4results about How to "Improve setting accuracy" patented technology

The application provides a pipe blank piercing process parameter self-adaptive optimization method and system, wherein the method comprises the following steps: acquiring the piercing process parameters and the pipe quality data of two-roller cross rolling; performing short-term self-adaptive optimization on the piercing process parameters through the pipe quality data and a preset short-term self-adaptive model; screening high-quality pipe quality data according to the results of the short-term self-adaptive optimization; establishing an excellent sample library based on the high-quality pipe quality data, wherein the excellent sample library comprises the high-quality pipe quality data and the piercing process parameters corresponding to the high-quality pipe quality data; performing long-term self-adaptive optimization on the piercing process parameters corresponding to the high-quality pipe quality data through the high-quality pipe quality data and a preset long-term self-adaptive model, and obtaining the setting precision interval of the pipe blank piercing process parameters. By using the application, the problems of low precision and low efficiency caused by the dependence of the current piercing machine process parameter setting on the calculation of the traditional analytical model and artificial experience correction can be solved.

The application discloses a construction linear control method for a large-span non-equal-span cast-in-situ box girder, and comprises the following measures: pre-camber optimization, theoretical deflection simulation based on a coupling model of the box girder and a movable formwork, model correction combined with pre-test, and selection of a sectional pre-camber design curve according to the span stiffness difference; deformation collaborative control, concrete pouring according to a layered sequence, control of the bottom form elevation and pouring interval time, and synchronous monitoring and coordination of the deformation of the movable formwork and the box girder; inter-span constraint control, rigid connection structure arranged in the unequal-span connection area to constrain the non-longitudinal displacement, and review of the elevation difference at the connection after pouring; stress adaptation control, real-time monitoring of the deflection and stress of the stress concentration area, and control through adjustment of the formwork elevation, adjustment of the pouring rhythm or addition of local reinforcing structure when the data is out of limit. The method can ensure that the bridge linear shape meets the design requirements and reduce the risk of structural stress concentration.

The image processing method disclosed herein includes: a step of acquiring first image data obtained by measuring a first sample using a first measurement means (S10); and a step of setting a candidate group of a first region of interest based on the first image data (S12). Furthermore, the image processing method includes: a step of acquiring second image data obtained by measuring the first sample using a second measurement means different from the first measurement means, reflecting a physical quantity different from the first image data (S14); and a step of setting a region of interest group in the first image data or the second image data based on the candidate group of the first region of interest and the second image data (S16).

The application provides a kind of air knife parameter setting method for continuous hot galvanizing production, relate to the technical field of hot galvanizing.The method comprises: generating air knife distance and height setting table based on historical production data statistical analysis, and realizing parameter continuous matching by using interpolation algorithm;At the same time, an air knife pressure prediction model based on random forest algorithm is constructed.Combining real-time data, parameters are extracted from the setting table and input into the model, and the output air knife pressure setting value is obtained.The setting table and the prediction model are updated and iteratively optimized using recent qualified data.The application obtains more accurate, stable and excellent air knife parameter setting for zinc layer thickness control through data acquisition, statistical analysis, setting table optimization, model construction and training, air knife pressure setting value output, adaptive updating and iterative optimization.The method is simple and easy to operate, low in cost, high in precision, strong in stability and high in efficiency, which is beneficial to industrial large-scale production and promotion.