4results about How to "Reduce statistical error" patented technology

The application provides a frequency standard measurement method, device, computer equipment and storage medium, the method comprises: frequency source output measurement signal is carried out frequency division processing, obtains low frequency pulse signal; using high-precision time interval counter to low frequency pulse signal is carried out delay measurement and time interval counting, and is output in the form of time stamp; by setting a sliding window, using sliding average algorithm to time stamp is carried out sliding average filtering processing, all time stamps are carried out sliding difference to obtain time difference, time difference is grouped according to order and is taken average in group to obtain average time difference; by increasing the length of the sliding window, the number of samples is increased to reduce the statistical error; using average time difference, calculate frequency measurement value, relative frequency deviation and allan variance. The method of the application increases the sliding window, and the frequency measurement result obtained by the algorithm of grouping and averaging the time difference has higher measurement precision and stability.

The invention discloses an intelligent top pipe splitting method based on a BIM technology. The method comprises the following steps that 1, a first Revit self-adaptive pipe joint family is manufactured; 2, generating an overall model of the pipeline according to a projection path of the pipeline by using the first Revit self-adaptive pipe joint family; 3, by means of Dynamo software, the splitting fixed length and the splitting distance of the pipeline are preset, segmentation is conducted, and multiple segments of segmented curves are obtained; 4, processing all the segmentation curves through Boolean operation by utilizing Dynamo software to obtain corresponding segmentation curves segmented into accurate lengths; 5, by utilizing Dynamo software, generating all pipe joints after the pipeline is segmented through the segmentation curve; 6, according to a preset corner threshold value of the adjacent pipe joints, the corner between the adjacent pipe joints is calculated; and 7, exporting a detailed list of all the pipe joints. According to the method, design and machining can be quickly joined, the material statistical error is reduced, and the design and machining efficiency is improved.

The application provides a rock mass internal joint network reproduction discrete element modeling method, comprising the following steps: measuring field joint information; establishing a discrete element numerical model; arranging a geological profile along the ore body dip direction; cutting a roadway boundary in the numerical model, cutting the measured joint information in the rock mass, and analyzing the correlation between the measured joint length and the triangular block length; selecting the range of the measured joint length and the triangular block length, respectively calculating the simulated joint size and the triangular block size of the hanging wall, the ore body and the footwall, simultaneously calculating the simulated joint spacing and the simulated gap, and embedding the numerical model; and based on the joint geometric parameters, constructing the joint network model of the hanging wall, the ore body and the footwall respectively. The engineering adaptability of the application is enhanced, the deep roadway surrounding rock stability analysis is supported, the model prediction result is close to the field monitoring data, and a reliable basis is provided for support design.

The invention provides a screening method and system for a blast furnace heat prediction model, and relates to the technical field of blast furnace smelting. The method comprises the following steps: training a plurality of candidate prediction models; calculating a combined evaluation index of each model for furnace heat abnormity early warning, wherein the indexes comprise three indexes for measuring prediction accuracy, abnormity capture capability and early warning advance; and determining an optimal prediction model according to an evaluation result of the combined evaluation indexes. According to the method, the combined evaluation indexes oriented to abnormal early warning are constructed, so that the model evaluation standard is aligned with the actual production demand, the screened optimal model has the capability of accurately early warning the key furnace heat abnormality in advance, precious reaction time can be won for field operators, and the method has relatively high practical value.