794results about "Material analysis using microwave means" patented technology

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 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.

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.

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.

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.

Herein disclosed is estimating alcohol content within a barrel based on a determination of a loss of fluid within the barrel. The loss of fluid may be determined by a measurement from outside the barrel. An implementation may comprise receiving information regarding an initial state of a liquid in a container, the initial state comprising at least one of an alcohol measure and a level of the liquid within the container, monitoring a level of the liquid within the container, wherein the monitoring is performed external to the container, determining an amount of loss of the liquid within the container based on the initial level and the monitored level, and estimating the alcohol measure of liquid remaining within the container based on the determined amount of loss of the liquid. An implementation may advantageously estimate alcohol content without affecting the internal ecosystem or contents of the barrel, improving product quality.

The invention discloses an electrolytic capacitor testing method and system, and particularly relates to the technical field of electrolytic capacitor testing, and the method comprises the steps: obtaining a time-frequency domain coupling waveform of electrolytic capacitor testing, and constructing an anti-interference reference feature library covering a process fluctuation interval based on a correlation function of an electrolyte dynamic impedance spectrum and an ultrasonic speed; based on a physical equation of electrolyte evaporation and polar plate corrosion, a topological structure updating rule of a graph neural network and a physically constrained graph topological structure are dynamically generated; the method comprises the following steps: extracting defect sensitive frequency band characteristics of a cross-modal signal through a differentiable frequency band selection network, extracting multi-scale fusion characteristics from a time-frequency domain coupling waveform based on the defect sensitive frequency band characteristics, inputting the multi-scale fusion characteristics into an edge keeping regularization layer, and adaptively adjusting reconstruction parameters according to the confidence coefficient of a defect gradient field so as to obtain an edge keeping regularization layer; and a three-dimensional defect form meeting the continuity constraint is generated, so that the problem of low detection precision of the internal defect of the electrolytic capacitor is solved.

The invention discloses a working temperature control method of a Josephson probe and a method for regulating and controlling the thickness of an Nb film, the working temperature of the Nb-based probe is increased to 7.2 K by regulating and controlling the film thickness parameter and controlling the working temperature of the probe, and the highest record of similar probes is created. According to the method for regulating and controlling the thickness of the Nb film, a four-groove quartz tube is selected as a substrate, and after ultrasonic cleaning, a nano needle tip is drawn by adopting a laser heating method, so that a needle tip structure with a clean surface and a controllable geometric structure is obtained; and horizontally fixing the prepared nano needle tip on a probe bracket, depositing a niobium film by adopting a magnetron sputtering process, and controlling the thickness of the Nb film to prepare the Josephson probe. According to the invention, the dependence of the probe on an extremely low temperature environment is obviously reduced, the limitation of the original process is broken, the available film thickness range is effectively widened, the preparation yield and the performance consistency of the probe are obviously improved, and a reliable device basis is provided for the practical development of near-field microwave imaging and quantum sensing technologies.

The invention relates to the technical field of soil change characteristic analysis, in particular to a soil pH spatial-temporal change characteristic analysis method which comprises the following steps: scanning a target area through a vehicle-mounted microwave radar to obtain a soil dielectric constant distribution diagram, and identifying a jump critical point of which a dielectric constant gradient value is greater than a gradient threshold value; s2, taking the jump critical point of S1 as a center, laying sampling clusters in a preset radius range, detecting the soil colloid content and the actually measured pH value, correcting the pH values of multiple points in each sampling cluster, performing difference judgment, and marking a jump confirmation cluster based on a judgment result; taking the jump confirmation cluster as a spatial interpolation breakpoint, performing partition independent interpolation based on the actually measured pH value, and generating a soil pH spatial-temporal change map with a jump boundary; according to the method, the buffer zones are arranged on the two sides of the breakpoint, and the enhancement correction model based on dielectric gradient driving is introduced, so that a clear and visible abrupt change boundary zone is successfully formed in the atlas, and the expression of color gradation sharpening of the abrupt change area is realized.

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.

The invention provides a sea surface oil spill monitoring system based on a GNSS-R receiver. The sea surface oil spill monitoring system comprises an unmanned aerial vehicle platform, the GNSS-R receiver, a signal processing module, an oil spill feature extraction module, a data storage and transmission module and a ground station data processing module, wherein the GNSS-R receiver, the signal processing module, the oil spill feature extraction module and the data storage and transmission module are installed on the unmanned aerial vehicle platform and connected in sequence. According to the system, the GNSS-R receiver acquires the GNSS scattering signals on the surface of the ocean by acquiring the reduced polarization, the requirements of independent inversion and application of parameter inversion of typical disasters of the ocean can be effectively met, the GNSS-R receiver supports multi-band and multi-polarization GNSS scattering signal receiving, the oil spill detection precision and reliability are improved, and the reliability of the system is improved. And high-precision oil spill detection can be realized under complex meteorological conditions.

The invention belongs to the technical field of near-field imaging, and particularly relates to a microwave and millimeter wave near-field subsurface microscopic imaging device and method based on signal interference, and the device comprises a vector network analyzer, a signal separation device, a phase adjustment device, a semi-steel coaxial line, a displacement platform, and an industrial control computer. The vector network analyzer comprises a signal separation unit, a frequency synthesis source, a first receiver and a second receiver, wherein the frequency synthesis source, the first receiver and the second receiver are respectively connected with the signal separation unit and used for generating microwave and millimeter wave test signals. The signal separation device is respectively connected with the vector network analyzer, the phase adjusting device and the semi-steel coaxial line, and the displacement table is connected with the vector network analyzer through the industrial personal computer; the tail end of the semi-steel coaxial line, which is far away from the signal separation device, is provided with a conical needle tip-shaped near-field probe; and the needle tip of the near-field probe is vertical to the surface of a to-be-detected sample arranged on the displacement table.

The invention discloses a two-phase cold plate liquid cooling dryness real-time measurement method and system based on data fusion, and relates to the technical field of liquid cooling data processing, and the method comprises the following steps: S1, collecting multi-mode liquid cooling working condition data in real time, carrying out the data preprocessing, carrying out the fusion of original dryness according to three types of dryness signals, and evaluating the health degree of signal fusion; s2, dynamically distributing adaptive signal weights for each type of dryness signals to obtain high-precision fusion dryness, and performing anomaly diagnosis; s3, the high-precision fusion dryness is optimized, flow adjustment is carried out, meanwhile, dead zone compensation of flow adjustment is carried out, and flow compensation correction is carried out; and S4, monitoring a flow regulation process and abnormal information in real time, and performing high-precision visual feedback and operation and maintenance optimization of the fusion dryness. The problems that an existing two-phase cold plate liquid cooling system generally adopts a single dryness detection mode and is prone to being interfered by the environment and lagging in response, so that the dryness measurement precision is insufficient, and the reliability and the heat dissipation efficiency of cooling capacity adjustment are affected are solved.