64results about How to "Improve the calibration effect" patented technology

The utility model relates to a method for calibrating an optical strapdown inertial navigation system based on a two-axis turntable. The method comprises the following six steps: firstly, selecting an error model; secondly, mounting three axles of the optical strapdown inertial navigation system to the two-axis turntable according to the east-north-up direction, and then collecting data after the whole system is powered on and preheated; thirdly, collecting data and storing the data to a calibration matrix according to the twelve positions of east-north-up, west-south-up, north-east-down, south-west-down, up-south-east, up-north-west, down-north-east, down-south-west, south-up-west, north-up-east, south-down-east and north-down-west; fourthly, rotating around the z-axis, the y-axis or the x-axis for 3 minutes at omega of plus or minus 2 degrees per seconds, plus or minus 10 degrees per seconds, plus or minus 30 degrees per seconds, plus or minus 60 degrees per seconds or plus or minus 100 degrees per seconds according to the two positions of east-north-up and north-west-up, and equalizing the output data and storing the average value in the calibration matrix; fifthly, collecting data for 15 minutes at each position of the four positions of east-north-up, west-north-up, north-east-down and south-west-down, and then equalizing the output data and storing the average value in the calibration matrix; and sixthly, using the least square method for calculating the calibration parameters of an accelerometer, and using an analysis method for calculating the calibration parameters of a gyroscope.

The invention discloses a high-precision multi-feature plane template. The high-precision multi-feature plane template includes a ChArUco black and white chequer template, wherein the chequer white area combination has an ArUco QR-code; the middle area of the ChArUco black and white chequer template is filled with random feature points to form a Random feature point template; and the edge area ofthe ChArUco black and white chequer template is provided with a plurality of segments with preset specific positions. The invention also provides a distortion optimization and calibration method of the high-precision multi-feature plane template. The high-precision multi-feature plane template and the distortion optimization and calibration method thereof have the advantages of solving the problemthat different focal length lens takes more images, consumes long operation time and is not accurate in edge distortion during the high precision calibration process; and conveniently and effectivelysolving the difficulty of calibration of a zoom lens by the calibration template, during the calibration process, having low requirement for the size of space, and not influencing the calibration function even when performing observation of part of the template; and the added linear segments around the calibration template, and being able to solve the problem of solving edge distortion without taking a large amount of images.

The invention relates to a robot calibration method based on a measuring head. The robot calibration method comprises the following steps: establishing a robot kinematic model; arranging the measuring head on an end of a flange disc of the robot; carrying out tool parameter calibration of the measuring head; disposing a calibration block in the robot working space; carrying out the demonstration and the measurement of the calibration block; carrying out the kinematic parameter calibration of the robot; and identifying the calibration experiment results. The measuring head is used for the technology field of the robot calibration, and the robot calibration method is simple, practical, and effective, and is suitable for any serial connection robots, and therefore the universality is strong, and at the same time, the absolute positioning precision of the robots can be improved.

The invention relates to a calibration device and a radar and camera combined calibration method and system, and the method comprises the steps: S1, providing a calibration device which comprises a camera calibration plate and a radar calibration plate, and enabling the calibration device to be located at a calibration position; S2, collecting pictures of the calibration device in different statesthrough a camera; meanwhile, through the radar detection calibration device, locating the camera calibration plate and the radar calibration plate in the same plane and jointly rotate by different angles around the first rotating shaft and rotate by different angles around the second rotating shaft; and S3, calculating calibration data according to the radar detection data corresponding to the time when the camera collects the picture, and outputting the calibration data, with the calibration data comprising a yaw angle, a pitch angle and a translation vector between the radar and the camera.According to the invention, the deviation of the installation angle is considered, so that the unification of the information obtained by the radar and the camera can be ensured and more accurate obstacle identification and tracking can be realized.

The invention, which belongs to the computer vision field, discloses a face characteristic point automation calibration method based on a conditional appearance model. The method comprises the following steps: assuming that front face calibration is known; firstly, establishing that a discrete characteristic point of the front face corresponds to the discrete characteristic point of a side face; through a mapping relation between discrete characteristic points and a structural calibration point, acquiring an initialization calibration result of the side face, wherein the mapping relation is acquired by a regression algorithm; then, establishing the conditional model between the side face calibration point and the front face calibration point, continuously carrying out iteration optimization on a model parameter according to a reverse synthesis algorithm so as to obtain a final calibration result. According to the invention, the space mapping of the discrete characteristic points and the structural calibration point is established through kernel ridge regression (KRR) so as to obtain the initial calibration of the face characteristic. A subsequent iteration frequency is reduced and calibration precision is improved. The conditional appearance model and the reverse synthesis iteration algorithm are designed. Appearance deformation searching can be avoided and a searching efficiency can be improved. Compared to a traditional active appearance model (AAM), by using the calibration method of the invention, the calibration result is more accurate.

The invention provides an integrated calibration method for a gyro and a magnetic transducer. The method is characterized by comprising the following steps: step 1, obtaining an associated measuring model of the magnetic transducer and the gyro, wherein the measuring model includes a calibration parameter; and step 2, adopting constraint non-linear least square estimation based on the calibration parameter to obtain a determined value of the calibration parameter. Compared with a method in the prior art, the integrated calibration method has the following beneficial effects: 1, both a misalignment angle between the magnetic transducer and the gyro and a gyro zero offset are calibrated; 2, in a calibration process, the more stable the magnetic field is, the better the calibration effect is, and the calibration effect is not interfered by any accelerated speed, so that the gyro and the magnetic transducer do not need to be kept in a stationary state; and 3, the method can be used for attitude rectification of the magnetic transducer and an inertia measuring unit (including the gyro and an accelerometer).

The invention relates to an accuracy calibration system for weak target magnitude simulation by an ultraviolet star simulator in a space simulation test. The system comprises a star simulator optical system, a stray light eliminating light shield, a detection objective, an optical filter, and a photon counter, with the star simulator optical system, the stray light eliminating light shield, the detection objective, and the optical filter arranged on one optical path in order and the photon counter on an emergent optical path passing through the optical filter. The invention provides a weak target ultraviolet magnitude calibration system characterized by effective accuracy calibration to magnitude simulation of a star simulator in a laboratory, calibration ability for magnitude grade simulation in a large dynamic range, and high magnitude calibration accuracy.

The invention discloses an automatic calibration method for discrete element linear stiffness parameters during geotechnical material simulation. According to the method, an analytic formula is used as an initial estimated value of a linear elastic contact parameter, a particle rigidity parameter is used as an independent variable, a numerical simulation actual result is used as a dependent variable, and the contact parameter in a discrete element model is automatically trained. According to the invention, the target parameters can be obtained through automatic training, and the time requiredby a traditional manual checking method is greatly reduced; the macroscopic deformation analytical solution based on the isotropic discrete sample is used as an initial value of parameter training, sothat the problems of local optimal traps, overlong training time and the like in the parameter training process are effectively avoided; elastic parameters are calibrated through response of the sample under the small strain condition, and the parameter calibration efficiency is high. The implementation process is simple, and the method is suitable for rapidly calibrating the mesoscopic deformation parameters of various discrete materials such as sandy soil and rockfill materials and bonded discrete materials such as sedimentary rock and ceramics during simulation research by adopting discrete elements.

The embodiment of the invention discloses a camera calibration method and device, an intelligent vehicle and a storage medium. Time synchronization processing can be carried out on an obtained initialcamera pose transformation sequence and an initial radar pose transformation sequence to obtain a camera pose transformation sequence and a radar pose transformation sequence, and then a first rotation external parameter is determined according to a first association relation; a second rotation external parameter, a scale factor and a translation parameter are determined according to the radar pose transformation sequence, the camera pose transformation sequence, the scale factor of the target camera, a second association relationship and the first rotation external parameter, and the camerapose transformation sequence is corrected according to the scale factor to obtain a corrected camera pose transformation sequence; and according to the radar pose transformation sequence, the corrected camera pose transformation sequence, the first association relationship and the second association relationship, a target rotation parameter and a target translation parameter are obtained. Therefore, camera calibration can be realized without using a calibration plate during camera calibration, and the calibration accuracy is improved.

The invention discloses an automatic calibration method of a mobile infrared temperature measurement system, and the mobile infrared temperature measurement system comprises a fixed-focus visible light camera, a fixed-focus infrared camera, a rotatable pan-tilt, a laser radar, and a mobile device, wherein the visible light camera and the infrared camera are installed on the mobile device with thelaser radar through the rotatable pan-tilt; and the visible light camera and the infrared camera have the same rotation effect and a part of overlapped view field relative to the rotatable pan-tilt. The automatic calibration method comprises the following steps: calibrating the relative positions of the visible light camera and the infrared camera, and calibrating the relative positions of the laser radar and the visible light camera of the rotatable pan-tilt at different rotation angles, to obtain the real-time relative positions of the laser radar and the infrared camera. According to the method, the external parameter calibration of the visible light camera and the infrared camera can be effectively completed, so that the calibration of the two cameras does not interfere with each other, and the calibration efficiency is obviously improved.

The invention relates to a collimator based camera calibration method. An angle measuring instrument measures angle directional information of an infinite distance target generated by a collimator, and an internal parameter of the camera is calculated according to a collinear equation calibration method by combining an image coordinate of an image point corresponding to the infinite distance target. The camera whose internal parameter is calibrated is fixed in a working position, control points are used to carry out absolute orientation, and an external parameter of the camera can be solved. The method can be widely applied to the visual field, can be applied to calibration of traditional small and medium-sized visual fields and well as camera calibration in large-visual-field outfield condition, and has significance in theoretical researches and wide application prospects.

The invention discloses a multi-camera external parameter automatic calibration method based on human skeleton extraction, and belongs to the technical field of computer vision. The method comprises the following steps: processing each frame of image, and extracting the position of a human skeleton joint point in the image by using a deep learning method; selecting any one camera coordinate system as a world coordinate system, and calculating external parameters of other cameras through the essential matrix; calculating a translation vector scale by using the human body size information. According to the method, human body skeleton joint points are used as feature points, point cloud formed by motion trails of the human body skeleton joint points is used as a virtual calibration object, then essential matrixes between cameras are calculated, relative poses between the cameras are obtained through essential matrix decomposition, and real-time online accurate external parameter calibration of a multi-camera system is completed.

The invention discloses a pressure sensor calibration device, and relates to the technical field of the pressure sensor. The pressure sensor calibration device comprises a base and a hydraulic outputdevice; a motor and a lead screw are arranged in the base, and a transmission gear is sleeved at the outside of one end of the lead screw; the hydraulic output device comprises a hydraulic cylinder, apiston and hydraulic oil; the piston and the hydraulic oil are located in the hydraulic cylinder, a thread groove is formed at the other end of the piston, one side of the top end of the hydraulic cylinder is fixedly connected with a mainstream pipe, one end of the mainstream pipe is fixedly connected with a T-joint, one end of the T-joint is fixedly connected with a first shunt. Through the pressure sensor calibration device disclosed by the invention, the pressure sensor is calibrated by using the hydraulic principle by arranging the hydraulic output device, the precision of the calibrationis improved; by arranging the measurement device, one the one hand, the phenomenon that the pressure sensor is damaged due to excessive pressure is avoided, on the other hand, the calibration operation is performed on the pressure sensor.

The invention relates to a circular array calibration board feature point extraction method, which belongs to the technical field of camera calibration. In view of a camera calibration way in which model parameters of the camera are solved by image coordinates and world coordinates of a known feature point according to the camera model, the analyzed feature point extraction precision directly decides a calibration result, a new ellipse center feature extraction algorithm is provided, the method has relatively high precision, the problem of matching between image coordinates and space point coordinates of a feature point obtained by the existing feature extraction algorithm can be well solved, and fully-automatic extraction of the ellipse center is realized.

The invention provides a calibration method and device for a CT image as well as a CT system. The method comprises steps as follows: arranging fixed type calibration pieces outside a channel area of a CT scanning device and inside a largest reconstruction area and storing theoretical values of the fixed type calibration pieces; collecting projection data of the fixed type calibration pieces and obtaining actual reconstruction images of the fixed type calibration pieces; and comparing the actual reconstruction images with the corresponding stored theoretical values and establishing a mapping function that calibrates the actual reconstruction images into theoretical values. According to the calibration method and device for the CT image as well as the CT system, the calibration quality can be effectively improved, the image calibration effect is enhanced, the reliability of the CT scanning device is improved, the maintenance cost is saved, and a high actual application value is obtained.

The invention discloses a sub-pixel-level distortion correction method and apparatus. According to the method and the apparatus, display points on a display (4) are controlled to be turned on from a known point by adopting an industrial personal computer, and a camera (1) is controlled to perform image extraction and processing. By adopting the method and the apparatus, the distortion calibration precision can be effectively improved, the sub-pixel-level distortion correction effect can be achieved, the edge calibration effect can be greatly improved, and a visual product can be applied to a more accurate occasion. By applying the method and the apparatus to a projection device, the projection distortion can be remarkably reduced, the projection effect can be improved, and the optical cost can be reduced. An algorithm is simple, and the image processing speed is not influenced, so that the method and the apparatus are very suitable for the fields of high-precision machine vision, camera imaging distortion correction, projection distortion correction and the like.

The invention discloses a biaxial tension test calibration debugging method based on a crossed test piece. The biaxial tension test calibration debugging method comprises the following steps: pastinga strain rosette to a specific position of the crossed test piece, and carrying out calculation by virtue of the strain rosette to obtain a shearing strain at the pasted position; regulating an actuator or other connecting members so that the value change rule and the value of the shearing strain are basically consistent within an elastic range, and in such a case, considering that the test piecehas a relatively small additional load; and carrying out loading after clearing data according to a general mechanical test on the basis to finish calibration. The debugging method is simple in adopted equipment, easy to implement, capable of achieving a relatively good calibration effect and suitable for calibration debugging before dynamic tests such as a quasi-static test or a fatigue test.

The invention relates to the field of metallic material analysis sample preparation technologies and particularly discloses a method of preparing a pure titanium EBSD sample under room temperature. According to the method, a to-be-tested surface of a pure titanium sample is subjected to polishing, electrolytic polishing and titanium corrosion treatment sequentially, and the pure titanium EBSD sample is obtained. The method of preparing the pure titanium EBSD sample is easy to operate and low in preparation cost and has a low requirement on environmental conditions, and the obtained pure titanium EBSD sample has a high calibration rate.

The invention provides an error parameter calibration method for a nine-axis sensor. Based on the assumption that the position is not changed and the environment magnetic field is not changed at a single position in the calibration process, an inertial navigation mechanical arrangement equation and a magnetometer observation model are taken as system state equations, a measurement equation is constructed by using pseudo-position observation and magnetic field projection component invariant constraints at the single position, and sensor calibration parameters are obtained through Kalman filtering. Compared with an existing calibration technology, the method is simple in algorithm and high in efficiency. Not only can zero offset and scale factor errors of a gyroscope and an accelerometer beobtained, but also soft and hard magnetic effect calibration of the magnetometer is realized, and a coordinate system of the magnetometer is aligned with a coordinate system of an inertial sensor. According to the invention, an accurate sensor calibration result can be obtained through a simple calibration action under the condition of no professional equipment tool and no dependence on external information.

The invention provides a magnetometer calibration method based on a known attitude angle. Based on the assumption that the total intensity of the magnetic field at a certain fixed position is unchanged and the projection component of the magnetic field intensity in the same coordinate system is unchanged, the observed value of a magnetometer is projected to a local coordinate system by using a known attitude angle according to a magnetometer measurement model, and the calibration parameters of the magnetometer are obtained through least square iteration. Compared with an existing calibration technology, the method is simple in algorithm and high in efficiency. Meanwhile, soft and hard magnetic effect calibration of the magnetometer is realized, and a coordinate system of the magnetometer is aligned with a coordinate system of an inertial sensor, so that information of the magnetometer and the inertial sensor is placed in a common frame, and the method can play an important role in multi-source sensor fusion positioning and sensor arrays.

The invention discloses a novel impeller electromagnetic flowmeter. The novel impeller electromagnetic flowmeter comprises a pipeline, an impeller, a coil, a supporting frame, a magnet assembly and anelectrical measuring instrument; the supporting frame comprises a shell and at least one support part; the support parts are connected to the outer wall of the shell; the supporting frame is locatedin the pipeline, and the support parts of the supporting frame are connected with the inner wall of the pipeline; the impeller comprises an impeller body and a plurality of blades; the blades are evenly distributed on the outer wall of the impeller body; the opening end of the impeller body is rotatably connected into the opening end of the shell; the coil is installed in the impeller body, a wireof the coil penetrates into the shell; the magnet assembly comprises a magnet I and a magnet II; the magnet I and the magnet II are symmetrically arranged on the outer wall of the pipeline; and the coil is located between the magnet I and the magnet II; the electric measuring instrument is electrically connected with the coil, and the electric measuring instrument measures the induced electromotive force frequency of the coil. The ovel impeller electromagnetic flowmeter is compact in structure, low in installation and debugging and maintenance costs, does not require too detailed operation compared with other flowmeters and is excellent in calibration performance.

The invention discloses a multi-camera system calibration method based on pedestrian head recognition, and belongs to the technical field of computer vision. The method comprises the following steps:processing each frame of image, and extracting an ellipse of a head portrait in the image by using a CNN method; calculating the three-dimensional position of the human head in each frame under a camera coordinate system according to the position and the size of the ellipse; selecting any camera coordinate system as a world coordinate system, and calculating external parameters of other cameras; and optimizing the obtained camera external parameters, and performing alignment conversion on the camera world coordinate system and the selected world coordinate system. According to the method, thehuman head is used as a feature point, the point cloud formed by the motion trail of the human head is used as a virtual calibration object, the method for calculating the three-dimensional coordinates of the head under the monocular single-frame image is provided, and the multi-camera external parameter calibration problem is converted into the three-dimensional point cloud alignment problem. Therefore, real-time online accurate external parameter calibration of the multi-camera system is completed by calculating the relative pose between the three-dimensional point clouds.

The invention provides a moisture content calibration method for a resistance-capacitance humidity sensor, and belongs to the technical field of gas measurement. The calibration method comprises the following steps: drawing a moisture content fitting curve in a coordinate system taking the moisture content measurement value of gas as an X axis and the theoretical moisture content of gas as a Y axis based on the moisture content measurement value and the theoretical moisture content of sample gas; selecting a first calibration point and a second calibration point on the moisture content fitting curve, and generating a first calibration model, a second calibration model and a third calibration model based on the coordinates of the first calibration point and the coordinates of the second calibration point; introducing gas to be measured into the resistance-capacitance humidity sensor, and calibrating the moisture content measurement value of the gas to be measured by adopting the first calibration model, the second calibration model or the third calibration model. By means of the method, the problem that in the prior art, a single-point calibration method is poor in calibration effect on the moisture content measurement value of the to-be-measured gas is effectively solved.