12results about How to "Adequate response time" patented technology

The invention relates to a heat supply prediction method and system based on spatial-temporal feature fusion deep learning, and the method comprises the following steps: S1, carrying out the collection and fusion of multi-source heterogeneous data, and constructing an integrated data set; s2, preprocessing the data; s3, constructing a graph structure model of the heat supply system, and constructing a weighted undirected graph; s4, constructing and executing forward calculation of the space-time double-flow deep network; s5, designing a composite loss function including mean square error loss and physical constraint loss, and performing joint optimization training on the space-time double-flow deep network; and S6, performing multi-step heat supply load prediction by using the trained model, outputting a heat supply load curve of each heat exchange station in a specified time period in the future, and integrating a prediction result with a heat supply scheduling system. The method has the advantages that the prediction precision is improved compared with that of a traditional machine learning model by capturing the spatial-temporal characteristics at the same time, and the advantages are more remarkable in extreme weather.

The invention discloses a hydropower station equipment operation state safety early warning method comprising the steps that a three-dimensional model is established, the actual shape of a dam body is scaled down and converted into a three-dimensional model of a dynamic deformation module, the surface of the dynamic deformation module is covered with grid points, and an environment parameter sensor is arranged in the dynamic deformation module; environment data of the hydropower station dam are collected, a first work consumption random number and a second work consumption random number are calculated, the value of the first work consumption random number is mapped to a color space to be converted into a thermal loop, and the value of the second work consumption random number is mapped to a strip to be converted into a water level pressure band; and when the displacement of the grid points is greater than a preset displacement threshold value, the grid points are highlighted and abnormal early warning is carried out. By establishing a dynamic deformation module, complex displacement data becomes visual, and by introducing a thermal loop and a water level pressure band, operators can quickly find abnormal conditions, and the efficiency and accuracy of hydropower station dam safety management are improved.

The invention discloses a wave pitching motion control method and system for an offshore floating type wind turbine generator, and belongs to the technical field of offshore wind power equipment control. The method comprises the following steps: signal acquisition: acquiring unit operation state, marine environment and pitching motion state parameters in real time; wave load prediction: predicting a future wave load based on the improved LSTM neural network model; evaluating a pitching motion state, pre-judging a motion trend through a kinetic model, and judging whether the motion trend exceeds a safety threshold value or not; cooperative control instruction generation: generating cooperative control instructions for fine tuning of a variable pitch angle, a generator torque and a cabin yaw angle based on an MPC algorithm; and control execution and feedback correction: driving an execution mechanism to act and dynamically correcting a control instruction. By accurately predicting the wave load, cooperatively adjusting multiple controllable components and dynamically correcting, efficient and accurate suppression of pitching motion is achieved, and the unit operation stability, the wind energy capturing efficiency and the equipment safety are improved.

The application discloses a mine area closed goaf pollution release early warning method based on water quality and water level monitoring, and belongs to the underground water monitoring field. The method comprises the following steps: collecting water level data and representative water samples of water-filled rock layers, performing water chemical and isotope analysis on the water samples, analyzing the direct contribution water volume of each water-filled rock layer, inputting a data set containing dynamic monitoring parameters and future expected parameters into a pre-trained water level prediction model to obtain a predicted water level, calculating the expected exchange flow between the closed goaf and the water-filled rock layer by using the Darcy seepage formula based on the predicted water level and the goaf shape, and calculating the expected pollutant discharge amount in the prediction period. If the expected pollutant discharge amount exceeds a preset safety threshold, a warning for the corresponding closed goaf is generated, so that the early warning of the pollutant discharge of the closed goaf is realized, and timely and scientific decision-making basis is provided for the active prevention and control and precise management and control of the mine area underground water pollution risk.

The present invention belongs to the technical field of power line monitoring and early warning, and discloses a method and system for early warning of severe convection of power lines based on meteorological radar data. The method obtains reflectivity grid data; judges the severe convection area according to the reflectivity grid data, and designs complexity parameters to measure the structural complexity and spatial connectivity of the severe convection area; judges whether a squall line is formed according to the spatial and temporal correlation between adjacent severe convection areas; judges the movement direction, movement speed and intensity change of the squall line, and evaluates the impact of the squall line on the power line, and issues an early warning. The present invention greatly improves the timeliness and accuracy of the early warning and reduces the false alarm rate and missed alarm rate by designing complexity parameters and conducting judgment and analysis of the squall line.

The invention discloses a rectifier data processing system and method, and relates to the technical field of rectifiers, and the system comprises the following modules: a state monitoring module which obtains the input voltage of a rectifier, obtains the output current of the rectifier, obtains the power factor of the rectifier, and obtains a state coefficient through the input voltage, the output current and the power factor of the rectifier; the state coefficient and the stability coefficient are combined through the rectifier early warning module to obtain a prediction coefficient, the future working state of the rectifier is accurately predicted by combining external influence factors and internal working factors of the rectifier, and whether an early warning alarm is started to remind a manager is judged through the prediction coefficient and a prediction coefficient preset threshold value. Therefore, early warning feedback can be conveniently carried out to a manager according to a prediction result, early warning can be further conveniently carried out before the rectifier stops working, and sufficient response time is provided for an operator to replace and maintain the rectifier.

The invention discloses a complex wind regime identification method based on deep learning, and particularly relates to the technical field of wind regime identification, and the method comprises the five steps: collecting the original data of a three-dimensional wind field through an X-band laser wind measurement radar; data preprocessing is completed through signal processing and edge calculation; constructing a composite model of a convolutional neural network and a long-short-term memory network, and training and optimizing in combination with transfer learning; outputting identification results of the type, the strength and the trend of the wind regime; and triggering a three-level grading safety protection strategy. The complex wind regime recognition method based on deep learning has the specific effects that data acquisition is accurate and comprehensive, processing is efficient and low in delay, the model recognition accuracy is larger than or equal to 95%, prediction can be carried out 30 minutes in advance, safety and efficiency balance is achieved through graded protection, and the method is suitable for complex wind fields on the sea, high altitudes and the like; operation safety of the fan can be effectively guaranteed, and the service life is prolonged.

This invention discloses a self-sensing flange gasket for structural health monitoring of pipeline systems. The flange gasket consists of functional components and signal transmission circuit components. The functional components have a three-layer concentric ring contact structure, including a sealing inner ring layer, a leakage detection middle ring layer, and a sealing reinforcement outer ring layer, used to achieve the sealing and condition monitoring functions of the flange gasket. The signal transmission circuit components include an inner ring edge electrode layer and a middle ring planar interdigitated electrode layer, used to acquire and transmit electrical signals from the flange gasket. All components use flexible PDMS as the base material to ensure the elastic deformation sealing capability of the flange gasket, while the self-adhesive properties of PDMS are used to achieve seamless assembly between the layers. This invention, through a multi-functional layer modular design, utilizes multi-dimensional electrical signal changes caused by different physical parameters to achieve simultaneous detection of fastening pressure and leakage components, thus meeting the engineering requirements for condition monitoring of pipeline systems.

The present invention relates to the field of cross-border logistics data processing technology, and specifically discloses a cross-border intelligent logistics cloud management system based on big data, which includes: a transportation transit section division module, a transportation road condition impact assessment module, a transportation path optimization adjustment module and a cross-border logistics database. The present invention can help to more accurately control and manage the logistics transportation process by refining the transportation route into multiple transit sections, thereby improving the controllability and flexibility of transportation. Through real-time road condition and meteorological data collection and analysis, transportation strategies can be adjusted in time to cope with emergencies, thereby reducing transportation delays and ensuring that goods arrive on time. The present invention helps to optimize the allocation of transportation resources. By evaluating the degree of impact of the transportation feasibility of each section, a more appropriate mode of transportation can be selected, which not only improves the efficiency and reliability of transportation, but also enhances the flexibility and responsiveness of the entire logistics system.

The invention provides flue gas denitration multi-pollutant collaborative treatment equipment, and belongs to the technical field of flue gas denitration, the flue gas denitration multi-pollutant collaborative treatment equipment comprises a sulfur dioxide absorption tower, an SCR reactor and an ammonia storage tank, and a blending bin and a heat exchanger are connected in series between the sulfur dioxide absorption tower and the SCR reactor; a turbulent flow pipe, a temporary storage cavity and a flow guide pipe are sequentially arranged in the blending bin from left to right, a linkage shaft is arranged in the middle of flow guide fan blades arranged in the flow guide pipe in a penetrating mode, the left end of the linkage shaft extends into the turbulent flow pipe and is provided with a plurality of flow guide fan blades, and a driving mechanism is arranged in the blending bin; gas sensors are arranged on the left side in the blending bin and in the temporary storage cavity; a flow adjusting mechanism is arranged between the temporary storage cavity and the flow guide pipe, and the top of the temporary storage cavity is vertically and slidably connected with a piston plate through a first elastic piece. A plurality of heat exchange plates are arranged on the left side of the interior of the blending bin in an array mode. The application can reduce the risk of direct discharge of substandard flue gas and ammonia escape.

The invention discloses a universal scanner countering method and system. The countering method comprises the following steps: a client forms communication flow with a TCP (Transmission Control Protocol) of a server through network security equipment bridged in a link; an independent countering device is arranged, the countering device and the network security equipment are accessible, and a port is opened on the countering device and waits for connection; the network security equipment detects an attack behavior in the traffic, and records the client as a unique identifier; and the network security device sends an RST or FIN message to the client for disconnecting or resetting the TCP session. According to the method, the scanner can be in a substantially disabled state, but the scanner still displays the normal operation state when the scanner cannot sense the abnormity of the scanning state and a hacker checks the state of the scanner, so that a misjudgment is caused to the hacker, and the hacker continues to wait for scanning completion, so that the time cost is increased, and the scanning efficiency is improved. And sufficient response time is provided for defenders.

The present invention provides a sequential mold opening locking mechanism and a sequential mold opening injection mold, including a locking machine base, a locking machine block, a locking machine lever and a locking machine hook. The locking machine block is movably installed on the locking machine base so as to have a locking position locked on the locking machine hook and a releasing position releasing the locking machine hook; the direction of the locking machine block from the releasing position to the locking position is defined as the locking direction; the locking machine base is provided with a lever groove, the locking machine lever is inserted into the lever groove, and the locking machine lever is also provided with a resistance part for fixing the locking machine block in the locking position; the end of the locking machine lever is also bent away from the locking direction to form an elbow structure. The locking machine block is fixed in the locking position by the resistance part of the locking machine lever, and in the process of mold opening, the elbow structure at the end realizes the release of the locking machine block, that is, unlocking is realized. The locking state of this locking mechanism has no movement gap, which solves the problem of poor stability and easy running failure of the existing locking mechanism.