16 results about "Data point" patented technology

A method and apparatus is provided for fault detection and classification based on calculating distances between data points. The method comprises receiving a data sample representative of measurements of one or more variables associated with a process operation, determining a distance between the data sample and one or more data points of a history data of the process operation and detecting a fault associated with the process operation based on the distance between the data sample and the one or more data points of the history data.

The invention discloses an underwater three dimensional terrain reconstruction method based on multi-beam sonar data, comprising the following steps of: firstly, collecting echo wave strength data and also measuring sounding data; secondly, carrying out linear interpolation on the sounding data and obtaining the sounding data having the same space resolution with the echo wave strength data; thirdly, calculating an angle and a range between a beam of each sounding data point and a horizontal line; fourthly, calculating the beam incident angle of each sounding data point by a point-by-point way; fifthly, fitting model parameters of a reflection model based on the echo wave strength data and correcting the angle between the beam and the horizontal line; seventhly, setting an iteration number N and enabling an average relative error absolute valve of estimated echo wave strength data and the collected echo wave strength data to be minimum; and eighthly, calculating sounding data and reconstructing an underwater three dimensional terrain. The method can enhance the space resolution of the sounding data and has an important significance on the aspects of underwater substance exploration, three dimensional visualization, underwater target detection and the like. The reconstructed underwater three dimensional terrain is also nearer to the real terrain.

A system for removing artifacts caused by x-ray reflective materials from an x-ray image of a patient's teeth. The system includes an x-ray source, an x-ray detector that captures several x-ray images, and a surface scanner that captures a surface scan of the patient's teeth. An image processor generates three-dimensional models from the optical surface data and the CT volumetric data. The models are resized and oriented to be of the same scale and orientation and then overlaid to create a combined data set. Data points that extend beyond the surface of the patient's teeth in the surface model are identified and may be removed if it is determined that they are artifacts. An artifact-reduced CT model is then displayed.

The invention provides a real-time three-dimensional image illumination simulation method based on graphics processing units. The method orderly comprises the following steps that: (1) to-be-processed texture in three-dimensional image data is saved in a graphics processing unit; (2) the graphics processing unit calculates the illumination amount of texture data points according to an illumination model arranged in the graphics processing unit; and (3) the graphics processing unit mixes the illumination amount of the texture data points with a data value. The calculation for the illumination amount of the three-dimensional image data has brightness calculation as well. The illumination simulation method can allow an image displayed on a screen to vividly simulate the illumination effect in the nature, and furthermore, the calculation for the illumination amount of each data point also has the brightness calculation, thereby ensuring that the image displayed on the screen has a concave-convex effect, so as to increase the reality effect of the image further. Because of the high-speed parallel mechanism of the graphics processing unit, the operation time needed by the illumination simulation calculation is little, which meets the requirement of the three-dimensional images on real-time display.

The invention relates to a cloud point filtering method and device, computer equipment and a storage medium. The method comprises that cloud point data is obtained; the cloud point data includes a setof data points obtained from the road scanning environment; a neighborhood of a present data point in the point cloud data is determined; when the counted first number of data points in the neighborhood of the present data point is lower than a preset threshold, the present data point is determined to be a candidate noise point; the candidate noise point as a seed point carries out regional growth to obtain a target growth region; when the counted second number of data points in the target growth region is lower than a preset threshold, the candidate noise point as a noise point is filtered from the point cloud data. The noise point is located preliminarily, and then determined by regional growth and filtered, data points formed by objects in the far place and sparse data points in the point cloud data are protected, and the accuracy of point cloud filtering is improved.

Method for improving the quality of a set of a three dimensional (3D) point cloud data representing a physical surface by detecting and filling null spaces (606). The method includes analyzing (206) the data to identify the presence of a plurality of level 1 fractals (401), each defined by a plurality of voxels (400) containing data points arranged in one of a plurality of three-dimensional patterns. The method also includes selectively filling (212) voxels in the 3D point cloud data with a first predetermined limited number of data points to increase a number of instances where level 2 fractals (604) can be used for representing the 3D point cloud data. Each level 2 fractal is defined as a common plurality of the level 1 fractals having a common three-dimensional pattern, where the common plurality of level 1 fractals are also arranged in accordance with the common three dimensional pattern.

The invention provides an abnormal data detection method and device, and the method is applied to the technical field of data processing and comprises the steps of obtaining the to-be-processed data;clustering the to-be-processed data according to a clustering algorithm to obtain a cluster; pruning the cluster and determining an outlier score of each data point in the pruned cluster; and if the outlier score of a certain data point is higher than a preset threshold value, determining the data point as abnormal data. According to the abnormal data detection method and device provided by the invention, the abnormal value of the to-be-processed data can be accurately detected.

A real time data compression method examines whether a present read-in data point is in a predicted tolerable error range. If yes, the previous data point is deemed as redundant and is ignored and after which a new data point is read in for comparing again. When a predetermined amount of data points is continuously ignored, it means the data is steady and only the final data point of these ignored ones is recorded. Otherwise, when data is varied greatly during a period, only the total amount of these varying data points and their value are recorded so the memory capacity for storing the compressed data is saved. Furthermore, the compressed data is stored in a form of a data structure in which the compressed data are expressed by multiple blocks. The block form allows increase of the efficiency of the searching process of the compressed data.

The invention discloses a heart rate data points extraction algorithm based on a piezoelectric sensor. Firstly, data preprocessing to original data S is conducted, after the processing, a new optimized data sequence A is obtained, then a local extremum value points sequence B is extracted from the new sequence; through the local extreme value points sequence B, in the collection of data, average time interval I between adjacent heart rate data points is estimated. Then, according to the above average time interval I, the algorithm can extract a heart rate data points sequence C from the localextremum value points sequence B. Finally, according to characteristics of human heart rate and characteristics of original data, the algorithm determines the loss of heart rate data, if a loss exists, then data from the sequence A is selected to complement the sequence C, a final heart rate data points sequence D is obtained. The algorithm has a good extraction effect for the piezoelectric sensorwith multi signal fusion and large signal disturbance and the like.

The invention discloses a detection method and system based on a multi-sensor fusion drivable area, and a vehicle, and the method comprises the steps: carrying out the nearest distance solving and data association calculation of data points of each lane, carrying out the comparative analysis of an association result, taking the data point with the highest existence probability as a cut-off point of each lane, and finally outputting the cut-off point. By means of the method, the drivable area can be detected in real time, the maximum passable range of each lane can be continuously output, the defects caused by missing detection of a single target detection module are effectively overcome, the safety of the whole vehicle is improved, and an effective judgment basis is provided for planning and decision making of an unmanned driving system.

The invention provides an automatic arrangement generating method of data point subscripts in a configuration software database. The method includes: classifying data points required in a project according to a physical device, setting a tag name for each data point and assigning system codes and data types in each data point tag name according to the physical device; and completing automatic arrangement generation of each data point subscript, namely, scanning an essential attribute of the tag name corresponding to each data point one by one, positioning each data point to a system code area in a distributed control system, and comparing each data point with numbered data points in the system code area of each data point one by one, so that automatic numbering and sequencing of the data point subscripts are completed. By the method, engineering data point tag name definition accuracy is improved effectively, control system construction workload is reduced, and automation level of configuration software is increased.

The invention discloses a method and system for measuring the uniform elongation of pipeline steel. The method comprises the following steps that: a to-be-measured pipeline steel plate sample is acquired; a tensile test is carried out on the pipeline steel plate sample, so that an engineering stress-strain curve can be obtained; a data point set of a preset interval is obtained from the engineering stress-strain curve, the starting point of the preset interval is a data point corresponding to strain of 0.5%, and the terminal point of the preset interval is a data point corresponding to a strain point of which the strain value corresponding to a maximum stress value is increased by 1-2%; the data point set is fitted, so that a fitted stress-strain curve can be obtained; and a formula corresponding to the fitted stress-strain curve is analyzed, so that the uniform elongation of the to-be-measured pipeline steel is obtained. With the method and system adopted, the technical problem that the result accuracy of an existing method for measuring the uniform elongation of pipeline steel is low can be solved.

The embodiment of the invention provides a method and device for dynamically estimating price elasticity. The commodity data in the preset time span can be selected, so that the old data can be removed in the calculation process of the price elasticity, the new data can be introduced, the more effective data can be continuously updated to the calculation of the price elasticity, and the model estimation result is more effective. The method comprises the steps of determining an optimal attenuation model of a commodity; calculating an optimal attenuation period of the commodity according to theoptimal attenuation model; and according to the optimal attenuation period, weighting the commodity data in the preset time span according to the unit data points, and estimating the price elasticityof the commodity by using the weighted commodity data.