24 results about "Detection diagnosis" patented technology

The invention provides a crop disease and pest recognition and pathology follow-up method and device and a medium, and relates to the technical field of crop disease and pest recognition. Coding the diagnosis hypothesis in the text format into vector representation of a fixed dimension; configuring comprehensive feature representation; through a multi-stage strategy, a soft label is generated by the teacher model, and the soft label is used as supervision information to guide the student model; model check points are saved in the training process, and student model performance is evaluated by using the verification set; predicting development condition parameters of various diseases; simulating the diffusion process of the disease in the space grid through convolution operation to obtain a propagation probability graph in the future N days; a disease progress prediction result generated in combination with the disease propagation condition is used for evaluating the development trend of crop diseases and insect pests. According to the invention, detection and diagnosis of crop diseases and insect pests are realized, the propagation path of the diseases and insect pests can be traced, and root blocking measures are recommended.

The invention discloses a semi-rigid base asphalt pavement recessive disease quantitative evaluation method, which comprises the following steps: S1, detecting a pavement in a detection area by using a ground penetrating radar, and carrying out image processing on acquired data to obtain high-quality detection data; s2, analyzing the detection data, performing classification marking on the images of the abnormal areas, recording the positions and sizes of the abnormal areas, and performing core drilling sampling on part of the abnormal areas to determine the disease types of the abnormal areas; s3, collecting deflection values of a normal road surface and an abnormal area by using a falling weight deflectometer, and determining an influence coefficient of the disease on the structural strength of the road surface; and S4, performing quantitative evaluation on the semi-rigid base asphalt pavement according to the influence coefficient and the disease area of the recessive disease. According to the method, the influence of the recessive diseases on the strength of the semi-rigid asphalt pavement can be quantified, the internal condition of the semi-rigid asphalt pavement can be evaluated, and reference can be provided for detection diagnosis and maintenance decision of the recessive diseases in the asphalt pavement.

The invention relates to the technical field of building curtain wall maintenance, in particular to a curtain wall hidden project safety diagnosis method and device, and the method comprises the steps: forming a detection hole in a diagnosis region corresponding to a connection structure of a curtain wall, carrying out the visual image data collection of the connection structure in a curtain wall hidden project through an endoscope, building a three-dimensional model, and carrying out the visual image data collection. According to the method, parts which are not easy to dismantle and observe in a hidden project are visually detected and diagnosed, the actual state of a connecting structure is displayed in a three-dimensional modeling mode, and the state of a curtain wall is accurately diagnosed through intelligent classification diagnosis and comprehensive processing of the connecting structure. According to the method, images and measurement data are accurately utilized to intuitively reflect and intelligently diagnose problems, the error rate of manual appearance diagnosis is reduced, the decision making process is more scientific and accurate, hidden danger areas can be timely maintained and modified, safety risks of existing curtain walls are clearly and accurately reduced, and potential safety hazards are eliminated.

The invention relates to the technical field of pathogen detection, and discloses a respiratory system infection viroid sample detection device, which comprises a detection cylinder, a detection card is arranged in the detection cylinder, a one-way air inlet blowing nozzle is arranged at the port of the detection cylinder, and blown air is guided to be stored in an air cavity in the detection cylinder; the detection card comprises a gas production area, the surface is horizontally unfolded opposite to the gas outlet end of the blowing nozzle, and a gap in contact with the gas cavity is reserved in the gas production area; the transparent window is arranged outside the detection cylinder, and a display area is arranged in the middle of the detection card. The handheld portable blowing detection tube is adopted, breath containing droplets is guided to be intensively blown to a detection card sample introduction area, the structure is simple, sampling and detection are efficiently integrated, the infection risk in the use process is greatly reduced, medical staff are not needed for detection, a large amount of manpower and material resources are saved, and the detection efficiency is improved. The method is especially suitable for rapid screening of people closely contacted with a large number of suspected cases and definite cases, and the pressure of detection and diagnosis work can be effectively relieved.

This abnormality diagnostic device for diagnosing an abnormality that occurs in a factory acquires data to be used for detecting an abnormality that occurs in a factory, detects an abnormality of a subject of diagnosis by using the data to be used for detecting an abnormality, reports the detected abnormality, acquires data to be used for analyzing an abnormality, and analyzes a candidate abnormality cause by using the data to be used for analyzing an abnormality in a period including a time point at which the abnormality has occurred, or by using the data to be used for analyzing an abnormality and the data to be used for detecting an abnormality in a period including a time point at which the abnormality has been detected.

The present disclosure relates to a drift detector to detect a drift in features of a diagnosis, the drift detector comprising a first collecting device configured to collect relevant explanations and raw data, a first database compiling the relevant explanations and raw data collected by the first collecting device, a second collecting device configured to collect relevant available expert knowledge from reliable sources, a second database compiling the relevant available expert knowledge from reliable sources collected by the second collecting device, a learned feature extractor configured to group initial data of the second database into a characteristic feature pattern for different diagnoses and to subsequently group the data from the first database into first feature patterns by diagnosis and from the second database into second feature patterns by diagnosis, a comparator configured to compare the empirical distributions of each of the grouped feature patterns in the databases with each other, and a processor configured to generate a report if results of the comparison do not comply with a predefined condition. Applications include medical applications such as recognizing new diseases.

The invention relates to the technical field of agent collaboration systems, in particular to a power station equipment anomaly detection decision management method based on Agent collaboration and related equipment, the system constructs four functional modules of a detection Agent, a diagnosis Agent, a knowledge Agent and a scheduling Agent, and real-time collection and standardized processing of multi-source heterogeneous detection data are achieved. The detection Agent monitors the standardized data in real time, and triggers the scheduling Agent to generate a diagnosis task tree when the standardized data is abnormal; and the scheduling Agent issues the subtasks to the diagnosis Agent for root cause analysis, or calls the knowledge Agent to obtain auxiliary diagnosis knowledge. The diagnosis Agent generates a preliminary conclusion, the knowledge Agent provides domain knowledge support, and the scheduling Agent fuses the information of the diagnosis Agent and the knowledge Agent to form a final decision containing an abnormal level, a risk level and an operation and maintenance strategy. According to the system, through data sharing and task collaboration between Agents, accurate identification, rapid diagnosis and scientific decision making of power station anomalies are realized, and the operation and maintenance efficiency and safety are improved.

A system and method for multivariate learning and optimization that repeatedly generates self-organizing experimental units (SOEUs) based on one or more hypotheses of a randomized multivariate comparison of a process decision to be provided to a user of the system. The SOEU is injected into the system to generate a quantitative inference regarding the process decision. In response to injecting the SOEU, at least one confidence interval within the quantization inference is identified, and the SOEU is iteratively modified based on the at least one confidence interval to identify at least one causal interaction of the process decision within the system. Causal interaction can be used for testing, diagnosis and optimization of system performance.

The application discloses a method and system for three-dimensional positioning of a medical diagnosis position by ultrasound. The method comprises the following steps: obtaining ultrasound images of different ultrasound positions and ultrasound angles; detecting features of each ultrasound image to obtain an ultrasound feature map containing information of a detected object; converting a gray value of the ultrasound image into a distance from the detected object; constructing a three-dimensional position matrix capable of representing the distance by a position and containing the ultrasound features; detecting features of a diagonal line using the three-dimensional position matrix; detecting features of multiple ultrasound positions and multiple ultrasound angles as values for judging whether the detected diagnosis position is accurate; and fusing the features of the diagonal line when detecting the diagnosis position.

The utility model discloses an in-vitro diagnostic analysis device which comprises an analyzer body, a detection groove is formed in a detection table on the upper side of one end of the analyzer body, a detection and diagnosis hole is formed in the bottom in the detection groove, an upper cover is hinged in a sealing cover on the upper side of the detection groove, a transparent cover body is arranged in the upper cover, and a transmission shaft is rotationally arranged on the inner side of the transparent cover body. A transmission shaft is arranged on one side of the transparent cover body in the upper cover, a stirring blade is arranged at one end of the transmission shaft through a connecting seat, a side wall scraping blade is arranged on the outer side of the stirring blade, one end of the transmission shaft is in transmission connection with a motor, and a flushing mechanism is further arranged on the outer side of the detection and diagnosis hole. When the stirring blades are inserted into the corresponding detection and diagnosis holes through the closed upper cover, the stirring blades are driven by the motor to rotate at a constant speed, so that detection mixed liquid in the detection and diagnosis holes can be stirred, and the diagnosis and analysis precision can be improved.

The utility model discloses high accuracy intelligence eye disease detection diagnosis and treatment appearance, the bottom plate upper end is equipped with the equipment box, the equipment box is slidably connected with the lifting piece, and the lifting piece upper end is connected with the detection body, and the equipment box is equipped with lifting assembly no.

The present application relates to the technical field of pathogen testing, and discloses a respiratory system infection virus sample detection device, which comprises a detection cylinder, a detection card is installed in the detection cylinder, a one-way air inlet blow nozzle is arranged at the port of the detection cylinder, and the blow gas is guided to the air cavity in the detection cylinder; the detection card comprises a gas sampling area, the surface of the gas sampling area is horizontally expanded towards the air outlet end of the blow nozzle, and a gap for contacting the air cavity is reserved in the gas sampling area; a transparent window is arranged outside the detection cylinder, and a display area is arranged in the middle of the detection card. The present application adopts a handheld convenient blow gas detection cylinder, guides the mouth gas containing droplets to be concentrated and blown on the sampling area of the detection card, has a simple structure, efficiently integrates sampling and detection, greatly reduces the infection risk in the use process, does not need medical staff to detect, saves a large amount of manpower and material resources, is especially suitable for rapid screening of a large number of suspected cases and close contacts of confirmed cases, and can effectively relieve the pressure of detection and diagnosis work.

The embodiment of the invention provides a fault detection and diagnosis method, system and device, and the method comprises the steps: generating a fault sample corresponding to a verification task through configuring the verification task corresponding to a to-be-verified fault diagnosis model, and carrying out the processing of the fault sample through the to-be-verified fault diagnosis model, obtaining a diagnosis verification result output by the to-be-verified fault diagnosis model, verifying and evaluating the diagnosis verification result based on a preset verification index, and generating a corresponding verification evaluation result; if the verification evaluation result meets the requirement, determining a failure coverage rate, a system coverage rate and index data of the to-be-diagnosed object; and generating a fault detection diagnosis result of the to-be-diagnosed object by using the failure coverage rate, the system coverage rate and the index data of the to-be-diagnosed object.

The invention provides a diagnosis basis detection method and system and a storage medium, and the method comprises the steps: carrying out the preliminary diagnosis of diagnosis diseases and disease grade information in a result, and determining a target disease history and associated risk factors in a to-be-detected diagnosis basis according to the diagnosis diseases; acquiring a disease parameter value in the history of the target disease, and determining target grade information according to the diagnosis disease, the disease parameter value and the associated risk factor; if the disease grade information is the same as the target grade information, judging that the diagnosis basis to be detected is sufficient for diagnosis of the diagnosed disease; and if the disease grade information is different from the target grade information, judging that the diagnosis basis to be detected is insufficient in diagnosis of the diagnosed disease. According to the embodiment of the invention, by judging whether the disease grade information is the same as the target grade information, whether the diagnosis of the to-be-detected diagnosis basis aiming at the diagnosis disease is sufficient can be automatically detected, and the diagnosis basis detection efficiency is improved.

This invention belongs to the field of medical testing and diagnostic technology, and discloses an AI-based, end-to-end intelligent auxiliary analysis method for electrocardiogram (ECG) testing and diagnosis, comprising: S1, constructing a three-dimensional mapping database, which includes a labeled dataset of samples; S2, positioning of a multimodal acquisition terminal and acquisition of multimodal data; S3, signal analysis and diagnosis through a fusion diagnostic model, including a two-level fusion decision model. In the first-level fusion part, the two-level fusion decision model forms a multimodal fusion feature vector; in the second-level fusion part, it analyzes and obtains diagnostic results and abnormality diagnostic results for ECG signals, and then weightedly fuses them to output the final diagnostic result. This invention can accurately distinguish between electrode displacement and actual pathological abnormalities, reducing the false positive rate, decreasing clinical misdiagnosis, and improving the reliability and efficiency of diagnostic results.

The invention discloses a hydraulic engineering detection system and method for hydraulic engineering, and belongs to the technical field of hydraulic engineering detection. The method comprises the following steps: step 1, carrying out real-time monitoring and data acquisition on key parameters of the water conservancy project; step 2, constructing an engineering state feature vector through a knowledge graph and semantic reasoning, and realizing preliminary identification and risk assessment of an abnormal state; step 3, performing multi-dimensional quantitative analysis on the identified abnormal state to realize accurate diagnosis of engineering diseases; step 4, based on the diagnosis result, automatically generating graded early warning information and matching a corresponding processing scheme; step 5, performing credibility evaluation on the diagnosis result, and realizing real-time dynamic adjustment of the early warning level and the processing suggestion; and step 6, displaying a detection diagnosis result through a visual interface, and automatically generating a standardized detection report according to an industrial standard.

The invention discloses a diagnosis method for tea tree black mold detection, and the method comprises the following steps: S1, obtaining image data of tea tree leaves, and constructing a data set containing high-resolution images of healthy and infected tea tree leaves; s2, analyzing the image data by using a deep learning model to identify the existence and severity of black mold; s3, enhancing the understanding of the model on images and texts by combining a visual question and answer technology and utilizing question and answer pairs corresponding to the image data, so as to improve the recognition accuracy; and S4, realizing real-time detection and diagnosis of the tea tree black mold by using the trained model through a mobile network and an unmanned aerial vehicle platform. Compared with a manual observation method, the method has the advantages that the accuracy of tea tree black mold detection is improved by more than 20%, the accuracy of tea tree black mold detection is improved by more than 5% compared with an existing image recognition method, light weight of the model can be realized, the average reasoning time at a mobile terminal and an unmanned aerial vehicle terminal is 0.2 second per image, and on-site real-time monitoring is facilitated.

The utility model discloses a gluing sheet suitable for detection and diagnosis, which comprises a sheet lower cover structure and a sheet upper cover structure, the sheet upper cover structure is inserted in the middle of the top of the sheet lower cover structure, and the left side of the outer part of the sheet lower cover structure is connected with a first butt joint tenon; a first butt joint mortise is arranged on the surface of the side, away from the first butt joint tenon, of the sheet lower cover structure. According to the gluing sheet suitable for detection and diagnosis, the first butt joint tenons, the first butt joint mortises, the second butt joint tenons and the second butt joint mortises are arranged on the left side, the right side, the front side and the rear side of each sheet lower cover structure correspondingly, so that multiple sets of sheet lower cover structures can be spliced and combined; according to the sheet upper cover structure, the sheet lower cover structure and the sheet lower cover structure are arranged, so that synchronous batch detection of different reagents is facilitated, and the sheet upper cover structure is inserted into structures between the sealing structure and the butt joint pile and between the sealing groove and the butt joint groove, so that structural protection can be provided for the reagents in the sheet lower cover structure, and meanwhile, the scattering problem can be avoided.

The application discloses a rendering abnormality automatic diagnosis system based on UE5 pixel readback and OpenCV, which comprises a pipeline extension layer, a data capture layer and an intelligent analysis layer; wherein the pipeline extension layer constructs a rendering pipeline extension model and collects RenderTarget data; the data capture layer realizes asynchronous reading of the RenderTarget by adopting a double buffering mechanism; the intelligent analysis layer constructs a multi-dimensional abnormality detection model based on OpenCV and analyzes image data to obtain abnormality analysis results. The scheme realizes multi-modal abnormality detection diagnosis through the construction of a three-layer architecture of "rendering pipeline extension-intermediate result capture-intelligent analysis decision", and can cover nine categories of abnormal types such as performance bottleneck, visual defect and rendering logic error. The scheme realizes intelligent diagnosis of rendering defects by inserting a customized Debug rendering Pass, capturing rendering intermediate results in real time and combining computer vision algorithms.

The invention discloses a Tibetan medicine-based urine diagnosis intelligent diagnosis method, a diagnosis system thereof and a diagnosis instrument, which are characterized in that the Tibetan medicine-based urine diagnosis intelligent diagnosis method is characterized in that a Tibetan medicine-based urine diagnosis method is adopted, urine characteristics and disease syndrome classification is realized based on deep learning, and a Tibetan medicine-based RAG knowledge base is constructed based on a large language model; the functions of intelligent question answering, Tibetan traditional Chinese and western medicine disease control and the like are utilized, detection, diagnosis and service are integrated, and the method comprises the steps of data collection, urine character recognition, syndrome type judgment, diagnosis suggestion generation and the like. The system is composed of a management subsystem, an acquisition subsystem, a training subsystem, a diagnosis subsystem, an RAG subsystem and the like. The diagnostic apparatus comprises a detection device composed of a temperature sensor, a camera, an electronic tongue, an electronic nose module and the like. Compared with the prior art, the Tibetan medicine urine diagnosis and intelligent diagnosis integration system has the advantages that automatic statistics and intelligent analysis are carried out by utilizing metadata and expert marks, the system, the device and the method are integrated, and standardized and intelligent support and inheritance and application of Tibetan medicine are facilitated.

A diagnosis method includes: a physical quantity detection step of detecting a physical quantity generated in a diagnosis target by using a physical quantity sensor; a Lissajous figure generation step of generating a three-dimensional Lissajous figure by plotting the physical quantity detected in the physical quantity detection step in a three-dimensional coordinate system including a first axis, a second axis, and a third axis; a vibration plane information acquisition step of acquiring information on a vibration plane of the vibration from the three-dimensional Lissajous figure generated in the Lissajous figure generation step; and a diagnosis step of diagnosing a state of the diagnosis target based on the information on the vibration plane acquired in the vibration plane information acquisition step.

The invention discloses a general verification and evaluation generation method, system and device for fault detection and diagnosis of mechanical and electronic products, and relates to the technical field of health diagnosis of electronic products, and the method comprises the steps: determining a first score representing the design capability of a to-be-diagnosed object according to the failure coverage rate and system coverage rate of the to-be-diagnosed object; determining a second score representing the cost capability of the to-be-diagnosed object according to the calculation performance index and the cost-efficiency index of the to-be-diagnosed object; determining a third score representing the algorithm performance of the to-be-diagnosed object according to the fault detection capability index, the fault isolation capability index and the fault diagnosis capability index of the to-be-diagnosed object; and generating a fault detection diagnosis result of the to-be-diagnosed object according to the first score, the second score and the third score. According to the method, the PHM capability of complex equipment such as machinery and electronic products can be systematically diagnosed and evaluated, the diagnosis and evaluation result is objective, accurate and comprehensive, and the operation process is convenient.

The invention provides an intelligent detector for combined detection of CRP and SAA. The detector comprises a sample processing module, a detection module, an intelligent analysis module and an interactive display module, the sample processing module is used for collecting, separating and conveying a detection sample; the detection module is used for carrying out synchronous detection on CRP and SAA on a detection sample by adopting a fluorescence immunochromatography mode; the intelligent analysis module is used for acquiring the detection data transmitted by the detection module, and analyzing and identifying the detection data to obtain a detection and diagnosis result; the interactive display module is used for displaying a detection and diagnosis result for a user through interactive equipment; according to the invention, synchronous detection and intelligent analysis of CRP and SAA are realized, infection types and risk assessment results can be efficiently output, and the detection accuracy and clinical application value are improved.