41 results about "Passive sensing" patented technology

The invention discloses a bolt pretightening force monitoring and early warning method, system and device applied to a hydroelectric generating set and a medium, and relates to the technical field of power equipment monitoring and early warning. Signal information which is generated by the passive sensing assembly in the bolt service process and reflects the stress state is collected; the receiving device carries out data reverse acquisition on energy excitation emitted by the passive sensing assembly through radio frequency energy coupling, and the sensing assembly sends signal information to the receiving device located in a bolt adjacent region in a wireless mode; edge-level preprocessing and cloud-level trend analysis are carried out on the received signal information, a self-learning threshold model based on historical data is established, and the bolt pre-tightening state is analyzed. According to the method, the passive sensing assembly is embedded, a state driving type sampling mechanism is introduced, a data processing framework with edge and cloud collaboration is constructed, and dynamic sensing and intelligent early warning of the bolt pretightening force of the hydroelectric generating set in the whole operation process are achieved.

The invention discloses a mechanical arm wireless energy transmission method and system with a direction neutralization strategy, and relates to the technical field of wireless energy transmission. Receiving a magnetic field signal through a passive sensing module, extracting three-dimensional coordinates, directions and energy states of nodes in combination with node feedback, and constructing a three-dimensional space layout diagram; the low-power-consumption intelligent control module judges an energy supply scene and calculates an optimal alignment attitude of a coil in a single-source scene, and a multi-source scene divides an energy supply area through clustering, calculates a geometric center, finely adjusts the direction according to node energy and power weight, and screens an unshielded suboptimal path according to an obstacle avoidance scene; the control module sends an instruction to the mechanical arm servo system and the coil driving module, and a coil is adjusted to a target posture and structure; and comparing the data with the optimal value, preferentially storing energy for the low-electric-quantity nodes, and timely correcting the attitude for the nodes with sufficient energy. According to the method, through passive sensing, a direction neutralization strategy and dynamic correction, the transmission efficiency and the energy supply reliability are improved, and the multi-scene wireless energy transmission requirement is met.

The invention provides a low-altitude aircraft-oriented air safety conflict early warning method and system, and the method comprises the steps: respectively detecting the signals of all low-altitude aircrafts in a region based on an active detection network and a passive sensing network, and obtaining first detection information and second detection information; performing matching verification on the first detection information of the same low-altitude aircraft based on the second detection information of the same low-altitude aircraft to obtain detection information after matching verification, and calculating position change tracks of any two low-altitude aircrafts within a preset time interval based on the detection information after matching verification of each low-altitude aircraft; performing intersection point judgment based on the position change trajectory to obtain a trajectory intersection point judgment result between any two low-altitude aircrafts; if the track intersection point exists in the track intersection point judgment result, sending out a leading air safety conflict early warning signal; and if the track intersection does not exist in the track intersection judgment result, not sending out the leading air safety conflict early warning signal. According to the invention, the reliability and comprehensiveness of low-altitude leader safety management are improved.

The invention provides a trapped person position state analysis method and system, and relates to the field of data processing. According to the method, building structure distribution, conductive fluid flow channels and metal component distribution in a disaster target area are constructed to form a background entropy flow ground state, and noise intensity probability distribution, a channel joint fluctuation relation and a time stability index are counted to generate a background entropy flow field. In the search and rescue stage, a background entropy flow field is converted into a controlled mode through active disturbance, multi-physical channel noise responses before and after disturbance are collected through a multi-field passive sensor network, and a multi-dimensional local entropy response vector is constructed. And combining the consistency, directivity and duration of the multi-noise channel to identify an initial suspected region and extract an entropy anomaly core region, finally inferring metabolic activity and posture limitation conditions according to a local entropy response cooperative relationship in different disturbance modes, and outputting a position state result of the trapped person. By implementing the technical scheme provided by the invention, the position state of the trapped person can be accurately identified.

The invention relates to the technical field of agricultural information and intelligent sensors, and discloses a farmland soil moisture content real-time monitoring method based on multi-sensor fusion. The method comprises the steps that passive sensing nodes integrating water content, temperature, conductivity and water potential sensors are arranged, soil micro-vibration is converted into electric energy through a piezoelectric energy collection module and stored in a super capacitor, and low-power-consumption wide-area synchronous communication is achieved through the narrowband Internet of Things; and the cloud carries out time alignment, abnormity elimination and fusion processing on the multi-source data to generate a soil moisture status field, and outputs an irrigation decision in combination with a crop growth model. According to the invention, high-precision, self-powered and maintenance-free soil moisture content in-situ monitoring and intelligent irrigation closed-loop control are realized.

The invention relates to a passive driving microcapsule movement color development method, and belongs to the field of sensor detection. According to the method, sweat generated during movement of a human body drives a photovoltaic device to spontaneously generate electric potential, the electric potential directly acts on microcapsule dispersion liquid to drive directional movement of black and white particles in the microcapsule dispersion liquid, and visual color development response without an external power source is achieved. The method mainly comprises the steps of sweat induced power generation, particle electrophoresis driving and ion concentration associated color development. The problems that an existing sweat detection technology depends on an external power source, the equipment size is large, and real-time visual reading cannot be achieved are solved, and the device is mainly applied to the fields of real-time sweat electrolyte analysis in exercise physiological monitoring, autonomous color development change of wearable medical equipment, passive sensing display integrated systems based on ion concentration gradient and the like.

The present application relates to the technical field of wireless passive sensing, and discloses a differential sensing system for metal crack detection and a quantitative detection method thereof, which comprises an RFID reader-writer and a passive RFID differential sensing tag; the passive RFID differential sensing tag comprises a communication antenna, an RFID chip, an impedance matching network, a planar inductive sensing module, a radio frequency switching module, an energy recovery module and a data processing unit; the impedance matching network is connected between the communication antenna and the RFID chip; the planar inductive sensing module comprises a reference planar inductor and a sensing planar inductor; after double-state alternate sampling of the reference sensing, difference is performed, so that environmental disturbances such as reading and writing distance, sensor posture, multipath and temperature drift are significantly suppressed, and differential noise suppression is realized; the switching module is powered by the energy collection antenna, voltage doubling rectification and charge management module in the energy collection management module, battery maintenance is avoided, and passive operation is realized.

The invention discloses a variable reluctance type proximity sensor with high reliability. The variable reluctance type proximity sensor comprises a target; the induction unit comprises a shell and an induction assembly, the induction assembly comprises a magnetic core, an excitation coil and a printed board, the excitation coil is wound on the framework through an enameled wire and arranged on the magnetic core, the excitation coil and the magnetic core are integrally inserted into the bushing ring, and the excitation coil is led out of the shell after being connected with the printed board. The whole induction assembly is encapsulated in the shell through sealant. The excitation coil generates an alternating magnetic field under the action of an excitation signal, and when the target is close to the induction surface of the induction unit, the magnetic resistance in the magnetic field is changed, so that the self inductance of the excitation coil is changed; the excitation coil is connected with the detection circuit, and inductance value changes of the excitation coil are obtained through the detection circuit and converted into electric signals capable of representing the approaching state of the target to be output. An integrated packaging structure is adopted, components and passive sensing assemblies are not arranged inside, good reliability is achieved, approaching / departing position detection can be achieved by installing the target on a detected object, and the target can be suitable for various complex and long-distance position detection.

The invention provides an animal health digital supervision method and system based on big data, and relates to the technical field of digital supervision, and the method comprises the steps: collecting animal health full-chain data, and customizing a passive sensing tag of an RFID chip; the fingerprint ear tag information is preprocessed, supervision partitions are divided, and processed data are collected to the corresponding partitions; calculating a comprehensive risk value of each partition and risk traceability information associated with the fingerprint ear tag; according to the comprehensive risk value, the risk hazard degree and the inter-partition interference coefficient, the depth risk value of each partition is calculated; and synchronizing the original data containing the comprehensive risk value and the depth risk value to the block chain mini node, carrying out hash encryption, binding the encrypted data with the tag physical fingerprint to generate a tamper-resistant evidence storage record, and caching off-line data. According to the invention, big data, the Internet of Things, the block chain technology and animal health supervision business are deeply fused, and standardized and precise management of supervision data is realized.

The invention provides a traffic flow density monitoring system and method based on passive resonant cavity modulation, and belongs to the technical field of traffic monitoring, the traffic flow density monitoring system comprises a portal frame fixedly installed on a road, a passive sensing unit connected to the portal frame and a base station; the passive sensing unit comprises a resonant cavity and a cantilever beam used for connecting the resonant cavity with the portal frame; the base station comprises a radio frequency module and a signal processing unit, and the radio frequency module is used for transmitting a radio frequency inquiry signal with a specific frequency to the passive sensing unit and receiving a radio frequency signal reflected by the passive sensing unit; and the signal processing unit is used for processing and analyzing the received reflected radio frequency signal, identifying a vehicle passing event by detecting the change of the resonant frequency, and calculating the traffic flow density based on event statistics. According to the invention, accurate, low-power-consumption and low-cost traffic vehicle density monitoring is realized.

Systems and techniques are provided for sensing and device tracking. For example, a process can include obtaining first sensor data from a plurality of sensors configured with a first sensor operation mode and included in a tracker device of a plurality of tracker devices. Neighbor context information can be determined for the tracker device based on passive sensing data included in the first sensor data, and can be indicative of a placement of the tracker device relative to one or more additional tracker devices included in the plurality of tracker devices. An updated sensor operation mode can be determined for the tracker device in response to one or more changes in the neighbor context information, the updated sensor operation mode different from the first sensor operation mode. Second sensor data can be obtained from the plurality of sensors based on configuring the tracker device with the updated sensor operation mode.

The present application relates to the technical field of anti-interference navigation signal deception, in particular to an anti-interference navigation signal deception waveform design optimization method and system; the system extracts space-time features by listening to the internal communication signals of the target network; the core is to use the extended Kalman filter to iteratively solve the network topology state in reverse, and combine the virtual constellation parameters to construct a systematic deception quality index; the optimal deception waveform is determined by optimizing the parameters to maximize the index; the system also corrects the topology state and strategy weight based on the deception effect error closed loop; the present application realizes the transition from open-loop blind deception to dynamic passive sensing, and solves the problem of being unable to perceive the target topology.

The invention provides an ultrasonic sensor and a preparation method thereof, an underwater ultrasonic detection system and an application method, a single-mode fiber-multimode fiber-grapefruit type photonic crystal fiber cascade structure is adopted, a PDMS elastomer is locally filled in a photonic crystal fiber, a built-in solid-gas Fabry-Perot interference cavity is formed, an external vibrating membrane is not needed, and the ultrasonic sensor is simple in structure and convenient to operate. Therefore, the structure is simplified, and the manufacturing cost is reduced. By optimizing welding parameters and a PDMS filling and curing process, stable and efficient preparation of the sensor is realized. The design enables the sensor to have high sensitivity and broadband ultrasonic response capability, and PDMS built-in packaging improves environmental durability and measurement stability. The all-fiber passive sensing mode has the advantages of electromagnetic interference resistance, miniaturization and narrow space measurement adaptation, the system is easy and convenient to build, and the system is suitable for ultrasonic detection under complex environments such as underwater and high-temperature environments.

Aspects of the disclosure relate to systems and methods for receiving, by a first user equipment (UE), a message comprising at least one of: reference signal information (RS-info) relating to one or more reference signals (RSs) corresponding to line-of-sight (LoS) signals targeting a receiver other than the first UE, and / or data-decoding information relating to data scheduled for purposes of on-going communication with a second UE, and not scheduled for purposes of on-going communication with the first UE. The disclosure also relates to systems and methods for monitoring for at least one of: encoded signals based on the data-decoding information, and / or for one or more RSs based on the RS-info. Other aspects, embodiments, and features are also claimed and described.

The invention discloses a hydropower station underground powerhouse personnel positioning system, method and device. The system comprises a personnel positioning terminal module, a passive sensing fusion module, a multimode sensing network module, a data transmission module, a data processing and monitoring center module and an early warning linkage module which are interconnected through an industrial protocol. The passive sensing fusion module comprises an entrance guard fingerprint machine unit, an entrance and exit face recognition gate unit, an important area face recognition camera unit and a passive data integration unit; the data processing and monitoring center module comprises a dual-mode positioning algorithm engine, corresponding weights are given to active data and passive data, and positioning results are fused through weighted average; and the early warning linkage module binds the personnel information with the dangerous area authority, triggers early warning according to the setting, and links the access control locking method, device and system to be matched and corresponding. The method has the advantages that the requirements of the pumped storage power station can be met, and the operation and maintenance cost is relatively low.

The invention provides a surrounding rock shallow damage dynamic monitoring system based on active and passive fusion sensing, which belongs to the technical field of underground engineering surrounding rock safety monitoring, and comprises a prefabricated sensing unit, a signal acquisition and processing unit and a data analysis and inversion unit, the signal acquisition and processing unit comprises a signal transmitting system and a signal receiving system; and the data analysis and inversion unit processes the dynamic strain signal and the micro-vibration signal. Active elastic wave monitoring and passive micro-seismic monitoring are fused, the limitation that a traditional method is single in function is overcome, the health condition of the rock mass can be evaluated regularly, and the dynamic fracture activity of the rock mass can be monitored in real time. The invention further relates to a monitoring method of the surrounding rock shallow damage dynamic monitoring system based on active and passive fusion sensing.

Systems and methods are provided for determining the tilt-state of a moveable surface using a batteryless mechanism. A tilt-sensing device may be coupled to a moveable surface, such that the tilt-sensing device changes orientation in a manner corresponding the orientation of the moveable surface. The tilt-sensing device may include an antenna and a moveable component. The moveable component may change locations as the tilt-sensing device changes orientation due to gravitational forces. When the tilt-sensing device is in a substantially horizontal orientation, the moveable component may cause a distribution of material on the antenna. The distribution of material may detune the antenna by applying a load. Signals transmitted by the antenna may be shifted with respect to an expected frequency range. An external computing device may determine the tilt-state of the tilt-sensing device based on the presence or absence of a shift within received signals from the tilt-sensing device.

This specification discloses a method and system for constructing, dynamically updating, and mining a global generic relationship passive sensing graph. The method deploys passive sensing nodes across the entire domain to silently collect generic relationship data of entities of all scales and types, performs preliminary anonymization, and constructs a unified global generic relationship graph after local encryption preprocessing. A dual-mode dynamic update mechanism is used to maintain the graph's validity, and a multi-dimensional anomaly mining algorithm is employed to identify abnormal associations. Data security control and differentiated handling are implemented throughout the process. This solution addresses the problems of incomplete relationship coverage, delayed updates, and insufficient data security in existing technologies, achieving accurate collection, anonymized identification, and security control of generic relationships.

Systems and techniques are provided for sensing and device tracking. For example, a process can include obtaining first sensor data from a plurality of sensors configured with a first sensor operation mode and included in a tracker device of a plurality of tracker devices. Neighbor context information can be determined for the tracker device based on passive sensing data included in the first sensor data, and can be indicative of a placement of the tracker device relative to one or more additional tracker devices included in the plurality of tracker devices. An updated sensor operation mode can be determined for the tracker device in response to one or more changes in the neighbor context information, the updated sensor operation mode different from the first sensor operation mode. Second sensor data can be obtained from the plurality of sensors based on configuring the tracker device with the updated sensor operation mode.

The application discloses a kind of multi-lamp cooperation's joint control lighting control method, device, equipment and medium.Each lamp includes light emitting unit and photosensitive unit, and the method includes: each lamp periodically emits modulated light signal through its own light emitting unit, and receives modulated light signal from other lamps through its own photosensitive unit to construct a reference light field;When mobile object appears in the reference light field, disturbance can occur, at which time the current position and movement state of mobile object can be judged by exchanging detection information between each lamp, whereby each lamp is controlled to carry out intelligent lighting.The application provides a passive sensing intelligent lighting control scheme that does not depend on traditional dedicated sensors;A passive sensing network is constructed using the inherent optical components of the lamps, which can detect mobile objects without blind spots, and based on cooperative judgment and predictive control, the passive sensing direction achieves precise, smooth and user-invisible control of the lamp lighting.

The utility model discloses a kind of multifunctional integrated passive sensing node devices for bridge, through piezoelectric cantilever beam collection bridge environmental vibration energy, and in combination with super capacitor energy storage, completely get rid of the dependence on solar panel, battery or external wiring, realize energy self-sufficiency, integrate MEMS accelerometer, multifunctional vibrating reed unit, attitude sensor multiple sensing functions in a unified sealed shell, solve the possible power failure of battery in continuous rainy days, and battery life is limited, need to be replaced regularly, maintenance cost is high, a large number of cable and independent power supply unit lead to installation complex, reliability reduces, fault point increases, each monitoring point needs a complete set of power supply and acquisition equipment, total cost is high, when new monitoring point, need to repeat complex installation and wiring work.

This invention belongs to the field of satellite navigation and mobile communication fusion technology, and provides a positioning method based on the control plane signaling of an integrated BeiDou and 5G base station. This method first continuously broadcasts and detects low-altitude areas using the inherent signals of the integrated base station control plane, achieving passive sensing and identification of low-altitude targets. Second, it achieves high-precision positioning and track tracking by combining control plane signaling measurement data from multiple base stations with the BeiDou high-precision spatiotemporal reference. Finally, a monitoring platform performs real-time compliance verification of target tracks, promptly issuing warnings to relevant management departments for non-compliant targets. This system requires no active cooperation from terminals and relies on large-scale integrated base stations to facilitate refined and intelligent airspace management, which is of great significance for improving the low-altitude airspace governance system and the development of the low-altitude economy.

The application provides a trapped personnel position state analysis method and system, and relates to the field of data processing. In the method, a background entropy flow base state is formed by constructing the building structure distribution, conductive fluid flow channel and metal component distribution in the disaster target area, and a background entropy flow field is generated by statistically analyzing the noise strength probability distribution, channel joint fluctuation relationship and time stability index. In the search and rescue stage, the background entropy flow field is converted to a controlled mode by active disturbance, and the multi-physical channel noise response before and after the disturbance is collected by relying on a multi-field passive sensing network to construct a multi-dimensional local entropy response vector. The initial suspected area is identified and the entropy anomaly core area is extracted by combining the consistency, directionality and duration of multiple noise channels. Finally, the metabolic activity and posture restriction condition are inferred according to the local entropy response coordination relationship under different disturbance modes, and the trapped personnel position state result is output. The technical solution provided by the application is convenient for accurately identifying the position state of trapped personnel.

The application relates to the technical field of passive sensing and behavior recognition, and discloses a passive posture monitoring method and system based on deep learning, wherein the passive posture monitoring method based on deep learning comprises the following steps: acquiring a target object monitoring image sequence collected by multiple visual angle cameras, and generating a multi-dimensional occlusion label tensor; calculating data validity weights based on the occlusion label tensor, and constructing a sparse multi-view observation tensor; decomposing the observation tensor into a low-rank background tensor, a sparse change tensor and a noise tensor by using a sparse time series tensor decomposition algorithm; inputting the low-rank background tensor and the sparse observation feature obtained through decomposition into a conditional variational autoencoder, and reconstructing a complete time series trajectory; and generating a high-confidence continuous posture monitoring sequence and a gradual abnormality early warning signal through physical constraint optimization and Bayesian inference. The application solves the technical problem of accurately monitoring the slow change of a lighting lamp posture under frequent occlusion conditions.

This invention provides a wireless monitoring system for deep deformation of concrete cracks, belonging to the field of civil engineering structural health monitoring technology. It includes a built-in passive sensing unit, an external wireless detection unit, and a cloud-based data analysis and inversion platform. The built-in passive sensing unit comprises a ferromagnetic sensing metal strip and a positioning structure. The external wireless detection unit includes a signal transmitting module. The cloud-based data analysis and inversion platform includes a signal receiving module and a main control processor. The signal transmitting module transmits electromagnetic wave signals to the concrete structure. This invention directly senses deep deformation of cracks through the embedded metal strip, rather than relying on surface inference or passively receiving weak signals. The metal strip and concrete deform in tandem, accurately reflecting the true deformation of cracks at depth, overcoming the limitations of traditional technologies that can only perform surface measurements or depth estimations. This invention also relates to a monitoring method for this wireless monitoring system for deep deformation of concrete cracks.

The application discloses a kind of RFID sensing system device and method based on magnetron antenna coupling.The product of required identification label has two separable parts, label and antenna coupler are installed in one part of product, magnet is installed in another part of product, coupling structure is formed between antenna coupler and label, read-write system is used to transmit radio frequency signal, receive and process the radio frequency signal returned by label, reed switch is connected between two coupling radiators to form antenna coupler, magnet is used to control the state of antenna coupler, the method comprises device installation, using read-write system to receive and process the radio frequency signal generated by label, and judging the state of antenna coupler through the data information of radio frequency signal to judge the use state of product.The application uses magnet to carry out wireless, passive sensing for various actions, and the inductive function does not need to design specific label, so the structure is simple and easy to deploy, and has good application potential in Internet of Things and smart home.

The present invention discloses an active and passive coordinated sensing fusion method for a radar communication dual-function system. The method includes: step 1 embedding a dedicated sensing symbol in a signal transmitted by a base station; step 2 solving a power allocation problem using an optimization problem; step 3 having a receiving access point receive a passive sensing signal and process direct path interference into white noise using a whitening filter; step 4 having the receiving access point determine whether a target is present using a generalized likelihood ratio test detector, and then the receiving access point and base station transmit the binary determination result and target detection probability to a fusion center; and step 5 having the fusion center vote and aggregate the received information to determine whether a target is present. The present invention can improve the accuracy and efficiency of target detection, positioning and acquisition of environmental information, and reconstruction, and has the potential to significantly improve the performance of wireless communication sensing networks.

The invention discloses a quasi-distributed sensing temperature decoupling detection system and method. On the basis of a wireless passive communication technology, feature points of all sensing structures are obtained by obtaining a starting power curve of a tag, and wireless passive sensing is achieved; sensing structure deformation caused by stress is reflected on feature point offset, and quasi-distributed stress sensing is achieved by loading a plurality of sensing structures with different feature points on the microstrip line at the same time. One channel in the dual-channel structure covers the dimension sensitive material, and the other channel which is not covered is compared to obtain temperature information, so that temperature decoupling is realized; meanwhile, different Young modulus plates are combined, and the flexible requirement for tight attachment of a sensing part and a measured surface and the requirements for rigidity and stability of a core circuit and an antenna part are considered. And a sampling technology compatible with RFID equipment is adopted, so that the cost of tags and acquisition equipment is remarkably reduced.

An apparatus can include a mouthpiece, a sonic transmitter disposed within the mouthpiece to transmit an emitted sound signal to a respiratory system, a sonic receiver disposed within the mouthpiece to receive a reflected sound signal from the respiratory system, and neural network circuitry to execute a neural network to generate an output indicative of a health condition of the respiratory system based on the reflected sound signal.

The application relates to a universal mobile Internet of Things multi-modal data dynamic transmission system and method, a motion-channel attenuation mapping model is constructed, electromagnetic frequency band state data of the surrounding environment of an Internet of Things device is acquired, short-term channel quality is predicted in combination with the model, a multi-protocol score array is generated, an optimal transmission path is selected, the clock of the device is calibrated to synchronization, data is reorganized, and transmission is realized; the system integrates IMU and passive sensing devices in a terminal device, and real-time collection of device motion states and electromagnetic environment data is realized; an edge terminal including a distributed edge computing node receives information transmitted by a device terminal and realizes dynamic protocol switching and resource scheduling, and timing calibration and repair of multi-protocol data are realized at a gateway terminal; and data is output after reorganization and security inspection. The application significantly improves the channel quality prediction accuracy and transmission reliability in a mobile scene, guarantees the whole-link priority occupation of emergency medical data, synchronizes errors, and meets the application requirements of high reliability and low time delay.