33results about How to "Preserve continuity" patented technology

The invention, a spiral-guided curved face numerical control machining method, belongs to the numerical control trajectory planning and processing areas. A spiral-guided curved face numerical control machining method is, processing the workpiece with 3D curved face mesh, making spline-interpolation-based planar isometric or non-isometric spiral line as the parameter line, and by mapping, generating 3D physical space processing trajectory, that is, with the clear mathematical expressed planar spiral line guidance, and the pitch of the spiral line should be determined by the spacing requirements of the processing trajectory. First, according to the 3D curved face of the workpiece, make processing trajectory planning; then, according to the used numerical control machine make post-processing to the planed trajectory. Using the spiral-line guided curved face machining method, the cutter movement smooth, wearing small, machine noise low, efficiency high, and save a lot of processing time, decrease the production cost.

The invention discloses a method for achieving up-sampling of a low-resolution depth image based on image features. According to content-based variance of the low-resolution depth image, content-based variance of a low-resolution color image and the coefficient of association between corresponding pixel points of the low-resolution depth image and the low-resolution color image, pixel values obtained after up-sampling of pixel points of the foreground edge of the low-resolution depth image can be well guided to reflect edge information, obtained after up-sampling, of the high-resolution depth image; for discontinuous pixel points in the low-resolution depth image, replacement and refinement are carried out on pixel values, obtained after up-sampling, of the discontinuous pixel points based on pixel points, in a window, of the low-resolution depth image according to the level of similarity between the pixel values obtained after up-sampling and pixel values, with the pixel values obtained after up-sampling as the center, of the pixel points in the appointed window, and therefore the continuity of the high-resolution depth image obtained after up-sampling can be well kept. Through the two steps, edge blur of the low-resolution depth image can be effectively restrained in the up-sampling process.

The invention relates to the technical field of machine part machining, in particular to an automobile hub bolt and a machining technology of the automobile hub bolt. The machining technology of the automobile hub bolt comprises the following technology steps of cold heading, heat treatment, tooth rolling, blacking and dehydrogenation. The automobile hub bolt comprises a lock head and a lock pillar, wherein the lock head and the lock pillar are integrally formed. Threads are formed on the outer surface of the lock pillar, and a positioning shaft shoulder is arranged between the lock pillar and the lock head. A notch is formed in the positioning shaft shoulder. According to the automobile hub bolt machining technology, heat treatment is performed at first, and the treatment of tooth rolling is then performed, metal flow lines of the threaded portion of a product and continuity of uniform organizations after the heat treatment can be better protected, and the adverse risks of decarburization, recarburization, cracking and the like of the product can be obviously prevented. The automobile hub bolt is high in strength, good in safety performance of use and capable of effectively reducing safety risks and danger of an automobile.

The invention discloses an analysis model construction method for typical characteristics of the wind power output. Original data are obtained and data pretreatment is carried out, the data are normalized by using multi-temporal-scale wind power volatility and simultaneous rate valuation indexes, and segmented aggregation is carried out to reduce the dimension; on the basis of an improved adaptivefuzzy clustering algorithm, an adaptive function alpha (c) is calculated and an optimal cluster number c is determined, and wind power output characteristics are classified; a variation dispersion coefficient betai is introduced and wind-power output distortion data are rejected; and a partition weighted median probability estimation method is put forward and a wind-power output daily typical characteristic curve/zone band is identified and extracted. According to the invention, the multi-space-scale large-scale wind power output characteristics and monthly, quarterly or yearly multi-time-scale wind-power output characteristics are analyzed and calculated and the wind-power output daily typical characteristic curve/zone band is extracted, so that the power operation staff can master the wind-power output rule well and a technical reference is provided for real-time scheduling of a power system, scheduling plan arrangement, wind farm planning and system backup configuration.

The invention discloses a video decoding method and a video decoder, which are used for receiving video code streams sequentially and decoding and outputting the video code streams. The video decodingmethod comprises the following steps: marking errors; recording error codes in the process of decoding according to the decoding situation; concealing the errors; generating error concealment parameters according to the error codes recorded in the step of marking the errors; and outputting the error concealment parameters and decoded video code stream data according to a receiving sequence.

The invention provides a method for processing data and identifying fluctuations of historical wind power output, which consists of the steps of: collecting historical wind power output data and analyzing & arranging the output data; carrying out the normalization processing and wavelet filtering processing of the analyzed and arranged historical wind power output data and then carrying out fluctuation division; checking the historical wind power output data and the wind fluctuation clustering effect by means of a visualization method. The invention provides the method for processing data and identifying fluctuations of historical wind power output, which can be used as the pre-stage basis of long-term output time series modeling of wind power and can also be used for the planning and operation analysis of the power system including wind power.

The invention relates to a carbon fiber winding paving variable cross-section adhesive transmission shaft and a combined type mould thereof. The carbon fiber transmission shaft comprises a carbon fiber tube 1, an integrated joint 2 and the combined type mould. The two ends of the carbon fiber tube 1 are bonded on the integrated joint 2, a three-ball pin column at the other end of the integrated joint 2 is matched with a needle bearing 3 and a ball ring 4 to form constant-speed universal connection, and the needle bearing is limited by a clamp spring. A clamp 5 is in a cylindrical shape, and the mold and machining equipment are connected by the clamp 5. The combined type mould comprises a mould body 6 with the two ends being hexagon-like cross sections (including a transition section) and amould body 7 with the middle being circular cross section, and the combined type mould is positioned and matched by a groove and a boss on the mould and then connected with the cylindrical clamp 5. Acenter hole of a square block 8 is used for assisting demoulding. According to the carbon fiber winding paving variable cross-section adhesive transmission shaft and the combined type mould thereof,the design is reasonable, assembly and disassembly of the mould are convenient, the paving scheme is flexible, the problem that demoulding is difficult is solved, the material performance is sufficiently utilized, the transmission shaft and the combined type mould can adapt to different machining equipment and working conditions, the feasibility and operability are high, the weight is lowered by about 53% compared with steel, the inertia is reduced, and energy is saved.

The invention provides a big data multidimensional data indexing method based on a space-filling curve and relates to the field of data indexing technology in the big data environment. According to the method, first, a new space-filling curve Flat-zorder is utilized to perform linearization on each record in a file, and then index creation, data retrieval and index update and maintenance are realized according to the corresponding relation between the linearization result and a file name. The Flat-zorder space-filling curve only requires that dimensions are expanded according to an integer ratio, therefore, the continuity of a linear id value on each dimension is reserved, and acceptable complexity and time complexity are achieved. Through the big data multidimensional data indexing methodbased on the space-filling curve, compared with traditional multidimensional data indexing, index creation and update efficiency is improved, data retrieval speed is increased, the size of an index file is reduced, and meanwhile precise matching query and range query are supported.

The invention provides a high-strength TBM center cutter box and a preparation method. The center cutter box comprises an outer cutter box and an inner cutter box, wherein the outer cutter box is madeof a structural steel material; the inner cutter box is made of a low-carbon medium-alloy structural steel material; and the inner cutter box and the outer cutter box are combined through welding. The center cutter box provided by the invention has the beneficial effects that the inner cutter box is treated with tempering and hardening, connection is realized in a firm of welding of the inner andouter cutter boxes, the inner and outer cutter boxes are formed by a forging technology, and the inner cutter box is made of low-carbon medium-alloy structural steel, so welding stress centralization, cracking and deformation of the inner and outer cutter boxes are reduced; through surface hardening of the inner cutter box, strength and fatigue performance of bearing parts can be enhanced; and through de-stress annealing of the inner and outer cutter boxes, distribution of residual stress during forging formation and welding stress centralization points of the inner and outer cutter boxes canbe reduced.

The invention provides a continuous flatly-pressing process for preparing a light wafer board from ultrathin wafers. The process comprises the following steps: 1) slicing wet wood raw materials into the ultrathin wafers; 2) carrying out mesh-belt low-temperature drying on the ultrathin wafers to reach a proper moisture content; 3) gluing the dried ultrathin wafers in a manner of flexible spray gluing and through a tank-type gluing machine; 4) uniformly laying the glued ultrathin wafers by virtue of a plurality of groups of multi-shape laying heads to obtain a board blank; and 5) carrying out hot-pressing shaping on the board blank in a manner of continuous hot-pressing. The process has the following characteristics: the ultrathin wafers are prepared by virtue of middle- and low-grade raw materials, the shape integrity of the wafers is kept through the methods of flexible drying and gluing, then the structure uniformity of the board blank is ensured by virtue of the layered laying of the plurality of laying heads, and continuous production line preparation for the high-performance and low-density wafer board is realized. The preparation process is high in production efficiency; andthe prepared wafer board product is low in density, high in performance, and high in market competitiveness.

The invention relates to the technical field of automobile driving, can be applied to automatic driving vehicles, and particularly relates to a driving style identification method and device, the method comprises the following steps: obtaining each feature vector value of a target vehicle at each continuous moment, the feature vectors being used for representing the instantaneous driving state of the target vehicle, the feature vector comprises a state feature used for representing a state between the target vehicle and a related object thereof; sampling each feature vector value by taking continuous N values as a sampling unit to obtain a plurality of samples, N being a preset value; and determining the driving style of the target vehicle according to the plurality of samples. Based on the technical scheme provided by the invention, the driving style identification result can be more comprehensive and accurate.

The invention relates to a continuous modeling method considering upstream and downstream linear design parameters of a road section, and is applied to the field of combined linear safety assessment and optimization. The method comprises: a road operation index change sequence of a driver sample is collected, and when upstream and downstream linear parameters are extracted, the optimal set metering distance of operation indexes is selected by comparing the fitting goodness of a prediction model; extracting a mean value from the continuous variable speed to construct a multivariate linear regression model, and constructing a hybrid linear model taking a driver as a classification variable based on the individual value of the driver of each variable; and according to model comparison and parameter estimation results, selecting an upstream and downstream set counting distance with an optimal fitting effect; and finally obtaining a model parameter estimation result.

The invention provides an unsupervised driving style analysis method based on a basic driving operation event. The unsupervised driving style analysis method comprises the steps that data are acquired and preprocessed; extracting a basic driving operation event; performing feature construction and extraction on each event in the basic driving operation events to obtain event intensity features; event intensity clustering is carried out through k-means, and event intensity category labels are marked; obtaining a dynamic time window, and constructing a time-varying event curve which represents a driving style in the dynamic time window and has an event intensity category label; and based on a curve clustering algorithm fused with DTW, the curves of the dynamic time windows are clustered to obtain various time window curves, and driving style types are labeled. According to the method, a basic driving operation event is taken as a basic unit, event intensity and event transfer characteristics are considered, a change curve of the event along with time is taken as a characteristic for describing a driving style, dynamic decision information, data continuity and time characteristics of a driving behavior are reflected, original data information is reserved, and driving style analysis accuracy is improved.

The invention is suitable for the field of image processing, and provides a method and device for smoothening a disparity map and electronic equipment. The method comprises the following steps: initializing A(z, y), B(x, y) and F(x, y) into all-zero matrixes; acquiring all pixel points (x<k>, y<k>) satisfying S(x, y)=k in S(x, y); making A(x<k>, y<k>)=M(x<k>, y<k>), B(x<k>, y<k>)=1; computing all A(x<k>-i, y<k>-i) and T(x<k>, y<k>) taking x<k>, y<k> as a center; computing the sum of all B(x<k>-i, y<k>-i) taking x<k>, y<k> as a center to obtain the quantity T(x<k>, y<k>) of all the pixel points satisfying S(x, y); and computing F(x<k>, y<k>) according to T(x<k>, y<k>) and T(x<k>, y<k>). Through adoption of the method and device for smoothening the disparity map and the electronic equipment, the smoothness or continuity of disparity is realized, and the sudden change or discontinuity of an object edge is kept.