2391results about "Telemetry/telecontrol selection arrangements" patented technology

The invention provides a Beidou electric power data intelligent acquisition and dynamic communication scheduling method and system. The method comprises the steps that a master station constructs a database and trains a data priority classification model, a channel quality prediction model and an intelligent compression model; a substation collects power data through an edge calculation unit, constructs a skyline candidate set to perform data screening, and performs intelligent classification marking by using a data priority classification model; performing reliability evaluation on the data stream by using a Gaussian mixture model, selecting a compression strategy according to a reliability score, a data type and a priority, and packaging into a data frame; determining a transmission strategy in combination with a channel quality prediction result and a context-aware intelligent switching protocol, and sending a data frame; the master station receives the data frame, performs integrity verification, decompresses and reconstructs the data frame, and feeds back a communication state for model updating; and monitoring the operation state, performing early warning based on the anomaly detection model, and triggering a self-healing strategy. According to the invention, the Beidou communication resource utilization rate and the system reliability are improved.

The invention relates to the technical field of electric power intelligent judgment, in particular to an AI-based intelligent electric energy meter fault diagnosis system, which comprises an operation data acquisition module, a jump correlation judgment module, an operation deviation judgment module, a current waveform diagnosis module and an abnormity alarm module. According to the invention, through synchronous acquisition of the current data and the operation data of the refrigeration storage, whether the current jump is related to the gating action is judged, and the refrigeration performance abnormity of the refrigeration storage and the fault type of the intelligent electric meter are effectively identified by further combining multiple cross validation of baseline energy consumption and temperature change; an ideal current waveform is constructed through an AI algorithm and is compared with an actually measured waveform, so that intelligent judgment and classification of fault types are realized; meanwhile, the diagnosis result is linked with the operation and maintenance system, the response efficiency is improved, and the method is particularly suitable for scenes with high requirements on the stability of the electric meter, such as cold chain storage, and has good practical value and popularization prospect.

The invention relates to the technical field of electric power inspection, and provides a multi-unmanned aerial vehicle cooperative electric power inspection method, system and device, a medium and equipment, and the method comprises the steps: obtaining environment information of a to-be-inspected area, inspection task information and equipment state information corresponding to a plurality of unmanned aerial vehicles; collecting multi-source sensor data of a to-be-inspected area based on multiple sensors on each unmanned aerial vehicle, and constructing a three-dimensional real-time environment model based on the multi-source sensor data and environment information of the to-be-inspected area; generating a task allocation scheme based on the three-dimensional real-time environment model, the inspection task information and the equipment state of each unmanned aerial vehicle; based on the scheme, a three-dimensional real-time environment model and a path planning algorithm, determining a flight path of each unmanned aerial vehicle; and controlling each unmanned aerial vehicle to inspect according to the flight path to obtain inspection information. According to the embodiment of the invention, efficient cooperative inspection of multiple unmanned aerial vehicles in a complex environment is realized, the accuracy and comprehensiveness of inspection are improved, and the efficiency and quality of electric power inspection work are effectively improved.

The invention discloses a method and a system for verifying the reliability of remotely acquired data of an electric meter box, particularly relates to the technical field of communication and data transmission, and aims to solve the problem that the reliability of the remotely acquired data of the electric meter box is verified without changing an existing netmeter and a communication protocol. The invention aims to solve the problem of how to execute cross-layer reviewable reliability verification and quantitative credibility evaluation on a single reading result remotely acquired by an electric meter box so as to identify and eliminate the abnormity that communication is successful but data is not credible in real time, and support source end positioning. By introducing fusion of a cross-layer evidence set and an active detection mechanism, the credibility of each copying and reading result can be comprehensively evaluated. Multi-level data of a physical layer, a link layer, an application layer and the like are verified, and data exception is identified through active detection. Through the mechanisms, the method can effectively eliminate reading results which succeed in communication but have errors in actual data, thereby ensuring that the collected data are more reliable and accurately reflect the actual state of the electric meter.

A device located within a user environment may be used to measure one or more environmental conditions within the user environment. For example, the sensor device may measure the temperature, humidity, light intensity, color temperature, and / or the like. The sensor device may periodically measure the environmental conditions, and may periodically transmit the values of the measured environmental conditions to a computing device. A mobile device associated with a user may receive the measured values from the sensor device when the mobile device is within range of the sensor device, and may present a survey to the user that includes one or more questions that prompt the user to report their comfort level with respect to the measured environmental conditions. The mobile device and / or another computing device may build a profile for the location and / or the user based on the values and the user's reported comfort levels.

The invention discloses an electronic watt-hour meter intelligent data processing system and method based on remote communication, and relates to the technical field of watt-hour meter data processing.The method comprises the steps that windowing management is conducted on electric energy data, data pre-evaluation is conducted at the same time, and data windows needing to be processed are screened out; adjusting infrastructure constraints to reduce the basic capability limitation of decision processing; performing hierarchical judgment on the data window marked as needing to be processed so as to optimize a decision processing level, and performing gap data processing according to a hierarchical judgment result; key data of all electric energy meters and corresponding time periods are collected and analyzed in real time, data portraits of different objects and time periods are constructed, analysis is carried out according to various data anomalies and operation states, various decision parameters are dynamically adjusted, efficient processing and decision optimization of the data of the electric energy meters are achieved, and the data processing efficiency is improved. Therefore, the problem of low accuracy in dynamic statistics and trend analysis of the acquired real-time electric energy data caused by improper decision processing of the data in the prior art is effectively solved.

The invention provides a building equipment monitoring fault point identification method, and relates to the technical field of intelligent building operation and maintenance, and the method comprises the steps: collecting equipment operation data, environment data and video stream data in real time through an edge calculation node, generating a state feature vector through multi-modal fusion processing, and extracting a dynamic trend to calculate a composite feature index; a pre-trained anomaly detection model is used for identifying equipment anomaly behaviors, when the anomaly confidence exceeds a threshold value, an equipment association map (including a physical connection and data coupling relationship) is constructed, a root fault point is positioned in combination with a historical fault library, and a hierarchical alarm signal is generated and pushed to an operation and maintenance terminal; and finally, updating an anomaly detection model (retraining through a negative sample library) and a correlation graph (dynamically adjusting an edge weight) based on operation and maintenance feedback data. According to the invention, the problems of fault identification lagging, high false alarm rate, difficult positioning and low maintenance efficiency in a traditional monitoring mode are solved, and the real-time performance, accuracy and self-adaptability of building equipment operation and maintenance are realized.

The invention discloses a radar station lightning protection device online monitoring method and system based on the Internet of Things, and relates to the technical field of equipment online monitoring. According to the invention, sensors are deployed in each component of the lightning protection device, real-time transmission and integration of monitoring data are realized by using the Internet of Things technology, a health degree evaluation model based on artificial intelligence is constructed, and remote automatic monitoring and health degree prediction of the lightning protection device of the radar station in a remote area are realized; according to the invention, the health degree evaluation model is combined with the correction coefficient to analyze the assembly evaluation data, and the health degree of each component is accurately predicted, so that the lightning protection effect of the lightning protection device is determined; according to the technical scheme, the space-time limitation of traditional manual inspection is broken through, the problem that a lightning protection device of a radar station in a remote area is difficult to monitor is solved, and conversion from passive maintenance to active prediction is achieved; through real-time data acquisition and intelligent analysis, potential hidden dangers of components can be found in advance, so that workers can take measures in time, and the lightning stroke risk is reduced.

The invention relates to the technical field of data processing, in particular to a mine slope intelligent early warning method and system based on dynamic threshold optimization and a medium. Comprising the following steps: acquiring a multi-modal heterogeneous data stream from a sensor network, generating a time sequence data matrix, and sending the time sequence data matrix into a parallel data processing model; the first data processing model executes statistical process analysis to generate a first data set; the second data processing model compares the data with the prediction data set to generate a second data set; fusing the data sets, verifying and judging, and generating a slope data record; when the conditions are met, an optimization process is started; and outputting a state list, storing the state list in a graph database, and performing parameter adjustment on the prediction model. According to the system, heterogeneous data streams are analyzed through a parallel data processing and data fusion method, comprehensive state evaluation is generated, data attribution and model closed-loop optimization are started when conditions are met, high-precision recognition of sudden change and gradual change modes in the data streams is achieved, and the diagnosis depth and the self-adaptive capacity of the analysis system are improved.

The invention provides a metering box state detection and customer electricity utilization information collaborative electricity larceny prevention method, and relates to the technical field of electricity larceny prevention, and the method comprises the following steps: a physical sensor and an electrical sensor are deployed in a metering box and an electricity utilization loop, the physical sensor is used for collecting the state data of the metering box, and the electrical sensor is used for collecting customer electricity utilization information; data of the physical sensor and the electrical sensor are collected in real time, and the collected data are preprocessed and then transmitted to the cloud platform; the cloud platform performs physical anomaly identification on the state data of the metering box and performs electricity consumption anomaly identification on the electricity consumption information of the client; through multiple deployment of the physical sensor and the electrical sensor, the risk that a single sensor is deceived is avoided, through a cooperative verification mechanism of metering box state-electricity utilization information, box opening non-electricity stealing and box-immovable electricity stealing can be effectively distinguished, and through actual verification, the misjudgment rate is greatly reduced, and the missing report rate is controlled within 5%.

The invention provides an electric field variation measuring method and system. The method comprises the following steps: installing a differential electric field sensor in an electric field variation to-be-measured area; collecting and preprocessing electric field change data of the electric field change quantity to-be-measured area based on a differential electric field sensor; based on the preprocessed electric field change data, an electric field change quantity distribution model is established, and a data analysis result is obtained; and generating an electric field variation monitoring report based on a data analysis result. The system comprises a differential electric field sensing module which is used for capturing an electric field change signal in an electric field change quantity to-be-measured area by adopting a differential electric field sensor; the high-precision data processing unit is used for receiving and preprocessing the electric field change signal to obtain electric field change data; the remote communication module is used for realizing real-time remote transmission of electric field change data by adopting a low-power wide area network technology or a wired communication mode; and the intelligent analysis platform is used for receiving the electric field change data, performing comprehensive analysis and generating an electric field change quantity monitoring report.

The invention relates to the technical field of data transmission, and discloses a gas meter information secure transmission method based on response function compensation, which comprises the following steps: collecting multi-source data and network signal quality information of a gas meter; according to a real-time network environment and physical conditions, data transmission parameters are dynamically adjusted through a response function compensation algorithm, when data transmission in a static time slot fails, a dynamic retransmission time slot is automatically allocated for retransmission, a retransmission frequency threshold value is set, and packet loss caused by channel errors or collision is compensated through a retransmission response function; a multi-layer encryption mechanism is adopted to encrypt transmission data, an optimal transmission channel is intelligently selected according to network conditions, adaptive hybrid communication is performed through star flash short-distance communication or Wi-Fi wide-area transmission, and a response compensation mechanism of multi-dimensional environmental parameters is established based on a signal transmission model; transmitting the encrypted data to a monitoring management platform through a secure channel; therefore, safety early warning decision is realized, and dynamic accurate transmission and active safety protection are realized.

The invention discloses a track noise control method and system based on active acoustic control, and the method comprises the steps: collecting a track noise signal through a sensor array, and processing the signal through Fourier transform to obtain a spectrum distribution characteristic; judging the type of a noise source according to the spectral distribution characteristics, if the spectral distribution shows high-frequency dominance, determining the noise as wheel-rail contact noise, and if the spectral distribution shows low-frequency dominance, determining the noise as rail vibration noise, and obtaining a noise source contribution proportion; according to the noise source contribution proportion, a dynamically adjusted control signal is obtained; acquiring noise source coupling information which changes in real time from the dynamically adjusted control signal, and determining a fused noise source model; according to the fused noise source model, a least square method is adopted to optimize a control strategy, and an optimized control instruction sequence is obtained; and according to the optimized control instruction sequence, acquiring matching data of the current operation density and speed, and if the effect does not reach the standard, iteratively updating the model to obtain final control output.

The invention relates to the technical field of flexible electronic sensing, and particularly discloses a composite fiber membrane-based capacitive flexible pressure sensor integrated system and a preparation method thereof. The sensor is composed of a composite fiber membrane sensitive layer, an interlayer type electrode structure, a multi-channel signal acquisition module and an intelligent data processing system. Wherein the composite fiber membrane is prepared through an electrostatic spinning technology, polyvinylidene fluoride serves as a matrix, ionic liquid with the mass ratio of 40%-70% is evenly dispersed, a three-dimensional porous structure is formed, and a pressure signal is converted into capacitance change through the double-electric-layer capacitance effect; the signal acquisition module adopts a high-precision capacitance digital converter to cooperatively work with a microcontroller, 9-channel parallel data acquisition is realized, the resolution reaches 6aF, and data is transmitted through an anti-interference bus protocol; and the data processing system dynamically analyzes the pressure-capacitance relationship based on an exponential function model, suppresses noise to be below 0.1 aF RMS in combination with a filtering algorithm, and synchronously generates a visual pressure distribution map.

The invention relates to the technical field of information acquisition, in particular to an electric power information acquisition method based on dual-mode communication, which comprises the following steps: S1, acquiring multi-dimensional evaluation data of a dual-mode communication channel by an acquisition terminal before an electric power information acquisition task is initiated each time; s2, acquiring task characteristics according to the current network state; according to the invention, through multi-dimensional evaluation and dynamic weight, the success rate of single acquisition is improved, the communication time delay is reduced, only key data is transmitted in a dual-mode concurrent manner, the energy consumption is reduced, the congestion rate of an RF channel is reduced through space-time association and reinforcement learning, the acquisition efficiency in a peak period is improved, and the acquisition efficiency is improved. According to the method, the condition of global degradation caused by local optimization is avoided, through a closed loop of data acquisition-strategy optimization-feedback execution, the method can adapt to long-term changes such as season replacement and equipment aging, and when HPLC interference is increased in winter, the RF priority is automatically improved, manual intervention is not needed, and the operation and maintenance cost is reduced.

The invention belongs to the technical field of water conservancy informatization and automatic control, and discloses an intelligent water conservancy-oriented multi-source hydrological data monitoring and safety early warning system, which comprises a monitoring link for acquiring water level, rainfall, flow velocity, flow and meteorological elements, and acquiring environment information in combination with videos and remote sensing images; the communication processing link supports multi-link transmission and generates an integrity mark for the data; in the data processing link, field mapping is realized based on a unified semantic model, conflict judgment is carried out through a timestamp, an integrity mark and an adjacent monitoring point weighting sequence, and an abnormal mark is generated at the same time; in the digital modeling link, three-dimensional twin models of a river channel, a reservoir and a dam are established, and abnormal factors are written in; in the risk prediction link, a risk assessment result is output in a multi-factor weighting mode; the early warning control link determines a release object based on the three-dimensional permission matrix and executes a boundary rule; and the linkage link issues a scheduling instruction after manual reexamination and confirmation, and feeds back an audit record to the model to form closed-loop correction.

The invention relates to the technical field of ship offset early warning, and provides a ship offset early warning method for a deep-sea mining in-situ pilot production system, which can solve the problem that the existing mother ship offset monitoring mode is too simple, improve the accuracy of judging the position of a ship body and perform effective early warning. Comprising the following steps: S100, establishing an information transmission network and carrying out data acquisition; s200, carrying out coordinate conversion on the collected real-time longitude and latitude information of the ship and the vehicle, and calculating a relative distance between the ship and the vehicle; s300, calculating a ship offset area of the mining system, calculating an allowable offset of a mining ship relative to a mining vehicle, dividing operation states according to the offset, and determining a reasonable ship offset area map; and S400, the ship deviation safety early warning area is built in a system early warning program, monitoring data are read at regular time, monitoring information such as environment monitoring information, ship-vehicle distance and the like and umbilical cable length monitoring information are read in real time, and the ship deviation state is judged in real time according to the ship deviation safety area.

A system including a server and a wireless RF access node connected to a communication network is provided. The server provides a first publish-subscribe broker of one or more publish-subscribe brokers forming part of a publish-subscribe broker network. The server connects to the wireless RF access node. A first entity connects via the wireless RF access node to the first publish-subscribe broker using a unicast IP address and thereafter publishes data packets. A second entity connects to the publish-subscribe broker network via any of the one or more publish-subscribe brokers. The server provides packet distribution services via the first publish-subscribe broker for the first entity, the publish-subscribe broker network routes communications from the first entity to the second entity when the second entity is subscribed; and the data packets published by the first entity are routed through the publish-subscribe broker to which the second entity is connected.

The invention relates to the technical field of industrial Internet of Things and industrial automation monitoring, in particular to an industrial Internet of Things temperature transmitter data low-power-consumption transmission system which comprises a local trend feature extraction unit used for maintaining a sliding time window and solving the change rate and the change acceleration of the current physical process; generating a current model parameter; the virtual shadow prediction unit is used for obtaining a virtual prediction value; the dynamic confidence interval judgment unit is used for generating a dynamic confidence threshold value; comparing the deviation with a dynamic confidence threshold; when the deviation is greater than the dynamic confidence threshold, generating a model failure trigger signal; the model parameterization resynchronization unit is used for constructing the current model parameters into data frames; sending a data frame through a wireless module; writing the current model parameter back to the virtual shadow prediction unit to update the sent parameter; according to the method, the problem that details of a key process are lost due to discretization in a traditional dead zone scheme is effectively solved, and the analysis value of industrial monitoring data is improved.

The invention relates to the technical field of lubricating oil quality monitoring, in particular to a lubricating oil quality on-line monitoring system and method, and the system comprises a data collection module which collects lubricating oil parameters in real time through a sensor array; the communication transmission module is used for constructing a data flow network and supporting multi-level interaction; the data analysis and diagnosis module is used for realizing state evaluation and fault early warning; the user interaction and visualization module provides a human-computer interaction interface and decision support; and the intelligent decision module realizes monitoring-maintenance closed-loop control, gives an alarm in time and realizes full-link intelligent control triggered by a maintenance action. According to the method, the prediction precision and the early warning capability of the degradation trend of the oil system are effectively improved through the improved autoregression moving average model, the real-time state of the oil is accurately reflected by dynamically adjusting the alarm threshold value, and the fault positioning precision is greatly improved through the space matching algorithm.

To provide an image display system or the like capable of grasping a position in a depth direction in a two dimensional image.SOLUTION: There are provided a coordinate acquisition unit that acquires a position of an object as three dimensional coordinates with a depth direction as a first axis, a conversion unit that converts the three dimensional coordinates into a two dimensional image with the first axis and a second axis orthogonal to the first axis as coordinate axes, and a display unit that displays the two dimensional image in a display form according to coordinates of a third axis orthogonal to the first axis and the second axis. The display part displays the two dimensional image in a display color corresponding to the coordinate of the third axis as a display form.SELECTED DRAWING: Figure 1

The invention discloses a multimodal transport cargo transportation state monitoring system based on a standardized intelligent tray group. The system comprises a modular tray group composed of a main control tray and at least one functional tray; the main control tray is integrated with an edge calculator, an RFID reader-writer, a temperature and humidity sensor and a power supply module; the functional tray comprises a strain sensor and an acceleration sensor; the tray groups are rigidly connected through electromagnetic lock catches, and a voltage sensor is arranged to monitor the connection state; the tray group transmits data through a mixed communication channel; LoRa wireless communication is adopted by default, and magnetic attraction wired connection is switched when the packet loss rate is greater than 1%; after being preprocessed by the edge calculator, the data are encrypted by the Beidou system and uploaded to the background server; the background server executes overload and unbalanced load analysis, vibration grade evaluation, environmental risk early warning and lock catch state monitoring; and triggering a user side to give an alarm when an exception is detected. The safety monitoring problem of goods transportation is effectively solved, the transportation safety is improved, and the accident risk is reduced.

The invention provides a metering box electricity larceny detection method, system, equipment and medium under carrier communication, and relates to the field of metering box electricity larceny prevention, and the method comprises the following steps: collecting the three-phase current ICCO, voltage UCCO and freezing electric quantity QCCO of a split-phase protection intelligent circuit breaker, and the current Ij, voltage Uj and freezing electric quantity Qj of an electric energy meter in real time; calculating a correlation coefficient and an average distance between the voltage sequence {Uj} of the electric energy meter and the three-phase voltage sequence {UA, UB, UC} of the circuit breaker, and determining a connection phase of each electric energy meter; the deviation value delta I of the sum of the current ICCO of the circuit breaker and the current Ij of the connected electric energy meter under the same phase is calculated, a line loss model is constructed by combining the freezing electric quantity Qj and the QCCO, and the line loss rate p is solved; and performing three-level electricity stealing judgment, positioning an electricity stealing point and generating an electricity stealing probability Ptheft. Through multi-source data fusion, edge-side autonomous efficient electricity stealing closed-loop judgment and split-phase protection and electricity stealing prevention collaborative optimization, the accuracy of electricity stealing identification and the reliability of power supply are remarkably improved.

A parameter-setting program operates on an information terminal 50 that may perform wireless communication with a combustion device 10. The parameter-setting program may cause the information terminal 50 to execute: processing to cause, when a parameter is to be set for one combustion device 10, the information terminal 50 or an external storage device to store the parameter inputted into the information terminal 50; processing to cause, when, after the storing, the parameter is to be set for another combustion device, the information terminal 50 to display an option to instruct the information terminal 50 to write the stored parameter into the other combustion device 10; and processing to write the stored parameter into the other combustion device 10 when the option is selected.

The invention relates to the technical field of fusion terminals, and particularly provides a fusion terminal data reporting missing rereporting method and system and a medium, and the method comprises the steps: through a reporting task initialization mechanism, when a fusion terminal is started or a task scheme and a table file change, emptying historical data and carrying out initialization again; adopting an acquisition scheme matching strategy based on the matching degree and the interrogation interval to accurately select a target acquisition scheme; in combination with a two-stage compensation mechanism of self-compensation and failure linked list compensation, compensation is scheduled according to protocol timeout in the self-compensation stage, and periodic compensation, forced compensation and redundant data cleaning are executed in the failure linked list stage. Through the above steps, the integrity and reliability of data reporting of the fusion terminal are effectively improved, and the accuracy of collection success rate statistics of the master station is guaranteed.

The invention relates to a test method based on a multi-modal context protocol and a three-stage verification mechanism. The test method comprises the following steps: capturing multi-modal data related to a user operation sequence, system state data and an external event in real time; carrying out multi-modal fusion on the multi-modal data by the MCP engine, and constructing a dynamic context graph; performing three-stage verification based on the multi-modal data and the context graph; dynamically generating a test case, and intelligently adjusting a test strategy; and analyzing and generating repair suggestions. The test case generation efficiency and coverage rate can be improved, manual intervention is reduced, cross-application and cross-system test case migration and execution are achieved, the defect detection rate is increased, the false alarm rate is reduced, the intelligent and automatic test process is provided, the test threshold is reduced, and the test efficiency is improved. The method is especially suitable for intelligent test processes of complex scenes such as financial transactions, industrial control, Internet of Things equipment and the like.

The invention relates to the technical field of coal mine dynamic mine pressure monitoring and intelligent early warning and prediction, and particularly discloses a coal mine dynamic mine pressure monitoring and intelligent early warning and prediction system, which comprises a monitoring terminal layer, which comprises a plurality of mine pressure monitoring sensors, and the mine pressure monitoring sensors are respectively arranged in different monitoring areas of an underground coal mine. The mine pressure parameter acquisition module is used for acquiring mine pressure parameters of a corresponding area in real time, and the mine pressure parameters comprise roof subsidence, support working resistance, coal seam stress and surrounding rock deformation; and the data transmission layer is connected with the monitoring terminal layer and comprises an underground ring network switch and a ground industrial Ethernet. According to the dynamic mine pressure monitoring and intelligent early warning prediction system for the coal mine, the data reliability is ensured in combination with sensor state monitoring, the mine pressure trend in the next 24 hours is accurately predicted by adopting an improved LSTM neural network and an AWA-GC optimization algorithm, and the system adapts to nonlinear changes under complex geological conditions.

Systems and methods for configuring and managing a network device with a transformer model under control of a network control function (NCF) are disclosed. A processor of the NCF receives a request that identifies a network management task and associated service targets. The processor forms a token set of schema-defined tokens that represent network context, applies positional encodings to generate an ordered token sequence, and invokes the transformer model to produce a configuration patch. The configuration patch is validated against a schema-constrained decoder that enforces device grammar and is applied to the target network device. Device state and telemetry are read back to obtain a read-back state, which is evaluated against the service targets. When telemetry deviates, the processor generates a further configuration patch that modifies a bounded subset of parameters relative to the read-back state to restore compliance