CN113776458A - High dynamic range complex curved surface measuring method, system and storage medium - Google Patents

High dynamic range complex curved surface measuring method, system and storage medium Download PDF

Info

Publication number
CN113776458A
CN113776458A CN202111016903.5A CN202111016903A CN113776458A CN 113776458 A CN113776458 A CN 113776458A CN 202111016903 A CN202111016903 A CN 202111016903A CN 113776458 A CN113776458 A CN 113776458A
Authority
CN
China
Prior art keywords
point cloud
cloud data
sensor
local area
target position
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN202111016903.5A
Other languages
Chinese (zh)
Other versions
CN113776458B (en
Inventor
张志辉
黎达
陈建良
何丽婷
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Shenzhen Research Institute HKPU
Original Assignee
Shenzhen Research Institute HKPU
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Shenzhen Research Institute HKPU filed Critical Shenzhen Research Institute HKPU
Priority to CN202111016903.5A priority Critical patent/CN113776458B/en
Publication of CN113776458A publication Critical patent/CN113776458A/en
Application granted granted Critical
Publication of CN113776458B publication Critical patent/CN113776458B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Classifications

    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical techniques
    • G01B11/24Measuring arrangements characterised by the use of optical techniques for measuring contours or curvatures
    • GPHYSICS
    • G01MEASURING; TESTING
    • G01BMEASURING LENGTH, THICKNESS OR SIMILAR LINEAR DIMENSIONS; MEASURING ANGLES; MEASURING AREAS; MEASURING IRREGULARITIES OF SURFACES OR CONTOURS
    • G01B11/00Measuring arrangements characterised by the use of optical techniques

Landscapes

  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Length Measuring Devices By Optical Means (AREA)

Abstract

The invention discloses a high dynamic range complex curved surface measuring method, a system and a storage medium, wherein the method is applied to a multi-sensor measuring instrument which comprises a plurality of position sensors and a visual sensor, and a target position sensor of each local area is determined from the sensors by dividing the surface of a measured object into a plurality of local areas; performing point cloud detection on each local area according to a target position sensor to obtain point cloud data of the surface of the measured object; and adjusting the vision sensor, and measuring the surface appearance of each local area according to the adjusted vision sensor to obtain the surface appearance information of the measured object. According to the invention, the surface of the object to be measured is processed in different areas, and different sensors in the multi-sensor measuring instrument are selected to measure according to the characteristics of each area, so that the precise measurement of the surface of the workpiece is realized, and the problem that the workpiece appearance is detected by adopting the multi-sensor measuring instrument at present and the precision range is not high is solved.

Description

High dynamic range complex curved surface measuring method, system and storage medium
Technical Field
The invention relates to the technical field of measurement, in particular to a method and a system for measuring a complex curved surface with a high dynamic range and a storage medium.
Background
The high dynamic range complex surface is an irregular non-rotational symmetric surface with multi-scale characteristics and is generally difficult to describe by a unified mathematical equation. To date, no well-established measurement and evaluation method exists. Multi-sensor measurement techniques are considered to be an effective method of measuring high dynamic range multi-scale surfaces. The principle is to integrate multiple sensors into the same measurement system. However, the existing multi-sensor scheme is generally applied to workpiece morphology detection in the rough machining process, and the precision range is not high.
Thus, there is still a need for improvement and development of the prior art.
Disclosure of Invention
The technical problem to be solved by the present invention is to provide a method, a system and a storage medium for measuring a complex curved surface with a high dynamic range, aiming at solving the problem that the prior art adopts a multi-sensor measuring instrument to detect the appearance of a workpiece and has a low precision range.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect, an embodiment of the present invention provides a high dynamic range complex curved surface measurement method, where the method is applied to a multi-sensor measurement instrument, where the multi-sensor measurement instrument includes a plurality of position sensors and a vision sensor, and the method includes:
dividing the surface of a measured object into a plurality of local areas, and determining a target position sensor corresponding to each local area from the plurality of sensors;
performing point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensors to obtain point cloud data corresponding to the surface of the object to be detected;
and adjusting the vision sensor, and respectively measuring the surface appearance of each local area according to the adjusted vision sensor to obtain the surface appearance information corresponding to the measured object.
In one embodiment, the dividing the surface of the object to be measured into a plurality of local areas includes:
processing information corresponding to the measured object is obtained, and a dividing mode is determined according to the processing information;
and dividing the surface of the measured object into a plurality of local areas according to the dividing mode.
In one embodiment, the determining the target position sensor corresponding to each of the local areas from the plurality of sensors includes:
determining a gradient difference corresponding to each local area;
and determining a target position sensor corresponding to each local area from a plurality of sensors according to the gradient difference corresponding to each local area.
In one embodiment, the determining the target position sensor corresponding to each of the local regions from the plurality of sensors according to the gradient difference corresponding to each of the local regions includes:
when the gradient difference is smaller than or equal to a preset gradient threshold value, taking a laser sensor as the target position sensor;
and when the gradient difference is larger than the preset gradient threshold value, taking a probe as the target position sensor.
In one embodiment, the performing point cloud detection on each local area in a one-to-one correspondence manner according to the target position sensor to obtain point cloud data corresponding to the surface of the object to be measured includes:
performing point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensor to obtain a plurality of local point cloud data;
converting the local point cloud data into a unified coordinate system to obtain standard point cloud data;
and adjusting the density of the plurality of standard point cloud data respectively, and splicing the plurality of adjusted standard point clouds to obtain point cloud data corresponding to the surface of the measured object.
In one embodiment, the adjusting the density of the plurality of standard point cloud data respectively comprises:
determining original densities corresponding to the standard point cloud data respectively, and dividing the standard point cloud data into dense point cloud data and sparse point cloud data according to the original densities, wherein the original densities corresponding to the dense point cloud data are larger than a preset density threshold value, and the original densities corresponding to the sparse point cloud data are smaller than or equal to the preset density threshold value;
and performing dispersion processing on the dense point cloud data, and performing interpolation processing on the sparse point cloud data.
In one embodiment, the adjusting the vision sensor and measuring the surface topography of each local area according to the adjusted vision sensor respectively includes:
and before each measurement, adjusting the vision sensor according to the target position sensor corresponding to the measured local area.
In one embodiment, the adjusting the vision sensor according to the target position sensor corresponding to the measured local area includes:
determining the working distance of a target position sensor corresponding to the measured local area;
and adjusting the optical parameters of the vision sensor according to the working distance.
In a second aspect, an embodiment of the present invention further provides a high dynamic range complex curved surface measurement system, where the system includes:
the multi-sensor measuring instrument is used for loading a plurality of position sensors and vision sensors;
the surface partition module is used for dividing the surface of the object to be measured into a plurality of local areas and determining a target position sensor corresponding to each local area from the plurality of sensors;
the point cloud detection module is used for carrying out point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensor to obtain point cloud data corresponding to the surface of the object to be detected;
and the appearance measuring module is used for adjusting the visual sensor and respectively measuring the surface appearance of each local area according to the adjusted visual sensor to obtain the surface appearance information corresponding to the measured object.
In a third aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a plurality of instructions are stored, where the instructions are adapted to be loaded and executed by a processor to implement any of the steps of the high dynamic range complex surface measurement method described above.
The invention has the beneficial effects that: the method comprises the steps of dividing the surface of a measured object into a plurality of local areas, and determining a target position sensor corresponding to each local area from the sensors; performing point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensors to obtain point cloud data corresponding to the surface of the object to be detected; and adjusting the vision sensor, and respectively measuring the surface appearance of each local area according to the adjusted vision sensor to obtain the surface appearance information corresponding to the measured object. According to the invention, the surface of the object to be measured is processed in different areas, and different sensors in the multi-sensor measuring instrument are selected to be used for measuring according to the characteristics of each area, so that the surface of the workpiece can be precisely measured, and the problems that the workpiece appearance is detected by using the multi-sensor measuring instrument in the prior art and the precision range is not high are solved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a high dynamic range complex surface measurement method provided by an embodiment of the present invention.
Fig. 2 is a schematic diagram of an internal module of a high dynamic range complex curved surface measurement system according to an embodiment of the present invention.
Fig. 3 is a schematic block diagram of a terminal according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention clearer and clearer, the present invention is further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
It should be noted that, if directional indications (such as up, down, left, right, front, and back … …) are involved in the embodiment of the present invention, the directional indications are only used to explain the relative positional relationship between the components, the movement situation, and the like in a specific posture (as shown in the drawing), and if the specific posture is changed, the directional indications are changed accordingly.
The high dynamic range complex surface is an irregular non-rotational symmetric surface with multi-scale characteristics and is generally difficult to describe by a unified mathematical equation. To date, no well-established measurement and evaluation method exists. Multi-sensor measurement techniques are considered to be an effective method of measuring high dynamic range multi-scale surfaces. The principle is to integrate multiple sensors into the same measurement system. However, the existing multi-sensor scheme is generally applied to workpiece morphology detection in the rough machining process, and the precision range is not high.
In view of the above-mentioned drawbacks of the prior art, the present invention provides a method for measuring a complex curved surface with a high dynamic range, the method being applied to a multi-sensor measuring instrument, the multi-sensor measuring instrument including a plurality of position sensors and a vision sensor, the method determining a target position sensor corresponding to each local area from the plurality of sensors by dividing the surface of an object to be measured into the plurality of local areas; performing point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensors to obtain point cloud data corresponding to the surface of the object to be detected; and adjusting the vision sensor, and respectively measuring the surface appearance of each local area according to the adjusted vision sensor to obtain the surface appearance information corresponding to the measured object. According to the invention, the surface of the object to be measured is processed in different areas, and different sensors in the multi-sensor measuring instrument are selected to be used for measuring according to the characteristics of each area, so that the surface of the workpiece can be precisely measured, and the problems that the workpiece appearance is detected by using the multi-sensor measuring instrument in the prior art and the precision range is not high are solved.
As shown in fig. 1, the method comprises the steps of:
step S100, dividing the surface of the measured object into a plurality of local areas, and determining a target position sensor corresponding to each local area from the plurality of sensors.
Specifically, when the surface of the object to be measured is a complex curved surface with a high dynamic range, it is difficult to ensure the measurement accuracy if a single measurement tool is used to measure the surface, so that an accurate measurement result cannot be obtained. Therefore, the present embodiment needs to partition the surface of the object to be measured, and divide the surface into a plurality of local areas, where each local area is used to reflect a part of the surface of the object to be measured. Then, for each local area, which position sensor of the multi-sensor measuring instrument is used for measuring the local area is determined according to the characteristics of the local area. The embodiment performs the regional measurement on the surface of the measured object, and adopts the position sensor which accords with the characteristics of each local region during the measurement, so the measurement precision can be effectively improved.
In one implementation, the dividing the surface of the measured object into a plurality of local areas specifically includes the following steps:
s101, obtaining processing information corresponding to the measured object, and determining a dividing mode according to the processing information;
and S102, dividing the surface of the measured object into a plurality of local areas according to the dividing mode.
Specifically, the processing information of the object to be measured may be a design file of the object to be measured, such as a CAD drawing or a Visio drawing. Since the processing information may reflect the contour and the shape of the object to be measured, the surface of the object to be measured may be divided into a plurality of local regions based on the processing file, and each local region may be a regular region or an irregular region. And after the division is finished, combining all the local areas to obtain the whole surface of the measured object.
In one implementation, the determining, from the plurality of sensors, a target position sensor corresponding to each of the local areas specifically includes the following steps:
step S103, determining a gradient difference corresponding to each local area;
and step S104, determining a target position sensor corresponding to each local area from a plurality of sensors according to the gradient difference corresponding to each local area.
Specifically, in order to improve the detection accuracy, in this embodiment, a suitable position sensor is selected for each local area, that is, a target position sensor corresponding to each local area is used to detect the local area. In order to determine the target position sensor corresponding to each local area, in this embodiment, the respective gradient difference of each local area needs to be determined first, and if the gradient difference is large, it indicates that the range to be measured is large, a position sensor with a large measurement range needs to be selected; if the gradient difference is small, the range needing to be measured is small, and a position sensor with a small measurement range can be selected.
In one implementation, the gradient difference for each local region may be determined based on the spatial distance between the highest and lowest points of the local region.
In one implementation, the plurality of sensors includes a laser sensor and a probe, and the step S104 specifically includes the following steps:
step S1041, when the gradient difference is smaller than or equal to a preset gradient threshold, taking a laser sensor as the target position sensor;
and S1042, when the gradient difference is larger than the preset gradient threshold, using a probe as the target position sensor.
Specifically, in order to determine the magnitude of the gradient difference, the present embodiment sets a gradient threshold value in advance. If the gradient difference of a certain local area is smaller than or equal to the gradient threshold, it indicates that the gradient difference of the local area is small, that is, the measurement range is small, so that the local area can be detected by using a laser sensor with a small measurement range (the measurement range is usually within 5 mm); if the gradient difference of the local area is greater than the gradient threshold, it indicates that the gradient difference of the local area is large, that is, the measurement range is large, and therefore a probe with a large measurement range needs to be used to detect the local area.
As shown in fig. 1, the method comprises the steps of:
and S200, carrying out point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensor to obtain point cloud data corresponding to the surface of the object to be detected.
After the target position sensor corresponding to each local area is determined, point cloud detection is performed on each local area according to the corresponding target position sensor, so that respective point cloud data of each local area is obtained, and point cloud data of the surface of the object to be measured can be obtained according to the point cloud data of all the local areas. For example, if the surface of the object to be measured is divided into the local area A, B, and the target position sensors corresponding to the local area A, B are a laser sensor and a probe, respectively, point cloud detection is performed on the local area a according to the laser sensor, point cloud detection is performed on the local area B according to the probe, and finally point cloud data of the surface of the object to be measured is obtained according to the point cloud data of the local area A, B.
In an implementation manner, the step S200 specifically includes the following steps:
step S201, carrying out point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensor to obtain a plurality of local point cloud data;
step S202, converting the local point cloud data into a unified coordinate system to obtain standard point cloud data;
and S203, respectively adjusting the densities of the plurality of standard point cloud data, and splicing the plurality of adjusted standard point clouds to obtain point cloud data corresponding to the surface of the measured object.
Specifically, for each local area, the present embodiment may perform point cloud detection on the local area according to the target position sensor corresponding to the local area, so as to obtain point cloud data corresponding to the local area, that is, local point cloud data. And for the local point cloud data of all local areas, the point cloud data of the surface of the measured object can be obtained after splicing. However, since different local point cloud data correspond to different point cloud coordinate systems, all the local point cloud data need to be converted into a uniform coordinate system and then spliced. In addition, different local areas may adopt different position sensors for point cloud detection, so that the densities of different local point cloud data may have large differences, in order to obtain uniform point cloud data on the surface of the measured object, after all the local point cloud data are converted into a uniform coordinate system, standard point cloud data corresponding to each local point cloud data are obtained, the densities of each standard point cloud data need to be adjusted, so that the density difference of each standard point cloud data reaches a preset requirement, and then the adjusted standard point cloud data are spliced, so that uniform point cloud data on the surface of the measured object are obtained.
In one implementation, the adjusting the densities of the plurality of standard point cloud data respectively specifically includes the following steps:
step S2031, determining original densities corresponding to the standard point cloud data respectively, and dividing the standard point cloud data into dense point cloud data and sparse point cloud data according to the original densities, wherein the original densities corresponding to the dense point cloud data are greater than a preset density threshold, and the original densities corresponding to the sparse point cloud data are less than or equal to the preset density threshold;
step S2032, performing dispersion processing on the dense point cloud data, and performing interpolation processing on the sparse point cloud data.
In short, when the density of each standard point cloud data is adjusted, firstly, the adjustment mode of the corresponding density is determined according to the original density of each standard point cloud data. Specifically, for each standard point cloud data, if the original density corresponding to the standard point cloud data is greater than a preset density threshold, it indicates that the density of the standard point cloud data is greater, and therefore the standard point cloud data is determined to be dense point cloud data, and for the dense point cloud data, the embodiment adopts a discrete processing adjustment mode; if the original density corresponding to the standard point cloud data is less than or equal to the preset density threshold, it indicates that the density of the standard point cloud data is small, and therefore the standard point cloud data is judged to be sparse point cloud data. For example, if a target position sensor in a certain local area is a laser sensor, and local point cloud data corresponding to the laser sensor is usually dense point cloud data, discrete processing is required; if a target position sensor in a certain local area is a probe and the corresponding local point cloud data is usually sparse point cloud data, interpolation processing is required.
In one implementation, the specific process of adjusting and stitching the density of each local point cloud data is as follows:
1. determining a point cloud type corresponding to each local point cloud data, wherein the types comprise dense point cloud data and sparse point cloud data;
2. respectively processing the dense point cloud data and the sparse point cloud data by using a Gaussian process to obtain first position data and second position data in a Z direction based on the Gaussian process, wherein the first position data corresponds to the dense point cloud data, and the second position data corresponds to the sparse point cloud data;
3. and solving the attitude of the sensor according to the acquired data of the motion sensor (the accelerometer and the gyroscope) to obtain a position sequence of the sensor in the X direction and the Y direction.
4. Obtaining dense three-dimensional point cloud data of the surface of a measured object according to the position sequences of the sensor in the X and Y directions and the first position data, and performing discrete processing on the dense three-dimensional point cloud data to obtain first point cloud data;
5. obtaining sparse three-dimensional point cloud data of the surface of the measured object according to the position sequences of the sensor in the X direction and the Y direction and the second position data, and performing interpolation processing on the sparse three-dimensional point cloud data to obtain second point cloud data;
6. and splicing the first point cloud data and the second point cloud data to obtain uniform point cloud data of the surface of the measured object.
As shown in fig. 1, the method comprises the steps of:
and S300, adjusting the vision sensor, and respectively measuring the surface topography of each local area according to the adjusted vision sensor to obtain the surface topography information corresponding to the measured object.
In short, in this embodiment, not only the point cloud data of the surface of the object to be measured needs to be obtained, but also the surface of the object to be measured needs to be measured in three dimensions to obtain the surface topography information of the object to be measured, and the surface of the object to be measured is comprehensively described through the point cloud data of the surface of the object to be measured and the surface topography information. Particularly, for the measured object with the surface of a complex curved surface with a high dynamic range, the method can be used for accurately measuring and evaluating the surface of the measured object. Specifically, in the present embodiment, the surface topography information of the object to be measured is measured by the vision sensor, and a method of measuring by regions is also adopted during measurement, that is, a method of separately measuring is adopted for each local region, and a uniform vision sensor is adopted during measurement, but before different local regions are measured, the vision sensor needs to be adjusted according to the local region to be measured, so as to achieve a better measurement effect. And after each local area is measured, obtaining the surface appearance parameters of the local area, and obtaining the surface appearance information of the object to be measured according to the surface appearance parameters of all the local areas.
In one implementation, the adjusting the visual sensor, and respectively measuring the surface topography of each local region according to the adjusted visual sensor specifically includes the following steps:
step S301, before each measurement, the vision sensor is adjusted according to the target position sensor corresponding to the measured local area.
Specifically, for each local area, before the local area is measured, the visual sensor needs to be adjusted according to the target position sensor corresponding to the local area, and then the local area is measured according to the adjusted visual sensor, so as to obtain the surface topography parameter of the local area.
In one implementation, the adjusting the vision sensor according to the target position sensor corresponding to the measured local area specifically includes the following steps:
step S3011, determining a working distance of a target position sensor corresponding to the measured local area;
and S3012, adjusting the optical parameters of the vision sensor according to the working distance.
Specifically, before the visual sensor is adjusted, in this embodiment, the working distance of the target position sensor in the measured local area needs to be determined, and then the optical parameters of the visual sensor are adjusted correspondingly based on the working distance, so as to ensure that the visual sensor can focus clearly at the working distance, and the details of the measured local area are clearly visible under a proper illumination condition, that is, clear imaging of the visual sensor needs to be ensured. In the measuring range covered by the optical system of the vision sensor, the local area can be measured in three dimensions, so that the surface topography parameters of the local area are digitally output.
In one implementation, the vision sensor may employ an automatic parallax sensor to achieve automatic parallax three-dimensional measurement of a local region to be measured. An automatic parallax sensor is one of vision sensors, which work in a visible light band, and the measurement process does not need scanning.
The invention has the advantages that:
1. the conventional multi-sensor scheme is generally applied to workpiece appearance detection in the rough machining process, and the precision range is not high. The technical scheme mainly aims at measuring the surface of the ultra-precise workpiece after finish machining. For example, the comparison scheme adopts structured light and a CMM probe to measure a workpiece, the highest precision can reach a micron level, and the scheme adopts a high-precision laser position sensor, and the precision can reach a submicron level.
2. Complex surfaces with features of different dimensions are measured in a single measurement process.
3. Compared with other measuring methods/devices/instruments, the device has more reliable performance, lower cost and easier maintenance.
Based on the above embodiment, the present invention further provides a high dynamic range complex curved surface measurement system, as shown in fig. 2, the system includes:
the multi-sensor measuring instrument 01 is used for loading a plurality of position sensors and vision sensors;
the surface partition module 02 is used for dividing the surface of the object to be measured into a plurality of local areas and determining a target position sensor corresponding to each local area from the plurality of sensors;
the point cloud detection module 03 is configured to perform point cloud detection on each local area in a one-to-one correspondence manner according to the target position sensor, so as to obtain point cloud data corresponding to the surface of the object to be detected;
and the appearance measuring module 04 is used for adjusting the visual sensors, and respectively measuring the surface appearance of each local area according to the adjusted visual sensors to obtain the surface appearance information corresponding to the measured object.
According to the embodiment, the plurality of position sensors and the visual sensor are mounted on the same multi-sensor measuring instrument, and different position sensors are selected for measurement according to different local areas of the surface of the measured object, so that not only can secondary clamping errors caused by taking out a workpiece be avoided, but also the measurement precision of each local area can be guaranteed. It should be noted, however, that it is necessary to ensure that the movement does not interfere within the range permitted by the working space of the apparatus. The embodiment can also adjust the distance between the sensor and the workpiece at any time.
Based on the above embodiments, the present invention further provides a terminal, and a schematic block diagram thereof may be as shown in fig. 3. The terminal comprises a processor, a memory, a network interface and a display screen which are connected through a system bus. Wherein the processor of the terminal is configured to provide computing and control capabilities. The memory of the terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the terminal is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to implement a high dynamic range complex surface measurement method. The display screen of the terminal can be a liquid crystal display screen or an electronic ink display screen.
It will be understood by those skilled in the art that the block diagram shown in fig. 3 is a block diagram of only a portion of the structure associated with the inventive arrangements and is not intended to limit the terminals to which the inventive arrangements may be applied, and that a particular terminal may include more or less components than those shown, or may have some components combined, or may have a different arrangement of components.
In one implementation, one or more programs are stored in a memory of the terminal and configured to be executed by one or more processors include instructions for performing a high dynamic range complex surface measurement method.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
In summary, the present invention discloses a method, a system and a storage medium for measuring a complex curved surface with a high dynamic range, wherein the method is applied to a multi-sensor measuring instrument, the multi-sensor measuring instrument comprises a plurality of position sensors and a plurality of visual sensors, the method comprises dividing the surface of a measured object into a plurality of local areas, and determining a target position sensor corresponding to each local area from the plurality of sensors; performing point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensors to obtain point cloud data corresponding to the surface of the object to be detected; and adjusting the vision sensor, and respectively measuring the surface appearance of each local area according to the adjusted vision sensor to obtain the surface appearance information corresponding to the measured object. According to the invention, the surface of the object to be measured is processed in different areas, and different sensors in the multi-sensor measuring instrument are selected to be used for measuring according to the characteristics of each area, so that the surface of the workpiece can be precisely measured, and the problems that the workpiece appearance is detected by using the multi-sensor measuring instrument in the prior art and the precision range is not high are solved.
It is to be understood that the invention is not limited to the examples described above, but that modifications and variations may be effected thereto by those of ordinary skill in the art in light of the foregoing description, and that all such modifications and variations are intended to be within the scope of the invention as defined by the appended claims.

Claims (10)

1. A high dynamic range complex surface measuring method is applied to a multi-sensor measuring instrument, and is characterized in that the multi-sensor measuring instrument comprises a plurality of position sensors and vision sensors, and the method comprises the following steps:
dividing the surface of a measured object into a plurality of local areas, and determining a target position sensor corresponding to each local area from the plurality of sensors;
performing point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensors to obtain point cloud data corresponding to the surface of the object to be detected;
and adjusting the vision sensor, and respectively measuring the surface appearance of each local area according to the adjusted vision sensor to obtain the surface appearance information corresponding to the measured object.
2. The method for measuring the complex curved surface with the high dynamic range according to claim 1, wherein the dividing the surface of the measured object into a plurality of local areas comprises:
processing information corresponding to the measured object is obtained, and a dividing mode is determined according to the processing information;
and dividing the surface of the measured object into a plurality of local areas according to the dividing mode.
3. The method according to claim 1, wherein the determining the target position sensor corresponding to each of the local areas from the plurality of sensors comprises:
determining a gradient difference corresponding to each local area;
and determining a target position sensor corresponding to each local area from a plurality of sensors according to the gradient difference corresponding to each local area.
4. The method as claimed in claim 3, wherein the plurality of sensors includes a laser sensor and a probe, and the determining the target position sensor corresponding to each of the local regions from the plurality of sensors according to the gradient difference corresponding to each of the local regions comprises:
when the gradient difference is smaller than or equal to a preset gradient threshold value, taking a laser sensor as the target position sensor;
and when the gradient difference is larger than the preset gradient threshold value, taking a probe as the target position sensor.
5. The method for measuring the complex curved surface with the high dynamic range according to claim 1, wherein the performing point cloud detection on each local area in a one-to-one correspondence manner according to the target position sensor to obtain point cloud data corresponding to the surface of the object to be measured comprises:
performing point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensor to obtain a plurality of local point cloud data;
converting the local point cloud data into a unified coordinate system to obtain standard point cloud data;
and adjusting the density of the plurality of standard point cloud data respectively, and splicing the plurality of adjusted standard point clouds to obtain point cloud data corresponding to the surface of the measured object.
6. The method for measuring complex curved surfaces with high dynamic range according to claim 5, wherein the adjusting the density of the plurality of standard point cloud data respectively comprises:
determining original densities corresponding to the standard point cloud data respectively, and dividing the standard point cloud data into dense point cloud data and sparse point cloud data according to the original densities, wherein the original densities corresponding to the dense point cloud data are larger than a preset density threshold value, and the original densities corresponding to the sparse point cloud data are smaller than or equal to the preset density threshold value;
and performing dispersion processing on the dense point cloud data, and performing interpolation processing on the sparse point cloud data.
7. The method for measuring a complex curved surface with a high dynamic range according to claim 1, wherein the adjusting the vision sensor and the measuring the surface topography of each local area according to the adjusted vision sensor respectively comprises:
and before each measurement, adjusting the vision sensor according to the target position sensor corresponding to the measured local area.
8. The method according to claim 7, wherein the adjusting the vision sensor according to the target position sensor corresponding to the measured local area comprises:
determining the working distance of a target position sensor corresponding to the measured local area;
and adjusting the optical parameters of the vision sensor according to the working distance.
9. A high dynamic range complex surface measurement system, the system comprising:
the multi-sensor measuring instrument is used for loading a plurality of position sensors and vision sensors;
the surface partition module is used for dividing the surface of the object to be measured into a plurality of local areas and determining a target position sensor corresponding to each local area from the plurality of sensors;
the point cloud detection module is used for carrying out point cloud detection on each local area in a one-to-one correspondence mode according to the target position sensor to obtain point cloud data corresponding to the surface of the object to be detected;
and the appearance measuring module is used for adjusting the visual sensor and respectively measuring the surface appearance of each local area according to the adjusted visual sensor to obtain the surface appearance information corresponding to the measured object.
10. A computer readable storage medium having stored thereon a plurality of instructions adapted to be loaded and executed by a processor to perform the steps of the high dynamic range complex surface measurement method as recited in any one of claims 1-8.
CN202111016903.5A 2021-08-31 2021-08-31 High dynamic range complex curved surface measurement method, system and storage medium Active CN113776458B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN202111016903.5A CN113776458B (en) 2021-08-31 2021-08-31 High dynamic range complex curved surface measurement method, system and storage medium

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202111016903.5A CN113776458B (en) 2021-08-31 2021-08-31 High dynamic range complex curved surface measurement method, system and storage medium

Publications (2)

Publication Number Publication Date
CN113776458A true CN113776458A (en) 2021-12-10
CN113776458B CN113776458B (en) 2024-03-19

Family

ID=78840530

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202111016903.5A Active CN113776458B (en) 2021-08-31 2021-08-31 High dynamic range complex curved surface measurement method, system and storage medium

Country Status (1)

Country Link
CN (1) CN113776458B (en)

Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101000499A (en) * 2006-12-18 2007-07-18 浙江大学 Contour machining method and system based on multi-sensor integral measuring
CN102305601A (en) * 2011-05-18 2012-01-04 天津大学 High-precision non-contact measurement method and device for three-dimensional profile of optical freeform curved surface
CN103453849A (en) * 2013-07-18 2013-12-18 黑龙江科技大学 Method and device for three-dimensionally measuring complex curved surface parts through multi-optical-sensor cooperation
CN106969721A (en) * 2017-02-20 2017-07-21 深圳大学 A kind of method for three-dimensional measurement and its measurement apparatus
DE102018217285A1 (en) * 2017-10-11 2019-04-11 Carl Zeiss Industrielle Messtechnik Gmbh Touch probe for optical and tactile measurement of at least one DUT
CN110415342A (en) * 2019-08-02 2019-11-05 深圳市唯特视科技有限公司 A kind of three-dimensional point cloud reconstructing device and method based on more merge sensors
CN210741384U (en) * 2019-12-06 2020-06-12 青岛海之晨工业装备有限公司 Robot vision measurement system with two-dimensional sensor and three-dimensional sensor fused
CN111623722A (en) * 2020-07-29 2020-09-04 湖南致力工程科技有限公司 Multi-sensor-based slope deformation three-dimensional monitoring system and method
CN112040625A (en) * 2020-07-21 2020-12-04 西安电子科技大学 High-precision high-space-time resolution three-dimensional determination method, system, medium and application
CN112223302A (en) * 2020-12-17 2021-01-15 国网瑞嘉(天津)智能机器人有限公司 Rapid calibration method and device of live working robot based on multiple sensors

Patent Citations (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101000499A (en) * 2006-12-18 2007-07-18 浙江大学 Contour machining method and system based on multi-sensor integral measuring
CN102305601A (en) * 2011-05-18 2012-01-04 天津大学 High-precision non-contact measurement method and device for three-dimensional profile of optical freeform curved surface
CN103453849A (en) * 2013-07-18 2013-12-18 黑龙江科技大学 Method and device for three-dimensionally measuring complex curved surface parts through multi-optical-sensor cooperation
CN106969721A (en) * 2017-02-20 2017-07-21 深圳大学 A kind of method for three-dimensional measurement and its measurement apparatus
DE102018217285A1 (en) * 2017-10-11 2019-04-11 Carl Zeiss Industrielle Messtechnik Gmbh Touch probe for optical and tactile measurement of at least one DUT
CN110415342A (en) * 2019-08-02 2019-11-05 深圳市唯特视科技有限公司 A kind of three-dimensional point cloud reconstructing device and method based on more merge sensors
CN210741384U (en) * 2019-12-06 2020-06-12 青岛海之晨工业装备有限公司 Robot vision measurement system with two-dimensional sensor and three-dimensional sensor fused
CN112040625A (en) * 2020-07-21 2020-12-04 西安电子科技大学 High-precision high-space-time resolution three-dimensional determination method, system, medium and application
CN111623722A (en) * 2020-07-29 2020-09-04 湖南致力工程科技有限公司 Multi-sensor-based slope deformation three-dimensional monitoring system and method
CN112223302A (en) * 2020-12-17 2021-01-15 国网瑞嘉(天津)智能机器人有限公司 Rapid calibration method and device of live working robot based on multiple sensors

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
ZHANG, ZH: "Improved dynamic stability of superomniphobic surfaces and droplet transport on slippery surfaces by dual-scale re-entrant structures", 《CHEMICAL ENGINEERING JOURNAL》 *
张志辉: "超精密加工的三维表面形貌预测", 《中国机械工程》 *

Also Published As

Publication number Publication date
CN113776458B (en) 2024-03-19

Similar Documents

Publication Publication Date Title
CN112082491A (en) Height detection method based on point cloud
CN110842901A (en) Robot hand-eye calibration method and device based on novel three-dimensional calibration block
CN109990761B (en) Levelness measuring system and levelness measuring method
CN113304971B (en) 3D dynamic guiding dispensing compensation method, device and equipment and storage medium thereof
WO2020132924A1 (en) Method and device for calibrating external parameters of robot sensor, robot and storage medium
US20090289953A1 (en) System and method for adjusting view of a measuring report of an object
CN108286946B (en) Method and system for sensor position calibration and data splicing
CN113776458B (en) High dynamic range complex curved surface measurement method, system and storage medium
CN112556625B (en) Method, device and equipment for measuring angle of hub mounting surface and storage medium
KR101373139B1 (en) Method to measure squareness using laser interferometer
CN116124081B (en) Non-contact workpiece detection method and device, electronic equipment and medium
CN115393381A (en) Straightness detection method and device, computer equipment and storage medium
US11662194B2 (en) Measurement point determination for coordinate measuring machine measurement paths
CN114998864A (en) Obstacle detection method, device, equipment and storage medium
CN112632691B (en) Virtual product assessment by adjusting the orientation of virtual component models
CN114705266A (en) Oil tank oil quantity detection method and device, oil tank, T-box and vehicle
CN112630751B (en) Laser radar calibration method
CN112729341A (en) Visual ranging precision testing method and system
CN115511718A (en) PCB image correction method and device, terminal equipment and storage medium
CN113256734A (en) Vehicle-mounted sensing sensor calibration method and system and electronic equipment
CN113494927A (en) Vehicle multi-sensor calibration method and device and vehicle
CN115457139A (en) Local positioning method, device, equipment and storage medium of optical positioning system
Haig et al. Lens inclination due to instable fixings detected and verified with VDI/VDE 2634 Part 1
CN115106837B (en) Attitude determination method and system based on intelligent pressing plate
Maresca et al. Evaluation of traceability in continuous 2D measurements employing machine vision systems

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant