14results about How to "Solve cumulative error" patented technology

This utility model relates to the technical field of biscuit processing equipment, specifically a hard-limit positioning pin mechanism. It includes a frame, a drive shaft located at the center of the top surface of the frame, a turntable mounted on the top of the drive shaft, and positioning components mounted on the outer circumference of the drive shaft. Multiple positioning seats are mounted on the top surface of the frame, circumferentially along the drive shaft. Rotation of the drive shaft causes the positioning components to engage with positioning seats at different positions. In this hard-limit positioning pin mechanism, the engagement of the positioning components and positioning seats forms a hard-limit structure. The arc-shaped design of the positioning head and positioning groove, combined with the preload of a spring, allows for precise engagement when the drive shaft drives the turntable to a preset position. This mechanism directly constrains the positional deviation of the turntable through mechanical hard limiting, effectively solving the problem of cumulative errors caused by speed fluctuations and component wear. It avoids misalignment between the forming cavity and the processing components, fundamentally eliminating uneven distribution of compressed biscuit raw materials and deformation of the shape.

This invention discloses a production equipment and method for suspended wire clamps with uniform gripping force, belonging to the field of wire clamp manufacturing technology. The production equipment for suspended wire clamps with uniform gripping force includes a U-shaped frame, and further includes: a conveying unit, which has two sets and is respectively arranged on both sides of the U-shaped frame; a drilling unit, which is movable on the upper side of the U-shaped frame, and includes a positioning component for positioning the hull and a first drilling component and a second drilling component for drilling holes on the bottom and sides of the hull; and a reciprocating conveying mechanism, which is arranged on one side of the U-shaped frame and is used to convey the drilling unit and move it back and forth along the length of the U-shaped frame. This invention, by setting multiple independently moving drilling units in a circular motion, achieves tracking and following processing of the hull workpiece on a continuous conveyor line, solving the problem of production line downtime, and realizing efficient continuous processing of suspended wire clamp hulls while ensuring hole position accuracy.

The invention relates to the technical field of pipe contracting machines, and discloses a straightening structure of a large pipe contracting machine and the large pipe contracting machine using the straightening structure. The straightening structure comprises a bottom plate, two adjusting assemblies, two supporting assemblies and a plurality of positioning assemblies; a first sliding groove, a second sliding groove, a third sliding groove and a fourth sliding groove are formed in the side face of the bottom plate, the two supporting assemblies are used for supporting the bottom plate, a straight-through hole is formed in the middle of the bottom plate and used for keeping away from a machined pipe fitting, and the multiple positioning assemblies are arranged in the circumferential direction of the straight-through hole at equal intervals. The first sliding groove, the second sliding groove, the third sliding groove and the fourth sliding groove are formed in the periphery of the bottom plate and matched with the two active adjusting assemblies and the two elastic supporting assemblies, an adjusting matrix with the self-locking and dynamic balancing capacity is constructed, and the problem that in the diameter reducing process of large pipes, due to the dead weight or machining deviation, the axial lead deviates is solved.

The application provides a robot mechanical arm cooperative control method based on imitation learning. The method comprises the following steps: constructing a robot historical state data set, performing feature extraction on the robot historical state data set through an encoder structure to obtain a latent feature representation; obtaining a color image and a depth image of a target operated by a robot to be predicted through a binocular camera, performing feature extraction processing on the color image and the depth image through a mode classification module and a visual feature extraction network to obtain a mode feature and a visual feature vector; inputting joint state information, the latent representation, the operation mode feature and the fused visual feature into a decoder to obtain an action block prediction result, performing weighted averaging on action blocks at multiple continuous time points based on a time series integration weighting mechanism to obtain a continuous control trajectory of the robot mechanical arm. The application solves the multi-stage strategy discontinuity and error accumulation problems existing in the traditional control algorithm, and realizes smooth action, stable task and double-arm cooperative control.

The application discloses a kind of laser cutting automatic control method and system based on servo motor, record when cutting position X axis absolute value encoder reading, and set the position limit of laser head in X axis direction, control X axis side servo motor completes cutting positioning;Control Y axis servo motor so that laser head moves to the cutting starting point of transmission material edge portion, open laser and cutting gas, laser head moves at specified cutting speed along Y axis uniform speed and cuts transmission material, when laser head moves to cutting end point, cutting is completed and laser and cutting gas are closed;After cutting is completed, laser head returns to cutting starting point at Y axis with the change speed of first fast then slow, when zero position limit switch appears rising edge signal, carry out laser head in the automatic zero point correction of Y axis direction.The application can solve the accurate positioning problem of each direction axis in laser cutting process.

The application provides a flow velocity measurement method and device based on AI image recognition; including: collecting fluid images and preprocessing to obtain feature point motion information, acquiring fluid images of different wavelengths through a multispectral image acquisition device, removing high light areas and jitter noise after image registration; using an improved semantic segmentation network to identify the bubble profile in the image and extract the bubble dynamics parameters; combining infrared temperature measurement data with an image gray scale distortion model to reconstruct the temperature field distribution and calculate the refractive index gradient parameters; performing spectral analysis on the continuous image sequence to extract the turbulent characteristic frequency and pressure fluctuation parameters; sequentially passing the initial flow velocity through a bubble influence correction model, a temperature gradient coupling correction model and a turbulent pressure fluctuation correction model for iterative correction, and performing secondary optimization on the correction results through a deep belief network to output the final flow velocity value; the application can comprehensively quantify external interference and realize progressive correction.

The invention discloses an unmanned aerial vehicle group space structure regularity evaluation method based on brain-like calculation, and belongs to the technical field of unmanned aerial vehicle group space structure evaluation, and the method comprises the steps: calculating the optimal pose estimation of an unmanned aerial vehicle group under a global coordinate system, and extracting a global position set at a selected moment; constructing three variant matrixes of various distance deviations; calculating a correlation coefficient matrix and an autocorrelation value of each variant matrix; mapping the self-correlation value into structural regularity, and calculating confidence in combination with a consistency index; constructing a heterogeneous integrated learning framework based on a spiking neural network and a gradient boosting decision tree model, inputting the self-correlation value into the spiking neural network, inputting the self-correlation value and the structure regularity into the gradient boosting decision tree model, and executing a heterogeneous model fusion strategy to obtain an integrated evaluation result; through system performance verification and evaluation, a core output parameter set of the integrated system is generated, and high-precision global unified positioning in a denial environment is realized.

This invention provides a dual-redundancy method for measuring aircraft attitude. It establishes a first measurement channel for the aircraft's heading angle by jointly measuring and calculating with a triaxial accelerometer and a Hall effect magnetometer. A second measurement channel for the heading angle is then established using a MESE rate gyroscope and a MESE angle gyroscope. The errors from these two channels are then combined and nonlinearly transformed, and the error is fed back to the rate gyroscope for secondary measurement correction. Finally, the combined aircraft attitude measurement signal is obtained through integration. Furthermore, when the triaxial accelerometer, magnetometer, rate gyroscope, or angle gyroscope malfunctions, information from the normally functioning sensors is used, and the gain of the combined measurement feedback channel is switched on and off to form a dual-redundancy measurement, thus improving the reliability and accuracy of the overall attitude measurement.

This invention belongs to the field of computational electromagnetics, specifically a method for transforming a one-dimensional axial magnetic field into a three-dimensional axisymmetric magnetic field. This invention uses two variable-step-size, four-point numerical differential calculations followed by averaging to approximate the first derivative at the point to be calculated. This avoids the problem that calculating four points once might not improve accuracy, and also avoids the overly complex formula of directly using five points. Furthermore, by using the approximate value of the first derivative at known coordinates combined with Spline curve fitting to estimate the approximate value of the first derivative at the point z to be calculated, the problem of error superposition is effectively avoided, resulting in a higher accuracy for the radial component B of the calculated three-dimensional axisymmetric magnetic field. r The results are closer to the theoretical values. This invention effectively solves the problems of low accuracy and error accumulation in the transformation from one-dimensional axial magnetic field to three-dimensional magnetic field, and provides strong support for magnetic field loading in the design of devices such as vacuum electronic devices, ion sources, and particle accelerators.

This invention discloses a multi-robot path planning method and system based on hierarchical control. The method acquires model information and basic parameters of each robot in the system, and constructs a realistic map of the working environment using the SLAM algorithm. The grids of the constructed realistic map are merged, transforming a fine-grained grid map into a coarse-grained one. Considering the overall movement direction and target position of the robots, a global path input for the navigation system is obtained. This global path input is published to each robot, and robots can subscribe to other robots' paths to capture their global path information. Each robot perceives local environmental information in a local map and obtains information about obstacles around other robots. Based on the global path results from the MAPF algorithm, a local path planning method is used to generate local paths, enabling avoidance between robots. This provides a reliable solution for efficient collaboration in multi-robot systems.

The application belongs to the field of high-end equipment manufacturing industry, and relates to a manufacturing method of a multi-station precision stamping die for isolation strip metal products, which comprises the following steps: obtaining initial design data of a multi-station layout, calculating a potential range of error accumulation by analyzing the transfer path and positioning point distribution of a workpiece between stations, and obtaining a distribution model of workpiece transfer error; obtaining matching parameters of integrated design optimization, determining the deformation and size deviation of the workpiece between the stations by running a virtual machining process on a continuous stamping stability test platform, and obtaining real-time data of error accumulation control; and for the real-time data of error accumulation control, if the deformation exceeds a preset stability threshold, the guide gap and support point position of the precision guide mechanism are adjusted iteratively to determine the final guide system configuration scheme.

The invention discloses an FMCW laser ranging light source spectrum degradation suppression method based on strategy online deployment. Belongs to the laser radar field. The objective of the invention is to solve the technical problems of spectrum degradation and measurement precision reduction caused by frequency modulation nonlinearity of an FMCW laser ranging light source. Comprising the following steps: building an FMCW laser nonlinear dynamic system platform, and constructing a deep learning model to simulate a dynamic environment; designing a nonlinear correction process as a Markov decision process, and training a reinforcement learning agent by using a TD3 algorithm; carrying out lightweight processing on an Actor network in the policy network, wherein the lightweight processing comprises pruning and quantization operations so as to reduce the complexity of the model; a lightweight strategy network is deployed on a hardware platform, strategy network forward reasoning is achieved on an FPGA, the strategy network is cascaded with a state extraction module and an action output module to form a closed-loop correction system, and dynamic modulation current optimization is achieved. According to the invention, frequency spectrum degradation caused by frequency modulation nonlinearity can be inhibited on line, and the measurement precision is improved.

A method for machining an aero-engine nozzle housing and a multi-station clamping fixture are disclosed, belonging to the field of aero-engine nozzle manufacturing technology. The method is as follows: Uneven allowances and irregular structures are removed to form a regular machining plane with dimensional accuracy requirements; a multi-station clamping fixture is used to center and clamp the nozzle housing blank, completing the final machining of the external dimensions, and precision machining of the datum surface and oil passage holes; the housing is removed for further precision machining; tool marks and residual radius corners are polished; and the datum plane is inspected with coloring. This invention ensures the centering and clamping of the part, avoiding machining deviations due to scribing and alignment errors, thus preventing waste of blank costs. It also avoids positioning datum conversion errors caused by multiple clamping operations and plastic deformation during multiple machining processes, reducing product scrap rates. It eliminates the need for repeated alignment and positioning, and is suitable for batch processing on flexible production lines.

The application discloses a lithium ion battery state of charge estimation method based on an Informer, which comprises the following steps: collecting battery sample data, constructing an Informer network model, processing the battery sample data by using the Informer network model, and obtaining a state of charge estimation value of the lithium ion battery. The Informer network model used in the application reduces the point product calculation of the attention mechanism and improves the encoder-decoder architecture, thereby reducing the calculation complexity and spatial complexity, improving the model training and calculation speed, and to some extent, solving the cumulative error problem existing in the recurrent neural network, achieving higher SOC estimation accuracy, showing superiority in MAE and RMSE error indicators, and better solving the estimation difficulty under low temperature conditions and the problem of insufficient temperature expansion capability. The application is widely applied in the technical field of batteries.