XAS-based textile fabric full-width wide-belt liquid amount detection system

Abstract

The invention relates to the technical field of textile fabric detection, and discloses an XAS-based textile fabric full-width wide-band liquid amount detection system, which comprises a conveyor belt system, a rotary X-ray detection device, a multi-module parallel detection unit, an edge computing node and a central data processing system. According to the invention, a self-rotating X-ray detection device is adopted, and full-width seamless coverage scanning is realized by rotating the detector frame. Meanwhile, a multi-module parallel detection system is designed, and each module works independently and cooperatively processes different areas of the cloth. The modular design remarkably improves the detection efficiency, meets the requirements of a high-speed production line, and avoids the pause and overlapping problems of traditional linear scanning. Particularly, the holder control system is combined with the self-rotating X-ray emitter, so that errors and fuzziness caused by vibration brought by a rotating device are effectively reduced, and the detection precision is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of textile detection, and specifically to a full-width broadband liquid volume detection system for textiles based on XAS. Background Art

[0002] The textile industry occupies an important position in modern industrial production. The quality detection of textiles is of great significance for ensuring product quality and improving production efficiency. Among them, the liquid content detection is a key link in the textile production process, directly affecting the subsequent processes of the product (such as dyeing, printing, post-finishing, etc.) and the final performance. However, the existing detection methods still have many limitations and are difficult to meet the production requirements of high efficiency, precision, and intelligence.

[0003] Currently, the liquid content detection of textiles mostly adopts offline detection or single-point measurement methods. Common methods include:

[0004] Weight difference method: Calculate the liquid content by comparing the weight difference of the textile before and after liquid absorption. Although this method is simple and intuitive, it is necessary to remove the sample from the production line, with cumbersome operation and low efficiency.

[0005] Capacitance method: Detect by using the influence of the change in the liquid content of the textile on the capacitance value. However, this method is sensitive to factors such as the type and thickness of the textile, and has a limited applicable range.

[0006] Near-infrared spectroscopy (NIR): Measure the liquid content by analyzing the spectral reflection characteristics on the surface of the textile. However, the near-infrared spectrum has weak detection ability for deep-layer liquids in the fabric and is difficult to provide uniform detection across the full width.

[0007] These three detection processes require offline operation of the sample, cannot meet the requirements of real-time detection in modern production; the measurement range is limited, it is difficult to cover the entire fabric width, especially the uniformity detection of wide-width fabrics; it is greatly affected by environmental conditions, with low accuracy and repeatability.

[0008] In order to overcome the deficiencies of traditional methods, the detection method based on X-ray absorption spectroscopy (XAS) has gradually become a research hotspot. The XAS technology can accurately measure the liquid content and its distribution characteristics of textiles by detecting the absorption intensity of different energy X-rays by substances. Compared with traditional methods, the XAS technology has the following advantages:

[0009] 1. Strong penetration ability: It can detect the liquid distribution deep in the textile, not limited to surface information.

[0010] 2. High precision: The measurement error of the liquid content is small, and it can meet the requirements of high-precision detection.

[0011] 3. Non-contact detection: Avoids contamination or damage caused by sample contact.

[0012] Although XAS technology has great application potential in textile testing, its promotion and application still faces some technical challenges, such as insufficient real-time performance, low data processing efficiency, and complex equipment structure. In view of this, we propose a full-width broadband liquid volume detection system for textiles based on XAS. Summary of the invention

[0013] In view of the deficiencies in the prior art, the present invention provides a full-width broadband liquid quantity detection system for textiles based on XAS, which solves the problem.

[0014] To achieve the above objectives, the present invention is implemented through the following technical solutions: A textile full-width broadband liquid quantity detection system based on XAS, a textile full-width broadband liquid quantity detection system based on XAS, including a conveyor belt system, a rotary X-ray detection device, a multi-module parallel detection unit, an edge computing node and a central data processing system, characterized in that:

[0015] The XAS-based full-width broadband liquid quantity detection system for textiles includes a two-degree-of-freedom pan-tilt control system for accurately adjusting the angle and position of the self-rotating X-ray detection device;

[0016] The conveyor belt system includes a tension sensor, a speed sensor and a flatness detection device, which are used to collect the tension, speed and flatness data of the cloth in real time, transmit them to the central data processing system through the network, and dynamically adjust the scanning parameters of the rotary X-ray detection device and the operating status of the detection module;

[0017] The rotary X-ray detection device is composed of several independent X-ray detection modules, each module is composed of an independent X-ray source, a detector and a data processing unit, and each module is connected to the central data processing system through a high-speed data bus;

[0018] Each detection module of the multi-module parallel detection unit is equipped with an edge computing node for locally processing liquid volume and density distribution data, and screening out abnormal area data based on preset thresholds, and uploading them to the central system for further analysis in priority.

[0019] Preferably, the self-rotating X-ray detection device automatically adjusts the scanning frequency and speed according to the conveyor belt speed, and adopts a servo control system to achieve synchronous scanning. The detection device is equipped with a gyroscope and an accelerometer, which can monitor the posture and motion state of the device in real time, and carries an optical sensor inside to confirm the position of the cloth.

[0020] Preferably, the central data processing system adopts an FPGA+GPU architecture for performing big data analysis and machine learning algorithm operations. The FPGA module is used for real-time preprocessing of the detection data uploaded by multiple modules, and the GPU module performs in-depth analysis, including anomaly recognition of detection data, prediction of fabric characteristics, and X-ray power optimization.

[0021] Preferably, the tension sensor adopts a bidirectional strain gauge structure for real-time detection of fabric tension fluctuations and linkage with the tension control device to adjust the running speed of the conveyor belt.

[0022] Preferably, the fault monitoring and handling mechanism includes: a real-time data monitoring module, an automatic fault diagnosis module, and a dynamic adjustment module; when an abnormal situation is detected, the system determines the abnormal source through the fault diagnosis module and automatically adjusts the detection process, including switching to a standby module, adjusting X-ray parameters, or prompting manual intervention.

[0023] Preferably, the XAS-based full-width and broadband liquid volume detection system for textiles has a visual monitoring interface for real-time display of detection data, conveying status, and fault alarm information. The interface provides a manual intervention interface, allowing the operator to manually adjust the detection parameters or process according to actual needs.

[0024] Preferably, an XAS-based full-width and broadband liquid volume detection method for textiles is characterized by including the following steps

[0025] S1: Real-time monitoring and adjustment of the conveyor belt system

[0026] A high-speed conveyor belt is adopted, and fabric state data is collected by a tension sensor, a speed sensor, and a flatness sensor, uploaded to the central system, and the conveying speed and tension are dynamically adjusted to ensure the smooth operation of the fabric;

[0027] S2: Rotary X-ray detection

[0028] The detector rack of the rotary X-ray detection device is driven to rotate by a servo motor, synchronized with the conveyor belt speed, and seamlessly scans the full-width area of the fabric. The detector collects the X-ray transmission signal, calculates the liquid volume and density distribution data, and transmits it to the edge computing node;

[0029] S3: Multi-module parallel detection

[0030] Multiple X-ray detection modules are distributed in the detection area, independently responsible for the liquid volume detection of different areas, and the detection results are uploaded to the central system in real time for integration and analysis;

[0031] S4: Edge computing and central system data processing

[0032] The edge computing unit performs local analysis on the liquid content data and uploads key data. The central data processing system integrates and deeply analyzes the uploaded data based on the FPGA+GPU architecture to optimize the control parameters.

[0033] S5: Detection result display and manual intervention

[0034] The detection results are displayed in real time through a visualization interface. In case of anomalies, the administrator can manually adjust the detection parameters.

[0035] S6: Detection data storage and long-term analysis

[0036] All detection data and conveying status data are uploaded to the central database for storage, and historical data is used for in-depth analysis to optimize the production process.

[0037] Preferably, in the S2 rotary X-ray detection step, the rotary X-ray detection device is built-in with a gyroscope and an accelerometer to monitor the device's attitude and motion state in real time. The PID control algorithm is used to control the rotation speed and direction of the motor, and the central system adjusts the angle and position of the X-ray source and the detector rack to ensure that the X-ray beam is synchronized with the movement of the high-speed conveyor belt, avoiding detection errors and blurring.

[0038] Preferably, in the S4 edge computing and central system data processing step, the FPGA module of the central data processing system is used to preprocess the detection data uploaded by multiple modules in real time, and the GPU module performs in-depth analysis, including anomaly recognition of detection data, prediction of fabric characteristics, and optimization of X-ray power.

[0039] The present invention provides a full-width wide liquid content detection system for textiles based on XAS. It has the following beneficial effects:

[0040] 1. The present invention adopts a rotary X-ray device to achieve seamless coverage of the detection area, and through the collaborative work of multiple modules, significantly improves the detection efficiency. By introducing a pan-tilt control system, the present invention not only improves the detection accuracy and stability but also greatly enhances the real-time response ability of the system.

[0041] The precise adjustment function of this control system effectively eliminates the vibration error generated by the rotating device, making the entire detection process more accurate and stable. Especially in high-speed production lines, the pan-tilt control system can ensure the synchronous movement of the X-ray device and the fabric, thereby improving the detection accuracy and efficiency.

[0042] 2. The present invention introduces a central data processing system with an FPGA+GPU architecture and combines edge computing nodes, significantly improving the running speed of big data analysis and machine learning algorithms.

[0043] 3. Through real-time monitoring and feedback control, the present invention dynamically adjusts the detection parameters to ensure the stable operation of the system, and can guarantee the detection continuity even in case of failures.

[0044] Through the implementation of the present invention, the liquid content detection technology of textile fabrics will be effectively improved, providing strong technical support for the intelligent production of the textile industry, and having broad industrial application prospects at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 is the architecture diagram of the central data processing and edge computing system of the present invention;

[0046] Figure 2 is the system diagram of the full-width and wide-band liquid content detection system for textile fabrics based on XAS of the present invention;

[0047] Figure 3 is the structure diagram of the full-width and wide-band liquid content detection system for textile fabrics based on XAS of the present invention;

[0048] Figure 4 is the structure diagram of the XAS ray source of the present invention;

[0049] Figure 5 is the flow chart of the full-width and wide-band liquid content detection system for textile fabrics based on XAS of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the specification of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0051] Embodiment:

[0052] Please refer to the attached Figure 1 - attached Figure 5 , the embodiment of the present invention provides a full-width and wide-band liquid content detection system for textile fabrics based on XAS, including a conveyor belt system, a rotary X-ray detection device, a multi-module parallel detection unit, an edge computing node and a central data processing system, and is characterized in that:

[0053] The full-width and wide-band liquid content detection system for textile fabrics based on XAS includes a two-degree-of-freedom pan-tilt control system for precisely adjusting the angle and position of the self-rotating X-ray detection device;

[0054] The conveyor belt system includes a tension sensor, a speed sensor and a flatness detection device, which are used to collect the tension, speed and flatness data of the cloth in real time, transmit them to the central data processing system through the network, and dynamically adjust the scanning parameters of the rotary X-ray detection device and the operating status of the detection module;

[0055] The rotary X-ray detection device is composed of several independent X-ray detection modules, each module is composed of an independent X-ray source, a detector and a data processing unit, and each module is connected to the central data processing system through a high-speed data bus;

[0056] Each detection module of the multi-module parallel detection unit is equipped with an edge computing node for locally processing liquid volume and density distribution data, and screening out abnormal area data based on preset thresholds, and uploading them to the central system for further analysis in priority.

[0057] The self-rotating X-ray detection device automatically adjusts the scanning frequency and speed according to the conveyor belt speed, and adopts a servo control system to achieve synchronous scanning. The detection device is equipped with a gyroscope and an accelerometer, which can monitor the posture and movement state of the device in real time. It carries an optical sensor inside to confirm the position of the cloth.

[0058] The central data processing system adopts FPGA+GPU architecture for big data analysis and machine learning algorithm operations. The FPGA module is used for real-time preprocessing of detection data uploaded by multiple modules, and the GPU module performs in-depth analysis, including abnormal identification of detection data, fabric property prediction and X-ray power optimization.

[0059] The tension sensor adopts a bidirectional strain gauge structure, which is used to detect cloth tension fluctuations in real time and cooperate with the tension control device to adjust the conveyor belt running speed.

[0060] The fault monitoring and processing mechanism includes: a real-time data monitoring module, an automatic fault diagnosis module and a dynamic adjustment module; when an abnormal situation is detected, the system determines the abnormal source through the fault diagnosis module and automatically adjusts the detection process, including switching to a backup module, adjusting X-ray parameters or prompting manual intervention.

[0061] The XAS-based textile full-width broadband liquid quantity detection system has a visual monitoring interface for real-time display of detection data, conveying status and fault alarm information. The interface provides a manual intervention interface, allowing the operator to manually adjust the detection parameters or processes according to actual needs.

[0062] A method for detecting liquid volume in a full-width wideband textile based on XAS comprises the following steps:

[0063] S1: Real-time monitoring and adjustment of conveyor belt system

[0064] The textiles enter the conveyor belt system, which uses high-speed mode to ensure detection efficiency. The conveyor belt is made of anti-static and wear-resistant materials to avoid static electricity or friction affecting the state of the fabric.

[0065] The system integrates tension sensors, speed sensors and flatness sensors to collect real-time data on the status of fabric during transportation. The tension signal is used to adjust the tension of the conveyor belt to ensure that the fabric is wrinkle-free. The speed signal is synchronized with the rotary X-ray detection device to ensure accurate detection results.

[0066] The real-time detected conveyor belt status data is uploaded to the central system. The system dynamically adjusts the conveying speed and tension to keep the fabric running smoothly and avoid detection errors caused by irregular operation;

[0067] S2: Rotary X-ray Inspection

[0068] The rotating X-ray detection device includes a rotatable detector frame and an X-ray source. The detector frame is driven by a servo motor to rotate. The detection device is equipped with a gyroscope, accelerometer, etc. to monitor the attitude and motion state of the device in real time. In addition, the control system includes some algorithms, such as PID control algorithm, to control the rotation speed and direction of the motor.

[0069] The X-ray source and detector rack are precisely adjusted by the central system, which controls the angle and position of the self-rotating X-ray emitter in real time, ensuring that the X-ray beam is synchronized with the movement of the high-speed conveyor belt, thus avoiding errors and blurring caused by fabric vibration or irregular movement of the conveyor belt. The rotation frequency of the detector rack is synchronized with the conveyor belt speed, ensuring seamless scanning of the full width of the fabric.

[0070] During the operation of the conveyor belt, more than two detection units will cooperate with each other in the direction of the conveyor belt movement to detect a certain length of cloth divided by the system (the cloth position is determined by the optical sensor of the detection device). First, this length of cloth is divided into several smaller areas, which are detected by the corresponding number of detection units.

[0071] After being reset, a single independent detection unit will perform real-time detection of the area it is divided into. During this process, the detection unit will upload its own motion state data to the central system through the inertial sensor unit, and the spectral data will be uploaded to the edge computing node. The central system adjusts the rotation angle, position and scanning frequency of the X-ray emitter in real time according to the motion data of the conveyor belt to ensure the synchronization of the X-ray scanning and the fabric, and avoid errors caused by fabric vibration or irregular conveyor belt movement. After the detection unit completes the detection of the area, it will automatically reset and wait for the next section of fabric divided by the system to enter the detection area.

[0072] The detector collects X-ray transmission signals, and based on the absorption characteristics of the fabric for X-rays, calculates the liquid content and density distribution data. The data is transmitted to the edge computing node for preprocessing, extracting key parameters and forming regional detection results. Among them, the following key equations are involved in the computer-aided detection process:

[0073] The calculation of the liquid content is based on the absorption characteristics of the textile for X-rays and is described as follows:

[0074] I = I 0 e -μx

[0075] Where:

[0076] I: X-ray transmission intensity;

[0077] I0: Incident intensity;

[0078] μ: Linear absorption coefficient of the material, including the absorption characteristics of the fabric and the liquid;

[0079] x: Thickness of the ray penetration path.

[0080] By measuring the incident intensity I0 and the transmission intensity I, and combining the known absorption coefficient μ, the thickness of the fabric or the liquid content can be obtained.

[0081] In the above design of the combination of the pan-tilt control system and the self-rotating XAS emitter, the main function of the pan-tilt system is to accurately control the angles and positions of the X-ray emitter and the detector to ensure the synchronization of the X-ray beam with the movement of the high-speed conveyor belt, avoiding errors and blurs. The most important of which is the pan-tilt stability equation:

[0082] (J Y2 + J Z3 )β + (J Z2 + J Z3 )sin 2 β = M 1

[0083] J Z3 (γ - sinβ - βcosβ) = M 2

[0084] In the formula: JZ and JY are the fixed-axis moments of inertia of the roll axis and the pitch axis respectively; β and γ are the fixed-axis rotation angles of the roll axis and the total roll axis respectively.

[0085] Through the precise rotation and stable positioning of the pan-tilt system, beam offset, motion blur and data errors are reduced, thereby improving the accuracy of detection;

[0086] S3: Multi-module parallel detection

[0087] Multiple X-ray detection modules are distributed in the detection area, independently responsible for detecting the liquid content in different areas of the textile. Each module is equipped with an independent X-ray source, detector, and data processing unit to ensure a clear division of labor for the detection tasks.

[0088] The detection modules work simultaneously to reduce the overall detection time. The detection results of each module are uploaded to the central system in real-time for integration and analysis. The modular design facilitates the implementation of redundant backups. If a certain module fails, it can be automatically switched to the backup module to ensure that the detection process is not interrupted;

[0089] S4: Edge Computing and Central System Data Processing

[0090] The edge computing unit of each detection module performs local analysis on the liquid content data, eliminates invalid data, and extracts key parameters (such as tension data, degree of wrinkle, etc.). The processed key data is uploaded to the central system to reduce the data processing burden on the central system.

[0091] The central data processing system is based on the FPGA+GPU architecture and integrates and deeply analyzes the data uploaded by each module. The central system receives and analyzes the data of each module, automatically identifies anomalies, and optimizes control parameters. Through machine learning and big data analysis, the system can adjust the scanning power, speed, and accuracy of the X-ray according to the real-time state of the fabric, further improving the detection effect and ensuring the automatic adjustment and optimization of the system;

[0092] S5: Detection Result Display and Manual Intervention

[0093] The detection results are displayed in real-time through a visual interface, including the fabric humidity distribution, liquid content distribution map, density distribution map, and conveyor belt status information. The interface adopts an interactive design, and the administrator can select a specific area to zoom in and view detailed data.

[0094] In case of anomalies, the administrator can manually adjust the X-ray power, scanning speed, or optimize the conveyor belt parameters through the interface. For special orders, the system allows the administrator to prioritize the processing of key fabrics to ensure production flexibility;

[0095] S6: Detection Data Storage and Long-term Analysis

[0096] All detection data and conveyor status data are uploaded to the central database for storage, providing a basis for subsequent production analysis. Data storage includes humidity distribution, liquid content, density distribution, and historical records of conveyor parameters.

[0097] The system uses historical data for in-depth analysis, identifies potential problems in the production line, and proposes improvement suggestions. Through data-driven process optimization, the overall efficiency and quality of textile production are improved.

[0098] In the S2 rotary X-ray detection step, the rotary X-ray detection device is built-in with a gyroscope and an accelerometer to monitor the device's attitude and motion state in real time. The PID control algorithm is used to control the rotation speed and direction of the motor, and the central system adjusts the angles and positions of the X-ray source and the detector rack to ensure that the X-ray beam is synchronized with the movement of the high-speed conveyor belt, avoiding detection errors and blurring.

[0099] In the S4 edge computing and central system data processing step, the FPGA module of the central data processing system is used to preprocess the detection data uploaded by multiple modules in real time, and the GPU module performs in-depth analysis, including anomaly recognition of detection data, fabric characteristic prediction, and X-ray power optimization.

[0100] Although the embodiments of the present invention have been shown and described, it will be understood by those of ordinary skill in the art that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A full-width broadband liquid volume detection system for textiles based on XAS, including a conveyor belt system, a rotary X-ray detection device, a multi-module parallel detection unit, an edge computing node and a central data processing system, characterized in that: The XAS-based full-width broadband liquid quantity detection system for textiles includes a two-degree-of-freedom pan-tilt control system for accurately adjusting the angle and position of the self-rotating X-ray detection device; The conveyor belt system includes a tension sensor, a speed sensor and a flatness detection device, which are used to collect the tension, speed and flatness data of the cloth in real time, transmit them to the central data processing system through the network, and dynamically adjust the scanning parameters of the rotary X-ray detection device and the operating status of the detection module; The rotary X-ray detection device is composed of several independent X-ray detection modules, each module is composed of an independent X-ray source, a detector and a data processing unit, and each module is connected to the central data processing system through a high-speed data bus; Each detection module of the multi-module parallel detection unit is equipped with an edge computing node for locally processing liquid volume and density distribution data, and screening out abnormal area data based on preset thresholds, and uploading them to the central system for further analysis in priority.

2. According to the XAS-based textile full-width broadband liquid quantity detection system of claim 1, it is characterized in that: The self-rotating X-ray detection device automatically adjusts the scanning frequency and speed according to the conveyor belt speed, and adopts a servo control system to achieve synchronous scanning. The detection device is equipped with a gyroscope and an accelerometer, which can monitor the posture and movement state of the device in real time. It carries an optical sensor inside to confirm the position of the cloth.

3. The XAS-based textile full-width broadband liquid volume detection system according to claim 1, characterized in that: The central data processing system adopts FPGA+GPU architecture for big data analysis and machine learning algorithm operations. The FPGA module is used for real-time preprocessing of detection data uploaded by multiple modules, and the GPU module performs in-depth analysis, including abnormal identification of detection data, fabric property prediction and X-ray power optimization.

4. The XAS-based textile full-width broadband liquid volume detection system according to claim 1, characterized in that: The tension sensor adopts a bidirectional strain gauge structure, which is used to detect cloth tension fluctuations in real time and cooperate with the tension control device to adjust the conveyor belt running speed.

5. The XAS-based textile full-width broadband liquid volume detection system according to claim 3, characterized in that: The fault monitoring and processing mechanism includes: a real-time data monitoring module, an automatic fault diagnosis module and a dynamic adjustment module; when an abnormal situation is detected, the system determines the abnormal source through the fault diagnosis module and automatically adjusts the detection process, including switching to a backup module, adjusting X-ray parameters or prompting manual intervention.

6. The XAS-based textile full-width broadband liquid volume detection system according to claim 1, characterized in that: The XAS-based textile full-width broadband liquid quantity detection system has a visual monitoring interface for real-time display of detection data, conveying status and fault alarm information. The interface provides a manual intervention interface, allowing the operator to manually adjust the detection parameters or processes according to actual needs.

7. The XAS-based full-width broadband liquid volume detection method for textiles according to claim 1, characterized in that: The following steps are involved: S1: Real-time monitoring and adjustment of conveyor belt system High-speed conveyor belts are used, and tension sensors, speed sensors and flatness sensors are used to collect fabric status data, which is uploaded to the central system and dynamically adjusts the conveying speed and tension to ensure smooth fabric operation; S2: Rotary X-ray Inspection The detector frame of the rotating X-ray detection device is driven by a servo motor to rotate synchronously with the conveyor belt speed, and seamlessly scans the full width of the fabric. The detector collects X-ray transmission signals, calculates the amount of liquid and density distribution data, and transmits them to the edge computing node; S3: Multi-module parallel detection Multiple X-ray detection modules are distributed in the detection area, independently responsible for the liquid volume detection in different areas, and the detection results are uploaded to the central system in real time for integration and analysis; S4: Edge computing and central system data processing The edge computing unit performs local analysis on the liquid volume data and uploads key data. The central data processing system integrates and deeply analyzes the uploaded data based on the FPGA+GPU architecture to optimize the control parameters. S5: Test result display and manual intervention The test results are displayed in real time through a visual interface, and the administrator can manually adjust the test parameters in abnormal situations; S6: Detection data storage and long-term analysis Upload all inspection data and conveying status data to the central database for storage, use historical data for in-depth analysis, and optimize production processes.

8. The XAS-based full-width broadband liquid volume detection method for textiles according to claim 7, characterized in that: In the S2 rotary X-ray detection step, the rotary X-ray detection device has built-in gyroscopes and accelerometers to monitor the device's posture and motion state in real time, and uses a PID control algorithm to control the motor's rotation speed and direction. The central system adjusts the angle and position of the X-ray source and the detector frame to ensure that the X-ray beam is synchronized with the high-speed conveyor belt movement to avoid detection errors and ambiguity.

9. The XAS-based full-width broadband liquid volume detection method for textiles according to claim 7, characterized in that: In the S4 edge computing and central system data processing steps, the FPGA module of the central data processing system is used to pre-process the detection data uploaded by multiple modules in real time, and the GPU module performs in-depth analysis, including abnormal identification of detection data, fabric property prediction and X-ray power optimization.

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