36results about How to "Provide accurately" patented technology

The invention relates to the field of application of an instantaneous elasticity imaging technology to liver sclerosis detection, in particular to an intelligent analysis system based on the instantaneous elasticity imaging technology. Comprising a shear wave imaging module, a medical history detection calling module and an intelligent analysis module, and the shear wave imaging module is used for generating shear waves and longitudinal waves through energy pulses and conducting imaging processing on real-time data of the shear waves obtained through patient detection; the medical history detection calling module is used for acquiring detailed patient conditions through the patient medical history and detection records; and the intelligent analysis module is used for jointly analyzing through the shear wave imaging module and the medical history detection calling module so as to determine disease causes and give suggestions. According to the image drawn by the shear wave, the condition of the liver of a patient can be reflected more visually and accurately, the judgment of the liver is more accurate, inaccurate factors in illness state judgment are reduced, and the system can reduce errors caused by the influence of factors such as the technical level of an operator, equipment performance and the like when the liver is detected by an instantaneous elastography technology.

The invention provides an information base construction method and device, a text information generation method and device, equipment and a medium. Comprising the steps of obtaining to-be-constructed task requirement information and to-be-constructed text examples; determining a keyword of to-be-constructed task requirement information; generating and displaying original text information to the user based on the keyword and the to-be-constructed text example; in response to a feedback operation of the user on the original text information, determining target original text information and non-target original text information in the original text information; and if the target original text information and the non-target original text information meet a preset similarity requirement, storing the keyword and the to-be-constructed text example into an information base, and constructing an index relationship between the keyword and the to-be-constructed text example in the information base, so that the language processing model can obtain the to-be-constructed text example after receiving the task requirement information. And carrying out use when the target text information is generated. Through the method, the effect of generating the original text content by the language processing model is improved.

The invention relates to the technical field of power distribution and utilization and communication, in particular to a multi-source wide-area power distribution and utilization terminal time correction method and device, electronic equipment and a chip. The time correction method comprises the steps that a multi-source fusion power distribution and utilization terminal obtains reference time service time based on a preset reference time service source or based on multiple different time service sources, a time service deviation value between the reference time service time and the time service time of the to-be-corrected time service source is calculated, a time service time optimization parameter is determined according to the time service deviation value in combination with a moving average filtering algorithm improved based on Pearson's correlation, and the time service time optimization parameter is used for correcting the time service time of the to-be-corrected time service source. When time service time optimization parameters are determined, a moving average filtering algorithm which is improved based on Pearson's correlation is combined, and the correlation between data is considered, so that noise can be effectively filtered, time deviation can be smoothed, the accuracy of time service correction is improved, and the high-accuracy time service synchronization requirement of the power distribution and utilization terminal in a power system is met.

The invention provides a method, a device, a storage medium and a system for determining overheating abnormity of a target component. The method comprises the following steps: acquiring infrared images and ultraviolet detection images of a plurality of switch cabinets; according to the plurality of infrared images and the plurality of ultraviolet detection images, judging whether the switch cabinet has an overheating area or not; and under the condition that the target switch cabinet has the overheat area, according to the space information of the target switch cabinet and the overheat area, a target assembly with overheat abnormity in the target switch cabinet is determined, the first detection temperature of the overheat area is larger than a first threshold value, and the space information comprises position distribution information of a plurality of assemblies in the target switch cabinet. The method can at least solve the problem that the overheating abnormal component in the switch cabinet cannot be accurately obtained in the prior art.

The novel beacon vessel comprises a base and further comprises a water flow power generation device and a solar power generation device which are installed on the base, the base is arranged to be cylindrical, a notch is formed in the middle of the base, an impeller of the water flow power generation device overhangs in the notch to rotate, and the cylindrical base rotates in real time in the water flow direction. A solar power generation device is mounted on the top surface of the base at the rear part of the notch, and is provided with a foldable turnover mechanism, so that a solar panel of the solar power generation device is always positioned at the optimal sunlight receiving angle; multi-source power generation is achieved through the water flow power generation device and the solar power generation device, redundant electric energy is stored for standby application and delivery while power is supplied to the beacon light and other electric equipment on the device, real-time data acquisition is achieved through the camera and the light induction sensor, and the device is simple and compact in structure, reliable in operation, low in cost, convenient to install and high in practicability. Power generation is stable and efficiency is high.

The invention discloses a multi-modal named entity recognition method based on multi-granularity feature enhancement, which comprises the following steps of: firstly, carrying out single-modal feature extraction on input data, and then carrying out multi-modal multi-granularity feature interaction on the input data based on a single-modal feature extraction result; and finally, performing label prediction of the input data based on a multi-granularity feature interaction result to complete entity identification. According to the scheme, a multi-modal named entity recognition framework capable of being used for multimedia image-text posts is defined, the single-modal feature extraction firstly reduces the influence of the result of irrelevant interference of texts and images, the performance of processing informal and short text contents is achieved, the problem of sparse and noisy data is effectively solved, and the recognition efficiency of the multi-modal named entities is improved. The multi-modal multi-granularity semantic interaction fully considers the correlation between the text and the picture and the local and overall necessity of the picture feature, more comprehensive visual guidance required by the text is obtained, the accuracy of final label prediction is improved, and the experiment has a good experiment result on a witter data set and has certain popularization and practical values.

The invention discloses a wearable health scheme recommendation system based on an Internet of Things gateway, and belongs to the field of wearable medical equipment. Comprising an MCU processor, a touch screen display module used for displaying human body characteristic data, a voice module used for interacting with wearable medical equipment, a communication module used for uploading obtained human body monitoring indexes to a big data cloud platform, a data obtaining module used for obtaining detailed vital sign data of a wearer, and an AI module, and the module is used for analyzing the health data recorded by the wearer, is located on a cloud network platform, accesses the AI model, analyzes the health index data acquired by the sensor, compares a historical medical case database, and formulates a set of personalized medical health scheme for the wearer by adopting a health scheme recommendation algorithm based on cases. The invention aims to become an innovative customized platform, so that wearers can integrate health tracking into personal health habits of the wearers, and a sexual health scheme can be timely and accurately provided.

This invention provides a method and apparatus for detecting the reuse of centrifuge tubes in ultra-high-speed centrifuges, comprising the following steps: S1, pressurizing and filling a medium into a new centrifuge tube, and detecting the diameter deformation of the centrifuge tube online; S2, using the maximum pressure that the centrifuge tube can withstand to return to its initial diameter as the yield limit pressure value; S3, replacing the centrifuge tube to be reused, pressurizing and filling the centrifuge tube to be reused with a medium, controlling the reuse pressure value at 75%~95% of the yield limit pressure value; S4, detecting the diameter deformation of the centrifuge tube to be reused online; S5, selecting the centrifuge tube that can return to its initial diameter as the reuse centrifuge tube. This invention can detect centrifuge tubes and determine whether they can be safely reused, significantly reducing experimental costs. It can be used to detect whether replacement centrifuge tubes meet the application requirements of ultra-high-speed centrifuges. It prevents substandard centrifuge tubes from entering the ultra-high-speed centrifuge, causing equipment damage or even sample leakage.

This application provides an artificial intelligence model download method, an apparatus, and a system. The method includes: A terminal device receives model feedback information from an access network device, where the model feedback information indicates a download mode that is of a first artificial intelligence model and that is configured for the terminal device, and the download mode that is of the first artificial intelligence model and that is configured for the terminal device is a download mode supported by the terminal device. The terminal device may download the first artificial intelligence model in the download mode indicated by the model feedback information. According to the foregoing method, a network device configures, for the terminal device by using the model feedback information, the download mode that can be supported by the terminal device, so that the terminal device can download the first artificial intelligence model supported by the terminal device, to avoid a case in which a downloaded artificial intelligence model cannot be used.

The utility model discloses a kind of heat recovery devices for efficient desulfurizer preparation system, it is related to desulfurizer preparation technical field, including heating furnace, heat exchange tube and phase change heat storage tank, the heating furnace surface is wound with heat exchange tube, the both ends of the heat exchange tube are respectively equipped with liquid inlet and liquid outlet, the side of the heating furnace is equipped with phase change heat storage tank, the phase change heat storage tank is filled with composite phase change heat storage material, the liquid inlet and the liquid outlet are respectively fixedly connected with the top and bottom of one side of phase change heat storage tank.The utility model is by being provided with spiral winding heat exchange tube, greatly increase heat exchange area, combine high thermal conductivity material, significantly improve heat collection efficiency, compared with traditional device can recycle more heat, and adopt the phase change heat storage tank filled with composite phase change heat storage material, cooperate with heat preservation layer and stirring device, can efficiently store heat, guarantee the stable supply of heat, and make heat storage material heated evenly.

The utility model relates to the technical field of water pump drivers, in particular to a solar water pump driver capable of working at wide voltage, which is characterized by comprising a single chip microcomputer, a motor driving module and a DCDC power supply module, the DCDC power supply module is used for connecting a solar panel and receiving a wide voltage source VB +, the single chip microcomputer is connected with the motor driving module, and the motor driving module is connected with the motor driving module. The motor driving module is used for being connected with a water pump motor, a PWM pin of the single-chip microcomputer is connected with the voltage regulating circuit, the voltage regulating circuit obtains a wide voltage source VB + and provides a working voltage source VBUS, the working voltage source VBUS is provided for the motor driving module, and the single-chip microcomputer is further connected with the voltage sampling circuit. The two voltage sampling circuits are respectively connected with the voltage regulation circuit to respectively sample a wide voltage source VB + and a working voltage source VBUS. According to the utility model, the input and output voltages in the voltage regulation process are sampled in real time, and the voltage regulation circuit is utilized to regulate and configure the wide-range voltage of the solar panel, so that the beneficial effect of improving the working safety and reliability of a hardware circuit is achieved.

The invention discloses a precipitation estimation method based on DEM (Digital Elevation Model) and SAR (Synthetic Aperture Radar) data. The method is characterized by comprising the following steps: acquiring and preprocessing data; data registration: performing accurate geographic registration on the multi-temporal dual-polarized SAR image and the DEM data to ensure that the two kinds of data are aligned under the same geographic coordinate system; surface water body extraction: carrying out image enhancement on the SAR image, and selecting a threshold value to carry out water body extraction; and surface change detection: detecting the range change of the surface water body by using a change detection technology, and identifying the change of the surface water body by comparing SAR image water body images before and after rainfall. In the change detection, two SAR images in different periods are analyzed, and the pixel difference of the SAR images is calculated to detect the surface change; and carrying out precipitation estimation in combination with DEM data. And establishing a mathematical model between the precipitation and the surface deformation by using topographic information provided by the DEM data, and estimating the precipitation. The method can accurately and quickly provide precipitation information of severe terrain areas in extreme weather.

The invention provides a license-plate-free automatic weighing method and weighing system based on Tag identification, and relates to the technical field of weighing, the method and system are applied to a weighing vehicle of which the front end and the rear end are both provided with Tag equipment, the front end and the rear end of the weighing vehicle are provided with the Tag equipment, when the weighing vehicle enters a weighing area, a first Tag sensor reads front-end Tag information, the front-end Tag information is compared with a data mapping library to confirm the vehicle, and after confirmation, the weighing vehicle enters the weighing area. The first Tag sensor and the second Tag sensor work at the same time, whether the vehicle is completely located in the weighing area or not is judged according to front and back Tag information, if yes, vehicle information and weight data are recorded, and when the vehicle leaves, the second Tag sensor detects the rear end Tag, and if not, it is regarded that the vehicle leaves the parking lot. Through Tag identification and position confirmation, accurate and efficient weighing is ensured, manual intervention is reduced, and logistics transportation efficiency and safety are improved.

The invention provides a centrifuge tube reuse detection method and device for an ultra-high-speed centrifuge, and the method comprises the following steps: S1, pressurizing and filling a new centrifuge tube with a medium, and carrying out the online detection of the diameter deformation condition of the centrifuge tube; s2, taking the maximum pressure value which can be borne by the centrifugal tube when the centrifugal tube returns to the initial diameter as a yield limit pressure value; s3, replacing the to-be-reused centrifugal tube, pressurizing and filling the to-be-reused centrifugal tube with a medium, and controlling the reuse pressure value to be 75-95% of the yield limit pressure value; s4, detecting the diameter deformation of the centrifuge tube to be reused on line; and S5, selecting a to-be-multiplexed centrifugal tube capable of returning to the initial diameter as a multiplexed centrifugal tube. The centrifugal tube can be detected, whether the centrifugal tube can be safely reused or not is judged, and the experiment cost is greatly reduced. The device can be used for detecting whether the replaced centrifuge tube meets the application requirements of the ultra-high-speed centrifuge. And the centrifugal tube with substandard quality is prevented from entering the ultra-high-speed centrifugal machine to cause equipment damage and even sample leakage.

The invention relates to a PET low-dose imaging method and device based on deep learning and a medium. The method comprises the following steps: extracting two-dimensional image slices from paired low-dose PET data and full-dose PET data along a sagittal plane, a coronal plane and a cross section respectively; respectively slicing the two-dimensional PET image extracted from each surface to obtain a slice image of each surface, and training to obtain an image estimation model of each surface through a two-dimensional coding and decoding network; inputting each surface of the low-dose three-dimensional PET into the image estimation model to obtain a full-dose estimation result of each surface, and superposing the estimation results to obtain a full-dose three-dimensional PET of three-surface estimation; and after splicing, inputting into a three-dimensional residual depth fusion network, and eliminating direction artifacts to obtain a final full-dose three-dimensional PET estimation result. Compared with the prior art, the image obtained by the method comprises three-dimensional features and spatial fusion perception information, and has the advantages of low acquisition difficulty, high image quality and the like.

The invention discloses a quantitative business classification method and system supporting extension, and the method is characterized in that the method comprises the following steps: collecting customer complaints and suggestions, and carrying out the semantic extraction of the customer complaints and suggestions; performing key point identification and analysis according to the extracted semantic information to obtain key semantics; performing intelligent key point analysis on the key semantics to realize customer complaint classification; and based on the customer complaint classification, automatically assigning current customer complaints and suggestions to a business unit executing customer complaint processing. The method has good diversity, comprehensiveness, complementarity and robustness.

The invention provides an impedance matching network and a radio frequency power supply system, and relates to the technical field of radio frequency. The impedance matching network is used for performing impedance matching on the radio frequency power supply and the load. The impedance matching network comprises a first cable, an adjusting module, a sampling module and a control module. The first cable is provided with a first end and a second end which are opposite and a grounding point located between the first end and the second end, the first end is used for being connected with the input end of the load, the second end is open-circuited, and the grounding point is used for grounding. The adjusting module is used for adjusting the position of a grounding point of the first cable, so that the grounding point changes between the first end and the second end. The sampling module is used for sampling reactance parameters of the load. The control module is connected with the adjusting module and the sampling module, and the control module is used for receiving reactance parameters of the load and controlling the adjusting module to adjust the position of the grounding point according to the reactance parameters of the load. According to the invention, impedance matching can be rapidly, conveniently and accurately carried out on the radio frequency power supply and the load.

The invention relates to the technical field of environmental protection, in particular to a dust particle counting device which comprises a particle counter, an air guide pipe, a transfer bin and a collecting pipe and further comprises a first sealing plate, and the first sealing plate is arranged in the collecting pipe. The second sealing plate is rotationally arranged in the collecting pipe and is attached to the first sealing plate; the induction filter plate is positioned on the transfer bin; the dustproof locking assembly is arranged on the transfer bin, and when the sensing filter plate is blocked by dust in air, the dustproof locking assembly is used for driving the second sealing plate to rotate to seal the collecting pipe. When the dust particle counting device is used, high-concentration dust may damage precise parts of the dust particle counting device, such as blocking of a sensor and abrasion of mechanical parts, the dust particle counting device avoids direct damage of dust to equipment through the dustproof locking assembly, and the service life of the equipment is prolonged.

The system of the present invention dynamically calls artificial intelligence memory and emotion to interact with a large language model, including a processor, a remote server for processing the emotional state of an administrator, and a first display module for users with a first camera module installed and a second display module for administrators with a second camera module installed, respectively used to capture the user's face and the administrator's face; the user uses a first voice module, and the administrator uses a second voice module; the processor can run the following program modules: a knowledge acquisition module, a knowledge parsing module, an input module, and an evaluation module. The interactive knowledge management system of the present invention interacts with the user and the administrator respectively in terms of face and voice, realizes rapid association with other user faces in the same field or with the same preferences, and efficiently and accurately provides the knowledge data that the user is concerned about, realizes the administrator's emotional monitoring, and makes the managed knowledge data more able to avoid unexpected security issues.

The invention discloses a multi-body-position adjustable ultrasonic image examination device which comprises a base, a fixed transverse plate, a synchronous frame and a connecting rod, a sliding groove is formed in the fixed transverse plate, and the two ends of the fixed transverse plate are movably connected with a first sliding frame and a second sliding frame respectively and matched with the sliding groove. A first linkage plate and a second linkage plate are fixedly installed at the two ends of the synchronous frame and are arranged in parallel, a third linkage plate is movably connected to one side of the first linkage plate, a linkage frame is hinged to the third linkage plate through a second connecting rod, and a supporting frame is fixedly installed at one end of the linkage frame; one end of the supporting frame is fixedly connected with a bed surface, a movable plate is arranged at one end of the bed surface, guardrails are fixedly installed on the two sides of the bed surface, and a multi-angle leg frame is fixedly installed at one end of the movable plate. The linkage device is arranged to drive the whole equipment to operate, and multi-angle folding and position changing can be carried out, so that examination of multi-body-position changing is achieved.

The present application relates to the technical field of glass production, and provides a mixing method for improving the temperature of glass production mixture, which is applied to a mixer with a stirring cavity and comprises the following steps: S1, starting the mixer to sequentially perform dry mixing and wet mixing on glass raw materials; S2, when entering the wet mixing stage, a steam supply unit is opened, so that high-temperature steam starts to be introduced into the stirring cavity of the mixer; and during the whole duration of the wet mixing stage, the steam supply unit is kept in an opened state; S3, when the wet mixing stage reaches a preset duration of the system, the steam supply unit is closed, and the introduction of high-temperature steam is stopped; and when the wet mixing stage ends, the temperature of the material is improved from an initial value to not less than a preset target temperature, thereby effectively solving the problem that the mixing temperature is substandard in a low-temperature environment. The present application also provides a mixing system for realizing the method, which can significantly improve the mixing uniformity and reaction activity, and has the advantages of precise temperature control, energy saving and high efficiency.

The invention relates to the technical field of power distribution network management, in particular to a power grid power supply information digitization system, which comprises a central control module, and the central control module is connected with an intelligent identification module, an information arrangement and classification module, a data verification and supplement module, a power consumption prediction module and a service push module. Arrangement and classification are carried out according to the correlation degree, verification and supplement are carried out through government and enterprise data integration, authenticity reflection of data is achieved, then electricity utilization information of customers is integrated to push services of the customers, and according to the principle of deep learning, the electricity utilization habits of single customers are predicted and judged, and then accurate service providing is achieved. In addition, a digital transformation and digital power grid construction technical route can provide good use experience for customers, and a safe and reliable power supply service guarantee framework is provided for the customers.

The invention relates to an inpatient vital sign monitoring device. An inner cavity is formed in the fixing cylinder, the baffles are fixedly arranged at the front end and the rear end of the fixing cylinder, the air bag assembly is arranged at the inner end of the fixing cylinder and connected with the baffles on the two sides, and the elastic assemblies are fixedly arranged on the peripheral side of the air bag assembly. The heart rate sensor and the blood oxygen sensor are fixedly arranged on the inner side wall of the air bag assembly; the elastic assembly comprises a top plate and a first spring, and the top plate is fixedly connected with the air bag assembly. According to the device, the hand of a patient extends into the air bag assembly, the air bag assembly is filled with air through the air inlet pipe, and the air inlet pipe is closed, so that the air bag assembly wraps and clamps the arm of the patient, and the heart rate sensor and the blood oxygen sensor arranged on the air bag assembly on the inner side of the air bag assembly are tightly attached to the skin of the patient; interference of external factors is reduced, and monitoring data can be accurately provided in real time.

The invention provides a theoretical prediction and verification method for a thermal expansion coefficient of a composite material 2D fabric, and the method comprises the steps: extracting a circulation structure in the composite material 2D fabric, and building an RVE model; predicting x-direction and y-direction thermal expansion coefficients of the RVE model, and predicting z-direction thermal expansion coefficients of the RVE model; establishing an RVE finite element numerical model based on the actual geometric dimension and the weaving structure of the composite material fabric, performing simulation analysis, and verifying an analytical solution; an RVE finite element model is established according to weaving structure parameters of the composite material fabric, a thermal expansion coefficient numerical solution is obtained through finite element simulation calculation, the prediction trend of the numerical solution and the prediction trend of an analytical solution are consistent, the error is within 2%, the prediction precision of an APTC method is verified, and the accuracy of the method is proved. The method can rapidly predict the thermal expansion coefficient of the composite material, reduces the cost, and improves the efficiency of scientific research and production.

A multi-fuel blending test system for conveying blended fuel to a test piece is provided, the system comprises an aviation kerosene supply assembly, a biofuel supply assembly, a blending assembly, a nitrogen supply system and a pump set, and the aviation kerosene supply assembly comprises a kerosene tank; the biofuel supply assembly comprises a biofuel oil tank; the mixing assembly is connected with the aviation kerosene supply assembly and the biofuel supply assembly and used for adjusting the mixing proportion of aviation kerosene and biofuel and outputting mixed fuel. The nitrogen supply system is used for providing pressure for driving aviation kerosene and biofuel to flow; and the pump set is arranged between the mixing assembly and the test piece and is used for secondarily pressurizing and mixing the fuel. The invention further provides a multi-fuel mixing test method. According to the system and the method, the blended fuel can be stably and accurately provided.

The invention provides a PMU and PQMD hybrid harmonic state estimation method based on measurement data adaptive correction, which comprises the following steps of: taking a PMU sampling moment as an estimation moment, introducing an optimization factor into a maximum value and a minimum value of PQMD statistical data, representing harmonic data of a PQMD measurement point as a bounded uncertainty variable, and constructing a PMU and PQMD hybrid harmonic measurement set. Establishing a hybrid harmonic state estimation model by taking the optimizing factor and the harmonic state quantity as optimization variables and taking the minimum standardized measurement residual sum of squares as an optimization target; solving a linear feasible region of the harmonic state quantity by adopting a linear programming algorithm based on iterative operation, and simplifying a harmonic state estimation model into a convex optimization model with a linear constraint condition; and solving the simplified harmonic state estimation model by adopting an interior point method, searching an optimal solution of an optimization target in an optimization variable feasible region, and adaptively correcting harmonic data of a PQMD measurement point by utilizing an optimization factor in the solving process so as to estimate a whole-network harmonic state quantity at a PMU sampling moment.

The invention provides a transformer area network loss analysis method, system and device and a medium. The method comprises the steps that a simulation analysis model is established based on various collected data containing distributed power sources in a transformer area; based on each accessible position of the distributed power supply, performing power flow simulation calculation by using the simulation analysis model to obtain a simulation result of each access position; and respectively calculating the transformer area network loss corresponding to each access position based on the simulation result of each access position. According to the invention, through load flow calculation, the phase angle information of voltage and current and the problems of nonlinear load and three-phase imbalance caused by access of the distributed power supply can be comprehensively considered, so that a network loss analysis result can be accurately and comprehensively provided, and meanwhile, the calculation efficiency is also improved.

The invention discloses a water supply pipeline network intelligent monitoring system based on an artificial intelligence algorithm, which relates to the technical field of water supply pipeline monitoring and realizes real-time monitoring and intelligent management of the running state of a water supply pipeline by integrating a plurality of functional modules such as data acquisition, data processing, calculation analysis and intelligent alarm. Compared with a traditional underwater sound leakage detection and manual inspection mode, the system improves the accuracy and efficiency of leakage detection to a certain extent, reduces the workload and cost of manual inspection, and can quickly position a leakage point and give an alarm in time based on DMA partition metering and intelligent analysis technologies, so that the leakage detection efficiency is improved. The operation efficiency and safety of the water supply network are improved, the overall management level of the water supply system is improved to a certain extent, the system can accurately position the position where a problem possibly exists in the pipeline network by calculating the position judgment function E (in), and the accurate positioning can quickly respond and accurately repair the abnormal or fault point of the pipeline.

The application provides a question and answer method and system based on a large language model, which comprises the following steps: determining a current question of a user and a natural language understanding prompt word; inputting the current question and the natural language understanding prompt word into a pre-trained large language model to obtain a question understanding result and a question to be answered output by the large language model according to a natural language understanding strategy; in the case that the question understanding result is a factual question, retrieving an answer from a knowledge graph based on semantic analysis; inputting the retrieved answer and an answer verification prompt word into the pre-trained large language model to obtain an answer verification result; in the case that the verification is reasonable, taking the retrieved answer as the final answer to the current question; and in the case that the verification is unreasonable, generating an answer by the large language model. In the multi-round question and answer task, the application can deeply understand the question of the user based on the context, effectively retrieve and integrate information from different knowledge sources, and thus accurately and efficiently provide an answer to the current question.

The present invention discloses a method for inversion of microseismic monitoring of dynamic and static stress fields of coal-rock formations and intelligent recognition of abnormalities. Firstly, using data such as source location and coordinates of microseismic sensors, wave velocity field inversion imaging is performed on coal-rock formations; secondly, two microseismic events located in adjacent time periods and close to each other are used to perform time difference imaging on the time difference of the first arrival of the P wave reaching the sensor, and a wave velocity time difference image is obtained; on this basis, according to the microseismic signals generated by the destruction of coal-rock formations, the source location and quantitative inversion of the focal mechanism of the destruction of coal-rock formations are performed to obtain the destruction position, fracture size and crack direction of the coal-rock formations; the dynamic and static stress fields of coal-rock formations are jointly inverted by comprehensively utilizing wave velocity field imaging, wave velocity time difference imaging, source location and quantitative parameters of focal mechanism, and the dynamic and static stress fields of coal-rock formations are obtained; finally, the abnormal areas of the dynamic and static stress field images are intelligently identified based on the deep learning algorithm, providing technical support for the monitoring of the dynamic and static stress fields of coal-rock formations.