1678 results about "Diagnostic equipment" patented technology

The invention discloses an air purification system for a clean workshop. The air purification system comprises a self-adaptive control unit, an air quality monitoring module, an air flow control assembly, an environmental parameter adjusting assembly, a self-optimization filtering assembly, a human-computer interaction interface and predictive maintenance system, an energy efficiency optimization module and a remote diagnosis and early warning system. On the basis of intelligent technologies such as machine learning, reinforcement learning and a data fusion algorithm, real-time monitoring, dynamic optimization and energy efficiency management of the air quality of the clean workshop are achieved. Based on real-time data and historical data, an algorithm is used for carrying out self-adaptive optimization on the air purification system, and manual intervention is reduced. And the running state of the system is dynamically adjusted through the energy efficiency optimization module, so that the energy consumption is reduced while the cleanliness is ensured. The system can diagnose equipment faults in advance, reduce downtime and prolong the service life of equipment. And due to a man-machine interaction interface and a remote monitoring function, an operator can know the state of the system at any time and carry out regulation and control.

A handheld medical diagnostic device integrates at least seven sensor modules, including a high-magnification camera, otoscope camera, stethoscope, infrared thermometer, EKG, pulse oximeter, body composition monitor, glucometer, and / or hematology analyzer. The device features a system-on-chip (SoC) processor for intelligent data management, edge computing, and cloud-based AI processing, while applying privacy-preserving techniques. A wireless transceiver enables data transmission and reception between the sensors, edge compute nodes, and cloud platforms. The ergonomically designed housing includes a display with a force-sensitive layer for user input and navigation. The high-magnification camera module offers 300× magnification for visualizing blood cells and skin, with an annular LED array, encryption engine, and physically unclonable function (PUF) circuit. The otoscope camera module features a narrow profile for ear, nose, and throat imaging, with an annular LED array.

The invention discloses a multi-source modal data fusion-oriented charging pile fault diagnosis method and system. The method comprises the following steps of: acquiring message stream data, audio data and infrared sensing data associated with a charging equipment fault through a sensor system; and based on the characteristics of each modal data, fault characterization and identification are carried out by adopting a random forest, a convolutional neural network and a YOLO-v8 target detection model. According to the marked fault data, a mapping relation among multi-source data is established, and a Dempster-Shafer multi-source fusion theory is utilized to aggregate a multi-modal fault judgment result, so that the equipment fault is accurately diagnosed. According to the method, the accuracy of fault diagnosis and diversified presentation of fault types are effectively improved, the repair rate is reduced, and the method has a good engineering application prospect.

Medical or laboratory diagnostic equipment and facilities. 2.1) Perspective view; 2.2) Front view; 2.3) Left side view; 2.4) Right side view.

The invention relates to the technical field of automobile data updating, in particular to a data updating method of automobile diagnosis equipment and the automobile diagnosis equipment. The method comprises the following steps: acquiring a historical running log of a vehicle; vehicle owner driving behavior multi-point sampling is carried out on the vehicle historical operation log, and different scene behavior characteristic evolution is carried out, so that different scene driving behavior models of a vehicle owner are obtained; extracting vehicle time sequence state parameters based on the vehicle historical operation log; performing multi-scene operation simulation on the vehicle time sequence state parameters according to different scene driving behavior models of the vehicle owner, and generating vehicle state operation simulation data of each scene; and carrying out future time period vehicle state rolling prediction and fault time window probability calculation on the vehicle state operation simulation data of each scene to obtain a vehicle abnormal fault part positioning point and a fault time window probability curve. According to the invention, the data updating efficiency and group accuracy of the automobile diagnosis equipment are realized.

The invention discloses an OBD tamper-proof two-way verification method, which comprises the steps of obtaining OBD equipment data and vehicle sensor data, registering to a cloud end based on the OBD equipment data, obtaining registration data, obtaining key data and non-key data according to the vehicle sensor data, symmetrically encrypting the key data by using a session key in the registration data, and verifying the key data and the non-key data. Performing approximate homomorphic encryption on the non-key data, obtaining a double-entropy source dynamic salt value according to the time entropy of the ciphertext and the OBD equipment operation entropy, reversely reconstructing the dynamic salt value by the cloud according to the timestamp and the registration data, verifying the ciphertext structure by using the dynamic salt value and generating a random challenge containing a salt value check code, and sending the random challenge to the cloud; the equipment verification result and the challenge value are signed and then transmitted back, the OBD equipment carries out reverse verification on the salt value according to the signature and the equipment verification result, and the cloud generates an authority token based on the reverse verification result. According to the method, the data authenticity and integrity of the diagnostic equipment are guaranteed through packet encryption, dynamic salt value generation and bidirectional identity verification of transmission data.

Aspects of the present invention relate to a diagnostic apparatus (100) for use in testing an electromechanical actuator system of a vehicle (500). The diagnostic apparatus comprises one or more controllers (110), and the diagnostic apparatus configured to: generate a torque demand signal (155) corresponding to a torque demand profile (300), the torque demand profile configured to cause actuators of the electromechanical actuator system to modify a suspension of the vehicle (402); transmit the torque demand signal to the electromechanical actuator system of the vehicle (404); record a suspension characteristic of the vehicle in response to application of the torque demand signal (406); and output the recorded suspension characteristic of the vehicle (408).

The invention relates to the technical field of vehicles, and discloses a vehicle diagnosis method, vehicle diagnosis equipment, a vehicle diagnosis system and a storage medium, and the method comprises the steps: obtaining a to-be-executed diagnosis function instruction of a to-be-detected vehicle; according to a stored first corresponding relation, all execution paths of a diagnosis function instruction to be executed in the vehicle diagnosis equipment are determined, and the first corresponding relation is the corresponding relation between the diagnosis function instruction and the execution paths; acquiring vehicle configuration information of a to-be-detected vehicle; according to a stored second corresponding relation, a target execution path matched with the vehicle configuration information of the to-be-detected vehicle is determined from all the execution paths, and the second corresponding relation is the corresponding relation between the execution paths and the vehicle configuration information; and executing a diagnosis function corresponding to the target execution path on the to-be-detected vehicle. Through the above mode, the vehicle diagnosis efficiency is improved.

The invention relates to the technical field of high-energy particle diagnosis, and discloses an ion probe and diagnosis device.According to the scheme, an insulating plate is arranged in a probe, the insulating plate is plated with a plurality of aluminum films (forming conductive parts) arranged at intervals, when high-energy ions bombard the aluminum films at different positions, current signals can be generated in the corresponding conductive parts, and the high-energy ions can be detected through the current signals; the current amplifier amplifies a generated current signal, transmits the current signal to the signal processing system through the isolation amplifier, collects and analyzes the current signal by the signal processing system, and judges whether the conductive part is bombarded by high-energy ions by detecting the current signals formed in different conductive parts; the angle range of the high-energy ions relative to magnetic lines and the energy distribution range of the high-energy ions are obtained; according to the scheme, the aluminum film is bombarded based on the high-energy ions, the current signal is generated, the experiment cost can be effectively reduced, collection is greatly facilitated, interference of other signals is avoided, and the accuracy of high-energy ion diagnosis is improved to a certain extent.

The invention discloses a vehicle diagnosis method and device, equipment and a medium, and relates to the technical field of vehicle diagnos.The method comprises the steps that target related data are determined from a local database based on a received search instruction, and the target related data are displayed at the front end of the diagnosis equipment in a preset display mode so that a corresponding selection instruction can be received through the front end; determining a corresponding menu path according to the selection instruction, and determining to-be-transmitted data corresponding to the menu path from a local database when a diagnosis program under the menu path needs to be transmitted; and skipping to the menu path to determine a diagnosis program under the menu path, transmitting the to-be-transmitted data to the diagnosis program in an encrypted form after receiving a target diagnosis instruction, and starting the diagnosis program based on the to-be-transmitted data to diagnose the to-be-diagnosed vehicle. Therefore, the process of menu search and inter-page value transmission of the diagnostic software can be simplified to improve the diagnostic efficiency, and offline diagnosis is realized.

The invention relates to the technical field of power maintenance, and discloses a power distribution network-oriented single-phase earth fault AI comprehensive research and judgment system, which integrates a power distribution network monitoring module, a fault diagnosis equipment module and an AI comprehensive research and judgment module. The system can accurately judge the type, position and severity of the single-phase earth fault by monitoring and collecting all-dimensional data of the power distribution network in real time and combining intelligent analysis of the AI comprehensive research and judgment module, and the accuracy of fault positioning and isolation is remarkably improved. The AI comprehensive research and judgment module adopts a Markov decision process for modeling, and a deep reinforcement learning algorithm is used for training a research and judgment model, so that rapid fault positioning, isolation and power supply recovery are realized, the fault processing efficiency and the power supply recovery speed are effectively improved, and the power failure time and the influence on users are reduced.

The invention provides an electrical equipment fault diagnosis early warning system, and relates to the technical field of equipment fault diagnosis, and the system comprises a multi-sensor module which is used for obtaining electrical, thermal, mechanical and electromagnetic parameters of electrical equipment; the acquisition processing module is used for summarizing the acquired various parameters and carrying out preprocessing and feature extraction; the fault diagnosis module is used for analyzing indexes of electrical characteristics, thermal characteristics, mechanical characteristics and electromagnetic characteristics of the electrical equipment, fusing the indexes based on the type of the equipment and diagnosing the fault condition of the equipment; the early warning module is used for generating a fault trend image of the electrical equipment based on the fusion result; the man-machine interaction module is used for generating a corresponding signal based on the fault condition and the trend image; through the reasonable design and the processing mode based on the equipment working type, the method has good adaptability and universality to different electrical equipment and complex working conditions, overcomes the limitation of the prior art, improves the diagnosis accuracy, and provides time for maintenance personnel to avoid fault deterioration.

Understanding a health status and expected remaining lifetime of an EV (electric vehicle) battery is important before repurposing the battery for second life applications. A device for connecting to an unopened EV battery pack via operable coupling to signal and power wiring is disclosed. The device enables access to diagnostic information from the unopened EV battery. The device measures cell and / or module voltages and currents within the battery pack for several different depths of discharge. A self-learning algorithm implemented by the diagnostic device, which uses historical data and diagnostic information from the battery pack, determines a condition of the battery and provide recommended operational conditions for future use of the battery. For example, a degradation slope and expected capacity loss over time can be determined based on measured variations of cell and / or modular voltages and subsequently used, with cell impedance data, to recommend an operational C-rate for the battery pack.

The invention belongs to the technical field of vehicle diagnosis, and discloses a diagnosis report analysis method and system, terminal equipment and a storage medium, and the method comprises the steps: carrying out the vectorization of fault information, received by automobile diagnosis equipment, of a target vehicle, and obtaining target vector data; preprocessing the collected original data of the vehicle to obtain original vector data; calculating the similarity between the target vector data and the original vector data, and obtaining matched data in a preset similarity range; and performing diagnostic analysis on the target vector data and the matching data by using the first pre-constructed model to obtain a diagnostic analysis result of the target vehicle. After the original data is preprocessed to obtain the original vector data, the similarity between the target vector data and the original vector data is calculated, then the selected matching data is input into the first pre-purchase modeling for diagnosis analysis, the diagnosis decomposition result is obtained, and the interpretation efficiency and accuracy of interpreting the automobile diagnosis report are improved.

The invention relates to the field of equipment fault diagnosis, in particular to an Internet of Things equipment fault diagnosis method and system based on artificial intelligence, and the method comprises the steps: collecting operation state data and alarm signals of Internet of Things equipment, and carrying out the feature extraction to obtain a feature parameter set of the alarm signals; acquiring historical false alarm signals, extracting features of the false alarm signals and generating a false alarm signal feature library; performing feature matching on the feature parameter set of the alarm signal and a false alarm signal feature library, identifying and marking a false alarm signal label, and extracting a corresponding fault feature parameter from the false alarm signal feature library; judging the alarm signal with the false alarm signal label through a time delay verification method, and if the fault characteristic parameter of the alarm signal disappears, judging the alarm signal as a false alarm signal and removing the false alarm signal; if the fault characteristic parameter of the alarm signal does not disappear, determining that the alarm signal is a real alarm signal; real fault signals of equipment can be diagnosed more accurately, so that the accuracy and efficiency of fault diagnosis are improved.

The present invention provides a resistance property diagnosis apparatus, a diagnosis method, and a unit cell for a secondary battery satisfying a specific condition according to the method, the device comprising: an acquisition unit for acquiring a charge or discharge profile in a designated charge / discharge cycle of a unit cell; a generation unit for generating capacity-voltage differential data indicating a capacity-voltage differential value (dQ / dV) of the unit cell in a charge or discharge cycle included in the designated charge / discharge cycle, on the basis of the charge or discharge profile; and a diagnosis unit for diagnosing a resistance property of the unit cell on the basis of the capacity-voltage differential data.

A biosensor cartridge can include a circuit board having a connection terminal configured to be electrically connected to an external diagnostic device, a biosensor chip configured to detect a target material from an analysis specimen, and transmit an electrical signal to the connection terminal of the circuit board based on the target material being present in the analysis specimen, the biosensor chip including a reactant configured to react specifically with the target material, and a housing enclosing the circuit board and the biosensor chip, and the connecting terminal being exposed outside of the housing. Also, the biosensor chip includes a plurality of channel areas separated from each other, and the reactant is attached to the plurality of channel areas.

The invention discloses a knowledge distillation-based electrical equipment state transition diagnosis method and related equipment, relates to the technical field of deep learning, and solves the problem of low cross-equipment diagnosis accuracy. According to the method, the finite element model of the power equipment is constructed to generate the simulation fault data, so that the dependence on real fault data can be reduced, and the problem of fault sample data scarcity is solved; then training a teacher network based on the simulation fault data, training a student network based on the measurement fault data, and realizing knowledge migration from the teacher network to the student network through KL divergence, thereby improving the generalization ability of the student network; and the parameters of the student network are adjusted according to the real-time working condition parameters of the to-be-diagnosed equipment, so that the to-be-diagnosed equipment can be diagnosed more accurately through the obtained working condition self-adaptive diagnosis model. By adopting the embodiment of the invention, cross-equipment high-precision state transition diagnosis can be realized.

A battery diagnostic device according to an embodiment of the present disclosure includes: a measuring unit configured to measure a voltage and a temperature of a battery; an ohmic resistance determining unit configured to determine the ohmic resistance of the battery based on an impedance curve generated for the battery; and a control unit configured to calculate a voltage change by comparing the voltage of the battery measured by the measuring unit with a reference voltage, calculate a resistance change rate by comparing the ohmic resistance determined by the ohmic resistance determining unit with a reference resistance, determine a degree of internal gas generation in the battery by comparing the calculated resistance change rate with a reference resistance change rate, and determine a cause of internal gas generation in the battery by comparing the calculated voltage change with a standard voltage change.

The invention relates to the technical field of Internet of Things, in particular to an Internet of Things equipment operation and maintenance method based on large model fine tuning and multi-mode RAG, and a memory, and the method comprises the steps: respectively collecting external image information and data information for to-be-diagnosed equipment; generating question information according to the external image information and the data information, and inputting the question information into the Internet of Things large model to obtain feedback information fed back by the Internet of Things large model; and determining whether the to-be-diagnosed equipment is abnormal according to the feedback information. Aiming at the problems of low efficiency and inaccuracy of the manual inspection process of the Internet of Vehicles equipment in the prior art, external image information corresponding to equipment appearance inspection and data information acquired through channels such as a sensor and equipment metadata are introduced; and an Internet of Things large model optimized for the Internet of Things field is introduced to analyze the information, so that the Internet of Things large model effectively judges whether a fault exists or not, the inspection accuracy is improved, only appearance images need to be shot, and the efficiency is improved.

A mask-based diagnostic apparatus is provided for detecting a biomarker contained in exhaled breath of a test subject. An exhaled breath condensate (EBC) collector converts breath vapor received from the lungs and airways of the test subject into a fluid biosample. The EBC collector including a thermal mass, a condensate-forming surface and a fluid conductor disposed on the condensate-forming surface. A fluid transfer system receives the fluid biosample from the EBC collector. A biomarker testing unit receives the fluid biosample from the fluid transfer system and tests the fluid biosample for a target biomarker. A testing system support is provided for supporting the EBC collector, the fluid transfer system and the biomarker testing unit. The testing system support is configured and dimensioned to fit inside a face mask. A face mask is provided forming an exhaled breath vapor containment volume to hold the exhaled breath vapor in proximity to the EBC collector to enable the condensate-forming surface cooled by the thermal mass to coalesce the exhaled breath vapor into the fluid biosample.

The invention relates to the technical field of in-vitro diagnosis automation equipment, and discloses a reaction container feeding device and diagnosis equipment, and the reaction container feeding device comprises a hopper, a partition plate, a driving assembly, a material pushing part and a feeding assembly; a feeding hole is formed in the top of the hopper, and an opening is formed in the bottom; the partition plate is fixedly arranged in the hopper and divides the opening into a first sub-opening and a second sub-opening; the driving assembly is arranged at the lower end of the hopper; the material pushing part and the feeding assembly are connected with the driving assembly, the driving assembly drives the material pushing part to move up and down and penetrate through the first sub-opening so as to jack up the reaction container, and the driving assembly drives the feeding assembly to move up and down and penetrate through the second sub-opening so as to receive the reaction container jacked up by the material pushing part. The driving assembly is adopted to drive the material pushing piece to jack up the reaction container to the feeding assembly, meanwhile, the feeding assembly is driven to move upwards to receive the reaction container, the feeding structure of the reaction container is simplified, the occupied space is small, and the reliability is high.

The invention discloses a vehicle diagnosis method, device and equipment and a storage medium, and relates to the field of vehicle diagnos.The method comprises the steps that in the pre-diagnosis stage, physical connection with an electronic control unit on a target vehicle is established, and whether the electronic control unit broadcasts target data or not is monitored; if it is monitored that the current electronic control unit does not broadcast the target data, executing an operation of sending preset CAN data to the electronic control unit based on a preset Baud rate, and when the sending is successful, determining the preset Baud rate as a target Baud rate; if it is monitored that the current electronic control unit broadcasts the target data, determining a Baud rate during broadcasting as a target Baud rate; and after the target baud rate is determined, an electronic control unit activation command is sent to the electronic control unit based on the target baud rate, so that vehicle diagnosis operation is triggered after the electronic control unit is successfully activated. Therefore, the communication between the diagnosis equipment and the ECU in the offline state can be realized, so that the vehicle diagnosis is carried out.

There is provided an ultrasound diagnostic apparatus including an ultrasound probe and an apparatus main body wirelessly connected to the ultrasound probe, the ultrasound probe including a B-mode processing unit and an M-mode processing unit configured to generate a B-mode image and an M-mode image, a wireless communication circuit configured to wirelessly transmit the B-mode image and the M-mode image to the apparatus main body, and a probe control unit configured to control the wireless communication circuit such that, each time a generation of a certain number of scanning lines in the B-mode image, which is less than the number of scanning lines in a single frame of the B-mode image, is completed, wireless transmission of the certain number of scanning lines in the B-mode image and wireless transmission of the M-mode image are alternately performed.

The invention discloses a diagnostic software repairing method and device, equipment and a storage medium, and relates to the technical field of automobile diagnos.The method comprises the steps that a diagnostic software missing information message sent by diagnostic equipment is received; according to the missing information message, a target software upgrade package of the diagnostic software is generated, and a repair file of the diagnostic software is stored in a specified directory of the target software upgrade package; and sending the target software upgrade package to diagnostic equipment, and performing software repair on the diagnostic software by the diagnostic equipment according to a repair file under a specified directory of the target software upgrade package. According to the method, the repair software of the diagnostic software is stored in the target software upgrade package and sent to the diagnostic equipment together, and when the diagnostic software has file missing, the diagnostic software can be automatically repaired through the repair file, so that the user experience and the repair efficiency of the diagnostic software are greatly improved, and the after-sales cost is reduced.

The invention relates to the technical field of in-vitro diagnosis automation equipment, and discloses a feeding device cup arranging structure, a feeding device and diagnosis device.The feeding device cup arranging structure comprises a containing channel, a moving assembly, a base and a driving part; a feeding hole is formed in the top of the accommodating channel; the moving assembly is arranged in the containing channel, can move in the vertical direction of the containing channel and is used for bearing the reaction cup; the base is arranged at the lower end of the containing channel, the driving piece is arranged on the base, the moving assembly is connected with the driving piece through the connecting piece, and the driving piece is used for driving the moving assembly to move up and down along the containing channel. The moving assembly is arranged in the containing channel, the reaction cups collide with the inner wall of the containing channel in the falling process, under the action of gravity, the opening ends of the reaction cups are upwards arranged at the moving assembly, the cup clamping and cup transverse phenomena are avoided, and the reliability is high.

The invention relates to a power equipment output abnormal defect diagnosis method and device based on transfer learning, computer equipment, a storage medium and a computer program product. The method comprises the steps of collecting source domain data and target domain data, and constructing a source domain pre-training model; obtaining a target domain adaptation model; performing abnormity judgment by calling the historical maintenance record of the to-be-diagnosed equipment to obtain a final diagnosis result; and updating the source domain pre-training model and the target domain adaptation model. By adopting the method, the problem of target domain data scarcity in power equipment fault diagnosis can be effectively solved by combining transfer learning with adversarial training and semi-supervised fine tuning, cross-equipment high-precision anomaly detection and defect classification are realized, meanwhile, a diagnosis result is optimized by utilizing historical maintenance records, and continuous iterative optimization of a model is supported.

A mask-based diagnostic apparatus for detecting a biomarker contained in exhaled breath of a test subject. An exhaled breath condensate (EBC) collector converts breath vapor from the lungs and airways into a fluid biosample. The EBC collector includes a condensate-forming surface and a thermal mass in thermal connection with the condensate-forming surface. A fluid transfer system transfers the EBC to at least one of a testing unit and an EBC containment vessel. Prior to testing, a semipermeable membrane concentrates a target biomarker portion in the fluid biosample to form a concentrated fluid biosample for testing. A target biomarker releasing material, such as a lysing agent, and / or mechanical lysing, can be used to obtained a target biomarker for testing that is within a viral envelope. The testing unit can be a universal g-FET biosensor constructed as a packaged semiconductor device that receives and tests the EBC as a fluid biosample.

A battery diagnostic device, a battery pack, an electric vehicle, and a battery diagnostic method are provided. The battery diagnostic device according to the present invention is provided for a battery array including a first battery to an mth battery (m is a natural number equal to or greater than 3) connected in series. The battery diagnostic device includes a sensing unit that detects the voltage of each of the first battery to the mth battery, and a control unit that generates a first voltage profile to an mth voltage profile that indicate a voltage change history of each of the first battery to the mth battery during charging or discharging of the battery array. The control unit diagnoses the battery array by comparing a reference voltage profile, which is any one of the first voltage profile to the mth voltage profile, with a first comparison voltage profile to an (m-1)th comparison voltage profile that are the remaining (m-1) voltage profiles other than the reference voltage profile.

Methods and devices for analyzing non-volatile organics in exhaled breath and other aerosols using various diagnostic tools that enable rapid, low-cost point of care assays for several diseases including respiratory tract diseases such as COVID-19. The disclosed methods and systems selectively capture non-volatile organics in exhaled breath and other aerosols in a packed bed column. The non-volatile organics are eluted and samples are analysis using diagnostic devices including MALDI-TOFMS. The disclosed systems and methods provide for a diagnostic test result in less than about 20 minutes and provides for autonomous operation with minimal human intervention.