CN102645161B - Motor rotor position detection method based on image phase correlation algorithm - Google Patents
Motor rotor position detection method based on image phase correlation algorithm Download PDFInfo
- Publication number
- CN102645161B CN102645161B CN201210090920.8A CN201210090920A CN102645161B CN 102645161 B CN102645161 B CN 102645161B CN 201210090920 A CN201210090920 A CN 201210090920A CN 102645161 B CN102645161 B CN 102645161B
- Authority
- CN
- China
- Prior art keywords
- rotor
- image
- motor rotor
- end view
- shooting
- 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.)
- Active
Links
Landscapes
- Length Measuring Devices By Optical Means (AREA)
Abstract
The invention discloses a motor rotor position detection method based on an image phase correlation algorithm. An area array CCD (charge coupled device) camera is erected opposite to a low shaft of a reduction box used for reducing rotating speed of a motor rotor or a rotating motor rotor; when a motor rotates, continuous shooting is carried out by virtue of the area array CCD and two adjacent motor rotor end face images at different moments are obtained, the rotating angle of the motor rotor within shooting time is calculated according to the information of the two shot end face images, and the position of the motor rotor is further measured. The motor rotor position detection method disclosed by the invention is stable in performance, high in accuracy and low in cost, adopts a non-contact measurement mode, is not influenced by severe working environment and has wide application range.
Description
Technical field
The present invention relates to a kind of motor rotor position detection method, particularly relate to a kind of motor rotor position detection method based on image phase correlation algorithm.
Background technology
Motor rotor position detects and draws by measuring the rotor anglec of rotation, and the measuring system of the current rotor anglec of rotation mainly contains following several: Hall element, photoelectric encoder.The response speed of these devices and measuring accuracy are not very high, and are the measurements of contact, are not suitable for operating in severe working environment.Therefore need the inconvenience overcoming above-mentioned measuring element, now propose new measuring method, namely based on the outer corner measurement of the rotor of image phase correlation algorithm, the method can realize that measuring accuracy is high, real-time good, can carry out non-cpntact measurement.Reason is: 1, the method utilizes image information to calculate, and computational accuracy can reach Pixel-level, thus can realize precision measurement.2, DSP642 and fpga chip is adopted can to process image quickly and accurately, calculate, for the real-time measured provides guarantee.3, reached the object of precision measurement by shooting motor end face image, obvious which is non-contact measurement.These advantages make this detection method be beneficial to the precise hard_drawn tuhes of motor, are beneficial to and work in the presence of a harsh environment.
Summary of the invention
The object of this invention is to provide a kind of motor rotor position detection method based on image phase correlation algorithm, to solve pick-up unit of the prior art not high to motor rotor position inspection time difference method, install and use inconvenience, and operate unsafe problem.
For achieving the above object, the technical solution used in the present invention is:
Based on a motor rotor position detection method for image phase correlation algorithm, comprise motor and area array CCD camera, it is characterized in that: detect and comprise following key step:
1., the end face of the alignment lens rotor of described area array CCD camera;
2., described motor is in rotary state;
3., described area array CCD camera takes its end view drawing picture continuously to the rotor rotated;
4., according to the information of captured adjacent two width end view drawing pictures calculate the angle that rotor turns over, then combine the position determining rotor interval time of these adjacent two width end view drawing pictures of shooting.
Described a kind of motor rotor position detection method based on image phase correlation algorithm, it is characterized in that: choose informative image adhesion on motor end face, end view drawing picture is taken continuously with high-speed camera head, and polar coordinate transform is carried out to image, recycling phase place related algorithm finds out the cross-power spectrum peak value of the adjacent two width end view drawing pictures after conversion, determined the differential seat angle of adjacent two width images by cross-power spectrum peak value, this differential seat angle is the rotor anglec of rotation.
Described a kind of motor rotor position detection method based on image phase correlation algorithm, it is characterized in that: for the rotor run up, the image of shooting can produce motion blur, affect accuracy of detection, adopt Miniature precision reduction gear, draw a low speed rotating shaft, by the end face of shooting low speed rotating shaft, measure the corner of low speed rotating shaft, be converted to the anglec of rotation of rotor again according to the angular velocity ratio of miniature rotating speed case low speed rotating shaft and rotor, realize detecting the position of motor high speed rotor.
Described a kind of motor rotor position detection method based on image phase correlation algorithm, it is characterized in that: the rotary motion for low speed rotor end face also can produce motion image blurring, also certain impact can be produced on accuracy of detection, after can adopting Wiener's algorithm that clear picture is restored, then carry out phase place and to be correlated with outer corner measurement.
Beneficial effect of the present invention is:
Stable performance of the present invention, precision is higher, and cost is lower, adopts non-contact measurement, and the impact when use operates not by harsh environments is applied widely.
Accompanying drawing explanation
Fig. 1 is theory diagram of the present invention.
Fig. 2 is the theory diagram of area array CCD camera in the present invention.
Embodiment
Shown in composition graphs 1, specific embodiment of the invention step is described:
1. informative image adhesion, is chosen in motor end face;
2., the end face of the alignment lens rotor of area array CCD camera;
3., motor is in rotary state;
4., area array CCD camera takes its end view drawing picture continuously to the rotor rotated; If the motor run up, then take micro speed reducing case, make area array CCD camera photograph the end view drawing picture of the low axle of reducer casing;
5., Wiener's algorithm is adopted to make image restoration to the image collected;
6., to the image after restoring carry out polar coordinate transform, recycling phase place related algorithm finds out the cross-power spectrum peak value of two width end view drawing pictures after conversion, is determined the differential seat angle of two width images by cross-power spectrum peak value;
7. the position determining rotor interval time of these adjacent two width end view drawing pictures of shooting, is combined.
Shown in composition graphs 2, hardware configuration of the present invention is described.In figure, CCD is high-speed camera head, takes rotary motor rotor.The light signal photographed is sent to high-speed CCD chip, light signal is converted into electric signal by high-speed CCD chip, and electric signal is sent in image capture module obtains image, image carries out buffer memory by storer, racemization process is carried out again by DSP642, image information value after racemization process is imported into the FPGA related operation array that walks abreast and carries out phase place related operation, the data of computing gained send into DSP peak value searching and speed calculation module carries out last angle and speed calculates, and by the outside display translation of communication interface.High-speed CCD chip is driven by driving circuit, and image capture module is also controlled by CPLD time-sequence control module.
Installation method in the present invention: choose informative image adhesion on rotor end face, the end face of the alignment lens rotor of area array CCD camera, to the rotor run up, rotor connects micro speed reducing case rotor, choose informative image adhesion on the low axle of reducer casing, take with the low axle of alignment lens reducer casing of CCD camera.
Algorithm principle of the present invention: area array CCD camera carries out racemization process to the two width end view drawing pictures collected, the effect of Wiener filtering to the recovery rotating blurred picture is better, and therefore we adopt Wiener filtering algorithm to carry out racemization.If two width end view drawing pictures before and after racemization are respectively: f
1(x, y) and f
2(x, y).If the image that image f (x, y) is transformed to polar coordinate representation is f (ρ, θ), wherein ρ is footpath, pole, and θ is polar angle, then transformation relation is as follows:
Wherein (x
0, y
0) be transform center.So to f
1(x, y) carries out polar coordinate transform, then f
1(x, y) is transformed to:
F
2(x, y) is f
1(x, y) rotates the image that θ obtains, and expression formula is:
f
2 (x ,y)= f
1 ( xcosθ+ysinθ,-xsinθ+ycosθ) (4)
To f
2(x, y) carries out polar coordinate transform, namely carries out polar coordinate transform to formula (4) the right:
Formula (3) and (5) are respectively f
1(x, y) and f
2(x, y) carries out gained after polar coordinate transform, is set to f
3(x, y) and f
4(x, y), then can find out: f
4(x, y)=f
3(x, y-θ)
Thus can find out that the anglec of rotation of original image is converted to translational movement.
Carry out Fourier transform to formula (6) both sides to obtain: F
4(u, v)=F
3(u, v) e
-jv θ(7)
Convolution (7) calculates f
3(x, y) and f
4the cross-power spectrum of (x, y):
=e
(8)
In formula (8), F
(u, v) is F
the complex conjugate of (u, v), e
fourier inversion Two-dimensional Pulsed function δ (x, y-θ), this Fourier inversion is phase place related algorithm.Find out θ by its peak value, this is the anglec of rotation, then combines the position determining rotor interval time of these adjacent two width end view drawing pictures of shooting.
Claims (1)
1. based on a motor rotor position detection method for image phase correlation algorithm, comprise motor and area array CCD camera, it is characterized in that: detect and comprise following key step:
1., the end face of the alignment lens rotor of described area array CCD camera;
2., described motor is in rotary state;
3., described area array CCD camera takes its end view drawing picture continuously to the rotor rotated;
4., according to the information of captured adjacent two width end view drawing pictures calculate the angle that rotor turns over, then combine the position determining rotor interval time of these adjacent two width end view drawing pictures of shooting;
For the end view drawing picture determination motor rotor position according to shooting, concrete grammar adopts the adjacent two width end view drawing pictures of Wiener filtering algorithm to shooting to carry out racemization, if two width end view drawing pictures after racemization are respectively: f
1(x, y) and f
2(x, y); If the image that image f (x, y) is transformed to polar coordinate representation is f (ρ, θ), wherein ρ is footpath, pole, and θ is polar angle, then transformation relation is as follows:
If (x
0, y
0) be image polar coordinate transform center, so to f
1(x, y) carries out polar coordinate transform, then f
1(x, y) is transformed to:
F
2(x, y) is f
1(x, y) rotates the image that θ obtains, and expression formula is:
f
2(x,y)＝f
1(xcosθ+ysinθ,-xsinθ+ycosθ) (4)
To f
2(x, y) carries out polar coordinate transform, namely carries out polar coordinate transform to formula (4) the right:
Formula (3) and (5) are respectively f
1(x, y) and f
2(x, y) carries out gained after polar coordinate transform, is set to f
3(x, y) and f
4(x, y), then can find out: f
4(x, y)=f
3(x, y-θ) (6)
Thus can find out that the anglec of rotation of original image is converted to translational movement,
Carry out Fourier transform to formula (6) both sides to obtain: F
4(u, v)=F
3(u, v) e
-jv θ(7)
Convolution (7) calculates f
3(x, y) and f
4the cross-power spectrum of (x, y):
In formula (8),
for F
3the complex conjugate of (u, v), e
-jv θfourier inversion Two-dimensional Pulsed function δ (x, y-θ), this Fourier inversion is phase place related algorithm, finds out θ by its peak value, this is the anglec of rotation, then combines the position determining rotor interval time of these adjacent two width end view drawing pictures of shooting;
For the rotor run up, the image of shooting can produce motion blur, affect accuracy of detection, adopt Miniature precision reduction gear, draw a low speed rotating shaft, by the corner of the end surface measurement low speed rotating shaft of shooting low speed rotating shaft, then be converted to the anglec of rotation of rotor according to the angular velocity ratio of miniature rotating speed case low speed rotating shaft and rotor, realize detecting the position of motor high speed rotor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210090920.8A CN102645161B (en) | 2012-03-31 | 2012-03-31 | Motor rotor position detection method based on image phase correlation algorithm |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210090920.8A CN102645161B (en) | 2012-03-31 | 2012-03-31 | Motor rotor position detection method based on image phase correlation algorithm |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102645161A CN102645161A (en) | 2012-08-22 |
| CN102645161B true CN102645161B (en) | 2015-01-28 |
Family
ID=46658138
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210090920.8A Active CN102645161B (en) | 2012-03-31 | 2012-03-31 | Motor rotor position detection method based on image phase correlation algorithm |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN102645161B (en) |
Families Citing this family (8)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104515867B (en) * | 2014-09-19 | 2017-11-28 | 中国人民解放军军事交通学院 | Power set axle moment of torsion based on dual camera, rotating speed, power parameter measuring method |
| CN104713478B (en) * | 2015-03-05 | 2018-02-27 | 安徽大学 | A kind of linear motor rotor location measurement method |
| CN105716693A (en) * | 2016-01-27 | 2016-06-29 | 山东厚德测控技术有限公司 | Water meter gear real-time recognition system and method based on high-speed photography |
| CN106525865A (en) * | 2016-11-30 | 2017-03-22 | 南京理工大学 | Wafer image analysis device and method based on image processing |
| CN108151675A (en) * | 2017-11-16 | 2018-06-12 | 柳州健鱼科技有限公司 | A kind of motor rotor position detection based on image phase correlation algorithm |
| CN108195318B (en) * | 2017-12-25 | 2020-05-12 | 安徽大学 | Spherical motor rotor positioning device and positioning method based on laser curtain imaging |
| CN108827148A (en) * | 2018-05-24 | 2018-11-16 | 青岛杰瑞自动化有限公司 | Rotating accuracy measurement method and measuring device |
| US11694323B2 (en) * | 2020-04-23 | 2023-07-04 | Camx Power Llc | Image-based sensor for measuring rotational position of a rotating shaft |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10141879A1 (en) * | 2001-08-28 | 2003-04-03 | Vodafone Pilotentwicklung Gmbh | Determination of the absolute angular position of an electric motor rotor, using an array or reflecting surfaces arranged around the inner surface of a rotor to generate a light signal whose brightness varies with angular position |
| CN1862242A (en) * | 2006-06-14 | 2006-11-15 | 哈尔滨工业大学 | Steam turbine generator set torsion measuring method based on CCD photographing technique |
| CN1924537A (en) * | 2006-05-25 | 2007-03-07 | 上海交通大学 | Laser measuring method for non-contact type micro-rotor vibration displacement |
| CN101556145A (en) * | 2009-04-29 | 2009-10-14 | 徐州工程学院 | Device and method for monitoring slow-speed and over-load rotor eccentricity image |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201489014U (en) * | 2009-10-09 | 2010-05-26 | 湖南师范大学 | Non-contact type rotary speed measuring system |
-
2012
- 2012-03-31 CN CN201210090920.8A patent/CN102645161B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10141879A1 (en) * | 2001-08-28 | 2003-04-03 | Vodafone Pilotentwicklung Gmbh | Determination of the absolute angular position of an electric motor rotor, using an array or reflecting surfaces arranged around the inner surface of a rotor to generate a light signal whose brightness varies with angular position |
| CN1924537A (en) * | 2006-05-25 | 2007-03-07 | 上海交通大学 | Laser measuring method for non-contact type micro-rotor vibration displacement |
| CN1862242A (en) * | 2006-06-14 | 2006-11-15 | 哈尔滨工业大学 | Steam turbine generator set torsion measuring method based on CCD photographing technique |
| CN101556145A (en) * | 2009-04-29 | 2009-10-14 | 徐州工程学院 | Device and method for monitoring slow-speed and over-load rotor eccentricity image |
Non-Patent Citations (3)
| Title |
|---|
| 王群京,钱喆,李争,倪有源,鞠鲁峰.基于机器视觉的永磁球形步进电动机转子位置检测方法.《中国电机工程学报》.2005,第28卷(第36期), * |
| 赵静,赵吉文.基于图像位移测速的电机转子位置和速度检测方法.《电子技术》.2010,(第8期), * |
| 邓红梅,吴四夫.基于相位相关算法的研究与实现.《信息技术》.2005,(第4期), * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN102645161A (en) | 2012-08-22 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102645161B (en) | Motor rotor position detection method based on image phase correlation algorithm | |
| CN111612760B (en) | Method and device for detecting obstacles | |
| US10375376B2 (en) | Pose estimation apparatus and vacuum cleaner system | |
| CN201489014U (en) | Non-contact type rotary speed measuring system | |
| CN103411621B (en) | A kind of vision/INS Combinated navigation method of the optical flow field towards indoor mobile robot | |
| CN103440624B (en) | A kind of image deblurring method based on motion detection and device | |
| CN101915852B (en) | Velocity measurement method based on stereoscopic vision | |
| CN102243764B (en) | Motion characteristic point detection method and device | |
| WO2008060916A2 (en) | Passive single camera imaging system for determining motor vehicle speed | |
| CN102682448B (en) | Stereo vision rapid navigation and positioning method based on double trifocal tensors | |
| CN103686083B (en) | Real-time speed measurement method based on vehicle-mounted sensor video streaming matching | |
| CN101859439A (en) | Movement tracking device for man-machine interaction and tracking method thereof | |
| CN102692236A (en) | Visual milemeter method based on RGB-D camera | |
| CN102221358A (en) | Monocular visual positioning method based on inverse perspective projection transformation | |
| CN103064430A (en) | Mechanical and electrical integration type image stabilization device | |
| CN103033836B (en) | navigation pointing method of vehicle navigation pointing device | |
| CN101173956A (en) | Device and method for measuring solid particle speed of gas/solid phase stream in pneumatic conveying pipe | |
| CN102175169A (en) | Three-dimensional deformation wireless optical measurement system for engineering structure and measurement method thereof | |
| Ng et al. | Continuous-time radar-inertial odometry for automotive radars | |
| CN105096337A (en) | Image global motion compensation method based on hardware platform of gyroscope | |
| CN111609868A (en) | Visual inertial odometer method based on improved optical flow method | |
| CN102980555B (en) | Method and device for detecting direction of optical imaging type wheeled mobile robot | |
| CN111721305B (en) | Positioning method and apparatus, autonomous vehicle, electronic device, and storage medium | |
| CN110411475A (en) | A kind of robot vision odometer assisted based on template matching algorithm and IMU | |
| JP2011064639A (en) | Distance measuring device and distance measuring method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |