Textile processing procedure intelligent monitoring method based on intelligent terminal

Abstract

The invention relates to the technical field of textile processing, in particular to a textile processing procedure intelligent monitoring method based on an intelligent terminal, which comprises the following steps: determining a sampling frequency and a sampling amount according to the production of textile processing equipment within a certain time, and collecting a total sample according to the sampling frequency; performing linear density detection on the total sample; segmenting the total sample into a plurality of sub-samples according to the number and the type of the to-be-detected items; and performing corresponding item detection on each sub-sample. Sampling parameters are dynamically matched through production, the quality fluctuation detection rate is increased, and resource waste is avoided; unqualified samples are removed through linear density pre-detection, and the effectiveness of subsequent detection is guaranteed; the samples are segmented as required, and parameters are finely adjusted in combination with linear density to adapt to detection requirements; detection equipment is intelligently distributed, faults are handled, and the equipment utilization rate and the monitoring continuity are optimized. The intelligent terminal serves as a core, manual intervention is reduced, monitoring precision is achieved, intelligent upgrading of textile processing procedures is assisted, and efficient operation of a production line and stable product quality are ensured.

Description

Technical Field

[0001] This invention relates to the field of textile processing technology, and in particular to a method for intelligent monitoring of textile processing procedures based on smart terminals. Background Technology

[0002] With the continuous development of technology, more and more textile yarn production factories are adopting intelligent equipment for production lines. These intelligent equipment and production quality are being monitored intelligently to promptly detect equipment malfunctions and fluctuations in production quality, allowing for timely maintenance and adjustment of process parameters to ensure efficient production line operation. The transformation of the textile industry towards intelligent and automated processes is driving increased demand for real-time and precise monitoring of the production process.

[0003] Current technologies for monitoring textile processing steps do not correlate with production volume and often use fixed-frequency sampling. If production volume increases sharply, the fixed sampling volume may not be able to cover the quality fluctuation range; if production volume decreases, oversampling will result in sample waste. Repeated testing of a single sample for multiple items can easily lead to sample loss and cross-interference of test results.

[0004] Therefore, it is necessary to propose an intelligent monitoring method for textile processing procedures based on smart terminals to solve the above problems. Summary of the Invention

[0005] The purpose of this invention is to provide an intelligent monitoring method for textile processing based on smart terminals, in order to solve the problems that when production volume increases sharply, a fixed sampling volume may not be able to cover the quality fluctuation range; when production volume decreases, oversampling will cause sample waste; and repeated testing of a single sample for multiple items will easily lead to sample loss and cross-interference of test results.

[0006] To achieve the above objectives, the present invention provides the following technical solution: Intelligent monitoring methods for textile processing steps based on smart terminals include: The sampling frequency and sampling volume are determined based on the production volume of textile processing equipment within a certain period of time, and the total sample of the corresponding sampling volume is collected according to the sampling frequency. Linear density was measured on the total sample. The total sample is divided into multiple subsamples based on the number and type of items to be tested. Each subsample is assigned to the corresponding item for testing.

[0007] Preferably, the sampling frequency and sampling volume are determined based on the production volume of the textile processing equipment within a certain period of time, and a total sample of the corresponding sampling volume is collected according to the sampling frequency, including: The actual production data of the textile processing equipment during the regular production statistical cycle is collected through the sensors or data interfaces of the equipment, and the production data is transmitted to the smart terminal in real time. After receiving production data, the smart terminal automatically calculates and determines the corresponding sampling frequency and sampling quantity based on the preset production quantity and sampling association rules. The smart terminal sends the sampling frequency and sampling volume to the corresponding sampling device through instructions. The sampling device collects samples that meet the sampling volume requirements at the corresponding time nodes according to the instructions. All collected samples are summarized to form a total sample, and the collected signal is fed back to the smart terminal.

[0008] Preferably, linear density detection is performed on the total sample, including: After receiving the signal that the total sample collection is complete, the smart terminal automatically calls the preset linear density detection parameter library based on the textile type and production volume data associated with the total sample. Based on the linear density detection parameter library, the intelligent terminal automatically sets the detection parameters and sends a detection start command to the linear density detection equipment. The linear density testing equipment performs testing according to instructions to determine the linear density test results.

[0009] Preferably, after receiving the total sample line density detection results, the intelligent terminal automatically calls the corresponding acceptable line density threshold range, compares and calculates to determine the average line density value and fluctuation coefficient of the total sample: If the average linear density value is within the acceptable threshold and the fluctuation coefficient is less than or equal to the preset value, the total sample linear density is deemed acceptable and marked as a divisible sample. If the average linear density value is not within the acceptable threshold or the fluctuation coefficient is greater than the preset value, the total sample linear density is deemed unacceptable and marked as an indivisible sample.

[0010] Preferably, the total sample is divided into multiple sub-samples based on the number and type of items to be detected, including: The intelligent terminal retrieves the total sample of the separable samples; The smart terminal binds the total sample with the list of items to be detected to determine the basic data packet for segmentation; Based on the segmentation base data packet, according to the segmentation criteria corresponding to different detection items in the segmentation parameter association library built into the smart terminal, the corresponding segmentation parameters are retrieved from the association library according to the number and type of items. The smart terminal divides the total sample into multiple sub-samples according to the segmentation parameters.

[0011] Preferably, based on the segmentation parameters, the intelligent terminal fine-tunes the segmentation parameters by using the linear density values ​​of the segmentable samples.

[0012] Preferably, each subsample is assigned to a corresponding item for testing, including: The intelligent terminal monitors the status data of all connected testing devices in real time via industrial Ethernet, including busy, idle, and calibrating status. The intelligent terminal retrieves the latest calibration report of each testing device, extracts the accuracy parameters of the testing devices, and uses the accuracy requirements of the current sample to be tested as a benchmark to screen out devices that meet the accuracy standards through the device accuracy parameters; The intelligent terminal allocates testing equipment according to the type of testing project, accuracy requirements, and priority, and then uses the testing equipment to test the samples.

[0013] Preferably, when the intelligent terminal performs the allocation of testing equipment, it simultaneously collects the number of tasks to be tested and the estimated processing time of each task for each compliant equipment, calculates the equipment load value, and sorts the load values; for equipment with the same load value, it further retrieves the equipment's pass rate data and prioritizes allocating the sample to the equipment with the higher pass rate.

[0014] Preferably, after the intelligent terminal completes the allocation of testing equipment, it monitors the operating status of the target testing equipment and the progress of sub-sample testing in real time. If the testing equipment suddenly fails, the intelligent terminal immediately re-selects equipment from the equipment that meets the accuracy standard, and marks the status of the sub-samples that have not been tested in the original equipment as pending re-testing. After the new equipment receives the sub-sample, the intelligent terminal automatically synchronizes the testing parameters of the sub-sample to the new equipment, and the fault information of the faulty equipment and the sub-sample transfer record are transmitted to the intelligent terminal database in real time.

[0015] The technical effects and advantages of this invention are as follows: 1. This invention collects actual production data within a regular production statistical cycle. The intelligent terminal automatically calculates and determines the sampling frequency and sampling quantity based on preset production quantity and sampling association rules, replacing the traditional fixed frequency sampling mode, improving the detection rate of quality fluctuations, and effectively avoiding missed detections or oversampling caused by traditional manual setting of sampling parameters.

[0016] 2. Before sample segmentation, the present invention first calls the line density detection parameter library by the intelligent terminal to control the detection equipment to perform line density detection on the total sample. Then, it determines whether the sample is divisible by the dual indicators of average line density value and fluctuation coefficient, and eliminates the total sample with unqualified line density. This avoids the waste of resources caused by unqualified samples in the traditional process. On the other hand, the line density detection results provide basic data support for subsequent steps to ensure that the subsequent detection data can truly reflect the production quality.

[0017] 3. This invention binds the divisible total sample to the list of items to be tested via a smart terminal, retrieves basic segmentation parameters from the built-in detection item-segmentation parameter association library, and then fine-tunes them in conjunction with the total sample linear density value to finally complete the total sample segmentation. This avoids the problem of sample specifications not matching detection requirements caused by traditional random segmentation. By combining the fine-tuning parameters with the linear density value, it ensures that the subsamples can adapt to the detection accuracy requirements of different items, making the subsample detection data more representative. Attached Figure Description

[0018] Figure 1 This is a flowchart of the intelligent monitoring method for textile processing steps based on a smart terminal according to the present invention. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] This invention provides, for example Figure 1 The intelligent monitoring method for textile processing steps based on smart terminals shown includes: Step S1: Determine the sampling frequency and sampling quantity based on the production volume of the textile processing equipment within a certain period of time, and collect the total sample of the corresponding sampling quantity according to the sampling frequency.

[0021] Specifically, in this embodiment, the actual production volume data of the textile processing equipment during the regular production statistical cycle is collected through the sensors or data interfaces of the equipment, and the production volume data is transmitted to the smart terminal in real time. First, the actual production volume data of the textile processing equipment, such as spinning machines and looms, is collected through the sensors or data interfaces of the equipment in 4 hours, and the production volume data is transmitted to the smart terminal in real time. The production volume data includes yarn output, fabric length, etc.

[0022] After receiving production data, the smart terminal automatically calculates and determines the corresponding sampling frequency and sampling quantity based on the preset production quantity and sampling association rules.

[0023] Production volume is linked to sampling parameters. The higher the production volume, the higher the sampling frequency and the larger the sample size to cover more production batches and avoid missed detections due to quality fluctuations. The lower the production volume, the higher the sampling frequency and the larger the sample size are adjusted accordingly to reduce sample waste.

[0024] The smart terminal sends the sampling frequency and sampling volume to the corresponding sampling device through instructions. The sampling device collects samples that meet the sampling volume requirements at the corresponding time nodes according to the instructions. All collected samples are summarized to form a total sample, and the collected signal is fed back to the smart terminal.

[0025] The instructions sent by the intelligent terminal to the sampling device must include core information such as the target sampling device number, sampling time node details, precise value of a single sampling volume, and sample collection location specifications. These instructions are transmitted via industrial Ethernet in an encrypted format to prevent parameter tampering during data transmission. Upon receiving the instructions, the sampling device maintains clock synchronization with the intelligent terminal through its built-in time synchronization module, ensuring precise initiation of the sampling action at the set time node. After initiation, the device first guides the yarn or fabric output from the textile processing equipment smoothly to the length measurement module via a yarn guiding mechanism. When the length measurement module detects that the collected length has reached the sampling volume set in the instruction, the ultrasonic cutting blade immediately performs a cutting operation. After all sampling actions at the set time nodes are completed, the sampling device aggregates all single samples to form a total sample and sends a collection completion signal to the intelligent terminal via a data interface. This signal carries the total sample volume information. Upon receiving the signal, the intelligent terminal automatically verifies whether the total sample volume meets the preset requirements. If the verification passes, the total sample collection is marked as complete, preparing for the subsequent total sample linear density detection stage.

[0026] Step S2: Perform line density detection on the total sample.

[0027] Specifically, in this embodiment, after the smart terminal receives the signal that the total sample collection is complete, it automatically calls the preset linear density detection parameter library based on the textile type and production volume data associated with the total sample.

[0028] After receiving the total sample collection completion signal from the sampling device, the intelligent terminal first retrieves the core basic data associated with the total sample, including the textile type and the production volume data of the corresponding textile processing equipment. Then, based on this data, it automatically matches and calls the preset linear density detection parameter library. This parameter library contains the detection standards and parameters corresponding to different textile types and different production volume ranges. For example, for the total sample of pure cotton yarn with a production volume in the medium load range of 1001-1500 kg / hour, the preset detection standard in the parameter library is GB / T4743-2012 "Determination of linear density of yarn in packaged textiles". The detection parameters include detection length, detection speed, and constant temperature and humidity environment requirements.

[0029] Based on the linear density detection parameter library, the smart terminal automatically sets the detection parameters and sends a detection start command to the linear density detection equipment.

[0030] The intelligent terminal automatically sets the above detection parameters according to the parameter library data, generates a detection start command including the total sample number, detection standard, detection length, speed, and environmental parameters, and sends it to the line density detection equipment via industrial Ethernet.

[0031] The linear density testing equipment performs testing according to instructions to determine the linear density test results.

[0032] After receiving the total sample line density detection results, the smart terminal automatically calls the corresponding line density qualified threshold range, compares and calculates to determine the total sample average line density value and fluctuation coefficient.

[0033] If the average linear density value is within the acceptable threshold and the fluctuation coefficient is less than or equal to the preset value, the total sample linear density is deemed acceptable and marked as a divisible sample.

[0034] If the average linear density value is not within the acceptable threshold or the fluctuation coefficient is greater than the preset value, the total sample linear density is deemed unacceptable and marked as an indivisible sample.

[0035] After receiving the command, the linear density testing equipment automatically activates the environmental control module to adjust the environment inside the testing chamber to the set value. Then, the total sample is uniformly transported to the testing channel through the automatic yarn feeding mechanism. Simultaneously, the laser length measuring module records the transport length, and the high-precision weighing module collects the weight of the corresponding length of sample in real time. The linear density value is automatically calculated according to the formula: linear density = sample weight × testing length. The testing length is set to 1000m. During the testing process, instantaneous linear density data is recorded every 50m to statistically analyze the fluctuation coefficient. Finally, the linear density testing result is generated, which includes the average linear density value, fluctuation coefficient, and instantaneous testing data of each segment. The result is fed back to the intelligent terminal in real time through the data interface, providing a basis for subsequent total sample qualification judgment and sample segmentation.

[0036] Step S3: Divide the total sample into multiple subsamples according to the number and type of items to be detected.

[0037] Specifically, in this embodiment, the smart terminal retrieves the total sample of the divisible samples.

[0038] The intelligent terminal first retrieves the total sample data of samples that are determined to be divisible by the linear density detection from the system database. This data includes core information such as the total sample number, actual length, linear density value, and fluctuation coefficient, ensuring that the segmentation operation is only performed on samples that meet the basic parameters.

[0039] The smart terminal binds the total sample with the list of items to be detected in order to determine the basic data packet for segmentation.

[0040] Based on the segmentation base data packet, according to the segmentation criteria corresponding to different detection items in the segmentation parameter association library built into the smart terminal, the corresponding segmentation parameters are retrieved from the association library according to the number and type of items. The smart terminal divides the total sample into multiple sub-samples according to the segmentation parameters.

[0041] The smart terminal automatically reads the list of items to be tested, binds the total sample data with the item list, and generates a basic data package containing basic information about the total samples, the name and quantity of the items to be tested, and the basic requirements of each item for the samples. The smart terminal calls the built-in detection item-segmentation parameter association library, which pre-stores the segmentation standards corresponding to different detection items. For example, the breaking strength test requires a single-component sample length ≥ 20m, the feather test requires 5 independent samples with each group being 10m long, and the cotton knot test requires 10 independent samples with each group being 5m long. At the same time, it specifies the segmentation accuracy requirements for each item's samples.

[0042] The intelligent terminal accurately retrieves the corresponding segmentation parameters from the associated database based on the number and type of items to be detected, and performs allocation calculations in conjunction with the actual length of the total sample. For example, if the actual length of the total sample is 240m, 20m × 1 group of strong samples + 10m × 5 groups of feather samples + 5m × 10 groups of cotton knot samples = 20 + 50 + 50 = 120m, with the remaining 120m reserved as spare samples. Finally, the terminal sends a segmentation command to the sample segmentation device according to the calculation results, and the device performs the cutting in the order of first segmenting the short-length cotton knot samples and then segmenting the long-length strong samples.

[0043] Based on the segmentation parameters, the smart terminal fine-tunes the segmentation parameters by using the linear density values ​​of the segmentable samples.

[0044] After retrieving basic segmentation parameters from the detection item-segmentation parameter association library, the intelligent terminal further extracts the linear density detection results of the separable sample. This allows for targeted fine-tuning of the basic segmentation parameters to ensure that the sub-samples are adapted to subsequent detection needs. For example, if the separable sample is pure cotton yarn with a linear density detection value of 19.5 Tex, which is higher than the preset benchmark value of 18 Tex in the association library, the intelligent terminal determines that the sample has a greater weight per unit length. To avoid uneven tensile stress during strength testing due to excessive sample weight, the length of the sub-sample will be fine-tuned from 20m to 22m, balancing the impact of weight on the detection data by increasing the sample length. If the linear density fluctuation coefficient is 2.4%, which is close to the preset acceptable upper limit of 2.5%, it indicates poor sample uniformity. The intelligent terminal will then fine-tune the number of sub-sample groups for hairiness detection from 5 to 6, adding an extra sample group to cover possible variations in thickness within the total sample, thus improving the representativeness of the hairiness detection data.

[0045] After fine-tuning, the smart terminal will generate a fine-tuned segmentation parameter table and update it synchronously to the basic segmentation data packet to ensure that subsequent segmentation devices perform cutting operations according to parameters adapted to the line density characteristics.

[0046] Step S4: Assign each subsample to the corresponding item for testing.

[0047] Specifically, in this embodiment, the smart terminal monitors the status data of all connected testing devices in real time via industrial Ethernet. The status includes busy, idle, and calibrating.

[0048] The intelligent terminal first establishes real-time communication with all testing equipment via industrial Ethernet, and collects equipment status data every 10 seconds, clearly distinguishing between three states: busy, idle, and calibration, to ensure the timeliness and accuracy of status monitoring.

[0049] The smart terminal retrieves the latest calibration report of each testing device, extracts the accuracy parameters of the testing devices, and uses the accuracy requirements of the current sample to be tested as a benchmark to screen out devices that meet the accuracy standards through the device accuracy parameters.

[0050] The smart terminal retrieves the latest calibration report of each testing device from the local database. For example, the calibration report of the feather detection device shows a resolution of 0.1mm and a detection error of ±0.05 feathers / m. The smart terminal uses the accuracy requirements of the current sample to be tested, such as a resolution of ≤0.1mm and an error of ≤±0.08 feathers / m for feather detection, as a benchmark to select devices that meet the accuracy requirements and remove devices that exceed the error requirements.

[0051] The intelligent terminal allocates testing equipment according to the type of testing project, accuracy requirements, and priority, and then uses the testing equipment to test the samples.

[0052] The intelligent terminal performs allocation based on the project type and priority of the sample to be tested. It prioritizes allocating high-priority samples with urgent requirements to high-precision testing equipment that meets the accuracy standard and is in an idle state, and allocates low-priority samples with feathers to low-load, high-precision testing equipment. After allocation, it sends a testing instruction containing the sample number, testing standard threshold, and associated linear density basic data to the target testing equipment, and sends a sample delivery instruction to the automatic delivery system. After the sample is delivered, the testing equipment starts testing according to the instruction and feeds back the testing data to the intelligent terminal in real time.

[0053] When the intelligent terminal performs the allocation of testing equipment, it simultaneously collects the number of tasks to be tested and the estimated processing time of each task for each equipment that meets the accuracy standard, calculates the equipment load value, and sorts the load values. For equipment with the same load value, it further retrieves the equipment's test pass rate data and prioritizes allocating the sample to the equipment with the higher pass rate.

[0054] After selecting the testing equipment that meets the accuracy standards, the intelligent terminal synchronously collects the real-time load data of these equipment via industrial Ethernet. This includes the number of tasks currently pending testing for each equipment, as well as the estimated processing time per task calculated based on the equipment's historical testing data. The terminal automatically calculates the load value of each equipment using the formula: Equipment Load Value = Number of Tasks Pending Testing × Estimated Processing Time per Task. Then, the equipment that meets the accuracy standards is sorted in ascending order of load value, prioritizing the allocation of sub-samples to equipment with lower load values ​​to avoid equipment congestion. If there are equipment with the same load value, the intelligent terminal further retrieves the pass rate data of these two equipments over the past 30 days from the system database. With the core principle of ensuring the stability of testing quality, the sub-samples are prioritized for allocation to the equipment with the higher pass rate. After allocation, the intelligent terminal updates the load value and task queue of each equipment in real time and issues instructions containing sub-sample testing parameters to the target equipment, ensuring that the testing process is efficient and the quality is controllable.

[0055] After completing the allocation of testing equipment, the intelligent terminal monitors the operating status of the target testing equipment and the progress of sub-sample testing in real time. If a testing equipment suddenly fails, the intelligent terminal immediately re-selects equipment from those that meet the accuracy standards, and marks the status of the sub-samples that have not been tested in the original equipment as pending re-testing. After the new equipment receives the sub-samples, the intelligent terminal automatically synchronizes the testing parameters of the sub-samples to the new equipment, and the fault information of the faulty equipment and the sub-sample transfer record are transmitted to the intelligent terminal database in real time.

[0056] After the intelligent terminal completes the allocation of testing equipment, it will collect the operating status of the target testing equipment and the progress of sub-sample testing via high-frequency industrial Ethernet, and dynamically display it on the system interface, allowing staff to monitor the progress in real time. If the target testing equipment suddenly fails, the intelligent terminal will immediately trigger the fault response mechanism. On the one hand, it will re-select available equipment from the pool of previously selected equipment that meets the accuracy standards, according to the load value from smallest to largest. On the other hand, it will mark the status of the sub-samples that have not been tested in the original equipment as pending retesting in the system database, and record the progress of the sub-samples already tested to avoid duplicate testing or omissions. When the new equipment confirms receipt of the sub-sample, the intelligent terminal will automatically retrieve the complete testing parameters of the sub-sample from the database and synchronize them to the new equipment through an encrypted data transmission protocol. The new equipment can continue the testing progress without manual settings. At the same time, the intelligent terminal will upload the fault code, fault time, fault location of the faulty equipment, as well as the transfer time, transfer path, and receipt confirmation information of the sub-sample from the original equipment to the new equipment to the system database for archiving and storage in real time, providing data basis for subsequent maintenance of the faulty equipment.

[0057] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention. The scope of protection claimed by the appended claims and their equivalents is defined.

Claims

1. A method for intelligent monitoring of textile processing procedures based on smart terminals, characterized in that, include: The sampling frequency and sampling volume are determined based on the production volume of textile processing equipment within a certain period of time, and the total sample of the corresponding sampling volume is collected according to the sampling frequency. Linear density was measured on the total sample. The total sample is divided into multiple subsamples based on the number and type of items to be tested. Each subsample is assigned to the corresponding item for testing.

2. The intelligent monitoring method for textile processing procedures based on intelligent terminals according to claim 1, characterized in that, The sampling frequency and sample size are determined based on the production volume of textile processing equipment within a certain period of time, and a total sample of the corresponding sample size is collected according to the sampling frequency, including: The actual production data of the textile processing equipment during the regular production statistical cycle is collected through the sensors or data interfaces of the equipment, and the production data is transmitted to the smart terminal in real time. After receiving production data, the smart terminal automatically calculates and determines the corresponding sampling frequency and sampling quantity based on the preset production quantity and sampling association rules. The smart terminal sends the sampling frequency and sampling volume to the corresponding sampling device through instructions. The sampling device collects samples that meet the sampling volume requirements at the corresponding time nodes according to the instructions. All collected samples are summarized to form a total sample, and the collected signal is fed back to the smart terminal.

3. The intelligent monitoring method for textile processing procedures based on intelligent terminals according to claim 1, characterized in that, Linear density detection was performed on the total sample, including: After receiving the signal that the total sample collection is complete, the smart terminal automatically calls the preset linear density detection parameter library based on the textile type and production volume data associated with the total sample. Based on the linear density detection parameter library, the intelligent terminal automatically sets the detection parameters and sends a detection start command to the linear density detection equipment. The linear density testing equipment performs testing according to instructions to determine the linear density test results.

4. The intelligent monitoring method for textile processing steps based on intelligent terminals according to claim 3, characterized in that: After receiving the total sample line density detection results, the smart terminal automatically calls the corresponding acceptable line density threshold range, compares and calculates to determine the average line density value and fluctuation coefficient of the total sample: If the average linear density value is within the acceptable threshold and the fluctuation coefficient is less than or equal to the preset value, the total sample linear density is deemed acceptable and marked as a divisible sample. If the average linear density value is not within the acceptable threshold or the fluctuation coefficient is greater than the preset value, the total sample linear density is deemed unacceptable and marked as an indivisible sample.

5. The intelligent monitoring method for textile processing procedures based on intelligent terminals according to claim 1, characterized in that, Based on the number and type of items to be tested, the total sample is divided into multiple subsamples, including: The intelligent terminal retrieves the total sample of the separable samples; The smart terminal binds the total sample with the list of items to be detected to determine the basic data packet for segmentation; Based on the segmentation base data packet, according to the segmentation criteria corresponding to different detection items in the segmentation parameter association library built into the smart terminal, the corresponding segmentation parameters are retrieved from the association library according to the number and type of items. The smart terminal divides the total sample into multiple sub-samples according to the segmentation parameters.

6. The intelligent monitoring method for textile processing steps based on intelligent terminals according to claim 5, characterized in that: Based on the segmentation parameters, the smart terminal fine-tunes the segmentation parameters by using the linear density values ​​of the segmentable samples.

7. The intelligent monitoring method for textile processing procedures based on intelligent terminals according to claim 1, characterized in that, Each subsample is assigned to a corresponding item for testing, including: The intelligent terminal monitors the status data of all connected testing devices in real time via industrial Ethernet, including busy, idle, and calibrating status. The intelligent terminal retrieves the latest calibration report of each testing device, extracts the accuracy parameters of the testing devices, and uses the accuracy requirements of the current sample to be tested as a benchmark to screen out devices that meet the accuracy standards through the device accuracy parameters; The intelligent terminal allocates testing equipment according to the type of testing project, accuracy requirements, and priority, and then uses the testing equipment to test the samples.

8. The intelligent monitoring method for textile processing steps based on intelligent terminals according to claim 7, characterized in that: When the intelligent terminal performs the allocation of testing equipment, it simultaneously collects the number of tasks to be tested and the estimated processing time of each task for each equipment that meets the accuracy standard, calculates the equipment load value, and sorts the load values. For equipment with the same load value, it further retrieves the equipment's test pass rate data and prioritizes allocating the sample to the equipment with the higher pass rate.

9. The intelligent monitoring method for textile processing steps based on intelligent terminals according to claim 7, characterized in that: After completing the allocation of detection equipment, the intelligent terminal monitors the operating status of the target detection equipment and the progress of sample detection in real time; If the testing equipment suddenly malfunctions, the intelligent terminal immediately selects new equipment from those that meet the accuracy standards, and marks the status of the untested sub-samples in the original equipment as pending retesting. After the new equipment receives the sub-samples, the intelligent terminal automatically synchronizes the testing parameters of the sub-samples to the new equipment, and the fault information of the faulty equipment and the sub-sample transfer record are transmitted to the intelligent terminal database in real time.

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