152results about How to "Reduce diagnostic costs" patented technology

The invention relates to the fields of analysis and test, in particular to a multi-channel microfluidic chip capable of detecting various subtype swine influenza viruses (SIV) simultaneously. One of the aims of advancing the related diagnosis and treatment technology is to diagnose the SIV quickly and cheaply. The invention provides a diagnosis device, which can fulfill the aims. The key point of the scheme is that: the device, namely the microfluidic chip, comprises pipelines with a parallel structure, wherein the parallel structure comprises three branched pipelines arranged in parallel; three beads-shaped working electrodes are arranged in the three branched pipelines respectively; each beads-shaped working electrode consists of a conductive electrode and a gold colloid sensitive film; the gold colloid sensitive film is attached to the conductive electrode and embeds different subtypes of SIV specific antibodies; the gold colloid sensitive films on the surface layers of the three beads-shaped working electrodes embed three different subtypes of SIV specific antibody substances respectively; and the three different subtypes of SIV specific antibody substances are the subtype H1N1, the subtype H3N2 and the subtype H1N2 SIV specific antibody substances respectively.

The invention discloses a vehicle information remote monitoring and fault diagnosis system. The system comprises an intelligent vehicle-mounted terminal which is installed on a vehicle and is used foracquiring vehicle fault information and real-time state information, a cloud server platform and an intelligent mobile terminal. The system is used for instantly analyzing and processing a vehicle fault, and graphically displaying the various kinds of data of a vehicle on the intelligent mobile terminal. The invention also provides a vehicle remote diagnosis method. When the vehicle has a fault,the vehicle-mounted terminal can automatically transmit a fault code to cloud, a cloud management platform analyzes the fault code and matches a corresponding solution scheme to the user vehicle-mounted terminal, nearby selectable repair manufacturers are pushed to a user via GPS, and the user can check the real-time operation state information of the vehicle through the intelligent mobile terminal APP. Through the intelligent mobile terminal, a driving habit and vehicle fault hidden troubles are checked. A driver can correct a bad driving habit through the mobile terminal and potential safetyhazards of the vehicle are reduced.

The invention discloses a bearing fault diagnosis method based on transfer learning. The method comprises the steps of selection rules of a training data set and a test data set; auxiliary data normalization transferable degree quantification and a threshold selection method; and the algorithm flow of a TrAdaboost algorithm based on weight adjustment used for bearing fault classification. A thinking strategy that auxiliary data in transfer learning assist target data learning is introduced by aiming at problems of lacking of diagnosis generality caused by the conditions of variable working conditions, unavailable direct measurement and new fault types. According to the method, diagnosis precision of conventional machine learning in a small amount of target data can be enhanced, environmental adaptability of bearing fault diagnosis is enhanced, and the method has potential economic value in the field of bearing fault application under variable working condition loads, new faults and indirect measurement.

The invention discloses a non-intrusive fuel cell fault diagnosis method. The method comprises fault diagnosis classifier establishing and fault diagnosis testing. The fault diagnosis classifier establishing comprises the following steps of taking the actual operation data of a fuel cell as an original data set extraction diagnosis variable; preprocessing the diagnosis variable; training preprocessed data through an ELM learning algorithm and screening a clustering result which is the same with an actual fault label as a fault sample set; and through an ELM model, learning the fault sample setand outputting an ELM classification model so as to form a fault diagnosis classifier. The fault diagnosis testing comprises the following steps of detecting the data to be diagnosed of the fuel cell; through the data to be diagnosed, establishing a test sample; and sending the test sample into the ELM classification model for testing and outputting a test result. In the invention, the fault diagnosis of the fuel cell can be performed in a non-intrusive mode, and the timeliness, the reliability and the accuracy of fuel cell fault diagnosis are effectively increased.

The invention relates to a doubly-fed wind power generator stator current diagnosis method for an impeller imbalance fault. The method concretely comprises the steps that doubly-fed generator stator single-phase current is collected, and the fundamental frequency of the stator single-phase current is extracted by utilizing FFT analysis; the fault characteristic component of the stator single-phase current under the impeller imbalance fault is calculated by utilizing the obtained fundamental frequency; an impeller rotation speed signal of a wind generation set is collected, and the characteristic frequency of the impeller imbalance fault of the stator current is calculated; spectral analysis is performed on the obtained fault characteristic component of the stator phase current by utilizing FFT, according to the fault characteristic frequency at this time, the value of amplitude at the frequency is extracted, and under the same wind speed condition, characteristic frequency amplitude values of the wind generation set under normal circumstances are compared to judge the severity of the fault. According to the method, the problem that based on an existing direct fault diagnosis method for the stator current characteristic quantity of a wind power generator, the extracted fault characteristic quantity is not obvious is effectively solved. Accordingly, the method is a fault diagnosis method capable of effectively improving the safety and reliability of blades.

The invention discloses a running state monitoring and failure diagnosis method for a tobacco logistics system. The method comprises the following steps: (1) acquiring the whole running state information of the logistics system in real time on line through a data acquisition system; (2) remotely monitoring the state of common logistics system equipment in real time, and performing failure diagnosis; (3) firstly, determining various combination modes of the failure reasons of each key logistics equipment, and secondly, inputting a diagnosis rule into an SQL (Structured Query Language) database of a failure diagnosis server, wherein the diagnosis rule serves as the source of a failure experience knowledge base; (4) storing failure result information which is obtained by automatic diagnosis through the failure diagnosis server and serves as alarm information into a failure alarm record base, triggering a wireless alarm module, and informing an on-duty equipment maintainer of failure information immediately in a short message mode. According to the method, the failure burst rate of the tobacco logistics system is effectively reduced, the failure maintenance efficiency is improved, and the equipment maintenance cost is reduced.

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.

A medical detecting analyzer for dynamically detecting the parameters of organs to determine the shape and position of lesion region is composed of a casing, a microwave hating element for heating the skin or deep tissue, a microwave guide tube with external sleeve semiconductor pipe for preheating-precooling, internal insulating film and barrier block to form detecting hole, a temp measuring element with external infrared temp probe, a cooling fan, a central chip and a display screen and its controller. Its method is also disclosed.

The invention provides a method for identifying the failure state of the rotor vibration signal of an aircraft engine. The method mainly includes the following steps of: firstly extracting 11 time domains and frequency domains and characteristics of time and frequency domains of the rotor vibration signal; selecting the proper characteristics by clustering; training a classifier by using the clustering result; at last introducing new data into the trained classifier to generate classification result. According to the method, the problem that, when in existing aircraft engine rotor failure state identification, the lots of extracted diagnosis characteristics have many uncorrelated or uncorrelated due to objective and subjective reasons is overcome. The method of classifying rotor vibration signal faults of the aircraft engine by using the combination of the clustering method and the classifier is adopted to provides a frame of the method for identifying the failure state of the rotor vibration signal of the aircraft engine, the key characteristic sensitive to the fault characteristic can be automatically identified, the correlated characteristics insensitive to the fault characteristic can be removed, and the performance of identifying the failure state of the rotor vibration signal of the aircraft engine can be effectively promoted.

The invention relates to a detection kit for diagnosing tuberculosis, comprising a recombinant antigenic protein, wherein the recombinant antigenic protein is the fusion protein obtained by connecting ESAT-6 (early secreting antigen target 6KD), CFP-10 (cultufiltrate protein 10KD), and MPB64 (Mycobacterium bovis 64KD) by connecting peptides according to an arbitrary sequence, wherein the connecting peptides are short peptides which do not influence the immunogenicity of ESAT-6, CFP-10 and MPB64. Preferably, the recombinant antigenic protein in the detection kit for diagnosing tuberculosis is the antigenic protein with an amino acid sequence which is SEQ ID: No.1. When the detection kit in the invention is used for diagnosing tuberculosis, the diagnosis time is short, the diagnosis is fast, the sensitivity is strong, and the specificity is high; and the detection kit has an important significance on early diagnosis of tuberculosis.

The invention provides a chemiluminiscence diagnostic kit for sensitization allergens and a preparation method thereof. The diagnostic kit comprises a microporous plate coated with the sensitization allergens, a horseradish peroxidase-labeled anti-human IgE (immunoglobulin e) antibody, chemiluminiscence substrate solutions A and B, and a washing solution, wherein the sensitization allergens comprise one or more of an insect allergen, a pollen allergen, a fungus allergen and a food allergen. According to the diagnostic kit, the difference of the sensitivities of different proteins in one diagnostic kit is overcome, and the detection sensitivity of each allergen is enhanced to the maximum extent by repeatedly testing and adjusting the coating amount of the allergens, the concentration of the enzyme-labeled antibody and the formulae and the concentrations of the chemiluminiscence substrate solutions. The chemiluminiscence diagnostic kit is higher in detection sensitivity, safe, reliable, simple and convenient to operate and low in cost in comparison with the ELISA (enzyme linked immunosorbent assay), western-blot and RAST (radioallergo-sorbent test) diagnostic kits for the allergens.

The invention discloses a comprehensive airborne task system health management subsystem, and aims to provide a management system capable of monitoring the airborne task system function, the bus network and the hardware module health state in real time. The method is realized through the following scheme: system health management software acquires health state information of each area from a health information acquisition network, completes fusion processing and reporting of diagnosis information, and maintains a self-inspection instruction, queries a fault threshold and distributes a settinginstruction; the health information acquisition network is composed of an Ethernet switch, a CAN bus network management unit, an SRIO bus network management unit, a regional software state managementunit and a regional BIT management unit so as to collect the Ethernet state, the CAN bus network state, the SRIO bus network state, the software fault monitoring data and the BIT data; the health display and control assembly displays task system functions, modules and bus network health states in a graphical mode, and supports a user to start maintenance self-inspection and carry out query and setting of a fault threshold.

A method and device for extracting medically effective information by applying a millimeter-wave band electromagnetic wave to an organism and analyzing transmission, reflection and spontaneous radiation signals. The method and display comprise an acquiring step or means in which a database is so prepared in advance that from the transmission, reflection, and spontaneous electromagnetic wave data measured in a state that an organism is irradiated with an electromagnetic wave having wavelength components the wavelengths of which are 6 to 14 mm and a state that the organism is not irradiated, electromagnetic characteristics at the organism surface and in the organism is categorized and organized by actual condition of the organism constituent element, and the actual condition information on the organism constituent element of the subject is acquired according to the database information from the transmission, reflection, and spontaneous electromagnetic wave data measured in a state that the organism, the subject, is irradiated with a similar electromagnetic wave and a state that the organism is not irradiated; a step of associating the position information on the measurement portion of the subject with three-dimensional meridians and meridian points; and an image displaying step.

The invention discloses a methylated marker IL-2RG in a systemic lupus erythematosus (SLE) whole blood genome and application thereof. The sequence of the marker is shown as SEQ ID NO:1. The methylated marker IL-2RG in the SLE whole blood genome is applied to the preparation of a reagent for diagnosing SLE, in particular to a kit for diagnosing SLE. By detecting the methylation level of the methylated marker IL-2RG, a specific methylation locus with a great meaning and a remarkable difference is counted and taken as a basis for early diagnosis of SLE. By adopting the methylated marker, an accurate, cheap and quick clinical tool for early diagnosis of SLE, the disease activity, the curative effect and the prognostic evaluation is provided.

The invention discloses a method for diagnosing imbalance faults of blades. The method includes steps of (1), recording signals of current components i<q> of a quadrature axis of a generator and rotational speed signals of the generator when a wind generation set is in a running state; (2), extracting feature order components from the current components i<q> of the quadrature axis of the generator by a VKF-OT (Vold-Kalman filter order tracking) process; (3), computing an envelope spectrum of amplitudes of the feature order components; and (4), diagnosing the wind generation set according to a change condition of the envelope spectrum to determine whether the imbalance faults of the blades occur or not. The method for diagnosing the imbalance faults of the blades has the advantages that the imbalance faults of the blades of the wind generation set can be diagnosed in real time by the VKF-OT process; extra sensors or data acquisition equipment are omitted in a fault diagnosing procedure, the method is simple and feasible, and the diagnosing cost is low; non-stationary signals can be effectively processed by the VKF-OT process, so that shortcomings of the traditional signal processing technology can be overcome; and the diagnostic effectiveness, the diagnostic reliability and the diagnostic instantaneity are improved.

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 method and a system for fault feature information extraction and early fault early warning. The method comprises the steps of: acquiring system state data, preprocessing the system state data, extracting feature information, acquiring standardized variables, and establishing a covariance matrix of the standardized variables; reducing dimensionality of the covariance matrix by combining a PCA principal component analysis method, and selecting a principal component with the largest contribution rate; monitoring and acquiring data of the principal component with the largest contribution rate in real time as time sequence data, and acquiring a time sequence model and predicted error data through fitting and modeling; and judging the predicted error data, and sending out an early warning signal. According to the method, the data is subjected to dimensionality reduction by adopting the PCA principal component analysis method, the principal component with high contribution rate is extracted, the predicted error data is obtained on the basis of the time sequence data of the principal component, and the predicted error data is judged to perform timely prediction and diagnosis on a fault, thereby reducing the difficulty of diagnosis and manual inspection cost to a great extent.

The embodiment of the invention provides an air conditioner diagnosing and debugging system and relates to the technical field of air conditioners. The difficulty degree of air conditioner diagnosing and debugging can be reduced. The air conditioner diagnosing and debugging system comprises at least one air conditioner, at least one air conditioner adapter and a detection client; each air conditioner adapter is connected with at least one air conditioner; the air conditioner adapters are used for collecting real-time air conditioner operation data of the air conditioners in the specified states of the air conditioners and sending the real-time air conditioner operation data to the detection client; the detection client diagnoses the air conditioners according to matching of standard air conditioner operation data and the real-time air conditioner operation data, and a corresponding control parameter is obtained; the detection client further can be used for sending the control parameter to the air conditioner adapters; the air conditioner adapters also can be used for sending the control parameter to the air conditioners; and the air conditioners operate in the specified states according to the control parameter. The air conditioner diagnosing and debugging system is applied to the field of air conditioners.

The invention relates to a special multichannel syphilis diagnosis device combined with quasi-one-dimensional specific antigen modified electrodes. The device is a micro-fluidic chip, belonging to the field of analysis test. One of the targets of the relevant diagnosis and treatment technologies is to quickly diagnose syphilis patients with low cost. The invention provides a diagnosis device aiming to achieve the target. The key points of the proposal are that the device, namely the micro-fluidic chip, comprises channels of parallel structure inside, the parallel structure comprises four branch channels mutually connected in parallel, four catenulate working electrodes in total are respectively arranged in the four branch channels, the catenulate working electrode is composed of a conductive electrode and a gold size sensing membrane that attaches onto the conductive electrode and is embedded with the syphilis specific antibody, and the respective gold size sensing membranes on the superficial coats of the four catenulate working electrodes are respectively embedded with four different syphilis specific antibody substances which are respectively syphilis specific antibodies TP0684, TP0453, TP0821 and TP0319.

The embodiment of the invention discloses a remote control method and a remote control system which are used for carrying out remote control on ultrasound diagnostic equipment, thus improving the real-time performance of ultrasonic diagnosis and lowering the diagnosis cost. The method disclosed by the embodiment of the invention comprises the following steps that: a communications connection is established between an ultrasound system and a remote control terminal through a communication network; the remote control terminal acquires the control interface of the ultrasound system; and the remote control terminal operates the ultrasound system by virtue of the control interface. The embodiment of the invention also provides the remote control system. The remote control method and the remotecontrol system which are disclosed by the embodiment of the invention can used for carrying out remote control on the ultrasound diagnostic equipment, thus improving the real-time performance of the ultrasonic diagnosis and lowering the diagnosis cost.

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.

The invention discloses a method, device and system for detecting optical fiber faults. The method for detecting the optical fiber faults includes the steps that after receiving an optical fiber fault detection request transmitted by a network element management system, a PON MAC module transmits starting indication information to an OTDR module, and the switching state of an optical switch module is controlled; after receiving the starting indication information, the OTDR module transmits an OTDR detection signal to the optical switch module; according to control of the PON MAC module, the OTDR detection signal is switched by the optical switch module into corresponding optical fibers, and an OTDR reflected signal is received from the corresponding optical fibers and transmitted to the OTDR module; the OTDR module extracts OTDR sampling data from the OTDR reflected signal, and the OTDR sampling data are transmitted to the network element management system through the PON MAC module. As the OTDR module and the optical switch module are arranged in a PON board card, on the basis that OTDR optical fiber testing performance is guaranteed, the optical fiber diagnosis cost can be reduced, and meanwhile size limitation and power dissipation limitation of an optical module are avoided.

The invention discloses a chromatographic diagnosis method of an oil-immersed type transformer on-load switch leakage. According to the invention, a chromatographic analyzer detects gas components and concentration contents in a transformer body oil tank, each phase of sleeve oil chamber and on-load switch oil conservator insulation oil for at least three times; according to the detection time, a trend graph where time is taken as the transverse coordinate and the gas components and the concentration contents are taken as the horizontal coordinate is drawn; according to the trend graph, the gas components and the concentration contents in each part of insulation oil of each transformer are judged according to a certain rule, and if the judgment condition is met, the oil-immersed type transformer on-load switch leakage is determined. According to the invention, disadvantages in traditional judgment of the on-load switch oil leakage are overcome; the existence of oil leakage faults of the on-load switch is effectively diagnosed; mis-judgment is avoided; diagnosis efficiency is improved; fault power outage and diagnosis cost of the transformer is reduced; normal production orders are ensured.