116results about How to "Avoid hysteresis" patented technology

The invention provides a real-time disaster situation multi-dimensional verification alarm method and system based on a large model, and relates to the technical field of disaster situation response, and the method comprises the steps: carrying out the backtracking and calling of multi-source disaster situation associated data after a disaster situation early warning signal is received, and obtaining a heterogeneous disaster situation data set; starting a dynamic task chain scheduling mechanism, executing multi-priority thread trend analysis, and outputting a multi-dimensional index analysis result; executing multi-dimensional index cross verification, and outputting a disaster verification conclusion; disaster decision making is carried out, and a disaster decision instruction is generated; carrying out township-level disaster situation grid positioning, and outputting a disaster boundary coordinate set; after the thermal rescue target spot is framed, geological disaster avoidance analysis is carried out, and a safety buffer area is positioned; and executing an alarm verification response. The technical problems that in the prior art, a disaster monitoring and early warning system mainly depends on a step-by-step reporting mechanism, so that disaster information transmission is lagged, accuracy is lost, and timeliness and accuracy of post-disaster rescue work are affected are solved.

The invention discloses a wind generating set risk early warning method, device and equipment in sand storm weather and a storage medium, and relates to the technical field of wind power generation, and the wind generating set risk early warning method in sand storm weather at least comprises the following steps: collecting multi-source meteorological data in a target area, judging whether a preset sand storm early warning condition is triggered or not according to the multi-source meteorological data; in response to the condition of triggering sand storm early warning, simulating the motion condition of sand and dust according to the multi-source meteorological data and the digital elevation model of the target area, and predicting to obtain sand and dust settlement distribution information in the target area; determining at least one to-be-protected generator set according to a preset wind generating set distribution diagram and the sand and dust sedimentation distribution information; and executing a protection control strategy on the to-be-protected generator set according to the multi-source meteorological data and the sand and dust settlement distribution information. The protection effect on the wind generating set in the sand storm weather is improved, and power generation output is guaranteed.

This invention relates to the field of ultra-high performance concrete (UHVPC) curing technology, and more particularly to an intelligent temperature-controlled curing method for UHVPC. The method includes the following steps: generating preliminary temperature-controlled curing data for concrete based on UHVPC mix proportion parameters and temperature-controlled curing requirements data; analyzing the distributed temperature field characteristics of the pouring nodes using UHVPC pouring node data to generate distributed temperature field characteristic data for the pouring nodes; analyzing the temperature evolution and hydration state of the pouring node temperature field based on the distributed temperature field characteristic data and the preliminary temperature-controlled curing data to generate temperature evolution and hydration regulation state data; and performing dynamic temperature-controlled curing analysis on the preliminary temperature-controlled curing data to generate dynamic temperature-controlled curing data for the concrete. This invention achieves intelligent temperature-controlled curing by combining the application of UHVPC.

The invention discloses an MICP intensity prediction method and system based on machine learning and multi-feature fusion, and relates to the field of solidified data analysis. An accurate quality prediction mapping model and an abnormal compensation parameter mapping model are constructed based on historical data; the system has the capabilities of predicting curing quality from process parameters and intelligently recommending an optimal disposal scheme from an abnormal state; by setting a dual-threshold quality control mechanism and a real-time abnormity monitoring and early warning system, various abnormal conditions in the curing process can be actively identified and timely responded, and complete closed-loop processing from parameter deviation detection to automatic compensation measure execution to hardware standby switching can be realized. The stability of the solidification process and the consistency of the engineering quality are effectively guaranteed, the requirement for manual intervention and the misjudgment risk are greatly reduced, powerful technical support is provided for standardization, normalization and industrialization development of the sand solidification technology, and the engineering efficiency and economic benefits are remarkably improved.

The present application belongs to the field of material support operation, and particularly relates to a material support pre-scheduling method and system. The method comprises: in the process of material scheduling, when a risk event occurs, the real-time value of the system situation assessment characteristic parameter is input into the trained system situation assessment neural network according to the set period to obtain the predicted total delay time length of the system operation completion; if the total delay time length is greater than the pre-scheduling threshold, the pre-scheduling scheme generation is triggered; the system situation assessment neural network is trained by the system situation assessment characteristic parameter value and the corresponding total delay time length in the training set; including the current number of warehouses in the system, warehouse inventory information, task demand information, resource state information, warehouse operation state information, current operation completion rate and current operation delay. Through the risk event related to the operation delay, the total delay that may exist is monitored in advance, and the pre-scheduling scheme generation is triggered in time.

The invention provides a method and system for accurately controlling the temperature of an adhesive production reaction kettle, and relates to the technical field of adhesive production, and the method comprises the steps: applying a transient heating pulse to the reaction kettle in adhesive production, collecting the surface temperature data of a container wall, processing the data, calculating a temperature decline curve, and extracting key information of heat transfer characteristics. A heat abnormal area caused by uneven mixing is identified based on spatial distribution of key information, and the thermal state change of the adhesive reaction degree is estimated in combination with a time change mode. And adjusting a heating pulse mode and a working state of the stirring device according to the abnormal area and the change mode, and introducing a pause detection stage to collect surface temperature feedback under weak heating pulses so as to confirm an adjustment effect. And finally, associating the key information with the reaction degree based on feedback to generate a temperature adjusting command, and adjusting the heating or cooling intensity, so that accurate control on the temperature of the reaction kettle can be realized, and the production quality and efficiency are improved.

This application provides a photovoltaic power quality monitoring method, system, device, and storage medium, relating to the field of power quality monitoring technology. The method includes: predicting the initial trend of power generation of the photovoltaic power generation system within a preset time period based on historical operating data of the photovoltaic power generation system; adjusting the initial trend based on environmental information of the photovoltaic power generation system to generate a first trend of power generation of the photovoltaic power generation system within the preset time period; acquiring real-time and historical power consumption data from the user end, and combining the real-time and historical power consumption data to predict a second trend of user end power load within the preset time period; determining the power deviation value of the power grid within the preset time period based on the first and second trends, and generating a power regulation plan for the power grid based on the power deviation value. The technical effect of this application is: timely response to power fluctuations of the photovoltaic power generation system and user load, reducing power oscillations in the power grid.

This utility model relates to the field of actuator technology, and in particular to a centrally positioned pneumatic actuator, comprising a cylinder body and a main shaft disposed inside the cylinder body. A piston is fitted on each side of the main shaft, and the piston drives the main shaft to rotate. The actuator also includes a positioning block, a first adjusting screw, and a second adjusting screw. A hexagonal post is disposed on the main shaft, passing through and connecting to the positioning block. The main shaft drives the positioning block to rotate coaxially via the hexagonal post. The first and second adjusting screws are threaded through the side wall of the cylinder body, and each end of the first and second adjusting screws inside the cylinder body has a first limiting end and a second limiting end, respectively. The first and second limiting ends are used to limit the contact with both ends of the positioning block. This utility model, with its centrally positioned limiting structure, allows for real-time adjustment of the actuator's stroke range.

The embodiment of the application provides a time slot adjustment method and device, electronic equipment and storage medium, and relates to the technical field of network, the method comprises the following steps: in response to reaching a time slot monitoring opportunity, determining a bandwidth demand prediction value of a target service of a target network device in a target time period in the future; comparing the bandwidth demand prediction value with an actual bandwidth allocated to the target service at present, and determining a target time slot number allocated to the target service in the target time period based on a comparison result; determining a time slot adjustment opportunity of the target service; and adjusting the time slot number allocated to the target service to the target time slot number when the time slot adjustment opportunity is reached. The embodiment of the application can avoid untimely time slot adjustment during a traffic peak period, and reduce the idling of bandwidth resources during a non-peak period.

This invention relates to the field of energy forecasting technology, and in particular to a method and system for short-term energy load forecasting based on an improved Transformer using SE-Block. The method includes reversible normalization preprocessing of acquired multivariate load sequence data; feature extraction and fusion of the preprocessed data using improved cross-scale interactive patching, including multi-scale feature extraction, cross-scale interactive alignment, residual correction, and dynamic fusion; and feature filtering of the fused features based on a channel attention mechanism, including feature response based on improved SE-Block and nonlinear interaction of context vectors. This invention addresses the non-stationarity of actual load caused by meteorological conditions and user behavior. By automatically eliminating noise interference among multiple variables, the model accurately depicts the fluctuation details of the load curve, demonstrating its robustness in multivariate load forecasting for integrated energy systems.

The utility model provides a kind of machining piece displacement monitoring device, the displacement monitoring device includes control device, first alarm device, displacement detection device, power supply battery and second alarm device.Control device includes control box and controller, and controller is set in control box.First alarm device is set on control box, and first alarm device is electrically connected controller.Displacement detection device is set to the side of machining piece, and displacement detection device is electrically connected controller, and power supply battery is electrically connected controller.Second alarm device is wirelessly connected control device, and it is located the control panel side of machine tool.The displacement monitoring device overcomes the hysteresis of traditional measurement method, ensures that any small displacement change in processing can be captured in time.Double alarm mechanism not only improves the reliability of alarm, effectively avoids the safety accident caused by alarm signal not being perceived in time.

This invention discloses an energy-saving control method for central air conditioning chillers based on an energy demand prediction model, belonging to the field of central air conditioning energy-saving control technology. It addresses the problems of existing chiller control methods relying on manual experience, passive adjustments, and high energy consumption. The method includes: collecting relevant data from the air conditioning operating system, outdoor environment, control terminal environment, and control targets from multiple dimensions; constructing a chiller energy demand prediction model using machine learning algorithms to achieve accurate prediction of chiller energy demand; proactively and collaboratively adjusting the chiller operating frequency, circulating water pump operating status, the number of chillers and water pumps started and stopped, and inlet and outlet water temperatures based on the prediction results; and optimizing the model and control strategy through real-time feedback to form a closed-loop control. This invention achieves predictive and anticipatory chiller control, eliminating reliance on manual experience and realizing truly intelligent control. It significantly reduces chiller energy consumption, improves system operational stability and equipment lifespan, and is applicable to energy-saving control of various central air conditioning chiller systems.

This application discloses a multi-module combined aquaculture water purification method and system, relating to the field of water purification technology. The method includes: acquiring the rated aquaculture load and module distribution information of multiple aquaculture modules; determining the initial connection topology between the multiple water purification modules through a priori empirical model; collecting real-time monitoring data from the multiple aquaculture modules and calculating the real-time water quality load; optimizing water purification parameters based on simulation analysis; and controlling the aquaculture water purification in the target scenario based on the optimized water purification parameter results. This solves the technical problem of traditional aquaculture water purification methods being unable to dynamically adjust according to the actual load and distribution characteristics of different aquaculture modules, leading to low purification efficiency.

The invention relates to the technical field of information processing, in particular to a non-contact code read-write system and device for fire alarm, and the system comprises an RFID tag end and a code read-write device. The RFID tag end is made of a metal-resistant material and a ceramic packaging material with strong severe environment tolerance. The early warning module is used for acquiring environment data and judging whether active alarm is triggered or not according to change characteristics of the environment data, the storage module is used for recording key logs, and the analysis module is used for analyzing stored key log data and actively feeding back equipment states through Bluetooth beacons. And the coding read-write device comprises an RFID reading module for realizing information interaction with the RFID tag end, an RFID write-in module and a signal receiving module based on Bluetooth. The problems that in the prior art, an encoding read-write system cannot actively early warn and give an alarm and feed back the condition of fire alarm equipment, and RFID radio frequency signals are prone to being affected by severe environment factors such as high temperature, dense smoke and water mist and the like and are attenuated are solved.

The application discloses a flexible on-load voltage regulating transformer multi-target cooperative control system and method based on hour-level load prediction, which comprises the following steps: a node parameter acquisition module acquires electrical parameters of each node of a power distribution network; a load prediction module outputs a load prediction sequence in the future time; a multi-target optimization module generates an optimal control optimization strategy according to a cooperative optimization model; an upper prediction optimization layer makes an hour-level optimization decision on tap position and capacitor group switching; a lower real-time adjustment layer outputs a voltage dynamic compensation amount and generates a minute-level equipment adjustment instruction; and an execution module coordinates and controls flexible on-load voltage regulating transformer (FOLTC) tap switching, capacitor group switching and converter action, so that multi-target optimization of voltage deviation, reactive power compensation and equipment loss is realized. The application is suitable for voltage optimization, reactive power compensation and loss control in a conventional load fluctuation scenario of a power distribution network.

This invention relates to the field of intelligent logistics warehousing and automated storage technology, specifically a method, system, and apparatus for efficient pallet storage in logistics storage. The method includes: collecting actual outbound instructions and pallet flow records as initial data packets; performing time-series correlation analysis to obtain the spatiotemporal coupling characteristics of orders; extracting pallet flow probabilities and calculating predictive cache hit rates; classifying heat levels based on historical outbound frequencies and assigning migration priorities; calculating the physical topology entropy reduction index of the storage area in conjunction with pallet flow probabilities; extracting idle time slices of handling equipment and calculating fragmented time rebalancing conversion rates; constructing a multi-objective optimization function and solving it to obtain a dynamic topology rearrangement strategy; generating migration trigger conditions and cache execution instructions, and executing them when the conditions are met; and calculating scheduling preemption rollback delays and formulating rearrangement interruption recovery strategies when sudden tasks have higher priority. This invention thereby improves the accessibility and scheduling stability of high-frequency pallets.

The utility model discloses a kind of eyeglass lens edger circulating water quality monitoring systems, it relates to lens edger technical field.It includes water quality sensor: install on circulating water tank, for real-time detection suspended particulate matter concentration in circulating water tank;Control unit: with water quality sensor signal connection, control unit is used to receive and handle the real-time detection data of water quality sensor;Response module: with control unit output end connection, for based on the alarm signal and / or to edger output control signal of the processing result of control unit.It is beneficial for the utility model to install water quality sensor based on optical scattering principle on water tank, continuously, real-time monitoring concentration change of suspended particulate matter in circulating water, overcome the hysteresis of traditional artificial timing sampling detection or simple visual inspection, can send alarm when water quality starts to deteriorate but has not reached serious harm degree, provide valuable reaction time for operator, prevent problem accumulation deterioration.

The invention is suitable for the technical field of intelligent terminals, and provides an equipment adaptive time synchronization method and device, terminal equipment and a storage medium, and the method comprises the steps: periodically detecting the instantaneous deviation between the local time of the equipment and the network reference time according to a synchronization period; calculating a predicted time error according to the instantaneous deviation, a predicted time window and a clock drift rate, the clock drift rate being determined based on the instantaneous deviation; the predicted time error is compared with an allowable error threshold value, and if the predicted time error is larger than the allowable error threshold value, time synchronization operation is triggered; after the time synchronization operation is triggered, the synchronization period is dynamically adjusted according to the clock drift rate, and the adjusted synchronization period is used for determining the time for detecting the instantaneous deviation next time. According to the invention, the device can adaptively balance time precision and resource consumption, so that the synchronization effect of high precision, low power consumption and network friendliness is realized.

The application discloses a social media-based interpretable dynamic graph network benefit prediction model training method, relates to the technical field of text analysis and market prediction, and obtains market data and related social media data of a financial asset to divide the data by weeks; for the social media data of each week, a topic is taken as a node, and similarity between topics is taken as an edge weight, a topic correlation graph of each week is constructed to obtain weekly graph data; a prediction model performs time sequence updating and market prediction according to the weekly graph data; a text time sequence memory unit obtains a current week topic memory vector according to a current week topic text embedding vector and in combination with a last week topic memory vector; a multi-layer graph attention network captures the correlation features between nodes through an attention mechanism and adopts attention weights for weighted summation to obtain a current week global graph embedding; and a classifier outputs a next week price change prediction result. The application solves the problem that the prior art cannot effectively capture the time sequence evolution of topic sentiment and the correlation between topics.

This disclosure relates to a control method, device, and vehicle for contactless anti-pinch protection of vehicle windows, including: acquiring spatial motion status parameters of an obstacle relative to an onboard radar sensor on the window closing path, and obtaining the real-time position of the obstacle based on the spatial motion status parameters; generating movement parameters of the obstacle based on the real-time position at multiple time points; determining whether the obstacle meets threat conditions based on the spatial motion status parameters and movement parameters, wherein the threat conditions are used to characterize the risk of the obstacle being pinched; and triggering the window to perform anti-pinch operation when it is determined that the obstacle meets the threat conditions. This disclosure relies on the non-contact active sensing characteristics of radar, actively emitting electromagnetic waves for detection. Tens to hundreds of milliseconds before the glass and obstacle collide, the radar has already detected the obstacle's intrusion path, thereby achieving pre-collision intervention. This represents a technological upgrade from traditional passive motor load detection to active spatial sensing, allowing for early risk detection without physical contact with the obstacle.