560results about "Sub-station arrangements" patented technology

The invention discloses an intelligent monitoring method and system based on the Internet of Things, a medium and a program product, and the method comprises the steps: abstracting a monitoring region into a dynamic graph structure, and obtaining a self-adaptive monitoring scene graph; fusing at least one piece of video data and at least one kind of data of other sensors at each node to form a multi-mode sensing network; carrying out distributed feature extraction on the multi-modal sensing data to obtain data features, and compressing the data features into low-dimensional vectors; constructing a space-time knowledge graph; executing an anomaly detection algorithm on a preset number of spatial scales; matching a corresponding adjustment mode in a preset adjustment scheme according to the type and the degree of the abnormal event, and adjusting the numerical weights of the nodes and the edges to obtain an adjusted adaptive monitoring scene graph; and according to the adjusted adaptive monitoring scene graph and the numerical value weight corresponding to the node, synchronously adjusting the working parameters of all the cameras of the Internet of Things and other sensors. According to the invention, the integrity and comprehensiveness of the monitoring data acquired by the Internet of Things camera equipment are improved.

The invention relates to the technical field of fault detection, and discloses a remote electric energy meter fault detection and identification system and method, and the system comprises a data collection module, a data integration module, a data inspection module, a feature extraction module, a fault analysis module, and a fault alarm module. According to the method, multiple electric energy meter target data are collected and integrated into a corresponding data set, and a complete and ordered data basis is provided for analysis; abnormal values are recognized and replaced by calculating the average value and the standard deviation, the data quality is improved, and the accurate analysis result is guaranteed; key parameters covering multiple aspects are accurately extracted from a data set, and a powerful basis is provided for fault analysis; from metering, hardware and communication fault dimensions, according to comparison of extracted parameters and threshold values, fault types and positions are accurately judged in multiple directions; the fault alarm module remotely transmits an analysis result to a monitoring center, and generates an alarm message containing detailed information such as an electric energy meter number, a fault type, a parameter value, a threshold value and the like when a fault occurs, thereby facilitating timely maintenance by maintenance personnel.

The invention relates to the technical field of intelligent water affair management, and discloses a method and system for dynamically adjusting the reporting moment of an NB water meter, and the system comprises NB water meter terminal equipment which is responsible for collecting water meter data in real time and uploading the data to a data management platform through an NB-IoT network; the data management platform is responsible for receiving, processing and storing data from the plurality of NB water meter terminal devices; the reporting moment adjusting module is used for dynamically adjusting the reporting moment of the NB water meter terminal equipment according to the strategy generated by the data management platform; the communication management module is responsible for communication between the NB water meter terminal equipment and the data management platform; the intelligent alarm and event processing module is responsible for monitoring the running state of the system in real time; and an equipment remote control module. By dynamically adjusting the reporting time, the system can reduce unnecessary frequent reporting, especially in a time period when the water consumption is relatively small or relatively stable, so that the power consumption of the equipment is remarkably reduced. Therefore, the battery life of the NB water meter terminal equipment can be prolonged, and the maintenance cost is reduced.

The invention provides a monitoring point and data classification management method based on an intelligent monitoring platform, and belongs to the technical field of data processing, and the method comprises the steps: 1, importing a preset BIM model into a preset intelligent monitoring platform, and carrying out the analysis of the preset BIM model; 2, creating a monitoring project in a preset intelligent monitoring platform based on a model analysis result, and configuring monitoring project information; step 3, acquiring a monitoring demand matched with the monitoring project, determining the type of a monitoring point, analyzing the information of the monitoring project, and creating a plurality of monitoring points; 4, the monitoring equipment based on the monitoring points collects monitoring data in real time, uploads the monitoring data to a preset intelligent monitoring platform through a network, and automatically associates the uploaded real-time data with the corresponding monitoring points; and 5, analyzing the real-time data, and optimizing the deployment of the monitoring points and the data of the monitoring points. And an efficient and intelligent solution is provided for application scenes such as engineering monitoring and environment monitoring.

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 provides a concentrator efficient data acquisition optimization method and system. The method belongs to the technical field of electric power communication, and comprises the following steps: setting each reading task as an exclusive task or a parallel task, performing priority distribution on the reading tasks, and introducing a state machine for executing a first reading task, namely a to-be-read data task configured by a main station; after a system is started, whether exclusive tasks exist in a task pool or not is judged firstly, and if yes, all the exclusive tasks are executed according to a priority sequence; and after the execution of the exclusive task is completed, obtaining all parallel first copying and reading tasks in the task pool, performing parallel execution through a task scheduling mode of the state machine, and obtaining corresponding to-be-copied data items. By setting the reading task as the exclusive task or the parallel task and performing priority allocation, system resources can be utilized more efficiently, and the data acquisition efficiency is 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 discloses a lightning arrester data monitoring method and system for optimizing LoRa networking. The lightning arrester data monitoring method and system are used for effectively monitoring a lightning arrester. The method is applied to a lightning arrester data monitoring system. The system comprises a LoRa lightning arrester detection node module, a LoRa-GPRS concentrator gateway module, a remote control platform module, a field lightning arrester control terminal module and a circuit switch remote controller. The method comprises the steps that a LoRa lightning arrester detection node module monitors operation data of a lightning arrester and sends the operation data to a LoRa-GPRS concentrator gateway module through LoRa; the LoRa-GPRS concentrator gateway module receives the operation data and sends the operation data to the remote control platform module through a GPRS network; the remote control platform module performs data analysis on the operation data so as to judge the operation state of the lightning arrester; and the LoRa-GPRS concentrator gateway module performs information interaction with the field lightning arrester control terminal module through a CAN network, so that the field lightning arrester control terminal module processes the lightning arrester by using the circuit switch remote controller according to the operation state.

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 water treatment, and discloses a remote monitoring operation and maintenance system and method for water treatment equipment, and the system comprises a hypersensitive composite sensor matrix module, an intelligent edge collector module, a hybrid ad hoc network transmission module, a collaborative data processing center module, a cloud fusion computing platform module and a strategy generation module. By implementing the system and the method, water quality parameters, equipment operation pressure parameters and vibration signal parameters are collected in all directions, intelligent operation and maintenance management of water treatment equipment is realized, and stable operation and efficient treatment capacity of a wastewater treatment system are effectively guaranteed. The problems of how to accurately monitor the water quality change and the equipment operation state and how to carry out deep analysis and effective utilization based on data such as water quality, energy consumption and equipment operation are solved, so that the treatment process is optimized, and the energy consumption is reduced.

A first device for monitoring products repeatedly carries out a sensing step via a sensor and stores the result of sensing, time data, and status data in a storage unit. The first device conducts transmission via a first communication network whereby a first data set that includes transmission data identifying the transmission, first ID data identifying the first device, and sensing data of the associated time data is transmitted. The first device links the transmission ID data to the respective transmitted sensing data, and receives acknowledgement data sets that include transmission ID data identifying one of the transmissions conducted by the first device. The first device sets the transmission status of sensing data to “ready” upon storing the respective sensing data; and to set the transmission status of sensing data to “acknowledged” upon receiving an acknowledgement data set which comprises transmission ID data linked to the respective sensing data.

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 discloses a remote water meter reading method and system and electronic equipment, and particularly relates to intelligent water meter fault analysis, which comprises the following steps: acquiring water meter monitoring data of n intelligent water meters according to an electric signal, and generating a water meter monitoring coefficient based on the water meter monitoring data; the water meter monitoring data comprises actually measured fluctuation data and preset standard fluctuation data; extracting a water meter monitoring coefficient time sequence set of the nth intelligent water meter, inputting historical water meter monitoring coefficients in the water meter monitoring coefficient time sequence set into a pre-constructed first deep learning model, and predicting water meter monitoring coefficients at a future T moment; according to the invention, correct water meter monitoring data can be sent to the intelligent water meter, the abnormal intelligent water meter and the fault reason can be found quickly based on the water meter monitoring data, water management personnel can arrive at the corresponding position of the abnormal intelligent water meter in time, and the abnormal intelligent water meter can be repaired or replaced quickly according to the fault reason of the abnormal intelligent water meter. And the loss caused by the abnormal intelligent water meter is reduced.

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 relates to the technical field of data monitoring, in particular to a concentrator data acquisition method and device, equipment and a medium. The method comprises the following steps: collecting monitoring data received by a concentrator; classifying the monitoring data into a plurality of groups of data according to the acquisition equipment, wherein each group of data corresponds to one acquisition equipment; determining a device type corresponding to the target data set, and inputting the target data set into a preset recognition model corresponding to the device type to obtain a recognition result about whether the target data set output by the preset recognition model is abnormal, the target data set being any one of multiple groups of data; if the identification result is that the target data group is abnormal, analyzing an abnormal reason; and generating a warning signal containing the abnormal reason, and sending the warning signal to terminal equipment corresponding to the related personnel. According to the invention, the data exception of the concentrator can be identified in time.

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.

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 belongs to the technical field of measurement equipment, and particularly provides a temperature and humidity measurement device and method based on active identification communication, a terminal and a storage medium, and the device comprises a temperature collection element, a humidity collection element, a control module, an active identification module, a communication module, a measurement server, and a power supply module for supplying power to the whole device. The temperature acquisition element and the humidity acquisition element are both connected to the input end of the control module, the active identification module is connected to the control module, and the control module is connected to the measurement server through the communication module; by introducing the active identification module, the device realizes active identification coding and encryption processing of temperature data and humidity data, ensures uniqueness and security of the data in a transmission process, and effectively prevents data tampering and stealing. Meanwhile, dependence on a third-party platform is reduced, complexity and uncertainty of data transmission are reduced, and reliability and stability of data transmission are improved.

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.