9results about How to "Eliminate randomness" patented technology

The present application relates to the field of drilling engineering, and particularly relates to a kind of automatic spraying device and operating method of drill pipe thread grease, including self-locking screw lifting platform, rotating platform assembly, support assembly, telescopic rod assembly, spraying head and thread grease conveying pipe;Spraying head includes outer thread spraying assembly, push-pull cylinder A, piston rod A, push-pull cylinder B, piston rod B, inner thread spraying assembly and shell;The self-locking screw lifting platform realizes the lifting of spraying head;The rotating platform assembly realizes the rotation of spraying head;The telescopic rod assembly realizes the centring of spraying head;The spraying head is sprayed with thread grease to drill pipe joint.The beneficial effects of the present application are: automatic spraying thread grease is realized, intelligent drill pipe conductor ring is prevented from being contaminated, operation efficiency is improved and different specifications of drill pipe joint can be adapted.

The invention discloses a robot system for laboratory pretreatment autonomous operation, which relates to the technical field of intelligent robots and is formed by organically fusing four core parts, namely a moving and executing platform, a sensing module, an operation and end tool module and a control and calculation module. Autonomous operation is realized through a set of layered progressive closed-loop feedback intelligent control logic: firstly, a macroscopic experiment task is gradually decomposed into executable'action-nodes' from top to bottom; secondly, real-time closed-loop feedback is formed through multi-source 3D vision and tail end force perception, the track of the mechanical arm is dynamically corrected, and the operation force is accurately controlled; and finally, two arms are driven to work cooperatively through parameterized mapping and accurate time sequence control, so that unmanned, standardized and high-reliability operation of a sample pretreatment process is realized in a variable experimental environment, and the limitation of manual operation and an existing single-function automation scheme is effectively overcome.

The application discloses a kind of encapsulation glue selection methods and encapsulation structure for crystal screen film, and the selection method is established by the multi-dimensional performance index system with adhesion strength, light transmittance, weather resistance, yellowing index and modulus as core, and finally the encapsulation glue selection is completed by threshold preliminary screening, interface compatibility accelerated aging test, encapsulation interface stress simulation analysis through weighted quantitative comprehensive score;The encapsulation glue prepared by the selection method is used in the encapsulation structure of crystal screen film, including the layer-by-layer lamination of crystal screen film layer, encapsulation glue layer and cover layer.The application realizes the systematization and quantifiable selection of encapsulation glue for crystal screen film, solves the pain points of insufficient long-term reliability, interface failure and optical performance degradation caused by the experience selection of prior art, and can significantly improve the structural stability and service life of crystal screen film product, and is suitable for the encapsulation scene of crystal screen film of various high-end display devices.

The specification provides a construction method of a cost function, a computer readable storage medium and a program product, the method comprising: determining a corresponding initial cost function according to a target driving variable, the initial cost function containing unknown parameters; obtaining a driving data set for the target driving variable, the driving data set containing actual values of the target driving variable and corresponding cost observation values; determining an estimated value of the unknown parameters according to the driving data set, and constructing a target cost function according to the estimated value and the initial cost function.

The invention discloses a method for monitoring man-made interference in an ecological protection red line based on multi-source data fusion. The method comprises the following steps: constructing a matrix property-stress risk-wild property three-in-one dynamic monitoring index system; integrating multi-source heterogeneous data of remote sensing, territorial, forestry, meteorology and the like, and executing standardized preprocessing of coordinate unification, scale normalization and boundary clipping; adopting an entropy weight method to initially construct an ecological quality index, and combining an XGBoost algorithm to realize weight adaptive correction; performing time sequence trend robust diagnosis in combination with a Theil-Sen Median method and a Mann-Kendall method, and introducing an LSTM (Long Short Term Memory) model to realize ecological quality change prediction; and on the basis of a grid and county-level double-level evaluation framework, a current situation index, a historical trend and prediction information are fused, and a man-made interference grading early warning result with a space traceability capability is generated. According to the method, the accuracy of human interference identification, the reliability of dynamic tracking and the practicability of early warning response are improved, and quantifiable, traceable and operable technical support is provided for fine supervision and adaptive governance of ecological protection red lines.

The application discloses an open-pit to underground mine full-tailings consolidation backfill system and method, and relates to the field of deep mineral resource development and industrial automation control. The system is constructed based on a distributed control architecture, and integrates a full-process intelligent sensing subsystem, a multi-modal adaptive decision subsystem and a high-precision execution feedback subsystem. The method adopts a four-dimensional dynamic control strategy of "sensing-prediction-regulation-correction", and realizes real-time collection of slurry rheological and equipment state parameters through a multi-source heterogeneous sensor. A feedforward compensation combined with a feedback correction algorithm is used to realize time-space synchronous precise proportioning of cementing materials. Adaptive variable-frequency stirring from high-shear dispersion to laminar homogenization is executed based on non-Newtonian fluid characteristics. And multi-stage dynamic adjustment of vacuum dewatering is realized through a gas-liquid-solid three-phase coupling model. The application effectively solves the problems of parameter curing, large quality fluctuation and high energy consumption of the traditional backfill process, and significantly improves the strength consistency of the backfill body and the operation economy of the system.

The invention relates to the technical field of vehicle safety early warning, and discloses a triangular warning board dynamic early warning distance adjusting system and method for AI road condition recognition, the system comprises a main control system and a beacon device, the main control system comprises a reference establishment module, a path mapping module, a dynamic calculation module and a first wireless communication module; the beacon device comprises a second wireless communication module, a data acquisition module and a prompt module. The beacon device enables an operator to safely walk on an emergency lane and records a track through the data acquisition module, and the main control system intelligently maps the safe track to a traffic lane with the real-time lane position of an accident vehicle as a reference through the path mapping module and generates a corresponding virtual driving path. And then real-time integration is carried out on the virtual path through the dynamic calculation module to obtain an accurate curve length, a dynamic early warning distance is calculated, and an operator is prompted to carry out placement operation through the prompt module when the curve length and the dynamic early warning distance are matched, so that the safety guarantee for the operator is enhanced.

The application relates to the technical field of tailing resource utilization, and discloses a tailing sand particle grading dynamic optimization processing method and system. The method comprises the following steps: collecting particle size data at a detection node of a conveying pipeline and dividing the particle size data into particle size groups; calculating dynamic weight coefficients according to data stability coefficients and flow influence coefficients and performing weighted fusion; predicting a grading deviation value through a long short-term memory neural network to trigger an optimization decision to obtain a target grading ratio; calculating accurate adjustment amounts of each bin to generate a batching control instruction; performing closed-loop adjustment and secondary correction to obtain a target grading product. The application solves the problems of tailing sand particle grading optimization response lag, insufficient control precision, difficulty in multi-target cooperation and lack of self-adaptive capability in the prior art, and improves the real-time performance and accuracy of grading control.

The application provides a user environment scene recognition method, system and electronic equipment, comprising: sequentially completing multi-modal original data acquisition and alignment, noise reduction and normalization, multi-scale feature extraction, time sequence structure decision and dynamic network structure adjustment, through constructing time sequence consistency gating mechanism and dynamic structure interpolation control signal, realizing adaptive smooth adjustment of channel activation number and attention head number of a lightweight mixed backbone network, and then driving a learnable soft mask to sparsely schedule backbone network level calculation on demand, finally completing efficient and accurate environment scene recognition, the application effectively improves the calculation efficiency and inference accuracy of the scene recognition model under the condition that the terminal device resources are limited, and has good structure continuity and hardware adaptability.