103results about How to "Simplify the diagnostic process" patented technology

Disclosed is a system, method, and program for making data available to a first application program. A determination is made of an environment in which the first application program is called. Data is accessed in a first format if the determined environment is a first environment. Otherwise, if the determined environment is a second environment, then a second application program is called. The second application program performs accessing data in a second format and storing the accessed data in a storage location. The accessed data in the storage location is accessible to the first application program.

A fault diagnosis method of a vehicle lithium battery based on a multi-class support vector machine algorithm belongs to the field of vehicle lithium battery fault diagnosis. In order to solve the problem that the existing vehicle lithium battery fault diagnosis technology requires high amount of training data, which leads to the difficulty of realizing real-time on-line fault detection, the method of the invention comprises the following steps of: grouping battery samples into experiments, and sorting the collected data to form a training set and a test set; specifying battery failure criteria; using cross-validation and network search methods to optimize the parameters; constructing a kernel function support vector machine; constructing as biased binary tree five-class support vector machine to get the fault diagnosis model of vehicle lithium battery which can identify different states of lithium battery. The method can quickly and accurately complete the fault diagnosis of a lithiumbattery for a vehicle.

The invention provides a vehicle diagnosis method, a device and equipment. The method comprises the steps of fault symptom information of a vehicle, determining a target fault problem according to thefault symptom information of the vehicle, and determining a solution corresponding to the target fault problem. According to the method, the vehicle is not required to be detected completely; an acquisition scope of fault codes and data flows is reduced; the diagnosis efficiency is high; the vehicle can be directly diagnosed according to the fault symptom information; a diagnosis process is simplified; a diagnosis result is more reliable and complete; and the method is wider in applicability.

The invention discloses a diagnostic method for carbon canister flow. The diagnostic method comprises the following steps of: when a vehicle enters into a slide fuel-cut operating mode, adjusting and controlling an electronic signal for an opening of a carbon canister control valve by an engine managing system so as to change the opening of the carbon canister control valve, and synchronously detecting if the change speed of the pressure in an induction manifold changes following the change of the opening; if yes, confirming that the carbon canister flow is normal; and if not, confirming that the carbon canister flow is in fault. According to the diagnostic method for the carbon canister flow, the tightly blocking or pipeline blocking fault of the carbon canister control valve is effectively detected. The diagnostic method has the advantages of simple diagnostic process and lower cost.

The invention relates to a method and an arrangement for monitoring the operational status of a cyclically operated valve (5, 19), which valve is operated to allow a fluid or gaseous medium to flow from a first conduit (1, 18) to a second conduit (3, 20) due to a pressure difference between said conduits, whereby the valve (5, 19) operated using predetermined duty cycles. The method involves measuring pressure oscillations caused by the valve (5, 19) and generating an output signal, performing a frequency analysis on the signal to determine an amplitude for the signal at an oscillation frequency, comparing the amplitude of the oscillations to an expected amplitude for the oscillation frequency, and generating an error signal is if the difference between the calculated and the expected amplitudes exceeds a predetermined limit.

An image generation unit generates image data of a tomographic image based on an electric signal received from a send/receive unit through a control unit. An ROI setting unit sets an ROI to the generated tomographic image. A characteristic value extraction unit extracts a characteristic value (such as volume of left ventricular of a heart) to the set ROI. A synchronization generation unit generates a synchronization signal based on the extracted characteristic value. A synchronization information addition unit adds information that represents the generated synchronization signal to image data and stores the image data in an image data storage unit. A data reading unit reads out the image data to which the information that represents the synchronization signal is added from the image data storage unit. An image display unit displays a tomographic image of the read-out image data.

The invention discloses a turbo generator set vibration fault diagnosis method based on forward reasoning. After a diagnosed turbo generator set starts, a parameter detection device is employed to carry out real-time detection on related work parameters in a start and operation process of the diagnosed turbo generator set and synchronously sends the detection information to a vibration fault diagnosis device for automatic vibration fault diagnosis, vibration faults of the diagnosed turbo generator set are diagnosed level by level by the vibration fault diagnosis device according to the detection result transmitted by the parameter detection device in combination with the active power value of the diagnosed turbo generator set, and the fault diagnosis process comprises steps of 1, shaft vibration swinging value diagnosis; 2, start process vibration fault diagnosis; 3, zero load operation vibration fault diagnosis; and 4, loaded operation vibration fault diagnosis. The method is advantaged in that the steps are simple, and the method is reasonable in design, is convenient to realize, has good use effects, can conveniently and rapidly accomplish the online steam turbine vibration fault diagnosis process and can further realize accurate and reliable diagnosis results.

The invention belongs to the field of biotechnology, relates to a circRNA marker for depression diagnosis and treatment effect evaluation and a kit and provides a circRNA marker for depression diagnosis. The circRNA marker comprises hsa_circRNA_002143, hsa_circRNA_103636, hsa_circRNA_100679 and hsa_circRNA_104953. The primer sequences of the four kinds of circRNA are shown in SEQ ID NO.1-8. Probes of the four kinds of circRNA are provided. The sequences of the probes are shown in SEQ ID NO.9-12. The invention further provides a circRNA marker for treatment effect evaluation of anti-depression medicine. The circRNA marker has the advantages that the depression biological marker and the circRNA biological marker for evaluating the treatment effect of antipsychotics are provided for the first time, it is clinically proved that the marker has high specificity and sensitive value and has the high diagnosis reference value, and the circRNA will bring revolutionary change of depression diagnosis and treatment by being used as the depression specificity biological marker.

The invention discloses an analytic method for a cloud server diagnosis based on cell images. The previous processing steps comprises: step 1, sampling; step 2, filmmaking; step 3, dyeing; and step 4, scanning. The cloud server further comprises the following modules: module 1, which is a scanning module; a module 2, which is a file uploading module; a module 3, which is an automatic analysis and diagnosis module; module 4, which is a quality control module; module 5, which is a doctor diagnosis re-checking module; module 6, which is a result query module; and module 7, which is a central dispatch module, wherein the central dispatch module can be used for dispatching and managing the work of the modules 1 to 6. According to the analytic method, the cloud server is adopted to collect the data information files uploaded from various regions, automatic analysis is conducted by the cloud server firstly, then judgment is conducted by quality control staff and a doctor, the diagnostic process is simplified, and the diagnostic accuracy is improved; the image analyzing procedure is added, the cell images can be picked out from original sample image information, the cell parameters are calculated, and can be used for reference for the doctor, and the work efficiency of the doctor is improved.

The invention aims at providing a gas turbine adaptive gas circuit component performance diagnostic method based on the combination of a thermal model and particle swarm optimization. The method comprises the steps that the gas turbine nonlinear thermal model is established, gas circuit health indexes of a gas compressor and a turbine are redefined with similarity reduced parameters, gar circuit measurement parameters in a certain time frame in the stable running process of a current object gas turbine are collected and subjected to noise reduction processing and then serve as measurement parameters of a gas circuit to be subjected to offline diagnosis, and gas circuit health indexes of current components are obtained through iteration optimizing calculation of the particle swarm optimization and used for evaluating the practical performance health condition of the object gas turbine. By means of the method, the problem that the diagnostic precision of a traditional gas turbine gas circuit component performance diagnostic method is likely to be affected by changes of environment conditions and operation conditions is solved, the local optimization feature of the traditional diagnostic algorithm is changed, the accuracy of a diagnostic result is improved, the diagnostic process is simplified, and the method can be effectively applied to performance diagnostic situations with measurement noise and for complex gas turbine units.

The invention discloses a train running gear fault diagnosis method and a train running gear fault diagnosis device. The method includes acquiring a train speed; adjusting shooting frequency of a camera shooting component to enable the shooting frequency to be matched with the train speed when the train speed exceeding a preset range is judged, and acquiring a train running gear image shot by the camera shooting component according to the adjusted shooting frequency; searching a standard template image corresponding to the train running gear image from a preset database, comparing the train running gear image with a standard template according to a first preset algorithm, marking different positions on the train running gear image when a comparison result indicates difference between the two, and confirming that a train has faults; displaying the train running gear image marked with the different positions. By the train running gear fault diagnosis method, quick and accurate train running gear fault diagnosis is achieved, and a great quantity of manpower and material resources are saved.

A Candidatus Liberibacter spp. online rapid detection system based on deep learning includes a mobile phone client and a server end; the server end includes a data transmission module, a leaf and fruit detection module, a Candidatus Liberibacter spp. diagnosis module, and a sample database; a model of the leaf and fruit detection module is trained by using the data with instance annotations in a sample database to obtain the optimal model; a model of the Candidatus Liberibacter spp. diagnosis module is trained by using the data with diagnostic annotations in the sample database to obtain the optimal model; the leaf and fruit detection module transmits the output and detected single leaf and single fruit images to the Candidatus Liberibacter spp. diagnosis module. A Candidatus Liberibacterspp. online rapid detection method based on deep learning adopts the Candidatus Liberibacter spp. online rapid detection system based on deep learning. The invention belongs to the technical field ofintelligent identification of Candidatus Liberibacter spp., and has the advantages of rapid, efficient and reliable detection.

The invention discloses a vehicle diagnosis method. The method comprises that a vehicle diagnosis device obtains a vehicle identification code of a vehicle to be diagnosed, then, a query request with vehicle identification code information is sent to a vehicle diagnosis server, and the query request is used to indicate the vehicle diagnosis server to inquire and obtain a diagnosis project corresponding to the vehicle identification code; the vehicle diagnosis device receives response information from the vehicle diagnosis server; the response information responds to the query request; and according to the diagnosis project included in the response information, the vehicle diagnosis device diagnoses the vehicle to be diagnosed correspondingly. The invention also provides the vehicle diagnosis device. According to embodiments of the invention, a vehicle diagnosis process of the vehicle can be simplified, operation is simple, and time and labor are saved.

A method and arrangement are disclosed for detecting a working condition of a mechanical brake of vertical transport equipment, the vertical transport equipment including a frequency converter, an electrical motor and a mechanical brake. Movement of the vertical transport equipment can be controlled using a frequency converter configured to feed electrical power to the motor, the mechanical brake being configured to mechanically hold a car or load of the vertical transport equipment. Data relating to deceleration of the car or load is used as reference data. The mechanical brake is controlled into a closed position for decelerating movement of the car or load. Test data, relating to deceleration of the car or load is measured from information or from a control system of the frequency converter, and compared with reference data.

The invention relates to a deep learning-based Candidatus Liberibacter spp detection method, device and system. The method comprises the steps: acquiring image data of citrus leaves to be identified;Inputting the image data into a neural network model of Candidatus Liberibacter spp detection of a mobile terminal; And determining a detection result corresponding to the image data. The detection method is simple and convenient to operate, lossless, low in cost and popular with citrus producers; Moreover, the diagnosis process is simplified, the diagnosis cost is reduced, fruit farmers can be helped to detect and discover diseases as soon as possible, rapid, real-time, accurate and non-destructive diagnosis on citrus fruit trees in orchards is realized, reference can be provided for fertilization and production of the fruit farmers, great help is provided for the fruit tree yield, and a positive role is played in promoting accurate agriculture and agricultural informatization.

A scan chain latch circuit, a method of operating a latch circuit in a scan chain, and a computer-readable medium having stored thereon a data structure defining a scan chain latch circuit for instantiation on a semiconductor die are disclosed. In an embodiment, the scan chain latch circuit comprises a first latch for holding one data value, a second latch for holding another data value, and a multiplexor. The one data value is applied to a first data input of the multiplexor and the another data value is applied to a second data input of the multiplexor. An alternating clock signal is applied to a select input of the multiplexor to control the output of the multiplexor, wherein the output of the multiplexor toggles between the two data values held in the two latches at a defined frequency.

The present application concerns a device for measurement and analysis of the middle ear and ear channel colour for the diagnosis of ear infections. The device is composed of a otoscope (1), including two optical fibers (2a and 2b): one for ear illumination and another returning the reflected light. The electronic unit (3) can change linearly the power of emitted light, as well as, its colour. The received light is also independently measured, enabling the determination of changes on colour and texture associated with the ear inflammations. Command buttons in the otoscope handler (4) enable the user to save the values of the three colour components. The combined value of the components is shown in the digital display (5) of the electronic unit, as well as, by a set of LEDs (6) green, yellow and red that gives a diagnosis in a simple and immediate way. The otoscope allows, simultaneously, directly ear view through a magnifying glass (7) applied in the head of the otoscope, with a standard white light. This device is also useful in food industry.

The invention provides a rationality fault diagnosis and processing system and method for an oil temperature sensor. When the oil temperature electrical fault diagnosis does not report a fault, an oiltemperature rationality diagnosis module performs rationality diagnosis on an oil temperature signal acquired by the oil temperature sensor based on the oil temperature change characteristic; when the oil temperature electrical fault diagnosis reports a fault or the diagnosed oil temperature signal is irrational, an oil temperature replacement module replaces the irrational oil temperature signalwith a set oil temperature substitute value; and when the oil temperature signal is rational, an oil temperature filtering module filters the oil temperature signal acquired by the oil temperature sensor and the oil temperature signal before the rational fault or electrical fault of the oil temperature sensor is acknowledged, to replace the oil temperature signal before filtering with the filtered oil temperature signal. Based on the system, a rationality fault of the oil temperature signal can be determined, the diagnosis process is simple and effective, and the cost is reduced. Corresponding measures are taken for different diagnosis results to improve the shifting quality of a vehicle.

The present invention provides a method for determining the bandwidths of optical fibers, wherein the method provides the coupling of light with a first optical power and a first modulation frequency into an optical fiber, as well as measuring a first signal level as a function of the optical power of the light of the first modulation frequency, coupling light with the second optical power and a second modulation frequency into the optical fiber, measuring a second signal level as a function of the optical power of the light of the second modulation frequency, and determining the bandwidths of the optical fibers as a function of the first and second coupled optical [power and/or] the measured first and second signal levels while using a predetermined specification that describes the frequency-dependent attenuation response of the optical fiber, wherein the first and the second modulation frequencies have essentially the same value.

A diagnostic module for vehicle diagnosis includes: a communication unit that is embodied for data transfer with a control unit of a motor vehicle; a diagnostic unit that is embodied to perform a diagnosis of the motor vehicle on the basis of the diagnostic data transferred by the communication unit; and a transmitting unit that is embodied to transfer diagnostic data from the diagnostic module to a server. The transmitting unit is embodied to transfer the diagnostic data from the diagnostic module to the server via a mobile radio network and/or the internet.

Provided is an intervention type in-vivo real-time tumor imaging method and system. The imaging method comprises the steps that the polarization directions of terahertz and infrared source emergent light waves are adjusted, the light waves are conducted to the tissue to be detected through an array optical-fiber bundle, signals reflected by the tissue are converted into vertically polarized waves and then enter a detector for imaging in an incidence mode. The imaging system comprises a terahertz and infrared source, a terahertz detector, a reshaping unit, a polarization unit, a polarization conversion unit and an intervention unit. The system works in a terahertz and infrared frequency band, can perform tumor diagnosis in the human body in real time, has more advantages compared with X-ray, CT examination and other technologies, is high in spatial resolution, and has more advantages than a pathological biopsy technology in rapid, accurate and noninvasive characteristics. The intervention type in-vivo real-time tumor imaging method is safer, more accurate, quicker and more convenient and has the good application prospect in tumor diagnosis.

A data acquisition system and method includes monitoring a cooling system having a refrigerant compressor, evaporator, and condenser, and employs a number of sensors to monitor various operating parameters of the system. A database stores predefined operating parameters for a plurality of cooling systems. The operating parameters are provided to a computer, which compares the provided operating parameters of the monitored cooling system with the predefined operating parameters to provide diagnostic results for the monitored cooling system.

A method of generating an antibody comprising the steps of: immunizing a tissue containing cells for immunization in vitro in a culture liquid containing an antigen and a stimulating substance, selecting the immunized cells, and obtaining antibodies from the above selected immunized cells. According to this method of generating an antibody, antibodies can be prepared in a short period of time in large quantities, thereby contributing to the increased use of immunological testing.

The invention relates to the technical field of automobile diagnosis, and particularly relates to an automobile diagnosis system and method based on a universal platform. The invention provides the automobile diagnosis system based on the universal platform. The system comprises a diagnosis instrument and a cloud server. The cloud server is connected with the diagnosis instrument and sends automobile information to the diagnosis instrument according to a request of the diagnosis instrument; and the diagnosis instrument is connected with the to-be-operated automobile through an automobile communication interface, obtains the state and fault information of the to-be-operated automobile, carries out automobile fault diagnosis and displays a result. The automobile diagnosis system and method based on the universal platform are suitable for various automobile types, the diagnosis and updating process of an existing diagnosis instrument is simplified, a user can complete diagnosis or software refreshing of various automobile types without replacing automobile diagnosis equipment, automobile information is managed through the cloud server, and convenience is provided for the user.