according to the control instruction of the control module. According to the invention, the material and the humidity are identified firstly, and then drying or humidifying is carried out according to the set threshold value, so that the humidity of the cloth is ensured, array type micro-fog humidifying is adopted, the humidifying uniformity is improved, meanwhile, temperature data can be acquired, data compensation is carried out on the sensor by utilizing temperature, and the data acquisition precision is improved.

Description

Technical Field

[0001] This invention relates to the field of fabric inspection, and more particularly to a fabric inspection system for automatically controlling the humidity in garment processing. Background Technology

[0002] In the garment manufacturing industry, fabric inspection systems, as core equipment for fabric quality control, play a crucial role in detecting surface defects, color differences, and weft skew before cutting. These systems typically consist of a lighting source, a conveying mechanism, an image acquisition unit, and a manual or automated inspection platform. Through high-precision visual scanning of the continuously moving fabric surface, they locate and classify fabric defects. In actual operation, it has been found that environmental humidity has a significant impact on garment fabrics primarily composed of natural fibers. Due to the inherent hygroscopic properties of fibers such as cotton, linen, silk, and wool, irreversible microscopic deformation occurs with fluctuations in air humidity, leading to abnormal wrinkles or shrinkage on the fabric surface. Such visual interference can easily be confused with genuine defects, resulting in a higher rate of missed detections. Especially for high-count, high-density fabrics, the electrostatic adsorption effect caused by excessively low humidity will cause environmental dust and impurities to adhere to the fabric surface, while excessively high humidity will alter light transmittance and cause edge blurring artifacts in the image analysis system.

[0003] Current mainstream fabric inspection equipment only has static temperature and humidity control devices, which fail to take into account the humidity gradient changes caused by spatial differences during fabric operation. When the workshop environment changes drastically or different fiber materials are mixed for inspection, traditional methods are difficult to maintain the stability of the fabric's moisture content throughout the process.

[0004] Therefore, this invention proposes a fabric inspection system that can automatically control the humidity in garment processing. Summary of the Invention

[0005] The purpose of this invention is to address the shortcomings of existing technologies by proposing a fabric inspection system that can automatically control the humidity in garment processing.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A fabric inspection system for garment processing that can automatically control humidity includes: The data acquisition module includes a temperature sensor, a humidity sensor, and a material identification module. The data preprocessing module preprocesses the data collected by the sensors; The central processing module analyzes and identifies the preprocessed data and generates control logic. The control module generates control commands based on the control logic. The execution module includes a humidification unit and a drying unit, which execute accordingly based on the control instructions from the control module. The fabric inspection unit is responsible for inspecting the quality of the fabric after humidity control.

[0007] Preferably, the humidity sensor is a multispectral humidity sensor, and the material identification module determines the fabric material by analyzing the fabric composition through near-infrared spectroscopy.

[0008] Preferably, the humidification unit is a high-pressure micro-mist nozzle array, and the drying unit is a combination of a PTC semiconductor temperature control board and an air curtain.

[0009] Preferably, the working logic of the fabric inspection system is as follows: S1: The administrator pre-sets the humidity threshold range for each type of fabric based on its material. S2: The material identification module in the data acquisition module uses infrared spectroscopy analysis to obtain the material information of the fabric, and the humidity sensor obtains the humidity information of the fabric. S3: The temperature sensor acquires temperature information, and the data preprocessing module performs temperature compensation on the material spectrum and humidity spectrum based on the temperature information to obtain the calibrated material and humidity; S4: The central processing module compares the corresponding material humidity with the preset humidity threshold range and generates control logic; S5: The control module generates corresponding control commands based on the control logic; S6: The humidification unit or drying unit humidifies or dries the fabric according to the control command.

[0010] Preferably, in step S3, data preprocessing further includes data verification.

[0011] The data verification includes the following steps: SA31: Acquires sampling data from each sensor based on the sampling time node of the main control unit; SA32: If the sampled data is unique, the verification is correct; otherwise, the verification fails. SA33: Data that fails verification will have all data in that node deleted, and then the formula will be used. Replace the data at this node. P represents the data collected at the i-th time point prior to the current time point, where P is the replacement data.

[0012] Preferably, in step S3, the temperature compensation method includes the following steps: SB31: Place a cloth with known humidity or material in a closed experimental space; SB32: The temperature in the experimental space is continuously changed, and temperature and humidity or material information is obtained through sensors. SB33: Establish a coordinate system with temperature as the x-axis and the difference between the sensor's collected value and the actual value as the y-axis, and fill the coordinate system with the data points collected in step SB32; SB34: The data points are connected to form a data curve using the least squares fitting method, and the mathematical expression of the curve is the temperature compensation model.

[0013] Preferably, in step S4, the generation of control logic includes the following steps: S41: Set the error tolerance ratio coefficient ; S42: Obtain the temperature-compensated humidity value M, and the corresponding humidity threshold for the material. ; S43: If M < (1- ) Then the control logic is to start the humidification unit; S44: If M > (1 + ... ) Then the control logic is to start the drying unit; S45: If (1- ) ≤M≤M>(1+ ) Then there is no need for humidification and drying.

[0014] Preferably: In step S43, the starting power of the humidification unit is , where k1 is the coefficient of the power and humidification capacity of the humidification unit.

[0015] Preferably: In step S44, the starting power of the drying unit is , where k1 is the coefficient of the power and drying capacity of the drying unit.

[0016] The beneficial effects of this invention are as follows: This invention first identifies the material and humidity, and then dries or humidifies according to a set threshold, thereby ensuring the humidity of the fabric. It also uses an array-type micro-mist humidification to increase the uniformity of humidification. At the same time, it can collect temperature data and use temperature to compensate for the data of the sensor, thereby increasing the accuracy of data acquisition. Attached Figure Description

[0017] Figure 1 This is a flowchart of a fabric inspection system for automatically controlling the humidity in garment processing, as proposed in this invention. Detailed Implementation

[0018] The technical solution of the present invention will be further described in detail below with reference to specific embodiments.

[0019] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "setting" should be interpreted broadly. For example, they can refer to a fixed connection or setting, a detachable connection or setting, or an integral connection or setting. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0020] Example 1: A fabric inspection system for automatically controlling humidity in garment processing, comprising: The data acquisition module includes a temperature sensor, a humidity sensor, and a material identification module. The data preprocessing module preprocesses the data collected by the sensors; The central processing module analyzes and identifies the preprocessed data and generates control logic. The control module generates control commands based on the control logic. The execution module includes a humidification unit and a drying unit, which execute accordingly based on the control instructions from the control module. The fabric inspection unit is responsible for inspecting the quality of the fabric after humidity control.

[0021] The humidity sensor is a multispectral humidity sensor, and the material identification module determines the fabric material by analyzing the fabric composition through near-infrared spectroscopy.

[0022] The humidification unit is a high-pressure micro-mist nozzle array, and the drying unit is a combination of a PTC semiconductor temperature control board and an air curtain.

[0023] The working logic of the fabric inspection system is as follows: S1: The administrator pre-sets the humidity threshold range for each type of fabric based on its material. S2: The material identification module in the data acquisition module uses infrared spectroscopy analysis to obtain the material information of the fabric, and the humidity sensor obtains the humidity information of the fabric. S3: The temperature sensor acquires temperature information, and the data preprocessing module performs temperature compensation on the material spectrum and humidity spectrum based on the temperature information to obtain the calibrated material and humidity; S4: The central processing module compares the corresponding material humidity with the preset humidity threshold range and generates control logic; S5: The control module generates corresponding control commands based on the control logic; S6: The humidification unit or drying unit humidifies or dries the fabric according to the control command.

[0024] Example 2: A fabric inspection system for automatically controlling humidity in garment processing, comprising: The data acquisition module includes a temperature sensor, a humidity sensor, and a material identification module. The data preprocessing module preprocesses the data collected by the sensors; The central processing module analyzes and identifies the preprocessed data and generates control logic. The control module generates control commands based on the control logic. The execution module includes a humidification unit and a drying unit, which execute accordingly based on the control instructions from the control module. The fabric inspection unit is responsible for inspecting the quality of the fabric after humidity control.

[0025] The humidity sensor is a multispectral humidity sensor, and the material identification module determines the fabric material by analyzing the fabric composition through near-infrared spectroscopy.

[0026] The humidification unit is a high-pressure micro-mist nozzle array, and the drying unit is a combination of a PTC semiconductor temperature control board and an air curtain.

[0027] The working logic of the fabric inspection system is as follows: S1: The administrator pre-sets the humidity threshold range for each type of fabric based on its material. S2: The material identification module in the data acquisition module uses infrared spectroscopy analysis to obtain the material information of the fabric, and the humidity sensor obtains the humidity information of the fabric. S3: The temperature sensor acquires temperature information, and the data preprocessing module performs temperature compensation on the material spectrum and humidity spectrum based on the temperature information to obtain the calibrated material and humidity; S4: The central processing module compares the corresponding material humidity with the preset humidity threshold range and generates control logic; S5: The control module generates corresponding control commands based on the control logic; S6: The humidification unit or drying unit humidifies or dries the fabric according to the control command.

[0028] In step S3, data preprocessing also includes data verification.

[0029] The data verification includes the following steps: SA31: Acquires sampling data from each sensor based on the sampling time node of the main control unit; SA32: If the sampled data is unique, the verification is correct; otherwise, the verification fails. SA33: Data that fails verification will have all data in that node deleted, and then the formula will be used. Replace the data at this node. P represents the data collected at the i-th time point prior to the current time point, where P is the replacement data. In step S3, the temperature compensation method includes the following steps: SB31: Place a cloth with known humidity or material in a closed experimental space; SB32: The temperature in the experimental space is continuously changed, and temperature and humidity or material information is obtained through sensors. SB33: Establish a coordinate system with temperature as the x-axis and the difference between the sensor's collected value and the actual value as the y-axis, and fill the coordinate system with the data points collected in step SB32; SB34: The data points are connected to form a data curve using the least squares fitting method, and the mathematical expression of the curve is the temperature compensation model.

[0030] Example 3: A fabric inspection system for automatically controlling humidity in garment processing, comprising: The data acquisition module includes a temperature sensor, a humidity sensor, and a material identification module. The data preprocessing module preprocesses the data collected by the sensors; The central processing module analyzes and identifies the preprocessed data and generates control logic. The control module generates control commands based on the control logic. The execution module includes a humidification unit and a drying unit, which execute accordingly based on the control instructions from the control module. The fabric inspection unit is responsible for inspecting the quality of the fabric after humidity control.

[0031] The humidity sensor is a multispectral humidity sensor, and the material identification module determines the fabric material by analyzing the fabric composition through near-infrared spectroscopy.

[0032] The humidification unit is a high-pressure micro-mist nozzle array, and the drying unit is a combination of a PTC semiconductor temperature control board and an air curtain.

[0033] The working logic of the fabric inspection system is as follows: S1: The administrator pre-sets the humidity threshold range for each type of fabric based on its material. S2: The material identification module in the data acquisition module uses infrared spectroscopy analysis to obtain the material information of the fabric, and the humidity sensor obtains the humidity information of the fabric. S3: The temperature sensor acquires temperature information, and the data preprocessing module performs temperature compensation on the material spectrum and humidity spectrum based on the temperature information to obtain the calibrated material and humidity; S4: The central processing module compares the corresponding material humidity with the preset humidity threshold range and generates control logic; S5: The control module generates corresponding control commands based on the control logic; S6: The humidification unit or drying unit humidifies or dries the fabric according to the control command.

[0034] In step S3, data preprocessing also includes data verification.

[0035] The data verification includes the following steps: SA31: Acquires sampling data from each sensor based on the sampling time node of the main control unit; SA32: If the sampled data is unique, the verification is correct; otherwise, the verification fails. SA33: Data that fails verification will have all data in that node deleted, and then the formula will be used. Replace the data at this node. P represents the data collected at the i-th time point prior to the current time point, where P is the replacement data. In step S3, the temperature compensation method includes the following steps: SB31: Place a cloth with known humidity or material in a closed experimental space; SB32: The temperature in the experimental space is continuously changed, and temperature and humidity or material information is obtained through sensors. SB33: Establish a coordinate system with temperature as the x-axis and the difference between the sensor's collected value and the actual value as the y-axis, and fill the coordinate system with the data points collected in step SB32; SB34: The data points are connected to form a data curve using the least squares fitting method, and the mathematical expression of the curve is the temperature compensation model.

[0036] In step S4, the generation of control logic includes the following steps: S41: Set the error tolerance ratio coefficient ; S42: Obtain the temperature-compensated humidity value M, and the corresponding humidity threshold for the material. ; S43: If M < (1- ) Then the control logic is to start the humidification unit; S44: If M > (1 + ... ) Then the control logic is to start the drying unit; S45: If (1- ) ≤M≤M>(1+ ) Then there is no need for humidification and drying.

[0037] In step S43, the starting power of the humidification unit is , where k1 is the coefficient of the power and humidification capacity of the humidification unit.

[0038] In step S44, the starting power of the drying unit is , where k1 is the coefficient of the power and drying capacity of the drying unit.

[0039] This invention first identifies the material and humidity, and then dries or humidifies according to a set threshold, thereby ensuring the humidity of the fabric. It also uses an array-type micro-mist humidification to increase the uniformity of humidification. At the same time, it can collect temperature data and use temperature to compensate for the data of the sensor, thereby increasing the accuracy of data acquisition.

[0040] The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A fabric inspection system for automatically controlling the moisture content in garment processing, characterized in that, include: The data acquisition module includes a temperature sensor, a humidity sensor, and a material identification module. The data preprocessing module preprocesses the data collected by the sensors; The central processing module analyzes and identifies the preprocessed data and generates control logic. The control module generates control commands based on the control logic. The execution module includes a humidification unit and a drying unit, which execute accordingly based on the control instructions from the control module. The fabric inspection unit is responsible for inspecting the quality of the fabric after humidity control.

2. The fabric inspection system for automatically controlling humidity in garment processing according to claim 1, characterized in that, The humidity sensor is a multispectral humidity sensor, and the material identification module determines the fabric material by analyzing the fabric composition through near-infrared spectroscopy.

3. The fabric inspection system for automatically controlling humidity in garment processing according to claim 1, characterized in that, The humidification unit is a high-pressure micro-mist nozzle array, and the drying unit is a combination of a PTC semiconductor temperature control board and an air curtain.

4. A fabric inspection system for automatically controlling humidity in garment processing according to any one of claims 1-3, characterized in that, The working logic of the fabric inspection system is as follows: S1: The administrator pre-sets the humidity threshold range for each type of fabric based on its material. S2: The material identification module in the data acquisition module uses infrared spectroscopy analysis to obtain the material information of the fabric, and the humidity sensor obtains the humidity information of the fabric. S3: The temperature sensor acquires temperature information, and the data preprocessing module performs temperature compensation on the material spectrum and humidity spectrum based on the temperature information to obtain the calibrated material and humidity; S4: The central processing module compares the corresponding material humidity with the preset humidity threshold range and generates control logic; S5: The control module generates corresponding control commands based on the control logic; S6: The humidification unit or drying unit humidifies or dries the fabric according to the control command.

5. A fabric inspection system for automatically controlling humidity in garment processing according to claim 4, characterized in that, In step S3, data preprocessing also includes data verification.

6. A fabric inspection system for automatically controlling humidity in garment processing according to claim 5, characterized in that, The data verification includes the following steps: SA31: Acquires sampling data from each sensor based on the sampling time node of the main control unit; SA32: If the sampled data is unique, the verification is correct; otherwise, the verification fails. SA33: Data that fails verification will have all data in that node deleted, and then the formula will be used. Replace the data at this node. P represents the data collected at the i-th time point prior to the current time point, where P is the replacement data.

7. A fabric inspection system for automatically controlling humidity in garment processing according to claim 4, characterized in that, In step S3, the temperature compensation method includes the following steps: SB31: Place a cloth with known humidity or material in a closed experimental space; SB32: The temperature in the experimental space is continuously changed, and temperature and humidity or material information is obtained through sensors. SB33: Establish a coordinate system with temperature as the x-axis and the difference between the sensor's collected value and the actual value as the y-axis, and fill the coordinate system with the data points collected in step SB32; SB34: The data points are connected to form a data curve using the least squares fitting method, and the mathematical expression of the curve is the temperature compensation model.

8. A fabric inspection system for automatically controlling humidity in garment processing according to claim 4, characterized in that, In step S4, the generation of control logic includes the following steps: S41: Set the error tolerance ratio coefficient ; S42: Obtain the temperature-compensated humidity value M, and the corresponding humidity threshold for the material. ; S43: If M < (1- ) Then the control logic is to start the humidification unit; S44: If M > (1 + ... ) Then the control logic is to start the drying unit; S45: If (1- ) ≤M≤M>(1+ ) Then there is no need for humidification and drying.

9. A fabric inspection system for automatically controlling humidity in garment processing according to claim 8, characterized in that, In step S43, the starting power of the humidification unit is , where k1 is the coefficient of the power and humidification capacity of the humidification unit.

10. A fabric inspection system for automatically controlling humidity in garment processing according to claim 8, characterized in that, In step S44, the starting power of the drying unit is , where k1 is the coefficient of the power and drying capacity of the drying unit.

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