29 results about "Energy sensing" patented technology

The invention discloses a medical signal generation method and system based on a time-frequency double-domain constraint generative adversarial network. According to the method, a multi-category electrocardiosignal generation model is designed on the basis of a conditional generative adversarial network, global attention interaction is carried out by utilizing a learnable potential feature prototype and position-coded signal features through an adaptive neural representation module, and long-distance time sequence dependence of electrocardiosignals is modeled; through the adaptive spectrum sensing module and the dynamic mask mechanism of energy sensing, the discriminator intensifies the discrimination of the consistency of signal frequency domain information while paying attention to the time domain form, thereby effectively inhibiting the non-natural high-frequency artifacts in the generation process, and ensuring the high fitting of the generated signal and the real signal. Experiments show that the fidelity and diversity of generation of various types of electrocardiosignals can be remarkably improved.

A multi-agent reinforcement learning-based optimal energy sensing threshold control method in distributed cognitive radio networks includes: (a) constructing a state space for a network environment including a plurality of primary terminals and a plurality of secondary terminals, the state space including each state about whether the primary terminals are occupied; (b) selecting an action in accordance with a policy by applying partial observation of each secondary terminal to a reinforcement learning-based actor-critic network model by means of an agent, and calculating a reward on the basis of a sensing result of the primary terminals on the basis of the selected action in the environment, the action being a sensing threshold; (c) storing the partial observation, the selected action, the reward, and next observation into a replay buffer as experiences; and (d) updating the actor-critic network model on the basis of the experiences stored in the replay buffer.

The invention relates to the technical field of ocean energy sensing equipment, in particular to a self-powered sensor and method for wave height monitoring. The self-energized sensor comprises a first shell with two open ends, a sealed second shell and a plurality of power generation units. The upper end of the first shell is fixedly installed on one side of the second shell, and the lower end of the first shell is bent outwards. The multiple power generation units are sequentially arranged in the axis direction of the second shell. The power generation unit comprises a rotating part, a first substrate and a second substrate, a dielectric layer and an electrode layer which are different in electronegativity are arranged on the two opposite side walls of the first substrate and the second substrate, the rotating part rotates to drive the second substrate to rotate relative to the first substrate, and then the dielectric layer and the electrode layer are driven to move relatively to generate current. The self-energized sensor provided by the invention not only can monitor the wave height based on the electric signal output by the power generation unit, but also can supply power to the sensor by the generated electric signal, so that the self-energized sensor provided by the scheme can stably run for a long time.

This utility model discloses an energy transmission device, including an energy sensing element and a coil. The energy sensing element includes a first sensing part and a second sensing part. The second sensing part is disposed adjacent to the first sensing part. The coil is disposed adjacent to the energy sensing element. The first sensing part and the second sensing part are made of different materials.

The invention belongs to the technical field of monitoring power supply, and discloses a monitoring power distribution control system based on energy state perception, and the system is characterized in that a commercial power monitoring module is used for monitoring commercial power parameters of a power grid; the power supply module is used for converting alternating current of a power grid into power supply voltage; the battery control module is used for collecting battery operation parameters of the battery; the energy state sensing module is used for collecting equipment power utilization parameters of an equipment power supply interface and an internal function module, calculating commercial power quality data according to commercial power parameters, and calculating battery state information according to battery operation parameters. The mains supply quality data, the battery state information and the equipment power utilization parameters are used as energy sensing data to be sent to the main control module; controlling the power supply voltage and the battery voltage to supply power to the equipment power supply interface and the internal function module based on the mains supply quality data; the master control module is used for controlling on-off of the equipment power supply interface and the internal function module based on the energy perception data. According to the invention, the stability of power distribution monitoring is improved.

The application relates to the technical field of electric arc processing equipment, and discloses an electric arc energy sensing variable-diameter nozzle regulating device and method, which solves the problem that the diameter of a nozzle cannot be self-adaptively adjusted according to electric arc energy variation, and comprises a conical nozzle body, the end of the conical nozzle body is provided with a front-end horn-shaped nozzle, the front-end horn-shaped nozzle is integrally arranged with the conical nozzle body, the outer side of the front-end horn-shaped nozzle is provided with a regulating mechanism, a driving mechanism is arranged on the regulating mechanism, the regulating mechanism comprises a regulating sleeve located on the outer side of the front-end horn-shaped nozzle, a plurality of inner arc-shaped rods are fixedly connected to the inner side of the front-end horn-shaped nozzle at equal angles, and a connecting column is fixedly connected to the outer side of each inner arc-shaped rod; the front-end horn-shaped nozzle is expanded outward under the action of the force of each reset spring, the diameter is increased, and the diameter of the whole nozzle is conveniently regulated.

The application discloses a structure icing / snowing synchronous classification monitoring system based on energy sensing and computer vision, realizes composite self-power supply through a fan and a thermoelectric material, triggers a built-in high-definition camera of a deep residual network to perform morphological feature extraction in ice and snow weather, and realizes snow / icing / normal three-state classification identification for the first time; the output visual probability matrix, equivalent physical density and pre-physical prior feature are subjected to fusion analysis and judgment of multi-modal data, and all-weather autonomous monitoring and early warning of structure snow and icing synchronous classification are realized. Not only the problems of high energy consumption, difficult independent operation and single monitoring capacity of traditional equipment are effectively solved, but also precise synchronous classification of structure icing, snowing and normal state is realized, and the false alarm and missed alarm rates of traditional sensors are greatly reduced.

The application provides an anti-interference acoustic signal data extraction method based on energy data sensing, and belongs to the technical field of underwater acoustic signal processing. The method comprises the following steps: A / D sampling and digital quadrature demodulation are performed on a received acoustic signal to obtain a baseband signal; low-pass filtering and down-sampling are performed on the baseband signal to obtain a pretreated signal; the pretreated signal is matched filtered by using a reference signal; a key improvement lies in that a local energy estimation function of the pretreated signal is calculated, and the matched filtering result is normalized with the energy estimation function to obtain a normalized detection signal. Through energy sensing normalization, the application effectively suppresses the shielding effect of strong interference signals on weak target signals due to non-quadrature reference signals and the "near-end strong and far-end weak" scene, significantly reduces the false recognition probability, and improves the accuracy and reliability of extracting a long-distance and low signal-to-noise ratio target beacon signal in a complex underwater acoustic environment. The application is suitable for underwater navigation, positioning and communication systems.

The utility model discloses an impact energy testing device for a fuse impactor, which relates to the technical field of impact detection and comprises a bottom plate, anchor screws are fixedly mounted at four corners of the bottom end of the bottom plate, and an energy sensing assembly and a sample lifting assembly are mounted on the top end face of the bottom plate. The top end of the sample lifting assembly is provided with a left-right side fine adjustment assembly and a sample mounting assembly, the sample mounting assembly is movably provided with a sample, and the sample lifting assembly is matched with the energy induction assembly to be used for detecting the impact energy level of the sample; according to the utility model, by controlling the sample lifting assembly, the left and right side fine tuning assembly and the sample installation assembly, multi-directional installation of a sample is realized, and by cooperating with the separation blade, the rotating shaft, the pointer, the encoder and other components, detection work of electronic components such as a fuse impactor and the like is realized.

The invention discloses an automobile braking mechanical control anti-lock braking system and an emergency braking method, and relates to the technical field of automobile braking. The automobile braking mechanical control anti-lock braking system comprises a braking energy sensing module, a double-threshold self-adaption module and a pressure dynamic balance module, and an anti-lock braking control link without electronic control is formed through pure mechanical link linkage. The brake energy sensing module converts wheel kinetic energy changes into mechanical signals, the double-threshold self-adaption module switches threshold values according to the brake input strength, and the pressure dynamic balance module achieves brake pressure closed-loop adjustment. According to the emergency braking method, braking control is completed through scene recognition, early warning and pre-adjustment, dynamic balancing and resetting. Electronic elements are abandoned, the problems of poor reliability, narrow adaptability and high cost in an extreme environment in the traditional technology are solved, and the brake is suitable for various vehicle types, gives consideration to brake efficiency and stability and has extremely high popularization value.

The invention discloses a wide-band spectrum sensing method and device based on threshold improvement, equipment and a medium. The method comprises the following steps: dividing a preset frequency band into a plurality of continuous and equal-broadband sub-frequency bands; for each sub-frequency band, calculating a bottom noise sequence of the sub-frequency band according to the receiving tying band IQ signal in the sub-frequency band and the number of frequency points in the sub-frequency band; performing J-layer wavelet decomposition on the bottom noise sequence to obtain an approximation coefficient and a detail coefficient; reconstructing the ground noise sequence to obtain a smoothed ground noise sequence; according to a preset system total target false alarm probability, a system frequency slot number, a spectral line number of each frequency slot and a variance of the smoothed bottom noise sequence, calculating an energy threshold value of each frequency point of the sub-frequency band; and taking the thresholds corresponding to the plurality of sub-bands as judgment thresholds of an energy sensing algorithm, and processing the signal by using the energy sensing algorithm to obtain a sensing result. According to the embodiment of the invention, the false alarm rate in wide-band spectrum sensing can be reduced, and the sensing accuracy is improved.

The invention discloses a green energy computing network system based on multi-modal energy collaborative scheduling, and particularly relates to the technical field of power grid scheduling, which comprises a multi-modal energy sensing module, a computing power task energy efficiency model building module, a computing network node layer, a two-dimensional prediction scheduling module, a computing power scheduling control module and a computing power flexible control module, according to the method, green energy data is collected in real time, expectation of the power consumption demand of a computing power task is calculated, a decision basis is provided for upper-layer scheduling through resource integration and cross-regional data interaction of a green power region and a computing power region, and an optimal collaborative scheduling strategy is output by adopting an improved particle swarm optimization algorithm based on the green energy data and a task energy efficiency portrait. The computing power task scheduling of the power shortage area is realized, the impact computing power scheduling instruction is converted into the power output by introducing the power ramp rate control of the S-shaped curve, the computing power is converted into the schedulable flexible load from the impact load of the power grid, and the stability in the power grid scheduling process is enhanced.

There is provided a control device for controlling a power conversion apparatus, the power conversion apparatus including: a primary side circuit having a primary winding and a main switch, a secondary side circuit having a secondary winding, and an auxiliary circuit having an auxiliary winding, where the primary winding, the secondary winding, and the auxiliary winding constitute a transformer; when the main switch is turned off, the voltage of the same oscillation waveform as the voltage across the main switch is formed on the auxiliary winding, and the main switch realizes energy accumulation of the primary side circuit and energy induction of the secondary side circuit through on / off operation; the control device includes: a processor for controlling an on / off operation of the main switch; and an ON time controller for generating an ON signal defining an ON time point of the main switch after sequential ON and OFF operations of the main switch based on a voltage formed in the auxiliary circuit, impedance information of the passive element, and a predefined reference voltage, and outputting the ON signal to a processor.

The application discloses a satellite signal demodulation method, device, equipment and medium. The method comprises the following steps: acquiring a current satellite signal and current adjustment parameter information at a current time, wherein the current adjustment parameter information comprises a demodulation gain parameter, a first optimization gain parameter and a filter coefficient; performing channel energy sensing and signal demodulation on the current satellite signal based on the current adjustment parameter information, and determining next adjustment parameter information and a demodulated current data frame at a next time. By adopting channel energy sensing to determine the demodulation gain parameter, the first optimization gain parameter and the filter coefficient at a downlink time slot, the acquisition of a synchronization header and the frame demodulation and decoding are completed at the downlink time slot, the current data frame is obtained, the automatic adjustment of the adjustment parameter information is realized for different interference conditions, the anti-interference capability of the satellite signal demodulation is improved, and the anti-interference requirements of more extensive application scenarios are adapted.

The invention relates to the technical field of induction motors. The technical problem to be solved is that the induction motor returns electric energy in heavy-load and overspeed states, increases power and returns electric energy at the same time in heavy-load and overspeed states, and increases resistance and returns electric energy at the same time in overspeed. And calculating the optimal working point and the control method of the common induction motor according to the characteristics of the energy return motor. According to the technical scheme, the energy-returning motor is composed of an input end, a rotor and an output end. The input end injects energy into the rotor, the rotor transmits the energy of the input end to the output end, and the output end induces the energy of the rotor to the output end to output electric energy. The energy return mode of the energy return motor must be that electric energy is returned from a rotor to a stator coil at an output end and cannot be returned from an input end to an output end directly. Main parameters influencing the energy-returning motor comprise power supply frequency, coil pole pair number or magnet pair number, coil and rotor combination mode and the like. The motor is mainly applied to places needing common motors in industry and agriculture.

The invention relates to the technical field of wind power sensing, and discloses a wind vector sensor and a wind vector sensing system. The wind vector sensor comprises a shell, a wind energy sensing assembly, a signal generation assembly and a signal analysis assembly. Air inlets of at least two containing cavities are formed in the circumferential outer wall of the shell at intervals. The fixed end of a sensing unit in the wind energy sensing assembly is fixed, and the free end of the sensing unit is arranged opposite to the corresponding air inlet and used for generating vibration. A generating unit in the signal generating assembly is located on one side, in the first direction, of a sensing unit corresponding to the generating unit, and the generating unit is used for generating a corresponding vibration signal according to the vibration state of the sensing unit through non-contact relative movement when the generating unit vibrates. And the signal analysis assembly is connected with the signal generation assembly and is used for acquiring the vibration signal and processing the vibration signal. The wind vector sensor can effectively respond under the conditions of low wind speed and variable wind directions, synchronously obtain wind vector information, and can stably run for a long time through self power supply in an extreme environment.

The invention discloses a system and a method for intelligent energy management of an excavator. The method comprises the following steps: acquiring intelligent energy sensing information of the excavator; preprocessing the intelligent energy sensing information of the excavator to obtain target processing intelligent energy information; and analyzing and processing the target processing intelligent energy information to obtain target intelligent energy analysis result information.

The invention provides an age-aware routing and unloading joint optimization method for a satellite network, and the method comprises the steps: enabling each satellite node to broadcast a lightweight HELLO beacon to a neighbor at the beginning of each decision time slot, and receiving the beacon of the neighbor; starting an independent optimization process for each observation task newly arriving at a satellite node in the time slot to determine a joint decision tuple; each satellite node enters a local execution stage, and after each time slot is finished, the queue value and the real battery energy of the virtual energy queue are updated according to the actual energy consumption and the energy collection amount of the satellite node in the time slot; according to the invention, a virtual energy queue is introduced to realize long-term energy balance constraint conversion, a block coordinate descent method is adopted to solve an optimal routing path, unloading nodes and a data compression ratio are calculated, and a self-adaptive energy sensing routing mechanism and a scheduling strategy based on an information age priority are combined to obtain an optimal routing path. And dynamic optimal balance among information freshness, data processing precision and energy sustainability is realized.

The invention discloses an air-ground integrated intelligent operation system and method for a mooring unmanned aerial vehicle. The system comprises an unmanned aerial vehicle end, a ground station and a mooring cable connecting the unmanned aerial vehicle end and the ground station. The unmanned aerial vehicle end is provided with an airborne controller, the ground station is provided with a ground controller, and a distributed model prediction control unit is formed; the unmanned aerial vehicle end is further provided with a power state observer which is used for calculating a power estimation value according to the collected voltage signals and current signals in combination with cable resistance parameters. And the power estimation value is sent to a ground station through a timestamp-synchronized communication link for a ground controller to carry out global optimization calculation. The system further comprises a multi-sensor fusion positioning module, a dynamic resource distributor, a main-standby double-link communication architecture and a Lyapunov optimizer. Through distributed control, accurate energy perception, intelligent state estimation and cross-layer collaborative optimization, accurate control, energy efficiency maximization and high-reliability operation of the mooring unmanned aerial vehicle in a dynamic environment are realized.

The invention discloses an intelligent brain biosensor based on biological energy fusion and a disease conditioning method, and relates to the cross technical field of biomedical technology and intelligent sensing technology, the intelligent brain biosensor comprises a biological energy sensing module, a signal analysis and regulation module, a biological energy wave generation module and a feedback monitoring module, all the modules cooperate to form a closed-loop conditioning system, the bio-energy sensing module is of a non-invasive structure, comprises a flexible electroencephalogram electrode array and a multi-channel bio-electricity collection chip and is used for collecting brain waves and body surface bio-electricity signals, the human body bio-electricity state can be monitored in real time, and bio-energy wave parameters are dynamically optimized; personalized and safe disease conditioning is achieved, the method is suitable for auxiliary conditioning of brain related functional diseases such as sleep disorder, mild cognitive dysfunction and chronic headache, and a new technical path is provided for non-drug disease intervention.

This invention discloses a cargo electric-assisted bicycle with gravity adaptive adjustment and intelligent energy distribution, comprising a frame body, a cargo frame outer frame, a height-adjustable suspended cargo shelf, a rope tensioning system that applies adjustable vertical suspension tension to the suspended cargo shelf by retracting and extending a flexible tension rope, a gravity transmission mechanism disposed between the seat post and the cargo frame outer frame for transferring part of the rider's weight to the suspended cargo shelf, a road sensing system for collecting road surface information, an energy sensing component for sensing gradient, vehicle speed, and human input status, and a main controller electrically connected to the above systems. The main controller adjusts the suspension height and support stiffness of the suspended cargo shelf in a closed loop based on the tension sensor signal, pre-adjusts the suspension stiffness based on road surface information to buffer impacts, and dynamically calculates the electric auxiliary power ratio by comprehensively considering load, gradient, vehicle speed, and human input power, and initiates regenerative braking to recover kinetic energy under preset operating conditions.

The invention discloses a total station scanner autonomous path planning method for tunnel undercut detection, and relates to the technical field of tunnel engineering intelligent detection, and the method comprises the following steps: 1) constructing a coupling deformation-path offset-construction disturbance ternary deformation energy-path offset mapping model, coupling deformation energy is defined, the mapping relation between the coupling deformation energy and the track curvature, the node density and the scanning angle is established, and the model is written into a scanner control system; according to the method, a ternary deformation energy-path offset mapping model, a dual-mode deformation energy sensing mark, a self-driven closed-loop path planning system and a multi-dimensional construction linkage mechanism are utilized; the problems that coupling deformation signals are not utilized in existing path planning, an under-excavation detection and stability evaluation integrated framework is lacked, scanning resource distribution is unbalanced, detection and construction are disjointed, and cost is high are solved, and the effects of sub-micron under-excavation detection, pre-judgment of surrounding rock deterioration in advance, dynamic optimization of scanning and construction parameters and reduction of energy consumption and detection cost are achieved.

Certain aspects of the present disclosure provide techniques for subchannel-based listen before talk (LBT). An example method that may be performed by a user equipment (UE) includes receiving one or more transmissions indicating one or more allocated subchannels of a frequency band that are allocated during a first time period, the frequency band comprising the one or more allocated subchannels and one or more unallocated subchannels during the first time period; sensing the one or more unallocated subchannels for at least a portion of the first time period prior to a second time period; and transmitting a signal within the frequency band during the second time period based on energy sensed for the one or more unallocated subchannels being less than a threshold.

This invention relates to the field of intelligent monitoring technology for power systems, and discloses a control device and method for a power grid edge monitoring terminal combined with active energy sensing. The device includes: a micro-meteorological sensing module for real-time acquisition of meteorological parameters of the environment where the monitoring terminal is located; an energy prediction module for predicting expected energy gains within a future time window using a time-series prediction model; an energy assessment module for calculating an energy availability score; a mode decision module for dynamically switching the operating mode of the monitoring terminal based on a comparison of the energy availability score with a preset threshold; a defect detection module for real-time defect detection of acquired images or video streams; and a verification decision module for determining whether to trigger a second power consumption mode for defect verification when the defect detection module detects a suspected defect in a first power consumption mode. This invention can significantly reduce the false negative rate of dynamic defects without increasing hardware costs or battery capacity.

The invention relates to the technical field of wearable equipment, and discloses wearable glasses equipment with multi-color dimming and positioning functions, the glasses are integrated with a piezoelectric sensor, a temperature difference sensor and an organic photovoltaic film also serving as an illumination sensor, a micro-control unit collects vibration, heat flow and light intensity data in real time, and a multi-dimensional energy fingerprint is generated through fusion. By matching the fingerprint with a pre-stored template library, the system can accurately identify complex context events such as wearing, accidental falling, charging operation and the like, so that the equipment can automatically adjust the light transmittance of the lens, activate a retrieval system comprising a buzzer and a positioning beacon during falling, and switch to a low-power-consumption mode, and the power consumption of the equipment is reduced. And during charging, the safety lock is triggered to physically isolate the data contact, so that the information safety is guaranteed. According to the method, deep context understanding and active control are realized by constructing the multi-physical-dimension energy sensing model, and the adaptability, the safety and the energy efficiency of equipment are remarkably improved.

The application provides an organic-inorganic hetero dielectric layer-based sensing, storage and calculation integrated transistor and a preparation method and application in programmable display driving, and belongs to the technical field of organic field effect transistors. The organic-inorganic hetero dielectric layer-based sensing, storage and calculation integrated transistor comprises, from bottom to top, a substrate, a dielectric layer, an organic small molecule semiconductor layer and source / drain electrodes; the dielectric layer is an organic-inorganic hetero dielectric layer; the organic-inorganic hetero dielectric layer is a double-layer structure composed of a lower dielectric layer and an upper dielectric layer; the upper dielectric layer is a polyamide acid layer; and the lower dielectric layer is a hafnium oxide layer. The polyamide acid-hafnium oxide hetero dielectric layer is used to obtain a high-performance, low-energy sensing, storage and calculation integrated organic thin film transistor array with storage performance and excellent photoelectric sensing performance, and the organic thin film transistor array is used in programmable display driving, thereby opening up a new way for the development and application of organic sensing, storage and calculation integrated neuromorphic vision devices and display driving fields.

The invention relates to the technical field of turnover cabinet information management, in particular to an intelligent metering turnover cabinet information management method and system based on the RFID technology. The method comprises the following steps that after the transfer cabinet detects that assets are placed in, space scanning detection is conducted on storage positions through energy induction probe arrays and phased-array antennas deployed in the storage positions so as to obtain space energy distribution data; constructing a layered label activation strategy according to the spatial energy distribution data; and controlling the phased-array antenna to execute multiple rounds of radio frequency excitation according to a layered label activation strategy, capturing a label reflection signal in a directional receiving mode, and then comparing a captured actual inventory count value with an obtained theoretical inventory count value to obtain turnover cabinet inventory state data so as to realize intelligent metering turnover cabinet information management. According to the invention, accurate inventory of the three-dimensional high-density label array is realized, and the problem that high-density stacked assets are difficult to accurately inventory in an intelligent turnover cabinet is solved.

The invention discloses a two-step broadband spectrum sensing method and system, and relates to a spectrum sensing technology, and the method comprises the steps: taking collected scanning data of a sensing frequency band as input data; the average value of the input data is taken as a test statistic, and a round of energy detection is completed according to a noise power calculation threshold value; after executing energy detection of a preset number of times, taking data acquired in multiple rounds as covariance detection input, and according to a covariance detection result, calculating a power mean value of non-interfered frequency points for updating an energy detection threshold value; and outputting a detection result according to the energy detection and the updated threshold value. According to the method, the energy detection algorithm and the covariance detection algorithm are combined to realize rapid sensing of the broadband, the influence of background noise fluctuation on the energy sensing detection precision can be effectively solved, and the influence caused by interference signals can be removed in the rapid detection stage according to the detection result of the covariance.

The present application relates to the technical field of turnover cabinet information management, and particularly relates to an intelligent metering turnover cabinet information management method and system based on RFID technology. The method comprises the following steps: after detecting that an asset is placed, the turnover cabinet performs spatial scanning detection on the storage location through an energy induction probe array and a phased array antenna arranged in the storage location to obtain spatial energy distribution data; a hierarchical label activation strategy is constructed according to the spatial energy distribution data; the phased array antenna is controlled to perform multiple rounds of radio frequency excitation according to the hierarchical label activation strategy, and the label reflection signal is captured in the directional receiving mode; then, the actual inventory count value captured is compared with the theoretical inventory count value obtained, and turnover cabinet inventory state data is obtained, so as to realize intelligent metering turnover cabinet information management. The present application realizes accurate inventory of a three-dimensional high-density label array, and solves the problem that high-density stacked assets are difficult to accurately inventory in an intelligent turnover cabinet.