335results about How to "Shorten diagnostic time" patented technology

An optical and / or optoelectrical transceiver and system are disclosed that enable parallel transmission of data and management signals via an optical fiber without affecting data signal transmissions transmitted on the optical fiber. Furthermore, the present transceiver and system provide a fault diagnosis function for an optical fiber link. The transceiver and system generally comprise an interface, an intersecting transmission management unit, a driver, a management signal driving unit, an optical transmitter, an optical receiver, an amplifier, a management signal recovery unit, a management unit, and optionally, a power supply unit.

The invention relates to a fault diagnosis device and method of a fuel cell system. The fault diagnosis device comprises a communication unit, a diagnosis core unit and a man-machine interaction unit and is characterized in that the communication unit is used for receiving the procedure parameters and working condition information of a main controller as well as the single cell voltage information of a monitor unit and sending diagnosis results and various parameters and data to a field remote control monitoring center and an upper computer; the diagnosis core unit is used for detecting and positioning the faults of the sensor, actuator, controller, monitor unit and galvanic pile of the fuel cell system through the formulated diagnosis strategy; and the main-machine interaction unit is used for displaying, setting, clearing and modifying the diagnosis results and providing maintenance suggestions and measures. By considering the electrochemical reaction mechanism of fuel cells, combining the knowledge and experience of experts and adopting a multisensor information fusion method, the device can be effectively applied to the long-range, short-range, off-line and online fault diagnosis of the fuel cell system, thus the fault diagnosis accuracy and maintainability are improved.

A dynamic layer diagnostic device for smart power grid fault comprises a data collection and monitoring unit, a data processing unit, a data base unit, a communication unit and a man-machine interaction unit. A dynamic layer diagnostic method includes: when a smart power grid breaks down, calculating fault diagnosis starting conditions to conform a diagnosis strategy, wherein the fault diagnosis strategy comprises switch layer diagnosis, feeder layer diagnosis and transformer substation layer diagnosis; starting the switch layer diagnosis when changes of switch motion information are remarkable before and after the fault; starting the transformer substation diagnosis when changes of electricity amount information are remarkable before and after the fault; stopping the diagnosis when a fault element is the only one element during the diagnosis of the switch layer; otherwise, retrieving the switch historical action recording, and starting the transformer substation diagnosis when recording matched with the current switch action exists; and otherwise, starting the feeder layer diagnosis. The dynamic layer diagnostic method performs layering analysis on the fault, fully utilizes various fault information and improves fault diagnosis accuracy according to different characteristics of multisource information after the power grid fault and difficulty layer in obtaining and processing of various information.

Equipment failures are diagnosed using an integrated approach of case-based reasoning (CBR) and statistical reliability analysis. The method outputs a single list of suggested failed components, ranked by an overall probability of failure, and their associated past solutions from the case base. The overall probability of failure is calculated using the combined logic of case based reasoning and statistical reliability analysis. The method is typically used in a real-time decision support system to aid equipment diagnosis by a maintenance technician working in the field.

A method and apparatus for inserting design-for-debug (DFD) circuitries in an integrated circuit to debug or diagnose DFT modules, including scan cores, memory BIST (built-in self-test) cores, logic BIST cores, and functional cores. The invention further comprises using a DFD controller for executing a plurality of DFD commands to debug or diagnosis the DFT modules embedded with the DFD circuitries. When used alone or combined together, these DFD commands will detect or locate physical failures in the DFT modules in the integrated circuit on an evaluation board or system using a low-cost DFT debugger. A computer-aided design (CAD) method is further developed to synthesize the DFD controller and DFD circuitries according to the IEEE 1149.1 Boundary-scan Std. The DFD controller supports, but is not limited to, the following DFD commands: RUN_SCAN, RUN_MBIST, RUN_LBIST, DBG_SCAN, DBG_MBIST, DBG_LBIST, DBG_FUNCTION, SELECT, SHIFT, SHIFT_CHAIN, CAPTURE, RESET, BREAK, RUN, STEP, and STOP.

The invention discloses a long-distance diagnosis and treat method of traditional Chinese medical science, comprising the following steps: an originator logs on a consultation system to send a consultation application and provides diagnosis and treat information, i.e. physicochemical indexes, treatment experiences, and the like, of a patient; consultation specialists are determined and a consultation compere is appointed in on-line response specialists; an analyzing platform is openly qualified and quantified; a question proposed stage, a diagnosis and treat scheme proposed stage and a scheme discussion stage of the long-distance diagnosis and treat method of the traditional Chinese medical science are carried out after equipment is detected to be normal, and a diagnosis report of consultation is finally obtained after the deep discussion of each consultation specialist; and the consultation scheme is fed back to the consultation system in time after being carried out and forms the contribution degree of each consultation specialist who takes part in the consultation process. In the long-distance diagnosis and treat method, the consultation specialists can share medical records and diagnosis data of patients in real time and can be more directly mutually exchanged from the patients, and the selection scientificalness and the accuracy of the diagnose result of the specialists are further enhanced by combining the intelligence of each specialist.

Glioblastoma multiforme (GBM) is the most aggressive type of brain cancer. It is critical to determine the most effective patient-specific treatment quickly. Exemplary embodiments use a data-driven approach to extracting brain tumor information from data obtain from Whole Slide Image that is uploaded through an interface. Exemplary embodiments generate the following information about a glioblastoma tumor from a brain biopsy slide using neural networks: annotated areas of relevant tissues, molecular subtype, and expression status of an important gene and include three steps: the segmentation of tumor features; prediction of molecular subtype; and prediction of gene methylation status from a WSI.

Equipment failures are diagnosed using an integrated approach of case-based reasoning (CBR) and statistical reliability analysis. The method outputs a single list of suggested failed components, ranked by an overall probability of failure, and their associated past solutions from the case base. The overall probability of failure is calculated using the combined logic of case based reasoning and statistical reliability analysis. The method is typically used in a real-time decision support system to aid equipment diagnosis by a maintenance technician working in the field.

The invention relates to a remote traditional Chinese medical diagnosis and treatment system which comprises a consultation module, a specialist selection module, a specialist terminal, a host terminal and an analysis platform. The consultation module comprises a consultation initiation unit, a consultation control unit, a consultation report unit and a consultation evaluation unit, and a clinician can log in the consultation initiation unit to send a consultation application; the specialist selection module is used for selecting consultation specialists and appointing a consultation host according to the type of a disease; the consultation control unit is used for opening the analysis platform, bringing in the consultation specialists and controlling a consultation progress; the consultation report unit is used for summarizing a consultation scheme obtained after a deep discussion and forming a consultation report; and after the consultation scheme is executed, the consultation evaluation unit forms the contribution degrees of each specialist participating in the consultation process. In the remote diagnosis and treatment system, the consultation specialists can share a patient case and diagnosis data in real time, and under the help of the analysis platform, the consultation specialists and a patient can more intuitionally communicate mutually, thus the wisdoms of the specialists are integrated, thereby further improving the scientificity of specialist selection and the accuracy of a diagnosis result.

Pressure detection means detects the pressure of an evaporation purge system that includes a fuel tank and a communicating tube, which connects a canister for adsorbing and retaining fuel vapor to an intake pipe. Shutout means shuts out the evaporation purge system from atmospheric air. A pump is driven for pressurization or depressurization purposes while the shutout means shuts out the evaporation purge system from atmospheric air. The pump is stopped when the pressure detected by the pressure detection means reaches a predetermined level. A leak judgment is formulated in accordance with pump drive time and a pressure change after pump stoppage.

A field effect transistor-based rapid human tumor diagnosis apparatus comprises a field effect transistor biochip, a microfluidic channel sample packaging system and a set of electronic detection system. The semiconductor manufacturing technology is utilized to construct a source electrode, a drain electrode and a semiconductor channel between the source electrode and the drain electrode on a silicon substrate, silane reagent is covalently modified on the channel to serve as connecting molecules, which are connected with the specific antibody protein of a certain tumor marker, a microfluidic channel which is constructed with polydimethylsiloxane is then tightly attached and packaged on the silicon substrate, and finally, the source electrode and the drain electrode are connected with the signal detection system. By assaying the tumor marker in human blood, the tumor diagnosis apparatus can rapidly, accurately and early diagnose whether a patient suffers from a certain type of cancer, and is an integrated, high-flux and portable tumor diagnosis apparatus.

The microwave hemorrhagic stroke detector includes a low power pulsed microwave transmitter with a broad-band antenna for producing a directional beam of microwaves, an index of refraction matching cap placed over the patients head, and an array of broad-band microwave receivers with collection antennae. The system of microwave transmitter and receivers are scanned around, and can also be positioned up and down the axis of the patients head. The microwave hemorrhagic stroke detector is a completely non-invasive device designed to detect and localize blood pooling and clots or to measure blood flow within the head or body. The device is based on low power pulsed microwave technology combined with specialized antennas and tomographic methods. The system can be used for rapid, non-invasive detection of blood pooling such as occurs with hemorrhagic stoke in human or animal patients as well as for the detection of hemorrhage within a patient's body.

The invention provides a construction method and application of a thoracic disease detection model. The construction method comprises the following steps: A, acquiring chest X-ray images of a specified number of thoracic disease patients; B, performing image preprocessing on the X-ray images to obtain pre-processed image data; and C, inputting the pre-processed image data to a convolution neural network model for training to obtain the trained model for thoracic disease detection. The thoracic disease detection model can accurately predict a type and a location of a thoracic disease, the diagnosis time of the doctor is greatly shortened, and the rate of missed diagnosis and misdiagnosis is lowered.

The invention relates to a medical prescription checking method and a device. The medical prescription checking method comprises the steps of detecting whether a doctor prescription system sends a first prescription checking request to a checking platform or not; upon detecting that the doctor prescription system sends the first prescription checking request to the checking platform, recording thetime of detecting the first prescription checking request; detecting whether a first checking result returned by the checking platform is received within a preset time period or not; when the first checking result is received within the preset time period, displaying a checking window, and displaying the first checking result in the checking window; when no first checking result is received within the preset time period, canceling the task of receiving any checking result, generating a skip waiting instruction and sending the skip waiting instruction to the doctor prescription system. Based on the medical prescription checking method, the diagnosis time of doctors can be greatly saved, and the diagnosis efficiency of doctors can be improved. The network processing efficiency can be effectively improved. Correspondingly, the invention further provides a medical prescription checking device.

The invention provides a fever to-be-checked computer aided diagnosis method based on PET / CT images. Full-automatic analysis of the PET / CT bone images is achieved, and a doctor is assisted in diagnosing fever to-be-checked patients. Firstly, lossless interpolation of the PET images is conducted; secondly, hospital beds in the CT images are automatically removed; thirdly, full-automatic bone segmentation of the CT images is conducted; fourthly, bone segmentation is conducted on the whole-body CT images through an optimal active contour model of a CV active contour region; fifthly, after-treatment of the CT segmented images is conducted; sixthly, bone tissue information of the PET images is acquired; seventhly, bone tissue SUVs and bone tissue BSI values are acquired through calculation, wherein the SUVs of bones, marrow and bone cortices are acquired through calculation respectively, and the BSI values of the bones, the marrow and the bone cortices of the patients are acquired through calculation via the SUVs; eighthly, diagnosis is conducted based on the BSI values, wherein the SUVs and the BSI values are compared with SUVs and BSI values in an existing confirmed patient database, and a diagnosis report is made.

The invention discloses a method for processing multi-mode brain nerve image characteristics, and relates to image preprocessing for extracting image characteristics or features of a recognition figure. The method comprises the following steps of: firstly, performing characteristic selection on multi-mode data by adopting a multi-mode nerve image characteristic selection method with sample weightand low rank constraint to obtain a low-dimensional characteristic matrix, calculating a nuclear matrix of each mode to obtain a low-dimensional characteristic matrix, calculating a nuclear matrix ofeach mode, fusing the nuclear matrices of different modes into a nuclear matrix to select more discriminative biomarker characteristics. New Alzheimer disease sample cases are predicted and classifiedby using a multi-core support vector machine. The defects that, in the prior art, a subject can be injured by using biomarker characteristics, an illness brain area of a patient cannot be found by only using one kind of brain image characteristic data or not fully utilizing the multi-mode brain nerve image characteristics, and the characteristics in the used brain image are free of medical explanation are solved.

A storage device can reduce time for diagnosis and allows the diagnosis to be conducted on the entire area of a memory. The storage device includes a temporary memory that temporarily stores for a storage medium, data written to and / or read from a host system by the storage medium; a memory manager that manages writing and / or reading performed on the temporary memory; a first storage memory that complements a difference in processing speed of writing and / or reading between the host system and the temporary memory; and a second storage memory that complements a difference in processing speed of writing and reading between the storage medium and the temporary memory. The memory manager has a comparator, which compares the diagnostic data stored in the first storage memory with the read data stored in the second storage memory, and determines that there is an abnormality if a comparison result is inconsistent.

The invention belongs to the field of a detection reagent, and relates to a detection and identification kit for MTBC (mycobacterium tuberculosis complex) and an identification method of the MTBC. According to the method, fluorescence probes and amplification primers for detecting the MTBC are designed through sequence alignment, mycobacterium and the MTBC specific SNP (single nucleotide polymorphism) loci on an rrs gene are detected based on a real-time fluorescent quantitative PCR (polymerase chain reaction) platform and with an asymmetric PCR amplification technology and a probe melting curve analysis technology, so that mycobacteria are identified, and the MTBC and NTM (nontuberculosis mycobacteria) are further identified. The method has the characteristics of convenience in operation, short detection time and high specificity and sensitivity.

The invention discloses an internet of things based high- and low-voltage switchgear system. The system is characterized by comprising a switchgear master control unit and an intelligent router unit. The intelligent router unit is used for establishing connections of all switchgear master control units of a power supply station and a client and for establishing a virtual local area network; the switchgear master control unit converts power signals periodically received, into power information; the power information is subjected to comprehensive judgement of operation load. The system is available for remote updating and debugging of system files of switchgear and for autonomous trip control; the system is capable of remotely monitoring and controlling the switchgear according to the transmitted power information, thus electrical equipment is more intelligent and equipment monitoring capacity and controllability is enhanced.

N images in a respiratory cycle which are radiographed in year P are input, and binary lung field images are extracted from the respective front chest images. Lung field areas S and lung field heights are then calculated. In forming area and height variation waveforms, regions of the N input images are obtained and plotted. Each image is determined as an image belonging to the inspiration mode or expiration mode. The respective images are sorted and stored. Similar processing is performed for N images in a respiratory cycle which are radiographed in year P+1, and the resultant images are stored. Difference images are obtained from the basic images radiographed in year P+1 and the reference images radiographed in year P for each mode by image analysis, thereby extracting changes over time.

The invention relates to the technical fields of medical image processing, three-dimensional visualization and communication, and discloses a method for processing and displaying image data in a PACS (Picture Archiving and Communication System) by a mobile terminal. The method comprises the following steps: taking an intermediate server as a proxy of the mobile terminal and acquiring an image list from a server of the PACS system; and acquiring the image data from the server of the PACS system by using the acquired image list and using the intermediate server as the proxy through the mobile terminal. According to the method disclosed by the invention, original image data in the PACS system are processed and displayed by the mobile terminal, and thus the effect of the image data in the PACS system can be browsed anytime and anywhere.

The invention provides an intelligent electrical-network fault diagnosis method based on multilevel feedback adjustment. The method comprises the steps that historical switching information and electrical quantity attribute information of different devices in an electrical network when the electrical network has faults are stored in a historical fault information base; electrical quantity information of the devices in the electrical network is obtained when the electrical network has faults; diagnosis at the rough identification level is carried out according to the obtained electrical quantity information of the devices in the electrical network, and suspected fault elements are determined in a minimal breaking zone defining method based on the equivalent network to form a candidate set of the suspected fault elements; diagnosis at the fuzzy decision making level is carried out; diagnosis at the accurate positioning level is carried out; and according to results of three levels of fault diagnosis, intersection elements are obtained from suspected fault element sets E1 and E2 to finally determine a diagnosis result of fault elements. The electrical network with faults is analyzed at different levels according to the different sources of the multi-source fault information and the obtaining and processing difficulty of different type of information, and different types of fault information is fully utilized and information is complementary to improve the accuracy of fault diagnosis.

The invention discloses a magnetic-navigation motion control system for use in capsule endoscopy, which can realize the motion control and position control over a capsule endoscope in the alimentary canal. The system comprises a supporting part for an examination receiver, a magnetic assembly, a magnetic support seat and a servo control unit, wherein the magnetic assembly generates a quasi-static magnetic field by using a permanent magnet and mechanical movement to realize the positioning and orienting of the capsule endoscope with a built-in permanent magnet. The magnetic-navigation motion control system provided by the invention has 5 universal driving shafts and can realize the motion control and position control over the capsule endoscope in the alimentary canal with the external control over the feeding speeds, rotating speeds and relative movement speeds of the parts of a magnetic navigator system.

An anatomical imaging system including a scanner having an opening for receiving a patient, a transport mechanism mounted to the base of the scanner, wherein the transport mechanism comprises a movement mechanism for moving the scanner, relative to the patient, and a radiation-protective curtain pivotally connected to the scanner so as to cover at least one side of the opening in the scanner during scanning.

The invention discloses a local model migration learning-based gear fault recognition method. The method comprises time-frequency domain feature extraction, auxiliary data set selection in migration learning and migration learning on the basis of a local model. The method comprises the following steps of: calculating a similarity between target data and auxiliary data through establishing a Wilcoxon signed rank test and chi-square test combined model on the basis of a given time-frequency domain extraction characteristic, and screening the auxiliary data; and migrating useful common parametersof the screened auxiliary data to the target data by utilizing a local migration model taking an SVM as a core so as to realize fault recognition of a gearbox. According to the method, the diagnosisprecision of machine learning when less target data exists is enhanced, the diagnosis cost is reduced, the environmental suitability and universality of gear fault diagnosis are strengthened, and potential economic value is provided.

A diagnostic control device for a hybrid vehicle is provided for shortening the time required for a failure diagnosis of an evaporation purge system. After introducing the inlet-pipe's negative pressure into the evaporation purge system 51, the evaporation control unit 52 diagnoses failure states concerning the evaporation purge system 51 such as a leak by detecting changes in inner tank pressure over a prescribed time. In order to shorten such failure diagnosis control time, a motor generator 12 is driven to assist the engine when introducing the inlet-pipe's negative pressure into the evaporation purge system 51. With such assist-driving, it becomes possible to reduce engine load, therefore, the throttle valve 67 of the engine 11 can be controlled to be on the closed side, making it possible to create sufficient inlet-pipe's negative pressure. Through this, the pressure in the evaporation purge system 51 can be decreased quickly, which shortens the time for failure diagnosis in the evaporation purge system 51.

The invention relates to a generation method and system for a dynamic diagnosis report. The generation method comprises the steps of obtaining check data, wherein the check data comprises personal information and condition checking information of a patient; generating a main body of the dynamic diagnosis report according to the obtained check data; performing labeling on a medical striograph in the obtained condition checking information; enabling a labeled picture format file to be associated to the main body of the dynamic diagnosis report; and receiving signature information, and performing synthesis on the signature information and the associated main body of the dynamic diagnosis report to obtain the dynamic diagnosis report. The generation system comprises a check data acquisition module, a report main body generation module, a medical striograph labeling module, an image-text associating module and a dynamic diagnosis report generation module. According to the generation method and system disclosed by the invention, the electronic type dynamic diagnosis report is adopted to replace a conventional paper report, so that the electronic type dynamic diagnosis report can be stored and read conveniently; and by enabling the medical image to be associated with examination findings or diagnosis opinions, so that the condition information of the patient can be presented more intuitionally.

The invention discloses a circuit fault diagnosis method based on a random forest algorithm, which comprises the steps that all fault types of a circuit under test, the external output state of each fault type and the corresponding fault location are analyzed; the training for multiple decision-making trees is completed, and the multiple decision-making trees form a random forest model; and the current fault state of the circuit under test is collected, the fault state is inputted into the random forest model, and the random forest model finally outputs the current fault location of the circuit under test. According to the invention, firstly all fault types, the external output state of each fault type and the corresponding fault location of the circuit under test are analyzed, then the training for the random forest model is completed, and the fault location of a circuit can be obtained by only inputting the fault state of the circuit into the random forest model in the process of performing fault diagnosis on the circuit in the future, so that the diagnosis time is saved to the maximum extent, and work efficiency is improved. The circuit fault diagnosis method is used for performing diagnosis on a circuit fault condition.

A system, apparatus, and method for analyzing photon emission data to discriminate between photons emitted by transistors and photons emitted by background sources. The analysis involves processing of integrated circuit computer aided design data to identify transistors within the CAD data. The analysis may further involve the use of Boolean operators to process the CAD data to particularly identify, such as through a channel, the location of the NMOS and PMOS gates, the location of the drain and source, or some combination of the location of the gate and drain or source to particularly identify the pinch-off region.