44 results about "Diagnosis Type" patented technology

A system adds functionality to a power button where use of the power button controls the entry and exit from a diagnostic mode. The system includes an information appliance connected to a diagnostic appliance. Once an information appliance is powered up, the information appliance monitors its power button for a press which indicates a request to enter a diagnostic mode. Absent a press of the power button, the system continues to be under control of the information appliance and never enters a diagnostic mode. However, if a press of the power button is detected, the system enters a diagnostic mode. Once in a diagnostic mode the system provides an exit therefrom by interpreting a power button press as a request to exit. The window of time to make such an exit closes once the diagnostic appliance achieves communication with the information appliance. If the power button is pressed during this window of time, then the system ends its diagnostic mode and control of the system returns to the information appliance. If the power button is pressed after the window of time has closed, then the diagnostic appliance retains control of the information appliance and maintains its ability to execute diagnostic type commands thereon. The illustrative system is particularly useful when incorporated into devices with limited interface connections such as legacy-free information appliances. The system allows for a standard existing button on the information appliance to serve diagnostic purposes, avoiding the need for initializing peripherals requiring substantial execution space.

The invention discloses a GIS partial discharging detection system which comprises a partial discharging ultrasonic subsystem and a partial discharging ultrahigh frequency subsystem. The partial discharging ultrasonic subsystem and the partial discharging ultrahigh frequency subsystem are connected with a computer. Further disclosed is a detection method. The detection method comprises the steps of (1) detecting a detected GIS, uploading the detection results to the computer, (2) allowing the computer to carry out data processing and identification on the results detected through the ultrasonic detection method, giving evidences according to the detection results to assign a function value to an elementary probability of a target, namely the assigned probability, (3) calculating evidence space of each GIS fault, and (4) confirming diagnosis results, namely diagnosis types according to diagnosis decisions. According to the GIS partial discharging detection system and method, the partial discharging faults of the GIS can be accurately found, accuracy for identifying the fault types can be improved, maintenance of the GIS is promoted to be developed from periodic maintenance and accident maintenance to state maintenance and reliability maintenance, and detection accuracy is improved.

The invention relates to a Bayesian network (BN)-based rolling bearing fault diagnosis method. According to a common rolling bearing fault diagnosis method, a mathematical model is required to be established, and an initial diagnosis effect is unsatisfactory; problems of the selection of a wavelet base function are unsolved; and the interpretability of a deduction process is low. The method comprises the following steps of: sampling a vibration signal of a bearing, acquiring a sample, performing N-point rapid Fourier transformation processing to convert a time-domain signal into a frequency-domain signal, calculating a fault characteristic vector, discretizing the fault characteristic vector, establishing a fault diagnosis reasoning BN model, setting a fault sample to be diagnosed, acquiring an observational evidence of the bearing, finishing updating the reliability Theta of a fault diagnosis type node Bearing in the BN model, calculating a fault diagnosis type node, and outputting a result. A complex mathematical modeling process for the vibration signal is avoided, an obtained diagnosis reasoning model has the advantages of a few characteristic parameters, prominent fault characteristics, high interpretability and the like, and an effective way for solving the problems of the rolling bearing fault diagnosis is provided.

The invention provides a method for diagnosing switch faults based on a deep learning model. The method comprises the following steps of normalizing the real-time to-be-detected switch starting current data L; then, inputting the normalized current data into a trained self-organized encoder; enabling the self-organized encoder to compress the switch starting current data L, outputting hidden layer data, and recording the outputted data as data L'; inputting the data L' into a RBF (radial basis function) neural network obtained in step 10, wherein the output of the RBF neural network is the fault diagnosis type reflected by the data L. The method has the advantages that the self-organized encoder is serially connected with the RBF neural network to form a novel deep learning model, so as to intelligently identify the switch starting current data, and reach the purpose of automatically diagnosing the switch faults. The deep learning model has the advantages that the switch fault is automatically diagnosed, and the diagnosis accuracy is high.

The invention discloses an FOA-RBF based high-voltage circuit breaker fault diagnosis method, which comprises the steps of according to the waveform, which varies along with the time, of closing current of a high-voltage circuit breaker, extracting feature variables, and selecting 24 groups of typical data to act as a feature variable sample; performing pretreatment and normalization on the feature variable sample, carrying out binary coding on six groups of diagnosis types, performing iterative optimization on a spreading parameter spread of an RBF network in the global scope, reserving an optimal spread value, and building an FOA-RBF based fault diagnosis model; selecting sample feature variables to act as input of an FOA-RBF network, enabling the six groups of diagnosis types to act as output of the FOA-RBF neural network, and performing high-voltage circuit breaker fault diagnosis. According to the FOA-RBF based high-voltage circuit breaker fault diagnosis method, an artificial intelligence method of FOA-RBF is applied to fault diagnosis for the high-voltage circuit breaker, and quick and effective detection can be performed on a fault.

The invention relates to a transformer fault diagnosis method based on a multi-classification support vector machine, and the method comprises the following steps: S1, selecting the contents of at least two characteristic gases in a power transformer as sample data, and forming a sample set; s2, quantifying sample data in the sample set in the step S1; s3, establishing a multi-classification support vector machine fault diagnosis model, training the multi-classification support vector machine fault diagnosis model by using the sample data obtained in the step S2, and carrying out parameter optimization on the multi-classification support vector machine fault diagnosis model by using a training result; and S4, inputting the sample data of the power transformer to be diagnosed into the trained multi-classification support vector machine fault diagnosis model, and outputting a diagnosis type by the multi-classification support vector machine fault diagnosis model.

The invention provides a tumor image report diagnosis result and pathological result correspondence and evaluation system, which comprises: an image report screening module for screening all tumor image structured reports of image examination items of a patient in a preset time period, including pathological examination sampling parts, on the basis of pathological examination of the patient; a first extraction module which identifies the image examination part and the diagnosis result, and extracts the code of the image examination part and the code of the first diagnosis type; a second extraction module which is used for identifying a sampling part and a pathological result of pathological examination and extracting a code of the sampling part and a code of a second diagnosis type; a diagnosis quality judgment module which judges the conformity of the diagnosis result and outputs a judgment result based on a judgment rule; and a judgment result display module which displays the judgment result in a patient list. The invention further discloses a tumor image report diagnosis result and pathological result correspondence and evaluation method. According to the invention, the diagnosis result and the pathological result can automatically correspond to evaluate the image report, the efficiency is improved, and errors are reduced.

The invention relates a method for guiding to acquire an ultrasonic tangent-plane image by manpower. The method comprises the following steps: dividing a display screen into an image acquisition display region, an information prompting region and a standard image display region; sequentially giving prompts including an ultrasonic diagnosis type, an ultrasonic probe model, a connecting step, a position where an ultrasonic probe is in contact with a body of a patient, matters needing attention and the like in the information prompting region according to an operation sequence of medical staff, so as to guide the medical staff to finish selection, connection, relative operation and the like of the ultrasonic probe; displaying transition tangent-plane images and standard tangent-plane images to prompt the medical staff to preserve the closet transition tangent-plane image as a target tangent-plane image, so as to finish collection of the plurality of target tangent-plane images in a scanning region. Therefore, common medical staff can acquire the ultrasonic tangent-plane images through common training and ultrasonic diagnosis can be more widely applied; ever increasing requirements of patients are met and the time of queuing up to wait for the ultrasonic diagnosis of the patients is shortened; delayed diagnosis of diseases is avoided and the working load of doctors is alleviated.

The application embodiment provides a vehicle diagnosis method, a diagnosis terminal and a diagnosis box; the vehicle diagnosis method comprises the following steps: the diagnosis terminal determinesa diagnosis type to which a to-be-diagnosed vehicle belongs according to a received diagnosis command, and further determines a target diagnosis mode of the needed diagnosis box according to the diagnosis type when the to-be-diagnosed vehicle is diagnosed; the diagnosis terminal obtains the present diagnosis mode of the diagnosis box; if said two diagnosis modes are different, the diagnosis terminal sends a diagnosis mode switching command to the diagnosis box so as to remind the diagnosis box to switch the target diagnosis mode, thus enabling the diagnosis terminal to diagnose the to-be-diagnosed vehicle via the diagnosis box working in the target diagnosis mode. The method integrates the diagnosis box that supports new model diagnosis standards and old model diagnosis standards with diagnosis software, thus automatically selecting a proper diagnosis mode according to the to-be-diagnosed vehicle model, preventing frequently switching of the diagnosis modes and diagnosis software of the diagnosis box, and improving the diagnosis efficiency.

The invention relates to a real-time valve fault diagnosis system and method based on time sequence analysis, and belongs to the technical field of valve fault detection and diagnosis. The method concretely comprises that a vibration accelerometer and a sound pressure sensor monitor a valve in real time; a signal collection chip collects monitored vibration acceleration and sound pressure signalsto a diagnosis processor; five-point three-times smooth denoising is carried out on the data; diagnosis data training sets of different fault diagnosis types are generated; a fault diagnosis sequential model is established; a forward algorithm is used to calculate the likelihood probabilities of different HMM models successively, and a fault diagnosis result is obtained; and a Bluetooth model transmits the fault diagnosis result to an industrial display screen for display. Fault of the valve is diagnosed by time sequence analysis, fault information can be identified and the corresponding faulttype can be obtained at initial stage of the fault, the limit that fault can only be observed in single time is changed, the false detecting rate of faults is reduced, and the using performance of the valve is substantially improved.

The invention belongs to the field of tumor information processing, and provides a whole-course supervision system and method for soft tissue tumor informatization pathology auxiliary diagnosis. The system comprises: a clinical data management platform in which clinical data of soft tissue tumors and expression profiles or/and characteristic spectra of different types of soft tissue tumors at different levels are pre-stored; a pathological diagnosis data platform which is used for receiving clinical data, pathological histological images, immunohistochemical results and molecular genetics results of patients to form expression profiles or/and characteristic spectra of different levels, comparing the expression profiles or/and characteristic spectra with the expression profiles or/and characteristic spectra of corresponding levels in the clinical data management platform, determining the same tumor type determined at different levels as a final pathological diagnosis type, and generating a standardized diagnosis report; and a prognosis data information platform which is used for evaluating prognosis risk factors and feeding back the prognosis risk factors to the pathological diagnosis data platform, establishing a clinical prediction model, evaluating the survival rate, regularly prompting follow-up visit patient time and content, and recording follow-up visit information.

The invention discloses an oil well working condition intelligent diagnosis and analysis method and device based on an SVM model. The invention belongs to the technical field of oil field oil extraction processes, and provides an SVM model-based oil well working condition intelligent diagnosis and analysis method, which comprises the steps of 1, obtaining multiple groups of normal indicator diagrams of an oil well, extracting HOG features of the multiple groups of normal indicator diagrams, and gathering the HOG features of the normal indicator diagrams into a normal HOG feature set; under thecondition that the working conditions of the oil well are complicated and changeable caused by different oil reservoirs and different well bore structures and physical property differences, a set ofuniversal high-accuracy indicator diagram identification method is provided; the problem that matrix features of a matrix feature recognition method do not describe subtle changes of an indicator diagram sufficiently is solved, slight sand production, upward collision and downward hanging can be recognized accurately, the problem that features useful for diagnosis are removed in the actual application process of a differential curve method is solved, the number of diagnosis types is large, and quantitative evaluation can be achieved. Compared with a PSO-RBF neural network algorithm, the methodis more accurate in recognition under complex working conditions.

The invention discloses a semiconductor variable-temperature application device which comprises an application sheet, a medium circulating pipeline, a temperature sensor, a temperature control device, a power source and a temperature control panel. The temperature sensor and the medium circulating pipeline are arranged on the application sheet, and the temperature control device comprises a cooling fan, cooling fins, a semiconductor cooling and heating chip, a medium container and a heat-insulation pad which are sequentially overlaid on one another. The semiconductor variable-temperature application device has the advantages that the shortcoming of clinical separation of 'physiotherapy' and 'drug treatment' can be overcome, and a synergistic interaction effect of physiotherapy and drug treatment can be effectively realized; the temperature of the application sheet can be regulated by the aid of the semiconductor variable-temperature chip according to different diagnosis types of initial stages of diseases and symptom variation caused in disease treatment procedures, so that effects of 'cooling when feeling hot and heating when feeling cold' can be realized.

The invention discloses a bearing fault diagnosis method and system based on Transform and data enhancement. The method comprises the following steps: acquiring data in a bearing operation process; performing data enhancement processing on the acquired data, and dividing the enhanced data into a training data set X and a verification data set Y; constructing a feature extraction network based on a Transform; establishing a network training and verification framework, selecting data of the training data set X and the verification data set Y in batches, and sending the data into the established feature extraction network to obtain a feature extraction network output result; and analyzing an output result of the feature extraction network, obtaining a fault diagnosis type of the bearing, and completing bearing fault diagnosis. According to the method, the network performance is generalized by using a data resampling enhancement method, and meanwhile, the Transform is used as a feature extractor, so that the fault diagnosis verification accuracy of the method reaches 95%.

The invention provides a system for realizing diagnosis logic based on the design of a structured report subtemplate, which comprises a feature definition module for configuring a CDE set corresponding to feature description of each diagnosis type, the CDE set comprising CDE of a part/tissue of a disease, CDE of an imaging representation feature and CDE of a clinical representation feature, wherein each CDE is composed of at least one sub CDE; a diagnosis type sequencing module, wherein when a doctor fills in the CDE set of the diagnosis type corresponding to the core focus, the diagnosis typesequencing module performs priority sequencing on the diagnosis type associated with the CDE set according to a preset rule; a CDE logic recommendation module which is used for automatically loadingthe next sub-CDE for the doctor to fill every time the doctor completes the sub-CDE under one sorted diagnosis type until the last CDE set is filled up; and a structured report generation module whichoutputs a diagnosis conclusion. The invention also discloses a method for realizing diagnosis logic based on the design of the structured report subtemplate. According to the invention, the difficulty of doctor image diagnosis can be reduced and the working efficiency of doctors is improved.

The invention discloses a diagnosis type crankcase ventilation pipe. The diagnosis type crankcase ventilation pipe comprises a connector, wherein the connector comprises a female connector and a maleconnector, the female connector is connected with the male connector in a clamped mode, an outer connector is arranged outside a connecting position of the female connector and the male connector, anda diagnosis circuit is arranged between the female connector and the male connector and is mutually extruded and communicated when the female connector and the male connector are connected. Accordingto the diagnosis type crankcase ventilation pipe disclosed by the invention, the female connector and the male connector are connected in a clamped mode, meanwhile, the outer connector is used for reinforcing connection, and reliable connection of the connectors is guaranteed; and through arrangement of the diagnosis circuit, the real-time vehicle-mounted detection is realized, when the connectoris loosened, the diagnosis circuit is disconnected, the control unit cannot receive a signal, and an alarm is given.

The quick detection method of pathogenic microbe diagnosis type gene chip includes the following steps: preparing slide; preparing probe of length from several hundred to several thousand base and concentration of 0.25-0.5 microgram/microliter via PCR proliferation of genes and specific segments in pathogen genome; preparing chip via sample application with gene chip sample applying instrument; printing and processing; processing sample via incorporating marker Cy5-dUTP in PCR proliferation and introducing restrictive enzyme incision to obtain segment of 200-600 bps length; hybridizing in 2X hybridizing liquid comprising 60 % formamide, 12XSSC and 0.24 % SDS; cleaning after hybridization; and scanning detection. The present invention has the advantages of high marking efficiency, stable hybridizing detection result, greatly shortened hybridization time, etc. and is especially suitable for the diagnosis of infectious diseases clinically.

The invention discloses a medical record level-to-level management system. The system comprises a data storage module, a data scheduling server and a user operation module, according to the system, the architecture of a hospital is divided into four architectures, namely, regional branch hospitals, departments, consulting rooms and definite diagnosis types, for medical record management by utilizing the concept of level-to-level management. And the permission system is designed to divide the permission of each user who logs in the system to check or operate the medical record, so as to ensure the privacy protection of the medical record information. The medical record management module under each hierarchical framework has the functions of medical record retrieval, medical record listing, medical record input, medical record details, batch medical record import, batch medical record export and the like. The problem that the medical record classification structure is not clear in the medical record management and the problem that the medical record information privacy protection is weak due to the fact that the user permission division is not clear are solved, and meanwhile the medical record maintenance efficiency of medical workers can be effectively improved by perfecting the function design of the user operation module.

The invention provides a financial health diagnosis system, and relates to the field of financial systems. A financial health diagnosis system comprises a range selection module, a category diagnosismodule, an index diagnosis module, a condition diagnosis module and an opinion diagnosis module; the range selection module is used for selecting a diagnosis range of financial data, and the categorydiagnosis module is connected with the range selection module. The index diagnosis module is connected with the category diagnosis module to select a diagnosis type and a diagnosis mode of the financial data, and the index diagnosis module is connected with the category diagnosis module to select financial indexes of the financial data according to the diagnosis type and the diagnosis mode. Financial problems can be found as soon as possible, and financial health risks can be prevented conveniently.