377results about "Sub-station arrangements" patented technology

The invention discloses an efficient distributed multi-source data acquisition method, which realizes efficient acquisition of large-scale multi-source data by identifying and classifying multi-source data, reasonably deploying distributed acquisition nodes and formulating an intelligent acquisition strategy. Firstly, data sources are grouped according to characteristics such as types, formats and updating frequencies; then deploying a plurality of acquisition nodes in the network and cooperating through an efficient communication protocol; making an intelligent acquisition strategy according to the characteristics of the data source, for example, performing real-time acquisition on a high-update-frequency data source and the like; the acquisition nodes pre-process and fuse the data and then transmit the data to the central storage system through a safe and efficient transmission channel. Meanwhile, an acquisition strategy is continuously optimized by monitoring and analyzing an acquisition process index. The method improves data acquisition efficiency, reduces resource consumption, enhances reliability, has good expansibility, can be widely applied to various scenes needing multi-source data acquisition, remarkably reduces acquisition cost, and improves data acquisition efficiency and quality.

The invention discloses an intelligent industrial wastewater treatment method based on edge calculation and multi-modal data fusion, which comprises the following steps: synchronously acquiring various data of an industrial wastewater treatment site through edge nodes, automatically adjusting and aligning the generation time of each data, and ensuring that the time error of different data is less than a set threshold value; organically fusing the image features, the chemical parameters and the component analysis report to generate pollutant description features; constructing a simplified simulation model on the edge equipment, and predicting the diffusion trend of the wastewater pollutants by using the simulation model based on the pollutant description characteristics; and when the network is interrupted, the edge equipment is automatically switched to a local mode, and the operation is continued by using the stored model and the wastewater data acquired in real time. According to the method, the simulation model is deployed through the edge equipment, so that the calculation amount can be greatly reduced, the diffusion trend of wastewater pollutants can be accurately predicted, effective treatment measures can be taken in time, and the stability and reliability of an industrial wastewater treatment system are improved.

The invention relates to the technical field of construction intelligent monitoring, in particular to a building construction remote intelligent monitoring system based on 5G telephone communication and edge computing. Comprising an on-site sensing unit; the edge processing unit is used for realizing accurate integration of heterogeneous data through an improved self-adaptive weighted fusion algorithm and generating a real-time control strategy in combination with a working condition dynamic model; the 5G communication unit is combined with predictive slice scheduling and a multi-mode anti-interference protocol; and a remote monitoring unit. The industrial-grade sensor array is adopted to collect related data, a monitoring data stream with a timestamp and marked with an abnormal identifier is generated, meanwhile, an edge processing unit complements abnormal data through a data preprocessing module, heterogeneous data integration is achieved through an improved self-adaptive weighted fusion algorithm, and the data processing efficiency is improved. According to the method, the problems that the data processing architecture and the construction multi-source data characteristics are insufficient in adaptation and data validity tracing is missing are effectively solved, and effective tracing and accurate integration of the construction scene multi-dimensional monitoring data are achieved.

The invention provides an intelligent gas meter remote meter reading method and system based on the Internet of Things, and relates to the technical field of intelligent gas meters. The method comprises the following steps: collecting local metering data and Internet of Things transmission data; constructing a dual-source data multi-dimensional conflict identification system, and screening conflict data groups; performing accuracy verification on the conflict data group; an encrypted transmission channel is established, and the traceability of the data transmission process is realized; triggering a grading early warning mechanism for the abnormal usage data deviating from the baseline; and carrying out iterative updating on the meter reading data knowledge base, and carrying out remote calibration. According to the method, double-source data conflicts are identified through multiple dimensions, conflict data are corrected in combination with a hybrid model, metering accuracy is guaranteed, and disputes are reduced; through constructing a baseline model and a grading early warning mechanism, abnormal usage is accurately identified and disposed, hidden dangers are timely prevented, and service is excellent. Through dynamic on-demand remote calibration of equipment, the metering precision is guaranteed, the operation and maintenance cost is reduced, the user data transparency is improved, and intelligent gas management is assisted.

The invention discloses an intelligent measurement terminal-based electric energy meter protocol detection and meter reading method, which relates to the technical field of electric energy meter verification, and comprises the following steps of: 1, preparing a 645 detection message containing multiple data items; step 2, sending a detection message to the electric energy meter; 3, receiving a check reply message, determining the protocol type of the electric energy meter, and storing detection parameters; 4, preparing an electric energy meter 645 reading message according to the electric energy meter protocol type; and step 5, detecting the changed electric energy meters in the transformer area and updating detection parameters. According to the detection method, the execution of a periodic meter reading task of the intelligent measurement terminal is not influenced, the accuracy and timeliness of a detection result can be ensured by active periodic detection and emergency detection, and the high-efficiency meter reading characteristic of a DL / T645-2021 protocol electric energy meter and the high-performance advantage of the intelligent measurement terminal are fully utilized by performing sub-protocol meter reading based on the detection result.

The invention relates to the technical field of data processing, in particular to an efficient transmission method for electric energy meter acquired data, which comprises the following steps: acquiring multi-dimensional feature data of an electric energy meter at each moment, and obtaining multi-dimensional real-time feature data at the current moment and a multi-dimensional historical feature data sequence within a preset historical time period; using an isolated forest algorithm to randomly select sample points to form at least one sample subset, for any sample subset, obtaining the abnormal degree of each sample point in any sample subset under each feature, obtaining a segmentation condition under each feature according to the abnormal degree, and generating an isolated tree; obtaining a normal weight of each path in the isolated tree according to fluctuation features of sample points in a sample subset corresponding to the isolated tree and differences between the sample points and the multi-dimensional real-time feature data; and the final score is obtained by using the normal weight of each path in each isolated tree, and the adjustment frequency is obtained according to the final score, so that the interference of non-system abnormal data such as noise on frequency adjustment is effectively reduced.

The invention relates to a tunnel crack monitoring method, system and device and a medium, and belongs to the technical field of tunnel monitoring, and the monitoring method comprises the steps: obtaining a three-dimensional model and a geological parameter library of a to-be-monitored tunnel, and constructing a sensor network topology structure; deploying a sensor network based on the sensor network topology structure; receiving static strain data and dynamic vibration data, collected by the sensor network, of each monitoring point in the tunnel; performing space-time alignment on the static strain data and the dynamic vibration data, eliminating environmental interference based on a pre-trained noise spectrum feature library, and generating a cleaned structured data table; extracting a strain gradient characteristic value and a dynamic chaos characteristic value in the structured data table, inputting the strain gradient characteristic value and the dynamic chaos characteristic value into a multi-stage classification model for crack type identification and risk grade evaluation, and generating a crack risk grade map; and generating corresponding maintenance prompt information according to the crack risk grade map. According to the invention, the comprehensiveness and accuracy of tunnel monitoring can be improved.

The invention provides a structural engineering bearing capacity field detection method, and belongs to the technical field of structural engineering detection.The structural engineering bearing capacity field detection method comprises the steps that a multi-axial acceleration sensor and a strain gauge array are installed on the surface of a to-be-detected structural member, and an intelligent loading device is adopted to apply incremental loads; a mobile data acquisition terminal is utilized to acquire vibration response data and strain response data in real time, modal parameters are extracted based on a frequency domain analysis method to establish a load-modal parameter relation curve, the bearing capacity of a component is analyzed and calculated, a graph theory shortest path algorithm is adopted to optimize load transmission path analysis, and the load transmission path analysis is optimized. The bearing performance of the component is accurately evaluated through the structural response prediction model based on the Transform architecture, the technical integration of multi-dimensional detection data fusion, intelligent loading control, quantitative bearing capacity evaluation and accurate performance prediction is realized, and the technical problem of insufficient detection precision of the bearing capacity of the structural component is solved.

The invention relates to the technical field of cloud computing monitoring, in particular to a water consumption monitoring system based on a cloud platform, which comprises a data trend identification module, a water consumption transmission scheduling judgment module, a water consumption interval reconstruction module, a user behavior identification module and a scheduling feedback correction module. According to the method, by introducing a sequence matching strategy of a timestamp and a flow value, the recognition precision of continuous flow change is improved, terminal grouping and amplitude consistency screening are combined, the trend sequence stability is enhanced, short-time fluctuation interference is reduced, extreme value positioning and state segmentation processing are utilized, and multi-level sensing of water volume change is achieved; flow map features are enriched, the time sequence and behavior start-stop information are fused to identify the offset state, the response ability to water consumption mode changes is improved, a dynamic allocation mechanism is constructed through response codes and transmission features, channel resource allocation is optimized, and the data processing and resource response efficiency of the system in an abnormal state is improved.

The invention relates to the technical field of data acquisition, in particular to a data acquisition system based on edge computing, which comprises a sensor module, an edge computing module and a cloud server module, the sensor module is composed of various types of sensors, and the edge computing module comprises a data preprocessing unit, a data analysis unit and a data caching unit. The data analysis unit analyzes the preprocessed data in real time based on a preset analysis model, data feature extraction and pattern recognition are carried out, and the data caching unit is used for temporarily storing the analyzed key data and analysis results. According to the data acquisition system based on edge computing, real-time preprocessing, feature extraction, mode recognition and other operations are performed on the acquired data at the edge computing node, a simple decision task can be quickly judged, and once the equipment temperature exceeds a preset threshold value, the data can be quickly acquired. The edge computing node can immediately perceive and notify the production control system to take cooling measures, so that delay caused by data transmission to the cloud for processing is avoided.

The invention discloses a water supply control system based on an Internet of Things water meter and a management platform thereof, and relates to the field of water supply system adjustment, and the system comprises an Internet of Things water meter module, a multi-sensor module, a data processing module, a transmission fusion module and cloud equipment. The NB-IoT module and the LoRa module are subjected to data distribution through the transmission fusion module, the reliability and the real-time performance of data transmission of the water meter of the Internet of Things are improved, and the preprocessing module is used for conducting denoising, data repairing and other processing on all data subsets in the NB-IoT module in the initial stage; a proper compression algorithm is matched through a dynamic compression module according to intervals of data subsets, a dynamic distribution transmission module constructs a distribution model of multi-data subset optimization transmission, and for simultaneous transmission of a large number of Internet of Things water meter data, it is guaranteed that transmission of multiple Internet of Things water meters is rapid and synchronous, and the transmission efficiency is improved. And rapid and accurate judgment and effective management of the system on fault problems are improved.

The invention discloses an underground pipe gallery real-time state dynamic monitoring method and system based on multi-source data fusion, and relates to the technical field of state monitoring, and the method comprises the steps: obtaining a monitoring point set of an underground pipe gallery, and monitoring the monitoring point set; performing real-time risk identification, determining a risk real-time receiving data set and a risk monitoring point set, then performing causal traceability, and determining a traceability clue cluster; by taking the traceability clue cluster as an index, clue extraction is carried out, a traceability receiving data sequence cluster is determined, time sequence iteration trend risk authentication is carried out, and a risk trend feature cluster is determined; and determining a first dynamic monitoring frequency and a second dynamic monitoring frequency, and distributing the first dynamic monitoring frequency and the second dynamic monitoring frequency to the state monitoring terminal to monitor the monitoring point set. The technical problem that the real-time state monitoring frequency of the underground pipe gallery is fixed and cannot be dynamically adjusted according to the risk change in the prior art is solved, and the technical effects that the monitoring frequency is adaptively adjusted along with the risk state, and the monitoring accuracy and the response timeliness are improved are achieved.

A smart circuit breaker may provide a smart-circuit-breaker power monitoring signal that includes information about power consumption of devices connected to the smart circuit breaker. The smart-circuit-breaker power monitoring signal may be used in conjunction with power monitoring signals from the electrical mains of the building for providing information about the operation of devices in the building. For example, the power monitoring signals may be used to (i) determine the main of the house that provides power to the smart circuit breaker, (ii) identify devices receiving power from the smart circuit breaker, (iii) improve the accuracy of identifying device state changes, and (iv) train mathematical models for identifying devices and device state changes.

The invention discloses a multifunctional intelligent controller based on real-time parameters, which belongs to the technical field of instrument intelligent control and consists of a core processing unit, a multi-sensor interface module, a communication module, a remote maintenance module and a power management module. The core processing unit is integrated with a high-performance microprocessor and a real-time operating system to realize multi-task scheduling of data acquisition, processing, storage and the like; the multi-sensor interface module dynamically matches sensor types to guarantee stable connection; the communication module supports various wireless and wired communication, so that remote maintenance and OTA upgrading are facilitated; the remote maintenance module constructs a two-way communication link based on the cloud platform to ensure data security; the power management module adopts dual-mode power supply, a detachable structure realizes mode switching, and portability and stability are both considered. The controller can be compatible with various instruments, supports multi-parameter synchronous measurement, achieves automatic calibration, effectively solves the problems of an existing instrument controller, and is widely applied to the fields of industrial automation, instrument monitoring and the like.

A sensing system includes a sensor, a wireless transmission system, a wireless receiver system, and a controller. The sensor is configured to determine sensor data, the sensor data associated with a sensing environment. The wireless transmission system is configured to wirelessly couple with the sensor, the wireless transmission system configured for wirelessly providing significant electrical energy to the sensor as wireless power signals and receive the sensor data as in-band data signals encoded in the wireless power signals. The wireless receiver system is operatively associated with the sensor and with which the wireless transmission system couples with the sensor and is configured to receive the significant electrical energy as the wireless power signals from the wireless transmission system. The controller is operatively associated with the wireless transmission system and is configured to decode the in-band signals from the wireless power signals as the sensor data.

The invention discloses a pressure monitoring method and system based on a power transmission cable axis sensor, and belongs to the technical field of data transmission, and the method comprises the steps: S1, a sensor module collects cable traction data and self position data at a measurement time point, and transmits the data to a monitoring module through a relay module; the monitoring module generates adjustment data based on the traction force data, wherein the adjustment data comprises an adjustment numerical value and an adjustment time point; s2, the cloud storage module obtains the data sequence and verifies the data sequence, and if verification is passed, the step S3 is executed; s3, analyzing the adjustment data, if an analysis result does not meet a preset rule, extracting an adjustment time point, and defining the adjustment time point as an abnormal time point; and S4, a marking module obtains a measurement time point which is located after the abnormal time point and is closest to the abnormal time point, obtains corresponding position data based on the measurement time point, and marks an indication label. According to the invention, a manager can remotely supervise the cable laying process.

The invention discloses an electric energy acquisition terminal based on a distributed database, and relates to the technical field of intelligent power grid management. The electric energy acquisition terminal based on the distributed database comprises an intelligent electric meter; an electric energy data acquisition module; an electric energy transmission delay evaluation module; and an electric energy data verification module. According to the method, after initial acquisition electric energy data is pre-screened, data quality verification and compliance verification are executed, whether qualified acquisition optimization is carried out or not is judged, then electric energy transmission delay evaluation is carried out, and whether electric energy data delay evaluation result optimization is carried out or not is judged; and finally, performing electric energy data verification and storage evaluation, and judging whether to perform electric energy data calibration storage optimization or not, thereby achieving the effect of improving the accuracy in the electric energy data acquisition process based on the distributed database. The problem that in the prior art, the accuracy is low in the electric energy data acquisition process based on a distributed database is solved.

The present invention relates to the technical field of node online monitoring, in particular to an edge computing-based intelligent multi-node online monitoring method and system. The monitoring method comprises: using sensors to acquire data of network nodes; on the basis of an edge computing method, performing data processing and analysis on the acquired data; and by means of the principle of magnetic induction, performing online monitoring of intelligent nodes. The present invention uses a highly-efficient sensor data acquisition module to accurately and stably acquire data of network nodes; by means of using the edge computing technology, the present invention reduces the data transmission delay, and improves the real-time performance of monitoring; by means of using the principle of magnetic induction, the present invention achieves accurate monitoring of node status within an intelligent-node online monitoring module; and comprehensively using the sensor data acquisition module, an edge computing and data processing and analysis module and the intelligent-node online monitoring module achieves cooperative intelligent online monitoring of multiple nodes.

The invention discloses a data acquisition interaction method of an electric energy meter data terminal. The data acquisition interaction method comprises the steps of instruction awakening and parameter initialization, dynamic sampling of environment perception, anomaly detection driven by spatial-temporal characteristics, multi-path quantum-classical hybrid encryption transmission and feedback retransmission and cache synchronization. According to the method, the sampling frequency is dynamically adjusted by fusing power load and environmental fluctuation data, a Mixer-Transform architecture is adopted to extract spatial-temporal characteristics, an abnormal threshold is updated in combination with EWMA, quantum or national secret encryption is selected according to a path quality score, fragmented parallel transmission is carried out, and hierarchical cache synchronization is carried out according to data timeliness. According to the method, the sudden change response speed is increased, the abnormal false alarm rate and the transmission packet loss rate are reduced, the data synchronization delay after network recovery is reduced, and the method is suitable for accurate acquisition and secure transmission of electric energy data in a complex environment.

A smart circuit breaker may provide a smart-circuit-breaker power monitoring signal that includes information about power consumption of devices connected to the smart circuit breaker. The smart-circuit-breaker power monitoring signal may be used in conjunction with power monitoring signals from the electrical mains of the building for providing information about the operation of devices in the building. For example, the power monitoring signals may be used to (i) determine the main of the house that provides power to the smart circuit breaker, (ii) identify devices receiving power from the smart circuit breaker, (iii) improve the accuracy of identifying device state changes, and (iv) train mathematical models for identifying devices and device state changes.

The invention discloses a safety monitoring system and method based on multi-modal data fusion, and relates to the technical field of safety monitoring, the system comprises a monitoring center, the monitoring center is in communication connection with a multi-source data acquisition module, a data processing fusion module, a safety evaluation module and an emergency response module; a plurality of acquisition point locations and a plurality of types of sensors are arranged through a multi-source data acquisition module, and then a sensor contact network is formed to acquire multi-source sensing data; performing data denoising and data correction on the multi-source sensing data through a data processing fusion module, and fusing the multi-source sensing data to generate a fused data set; performing mode recognition through a safety evaluation module, and further identifying a real-time environment state associated with the current fusion data set; and an emergency report is generated through the emergency response module and corresponding emergency measures are triggered, so that efficient and accurate safety monitoring is realized.

The present invention relates to the field of water treatment technology, and discloses a remote monitoring and operation and maintenance system and method for water treatment equipment. The system includes: an ultra-sensitive composite sensor matrix module, an intelligent edge collector module, a hybrid self-organizing network transmission module, a collaborative data processing hub module, a cloud-based fusion computing platform module, and a strategy generation module. By implementing the present invention, water quality parameters, equipment operating pressure parameters, and vibration signal parameters are collected in all directions, and intelligent operation and maintenance management of water treatment equipment is realized, effectively ensuring the stable operation and efficient processing capacity of the wastewater treatment system. The problem of how to accurately monitor water quality changes and equipment operating status, and to conduct in-depth analysis and effective utilization based on water quality, energy consumption, equipment operation and other data, thereby optimizing the treatment process and reducing energy consumption is solved.

An apparatus for transmitting telemetry through an external interface is disclosed. An integrated circuit includes at least one interface circuit configured to communicate on an external interface of the integrated circuit with a plurality of other integrated circuits. The integrated circuit further includes a first control circuit coupled to the at least one interface circuit, a first table circuit. The first control circuit is configured to store telemetry data transmitted by the plurality of other integrated circuits over the external interface in respective table entries of the first table circuit, based on which of the plurality of other integrated circuits transmitted the telemetry data.

The invention discloses a combustible gas remote monitoring management system and method based on Internet of Things and AI, and relates to the technical field of combustible gas monitoring. The system comprises a source heterogeneous sensing module, an edge AI reasoning module, a networking communication transmission module, an AI collaborative decision-making module and a judgment collaborative response module which run in sequence, and is technically characterized in that the AI collaborative decision-making module driven by a user behavior portrait is adopted in the scheme, and multi-dimensional characteristic factors are introduced, so that the dynamic sensing of abnormal gas consumption behaviors is realized, and the dynamic sensing of the abnormal gas consumption behaviors is realized; in addition, the understanding is completed by configuring an overrun protection item, it is ensured that sudden leakage and other situations are not missed to a certain extent, the defect that a traditional pure data driving model lacks interpretability and real-time performance is overcome, historical behavior contexts and real-time physical states are fused and bound, and collaborative optimization processing on safety and experience effects is completed.

The invention relates to the technical field of electric energy meter connectors, and particularly provides a state monitoring method of an electric energy meter connector and the electric energy meter connector. According to the method, early warning grading is carried out based on temperature data at a connector plug, a dynamic safety threshold value at the current moment, a temperature change rate and a temperature trend; the state monitoring result of the connector is determined based on the early warning level, the fault type and the residual life, the dynamic safety threshold is determined according to the real-time current data flowing through the connector and the real-time environment temperature, and the temperature trend and the temperature change rate are determined based on the sliding window strategy and the 3 sigma principle; the fault type is determined according to the temperature data, the current data and the historical data, and the residual life is predicted according to the temperature data and the time data corresponding to the temperature data. The problem that the operation state of the electric energy meter connector cannot be monitored in real time in the prior art is solved.

The safety systems for commercial blasting operations include wireless transmitter system(s) configured to send command signals wirelessly to wireless devices that are configured for wireless electronic blasting (web). The system also includes disable antenna(s) that define deactivation zone(s): vehicle / personnel presence detector system(s) including detectors that define detection zone(s), and / or RFID scanner system(s) with reader antennas that defined scanner zone(s); and a safety control system in electronic communication with the wireless transmitter system(s), and the vehicle / personnel presence detector systems and / or the RFID scanner systems, wherein the safety control system is configured to control the wireless transmitter systems to send wireless disable command(s) to disable the wireless devices that are within the deactivation zones, and / or to control alarm system(s) to generate alarms, in response to a vehicle / person being detected in the detection zones and / or a wireless device being detected in the scanner zones.

The invention provides a construction equipment energy-saving management system and method for building construction, and the system comprises a data collection module which is used for collecting the monitoring data of building construction equipment in real time according to a preset time period; the equipment management strategy generation module is used for transmitting the monitoring data of the building construction equipment to the monitoring terminal for identification and analysis, and outputting an equipment management strategy of the building construction equipment according to an identification and analysis result; and the management control module is used for reading the equipment management strategy, determining a management instruction for each piece of building construction equipment, and performing management control on the corresponding building construction equipment based on the management instruction. According to the energy-saving control method, the working effect of the building construction equipment is not affected, meanwhile, a large amount of energy resources are saved, the accuracy and reliability of energy-saving control over the building construction equipment are guaranteed, the intelligence of energy-saving control and the energy utilization rate are improved, and the energy-saving control effect is guaranteed.

The invention provides an intelligent gas unmanned inspection method and system based on the Internet of Things, the method is executed by a government safety supervision management platform of the intelligent gas unmanned inspection system based on the Internet of Things, and the method comprises the following steps: obtaining area data of a management area; based on the area data and the traffic data of the management area, whether the management area is determined as a to-be-inspected area is judged; in response to determining the management area as a to-be-inspected area, determining inspection parameters of the to-be-inspected area; the inspection parameters are related to at least one of pipeline monitoring equipment, detection personnel and unmanned inspection equipment; and sending the inspection parameters to a government safety supervision object platform to control at least one of pipeline monitoring equipment, detection personnel and unmanned inspection equipment so as to complete inspection of the to-be-inspected area. Through the above method, polling can be completed in a more targeted and timely manner, so that the polling result is more reliable, and smooth proceeding of subsequent troubleshooting is facilitated.