14 results about "Systematic deviation" patented technology

The present application relates to hoisting control technical field, disclose a kind of based on digital twinning pipeline overall hoisting positioning error pre-control method, comprising the following steps: step S101, extraction single frame hole ring radial error time slope;Step S102, obtain single-axis scaling angular velocity is calculated;Step S103, obtain corrected angular velocity is calculated;Step S104, extraction distortion point set characteristic parameter;Step S105, generate pre-control instruction vector;Step S106, obtain final docking target pose is calculated.This application is according to single frame hole ring radial error time slope and the geometric sensitivity analysis of digital twinning, without multiple frame data splicing can accurately eliminate swing scanning asynchronous caused point cloud distortion, through feedforward network correction angular velocity system deviation, again fusion static geometry difference and dynamic pre-control instruction, realize the integrated compensation of static size position deviation and dynamic swing deviation, substantially reduce docking positioning error.

The invention provides a product research and development process management method and system, relates to the technical field of product research and development process management, and aims to timely discover and record deviation which is difficult to capture by a traditional test method by introducing identification of systematic deviation of a product module and generate a deviation characteristic digital identifier and an interaction characteristic label. Hidden deviations and potential interaction risks are managed in a structured and traceable mode, in the product use stage, data processing logic is dynamically adjusted according to deviation characteristic digital identification, data distortion or function abnormity caused by module deviation is avoided, module combination risk early warning is generated based on interaction characteristic labels, and the product quality is improved. According to the technical scheme, unreasonable module combination is avoided, and during fault diagnosis, the BOM is traversed, whether explicit calling and compensation logic of deviation characteristic digital identification exists in a software code library or not is judged, and a high-priority attribution report is generated in combination with a preset risk association rule set, so that root cause analysis of complex faults becomes more efficient and accurate.

The invention relates to the technical field of diaphragm performance detection, in particular to a method for testing the actual tensile breaking strength of a diaphragm, which comprises the following steps: (S.1) measuring the apparent geometric parameters of a diaphragm sample, the apparent geometric parameters including width and thickness; (S.2) acquiring a microscopic image of the section of the diaphragm; (S.3) based on the microscopic image, analyzing a pore area proportion in the cross section; (S.4) carrying out a tensile test on the diaphragm sample to obtain the maximum force during fracture; and (S.5) calculating the actual tensile breaking strength based on the apparent geometric parameters, the pore area proportion and the maximum force. According to the method, through combination of microscopic section analysis and macroscopic mechanical testing and introduction of the pore area proportion as a correction factor, systematic deviation caused by neglecting of a porous structure in a traditional method is effectively overcome, the accuracy of a tensile strength testing result is remarkably improved, and the testing data can more truly reflect the intrinsic performance of a material.

This invention discloses a safety assessment method for inverting the internal force state of anti-slide piles based on corrected inclinometer data. Inclinometer data is collected along the depth direction of the anti-slide pile using an inclinometer, and the data is preprocessed. A polynomial model is established to fit the pile deflection. Then, a constraint matrix and constraint vector are constructed, and the constraints are solved using regularization. The distribution of internal forces in the pile is calculated using derivatives. The quiet zone at the bottom of the anti-slide pile is identified, and the foundation coefficient at each measuring point is inverted. The distribution of landslide thrust and thrust characteristic parameters are analyzed. The safety factor is calculated using the extreme values ​​of thrust internal forces, and a safety assessment and early warning are provided for the project. This application intelligently integrates the measured displacement of the pile top dial gauge with the relative displacement data of the inclinometer tube, solving the system deviation problem caused by initial readings and zero-point drift. It can accurately reflect the actual stress and deformation characteristics of the pile body. A high-order polynomial continuous fitting model for the entire pile achieves a precise description from discrete measuring points to continuous deformation.

The application discloses a drilling fluid overflow real-time monitoring system and method, and relates to the field of drilling fluid monitoring. First, a prediction benchmark with physical meaning and stability is provided by using a drilling well transient hydraulics model, which ensures that the model will not produce a prediction completely contrary to physical logic when facing rare working conditions, and solves the problem of vulnerability of a pure AI model. Then, an AI model is specially trained to learn and predict systematic deviation (i.e. residual) of the physical model due to excessive simplification and parameter uncertainty. By compensating the residual predicted by the AI to the benchmark value of the physical model, a high-precision hybrid prediction result is generated, which directly overcomes the defect of insufficient accuracy of a single physical model. In this way, the physical model provides a reliable anchor point for the AI, and the AI makes accurate corrections for the physical model, thereby realizing accurate and robust real-time monitoring of the overflow signal.

The invention discloses a data-driven WMS storage optimization method and system, and relates to the technical field of storage management, and the method comprises the steps: obtaining the actual inventory number of a WMS system of a middle library material and the theoretical inventory number of an ERP system at the end of each preset statistical period, and calculating the inventory difference rate; continuously collecting inventory difference rates of a plurality of statistical periods to form a difference rate time sequence; calculating a difference direction consistency coefficient and a progressive trend change rate of the difference rate time sequence; when the difference direction consistency coefficient and the gradual trend change rate both exceed respective threshold values, judging that the material has systematic deviation; for the material with systematic deviation, calculating a BOM revision coefficient according to the average value of the difference rate time sequence, and generating a BOM revision suggested value; according to the method, automatic and reasonable constraint on the BOM revision amplitude is realized through a difference rate revision technology combining a difference rate average value, a statistical period number and a confidence coefficient adjustment coefficient.

The invention relates to the technical field of mining engineering and rock stratum control, and discloses a section coal pillar width determination method based on scour prevention, and the method comprises the steps: constructing a whole-process mining numerical model, and determining a first optimal interval according to stress evolution characteristics; extracting the maximum vertical stress value of the advance area of the working face, dynamically correcting the stress concentration coefficient in the limit equilibrium theory, calculating the width of the limit equilibrium area of the coal pillar, and determining the width as a theoretical hardness lower limit; based on a mine burial depth matching engineering case library, performing statistics to obtain a second optimal interval; and performing intersection operation on the dual optimization interval to obtain a preliminary feasible region, performing one-way inequality truncation by using a theoretical hardness lower limit, and selecting an optimal width in an effective decision space. According to the method, through triangular verification of numerical simulation, theoretical calculation and engineering analogy, systematic deviation of a single method is eliminated, and coal pillar parameters meeting the dual requirements of anti-impact safety and high resource recovery rate are accurately positioned.

The application discloses an artificial intelligence operation and maintenance method and system based on a large model, which comprises the following steps: obtaining operation data of a target platform in multiple time periods; determining first operation and maintenance instructions of the multiple time periods by using an operation and maintenance large model based on a preset operation and maintenance instruction set and the operation data, the preset operation and maintenance instruction set being associated with instruction features, the preset operation and maintenance instruction set comprising at least one operation and maintenance instruction, and the first operation and maintenance instruction being determined by at least part of the operation and maintenance instructions in the preset operation and maintenance instruction set associated with the instruction features matched with operation data of a corresponding time period of the first operation and maintenance instruction; obtaining simulation operation and maintenance information of the multiple time periods based on the first operation and maintenance instructions; performing reinforcement learning on the operation and maintenance large model based on the simulation operation and maintenance information to obtain systematic deviations of the multiple time periods; and generating second operation and maintenance instructions of the target platform by using a target large model based on the systematic deviations of the multiple time periods and the operation data, and sending the second operation and maintenance instructions to the target platform, so that the automation efficiency of operation and maintenance and the rationality of an operation and maintenance scheme can be improved.

The invention discloses a drilling fluid overflow real-time monitoring system and a drilling fluid overflow real-time monitoring method, and relates to the field of drilling fluid monitoring, firstly, a prediction reference with physical significance and stability is provided by using a transient hydraulic model of a drilling shaft, so that the model is ensured not to generate prediction completely violating physical logic when facing rare working conditions; the problem of vulnerability of a pure AI model is solved. Then, an AI model is specially trained to learn and predict systematic deviation (namely, residual errors) generated by excessive simplification and parameter uncertainty of the physical model; a high-precision mixed prediction result is generated by compensating the residual error predicted by the AI to the reference value of the physical model, so that the defect of insufficient precision of a single physical model is directly overcome. According to the deep fusion mode, the physical model provides a reliable anchor point for the AI, and the AI accurately corrects the physical model, so that accurate and robust real-time monitoring of the overflow signal is realized.

The application discloses a tunnel over-under excavation measurement method and system without control points photogrammetry registration, and relates to the technical field of tunnel engineering measurement. Multi-source data of a tunnel containing at least three sections of lining and irregular profiles of an excavation surface are collected, three-dimensional point clouds are generated, and a lining point cloud subset is extracted after preprocessing. Transformation parameters are determined through multi-reference registration, over-under excavation deviation is calculated, and a trend prediction model is established. Without external control points, the application has the following advantages. A feature point set-whole profile double reference is constructed by using feature points such as ring joints of multi-section discontinuous lining and steel reinforcement reserved holes, a lining construction deviation compensation model is introduced to correct systematic deviation of the lining itself, the problem that a single lining reference is easily disturbed by construction deviation is solved, and an environment adaptive strategy is combined to distribute data source weights according to texture characteristics and adjust a collection mode according to environment parameters, so that the defect that a single data source has insufficient robustness in a tunnel weak texture and high dust environment is solved.

The application discloses a pig weight and body size measuring method, and belongs to the field of pig weight and body size measuring. The method comprises the following steps: collecting a back video above a cage scale and frame extraction to obtain a video frame set; constructing a structure adaptive coordinate corresponding to each video frame; initializing distortion parameters and scale parameters; performing body size measurement; if the distortion parameters and the scale parameters are converged, performing weight measurement, and calculating a weight uncertainty approximation and an abnormality proportion; if the weight uncertainty approximation or the abnormality proportion is greater than a corresponding threshold, performing re-measurement, otherwise, taking a segment-level body size and an observed weight of a current round as final pig body size and weight; if the distortion parameters or the scale parameters are not converged, sequentially updating the distortion parameters and the scale parameters, and returning to perform body size measurement again according to the updated distortion parameters and the scale parameters. The application solves the problems of scale calibration difficulty, unfixed visual angle and scale drift in the prior art, and the problems of systematic deviation of body size / weight.

This invention provides a method, apparatus, and system for determining the minimum test size of a flying probe testing machine. The method first determines the systematic and random deviations of the moving screw and target positioning accuracy in the flying probe testing device based on a moving screw and target positioning test. Then, it determines the systematic and random deviations of the vertical drop accuracy of the test probe in the flying probe testing device based on repeated probe drop tests. Finally, based on the systematic and random deviations of the moving screw and target positioning accuracy and the vertical drop accuracy of the test probe, and using an accuracy prediction model, the minimum test size of the flying probe testing machine is determined. This allows for a direct prediction of the minimum size of the solder pads that the current flying probe testing device can test, preventing frequent test probe misalignment errors and misjudgments / missed judgments due to insufficient testing accuracy of the flying probe testing device. It also reduces testing time extended by manual intervention and improves the testing efficiency of the flying probe testing device.

This invention discloses a method for identifying the geometric error of the B-axis in a five-axis swivel-head CNC machine tool, belonging to the field of CNC machine tool accuracy testing and error compensation technology. The method first establishes a B-axis body coordinate system model, measuring position-independent perpendicularity and angular positioning errors as known parameters. Then, it sequentially executes four measurement modes: B-X, B-Z, B-Y, and B-XY, obtaining the equations for the change in rod length of the ballbar in each direction. By solving the simultaneous equations, it sequentially solves for the three runout errors and three angular errors of the B-axis, completing the identification of all six position-related geometric errors. This invention has advantages such as comprehensive error identification, high measurement efficiency, high identification accuracy, small systematic deviation, adjustable parameters, and strong engineering applicability, and is suitable for the rapid and accurate identification of B-axis geometric errors in various types of five-axis swivel-head CNC machine tools.

The invention relates to a coating information prediction method and device for a silicon steel coating, equipment and a medium. The method comprises the steps that coating liquid basic parameters are obtained in real time; based on the coating liquid basic parameters and a preset initial quality prediction model, obtaining an initial quality prediction value of the silicon steel coating in unit area; based on the coating liquid basic parameters and a preset initial thickness prediction model, obtaining an initial thickness prediction value of the silicon steel coating in unit area; based on the initial quality predicted value and the initial thickness predicted value, a target quality predicted value and a target thickness predicted value of the coating in unit area are obtained, and the target quality predicted value and the target thickness predicted value are final credible values used for production control and quality judgment after the corresponding initial predicted values are superposed with correction values. According to the dynamic correction mechanism, systematic deviation caused by hydration reaction and magnesium carbonate generation is eliminated, online prediction and closed-loop control of coating parameters are achieved, and real-time data support is provided for technological parameter optimization.