550results about How to "Quick calculation" patented technology

The invention discloses a KR stirring vortex radius image recognition method, which comprises the following steps of S1, establishing an image data acquisition system, and acquiring image data; s2, preprocessing the image data according to the number of frames so as to enhance the image data; s3, carrying out threshold segmentation with correction on each frame of image data; s4, selecting an image recognition baseline position; s5, establishing a region window, and identifying a stirring radius; s6, establishing a search micro window in the area window, and determining the position of the stirring radius; and S7, carrying out filtering processing on the real-time identification data so as to smoothly process the discrete data and eliminate abnormal identification values. According to the method, the real-time vortex radius is recognized by adopting a threshold segmentation technology and combining a selective area window progressive search technology aiming at an image recognition parameter (vortex radius), and rapid calculation and image capture accuracy of vortex recognition are realized.

The invention discloses a cable joint early warning method, device and equipment and a storage medium, and the method comprises the steps: carrying out the preprocessing of a collected effective temperature data set, and constructing an initial temperature relation model; continuously acquiring real-time surface temperature data and environment temperature data of the cable joint, and calculating real-time internal temperature and temperature anomaly degree by using the initial temperature relation model and the temperature data acquired in real time; according to the temperature abnormal degree and the change trend thereof, performing multi-stage division on the abnormal condition, and generating temperature early warning information containing the abnormal degree and the position information; and when the temperature early warning information appears, retrieving a pre-established historical temperature anomaly case library, finding out historical cases similar to the current temperature anomaly condition, and generating targeted temperature anomaly processing suggestions according to the retrieved similar historical cases and the current power grid operation condition. According to the technical scheme of the invention, the potential abnormal temperature condition of the cable joint can be identified timely and accurately, and effective early warning and processing suggestions can be provided.

The invention discloses an asphalt pavement structure performance analysis method and system, relates to the technical field of road engineering, and aims to solve the problem that an asphalt pavement structure performance analysis model is insufficient in self-adaptability, and the asphalt pavement structure performance analysis method comprises the following steps: obtaining test measurement data of a drop weight deflectometer; combining the adjacent structural layers according to the similarity of the structural layer materials; different numerical simulation models are established according to different configuration parameter combinations, and structural performance evaluation indexes are calculated respectively; different samples are established according to different numerical simulation models, weights of different samples are calculated and normalized, and a sample training structure performance index calculation model is established and input; and calculating a structural performance evaluation index of the target road section according to test measurement data of the drop weight deflectometer of the target road section by applying the structural performance index calculation model. According to the asphalt pavement structure performance analysis method and system provided by the invention, the attention of the trained model to a specific sample can be improved, and the adaptive ability and prediction precision of the trained model are improved.

The invention discloses a current inversion method based on a magnetic sensor array, and the method comprises the steps: S1, setting a plurality of measurement points, uniformly dividing a conductor layout region in a to-be-measured part of a to-be-measured multi-conductor system into grids with M * N nodes, and numbering each grid node as (i, j); constructing a coordinate system and recording coordinates of all grid nodes; s2, establishing a finite element simulation calculation model, calculating a reference position coefficient matrix of all measurement points, and constructing a reference position coefficient matrix database; s3, calculating a conductor position coefficient matrix, and constructing a position coefficient matrix; s4, according to the magnetic field measurement value acquired by the magnetic sensor array, the conductor current is calculated through inversion; and S5, after resampling the magnetic field measurement value, substituting the updated measurement value and the position coefficient matrix stored in the step S4 into the linear equation set constructed in the step S4 to solve the current of each conductor. The method has the characteristics of rapid calculation and low operand while the accuracy is ensured, and the inversion calculation efficiency can be improved.

The invention relates to the technical field of carbon emission accounting, and particularly discloses a carbon emission calculation method and system for railway infrastructure construction, and the method comprises the steps: firstly, calling basic data of a railway infrastructure from a background database and corresponding carbon emission which is verified to be real to construct a reference sample set; and carrying out embedded coding and dynamic semantic search on the basic data of the to-be-verified railway infrastructure uploaded by the user and each reference sample by adopting a data processing technology based on deep learning, so as to query response information based on the semantic query between the to-be-verified basic data and each reference sample. And the reasonable carbon emission amount of the railway infrastructure to be verified is intelligently estimated, and whether the total carbon emission amount of the railway infrastructure to be verified uploaded by the user is true or not is judged based on the reasonable carbon emission amount of the railway infrastructure to be verified. According to the method, rapid and accurate calculation and verification of the carbon emission in the railway infrastructure construction process can be realized, false declaration is avoided, and the authenticity and reliability of the carbon emission data are improved.

The invention discloses a waterproof composite material production intelligent control system, and relates to the technical field of control systems, the system comprises a data acquisition layer, a standard template generation module, a data processing layer, a Transform-based model core layer and an output layer, the data acquisition layer acquires production data in real time; a data processing standard template is generated through a standard template generation module, standardization processing is conducted on real-time data through a data processing layer, production process modeling and production state analysis are conducted through a Transform model core layer, an analysis result is decoded into a control instruction through an output layer, and production line process parameters are adjusted. The production process is intelligently and optimally controlled by applying the artificial intelligence technology, the intelligent level, the operation efficiency and the product quality of the production line are remarkably improved, meanwhile, the production goals of energy conservation, efficiency improvement and intrinsic safety are achieved through refined management and control and whole-process safety protection, and intelligent and green development of the waterproof composite material industry is promoted.

The invention belongs to but is not limited to the technical field of three-dimensional space dose visualization, and discloses a three-dimensional nuclear emergency radiation field calculation and visualization method and system, based on a point nuclear method, a cumulative factor, mass attenuation factor and flux rate-dose rate conversion factor database is established, a mean free path solving algorithm is optimized, and a three-dimensional nuclear emergency radiation field is obtained. The geometric types of radioactive sources are expanded, and the dose calculation efficiency is improved through parallel calculation; plane dose rate drawing at a certain height is realized based on a two-dimensional texture mapping method; three-dimensional space dose rate contour surface drawing is realized based on a moving cube algorithm; and three-dimensional space dose rate volume rendering is realized based on a three-dimensional texture volume rendering technology. Radiation field dose calculation, three-dimensional radiation field dose visualization and GIS are integrated, and the system is used as a subsystem of a nuclear emergency aid decision simulation platform. The dose distribution diagram in the area can be judged more visually, and the method has a good help effect on nuclear emergency command.

The invention discloses an improved DWA and A * algorithm fused path planning method based on a ship intelligent collision avoidance decision-making system, and relates to the field of path planning. Constructing a rasterized map according to the electronic chart data and the starting point and the ending point of path planning, and determining physical information of ships on the water surface; an improved DWA algorithm is adopted for path planning, when the distance between the water surface ship and the obstacle is smaller than the safe distance, an improved A * algorithm is called for global path planning from the current position to the terminal point, and a path point is returned; extracting a path key point as a temporary end point of the improved DWA algorithm, and continuing to perform dynamic path planning until the surface ship reaches the end point; and importing the DWA algorithm and the A * algorithm after fusion improvement into a ship intelligent collision avoidance decision-making system, and generating an optimal obstacle avoidance path in combination with the marine environment data and the target fusion data. The method is suitable for a complex sea area dynamic environment, and the feasibility and safety of water surface ship path planning can be improved.

The invention relates to the technical field of tunnel surrounding rock structure deformation measurement, and provides a tunnel surrounding rock structure deformation measurement system based on machine vision, a visual recording module performs multi-angle image recording on the position of a tunnel surrounding rock structure, and a data preprocessing module performs gray processing on the image transmitted by the visual recording module; the structure deformation analysis module obtains tunnel surrounding rock structure images under the safe condition, and compares and measures the characteristic value difference value of the two images according to the images transmitted by the data preprocessing module. The cross validation module verifies the analysis result of the multi-angle recorded image in the structural deformation analysis module, the early warning module performs early warning according to the verification result of the cross validation module, and the standby measurement module monitors the operation state of an industrial camera in the visual recording module in real time. When the industrial camera in the visual recording module cannot work, access is carried out; according to the invention, the requirements of real-time monitoring and accurate early warning of surrounding rock deformation in the tunnel operation process are met.

The invention relates to the technical field of air traffic management, in particular to a low-altitude airspace unmanned aerial vehicle hot-spot-free flight path rapid planning method and system, and the method comprises the steps: receiving a hot-spot-free flight path planning request, and determining the constraint condition of hot-spot-free flight path planning based on the hot-spot-free flight path planning request; based on the starting position, the ending position and the constraint condition, generating a directed graph representing the flight path of the unmanned aerial vehicle in a space-time grid constructed by the eight-in-and-out-point grid airspace model; the edges of the directed graph are endowed with weights based on the airspace use cost and the energy consumption cost, a weighted directed graph is generated, the weighted directed graph is searched based on the airspace use cost and the energy consumption cost, and an optimal path in the weighted directed graph is obtained and serves as a hot-spot-free track; according to the method, the search complexity can be reduced, the execution efficiency is improved, and the airspace use overhead is reduced.

The invention provides an asymmetric short-circuit current calculation method and system for a large-scale new energy station. The method comprises the following steps: judging a fault type and a fault phase; the negative sequence impedance of each new energy station is calculated, and the positive sequence initial voltage of each new energy station is calculated; calculating the output short-circuit current of each new energy station; according to the fault composite sequence network, a simplified equivalent circuit is obtained through circuit simplification; calculating the positive sequence voltage of each new energy station; comparing the positive sequence voltage and the positive sequence initial voltage of each new energy station, judging whether a voltage difference value meets convergence precision or not, and solving negative sequence current and zero sequence current output by each new energy station according to a circuit equation; and outputting the output phase current of each new energy station. According to the method, the influence of converter control on a phase selection element is overcome, the number of iterations can be effectively shortened, the process of solving matrix inverse operation by a node voltage method is avoided, and the method has relatively good engineering practicability and precision and can be suitable for a large-scale new energy field station.

The invention relates to a method for rapidly calculating the RCS of a coated unmanned aerial vehicle under a complex background, and belongs to the field of stealth target electromagnetic scattering calculation. Comprising the following steps: determining reflection coefficients of a single-layer wave-absorbing material with a PEC substrate at different incident angles according to an equivalent transmission line theory; calculating induced current generated by incident electromagnetic waves on the surface of the target coated with the single-layer wave-absorbing material according to the reflection coefficient; based on the induced current, utilizing physical optics and physical diffraction theories to calculate scattered fields of all the illuminated surface elements, and superposing all the calculated scattered fields; the scattering field of each surface element on the sea surface model at a fixed angle is obtained through vector superposition of the scattering fields obtained through an EPO'field and a TSM; and finally, superposing all the scattered fields, and calculating the total field RCS of the complex sea background and unmanned aerial vehicle composite model based on the superposed total scattered field. According to the method, the RCS of the coating unmanned aerial vehicle under the complex background can be quickly calculated.

The invention belongs to the field of traffic control systems, and relates to a vehicle driving track prediction system and method based on an improved graph neural network model, and the system comprises an FPGCN model and a Social LSTM model. The FPGCN model comprises a graph convolution layer, a Dropout layer, a differential pooling layer, a feature fusion module and a full connection layer; obtaining node feature vectors from graph structure data through a graph convolution layer, a Dropout layer and a differentiable pooling layer, then dividing and conquering node features, generating global features through a dense attention mechanism and principal component analysis, and generating local features through virtual filling and matrix calculation; after global features and local features are obtained, a feature fusion module is used for fusion, then the features are input into a full connection layer, and the influence score of a historical trajectory diagram on a current state diagram is calculated; integrating the preprocessed driving data and the data of which the score is calculated by the FPGCN model, and inputting the integrated data into a Social LSTM model; according to the system, while the model expression ability is maintained, the parameter quantity is remarkably reduced, the calculation logic is optimized, and the prediction accuracy is improved.

The invention discloses a multi-fault risk assessment and early warning method for a power battery, and the method comprises the steps: requesting the recent life cycle data of an in-service electric vehicle power battery from a cloud server, carrying out the data preprocessing, and obtaining a temperature value of any single battery in the power battery through an interpolation method; differentiating the voltage value and the temperature value of any battery monomer to obtain a fault discrimination signal; establishing a multi-fault risk discrimination model based on the fault discrimination signal to calculate absolute fault degree scores corresponding to different faults of the battery; performing statistics on data distribution of various battery faults and fault degree scores, determining a fault grading range according to a distribution result, and drawing a multi-fault risk early warning graph; and carrying out early warning on results in a specific fault grading range according to severity. According to the method, various faults of the power battery can be evaluated and separated, battery maintenance and overhaul reference can be provided for a vehicle owner in time according to the multi-fault risk early warning graph, calculation is simple, deployment is convenient, and the method has practical application value.

The invention belongs to the field of computational explosion mechanics, and particularly relates to a rapid calculation method for a shock wave and detonation wave propagation process in a non-uniform medium, and the rapid calculation method comprises the following steps: 1, initializing a calculation program; step 2, estimating and calculating step length in each time step; step 3, carrying out integration on the ordinary differential equation by adopting an explicit three-order TVD Runge-Kutta format; 4, solving a Mach number through an A-M relation; 5, data correction is carried out, wherein the data correction comprises regularization and smoothing processing of grids; and step 6, checking whether termination time is reached or not, if so, ending all processes to complete operation, and if not, returning to the step 2 to continue to circularly solve. According to the rapid calculation method, rapid numerical calculation of propagation of shock waves and detonation waves in a non-uniform medium is achieved, wherein the phenomena comprise refraction, transmission, Mach reflection and the like.

The invention discloses an equivalent global average TEC calculation method and device based on occultation observation. The method comprises the following steps: acquiring VTEC characteristic parameters calculated by an occultation event within preset time periods before and after a to-be-calculated reference moment; and inputting the VTEC characteristic parameters into a trained neural network model, and outputting an equivalent global average TEC at a corresponding reference moment. According to the method, the parameters equivalent to the global average TEC are calculated by using global occultation observation, namely, the parameters equivalent to the global average TEC are calculated, and the calculation process of the global average TEC is simplified.

The invention discloses an underwater topographic data denoising method based on triangulation. The method comprises the following steps: step 1, carrying out tide level correction, sound velocity correction and attitude correction on collected underwater topographic point cloud data to complete data preprocessing; step 2, carrying out gridding processing on the point cloud data, and dividing regions according to topographic characteristics; step 3, in each grid, selecting an elevation median as a sample point, performing triangulation based on the grid sample point, and calculating an error distance from the point to a triangular surface; step 4, calculating an adaptive threshold according to multi-level error range statistics and dynamic weight optimization; and step 5, judging and eliminating noisy points according to the threshold value, and outputting purified point cloud data. According to the invention, the method combines regional dynamic threshold adjustment, multi-level error range statistics and dynamic weight optimization, and realizes rapid and efficient noise elimination.

The invention provides an epitaxial growth rate calculation method and system based on a neural network. The method comprises the following steps: collecting reflectivity data in a wafer epitaxial growth process; and preprocessing the reflectivity data to obtain input data. According to the method, the complex nonlinear relationship among the reflectivity data, the refractive index value (n) and the extinction coefficient value (k) is constructed through the neural network model, and the preprocessed reflectivity data is input into the neural network model, so that the refractive index value (n) and the extinction coefficient value (k) of the nonlinear relationship can be quickly and accurately obtained; the epitaxial growth rate of the wafer is calculated according to the refractive index value (n) and the extinction coefficient value (k). The method is high in processing efficiency, the epitaxial growth rate can be rapidly and accurately calculated in real time, the neural network model can adapt to multiple types of epitaxial growth by adjusting weight parameters in training, and the method has multi-process universality and is wide in application range.

The invention discloses a method for constructing a 3D Gaussian model based on threshold and statistical filtering optimization, which comprises the following steps: firstly, carrying out batch background removal on a reconstructed picture, cutting the size of the picture into half of the original size, and carrying out 3DGS reconstruction by taking the image as input data; and removing black Gaussian ellipsoids and discrete points by adopting a threshold and statistical filtering method, finally optimizing a 3D Gaussian point cloud file format, removing useless parameters in the 3D Gaussian point cloud file, and exporting the optimized point cloud file. According to the method, the background of the picture is firstly removed, the sparse point cloud reconstruction speed is accelerated, only the Gaussian model of the target object is generated, in addition, the black Gaussian ellipsoid and discrete points are removed by adopting a threshold and statistical filtering method, and the accuracy and the stability of the model are improved.

The invention relates to the technical field of prestress construction, in particular to a prestress duct friction resistance measuring method and system based on weak grating optical fibers. Comprising the following steps: during steel strand production, selecting a plurality of steel strands, and implanting weak grating optical fibers into the steel strands to form optical fiber steel strands; when a steel strand is installed, at least one steel strand with optical fibers is installed in a prestressed duct in a concrete beam, and a tensioning end system and an anchoring end system are arranged at the two ends of the installed steel strand; the weak grating optical fiber is connected with an optical fiber demodulator, and a tensioning end system is used for carrying out graded loading on the steel strand; and recording a tension value monitored by each strain grating measuring point, and calculating a pore friction resistance coefficient and a pore deviation coefficient based on the tension values. The measuring method provided by the invention is very simple and very accurate, does not need to purchase a pressure sensor additionally, has low requirements on test conditions, and can be suitable for any prestressed duct shape.

The invention discloses an intelligent intercepting gate control method and system based on three-dimensional decision, and relates to the technical field of intelligent control, and the method specifically comprises the steps: obtaining pipeline water inlet data, and carrying out the preprocessing of the pipeline water inlet data, and obtaining the preprocessing data; inputting the preprocessed data into a TransConv-LSTM (Long Short Term Memory) model, and outputting a predicted value of the ammonia nitrogen content; obtaining uncertainty distribution of the ammonia nitrogen content predicted value based on an uncertainty model; generating a control instruction according to the ammonia nitrogen content predicted value, the uncertainty distribution of the ammonia nitrogen content predicted value and a preset gate action condition; and controlling the closure gate to act based on the control instruction. According to the method, the accuracy and reliability of water quality control can be effectively improved, the cost can be reduced, the data privacy can be protected, and intervention is performed in advance by predicting the future trend, so that more efficient and sustainable water resource management is realized.

The invention discloses an unmanned aerial vehicle cluster control method and system based on distributed reasoning, and the method comprises the steps: generating a task calculation instruction, and transmitting an own resource condition reporting instruction to all slave unmanned aerial vehicles; determining the number of slave unmanned aerial vehicles needing to cooperate according to the calculated amount of the generated task, the priority and the time delay requirement; evaluating the calculation capability of each slave unmanned aerial vehicle according to the received resource information of the slave unmanned aerial vehicles, and determining the cooperative slave unmanned aerial vehicles; based on a load balancing target, determining a task splitting result and a data splitting result model splitting result, splitting the task into a plurality of sub-tasks according to the task splitting result, and distributing the sub-tasks to corresponding slave unmanned aerial vehicles needing collaboration; receiving an execution result of executing the allocated sub-task by the cooperative slave unmanned aerial vehicle; and receiving a final execution result of the task, and issuing a corresponding execution instruction to the unmanned aerial vehicles in the unmanned aerial vehicle cluster according to the final execution result. According to the invention, adaptability and flexibility are improved.

The invention discloses a device and method for detecting phase information of an electric energy meter based on dual-mode acquisition communication equipment, and the device comprises a central coordinator which is used for network configuration and networking, guarantees the mutual communication between equipment, and transmits the phase information of the acquisition communication equipment; the acquisition communication equipment acquires power grid phase information from the central coordinator after network access is successful, and broadcasts the phase information and zero-crossing information of the acquisition communication equipment through an RS-485 communication protocol; and the plurality of electric energy meters are used for receiving and collecting the phase information and the zero-crossing information of the communication equipment, and calculating the phase information of the electric energy meters by detecting zero-crossing signals of the electric energy meters and combining the phases of the communication equipment. According to the invention, mode expansion can be carried out on the basis of the existing RS-485 communication interface, the collected zero-crossing information of the communication equipment is stably synchronized to the electric energy meter, the electric energy meter calculates the phase information by combining the zero-crossing information of the electric energy meter, and the technical scheme of the invention is simple and reliable and occupies few resources.

The invention provides a slag field earth-rock volume measuring and calculating device and method based on close-range photogrammetry, and relates to the technical field of close-range photogrammetry. Comprising a photogrammetric device, the photogrammetric device is used for shooting image data of a slag field, the photogrammetric device comprises a digital camera, a tripod, a holder and a GPS and GNSS positioning system, and an image processing system is used for carrying out preprocessing, distortion correction, radiation correction and denoising processing on the shot image data. According to the technical scheme, by using the high-resolution camera and an advanced image processing algorithm, the device can more accurately capture details on the surface of the slag field, so that errors are reduced when a three-dimensional model is constructed, the high-precision three-dimensional model can more accurately reflect the actual shape and the volume of an earth-rock cube, and the accuracy of the three-dimensional model is improved. The calculation result of the earth-rock volume is more accurate, which is crucial for engineering management and resource planning because the method can reduce cost waste or resource shortage caused by inaccurate estimation.

The invention discloses an oil reservoir grade carbon dioxide burying stock calculation method and system, and relates to the technical field of oil and gas field development, and the method comprises the steps: carrying out a core waterflooding-CO2 flooding pore scale fluid characterization experiment based on a micro-nano core CT online scanning technology, and calculating CO2 burying efficiency ES; measuring a core oil-gas phase permeability curve and oil displacement efficiency ED, and judging whether a semi-logarithmic relation curve of kro / krg and Sg in the CO2 displacement stage meets a binomial change relation or not; obtaining target oil reservoir static parameters and production dynamic indexes, describing a gas-oil ratio and cumulative oil production change relation in a gas seeing stage, establishing a CO2 flooding characteristic curve, and performing data point fitting, oil reservoir recovery rate ER prediction and oil reservoir swept volume V calculation through a binomial expression; and calculating the reservoir-level CO2 burying amount VS according to the reservoir swept volume V and the CO2 burying efficiency ES. According to the method disclosed by the invention, the required data are few in types and high in availability, and the CO2 burying amount can be accurately calculated simply, conveniently and quickly only by the basic physical properties of crude oil and rock and the production dynamic data of an oil well.

The invention provides a cable insulation and outer sheath mechanical property detection device, method and equipment and a storage medium. The device comprises a stretching unit, a tracking detection unit and a data processing unit. The device utilizes a non-contact laser tracking ranging technology to accurately measure the displacement of the dumbbell sample in the stretching process, and errors of a traditional method are avoided. The tensile unit clamps the sample and applies tensile force to fracture, the data processing unit automatically collects tensile force and displacement data, and the tensile property of the cable outer sheath is rapidly and accurately evaluated. The device improves the detection efficiency and the result reliability, and provides powerful support for cable quality control.

The invention discloses a device and method for measuring the mechanical property of a thick oil-water interface by simulating oil reservoir conditions, and relates to the technical field of chemical cold production of thick oil, and the device comprises a thick oil injection module, a water injection module, a high-temperature and high-pressure bin module and a data acquisition and calculation and injection pump control module; the thick oil injection module is connected with the high-temperature and high-pressure bin module, and the thick oil injection module is configured to inject thick oil into the high-temperature and high-pressure bin module; the water injection module is connected with the high-temperature and high-pressure bin module and is configured to inject water into the high-temperature and high-pressure bin module; and the data acquisition calculation and injection pump control module is connected with the high-temperature and high-pressure bin module and the thick oil injection module, and is configured to acquire parameters such as temperature and pressure in a high-temperature and high-pressure cavity, obtain a hanging drop outline image in the high-temperature and high-pressure bin module and control the thick oil injection process in the thick oil injection module. The device solves the problem that most devices at present cannot measure the mechanical properties of the heavy oil-water interface under the real oil reservoir condition.

The invention discloses a blast hole parameter adaptive tunnel smooth surface effect prediction method, which comprises the steps of constructing a smooth surface effect prediction model based on a graph neural network; predicting rock mass displacement data by using the smooth surface effect prediction model; and calculating a tunnel smooth surface effect in combination with a prediction result of the rock mass displacement data. According to the method, the adaptive blast hole parameter smooth surface effect rapid prediction model based on the depth map neural network is constructed, smooth surface blasting data are comprehensively extracted by using the map neural network, the accuracy of a deep learning-based calculation method is improved, and the method has important theoretical significance and application value for tunnel blasting construction.

The invention discloses a multifunctional sensor of an FADS and a total temperature estimation method. The multifunctional sensor comprises a pressure sensor, an adapter, a temperature sensor and a heat flow sensor. The air entraining cover is arranged at the upper end of the base, and an inner cavity is formed between the air entraining cover and the base; a pressure measuring hole is formed in the outer surface of the air entraining cover and is communicated with the inner cavity; a T-shaped air guide hole is formed in the base; an air entraining channel is arranged in the adapter, and the upper end of the air entraining channel is connected with the lower end of the air entraining hole; the lower end of the air entraining channel is connected with an external air path and is used for transmitting pressure; the sensing ends of the temperature sensor and the heat flow sensor are located in the inner cavity and used for measuring the regional temperature in the inner cavity and measuring the heat flow of the pressure sensor. The device has a dustproof and anti-blocking structural design, and integrates the functions of measuring pressure, total temperature, heat flow and static temperature. The device is simple in structure, convenient to install and low in manufacturing cost, and can be applied to an embedded atmosphere data system of a high-speed aircraft.

The invention relates to a computer vision technology, in particular to a medical image processing technology based on deep learning and a medical diagnosis auxiliary method. The invention provides an airway stenosis automatic segmentation method, system and device based on a CT image, and the method specifically comprises the following technical means: 1) building an airway stenosis automatic segmentation model based on a marked training set and a verification set, so as to achieve the automatic recognition, positioning and segmentation of a narrow airway; (2) reasoning by using the established airway stenosis automatic segmentation model, and automatically identifying, positioning and segmenting a stenosis airway from an input CT (Computed Tomography) image; and 3) performing quantitative parameter measurement based on the narrow airway obtained by automatic segmentation. According to the automatic segmentation system and device for the airway stenosis, whether the airway stenosis exists in the CT image or not can be rapidly and accurately recognized, if yes, automatic positioning and segmentation of the stenosis can be achieved, and the system and device assist imaging departments or clinicians in rapidly and accurately diagnosing the narrow airway; meanwhile, based on the airway stenosis obtained through automatic segmentation, the stenosis range and the maximum, minimum and average lumen diameters of the stenosis part can be rapidly and accurately calculated, on one hand, the method can be used for evaluating the severity of the stenosis, and on the other hand, the method can be used for assisting clinical treatment.