9 results about "Fiber clustering" patented technology

The invention relates to a method for characterizing the size of an irregular proppant-fiber cluster unit in a slit, and the method comprises the steps: S1, carrying out a proppant-fiber mixed conveying physical model experiment, obtaining an experiment image, carrying out the preprocessing and threshold segmentation of the experiment image, focusing on a region of interest (ROI), and obtaining a proppant-fiber cluster unit size; dividing the pixel value of the image into continuous intervals according to a preset threshold parameter, and generating a multi-category segmentation mask; s2, performing multi-scale morphological operation on the segmented masks, removing small noise cluster units and filling internal holes of the cluster units; s3, identifying each connected region in the image, counting the area of the connected region, and dividing cluster units according to a preset level; and S4, performing color gradient rendering, contour labeling and area numerical value labeling on the cluster units of different levels to enhance the visual discrimination, and outputting an image. According to the experimental image processing method provided by the invention, the information of each cluster unit can be more intuitively obtained, and the action mechanism of the proppant-fiber cluster unit can be clearly known.

The invention provides an in-slit amorphous proppant-fiber cluster unit identification and size distribution characterization method, which comprises the following steps: S1, carrying out a proppant-fiber conveying experiment, carrying out local distribution division on an experiment picture according to a preset method, and respectively carrying out threshold segmentation on each local block, obtaining an overall mask matrix and dark pixel point coordinates of the experimental picture; s2, each dark pixel point is taken as an initial center, expansion is carried out around, a cluster unit index matrix is formed, and cluster unit segmentation is realized; s3, filling holes in the cluster units, identifying a hole area completely surrounded by a single cluster unit by scanning zero-value elements in an index matrix of the cluster units, and filling the holes with indexes of peripheral clusters; and S4, carrying out statistics on all cluster units, converting a pixel area into a real area, and outputting size distribution parameters of the cluster units. According to the invention, the automatic identification of the amorphous proppant-fiber cluster unit in the slit and the characteristic parameter output of the cluster unit can be realized.

The present disclosure belongs to the technical field of oil exploitation, and specifically relates to a temporary plugging fiber cluster, and a preparation method therefor, a usage method therefor and the use thereof. The temporary plugging fiber cluster provided by the present disclosure comprises degradable fiber filaments and a degradation promoter, wherein the degradable fiber filaments are wound around the outside of the degradation promoter.

The application discloses a cross-subject electroencephalogram emotion calculation method based on manifold dynamics, belongs to the field of electroencephalogram emotion calculation, and comprises the following steps: modeling an electroencephalogram observation space as a fiber cluster structure, realizing decoupling of emotional semantics and individual styles through instance normalization, and generating an enhanced sample set by using random style perturbation. A consistent autoencoder is constructed to map the samples to a low-dimensional latent space, and the geometric barycenter of multi-source domain data is mined as a canonical attractor. On this basis, a conditional flow matching technology is adopted to learn a time-dependent vector field, the source domain distribution is continuously evolved to the canonical attractor along an optimal transmission path by driving the source domain distribution through a neural ordinary differential equation, and the aligned features are obtained to complete emotion classification. The application realizes effective elimination of individual differences under the premise of maintaining the integrity of the topological structure, and significantly improves the accuracy and robustness of cross-subject emotion recognition.

The invention relates to the technical field of equipment control, and discloses a laboratory equipment control system and method based on data processing, and the system comprises a multi-scale feature analysis module, a topological manifold evolution module, a fiber cross section solving module, a singular point standard resolution module, a leaf-shaped structure discretization module and a semantic instruction coding module. Analyzing the original data to obtain multi-level stability features; carrying out topological structure evolution on the dynamic operation state to obtain a state evolution manifold; performing relation mapping on the state evolution manifold, and performing constraint derivation on the fiber bundle structure to obtain a continuous control section; performing abnormal point digestion on the continuous control section to obtain an ideal control manifold; carrying out leafy structure segmentation on the ideal control manifold, and carrying out cross discretization on the basic leafy structure to obtain a control action sequence; performing semantic coding on the control action sequence to obtain an operation instruction set; according to the invention, the reference information generation efficiency based on artificial intelligence and smart home can be improved.

The present application relates to a kind of surface flowing fiber cluster topology optimization method;The present application uses material interpolation method to determine surface flowing model, implicit two-dimensional manifold of surface flowing is defined on bottom flow form, porous medium is filled on implicit two-dimensional manifold, while artificial Darcy friction coefficient is introduced to surface Navier-Stokes equation, and surface flowing fiber cluster topology optimization is realized by filling porous medium to fixed two-dimensional manifold.

The invention discloses an image instance segmentation method for overlapping and separating fiber agglomerates in a papermaking process, and the method comprises the following steps: constructing a papermaking fiber suspension microscopic image data set, and carrying out the data preprocessing; constructing an image instance segmentation network model, and dynamically generating a thermodynamic diagram prior graph of a fiber category by using a Transform decoder output feature; carrying out down-sampling on a prior graph of the thermodynamic diagram and then fusing with original mask attention, and constructing an attention enhancement mechanism guided by thermodynamic diagram saliency; and constructing a thermodynamic diagram saliency loss function containing coverage degree and separation degree constraints, performing joint optimization with the native loss, and finally outputting a fiber mass image instance segmentation result. The method can effectively improve the separation precision of overlapped fiber agglomerates and the segmentation performance of small-scale instances, and is suitable for intelligent analysis of high-flux and high-precision fiber morphology in the papermaking industry.

The application discloses a kind of multi-working condition motion control method and system of movable platform, belong to multi-working condition motion control technical field;The method specifically includes: collection multi-working condition motion sequence set, constructs multi-working condition motion fiber cluster space, and is searched by particle swarm optimization algorithm transition mapping parameter optimization, obtains multi-working condition control benchmark set;Based on multi-working condition control benchmark set, motion semantic reduction operator fragment is screened out, and normal form rewriting reduction is carried out, constructs heading velocity coupling change diagram, obtains unified motion target set;Based on unified motion target set, generates multi-working condition motion joint control instruction sequence, carries out multi-working condition motion control to movable platform;The application improves the control continuity of multi-working condition motion control, enhances the stability of multi-working condition motion control.

The application belongs to the field of atomic emission spectrum analysis equipment and analysis technology, and particularly relates to a three-dimensional network fiber cluster micro-plasma excitation source and a spectrum detection device and method. The excitation source comprises a fiber tip discharge cluster working electrode and a counter electrode. The fiber tip discharge cluster working electrode and the counter electrode are horizontally arranged opposite to each other and a preset discharge gap is kept in the middle. The fiber tip discharge cluster working electrode and the counter electrode are electrically connected with the positive pole and the negative pole of a high-voltage direct current power supply respectively to form a discharge loop. The fiber tip discharge cluster working electrode comprises a fiber cluster conductor and an insulating support tube. The fiber cluster conductor is assembled in a strip or columnar form in the inner cavity of the insulating support tube. The fiber cluster conductor is a carbon felt strip. The three-dimensional isotropic random interweaving characteristics of the carbon felt fiber are utilized to construct a high-density micro-discharge site in a millimeter-level limited space. The field intensity interference between parallel fibers is effectively broken, and a cluster-shaped micro-plasma with high energy density is induced at a lower direct current voltage.