36results about "Moisture content investigation using microwaves" patented technology

This invention relates to the field of coal quality testing technology, specifically to an online method and system for detecting coal quality entering the furnace; it includes: a multimodal data acquisition step: acquiring microwave scattering parameters and surface element characteristic spectra using a microwave tomography sensor array and a surface spectrometer, respectively; a physical field inversion and modeling step: reconstructing the complex permittivity distribution map based on the scattering parameters to establish a three-dimensional physical distribution model including density and moisture; a field-spectrum coupling deduction step: using the characteristic spectra as boundary constraints, and combining them with the complex permittivity distribution map to deduce the internal chemical element distribution; and a volume-weighted quantization step: performing volume-weighted integration on the three-dimensional physical model and chemical distribution to output comprehensive coal quality parameters; this invention eliminates the detection blind spots of single technologies and significantly improves the representativeness and safety of full-section detection of coal entering the furnace.

The application provides a microwave online moisture detection device and method of a temperature and humidity control drying equipment, which comprises a temperature and humidity control drying equipment, a microwave online moisture detection system, a range finder device and a central control system, the microwave system is provided with an antenna guide rail platform capable of realizing XYZ three-axis movement and a symmetrical reference measurement microwave antenna, and the range finder is provided with a multilayer heat insulation protection structure; the method receives material signals through the microwave antenna, combines thickness measurement of the range finder and environment humidity detection of the reference antenna, calculates real moisture values through a thickness-humidity double compensation algorithm of linear interpolation or polynomial fitting, and finally displays and stores data by the central control system. The application realizes real-time, nondestructive and continuous detection of material moisture, has multi-point scanning capacity, is suitable for high-temperature drying conditions, greatly improves detection precision, and provides technical support for quality control and energy saving and consumption reduction of drying processes in the fields of pharmacy, food and the like.

This invention discloses a system and method for testing the collapsibility coefficient of undisturbed loess. The system includes a constant-force jacking device, a humidification and maintenance device, and a collapsibility coefficient determination device. The constant-force jacking device is installed at the annular soil mass within the test hole to apply a constant horizontal jacking force to the annular soil mass. The humidification and maintenance device covers the outside of the annular soil mass to gradually humidify it and obtain its moisture content. The collapsibility coefficient determination device is connected to the constant-force jacking device and the humidification and maintenance device to determine the collapsibility coefficient or self-weight collapsibility coefficient of the annular soil mass at different moisture contents based on the jacking distance of the constant-force jacking device. This invention utilizes undisturbed annular loess in the field, eliminating the need for sampling and indoor testing to obtain the collapsibility coefficient or self-weight collapsibility coefficient. It preserves the original structure of the loess, resulting in more accurate collapsibility test results that meet the needs of engineering design and disaster management.

In one embodiment, an electromagnetic imaging method, comprising: determining electromagnetic resonance data based on interrogating a stored commodity; and estimating features of the stored commodity based on the electromagnetic resonance data.

The present application relates to the technical field of agricultural drought information monitoring, and more particularly to an agricultural drought monitoring and prediction system based on unmanned aerial vehicle microwave remote sensing and deep learning, which comprises: a microwave remote sensing data fusion subsystem that carries multi-frequency microwave sensors on an unmanned aerial vehicle; dynamic adjustment of feature weights based on crop growth stages; elimination of geometric deviations between unmanned aerial vehicle flight strips through time series registration, and construction of a three-dimensional drought feature field by fusing multi-temporal data; a deep drought diagnosis subsystem that inputs the three-dimensional drought feature field into a space-time convolution network, extracts field patch-level anomalies in the spatial domain, and captures drought evolution patterns in the time domain; a drought response subsystem that divides drought levels based on the diagnosis results of the space-time convolution network; generation of differentiated irrigation schemes in combination with farmland Internet of Things data; and comparison of actual irrigation effects with prediction results. The present application realizes an upgrade of the agricultural drought prevention and control mode from passive monitoring to active prediction, and from extensive management to precise regulation.

The present application relates to a kind of experimental device for studying the influencing factor of water transport rate of sandstone surrounding rock, the experimental device includes base, multifunctional container, three microwave moisture sensors, three micro-pressure transmitters, high-density electrical instrument and data collector.Multifunctional container is equipped with cover and base fence;The front end of base fence is equipped with sample support vertical plate, and the front of sample support vertical plate is equipped with sensor fixed column;Multifunctional container is square hole, and square hole is equipped with sealing buckle;Sealing buckle is inserted with rock sample in contact with square hole;Rock sample is equipped with three sensor layout ports, and is sleeved with three electrode fixed frame, and electrode fixed frame is equipped with copper screw with electrode line;Electrode line is connected with high-density electrical instrument;Three micro-pressure transmitters are in contact with rock sample;Rock sample is uniformly distributed with a plurality of platinum resistance on one side.At the same time, the present application also discloses test method.The present application can realize the influence degree of water transport rate in rock sample under the action of different factors.

The invention relates to a building material device (1), which has at least one building material transport section (2) following a building material drum (3), which is configured to transport a building material (BS) to be at least partially hardened, and at least one part sensor (5) arranged in and / or in the building material transport section (2) and configured such that the at least part sensor (5) detects at least one intensive variable (IG) of the building material (BS) in the building material transport section (2) or at least one variable corresponding to an intensive variable.

The application discloses a kind of railway bed moisture content quantitative detection methods based on low high-frequency energy ratio, comprising: setting multiple transverse detection channels to collect ground penetrating radar signal;The radar signal of each transverse detection channel is continuously wavelet transformed, and the frequency axis in the time-frequency transform result is divided into low frequency band and high frequency band according to preset boundary frequency, and the low high-frequency energy ratio is calculated;The low high-frequency energy ratio mean of each transverse detection channel is calculated in each test area, and the low high-frequency energy ratio mean of multiple transverse detection channels in multiple test areas forms joint sample;According to joint sample, regression model for representing the nonlinear mapping relationship between water content severity index and low high-frequency energy ratio is constructed;The digital determination threshold of different water content grades is calculated according to regression model using interclass geometric midpoint method, establishes bed moisture state grading standard, and outputs moisture state grade.The application can realize accurate quantitative detection and grading of railway bed moisture content.

This invention discloses a method and apparatus for online monitoring of moisture content in insulating oil of substation oil-filled equipment, relating to the field of power equipment condition monitoring technology. The method involves extracting insulating oil from the lower part of the oil-filled equipment, removing particulate impurities, and then diverting it via a four-way valve to three measurement units—microwave resonance, capacitive sensing, and infrared spectroscopy—to simultaneously detect moisture content. The detected insulating oil is then dehumidified and returned to the equipment. The control unit analyzes the three measurement results and automatically triggers a three-level treatment mode based on the moisture content, dynamically adjusting the output of the oil pump and dehydration unit. It also analyzes the source of moisture based on multi-dimensional parameters such as oil temperature, load, and ambient humidity. Simultaneously, the apparatus uses a mixed adsorbent of molecular sieve and activated alumina, along with a polyimide hollow fiber membrane, to reduce the moisture content of the insulating oil to below 5 ppm and 3 ppm, respectively. This invention achieves real-time online monitoring, intelligent diagnosis, and closed-loop automatic processing of insulating oil moisture, improving the equipment's insulation performance and operational reliability.

This invention discloses a method and system for continuous monitoring of vegetation optical thickness and canopy moisture based on transmission signals from a Global Navigation Satellite System (GNSS). By deploying GNSS receiving modules above and below the vegetation canopy, GNSS signals from both modules are simultaneously acquired. Vegetation optical thickness is inverted, and multi-satellite data is fused. The fused time series is decomposed into low-frequency structural components and high-frequency dynamic components. The high-frequency dynamic components are then separated into plant internal water, canopy water retention, and residual noise, thus decoupling vegetation structural changes from short-term moisture dynamics and enabling monitoring of canopy moisture content and its dynamic changes. This method offers advantages such as non-destructive operation, high temporal resolution, and automated continuous monitoring, and can be widely applied to the continuous monitoring of vegetation structure and moisture status in forests and farmland.

Described is an electrical power distribution and monitoring system utilizing electrical heat tracing equipment for purposes of fault detection and maintenance forecasting, the system is intended to replace or augment an existing Electric Heat Trace Distribution Panel, and comprises components for testing, measuring, recording, and displaying a variety of sensors, parameters and components, and to forecast failures and required maintenance in electrical heat trace equipment

This invention discloses a soil volumetric water content (VWC) measurement system based on LoRa-RSSI and a drone. The system comprises several underground LoRa nodes for collecting environmental monitoring data; a host computer embedded in the soil; and an aerial node carried by a small drone. Combining IoUT technology, this invention designs an innovative system for soil VWC measurement based on LoRa received signal strength and a drone. The system utilizes the changes in LoRa-RSSI between the soil's internal transmitter and the drone's aerial receiver during the drone's angular rotation. Combined with a Long Short-Term Memory (LSTM) network, it collects differential LoRa-RSSI values ​​and uses a deep learning (DL) algorithm to calculate soil VWC, achieving relatively accurate soil VWC data. This invention eliminates the need for depth measurement of VWC data, utilizes soft sensors to measure soil VWC, and offers low cost, high efficiency, and small measurement error, providing a novel approach for soil VWC measurement design.

This invention discloses a real-time detection method for the moisture content of fine aggregates in concrete production, belonging to the field of fine aggregate moisture content detection. The method includes: acquiring several sand samples with different moisture contents for different fine aggregates; extracting stable feature values ​​of the signal from the original signal sequence acquired by a microwave moisture content sensor for each sand sample using the sliding window density peak method; calculating the average thickness, average flow velocity, and average temperature; constructing a first prediction model based on an enhanced multiple regression model; constructing a second prediction model based on a tree model; determining the optimal moisture content prediction model from the first and second prediction models; and in concrete production, acquiring the stable feature values, thickness, flow velocity, and temperature of the signal in real time, and calling the optimal moisture content prediction model for the corresponding fine aggregate to predict the moisture content. This invention solves the problem of measurement inaccuracy caused by random fluctuations in the original signal and variable material flow conditions when using microwave methods to detect the moisture content of sand and gravel online.

This invention discloses a device for in-situ monitoring of temperature and moisture changes in a soil profile, belonging to the field of soil testing technology. It includes a base body, a temperature sensing component, and a moisture detection component. The base body includes a first substrate parallel to the soil profile. The temperature sensing component includes multiple temperature sensing needles and insertion holes on the first substrate. The insertion holes are arranged in a "T" shape, with the lower insertion holes arranged vertically. The temperature sensing needles are inserted into the soil through the insertion holes to measure the temperature at different depths. The moisture detection component includes moisture probes for measuring soil moisture content. At least two moisture probes are located on one side of the first substrate, arranged vertically at intervals. This invention enables precise positioning and matching of the temperature sensing needles and the moisture probes using the insertion holes and connecting ropes.

The present application relates to the global navigation satellite system remote sensing technical field, disclose a kind of farmland soil moisture content inversion method based on multi-satellite dual-frequency GNSS signal intensity, including obtaining the frequency point observation data satisfying preset condition, extract original signal-to-noise ratio parameter and convert into signal intensity sequence, separate out multipath interference signal sequence;Least square method is used to extract single-frequency delay phase, calculate error index and calculate adaptive weight accordingly, obtain dual-frequency fusion delay phase by weighted summation;Calculate normalized microwave reflectance index, with dual-frequency fusion delay phase to form multidimensional input feature vector;Establish nonlinear inversion prediction model, adopt non-stationary random bayesian optimization algorithm to optimize hyperparameter, input multidimensional input feature vector and output soil moisture content prediction value.By dynamically allocating multi-frequency weight and compensating vegetation attenuation, combined with optimization algorithm, the generalization ability and inversion precision of the model are improved.

The invention relates to a method for measuring an internal quality of a fruit wherein use is made of a microwave measuring system. The invention further relates to a microwave measuring system for measuring an internal quality of a fruit. The method of the invention is an improved method because it allows to determine an internal quality of a fruit with a higher dynamic range. The method relies on measuring a complex reflection coefficient, and using this reflection coefficient as input in a regression model, within the Fraunhofer distance of the antenna.

The application discloses a high-precision small-interval soil wetting front monitoring system and relates to the technical field of soil moisture monitoring.The system comprises a plurality of high-resolution FDR or TDR moisture sensors, a laying mechanism and the like.The high-resolution FDR or TDR moisture sensors adopt a short-size probe structure and are suitable for small-interval laying scenes.The laying mechanism adopts a flexible support or a stepped module structure and can adapt to complex environments of different terrains and soil conditions.Meanwhile, each component module has good anti-interference capability and can be long-term stably operated in a harsh natural environment, thereby meeting the demand of long-term soil moisture monitoring of slope stability analysis, water and soil conservation and ecological restoration and the like in various complex environments.

The present application belongs to the technical field of satellite meteorological monitoring, and particularly relates to a water vapor real-time tomography monitoring system based on the signal attenuation characteristics of Beidou satellites, which comprises four modules of data acquisition, feature calculation, model construction and inversion warning. The data acquisition module is used for collecting meteorological parameters of a monitoring area and statistical variance of Beidou satellite signals. The feature calculation module is used for calculating thermal anomaly values and signal purity rights. The model construction module is used for obtaining dynamic projection coefficients and constructing a tomography observation equation set. The inversion warning module is used for iteratively solving the tomography observation equation set to obtain grid water vapor density, and outputting a warning when the grid water vapor density is out of limit and the thermal anomaly value is continuously high. The present application combines thermal features and signal quality constraints, and improves the water vapor inversion accuracy and warning reliability.

To provide a technique that enables highly accurate and stable moisture measurement without performing measurement of bulk density or layer thickness when performing moisture measurement by using a microwave for a measurement object conveyed on a conveyor.SOLUTION: A moisture measurement method for measuring the moisture of a measurement object conveyed on a conveyor includes: a conveyance amount measurement step of measuring a conveyance weight per unit time of the measurement object conveyed on the conveyor; a microwave transmission step of transmitting a microwave toward the measurement object as a transmission wave; a microwave reception step of receiving the microwave which has been transmitted in the microwave transmission step and has passed through the measurement object as a reception wave; a microwave change amount calculation step of calculating a change amount by comparing the transmission wave and the reception wave; and a moisture content calculation step of calculating a moisture content of the measurement object on the basis of the change amount calculated in the microwave change amount calculation step and the conveyance weight per unit time of the measurement object measured in the conveyance amount measurement step.SELECTED DRAWING: Figure 2

The application discloses a vegetation scattering albedo spatiotemporal dynamic parameterization method and system in a tau-omega model, wherein the method comprises the following steps: obtaining passive microwave original observation data and auxiliary data, performing data preprocessing and generating corresponding observation reference data; screening effective pixels based on the observation reference data; calculating the corresponding vegetation scattering albedo of each effective pixel on a daily scale to generate a corresponding pixel daily scale sequence; generating a multi-class spatiotemporal dynamic parameter mapping model based on the pixel daily scale sequence; determining an optimal dynamic parameter mapping model from each class of spatiotemporal dynamic parameter mapping model to obtain a target mapping model; and based on the optimal dynamic parameter mapping model, carrying out inversion result evaluation, gain quantification and product output. The application realizes mechanism spatiotemporal dynamic characterization of the vegetation scattering albedo, effectively suppresses system errors caused by static assignment, simultaneously improves microwave SM and VOD inversion accuracy, and optimizes the product to provide high-quality basic data for related research.

This invention discloses an intelligent moisture content detection system and method for mine exits based on the natural caving method. The system includes: a mobile inspection platform; an infrared thermal imager and an air-coupled step-frequency continuous wave radar mounted on it; and an industrial control computer and a host computer, each communicatively connected to the other two. The industrial control computer is configured to: control the infrared thermal imager to perform surface scanning of the area to be measured, acquiring surface infrared thermal images; identify and locate suspected high moisture content anomaly areas in real time based on a preset temperature anomaly analysis model; control the mobile inspection platform to move to the area and trigger the air-coupled step-frequency continuous wave radar to perform directional profile scanning; process the radar echo signal and obtain the soil profile moisture content distribution information based on a pre-trained support vector regression (SVR) model; and finally send the results to the host computer for display and storage. This invention, through the cascading of infrared initial screening and radar precision measurement, achieves rapid, accurate, and three-dimensional detection of moisture content in the mine exit area, providing reliable data support for early warning of disasters such as water inrush and landslides.

A cigarette machine comprises a suction belt conveyor including a rod guide channel, wherein the rod guide channel is delimited on one side by a material-conveying suction belt. Two channel cheeks are positioned opposite one another and configured to adjoin the rod guide channel An electromagnetic measuring apparatus comprises a resonator. The resonator comprises a first resonator half positioned on the side of the rod guide channel with the conveying suction belt, and a second resonator half of which is provided on the side which is situated opposite the first resonator half. The first resonator half is connected to the suction belt conveyor.

The application discloses a kind of mixing station moisture content rapid detection and regulation system and method, related to road engineering material control technical field.System liquid level detection module detects water tank liquid level, belt running detection module obtains belt start-stop state, moisture content microwave detection module real-time collection microwave intensity signal of mixture on conveying belt and send to central control module;Central control module converts real-time microwave signal into actual moisture content value quickly, and compares with the preset target moisture content input by interactive display module, and water flow regulation module controls water pump water volume to regulate moisture content, realizes the rapid detection and automatic regulation of mixture moisture content, shortens detection cycle, eliminates artificial experience fluctuation, effectively improves the stability of inorganic binder stabilized material, and guarantees road construction quality.

The present application relates to the technical field of artificial intelligence model construction, and more particularly to a soil moisture inversion method and system based on a deep learning model. The method comprises the following steps: collecting radar remote sensing data, optical-thermal remote sensing data and ground basic data; performing cloud area processing and space-time integration on the optical-thermal remote sensing data to generate a surface reflectivity and surface temperature sequence; constructing a deep learning model; inputting the radar remote sensing data, the surface reflectivity and surface temperature sequence and the ground basic data, completing self-adaptive calibration of the deep learning model parameters, and separating soil and vegetation scattering contributions; based on the separated soil scattering contribution, combining the surface reflectivity and surface temperature data, and obtaining surface soil moisture data through regression network operation. Through deep learning technology and model adjustment technology, the present application realizes continuous monitoring of field scale high spatio-temporal resolution multi-layer soil moisture, and provides accurate data support for irrigation scheduling and fine management of drought conditions in irrigation areas.

This invention proposes a dual-frequency microwave sensor, an oil-water two-phase water cut measurement device and method, relating to the field of petroleum testing technology. The dual-frequency microwave sensor includes a sensor pipe, a shielding layer, and various detection probes. The sensor pipe is cylindrical, with flange interfaces at both ends for connection to oil well pipe flanges. The detection probes include a high-frequency excitation probe, a high-frequency measurement probe, a low-frequency excitation probe, and a low-frequency measurement probe. The high-frequency excitation probe and the high-frequency measurement probe penetrate radially along the sensor pipe in a double parallel line structure, symmetrical about the sensor pipe axis, and are located at the upper part of the sensor pipe. The low-frequency excitation probe and the low-frequency measurement probe also penetrate radially along the sensor pipe in a double parallel line structure, symmetrical about the sensor pipe axis, and are located at the lower part of the sensor pipe. This application helps improve the completeness and accuracy of water cut detection.

This invention relates to a method for testing the water content of casing. First, a dielectric response curve test is performed on casings with different water contents within a frequency range of 1000Hz–0.01Hz using a Field-Sensitive Spectrum (FDS) method, obtaining FDS-based dielectric spectrum curves for different water contents. Then, feature parameters are extracted from the FDS-based dielectric spectrum curves. Next, using the extracted feature parameters and frequency as input layers and the water content as the output layer, a backpropagation neural network is used to fit the target model function, denoted as y. (FDS) Finally, the particle swarm optimization algorithm is used to optimize the weighting factors for each frequency band, resulting in the most accurate target model for precise testing of the moisture content of the transformer's solid insulation. This invention is not easily affected by leakage current, temperature, etc., and can accurately assess the bushing insulation condition; it can obtain specific moisture content values, and can quantitatively analyze and track changes in bushing moisture content over months or years; it can accurately measure the moisture content in the insulating paper of oil-paper capacitor bushings.

This application discloses a crude oil water content analyzer and a crude oil water content detection method, belonging to the field of water content detection technology. The crude oil water content analyzer includes three transmission lines and a circuit board. The circuit board integrates a processing circuit. The effective ranges of the three transmission lines refer to the portion above the first center line, the portion below the first center line, and the portions on both sides of the third center line of the cross-section of the pipe to be tested, respectively. Therefore, the effective range of these three transmission lines can cover the entire cross-section of the pipe. This means that the microwave signal received by the processing circuit can reflect the state of multiphase flow of crude oil within the entire cross-section of the pipe. Thus, the processing circuit can accurately determine the crude oil water content based on the microwave signal, thereby improving the accuracy of the determined crude oil water content.

The application relates to the technical field of non-contact humidity sensors, and discloses a non-contact microwave humidity sensor based on a dielectric material whispering gallery mode, which comprises a resonant cavity base and a top cover connected to the top of the resonant cavity base, and the resonant cavity base and the top cover jointly form an electromagnetic shielding chamber; further comprising a ring resonator made of low-loss dielectric material, a support frame supported in the ring resonator and connected to the bottom wall of the resonant cavity base; the sensor combines the mature high-Q value WGM principle of the optical wave band with the sensing application of the microwave wave band, creatively utilizes the intrinsic advantages and evanescent field sensing mechanism of the low-loss dielectric material, realizes millisecond-level ultrafast response, eliminates the risk of performance attenuation or failure of the sensitive coating, can effectively identify slight loss disturbance, and improves the detection precision.

The application discloses a kind of microwave humidity detection system and method based on homologous constraint coherent detection and near-field resonant cavity, and it relates to microwave dielectric measurement technical field.System includes microwave signal generation module, homologous reference distribution module, integrated resonant cavity probe, coherent detection module and signal processing module, homologous reference distribution module is distributed as transmission signal and reference signal with excitation signal, both maintain same frequency source and phase starting reference;Integrated resonant cavity probe adopts single-port transceiver integrated structure, and forms energy-restricted near-field detection area at cavity opening;Coherent detection module is under the constraint of homologous reference to the echo signal is synchronized demodulation.By homologous path constraint, systematic error is common-mode distribution in reference and measurement channel and self-offset in demodulation, combined with the spatial constraint of resonant cavity standing wave field to near-field energy eliminates distance sensitivity, constructs the microwave detection system that frequency drift, phase disturbance and installation position change are all robust, significantly improves long-term measurement stability and precision under industrial complex environment.