19results about How to "Reduce delivery pressure" patented technology

This invention provides a method and system for distributing I / O across SAS expanders between a controller and a disk. The method includes: an ITS module retrieving I / O requests from an I / O request queue and encapsulating them into SCSI commands; selecting a target device address; selecting the local expander channel address for odd-numbered slots and the peer expander channel address for even-numbered slots; the SAS driver transmitting the SCSI command to the local expander via the SAS bus; the local expander selecting the corresponding channel for transmission based on the SAS address encapsulated in the SCSI command; and when the local expander fails to distribute the I / O, it returns a corresponding I / O error to the ITS module, which modifies the SAS address in the SCSI command to the corresponding channel address on the peer expander and re-distributes the I / O. This invention provides a method and system for distributing I / O across SAS expanders between a controller and a disk, allowing I / O to be distributed to the storage disk via the expander belonging to the peer controller when I / O distribution between the current controller and the expander / storage disk fails.

The application discloses an e-commerce platform consumer behavior prediction method based on edge computing, comprising the following steps: collecting the behavior event flow of consumers in the e-commerce platform at the corresponding edge node of user access, and performing preprocessing; constructing a session state feature vector; constructing a local behavior transition graph for a micro-session segment and performing timing diagram coding on the local behavior transition graph; aligning and calculating the local behavior representation vector with a long-term preference anchor point set; generating a state digest based on an edge side prediction network and a collaborative routing indication value, and sending the state digest to a cloud node; the cloud node performs collaborative prediction in combination with the historical behavior characteristics stored in the cloud; collecting real behavior feedback of the edge side prediction result or the cloud prediction result to obtain difficult samples, generate a parameter correction amount or an anchor point correction amount, and write back to the edge node. The edge collaborative prediction realizes accurate identification of consumer behavior.

The application discloses a kind of based on thing networking's wisdom building energy consumption management and equipment monitoring system, belong to building intelligent management technical field.System uses layered distributed architecture, is composed of perception layer, network transmission layer, edge computing layer, platform application layer, terminal control layer;Perception layer realizes energy consumption, equipment, environmental global data acquisition, network transmission layer uses wired wireless dual-mode communication to guarantee data transmission, edge computing layer realizes local instant processing and emergency control, platform application layer realizes cloud big data analysis, visual management, intelligent strategy generation, terminal control layer realizes equipment automation regulation and control.The application overcomes the defects of traditional building management energy consumption waste, operation inefficiency, data isolation, insufficient intelligence, can realize building energy consumption accurate measurement, dynamic analysis, intelligent regulation and control, equipment full period monitoring, fault early warning, automation operation, effectively reduce building energy consumption, reduce operation cost, improve operation safety, applicable to various office buildings, shopping malls, communities, parks and other buildings, with excellent novelty, creativity and practicality, meet the development needs of green low-carbon building.

The application provides a medical institution safety production dynamic evaluation method and system based on multi-source heterogeneous data fusion, and is applied to the field of data processing. The application first collects multi-source heterogeneous full-dimensional data of equipment operation, environment monitoring, personnel operation, fire safety, logistics energy consumption and business process, realizes standardized conversion through cleaning, normalization and feature extraction, completes data deep coupling through weighted fusion, space-time correlation analysis and deep learning, and forms a fusion data set. Then, according to risk identification, grade determination and trend prediction, three-dimensional correlation nodes are constructed in layers, and a safety feature correlation system is established; combined with the analytic hierarchy process and fuzzy comprehensive evaluation modeling, core features are extracted, and a safety feature vector is generated. Relying on the edge-cloud collaborative engine, real-time updating, early warning and iterative optimization are completed, and through accuracy verification and dynamic correction, the final dynamic evaluation result supporting fine safety management and active risk prevention and control is formed.

The invention discloses a multi-stage oil fume and peculiar smell purification device for the catering industry, and belongs to the technical field of oil fume purification devices.The multi-stage oil fume and peculiar smell purification device comprises an air suction adjusting mechanism, the air suction adjusting mechanism comprises a double-shaft motor fixed to a conical air pipe, and one end of an output shaft of the double-shaft motor extends to a first blade in the conical air pipe; the outer wall of the first bevel gear is in meshing transmission with a second bevel gear which is fixed on the movable shaft; one end of the movable shaft is connected to a cam, the inner wall of the cam is connected with a telescopic end through a first spring, the outer wall of the telescopic end on the cam movably abuts against a lifting plate, and the lifting plate is connected with the side wall of the shell through a second spring. The technical problems that single pipeline arrangement can accelerate the attachment speed of oil fume in the device, the working load condition of the device is also aggravated, and long-time safe use of the device is not facilitated can be solved.

This invention discloses a method for sensing the operational status of a distribution network, relating to the field of distribution network monitoring and intelligent operation and maintenance. The method includes: synchronous acquisition of multi-source ubiquitous data to construct a low-cost ubiquitous sensing network; edge-side data preprocessing and lightweight analysis; topology-adaptive multi-source data fusion: constructing a distribution network topology map based on neural networks and mining the spatial and temporal correlations of multi-source data; multi-dimensional quantitative assessment of operational status: constructing a multi-dimensional status assessment system; precise fault location and hierarchical early warning: fusing multi-terminal information to achieve precise fault location; and online model iteration and closed-loop optimization. This distribution network operational status sensing method, by employing a low-cost ubiquitous sensing network combined with dedicated sensors and non-intrusive monitoring, covers the entire distribution network—from source to grid to load to storage—solving the problems of large blind spots and high deployment costs associated with traditional sensing methods. It achieves effective monitoring of end nodes and branch lines, realizing the goal of full-area, blind-spot-free sensing.

The embodiment of the invention relates to the technical field of computers, and provides a data acquisition method and electronic equipment, a first application and a first test tool are installed on the electronic equipment, and the first application comprises a reflection proxy service and a reflection interface. The electronic device determines a first reflection parameter through a reflection proxy service in response to a first data request of a first test tool. Wherein the first data request is used for requesting to obtain feature data of the first object, and the first reflection parameter comprises an identifier of the first object. Then, the electronic equipment transmits the first reflection parameter to the reflection interface through the reflection proxy service, the reflection interface is called to obtain first data generated by operation of the first application, and the first data comprises feature data of the first object; finally, the electronic device returns the first data to the first test tool through the reflective proxy service. Through the method, the complexity of cross-process communication interaction can be effectively reduced, and the data acquisition efficiency is improved.

The application discloses a multi-region power system event-triggered load frequency safety control method and system, and the technical scheme points are as follows: in view of the problem that the existing load frequency control method generally assumes that the communication link is continuously available and is difficult to maintain stable operation under the condition of DoS attack, the system is modeled as a switching system when the DoS attack exists, and the control mode is switched in real time according to whether the link is subjected to the DoS attack: the conventional learning control is executed to optimize the frequency regulation performance when the communication is normal; the anti-attack control mode is switched to when the attack occurs, so that the closed-loop stability can be maintained and the frequency deviation and the tie-line power fluctuation can be inhibited under the condition that the communication is blocked, and the system safety is significantly improved; in addition, based on the RL method, the control strategy is obtained by online learning through interaction with the environment under the condition that the system model is unknown or the parameters are uncertain, so that the control energy minimization and the operation economy are realized without depending on the accurate system dynamics.

The application relates to the field of image restoration, in particular to an intelligent image recognition and restoration processing system and method based on big data, which comprises an image verification module, a selection restoration module, a gray scale restoration module, a color separation enhancement module and a color mixing filter module; the image verification module is used for determining image information loss; the selection restoration module is used for calculating the peak signal-to-noise ratio of the image; the gray scale restoration module is used for outwardly extending the gray scale texture of the image; the color separation enhancement module is used for separating the image colors by using different color separation schemes; and the color mixing filter module is used for carrying out image denoising and image color mixing processing through a filter. The application can avoid the data block effect, blurring and color distortion caused by network fluctuation, reduce the image restoration time, adapt to the viewing demand of users, reduce the influence of data loss on the image, optimize the calculation efficiency of the restoration algorithm, improve the picture texture visual sense and improve the visual experience of terminal users.

A front-end and back-end combined hidden danger analysis system and method thereof, the system comprising: a front-end camera module, a video target recognition module, an image definition recognition module, an image similarity recognition module, a front-end slice compression module, a back-end image analysis module, a back-end hidden danger analysis result module and a front-end loudspeaker module, the method comprising: one: image acquisition; two: hidden danger target recognition; three: image definition recognition; four: image similarity recognition; five: video slice compression; six: image analysis; seven: hidden danger analysis; eight: hidden danger broadcast reminder; the video frame is preliminarily detected through the front-end video target recognition module, only the frame containing the hidden danger target is reserved for subsequent processing; combined with the image definition recognition module and the image similarity recognition module, further eliminate the fuzzy and repeated frames, generate high-quality video segments, effectively reduce the image data amount required to be processed by the back-end multi-modal large model, thereby greatly reduce the consumption of token.

The invention provides an end-side cloud collaborative big data analysis method and system, and the method comprises the steps: employing the hierarchical retrieval under end-side cloud collaboration, determining a retrieval starting level based on a deployment and control target type and retrieval task timeliness, and triggering continuous retrieval according to a preset collaborative strategy: carrying out the matching of an associated camera range according to the deployment and control target type and an incident site; in the terminal layer retrieval, each associated camera performs deployment and control target retrieval on historical feature data in a local short-term time window, and triggers edge layer retrieval when the historical feature data are not hit; according to edge layer retrieval, an edge box calls historical feature data in a middle-term time window uploaded by all associated cameras in an area, deploy and control target retrieval is carried out, and cloud layer retrieval is triggered when a target is not hit; and in the cloud layer retrieval, a cloud server screens feature data in a long-term window of a retrieval area from a cloud database according to a retrieval task and performs deployment and control target retrieval. The problems of high transmission pressure, low retrieval efficiency, resource waste and the like are solved.

The invention provides an inner wall embedded type multi-dimensional state monitoring system for a GIS transformer. Comprising a transformer shell integrated with a comprehensive information management system, a temperature difference heating module for providing direct current for a multi-source synthesis energy management module, a piezoelectric module for rectifying, boosting and storing energy through an energy management system of the multi-source synthesis energy management module, and an ultrasonic partial discharge detection sensor deposited on the inner wall of the transformer shell, the temperature sensor and the SF6 degradation gas metal oxide semiconductor sensor are used for acquiring signals, and the main control module is used for processing the acquired signals. According to the invention, synchronous acquisition of electric-acoustic-thermal-chemical four-dimensional information in the GIS transformer is realized, all the sensors are deposited on the inner wall of the transformer to improve the accuracy and confidence of diagnosis, and the vibration-thermal energy comprehensive energy supply system solves the problem of stable energy supply of the internal sensors. And a feasible scheme is provided for full-life-cycle intelligent monitoring of the equipment.

The application provides a residential area carbon flow monitoring method and system based on edge computing, which divides the residential area into three levels of area level, building level and indoor level, deploys edge nodes with different configurations corresponding to the three levels, and dynamically adjusts the data collection frequency and transmission strategy of each level edge node according to the energy consumption scene of the residential area to complete the collection and preprocessing of carbon-related raw data; based on the preprocessed raw data, each level edge node uses an adaptive weighted carbon flow accounting algorithm, combines dynamic carbon emission factors and multi-dimensional correction factors, and completes real-time accounting of the corresponding level carbon flow to obtain level carbon flow data; the building level edge node aggregates the indoor level carbon flow data and performs secondary accounting, and the area level edge node aggregates the building level carbon flow data to obtain the total carbon flow of the residential area, thereby realizing accurate and real-time monitoring of carbon flow while reducing cloud transmission pressure and overall energy consumption.

The invention discloses a real-time acquisition and storage method for key operating parameters of frequency converters, which belongs to the technical field of frequency converters, and comprises the following steps: aiming at the characteristics of concurrent access of multiple frequency converters, various data types, out-of-order arrival and continuous growth, performing acquisition, time alignment and packaging according to the data types on the operating parameters at an edge side; and a logic storage address is constructed on the center side based on the time interval, the equipment identifier and the data type, and mapping and ordered writing of the logic address and a physical storage position are realized through a storage positioning mechanism, so that the problem that the operation data of the plurality of frequency converters cannot be uploaded under the conditions of high concurrency and disordered uploading is solved. The technical problems of complete acquisition, stable storage and rapid positioning query are solved, the integrity of the original operation data is ensured, the network transmission pressure is effectively reduced, storage disorder caused by an uncertain data arrival sequence is avoided, and the storage efficiency and query efficiency of the operation data of the large-scale frequency converter are improved.

The utility model relates to the field of glass bottle conveying, in particular to a round bottle conveying device which comprises a first conveying mechanism, a buffering table and a buffering sorting mechanism, the buffering sorting mechanism comprises a conveying table, a guiding unit, a sorting conveying belt and a plurality of buffering conveying belts, the sorting conveying belt and the buffering conveying belts are arranged on the conveying table, and the buffering conveying belts are arranged in the same direction. The sorting conveying belt and the cache conveying belt are arranged in a reverse conveying mode, the first conveying mechanism and the cache sorting mechanism are horizontally and perpendicularly arranged and located on one side of the cache conveying belt, the buffer table is arranged between the first conveying mechanism and the cache sorting mechanism, and the guide unit comprises a guide structure used for guiding round bottles on the cache conveying belt to the sorting conveying belt. And the shunting structure is used for shunting the round bottles. By implementing the scheme, the occupied space is saved and the conveying pressure is relieved in the whole-column sorting and conveying stage of the round bottles.

The invention relates to the technical field of battery quality detection, in particular to a ship battery state estimation method and system based on data analysis, and the method comprises the steps: collecting voltage and current signals of a ship battery, and calculating the energy sequence of the voltage and current signals; evaluating from two dimensions of form and energy: calculating the form correlation between the voltage energy sequence and the current energy sequence subjected to time delay alignment to obtain a form correlation score; and calculating the normalized deviation of the energy value based on the dynamic reference to obtain an energy anomaly index. And fusing the morphological association score and the energy anomaly index to calculate a triggering confidence coefficient, and when the triggering confidence coefficient exceeds a preset threshold value, triggering to accurately collect the original high-frequency waveform before and after the abnormal feature. According to the method, the internal failure evolution characteristics of the battery are captured through an association mutual identification mechanism of multi-dimensional characteristics, and the accuracy and reliability of state monitoring are improved while the data storage pressure is reduced.

The utility model belongs to the technical field of plant irrigation, and particularly relates to an intelligent irrigation device for water conservancy project management, which comprises a water storage module, a movable spray head, a wind direction sensor, a wind resistance detector and a variable-pressure water pump, the spraying angle range is in bilateral symmetry by 90 degrees with the wind direction as the center, and the wind resistance detector is installed on the opposite side of the spraying direction of the movable spraying head and rotates along with the spraying angle change of the movable spraying head; the power assisting effect of wind is fully utilized for remote conveying, along with the angle change of the movable spray head, the detection pressure of the variable-pressure controller is gradually reduced to stop, and in the rotating process, the pressure of the water conveying pipe is gradually increased, so that the deviation influence caused by wind power is reduced, kinetic energy loss is reduced in the process, and the wind energy effect is fully utilized; the problem that the flight distance is too long due to the fact that the liquid coverage range is affected by wind is avoided.

The embodiment of the invention provides a communication method and device, a storage medium and a program product, relates to the technical field of communication, and solves the technical problems that when multiple data packets are transmitted between non-adjacent nodes, the transmission pressure of an intermediate node is large, the processing overhead of the intermediate node is increased, and the transmission delay of the data packets is increased. The method comprises the following steps: sending a first request message to a second node; wherein the second node is connected with the first node through the intermediate node; the first request message is used for requesting to establish a direct connection transmission channel between the first node and the second node.

This invention relates to the field of wireless communication and signal processing technology, specifically to a shortwave spectrum high-efficiency sampling method and system based on compressed sensing. The method includes: acquiring power spectral density data across the entire frequency band using a low-speed scanning receiver; determining a set of strong interference frequency points; generating a binary null observation sequence; loading the binary null observation sequence onto an analog front-end mixer circuit to perform analog domain orthogonal mixing and integration processing on the input RF signal, outputting voltage sample values; calculating signal sparsity coefficients using a compressed sensing reconstruction algorithm; calculating the reconstruction residual based on the voltage sample values ​​and the signal sparsity coefficients; triggering a re-acquisition process of power spectral density data in response to the reconstruction residual exceeding a preset error threshold; and outputting the signal sparsity coefficients in response to the reconstruction residual being less than or equal to the preset error threshold. This invention solves the problems of limited dynamic range and weak signal overload, significantly improving the receiving sensitivity of weak signals under strong interference environments.