1001results about "Material analysis using microwave means" patented technology

A system for material detection and identification includes an interface configured to access a material database associating each of a plurality of materials with a resonance frequency and one or more transmission parameters; an RF transmitter configured to, for each material of at least a subset of the plurality of materials in the material database transmit into an environment an RF signal the resonance frequency for the material using the one or more transmission parameters; an RF receiver configured to receive a response signal from the environment; and a processor configured to analyze the response signal for resonance characteristics that indicate a presence of the material and identify the material to a user if the presence of the material is indicated by the resonance characteristics.

The invention discloses a forest fire monitoring system based on satellite remote sensing, particularly relates to the field of forest fire monitoring, and is used for solving the problems of incomplete data coverage, inaccurate boundary recognition, difficulty in sheltered area restoration and the like in a forest fire monitoring process, and accurately capturing comprehensive coverage of a fire area through fusion of multi-source remote sensing data. And full space-time monitoring under complex weather and topographic conditions is realized. Dynamic changes of spectrums and vegetation before and after a fire disaster are continuously tracked, and continuous basic data are provided for evaluating the influence of the fire disaster. And in combination with the analysis of spectrum range and thermal signal propagation, the fine identification capability of a fire high-temperature area and an edge area is enhanced, and particularly, the boundary identification of a low-disturbance area is effectively optimized. According to the method, the space-time reconstruction and interpolation algorithm is adopted, data missing caused by smog and cloud shielding is comprehensively restored, the integrity and continuity of the image are ensured, and the accuracy of disaster assessment and decision support is improved.

A sensor as a service ecosystem is disclosed herein. In use, the system includes functionality for receiving first sensor data at a sensor as a service platform, where the first sensor data corresponds to a first capability level of a first sensor. The system also receives a selection of a sensor upgrade for the first sensor, and configures enhanced sensor capabilities for the sensor upgrade based on the selection. Further, the system sends a sensor update with the enhanced sensor capability from the sensor-as-a-service platform to the first sensor. Finally, the system receives second sensor data from the first sensor at the sensor as a service platform, where the second sensor data corresponds to a second capability level of the first sensor.

A method for material detection is described. The method may include extracting, from a material database, a resonance frequency for the target material. The method may further include comparing an application type to entries in a scan database. The scan database may store pre-defined scanning patterns and corresponding application types. The method may include extracting, from the scan database, a scan sequence for the application type. Also, the method may include instructing a gimbal to follow positions in the scan sequence. The method may also include transmitting into an environment an RF signal when the gimbal is at the positions in the scan sequence. The method may further include receiving a response signal from the environment. The method may include analyzing the response signal for resonance characteristics that indicate a presence of the target material. Additionally, the method may include generating a haptic feedback when the target material is detected.

A method includes accessing a material database associating each of a plurality of materials with one or more corresponding resonance frequencies; for each material of at least a subset of the plurality of materials in the material database: transmitting, via an RF transmitter, an RF signal into a target at a first resonance frequency for each material; receiving, via an RF receiver, a response signal from the target; and analyzing the response signal for resonance characteristics that indicate a presence of each material in the target; generating a report of each material in the target indicated by the resonance characteristics; and integrating the report with at least one of: a timestamp; image or video data from a camera; or geolocation data from a geolocation sensor.

A system for material detection and identification including: an RF transmitter configured for transmitting into an environment an RF signal at a first resonance frequency for a target material, wherein the first resonance frequency is obtained from a material database associating each of a plurality of materials with one or more corresponding resonance frequencies; an RF receiver configured for receiving a resultant response signal from the environment; and a processor configured for: analyzing the resultant response signal for resonance characteristics that indicate a presence of the target material, wherein analyzing includes, if the resonance characteristics are detected and no other material in the material database shares similar resonance characteristics for the first resonance frequency, reporting to a user that the target material has been identified.

The invention discloses an intelligent detection method for water pollutants, which comprises the following steps of: transmitting a signal of a specific frequency band to a water body through an electromagnetic wave transmitting module, acquiring reflected and refracted signals by using a multi-channel receiver, extracting the characteristics of dielectric constant, refractive index and the like of the water body, and analyzing the types and the concentration range of the pollutants by adopting a pattern recognition algorithm; the method comprises the following steps: selecting a micro-fluidic chip and an electrochemical unit, selecting a corresponding biosensor for targeted detection, processing detection data through the micro-fluidic chip and the electrochemical unit, predicting the concentration, spatial distribution and trend of pollutants through a data analysis module, setting a dynamic self-adaptive threshold by the system, realizing pollution early warning, and uploading data to a cloud platform through a remote communication module. And remote monitoring is supported. The method can be widely applied to the fields of water quality monitoring, environmental protection and pollution control, and the detection precision, the real-time performance and the intelligent level are improved.

The invention relates to the technical field of water quality pollution detection, in particular to a water quality pollution rapid detection method driven by a quantum sensing technology. A quantum sensor array is deployed in a water area to be detected, and quantum signal response data of the water area is collected; constructing a pollutant quantum recognition model, and inputting quantum signal response data into the model to obtain an initial predicted value of pollutant concentration; generating an initial detection parameter of the quantum detection instrument based on the initial predicted value, executing primary pollution detection by the instrument according to the parameter, and collecting primary deviation data of an actual detection value and an expected detection value; determining a detection error according to the deviation data, further correcting the initial detection parameter, and generating an optimized detection parameter; and finally, the instrument performs secondary pollution detection based on the optimized detection parameters. According to the method, complex water sample pretreatment is not needed, water quality pollution detection can be rapidly and accurately completed, detection requirements of different water areas are met, and the detection efficiency and accuracy are improved.

The invention relates to the technical field of fire coal control, and discloses a thermal power plant fly ash floating black online detection control method and system, and the method comprises the steps: 1, employing microwave, infrared and laser sensors for cooperative work, detecting carbon dielectric characteristics through microwave dust interference resistance, identifying thermal radiation difference through infrared, and analyzing particle distribution through laser; 2, on the basis of the detection requirements in the step 1, triple protection of air curtain barrier, ultrasonic cleaning and hydrophobic coating is designed, dust condensation is blocked, and it is ensured that the light transmittance of the sensor is larger than 90%; the invention provides a multi-mode sensing fusion-anti-interference current stabilization-closed loop optimization full-link solution for the industrial problem of signal distortion caused by optical window dew formation and dust deposition, airflow disturbance and environmental interference in fly ash floating black online detection. The light transmittance of the optical window is greater than 93% by combining triple protection of air curtain barrier, ultrasonic cavitation stripping and nano hydrophobic coating.

A method accessing a pre-trained specific material database associating each of a plurality of materials with a corresponding material profile, each material profile including one or more parameters including at least one of a transmit frequency and a response frequency; receiving a selection of a target material from a user; identifying first material profile associated with the target material using the pre-trained specific material database; transmitting, via an RF detection device, an RF signal into the target material using the one or more parameters for the target material associated with the first material profile; receiving, via the RF detection device, a response signal from the target material; analyzing the response signal using an AI algorithm to determine whether resonance characteristics of the response signal indicate a presence of the target material; and notifying the user if the presence of the target material is indicated by the resonance characteristics.

The invention relates to the technical field of geological disaster early warning, and discloses a geological disaster early warning device, which comprises an acoustic electromagnetic fusion sensor array for collecting multi-physical field data related to the internal structure change of a rock-soil body; the data pre-processing and feature extraction module is used for performing pre-processing and feature extraction on the original multi-physics field data so as to identify the change features of the internal structure of the rock-soil body; the multi-physics field collaborative inversion module reconstructs the internal structure distribution of the rock-soil body by adopting a multi-physics field collaborative inversion algorithm; the structure change cause analysis and risk assessment module is used for analyzing causes of internal structure change of the rock-soil body and assessing potential geological disaster risks; the grading early warning information generation module is used for generating targeted grading early warning information; according to the invention, high-precision monitoring of the internal structure change of the rock-soil body is realized through an acoustic electromagnetic fusion sensing technology, the monitoring precision is improved, and possible landslide or collapse events can be predicted in advance.

Globally our environment comprises structures built to perform a meet different requirements including residential, commercial, retail, recreational and service infrastructure. Whilst, millions of tons of construction materials are deployed annually the quality control procedures in many instances have not changed to reflect today's demands. Accordingly, it would be beneficial to provide construction companies, engineering companies, infrastructure owners, regulators, etc. with means to automated testing / characterization of construction materials during at least one of its manufacture, deployment in construction and subsequent infrastructure life. It would be further beneficial for such automated methods to exploit self-contained data acquisition / logging modules allowing them to be employed with ease at the different points in the life cycle of a construction material and / or construction project.

The invention relates to the technical field of recycled asphalt mixture recovery, in particular to a mixing uniformity monitoring method adaptive to a recycled asphalt mixture, which comprises the following steps: S101, performing time-space fusion on infrared thermal radiation field dynamic capture and microwave dielectric property synchronous monitoring bimodal sensing to jointly perform mixing defect alarm; s102, based on the dynamic sequence of the infrared thermal radiation field, judging the particle motion consistency through the standard deviation of the motion direction angle, integrating the infrared temperature field and microwave dielectric data, constructing a three-dimensional feature vector, comprehensively evaluating the uniformity through a weighting function, judging defects according to the maximum contribution term, and generating an optimization instruction; and S103, setting a grading standard based on the multi-modal features, and feeding back and adjusting the process according to a grading result. According to the invention, infrared thermal radiation and microwave dielectric characteristics are combined, temperature uniformity and material component distribution are evaluated synchronously, and the problem of monitoring that the thermal uniformity of the recycled asphalt is not equal to the component uniformity is solved.

A system for material detection and identification includes an interface configured to access a material database associating each of a plurality of materials with a resonance frequency and one or more transmission parameters; an RF transmitter configured to, for each material of at least a subset of the plurality of materials in the material database transmit into an environment an RF signal the resonance frequency for the material using the one or more transmission parameters; an RF receiver configured to receive a response signal from the environment; and a processor configured to analyze the response signal for resonance characteristics that indicate a presence of the material and identify the material to a user if the presence of the material is indicated by the resonance characteristics.

A method includes detecting interaction by a user with an entry detector; collecting credentials from the user; and, if the credentials indicate that the user is authorized to enter, accessing a material database associating each of a set of materials with one or more corresponding resonance frequencies; and for each material of the set of materials: transmitting, into an environment associated with the user, an RF signal at a first resonance frequency for a material of the set of materials; receiving a response signal from the environment; analyzing the response signal from the environment for resonance characteristics that indicate a presence of the material; and in response to the presence of the material being indicated: determining whether an action is required for the material; and if the action is required for the material, actuating an access apparatus to perform the action.

A method for material detection may include extracting, from a material database, a resonance frequency for the target material. The method may further include comparing an application type to entries in a scan database. The scan database may store pre-defined scanning patterns and corresponding application types. The method may include extracting, from the scan database, a scan sequence for the application type. Also, the method may include instructing a gimbal to follow positions in the scan sequence. The method may also include transmitting into an environment an RF signal when the gimbal is at the positions in the scan sequence. The method may further include receiving a response signal from the environment. The method may include generating a haptic feedback to indicate a directionality or a proximity to the target material. The method may include analyzing the response signal for resonance characteristics that indicate a presence of the target material.

A system for currency verification includes a currency apparatus configured for receiving alleged currency to be verified; at least one processor; a non-transitory computer-readable medium configured for storing instructions that, when executed by the at least one processor, perform a method comprising: accessing a material database associating each of a set of materials found in authentic currency with one or more corresponding resonance frequencies; for each material of the set of materials: transmitting into the alleged currency an RF signal at a first resonance frequency for each material; receiving a response signal from the alleged currency; and analyzing the response signal for resonance characteristics that indicate a presence of each material; and a display device configured for outputting that the alleged currency is authentic if the presence of at least a subset of the set of materials found in the authentic currency is indicated.

A system for material detection and identification including: an RF transmitter configured for transmitting into an environment an RF signal at a first resonance frequency for a target material, wherein the first resonance frequency is obtained from a material database associating each of a plurality of materials with one or more corresponding resonance frequencies; an RF receiver configured for receiving a resultant response signal from the environment; and a processor configured for: analyzing the resultant response signal for resonance characteristics that indicate a presence of the target material, wherein analyzing includes, if the resonance characteristics are detected and no other material in the material database shares similar resonance characteristics for the first resonance frequency, reporting to a user that the target material has been identified.

The invention discloses a visibility inversion method based on millimeter wave cloud radar and laser radar data fusion, and relates to the technical field of meteorology, and the method comprises the steps: guiding a millimeter wave cloud radar and a laser radar to carry out data correction and equivalent relation construction through employing a fog drop particle size distribution function measured by a fog drop spectrometer in a sample scene in advance; and then applying the correction coefficient and the equivalent function relationship to a target scene to perform multi-source data correction and fusion on the millimeter wave cloud radar and the laser radar and invert visibility. The method can fuse complementary advantages of the laser radar and the millimeter wave cloud radar; the introduction of the fogdrop particle size distribution function effectively avoids the distribution hypothesis of fogdrop shapes in the traditional model, can weaken the seasonal drift of the traditional empirical coefficient, significantly improves the accuracy and reliability of visibility inversion, and achieves the high-precision visibility monitoring under various weather conditions from clear sky to dense fog.

A method accessing a pre-trained specific material database associating each of a plurality of materials with a corresponding material profile, each material profile including one or more parameters including at least one of a transmit frequency and a response frequency; receiving a selection of a target material from a user; identifying first material profile associated with the target material using the pre-trained specific material database; transmitting, via an RF detection device, an RF signal into the target material using the one or more parameters for the target material associated with the first material profile; receiving, via the RF detection device, a response signal from the target material; analyzing the response signal using an AI algorithm to determine whether resonance characteristics of the response signal indicate a presence of the target material; and notifying the user if the presence of the target material is indicated by the resonance characteristics.

Aspects of the disclosure are directed to prediction of a predicted material profile of the target object based on measurement information associated with sensing (RF-S) signal(s). In an aspect, one or more actions are performed in response to the predicted material profile of the target object, the one or more actions including, e.g., constructing at least one digital twin associated with the target object based on the predicted material profile of the target object, or modifying operation of a wireless communications network, or a combination thereof. Such aspects may provide various technical advantages, such as more accurate digital twin generation (e.g., digital twins may be updated to reflected material profiles of objects detected in real-world), improved network operation (e.g., permit line of sight (LOS) through objects with certain material profiles, block LOS through objects with other material profiles, etc.), and so on.

The CSRR-based quarter substrate integrated waveguide sensor comprises a dielectric substrate, a square ring metal layer is arranged on the upper surface of the dielectric substrate, a lower metal layer is arranged on the lower surface of the dielectric substrate, and a row of metal holes are uniformly distributed in the circumferential direction of the square ring metal layer; the upper surface of the dielectric substrate is also provided with four triangular metal patches with different sizes, and each edge of the square ring metal layer is connected with one triangular metal patch; two concentric annular CSRRs are etched on the vertex angle, far away from the square ring metal layer, of the triangular metal patch. The sensor is novel in design, four mutually independent poles are generated, simultaneous multiband operation is realized, efficiency is improved, errors and loss are reduced, the size of the sensor is reduced by about 75% by adopting the QMSIW, and the sensor has the advantages of being small in size, easy to integrate, high in flexibility, low in loss and high in sensitivity.

A system (100) for detecting the onset of surface melting on Antarctic sea ice, wherein the system (100) comprises: a scatterometer (102) for acquiring backscatter coefficient (σ0) data at Ku-band frequency from dual-polarized scatterometers, including horizontal (HH) and vertical (VV) polarization, and is configured to generate scatterometer image reconstruction images (SIR) for noise reduction; a passive microwave radiometer (104) connected to the scatterometer (102) and configured to detect the sea ice concentration (SIC) and brightness temperatures (Tb19H, Tb37H) at different polarizations and frequencies for surface melt detection; a data interpolation unit (106) connected to the scattering meter (102) and the passive microwave radiometer (104) and configured to fill data gaps in the scattering meter and radiometer data using multiple regression and median filtering; a processing unit (108) connected to the data interpolation unit (106), which is configured to determine the onset of melting based on changes in the patterns of the backscattering coefficient during the summer melt season; an atmospheric data unit (110) configured to retrieve surface air temperature, latent and sensible surface heat flux, net shortwave and longwave radiation, and net heat flux from reanalysis data sources; a unit (112) for verifying the onset of melting, configured to confirm the onset of melting by analyzing atmospheric data and comparing the derived SIC values ​​and brightness temperature fluctuations with the pre-thresholds of -10 K for the presence of liquid water in the snowpack; a motion tracking unit (114) configured to determine sea ice motion by tracking features such as floes using successive satellite imagery and weekly sea ice motion vectors; and a controller (116) configured to process and synchronize inputs from the scattering meter (102), radiometer (104) and atmospheric data unit (110) to detect and confirm the onset of surface melting across different spatial and temporal scales.

The invention discloses a microwave sensor for measuring liquid, which comprises a microwave circuit and a liquid container, and is characterized in that the microwave circuit comprises a dielectric substrate, and a top layer metal and a bottom layer metal which are arranged on two side surfaces of the dielectric substrate; the top layer metal comprises a 50-ohm microstrip line used for feeding and a resonator used for generating a transmission zero point and a transmission pole point, and the resonator and the 50-ohm microstrip line form a coupling structure. The invention further discloses a measuring method of the microwave sensor for measuring the liquid. According to the invention, the detection process of the microwave sensor is simpler and more efficient, the microwave sensor is convenient to carry and operate, and the manufacturing and measuring cost of the microwave sensor can be further reduced. Besides, when the sensor is used for testing, liquid quantitative control is facilitated, instrument calibration only needs to be carried out once, system errors can be reduced to a great extent in cooperation with a pseudo-differential scheme during data processing, and the sensor has high robustness.

The invention discloses a post-raining side slope seepage characteristic testing method based on waveform inversion of nano-iron concentration distribution, and belongs to the field of seepage characteristic determination in foundation pit side slope stability monitoring, the method comprises the following steps: spraying a mixture of nano-iron particles and a surfactant into cumulonimbus to make nano-iron permeate into a side slope soil body along with rainfall; a radio frequency coil is arranged in the orthogonal direction of the selected section of the slope, an electromagnetic field is applied to excite nano iron resonance, and electromagnetic wave signals are collected; dividing the selected section of the slope into a plurality of grid units, and inverting the concentration distribution of the nano-iron in each grid unit by using an iterative optimization algorithm based on the electromagnetic wave signal to obtain an inversion result; and generating a seepage cloud picture based on the inversion result and calculating the seepage speed. According to the method, economic loss caused by large-area laying of nano-iron and interference to follow-up monitoring are avoided, the seepage position and size are determined, and complete and clear information is provided for monitoring seepage changes in slope engineering.

The present application relates to a kind of method and device for judging the trend of concrete oblique crack tip, fill metal powder in the crack to be measured;Determine the beginning and end point of crack trend according to the opening trend of crack surface to be measured, draw the center line of the connecting line of beginning and end point as the first measuring line, respectively from the two end points of the first measuring line along the first measuring line to crack opening position detection using electromagnetic wave radar detector, record the position and depth of the first fluctuation point on radar development map;With the first measuring line as reference line, rotate to make several new measuring lines, obtain the position and depth of the first fluctuation point of each new measuring line;Fluctuation point is sorted according to measuring line sequence, draw the connecting line diagram, i.e. the trend curve of oblique crack tip.The present application is based on the essential characteristics such as the height and form of oblique crack tip position, combined with the measurement mode from far to near, multi-angle, multiple measuring points and the reflection law of radar wave by metal powder, the position and depth of multiple points of concrete oblique crack tip are measured, and then the trend of crack tip is effectively judged.

The invention provides an online monitoring method for a curing process of a resin-based composite material, and belongs to the technical field of curing monitoring of composite materials. In the curing process of the resin-based composite material, a conductive patch is placed on the surface of the resin-based composite material to form a laminated structure consisting of the conductive patch, a dielectric layer containing resin and a high-reflection substrate, and the curing process of the resin-based composite material is deduced in real time by using a microwave signal to radiate the laminated structure and monitoring peak valley characteristics and temperature changes of a reflection signal. According to the method, a microwave signal is utilized to irradiate a laminated structure, and the curing process of the resin-based composite material is judged by monitoring the peak valley characteristics and temperature change of a reflected signal in real time. The in-situ online curing process monitoring method based on the microwave signal and the conductive patch film sensor not only can realize real-time online monitoring of the resin curing key point and the curing degree, but also has the remarkable advantages of being capable of adjusting the monitoring position in real time, realizing curing degree field monitoring and the like.

An antenna for high-frequency based measuring devices for determining a dielectric value of media is based on a high-frequency waveguide. The high-frequency signal is coupled in or out via a coaxial conductor that runs orthogonally through the axis of the high-frequency waveguide for this purpose. The conductor termination for the coaxial conductor extends extensively beyond the high-frequency waveguide in such a way that the coaxial conductor forms a defined capacitance in this region. In this way, the coaxial conductor is optimally matched to the high-frequency waveguide without having to integrate additional electrical components for this purpose.

This disclosure relates to an AI-driven, non-invasive system configured to analyze whiskey color and maturation outcomes based on sensor-tracked environmental and chemical variables through integrated machine-learning, high-accuracy volume sensing, dielectric-based proof monitoring, and environmental data analysis to forecast how whiskey will age inside a barrel over time, and by leveraging real-time barrel data such as time, proof, volume, temperature, humidity, and evaporation rates, the AI model can accurately analyze the final color, proof, and optimal aging duration for whiskey and other barrel-aged spirits, which can allow distilleries to reduce inconsistencies, improve yield management, and enhance quality control without relying on manual sampling or invasive testing.

The invention relates to a method, a device, equipment and a medium for measuring the alcoholic strength of base liquor in a winery, and relates to the field of alcohol measurement. The method comprises the following steps: according to the initial signal intensity of an electromagnetic wave emission signal, the attenuation value of the electromagnetic wave emission signal under a preset wine jar ceramic thickness, the electromagnetic wave attenuation coefficient of the electromagnetic wave emission signal in to-be-detected base wine and the propagation path length of the electromagnetic wave emission signal in the to-be-detected base wine, determining the initial signal intensity of the electromagnetic wave emission signal; calculating and determining the receiving signal intensity of the electromagnetic wave receiving signal; calculating and determining the signal characteristics of the electromagnetic wave receiving signal according to the receiving signal strength of the electromagnetic wave receiving signal by adopting a Hilbert-Huang transform algorithm; and adopting the signal characteristics of the first electromagnetic wave receiving signal, the signal characteristics of the second electromagnetic wave receiving signal and the first ratio as training samples to train an alcoholic strength detection model so as to predict the alcoholic strength of the to-be-detected base wine in the ceramic wine jar. According to the method, the base liquor loss in alcoholic strength measurement can be remarkably reduced, and potential safety hazards are eliminated.