10results about How to "Implementation time" patented technology

This invention discloses an in-situ lunar regolith thermal energy storage and controllable utilization device, relating to the field of lunar surface thermal energy storage technology. The invention includes: a lunar regolith thermal storage body, formed by high-temperature melting of in-situ lunar regolith for storing thermal energy; a heat spreader plate, disposed on the lower surface of the lunar regolith thermal storage body, serving as a channel for energy exchange between the lunar regolith thermal storage body and the outside; and a heat expansion component, fixedly connected to the heat spreader plate, used to improve the heating efficiency of the lunar regolith thermal storage body during the heating process. This invention achieves efficient storage of solar energy and redundant electrical energy during lunar daytime by combining the lunar regolith thermal storage body with a high-efficiency heat expansion component, and achieves stable energy release and cascaded utilization through a controllable heat release component, thereby realizing peak shifting and valley filling of lunar surface energy in both time and space dimensions.

The utility model discloses a novel continuous reactor device which comprises a tubular reactor, a first feed pipe is communicated and connected with the top of the tubular reactor close to the left side, and second feed pipes are respectively communicated and connected with the bottom of the tubular reactor close to the left side and the right side. The top end of the first feeding pipe and the bottom ends of the two second feeding pipes are respectively communicated and connected with an SK mixer, a combined SK mixer is arranged in the tubular reactor, and a heat exchange medium inlet is communicated and connected to the left side, close to the bottom, of the tubular reactor. According to the technical scheme, through mutual cooperation of the tubular reactor, the SK mixer, the combined SK mixer and other components, adding and continuous production of various materials at different time can be achieved, the SK mixer set is connected in parallel in the tubular reactor, the solution mixing and reaction efficiency is higher, the heat exchange efficiency is higher, local temperature rise is avoided, and the production efficiency is improved. And the reaction heat can be effectively utilized to supply heat to the two-stage reaction.

The invention relates to a parameter rollback method and device of a cloud native database and electronic equipment. The method comprises the following steps: packaging a parameter adjustment task into a user-defined resource object, and determining old parameter values, target parameter values, database components to which all parameters to be adjusted in the user-defined resource object belong and parameter effective layer identifiers; for each to-be-adjusted parameter, generating a parameter rollback snapshot, and writing the parameter rollback snapshot into a state field of the user-defined resource object; for each to-be-adjusted parameter, issuing a target parameter value to at least one of a configuration resource layer, a container configuration file layer and a database memory layer corresponding to the to-be-adjusted parameter layer by layer; and when it is detected that the adjustment of the target to-be-adjusted parameter fails, according to the parameter effective layer identifier recorded in the parameter rollback snapshot of the target to-be-adjusted parameter, executing a hierarchical rollback operation to recover the target to-be-adjusted parameter to a corresponding old parameter value. The technical problem that parameter rollback coarseness is difficult to be accurate and consistent is solved.

The invention relates to the technical field of big data analysis, in particular to a space-time big data acquisition and analysis system and method based on the Internet of Things, and the method comprises the following steps: inserting a drift compensation tag at the tail part of each time grid block, and outputting the time grid block with the drift compensation tag; combining the associated data items into a logic data unit; performing semantic isomorphic compression on the logic data unit and the data items with the same spatial hash codes at an edge node to generate a compression block with a spatial-temporal index; and the cloud server receives the compressed block, performs time conflict disambiguation and event-level causal reasoning on the spatio-temporal index by using a causal chain engine, and directly outputs drifting-free and redundancy-free spatio-temporal knowledge which is used for driving high-order application. According to the method, cross-space causal path matching and standard time sequence verification of the uploaded data are realized, and a plurality of actually occurring event-level causal chains can be automatically identified.

This invention relates to the field of automated litchi harvesting technology, specifically a high-low staggered harvesting device and method for harvesting litchi from the entire tree canopy. The device includes a walking mechanism, a high-low staggered double robotic arm, a flexible clamping mechanism, a curved guide rail mechanism, a shearing device, a control device, and an identification device. The identification device and shearing device are mounted on the robotic arms. The low-position 6-DOF robotic arm is mounted on the slide of the curved guide rail mechanism. The high-position 3-DOF robotic arm consists of three linear motion modules along the X, Y, and Z axes. The flexible clamping mechanism is placed on the X-axis linear motion mechanism, which is placed on the Y-axis linear motion mechanism, and the Y-axis linear motion mechanism is placed on the Z-axis linear motion mechanism. The Z-axis linear motion mechanism, control device, and curved guide rail mechanism are mounted on the walking mechanism. This invention can cover the entire litchi canopy for fruit harvesting, is suitable for harvesting in high-branch scenarios, and significantly improves the efficiency of litchi harvesting.

The application discloses a transformer fault prediction method and system, and relates to the technical field of power equipment.The method comprises the following steps: collecting the start-stop action times of each time window, and determining the temperature control response lag coefficient of each time window by analyzing the temperature control lag level of the cooling control system in the power transformer when the cooling control system faces power mutation; analyzing the non-steady-state operation degree of the cooling control system in the corresponding time window to determine whether the temperature control state of the cooling control system affects the normal operation of the power transformer, and issuing a transformer fault prediction instruction; combining the power consumption drift and voltage frequency spectrum disturbance of the power transformer in each time window, analyzing the non-normal operation degree of the power transformer in the corresponding time window, performing digital model analysis on the non-normal operation index of the power transformer in each time window, generating a corresponding grade fault prediction signal, and performing corresponding voice broadcast reminding.

The invention discloses a distributed DTU-based power distribution network slow-action fault response and collaborative reconstruction system, and relates to the technical field of power distribution systems. Abnormal event data of a power distribution network are automatically grabbed, timeline consistency analysis is carried out in combination with a topological structure of the power distribution network, then a time overlapping region of a slow-action response window of each DTU is judged, and a preliminary DTU set is formed; performing automatic identification, hierarchical monitoring and dynamic slow window adjustment on the time domain linkage relationship between the DTUs in the set; and then, performing dynamic correction on a slow motion window of a communication branch corresponding to each DTU set in the high-risk time coupling group, implementing neighborhood consistency verification and synchronous confirmation before execution of a slow motion fault response action, and ensuring coordinated triggering and execution of the action in the slow motion window through delay execution and idempotent control. DTU action conflicts in a high-risk time coupling group can be effectively avoided, time peak shifting and rhythm coordination of response actions are achieved, and the safety and reliability of power distribution network fault response are improved.

The invention discloses an insulator aging intelligent detection method and system based on the hyperspectrum of an unmanned aerial vehicle. The method comprises the following steps: completing synchronous calibration of radiation, spectrum, camera internal reference and time; flying according to a preset route, synchronously collecting data, and unifying timestamp marking; performing radiation correction on the hyperspectral data, and performing distortion correction on the visible light image; establishing a one-to-one correspondence relationship of the data through timestamp matching; based on the visible light image feature points, an insulator string sparse three-dimensional point cloud is constructed, and coarse registration of hyperspectral data and the three-dimensional point cloud is achieved; iteratively optimizing by taking the insulator feature point as a reference, correcting topographic deviation according to a digital elevation model, and ensuring that a registration error meets a threshold pixel; segmenting and extracting a single insulator, establishing a local coordinate system, performing geometric correction according to an actual space attitude, and eliminating inclination deflection distortion; and extracting the spectral characteristics and three-dimensional coordinates of the corrected insulator, judging the aging grade, and outputting a detection report containing accurate positioning.

The invention provides a soybean flowering time prediction method and system based on transcriptome data, and relates to the technical field of biomedical engineering.The method comprises the steps that soybean transcriptome expression data is collected to construct a gene expression state space, consistency analysis is conducted on expression evolution directions of different samples, and a soybean flowering time prediction result is obtained; constructing a gene regulation structure constraint model according to a preset soybean gene regulation relationship, rearranging transcriptome expression data, performing joint coding on gene expression quantity, expression change rate and regulation consistency, inputting a transcription regulation joint feature tensor into a development trigger state identification model, and identifying the development trigger state of the soybean. And continuously judging the transcriptional regulation state along the development pseudo time axis, identifying a development trigger state, executing time conversion under a natural time scale, and generating a prediction result. The technical problem that the soybean flowering period is difficult to accurately predict in the prior art is solved. The technical effects of accurately identifying the soybean flowering trigger state, predicting the natural time and improving the prediction accuracy and reliability are achieved.

The invention discloses a fault diagnosis method and system driven by flight parameters of a long-endurance unmanned aerial vehicle, and relates to the technical field of unmanned aerial vehicles, and the method comprises the steps: receiving multi-source flight data remotely transmitted by the unmanned aerial vehicle, and uniformly mapping the multi-source flight data to a global reference time axis for sampling continuity analysis, so as to recognize a missing section; for a continuous missing section, inputting a continuous flight parameter sequence before and after construction into a bidirectional time sequence estimation model, performing dynamic length prediction compensation to obtain a continuous flight parameter sequence, and performing flight state backtracking reconstruction based on a state space model to obtain a backtracking flight state sequence; extracting a multi-dimensional state feature vector from the backtracking flight state sequence, generating a fault diagnosis result by using a fault diagnosis model, constructing a fault evolution path and determining a fault cause by combining flight parameter abnormal trend analysis, parameter correlation analysis and environmental parameter auxiliary analysis, and realizing remote backtracking of the flight parameters of the long-endurance unmanned aerial vehicle. And the reliability of fault diagnosis is improved.