95 results about "Doppler flow" patented technology

The invention discloses a medical ultrasonic image intelligent processing method and system, and relates to the technical field of medical image.According to the main scheme, normal feature coordinates of different organs and tissues are calculated by obtaining normal ultrasonic image data, to-be-processed image data and historical medical record information of a patient; extracting coordinates of a to-be-detected image and comparing the coordinates with normal coordinates for preliminary judgment; performing secondary judgment by combining ovality and circularity; setting a lesion gray threshold to judge whether a lesion exists or not; calculating the size of a lesion area when the lesion exists; according to the method and the system, the comprehensive blood flow evaluation index is calculated in combination with color Doppler blood flow imaging data, the disease evaluation value is calculated according to known medical record data and the like, the disease level is judged, the diagnosis report is automatically generated, the accuracy and the efficiency of medical ultrasonic diagnosis are improved, and powerful support is provided for clinical diagnosis.

The invention relates to the field of ocean conductivity data processing, and discloses an Argo conductivity data correction method based on the influence of thermohaline internal waves, which comprises the following steps: installing a thermohaline depth sensor and an acoustic Doppler flow velocity profiler on an Argo buoy, sampling seawater in the vertical direction, and calculating the depth of the sampled seawater; acquiring temperature, salinity and flow velocity profile data of seawater; determining the upper and lower boundary depths of the thermohalocline and the thickness of the thermohalocline according to the acquired data, calculating the internal wave frequency and the internal wave number, and calculating the temperature internal wave amplitude, the salinity internal wave amplitude, the temperature internal wave phase and the salinity internal wave phase; establishing a conductivity data correction model according to the calculated parameters; and performing dynamic correction on the conductivity data by using the model. According to the method disclosed by the invention, the accuracy and the reliability of conductivity data can be remarkably improved, and support can be provided for research in many fields such as research on physical characteristics of the ocean thermocline and halocline, ocean ecological environment and ocean material circulation.

The invention discloses an acoustic Doppler flow velocity measurement method and system, and the method comprises the steps: generating an emission parameter combination adaptive to a current hydrological environment according to the depth characteristics and precision requirements of a target water area; original echo signals are collected based on the emission parameter combination, and a three-dimensional flow velocity vector of temperature compensation is output; inputting the three-dimensional flow velocity vector into the dynamic segmentation network to generate a layered flow velocity distribution model; calling a layered flow velocity distribution model, fusing fluxgate compass azimuth data to carry out flow direction compensation, triggering a deviation correction algorithm when equipment inclination exceeds a limit, and outputting absolute flow velocity distribution of pose calibration; and according to absolute flow velocity distribution and echo intensity dynamic range constraint, calculating an error interval of each depth unit, and outputting a final flow velocity profile with confidence identification. According to the embodiment of the invention, the environmental adaptability and data reliability of flow velocity measurement can be improved.

The invention discloses a bed load sediment transport rate measurement method based on multi-layer sediment acoustic signal attenuation correction of a Doppler velocity profiler, which comprises the following steps: sampling sediment on the surface of a riverbed in an overtopping area of a to-be-measured river reach, and measuring sediment gradation to obtain the median particle size of the bed sediment; obtaining flow measurement data, and extracting ship speed data from the flow measurement data; calculating a riverbed movement speed according to the ship speed data; filtering the riverbed movement speed data, and calculating a characteristic value of the filtered riverbed movement speed data; respectively calculating the vertical projection area ratio of bed load according to the filtered riverbed movement speed data characteristic values; calculating a dimensionless sediment particle size according to the median particle size of the bed sand; calculating the thickness of a bed load layer according to the dimensionless sediment particle size; calculating the volume concentration of the bed load according to the vertical projection area ratio of the bed load and the thickness of the bed load layer; calculating a multi-layer sediment sound signal attenuation correction coefficient according to the bed load volume concentration; and calculating the bed load sediment transport rate according to the multi-layer sediment sound signal attenuation correction coefficient. The bed load sediment transport rate can be accurately and effectively measured.

The present invention relates to the field of waterway monitoring technology, and specifically, to a real-time monitoring method and system for water depth of a port waterway. It includes: S1, selecting a monitoring point in the waterway, installing an intelligent buoy for monitoring waterway data at the monitoring point, the intelligent buoy is used to monitor waterway data, and deploying an acoustic Doppler current profiler to monitor the bottom flow velocity; S2, collecting waterway data collected by a sonar system and an acoustic Doppler current profiler; S3, constructing a waterway sedimentation model, and combining the real-time waterway data after preprocessing, introducing a time-dependent function, and correcting the measurement error of the real-time water depth data caused by silt silting; S4, based on the above steps S1-S3, constructing a network including multiple monitoring points to form a three-dimensional monitoring system for the waterway. By establishing a preliminary waterway sedimentation model of sedimentation rate and average bottom flow velocity, and introducing a time-dependent function and terrain factors, the prediction accuracy of future water depth changes in the waterway is improved.

The utility model discloses a pontoon type acoustic Doppler flow velocity profiler, which relates to the field of acoustic Doppler flow velocity profilers, and comprises a pontoon main body and an acoustic Doppler flow velocity profiler main body, and two electric push rods are arranged on the acoustic Doppler flow velocity profiler main body. Movable rings are installed at the output ends of the two electric push rods through piston rods, a plurality of connecting blocks are arranged on the outer wall of the acoustic Doppler flow velocity profiler body, stop levers are connected to the connecting blocks through rotating shafts, and push plates are connected between the stop levers and the movable rings through connecting shafts. According to the acoustic Doppler flow velocity profiler, the blocking rod and the protruding block are arranged, the blocking rod can protect the acoustic Doppler flow velocity profiler body and prevent objects from impacting the acoustic Doppler flow velocity profiler body, the protruding block is arranged so that the plastic bag can be conveniently hung, and the plastic bag in water is prevented from being wrapped on the outer wall of the acoustic Doppler flow velocity profiler body; therefore, the acoustic Doppler flow velocity profiler main body is prevented from detecting the water body.

The invention provides an ocean internal wave data acquisition method, medium and system, and belongs to the technical field of ocean hydrological observation.The ocean internal wave data acquisition method comprises the steps that an acoustic Doppler flow velocity profiler is used for acquiring water body movement data, a temperature-salinity-depth profiler is used for acquiring seawater parameters, and meanwhile a satellite altimeter and drifting buoy data are combined. Performing time-frequency analysis on the water body motion data, and obtaining internal wave candidate data by using band-pass filtering; and constructing an internal wave mathematical equation set comprising a hydromechanics basic equation, buoyancy frequency, a frequency dispersion relation and the like, and verifying and screening out effective data. And inputting the effective data into a pre-trained classification model to determine an internal wave type, finally extracting a key waveform segment through a preset extraction equation set, and generating and outputting internal wave characteristic waveform data. According to the method, multi-source observation data and a mathematical physical model are combined, identification, classification and feature extraction of the ocean internal waves are realized, and the problem that a data acquisition method capable of effectively extracting effective signals of the ocean internal waves and accurately identifying the features of the internal waves is lacked at present is solved.

An embodiment of the present application provides a method for determining blood flow velocity and a Doppler blood flow detection device, wherein the method comprises: obtaining an emission angle, which is the angle between the direction in which a signal is emitted by a transmitting element in the Doppler blood flow detection device and the direction in which blood flow moves in a blood vessel to be detected; obtaining the distance between a transmitting element and a receiving element in the Doppler blood flow detection device and the distance between the transmitting element and the blood vessel to be detected; determining a receiving angle according to the emission angle, the distance between the transmitting element and the receiving element, and the distance between the transmitting element and the blood vessel to be detected, wherein the receiving angle is the angle between the direction in which a signal is received by a receiving element in the Doppler blood flow detection device and the direction in which blood flow moves; determining a blood flow velocity measurement value according to the emission angle and the receiving angle; in this way, a more accurate blood flow velocity measurement value can be obtained.

The invention provides a water body motion state recognition method and device based on spectral moment characteristics and a readable storage medium thereof, and belongs to the technical field of hydrographic survey and intelligent analysis. According to the method, an acoustic Doppler flow meter is used for collecting a flow velocity sequence, the flow velocity sequence is converted into frequency domain power spectral density through short-time Fourier transform, multi-dimensional features including zero-order to fourth-order spectral moments, frequency band energy, statistics and spectrum features are extracted, a feature time heat map is constructed and input into a multi-scale residual convolutional neural network, and the multi-scale residual convolutional neural network is obtained. And identification of laminar flow, turbulent flow and backflow is realized. The method accurately depicts essential differences of three types of flow states through frequency domain features, retains weak signals in combination with multi-scale convolution kernel and residual connection, solves the problems that a traditional method is poor in interpretability and insensitive in distinguishing, and has the advantages of being high in recognition accuracy, high in robustness and suitable for multiple scenes such as rivers and dams.

The invention provides a three-dimensional multi-dimensional oceanic nekton monitoring method based on artificial intelligence, and relates to the technical field of oceanic nekton monitoring, and the method comprises the steps: deploying a temperature-salinity-depth section plotter and an acoustic Doppler flow velocity section plotter, collecting data, configuring an environment parameter data set, obtaining a three-dimensional environment parameter data set, and obtaining a three-dimensional environment parameter data set; and a multi-dimensional environment parameter database is generated. Various ocean fishery resource investigation means are fused, an advanced artificial intelligence method is applied, three-dimensional multi-dimensional dynamic monitoring of the ocean swimming animals is achieved, on one hand, the number composition and space-time distribution of the ocean swimming animals, especially the vertical distribution characteristics can be monitored, the population dynamics of the ocean swimming animals and the relation between the population dynamics and environmental factors can be revealed, and on the other hand, the population dynamics of the ocean swimming animals can be monitored. By monitoring the swimming animals, basic data can be provided for population resource evaluation, and the method serves formulation of fishing quota of ocean economic swimming animals, delimitation of ocean protection areas and the like.

The invention discloses a bed load particle movement velocity measurement method based on Doppler flow velocity profiler sound wave scattering correction. The method comprises the following steps: selecting a measurement river reach, sampling silt on the surface of a riverbed on a floodplain of an unsubmerged area, screening the sampled silt, and calculating the median particle size of the bed sand of the river reach according to the screening result; a measurement area is selected, an ADCP and a matched unmanned ship carrying DGPS are used for constant-speed cruise type flow measurement, and flow measurement data are obtained; calculating a riverbed movement speed according to the ship speed data; filtering the riverbed movement speed data, and calculating a characteristic value of the filtered riverbed movement speed data; respectively calculating a bed load vertical projection area ratio and a bed load scattering correction coefficient according to the filtered riverbed movement speed data characteristic value; and calculating the movement speed of the bed load according to the vertical projection area ratio of the bed load and the scattering correction coefficient of the bed load. According to the invention, the difficulty that the Doppler flow velocity profiler cannot be directly used to measure the accurate movement velocity of the bed load at present is overcome.

The invention particularly discloses a fractured rock mass grouting three-dimensional visualization test device and method, and relates to the technical field of rock mass engineering. The device comprises a test box body, a liquid inlet and outlet system, a monitoring system and a dynamic water environment simulation assembly, the test box body is made of a transparent acrylic material and is composed of an upper cover plate, a lower cover plate, a front cover plate, a rear cover plate, a baffle and two side cover plates, and a core experiment module is arranged in the test box body; the liquid inlet and outlet system is sequentially connected with the liquid holding device, the peristaltic pump, the valve, the Doppler flow velocity sensor and the test box body through rubber pipes; the monitoring system integrates an image collection unit and a data monitoring unit, an industrial-grade 3D camera and a binocular camera achieve visualization of the displacement process, and a fiber bragg grating pressure sensor synchronously collects fracture pressure data and transmits the fracture pressure data to a computer through a multifunctional data collection module. The device can be used for observing the displacement process of the slurry in the three-dimensional fracture in real time, synchronously monitoring key parameters, adapting to complex test working conditions and providing reliable support for grouting law research.

The invention discloses a method for correcting ultrafast ultrasonic motion displacement based on a VoxelMorph model to solve motion artifacts. Comprising the following steps: acquiring ultrafast ultrasonic data, preprocessing the acquired data to obtain an initial data set, and dividing the initial data set into a training set and a test set; constructing a VoxelMorph motion correction network model based on the lightweight attention module, training the neural network model based on the training set to obtain a motion calibration network model, and testing the motion calibration network model based on the test set to obtain motion calibration data; and performing clutter filtering by using singular value decomposition to separate a blood flow signal and a tissue signal of the calibrated data, extracting the blood flow signal, and performing power Doppler blood flow imaging. According to the method, motion artifacts and random noise occurring in the ultrafast ultrasonic imaging process can be effectively restrained, blur between blood vessels is reduced, and the Doppler blood flow imaging contrast ratio is improved.

A wearable Doppler blood flowmeter can be used with an inflatable cuff to measure blood flow, such as for assessing peripheral artery disease (PAD). The present approach can include techniques such as providing or using a wearable acoustic Doppler blood flowmeter, without requiring the intricate manipulation of a handheld Doppler probe. The system can select a pair of acoustic transmitter and acoustic receiver from a set of more than two transducers, including one or more of different locations, orientations, or spacings, such as to vary a targeted region. The RF echo response signal can be translated to an audio response signal. An audio response signal injection circuit can adaptively inject a noise or other enhancement signal, such as to help improve perceptibility of an audible characteristic of pulsatile arterial blood flow. A trained machine learning model can be employed to select or adjust operating settings, to assess diagnostic information, or both.

The invention provides a multi-parameter intelligent detection device for an urban underground drainage pipeline, and the device comprises an intelligent detection robot which comprises a trolley chassis module, a power module, an air-ground lifting module, a top road rolling module, and a mainboard module. The multi-sensor measurement system comprises a Doppler flow measurement module, an air parameter acquisition module, a heavy metal parameter acquisition module and a binocular parallax camera module; the intelligent detection robot collects and transmits flow parameters, gas components, heavy metal components and pipeline health state data of an underground pipe network in real time through the multi-sensor measurement system. According to the invention, the monitoring efficiency and management level of the underground drainage pipe network can be significantly improved, reliable data support is provided for operation optimization, flood control and drainage and pollution control of an urban drainage system, and smart city construction and environmental protection are assisted.

The invention relates to the technical field of water quality detection, and discloses a method and system for detecting the concentration of suspended solids in a canal water sample, and the method comprises the following steps: obtaining environmental parameters of a canal water body in real time, and synchronously collecting a light scattering intensity signal and an acoustic echo attenuation signal of the canal water body through a near-infrared optical sensor and an acoustic Doppler flow velocity profiler; calculating an initial suspended matter concentration value based on the light scattering intensity signal and the acoustic echo attenuation signal; correcting the initial suspended matter concentration value through a dynamic compensation algorithm according to the environmental parameters of the canal water body, and generating concentration data before calibration; inputting the concentration data before calibration into a pre-trained machine learning model, and outputting a final suspended matter concentration value; wherein the pre-trained machine learning model comprises a random forest regression model and a gradient boosting decision tree model. According to the scheme, the detection accuracy under the complex hydrological condition and the real-time response capability of the model under the disturbance scene can be improved.

The invention discloses a Doppler blood flow velocity estimation method based on high-frequency pulse differential frequency, and solves the problems of velocity estimation resolution reduction and artifacts caused by alternate transmission of a B mode and Doppler pulses in an ultrasonic dual-mode system. The method comprises the following steps: transmitting a high-frequency broadband ultrasonic signal compatible with B-mode imaging; the method comprises the following steps: receiving a superficial blood vessel echo signal, performing time domain sampling, converting into a discrete signal, extracting a narrow-band frequency spectrum through frequency sampling, and generating a low-frequency equivalent signal by using a multi-frequency-point differential frequency technology; calculating a covariance matrix of each signal, performing average weighting to remove artifacts, and generating low-frequency equivalent covariance data; and estimating the blood flow velocity through eigenvalue decomposition and spectral peak search. According to the method, two pulses do not need to be transmitted alternately, resolution reduction and artifacts are avoided, Doppler velocity estimation precision is remarkably improved, integrated waveform design is supported, and hardware implementation is simplified.

The invention discloses a method for measuring vascular elasticity modulus and blood pressure based on LC-OCT hyperelastic modeling, which comprises the following steps: accurately capturing dynamic deformation of blood vessels through high-resolution three-dimensional imaging and Doppler blood flow detection of LC-OCT, calculating the elasticity modulus (error is less than or equal to + / -5%) by combining a Fung model, and constructing a mixed blood pressure prediction model based on a theory-data dual-drive framework. High-precision inversion (MAE < = 5.1 mmHg) of systolic pressure, diastolic pressure and average arterial pressure is achieved, and dynamic transfer learning is adopted to adapt to the blood vessel characteristic differences of different crowds. The method has the advantages that blood vessel full-dimension characterization is achieved through multi-mode LC-OCT, dynamic transfer learning adapts to the difference of healthy / sick people, a theory-data dual-drive model gives consideration to physical interpretability and prediction precision, and a high-precision solution is provided for early diagnosis and personalized treatment of hypertension.

The invention belongs to the technical field of hydrodynamics, and relates to a subsurface flow accurate measurement method and system based on an acoustic Doppler flow velocity profiler. The method comprises the following steps: measuring a target water area by using an acoustic Doppler current profiler; extracting at least one boundary feature parameter at the measurement point; constructing a physical-data fusion model and carrying out pre-training; inputting effective flow velocity data located above the measurement blind area in the original data of the flow velocity profile and the boundary characteristic parameters into a pre-trained physical-data fusion model; and outputting the subsurface flow velocity distribution in the measurement blind area and the key statistic and confidence interval of the subsurface flow velocity distribution. According to the method, the respective defects of an existing physical model and an existing data driving model can be overcome, a subsurface flow accurate measurement method integrating physical interpretability and environment adaptability is provided, a traceable and verifiable model training and evaluation benchmark is provided, and the subsurface flow measurement accuracy in a complex environment is remarkably improved.

The invention discloses a pipeline flow measurement method and device for a non-full-flow pipeline, and relates to the technical field of pipeline flow measurement, measurement is carried out through a pipeline flow measurement system, and the pipeline flow measurement system comprises a sonar probe which is arranged in the pipeline and floats on the water surface of the pipeline and a Doppler flow meter which is arranged in a water passing area in the pipeline. The method comprises the steps that a target echo signal, detected by a sonar probe, of a water passing area in a pipeline is acquired, and section contour data and section area of the water passing area are determined according to the target echo signal; performing grid division on the water passing area according to the section contour data to obtain a preset number of grid units, and calculating flow velocity distribution of each grid unit through frequency shift detected by a Doppler flow velocity meter; on each grid unit, the corresponding flow velocity value is multiplied by the area of the grid unit according to the flow velocity distribution, and then summation is carried out to obtain the pipeline flow. The problem that in the prior art, the accuracy is low when the pipeline flow of the non-full-flow pipeline is measured is solved.

The invention relates to the technical field of submarine mining, in particular to a multi-vehicle cooperative deep-sea mining underwater positioning navigation system and a working method, and the system comprises a wireless communication positioning device, a long baseline positioning assembly, an ultra-short baseline positioning assembly, a communication cable, an inertial navigation system and a Doppler flow velocity log; the long baseline positioning assembly comprises a long baseline positioning node, a long baseline positioning terminal and a long baseline resolving unit; the ultra-short baseline positioning assembly comprises an ultra-short baseline positioning array and an ultra-short baseline positioning terminal. The method can be applied to underwater comprehensive positioning and navigation of a plurality of mining vehicles, conveying hoses, relay stations and conveying vertical pipes in a commercial mining system.

The invention provides an AS risk identification and prediction method based on AI ultrasonic images and hydromechanics, which quantifies the influence of plaques on blood flow through deep learning and hydromechanics simulation, and adopts ultrasonic images and Doppler data to construct a plaque AI identification model, so as to identify the AI risk of the plaques. Identifying plaque morphological characteristics in the artery cross section ultrasonic image of the patient and blood flow characteristics in the Doppler blood flow data, and outputting a morphological score corresponding to the plaque morphological characteristics and a hemodynamic score corresponding to the blood flow characteristics; and comprehensively calculating and outputting an AS risk score of the AS patient. The plaque detection accuracy based on the ultrasonic image is improved, and quantitative evaluation of the acute thrombus risk is realized. Multi-level analysis can be carried out on the form and blood flow characteristics of plaques, and more accurate risk grading support is provided for doctors. The non-invasive ultrasonic image is combined with AI and fluid mechanics simulation to realize double analysis of morphological characteristics and hemodynamic parameters of the atherosclerotic plaque.

The invention relates to a blood flow parameter measuring device, equipment, a storage medium, an ultrasonic probe and a system, and belongs to the field of medical instruments. The blood flow parameter measuring device comprises a first obtaining module used for obtaining a first measuring parameter obtained by a first transducer group in an imaging mode; the second acquisition module is used for acquiring a second measurement parameter acquired by the second transducer group in the imaging mode or the Doppler blood flow detection mode; the first measurement parameter and the second measurement parameter both comprise a blood vessel position, a blood vessel depth, a blood vessel diameter and a Doppler included angle; the correction module is used for performing combined calculation on the first measurement parameter and the second measurement parameter and correcting the blood vessel diameter and the Doppler included angle; and the monitoring module is used for monitoring hemodynamic parameters of the target object according to the corrected blood vessel diameter and Doppler included angle. According to the technical scheme, the stable hemodynamics evaluation result can be output.

The utility model discloses an acoustic Doppler flow velocity measuring device which comprises a lifting support, a chain guide rail is arranged on the lifting support, and a chain used for pulling a measuring mechanism is arranged in the chain guide rail. The first lifting mechanism comprises a driving part which is provided with an output shaft, a winding drum is arranged on the output shaft, and a steel wire for pulling the measuring mechanism to lift is wound on the winding drum; the second lifting mechanism comprises an arc-shaped guide rail, an arc-shaped groove is formed in the guide rail, and the chain can extend into the guide rail from one end of the arc-shaped groove and extend out of the guide rail from the other end of the arc-shaped groove; and the chain wheel is fixedly connected to one end of the output shaft and is meshed with the chain. According to the utility model, the first lifting mechanism and the second lifting mechanism are arranged at the same time, and when one lifting mechanism breaks down, the other lifting mechanism can be used for driving, so that the phenomenon that the measuring mechanism cannot be pulled due to the damage of the lifting mechanism is avoided.

The utility model relates to the technical field of acoustic Doppler flow velocity profiler detection, and discloses an acoustic Doppler flow velocity profiler pressure sensor online detection device, which comprises a main frame, a pulley component and a cross beam component, the main frame is formed by welding square tubes, the two square tubes arranged in parallel at the bottom serve as supporting guide rails of the tackle component, the two vertical guide rails are symmetrically arranged on the two sides of the main frame, the cross beam component is arranged between the two vertical guide rails, and the main frame, the tackle component and the cross beam component are combined. The pressure sensor on-line detection equipment is low in cost, simple in operation and compatible with acoustic Doppler flow velocity profilers of various specifications, three notches are formed in the side portion of a vertical guide rail so that a cross beam component can have a high-middle-low fixing position, and three notches are formed in a guide column so that a clamping assembly can have a high-middle-low fixing position. And meanwhile, by virtue of the length of the screw rod, the device can be adapted to acoustic Doppler flow velocity profiler in three height ranges.

The present invention relates to the field of ocean conductivity data processing, and discloses an Argo conductivity data correction method based on the influence of thermohaline cline internal waves, comprising the following steps: installing a thermohaline depth sensor and an acoustic Doppler current profiler on an Argo buoy, sampling seawater in a vertical direction, and obtaining the temperature, salinity, and current profile data of the seawater; determining the upper and lower boundary depths of the thermohaline cline and the thickness of the thermohaline cline based on the acquired data, calculating the internal wave frequency and the internal wave number, calculating the temperature internal wave amplitude and the salinity internal wave amplitude, as well as the temperature internal wave phase and the salinity internal wave phase; establishing a conductivity data correction model based on the calculated parameters; and dynamically correcting the conductivity data using the model. The method disclosed by the present invention can significantly improve the accuracy and reliability of conductivity data, and can provide support for research in many fields such as the physical characteristics of the ocean thermohaline cline, the marine ecological environment, and the circulation of marine materials.

The invention provides a muscle-bone injury area identification method and system, and relates to the technical field of muscle-bone image injury identification. The method comprises the following steps: acquiring a two-dimensional gray-scale ultrasonic image of a target muscle-bone injury area, and positioning a synovial tissue area from the two-dimensional gray-scale ultrasonic image; extracting target feature information from the synovial tissue region; and determining the inflammation activity degree of the synovial tissue according to the target feature information. According to the method, Doppler blood flow signals are completely bypassed, the rheumatism inflammation activity degree is evaluated only through rich information contained in the two-dimensional gray-scale ultrasonic image, and therefore interference of probe pressure artifacts is thoroughly avoided.

The invention provides a method and system for calculating a heart output state through an ultrasonic color image, and the method comprises the steps: obtaining a first image of a Doppler blood flow velocity and a second image of a Doppler blood flow intensity signal, and obtaining the variance of a blood flow signal through the calculation of the first image and the second image; calculating each pixel point in the ultrasonic color blood flow image frame, extracting the variance, speed and energy of a blood flow signal corresponding to the pixel point, and determining whether the current pixel point is a blood flow point; and for the color blood flow signal variance in the time dimension, according to an effective blood flow proportion, calculating a time curve of a blood flow point in the effective blood flow proportion to obtain a Doppler blood flow curve, and calculating the Doppler blood flow curve to obtain an average heart rate, a blood flow peak value frame and a blood flow valley value frame of the current ultrasonic color blood flow image. The system comprises an image processing module, a parameter calculation module and a curve analysis module. According to the invention, the output state of the heart can be comprehensively understood and evaluated.

The utility model discloses a Doppler flow meter device, and relates to the technical field of flow meters. Comprising a mounting support, a flow instrument probe is mounted on the mounting support, a Venturi jet device is mounted on the front side of the mounting support, a jet orifice of the Venturi jet device corresponds to the detection end of the flow instrument probe, a supporting rod is in threaded connection with the rear side of the mounting support, and the upper portion of the supporting rod is sleeved with a lower fixing plate; the lower fixing plate is in threaded connection with a hand-screwing bolt and is in fastening connection with the supporting rod through the hand-screwing bolt. According to the Doppler flow instrument device, the Venturi jet device is connected with the vortex fan, the high-pressure air source is connected, when the high-pressure air source enters the jet cavity from an inlet of the jet device to form high-speed jet fluid, dirt on the detection end of the probe is removed through impact, collision and friction of the high-speed jet fluid, the probe is easier and more convenient to clean, and the detection efficiency is improved. Manual checking and cleaning are not needed, and the accuracy of data measurement is improved.

The utility model relates to the technical field of acoustic Doppler flow velocity profiler assembly, and discloses a split transducer array locking and turning device of an acoustic Doppler flow velocity profiler, which comprises a workbench and a liftable support, the liftable support is arranged on the workbench, one end of the liftable support is rotatably provided with a vertical rotating shaft, and the other end of the liftable support is rotatably provided with a horizontal rotating shaft. A transverse rotating shaft in a horizontal posture is installed in the middle of the vertical rotating shaft, the transverse rotating shaft is fixedly connected with the cross beam through a support, and an elastic lifting pin is installed on the side portion of the support. The two faces of the split transducer array are operated on the device, overturning and station transferring can be achieved without two-person carrying, additional power source assistance is not needed, only small force is needed for overturning, one operator is saved, and the labor intensity of the operator is reduced.