9results about How to "Reduce statistical error" patented technology

The invention discloses an image recognition method and system for casting crude sand particle size distribution. The method comprises the steps that a crude sand particle image is obtained and preprocessed; introducing an instance segmentation branch network into the convolutional neural network model, and constructing an instance segmentation model; performing sand grain segmentation on the preprocessed crude sand grain image through a pre-trained instance segmentation model; calculating shape features of the sand grains according to the sand grain segmentation result, converting the shape features of the sand grains from a pixel size to an actual size, and calculating equivalent diameters and shape factors of the sand grains; and performing mesh classification according to the equivalent diameter and the shape factor of the sand grains, and counting the number of the sand grains of each mesh to obtain a casting crude sand grain size distribution identification result. According to the embodiment segmentation model constructed by the invention, the embodiment segmentation of the bonded sand grains can be realized, the statistical error caused by sand grain bonding is reduced, and the mesh classification and the casting crude sand particle size distribution statistics are carried out according to the shape characteristics of the sand grains, so that the calculation accuracy is improved.

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 present invention discloses an image recognition method and system for the particle size distribution of raw sand for casting, the method comprising: obtaining raw sand particle images and preprocessing them; introducing an instance segmentation branch network into a convolutional neural network model to construct an instance segmentation model; performing sand segmentation on the preprocessed raw sand particle images through a pretrained instance segmentation model; calculating the shape characteristics of the sand particles according to the sand segmentation results, and converting the shape characteristics of the sand particles from pixel size to actual size, calculating the equivalent diameter and shape factor of the sand particles; performing mesh classification according to the equivalent diameter and shape factor of the sand particles, counting the number of sand particles of each mesh, and obtaining the recognition result of the particle size distribution of raw sand for casting. The instance segmentation model constructed by the present invention can realize the instance segmentation of the sticky sand particles, reduce the statistical error caused by the sticking of the sand particles, and perform mesh classification and statistics of the particle size distribution of raw sand for casting according to the shape characteristics of the sand particles, thereby improving the accuracy of the calculation.

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 present invention belongs to the field of spectroscopy technology, and in particular, relates to a device and method for measuring the absorbance spectrum of a solution. The device includes a continuous spectrum white light source, a cuvette holder, a variable optical path assembled cuvette, a fiber optic spectrometer and a host computer. The variable optical path assembled cuvette is built with a solution to be tested, and the variable optical path assembled cuvette is arranged in the cuvette holder. The white light emitted by the continuous spectrum white light source passes through the solution to be tested and then enters the fiber optic spectrometer. The fiber optic spectrometer is connected to the host computer. The fiber optic spectrometer collects the spectrum of white light under the control of the host computer, and the host computer calculates the absorbance spectrum of the solution to be tested according to the spectrum. The present invention is suitable for trace, strong solvation effect and high transparency solutions, the device has low cost, and can achieve one-time absorbance spectrum measurement.

The invention discloses a method for rapidly obtaining a BNCT neutron energy spectrum, and solves the technical problems of long neutron energy spectrum obtaining time and low accuracy in the prior art. Comprising the following steps: bombarding a target material by protons with specific energy and angle to generate target neutrons; the target neutrons are moderated and shaped by the beam shaping device and then target neutrons are obtained at the exit window; extracting the proportion of the protons in each energy and direction in the accelerator proton energy spectrum, multiplying the proportion with the corresponding target neutrons in the database, and adding together to obtain a target neutron energy spectrum; and the target neutrons pass through the beam shaping device, and the neutron energy spectrum of the final exit window is obtained by adopting the same method according to the target neutron energy spectrum. According to the method, the required neutron energy spectrum can be rapidly obtained through proton energy spectrum calculation, when the neutron energy spectrum is unreasonable, the next neutron energy spectrum can be rapidly obtained through calculation, and compared with a traditional method, the neutron energy spectrum can be obtained more rapidly, and the error-tolerant rate is higher.

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.

The invention provides a method for accurately detecting the thickness of a tunnel secondary lining concrete protection layer. The method comprises the following steps: step 1, acquiring an actual detection image of a reinforcing steel bar in concrete; 2, processing the actual detection image of the reinforcing steel bar to obtain a corresponding geometrical relationship curve; 3, deducing a corresponding geometric equation according to the geometric characteristics of the geometric relation curve; 4, processing the geometric equation to obtain an electromagnetic wave propagation velocity v; 5, substituting the data to obtain an accurate electromagnetic wave speed; and step 6, performing time-depth conversion to obtain the accurate thickness of the concrete protection layer. According to the invention, the concrete thickness measurement precision is improved, the detection time is obviously shortened, and the field operation is simpler and more convenient.