X-ray equipment adaptive control and management system based on multi-modal intelligent analysis

Abstract

The invention belongs to the technical field of intelligent regulation and management of X-ray equipment, and particularly relates to an X-ray equipment self-adaptive regulation and management system based on multi-modal intelligent analysis, which comprises an X-ray equipment operation data acquisition unit; the preprocessing unit is used for acquiring data; a multi-modal data analysis unit; an intelligent analysis and decision unit; an X-ray equipment intelligent self-adaptive regulation and control unit; an X-ray equipment intelligent management unit; and an equipment user interaction and question feedback unit. According to the invention, automatic regulation and control of parameters of the X-ray equipment can be realized through application of the intelligent self-adaptive regulation and control unit of the X-ray equipment, and the operation efficiency of the equipment is improved; through cooperative application of the multi-modal data analysis unit and the intelligent analysis and decision-making unit, the radiation dose and the equipment energy consumption are reduced; through the intelligent management unit of the X-ray equipment, the state of the X-ray equipment can be monitored in real time, faults are predicted, maintenance suggestions are provided, and the service life of the equipment is prolonged.

Description

Technical Field

[0001] The present invention belongs to the technical field of intelligent regulation and management of X-ray equipment, and particularly relates to an adaptive regulation and management system for X-ray equipment based on multimodal intelligent analysis. Background Art

[0002] The core idea of multimodal intelligent analysis is to combine different types of data for processing, rather than relying solely on single-modal input. By integrating and understanding these different information sources simultaneously, an AI system can obtain a deeper and more comprehensive understanding than single-modal. Multimodal intelligent analysis has a wide range of applications in many fields, including but not limited to: intelligent regulation and management of equipment, autonomous driving, medical diagnosis, intelligent customer service, and image annotation and generation;

[0003] Multimodal intelligent analysis can provide more comprehensive and accurate analysis and decision-making by integrating different types of data. When the information of a certain modality is missing or incorrect, the information of other modalities can make up for the deficiency and improve the robustness of the system. The fusion of multiple modalities can make human-computer interaction more natural and efficient, similar to the way humans communicate through multiple senses.

[0004] An adaptive regulation and management system for X-ray equipment based on multimodal intelligent analysis is an advanced system integrating multimodal data fusion, intelligent analysis, and adaptive control technologies.

[0005] When providing services for enterprises, this system will conduct multi-angle evaluation and analysis on the usage of X-ray equipment from the perspective of the enterprise. However, the parameter regulation of traditional X-ray equipment depends on manual experience, making it difficult to achieve precision and automation. There is a lack of intelligent means for monitoring and maintaining the equipment operation status, and the ability to predict and prevent faults is insufficient. Summary of the Invention

[0006] The purpose of the present invention is to provide an adaptive regulation and management system for X-ray equipment based on multimodal intelligent analysis, aiming to solve the problems in the prior art that the parameter regulation of existing X-ray equipment depends on manual experience, making it difficult to achieve precision and automation, there is a lack of intelligent means for monitoring and maintaining the equipment operation status, and the ability to predict and prevent faults is insufficient.

[0007] To achieve the above purpose, the present invention provides the following technical solution: An adaptive regulation and management system for X-ray equipment based on multimodal intelligent analysis, comprising:

[0008] X-ray equipment operation data acquisition unit, which is used to collect relevant data such as X-ray images, image metadata, operating voltage, current, exposure time, focal length, filter settings, detector parameters, temperature, humidity, radiation dose, air pressure, X-ray tube, cooling system, mechanical motion state, power supply state, and log data during the operation of the X-ray equipment;

[0009] Preprocessing unit for the collected data, which is used to process missing values, outliers, duplicate data, and noise data in the collected data;

[0010] Multimodal data analysis unit, which is used to comprehensively analyze the processed data and generate a comprehensive information analysis result report;

[0011] Intelligent analysis and decision-making unit, which is used to perform structural analysis on the report of multimodal data analysis and form a processing decision;

[0012] Intelligent adaptive regulation unit for X-ray equipment, which is used to regulate the operating parameters of the X-ray equipment according to the processing decision;

[0013] Intelligent management unit for X-ray equipment, which is used to generate a maintenance plan and suggestions according to the status of the X-ray equipment and the result of fault prediction;

[0014] Interaction and problem feedback unit for equipment users, which is used to display the equipment status, analysis results, and regulation suggestions through a visual interface.

[0015] Preferably, for the X-ray equipment adaptive regulation and management system based on multimodal intelligent analysis of the present invention, the data collected by the X-ray equipment operation data acquisition unit includes equipment system configuration data, equipment operation image data, equipment operation text data, equipment use energy consumption data, sensor induction data, and equipment use environment data;

[0016] Equipment system configuration data such as the processor model, memory capacity, and software version used by the X-ray equipment, equipment operation image data such as X-ray images and thermal imaging maps generated during the operation of the X-ray equipment, equipment operation text data such as X-ray equipment operation logs and error logs, equipment use energy consumption data such as energy use efficiency and power consumption data, sensor induction data includes temperature, humidity, voltage, current, and vibration data collected through sensors, and equipment use environment data includes light, noise, and radiation data.

[0017] Preferably, for the X-ray device adaptive regulation and management system based on multimodal intelligent analysis of the present invention, the preprocessing unit for the collected data includes data cleaning, data alignment, feature extraction, and data augmentation;

[0018] Data cleaning: When there are missing values in the collected data, use the mean, median, mode, or prediction model to fill in the missing values; when there are outliers in the collected data, compare and correct the outlier data according to historical records; when there are duplicate data in the collected data, retain one of the data and then delete the remaining duplicate data; for noise data, remove the noise at specific frequencies through low-pass, high-pass, or band-pass filters.

[0019] Preferably, for the X-ray device adaptive regulation and management system based on multimodal intelligent analysis of the present invention, the data alignment matches, adjusts, and integrates data from different sources, different formats, or different structures to make them consistent or compatible in dimensions such as time, space, semantics, or structure;

[0020] For the feature extraction, use pre-trained deep learning models (such as ResNet, VGG) to extract image features, use the bag-of-words model (Bag of Words) or TF-IDF to extract text features, use time series analysis methods (such as Fourier transform, wavelet transform) to extract frequency domain features, and use Mel Frequency Cepstral Coefficients (MFCCs) to extract audio features;

[0021] For the data augmentation, use methods such as rotation, scaling, flipping, and cropping to generate new image samples, and use color transformation (such as brightness and contrast adjustment) to increase image diversity; use methods such as synonym replacement, random insertion, and random deletion to generate new text samples, and use back translation to translate the text into other languages and then translate it back; use methods such as time offset and noise addition to generate new time series samples.

[0022] Preferably, for the X-ray device adaptive regulation and management system based on multimodal intelligent analysis of the present invention, the multimodal data analysis unit includes multimodal data fusion, multimodal data modeling, model training and optimization, and result analysis;

[0023] Multimodal data fusion: Use machine learning algorithms (such as random forest, support vector machine) and deep learning models (such as convolutional neural network, recurrent neural network) for data fusion;

[0024] Multimodal data modeling: Integrate and analyze data from different modalities (such as images, text, audio, sensor data, etc.), and use data from multiple modalities (such as images, text, audio, sensor data, etc.) to build a model.

[0025] Preferably, for the X-ray device adaptive regulation and management system based on multimodal intelligent analysis of the present invention, for model training and optimization, the data is divided into a training set, a validation set, and a test set. The model is trained using the training set, the model parameters are adjusted, the model is trained using the training set, the model parameters are adjusted, the model is trained using the training set, and the model parameters are adjusted;

[0026] Result analysis: Use metrics such as accuracy, recall rate, and F1 score to evaluate the model performance, use metrics such as accuracy, recall rate, and F1 score to evaluate the model performance.

[0027] Preferably, for the X-ray device adaptive regulation and management system based on multimodal intelligent analysis of the present invention, the intelligent analysis and decision-making unit includes device mode recognition, prediction and analysis of the future operating state of the device, and formulation of control decisions;

[0028] Device mode recognition: Use machine learning and deep learning algorithms to perform mode recognition on the fused multimodal data to identify the normal operating state, abnormal state, and possible fault types of the device;

[0029] Prediction and analysis of the future operating state of the device: Based on historical data and real-time data, use algorithms such as time series analysis and regression analysis to predict the future operating state of the device in order to take regulatory measures in advance;

[0030] Formulation of control decisions: According to the results of mode recognition and prediction analysis, combined with the operating objectives and constraints of the device, formulate the optimal regulation strategy and management plan.

[0031] Preferably, for the X-ray device adaptive regulation and management system based on multimodal intelligent analysis of the present invention, the X-ray device intelligent adaptive regulation unit dynamically adjusts the operating parameters of the device according to the results of intelligent analysis; by intelligently analyzing the operating efficiency and energy consumption of the device, optimize resource allocation, reduce operating costs, and improve the overall performance of the device.

[0032] Preferably, for the X-ray device intelligent management unit of the X-ray device adaptive regulation and management system based on multimodal intelligent analysis of the present invention, it includes real-time monitoring of the device operating state, device fault warning, device fault prediction, and registration and maintenance suggestions for device repair records;

[0033] Real-time monitoring of the device operating state: Real-time monitor the operating state of the X-ray device and record the key indicators of the X-ray device;

[0034] Device fault warning: When the device is in an abnormal state, the system can issue a warning signal in a timely manner and provide possible fault reasons and solutions;

[0035] Equipment fault prediction: Use machine learning models to predict equipment faults and issue early warnings.

[0036] Equipment repair record registration and maintenance suggestions: Generate maintenance plans and suggestions based on equipment status and fault prediction results.

[0037] Preferably, for the X-ray equipment adaptive regulation and management system based on multimodal intelligent analysis of the present invention, the interaction and problem feedback unit of the equipment user provides an intuitive visualization interface to display equipment status, analysis results, and regulation suggestions; it supports user feedback on system decisions to optimize models and regulation strategies.

[0038] Compared with the prior art, the beneficial effects of the present invention are:

[0039] Through the application of the X-ray equipment intelligent adaptive regulation unit, automatic regulation of X-ray equipment parameters can be achieved, improving equipment operation efficiency.

[0040] Through the coordinated application of the multimodal data analysis unit and the intelligent analysis and decision-making unit, radiation dose and equipment energy consumption can be reduced.

[0041] Through the X-ray equipment intelligent management unit, the status of X-ray equipment can be monitored in real time, faults can be predicted, and maintenance suggestions can be provided, extending the service life of the equipment.

[0042] Through the application of the interaction and problem feedback unit of the equipment user, a friendly user interaction interface is provided, enhancing the user experience. Brief Description of the Drawings

[0043] The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0044] Figure 1 It is a schematic diagram of the system structure of the present invention;

[0045] Figure 2 It is a schematic diagram of the X-ray equipment operation data acquisition unit of the present invention;

[0046] Figure 3 It is a schematic diagram of the preprocessing unit for the data collected by the present invention;

[0047] Figure 4 It is a schematic diagram of the multimodal data analysis unit of the present invention;

[0048] Figure 5 It is a schematic diagram of the intelligent analysis and decision-making unit of the present invention;

[0049] Figure 6 It is a schematic diagram of the X-ray equipment intelligent management unit of the present invention.

[0050] In the figure: 1. X-ray equipment operation data acquisition unit; 2. Preprocessing unit for acquired data; 3. Multimodal data analysis unit; 4. Intelligent analysis and decision-making unit; 5. X-ray equipment intelligent adaptive regulation unit; 6. X-ray equipment intelligent management unit; 7. Interaction and problem feedback unit for equipment users. Specific implementation manners

[0051] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0052] Please refer to Figures 1 - 6 , the present invention provides the following technical solutions: An X-ray equipment adaptive regulation and management system based on multimodal intelligent analysis, including:

[0053] An X-ray equipment operation data acquisition unit 1, which is used to collect relevant data such as X-ray images, image metadata, operating voltage, current, exposure time, focal length, filter settings, detector parameters, temperature, humidity, radiation dose, air pressure, X-ray tube, cooling system, mechanical motion state, power supply state, and log data during the operation of the X-ray equipment;

[0054] A preprocessing unit 2 for acquired data, which is used to process missing values, outliers, duplicate data, and noise data in the acquired data;

[0055] A multimodal data analysis unit 3, which is used to comprehensively analyze the processed data and generate a comprehensive information analysis result report;

[0056] An intelligent analysis and decision-making unit 4, which is used to perform structural analysis on the report of multimodal data analysis and form a processing decision;

[0057] An X-ray equipment intelligent adaptive regulation unit 5, which is used to regulate the operating parameters of the X-ray equipment according to the processing decision;

[0058] An X-ray equipment intelligent management unit 6, which is used to generate a maintenance plan and suggestions according to the state and fault prediction result of the X-ray equipment;

[0059] The interaction and problem feedback unit 7 of the device user is used to display the device status, analysis results, and regulation suggestions through a visual interface.

[0060] Preferably, the data collected by the X-ray device operation data acquisition unit 1 includes device system configuration data, device operation image data, device operation text data, device usage energy consumption data, sensor induction data, and device usage environment data;

[0061] The device system configuration data such as the processor model, memory capacity, and software version used by the X-ray device, the device operation image data such as the X-ray image and thermal imaging map generated during the operation of the X-ray device, the device operation text data such as the operation log and error log of the X-ray device, the device usage energy consumption data such as the energy usage efficiency and power consumption data, the sensor induction data includes temperature, humidity, voltage, current, and vibration data collected by sensors, and the device usage environment data includes light, noise, and radiation data.

[0062] In specific use, the application of the X-ray device operation data acquisition unit 1 can be responsible for collecting various original relevant data during the operation of the X-ray device from various sources, providing a basis for subsequent data processing, analysis, and modeling.

[0063] Preferably, the preprocessing unit 2 of the collected data includes data cleaning, data alignment, feature extraction, and data augmentation;

[0064] Data cleaning: When there are missing values in the collected data, use the mean, median, mode, or prediction model to fill in the missing values; when there are outliers in the collected data, compare and correct the outlier data according to historical records; when there are duplicate data in the collected data, keep one of the data and then delete the remaining duplicate data; remove specific frequency noise from the noise data through low-pass, high-pass, or band-pass filters;

[0065] Data alignment matches, adjusts, and integrates data from different sources, different formats, or different structures to make them consistent or compatible in dimensions such as time, space, semantics, or structure;

[0066] Feature extraction, use pre-trained deep learning models (such as ResNet, VGG) to extract image features, use the bag-of-words model (Bag of Words) or TF-IDF to extract text features, use time series analysis methods (such as Fourier transform, wavelet transform) to extract frequency domain features, and use Mel-frequency cepstral coefficients (MFCCs) to extract audio features;

[0067] Data augmentation, using methods such as rotation, scaling, flipping, and cropping to generate new image samples, and using color transformation (such as brightness and contrast adjustment) to increase image diversity; using methods such as synonym replacement, random insertion, and random deletion to generate new text samples, and using back translation to translate the text into other languages and then translate it back; using methods such as time offset and noise addition to generate new time series samples.

[0068] In specific use, through the application of the data preprocessing unit 2 for collecting data, errors, inconsistencies, and redundant information in the dataset can be identified and corrected, thereby improving data quality. High-quality data can reduce errors in the analysis process, making the analysis results more reliable. The reliable data analysis results provide a solid foundation for decision-making, helping enterprises and organizations make more informed decisions.

[0069] Preferably: The multimodal data analysis unit 3 includes multimodal data fusion, multimodal data modeling, model training and optimization, and result analysis;

[0070] Multimodal data fusion, using machine learning algorithms (such as random forest, support vector machine) and deep learning models (such as convolutional neural network, recurrent neural network) for data fusion;

[0071] Multimodal data modeling, integrating and analyzing data from different modalities such as images, text, audio, sensor data, etc., and using data from multiple modalities such as images, text, audio, sensor data, etc. to build models;

[0072] Model training and optimization, dividing the data into training set, validation set, and test set, using the training set to train the model, adjusting the model parameters, using the training set to train the model, adjusting the model parameters, using the training set to train the model, adjusting the model parameters;

[0073] Result analysis, using indicators such as accuracy, recall rate, and F1 score to evaluate the model performance, using indicators such as accuracy, recall rate, and F1 score to evaluate the model performance.

[0074] In specific use, through the application of the multimodal data analysis unit 3, data from different sources such as text descriptions, image displays, audio recordings, etc. can be analyzed and integrated, providing a comprehensive understanding of things. Multimodal data analysis provides richer and more accurate data support for decision-making, making the decision-making more scientific and reasonable.

[0075] Preferably: The intelligent analysis and decision-making unit 4 includes device mode recognition, prediction analysis of the future operating state of the device, and control decision-making;

[0076] Equipment pattern recognition: Use machine learning and deep learning algorithms to perform pattern recognition on the fused multimodal data to identify the normal operating status, abnormal status, and possible fault types of the equipment;

[0077] Prediction and analysis of the future operating status of equipment: Based on historical data and real-time data, the future operating status of the equipment is predicted using algorithms such as time series analysis and regression analysis, so that regulatory measures can be taken in advance;

[0078] Control decision making: Based on the results of pattern recognition and predictive analysis, combined with the equipment's operating objectives and constraints, formulate the optimal control strategy and management plan.

[0079] In specific use, through the application of the intelligent analysis and decision-making unit 4, technologies such as artificial intelligence, machine learning, and big data analysis can be used to deeply mine and analyze massive and complex data to support more efficient and accurate decision-making processes. Using machine learning and deep learning technologies, intelligent analysis can build predictive models to predict future trends and events. Intelligent analysis can monitor key indicators in real time, promptly identify potential risks, and issue early warnings.

[0080] Preferably: the X-ray equipment intelligent adaptive control unit 5 dynamically adjusts the equipment's operating parameters according to the results of intelligent analysis; optimizes resource allocation, reduces operating costs, and improves the overall performance of the equipment by intelligently analyzing the equipment's operating efficiency and energy consumption.

[0081] During specific use, the application of the intelligent adaptive control unit 5 of the X-ray equipment can automatically adjust its operating parameters, strategies or structures according to changes in the internal and external environment to maintain optimal performance or achieve predetermined goals. This control method integrates multidisciplinary technologies such as artificial intelligence, machine learning, and control theory, and has significant advantages.

[0082] Preferably: the X-ray equipment intelligent management unit 6 includes real-time monitoring of equipment operation status, equipment failure warning, equipment failure prediction, and equipment maintenance record registration and maintenance suggestions;

[0083] Real-time monitoring of equipment operation status: real-time monitoring of X-ray equipment operation status and recording of key indicators of X-ray equipment;

[0084] Equipment failure warning: When the equipment is in an abnormal state, the system can issue a warning signal in time and provide possible causes of the failure and solutions;

[0085] Equipment failure prediction: Use machine learning models to predict equipment failures and issue early warnings;

[0086] Equipment maintenance record registration and maintenance recommendations: Generate maintenance plans and recommendations based on equipment status and fault prediction results.

[0087] In specific use, through the application of the intelligent management unit 6 of the X-ray device, a scientific maintenance plan can be formulated according to the usage situation and maintenance history of the device in enterprise device management, thereby prolonging the service life of the device.

[0088] Preferably: The interaction and problem feedback unit 7 of the device user provides an intuitive visual interface to display the device status, analysis results, and regulation suggestions; it supports the feedback of users on system decisions to optimize the model and regulation strategy.

[0089] In specific use, through the application of the interaction and problem feedback unit 7 of the device user, with a friendly user interface and user experience design, users can easily interact with the device, reducing the learning cost. Problems encountered by users during use can be immediately feedback, and the system can respond and process quickly.

[0090] Working principle of implementation: First, the X-ray device operation data acquisition unit 1 collects data on X-ray related parameters, and then the preprocessing unit 2 of the collected data preprocesses the collected data, namely data cleaning, data alignment, feature extraction, and data enhancement;

[0091] The processed data is then analyzed and processed by the multi-modal data analysis unit 3, and finally a comprehensive information analysis result report is generated; the intelligent analysis and decision-making unit 4 makes a processing decision based on the generated analysis result report, and the processing decision is used to regulate the parameters through the intelligent adaptive regulation unit 5 of the X-ray device;

[0092] Then, the intelligent management unit 6 of the X-ray device predicts the status and faults of the X-ray device, and finally generates a maintenance plan and suggestions; the visual interface provided by the interaction and problem feedback unit 7 of the device user displays the device status, analysis results, and regulation suggestions.

[0093] Finally, it should be noted that: The above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An X-ray device adaptive regulation and management system based on multimodal intelligent analysis, characterized in that, Including: An X-ray equipment operation data acquisition unit (1) which is used to collect relevant data such as X-ray images, image metadata, operating voltage, current, exposure time, focal length, filter settings, detector parameters, temperature, humidity, radiation dose, air pressure, X-ray tube, cooling system, mechanical motion state, power supply state, log data, etc. during the operation of the X-ray equipment; A preprocessing unit (2) for the acquired data which is used to process missing values, outliers, duplicate data and noise data in the acquired data; A multi-modal data analysis unit (3) which is used to comprehensively analyze the processed data and generate a comprehensive information analysis result report; An intelligent analysis and decision-making unit (4) which is used to perform structural analysis on the report of the multi-modal data analysis and form a processing decision; An X-ray equipment intelligent adaptive regulation unit (5) which is used to regulate the operating parameters of the X-ray equipment according to the processing decision; An X-ray equipment intelligent management unit (6) which is used to generate a maintenance plan and suggestions according to the state of the X-ray equipment and the fault prediction result; An interaction and problem feedback unit (7) for the equipment user which is used to display the equipment state, analysis result and regulation suggestions through a visual interface.

2. The X-ray device adaptive regulation and management system based on multimodal intelligent analysis according to claim 1, wherein: The data collected by the X-ray equipment operation data acquisition unit (1) includes equipment system configuration data, equipment operation image data, equipment operation text data, equipment usage energy consumption data, sensor induction data and equipment usage environment data; Equipment system configuration data such as the processor model, memory capacity and software version used by the X-ray equipment, equipment operation image data such as X-ray images and thermal imaging maps generated during the operation of the X-ray equipment, equipment operation text data such as X-ray equipment operation logs and error logs, equipment usage energy consumption data such as energy usage efficiency and power consumption data, sensor induction data includes temperature, humidity, voltage, current and vibration data collected by sensors, and equipment usage environment data includes light, noise and radiation data.

3. The X-ray device adaptive regulation and management system based on multimodal intelligent analysis according to claim 1, characterized in that: The preprocessing unit (2) for the acquired data includes data cleaning, data alignment, feature extraction and data enhancement; Data cleaning: When there are missing values in the collected data, use the mean, median, mode or prediction model to fill the missing values; When there are outliers in the collected data, compare and correct the outlier data according to the historical records; When there are duplicate data in the collected data, keep one of the data and then delete the remaining duplicate data; Remove noise at specific frequencies from the noise data through low-pass, high-pass or band-pass filters.

4. The X-ray device adaptive regulation and management system based on multimodal intelligent analysis according to claim 3, characterized in that: The data alignment matches, adjusts and integrates data from different sources, different formats or different structures to make them consistent or compatible in dimensions such as time, space, semantics or structure; For the feature extraction, a pre-trained deep learning model (such as ResNet, VGG) is used to extract image features, the Bag of Words or TF-IDF is used to extract text features, time series analysis methods (such as Fourier transform, wavelet transform) are used to extract frequency domain features, and Mel Frequency Cepstral Coefficients (MFCCs) are used to extract audio features; For the data augmentation, methods such as rotation, scaling, flipping, and cropping are used to generate new image samples, and color transformation (such as brightness and contrast adjustment) is used to increase image diversity; methods such as synonym replacement, random insertion, and random deletion are used to generate new text samples, and Back Translation is used to translate the text into another language and then back; methods such as time offset and noise addition are used to generate new time series samples.

5. The X-ray device adaptive regulation and management system based on multimodal intelligent analysis according to claim 1, characterized in that: The multimodal data analysis unit (3) includes multimodal data fusion, multimodal data modeling, model training and optimization, and result analysis; For multimodal data fusion, machine learning algorithms (such as random forest, support vector machine) and deep learning models (such as convolutional neural network, recurrent neural network) are used for data fusion; For multimodal data modeling, data from different modalities (such as images, text, audio, sensor data, etc.) are integrated and analyzed, and models are constructed using data from multiple modalities (such as images, text, audio, sensor data, etc.).

6. The X-ray device adaptive regulation and management system based on multimodal intelligent analysis according to claim 1, characterized in that: For model training and optimization, the data is divided into a training set, a validation set, and a test set. The model is trained using the training set, and the model parameters are adjusted. The model is trained using the training set, and the model parameters are adjusted. The model is trained using the training set, and the model parameters are adjusted; For result analysis, metrics such as accuracy, recall rate, and F1 score are used to evaluate the model performance. Metrics such as accuracy, recall rate, and F1 score are used to evaluate the model performance.

7. The X-ray device adaptive regulation and management system based on multimodal intelligent analysis according to claim 1, characterized in that: The intelligent analysis and decision-making unit (4) includes device mode recognition, prediction and analysis of the future operating state of the device, and formulation of control decisions; Device mode recognition: Machine learning and deep learning algorithms are used to perform mode recognition on the fused multimodal data to identify the normal operating state, abnormal state, and possible fault types of the device; Prediction and analysis of the future operating state of the device: Based on historical data and real-time data, algorithms such as time series analysis and regression analysis are used to predict the future operating state of the device so as to take control measures in advance; Formulation of control decisions: According to the results of mode recognition and prediction analysis, combined with the operating objectives and constraints of the device, the optimal control strategy and management plan are formulated.

8. The X-ray device adaptive regulation and management system based on multimodal intelligent analysis according to claim 1, characterized in that: The intelligent adaptive regulation unit (5) of the X-ray device dynamically adjusts the operating parameters of the device according to the results of intelligent analysis; by intelligently analyzing the operating efficiency and energy consumption of the device, the resource allocation is optimized, the operating cost is reduced, and the overall performance of the device is improved.

9. The X-ray device adaptive regulation and management system based on multimodal intelligent analysis according to claim 1, characterized in that: The intelligent management unit (6) of the X-ray device includes real-time monitoring of the device operating state, device fault warning, device fault prediction, and registration of device repair records and maintenance suggestions; Real-time monitoring of the device operating state: The operating state of the X-ray device is monitored in real time, and the key indicators of the X-ray device are recorded; Device fault warning: When the device is in an abnormal state, the system can issue a warning signal in a timely manner and provide possible causes of the fault and solutions; Device fault prediction: Use a machine learning model to predict device faults and issue early warnings; Device repair record registration and maintenance suggestions: Generate a maintenance plan and suggestions based on the device status and fault prediction results.

10. The X-ray device adaptive regulation and management system based on multimodal intelligent analysis according to claim 1, characterized in that: The interaction and problem feedback unit (7) of the device user provides an intuitive visual interface to display the device status, analysis results, and regulation suggestions; Supports user feedback on system decisions to optimize the model and regulation strategies.

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