CN104615147A - Method and system for accurately positioning polling target of transformer substation - Google Patents
Method and system for accurately positioning polling target of transformer substation Download PDFInfo
- Publication number
- CN104615147A CN104615147A CN201510080758.5A CN201510080758A CN104615147A CN 104615147 A CN104615147 A CN 104615147A CN 201510080758 A CN201510080758 A CN 201510080758A CN 104615147 A CN104615147 A CN 104615147A
- Authority
- CN
- China
- Prior art keywords
- target
- cloud terrace
- sampled images
- patrol
- examine
- 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.)
- Pending
Links
Abstract
The invention provides method and system for accurately positioning a polling target of a transformer substation. The method comprises the steps of determining a polling target; guiding a polling robot to reach the polling target; adjusting an image according to the task load, and adjusting the position of a holder; calculating the deviation of a polling target center in the sampling image center; slightly adjusting the position of the holder according to the deviation to obtain a clear target image. With the adoption of the method and system, the accuracy and precision of positioning the polling target can be improved.
Description
Technical field
The present invention relates to a kind of accurate positioning method and system, be specifically related to a kind of accurate positioning method and system of substation inspection target.
Background technology
The Intelligent Mobile Robot such as visible light camera, thermal infrared imager carries that mission payload system is used for detecting substation equipment abnormal appearance, the identification of temperature anomaly identification and instrument exception.But due to factor impacts such as the accurate positioning error of crusing robot self, course error, cloud platform rotation errors, mission payload system is caused accurately to be located inaccurate, cause and detect target not at field of view or slip chart inconocenter, be difficult to the image obtaining high resolving power, high definition, directly affect accuracy and the accuracy rate of substation equipment testing result.
Application number be 201210083408.0 patent of invention disclose a kind of Intelligent control system of magnetic navigation polling robot, this robot adopts magnetic navigation to improve the accurate positioning precision of platform, navigation accuracy controls within 5mm, after making platform arrival appointment patrol and examine target place, The Cloud Terrace only need move to according to the instruction preset and specify exact position, and mission payload system can meet accurate location requirement.But the realization of this accurate locator meams needs to lay a large amount of magnetic stripes in substation, consumes expensive in advance, cannot patrol and examine, robot environment's bad adaptability to the region robot cannot laying magnetic stripe.
Summary of the invention
For solving the problem, the invention provides a kind of accurate positioning method and system of substation inspection target, make robot platform when not relying on the environmental facilities such as magnetic stripe, quick lock in detects target, obtain high quality graphic, achieve mission payload system accurately to locate, improve robot platform environmental suitability, and save cost.
The object of the invention is to adopt following technical proposals to realize:
An accurate positioning method for substation inspection target, described method comprises:
Determine to patrol and examine target, crusing robot arrives and patrols and examines target place;
Image is gathered, adjustment The Cloud Terrace position according to mission payload; Wherein, described image comprises visible images and infrared image;
Calculate and patrol and examine the side-play amount of target's center at sampled images center, and according to described side-play amount and focal length of camera fine-adjustment tripod head position, obtain target image clearly.
Preferably, describedly determine to patrol and examine target, crusing robot arrives patrols and examines target place and comprises:
Utilize industrial computer to run autonomous navigation system, by position and the course of wheel speed code-disc positioning robot platform, adopt Monte Carlo Precision Orientation Algorithm to position according to the data of laser sensor.
Preferably, described adjustment The Cloud Terrace position comprises:
After patrolling and examining target place described in arriving when robot platform, the The Cloud Terrace movement instruction also stored in an rfid tag by RFID plug-in reader reading pre-set adjusts The Cloud Terrace.
Preferably, the described mission payload acquisition sampled images that utilizes comprises:
Utilize Optimum Classification device to extract the Haar-like feature of patrolling and examining target, in record sampled images, patrol and examine position and size (x, the y of target, φ), wherein, (x, y) for patrolling and examining the Cartesian coordinates set occurrence of target relative to sampled images center, φ is target sizes;
Calculate and patrol and examine the side-play amount of target's center at sampled images center:
(x
0,y
0)＝(x-W/2,y-H/2)
In formula, W and H is respectively width and the length of sampled images.
Further, according to patrolling and examining the side-play amount (x of target's center in sampled images
0, y
0), fine-adjustment tripod head horizontally rotate angle θ
x, vertical rotation angle θ
y, and focal length of camera f;
Described The Cloud Terrace corner parameter θ in the vertical direction
ybe calculated as follows:
than(θ
y)＝(A,y
l)/(A,O)
Wherein, (A, O) is focal length of camera f, (A, y
l) be the distance of target range CCD target surface center Y-direction, and patrol and examine the position one_to_one corresponding of target at image:
y
l/h＝y
0/H
Wherein, h is CCD target surface height, and H is sampled images height, therefore
than(θ
y)＝y
0×h/(H×f)；
Described The Cloud Terrace corner parameter θ in the horizontal direction
xbe calculated as follows:
than(θ
x)＝x
0×h/(H×f)
In formula, h is CCD target surface height, and H is sampled images height, and f is focal length of camera.
Further, when patrol and examine target sizes φ be less than in sampled images patrol and examine target sizes Φ time, by sampled images patrol and examine target amplify, its enlargement factor is:
φ/Φ＝f/F
Wherein, F is for expecting focal length, and f is current camera focal length, and video camera enlargement factor zoom is calculated as follows:
zoom＝f×Φ/(φ×4.7)
According to The Cloud Terrace side-play amount and video camera enlargement factor zoom fine-adjustment tripod head, the target of patrolling and examining identified is moved to sampled images center, to reach best observation position.
A Precise Position System for substation inspection target, described system comprises:
Robot platform, for patrolling and examining transformer station;
Industrial computer, for running autonomous navigation system;
The Cloud Terrace, for adjusting mission payload orientation;
Mission payload, for obtaining detection target;
Described mission payload is installed in The Cloud Terrace, and described The Cloud Terrace and described industrial computer are installed on robot platform.
Preferably, described robot platform comprises laser sensor and RFID plug-in reader; Wherein,
Described laser sensor is used for the distance in acquisition environment between object and robot;
Described RFID plug-in reader for reading the RFID label tag of pasting in environment, to obtain the The Cloud Terrace movement instruction of storage.
Preferably, described industrial computer comprises, autonomous navigation system and wheel speed code-disc;
Described autonomous navigation system is according to the data of described laser sensor, and guided robot platform is accurately located;
Described wheel speed code-disc is used for position and the course of accurate positioning estimation robot platform;
Preferably, described The Cloud Terrace comprises The Cloud Terrace motion-control module;
Described The Cloud Terrace motion-control module is used for by The Cloud Terrace movement instruction, adjustment The Cloud Terrace position.
Preferably, described mission payload comprises visible light camera and thermal infrared imager;
Described visible light camera is for detecting substation equipment abnormal appearance and Meter recognition;
Described thermal infrared imager is for detecting the temperature anomaly identification of substation equipment.
Further, described laser sensor is connected with described industrial computer by netting twine; The data of laser sensor reach described industrial computer by Ethernet; Described robot platform is accurately located according to the data of described laser sensor.
Compared with prior art, the beneficial effect that the present invention reaches is:
The present invention devises mission payload system closed loop accurate positioning method, realizes the accurate location of Intelligent Mobile Robot mission payload.When robot platform is accurately located inaccurate, the instruction adjustment The Cloud Terrace stored according to RFID label tag arrives patrols and examines target place, realizes the first accurate location of mission payload system.
Adopt mission payload system to obtain visible images and infrared image, using the position of impact point in visible images and infrared image and size as close-loop feedback, fine-adjustment tripod head position, achieves the accurate location of mission payload system, obtains high quality graphic.
The method lays a large amount of magnetic stripes without the need to prior in substation, saves spending; Robot avoids the restriction of environment in the process of patrolling and examining, and substantially increases the adaptability that robot platform is patrolled and examined thus.
Accompanying drawing explanation
Fig. 1 is the accurate positioning method process flow diagram of substation inspection target of the present invention
Fig. 2 is the Precise Position System schematic diagram of substation inspection target of the present invention
Wherein, 1. robot platform, 2. laser sensor, 3.RFID, 4. industrial computer, 5. The Cloud Terrace, 6. mission payload
Fig. 3 is that robot platform independent navigation of the present invention realizes schematic diagram
Fig. 4 is The Cloud Terrace of the present invention fine setting schematic diagram
Fig. 5 is image projection relation principle figure of the present invention
Embodiment
Below in conjunction with accompanying drawing, the specific embodiment of the present invention is described in further detail.
As shown in Figure 1, a kind of accurate positioning method of substation inspection target, described method comprises:
Determine to patrol and examine target, crusing robot arrives and patrols and examines target place; As shown in Figure 3, describedly determine to patrol and examine target, crusing robot arrives patrols and examines target place and comprises:
Utilize industrial computer to run autonomous navigation system, by position and the course of wheel speed code-disc positioning robot platform, adopt Monte Carlo Precision Orientation Algorithm to position according to the data of laser sensor.
Image is gathered, adjustment The Cloud Terrace position according to mission payload; Wherein, described image comprises visible images and infrared image; Described adjustment The Cloud Terrace position comprises: after patrolling and examining target place described in arriving when robot platform, the The Cloud Terrace movement instruction also stored in an rfid tag by RFID plug-in reader reading pre-set adjusts The Cloud Terrace.
Calculate and patrol and examine the side-play amount of target's center at sampled images center, and according to described side-play amount and focal length of camera fine-adjustment tripod head position, obtain target image clearly.The described mission payload acquisition sampled images that utilizes comprises:
An Optimum Classification device is obtained after adopting AdaBoost algorithm to carry out training study to image set, Optimum Classification device is utilized to extract the Haar-like feature of patrolling and examining target, position and the size (x of target is patrolled and examined in record sampled images, y, φ), wherein, (x, y) for patrolling and examining the Cartesian coordinates set occurrence of target relative to sampled images center, φ is target sizes;
Calculate and patrol and examine the side-play amount of target's center at sampled images center:
(x
0,y
0)＝(x-W/2,y-H/2)
In formula, W and H is respectively width and the length of sampled images.
As shown in Figure 4, the side-play amount (x in image is being gathered according to patrolling and examining target's center
0, y
0), fine-adjustment tripod head horizontally rotate angle θ
x, vertical rotation angle θ
y, and focal length of camera f;
Described The Cloud Terrace corner parameter θ in the vertical direction
ybe calculated as follows:
than(θ
y)＝(A,y
l)/(A,O)
As shown in Figure 5, wherein, (A, O) is focal length of camera f, (A, y
l) be the distance of target range CCD target surface center Y-direction, and patrol and examine the position one_to_one corresponding of target at image:
y
l/h＝y
0/H
Wherein, h is CCD target surface height, and H is sampled images height, therefore
than(θ
y)＝y
0×h/(H×f)；
Described The Cloud Terrace corner parameter θ in the horizontal direction
xbe calculated as follows:
than(θ
x)＝x
0×h/(H×f)
In formula, h is CCD target surface height, and H is sampled images height, and f is focal length of camera.
When patrol and examine target sizes φ be less than in sampled images patrol and examine target sizes Φ time, by sampled images patrol and examine target amplify, its enlargement factor is:
φ/Φ＝f/F
Wherein, F is for expecting focal length, and f is current camera focal length, and video camera enlargement factor zoom is calculated as follows:
zoom＝f×Φ/(φ×4.7)
According to The Cloud Terrace side-play amount and video camera enlargement factor zoom fine-adjustment tripod head, the target of patrolling and examining identified is moved to sampled images center, to reach best observation position.
As shown in Figure 2, a kind of Precise Position System of substation inspection target, described system comprises:
Robot platform, described robot platform is Intelligent Mobile Robot, for patrolling and examining transformer station; Described robot platform comprises laser sensor and RFID plug-in reader; Wherein,
Described laser sensor is used for the distance in acquisition environment between object and robot;
Described RFID plug-in reader for reading the RFID label tag of pasting in environment, to obtain the The Cloud Terrace movement instruction of storage.
Industrial computer, for running autonomous navigation system; Described industrial computer comprises, autonomous navigation system and wheel speed code-disc;
Described autonomous navigation system is according to the data of described laser sensor, and guided robot platform is accurately located;
Described wheel speed code-disc is used for position and the course of accurate positioning estimation robot platform;
Described laser sensor is connected with described industrial computer by netting twine; The data of laser sensor reach described industrial computer by Ethernet; Described robot platform is accurately located according to the data of described laser sensor.
The Cloud Terrace, for adjusting mission payload orientation; Level ± 180 ° can be realized, pitching-30 °-+90 °; Described The Cloud Terrace comprises The Cloud Terrace motion-control module; Described The Cloud Terrace motion-control module is used for by The Cloud Terrace movement instruction, adjustment The Cloud Terrace position.
Mission payload, for obtaining detection target;
Described mission payload is installed in The Cloud Terrace, and described The Cloud Terrace and described industrial computer are installed on robot platform.
Described mission payload comprises visible light camera and thermal infrared imager;
Described visible light camera is for detecting substation equipment abnormal appearance and Meter recognition;
Described thermal infrared imager is for detecting the temperature anomaly identification of substation equipment.
Finally should be noted that: above embodiment is only in order to illustrate the technical scheme of the application but not the restriction to its protection domain; although with reference to above-described embodiment to present application has been detailed description; those of ordinary skill in the field are to be understood that: those skilled in the art still can carry out all changes, amendment or equivalent replacement to the embodiment of application after reading the application; these change, amendment or equivalent to replace, and it is all within it applies for the right that awaits the reply.
Claims (12)
1. an accurate positioning method for substation inspection target, is characterized in that, described method comprises:
Determine to patrol and examine target, crusing robot arrives and patrols and examines target place;
Image is gathered, adjustment The Cloud Terrace position according to mission payload; Wherein, described image comprises visible images and infrared image;
Calculate and patrol and examine the side-play amount of target's center at sampled images center, and according to described side-play amount and focal length of camera fine-adjustment tripod head position, obtain target image clearly.
2. the accurate positioning method of substation inspection target as claimed in claim 1, is characterized in that, describedly determines to patrol and examine target, and crusing robot arrives patrols and examines target place and comprise:
Utilize industrial computer to run autonomous navigation system, by position and the course of wheel speed code-disc positioning robot platform, adopt Monte Carlo Precision Orientation Algorithm, the data according to laser sensor position.
3. the accurate positioning method of substation inspection target as claimed in claim 1, it is characterized in that, described adjustment The Cloud Terrace position comprises:
After patrolling and examining target place described in arriving when robot platform, the The Cloud Terrace movement instruction also stored in an rfid tag by RFID plug-in reader reading pre-set adjusts The Cloud Terrace.
4. the accurate positioning method of substation inspection target as claimed in claim 1, is characterized in that, the described mission payload acquisition sampled images that utilizes comprises:
Utilize Optimum Classification device to extract the Haar-like feature of patrolling and examining target, in record sampled images, patrol and examine position and size (x, the y of target, φ), wherein, (x, y) for patrolling and examining the Cartesian coordinates set occurrence of target relative to sampled images center, φ is target sizes;
Calculate and patrol and examine the side-play amount of target's center at sampled images center:
(x
0,y
0)＝(x-W/2,y-H/2)
In formula, W and H is respectively width and the length of sampled images.
5. the accurate positioning method of substation inspection target as claimed in claim 4, is characterized in that, comprising: gathering the side-play amount (x in image according to patrolling and examining target's center
0, y
0), fine-adjustment tripod head horizontally rotate angle θ
x, vertical rotation angle θ
y, and focal length of camera f;
Described The Cloud Terrace corner parameter θ in the vertical direction
ybe calculated as follows:
than(θ
y)＝(A,y
l)/(A,O)
Wherein, (A, O) is focal length of camera f, (A, y
l) be the distance of target range CCD target surface center Y-direction, and patrol and examine the position one_to_one corresponding of target at image:
y
l/h＝y
0/H
Wherein, h is CCD target surface height, and H is sampled images height, therefore
than(θ
y)＝y
0×h/(H×f)；
Described The Cloud Terrace corner parameter θ in the horizontal direction
xbe calculated as follows:
than(θ
x)＝x
0×h/(H×f)
In formula, h is CCD target surface height, and H is sampled images height, and f is focal length of camera.
6. the accurate positioning method of substation inspection target as claimed in claim 4, is characterized in that, when patrol and examine target sizes φ be less than in sampled images patrol and examine target sizes Φ time, the target of patrolling and examining in sampled images amplified, its enlargement factor is:
φ/Φ＝f/F
Wherein, F is for expecting focal length, and f is current camera focal length, and video camera enlargement factor zoom is calculated as follows:
zoom＝f×Φ/(φ×4.7)
According to The Cloud Terrace side-play amount and video camera enlargement factor zoom fine-adjustment tripod head, the target of patrolling and examining identified is moved to sampled images center, to reach best observation position.
7. a Precise Position System for substation inspection target, is characterized in that, described system comprises:
Robot platform, for patrolling and examining transformer station;
Industrial computer, for running autonomous navigation system;
The Cloud Terrace, for adjusting mission payload orientation;
Mission payload, for obtaining detection target;
Described mission payload is installed in The Cloud Terrace, and described The Cloud Terrace and described industrial computer are installed on robot platform.
8. the Precise Position System of substation inspection target as claimed in claim 7, it is characterized in that, described robot platform comprises laser sensor and RFID plug-in reader; Wherein,
Described laser sensor is used for the distance in acquisition environment between object and robot;
Described RFID plug-in reader for reading the RFID label tag of pasting in environment, to obtain the The Cloud Terrace movement instruction of storage.
9. the Precise Position System of substation inspection target as claimed in claim 7, it is characterized in that, described industrial computer comprises, autonomous navigation system and wheel speed code-disc;
Described autonomous navigation system is according to the data of described laser sensor, and guided robot platform is accurately located;
Described wheel speed code-disc is used for position and the course of accurate positioning estimation robot platform.
10. the Precise Position System of substation inspection target as claimed in claim 7, it is characterized in that, described The Cloud Terrace comprises The Cloud Terrace motion-control module;
Described The Cloud Terrace motion-control module is used for by The Cloud Terrace movement instruction, adjustment The Cloud Terrace position.
The Precise Position System of 11. substation inspection targets as claimed in claim 7, it is characterized in that, described mission payload comprises visible light camera and thermal infrared imager;
Described visible light camera is for detecting substation equipment abnormal appearance and Meter recognition;
Described thermal infrared imager is for detecting the temperature anomaly identification of substation equipment.
The Precise Position System of 12. substation inspection targets as described in claim 7-8, it is characterized in that, described laser sensor is connected with described industrial computer by netting twine; The data of laser sensor reach described industrial computer by Ethernet; Described robot platform is accurately located according to the data of described laser sensor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510080758.5A CN104615147A (en) | 2015-02-13 | 2015-02-13 | Method and system for accurately positioning polling target of transformer substation |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510080758.5A CN104615147A (en) | 2015-02-13 | 2015-02-13 | Method and system for accurately positioning polling target of transformer substation |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN104615147A true CN104615147A (en) | 2015-05-13 |
Family
ID=53149645
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510080758.5A Pending CN104615147A (en) | 2015-02-13 | 2015-02-13 | Method and system for accurately positioning polling target of transformer substation |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN104615147A (en) |
Cited By (22)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105137995A (en) * | 2015-09-11 | 2015-12-09 | 云南电网有限责任公司电力科学研究院 | Transformer substation X ray detection object identification method based on RFID technology |
| CN105445752A (en) * | 2015-12-16 | 2016-03-30 | 上海倍肯机电科技有限公司 | Power transmission line protection device and power transmission line protection method based on laser three-dimensional imaging |
| CN107092905A (en) * | 2017-03-24 | 2017-08-25 | 重庆邮电大学 | A kind of instrument localization method to be identified of electric inspection process robot |
| CN107219235A (en) * | 2016-10-27 | 2017-09-29 | 中新红外科技（武汉）有限公司 | A kind of wind energy infra-red inspection instrument and its operating system |
| CN107505049A (en) * | 2017-08-10 | 2017-12-22 | 国家电网公司 | A kind of transformer station's infrared detection method and system |
| CN107679775A (en) * | 2017-10-31 | 2018-02-09 | 合肥天鹰高科技有限公司 | A kind of power networks risk control platform |
| CN107703956A (en) * | 2017-09-28 | 2018-02-16 | 山东鲁能智能技术有限公司 | A kind of virtual interaction system and its method of work based on inertia capturing technology |
| CN107764405A (en) * | 2017-10-19 | 2018-03-06 | 上海电力学院 | Electric inspection process robot infrared temperature measurement apparatus based on laser ranging and viewing angle compensation |
| CN107807645A (en) * | 2017-10-31 | 2018-03-16 | 合肥天鹰高科技有限公司 | A kind of intelligent substation management method based on automatic guided vehicle |
| CN107941342A (en) * | 2017-10-19 | 2018-04-20 | 上海电力学院 | Comprehensive distance and the electric inspection process robot infrared temperature measurement apparatus and method at visual angle |
| CN108362203A (en) * | 2018-03-02 | 2018-08-03 | 中信重工开诚智能装备有限公司 | A kind of automatic positioning detectable substance system and method for wheeled crusing robot |
| CN108548527A (en) * | 2018-06-27 | 2018-09-18 | 云南电网有限责任公司昆明供电局 | Xun Wei robots of substation measurement point auxiliary device |
| CN109119923A (en) * | 2018-08-03 | 2019-01-01 | 合肥工业大学 | Transformer and distribution station device intelligence cruising inspection system and its method for inspecting |
| CN109238241A (en) * | 2018-09-30 | 2019-01-18 | 国网山东省电力公司电力科学研究院 | A kind of vehicle-mounted automatic tour inspection system of distribution line and its method for inspecting |
| CN111316185A (en) * | 2019-02-26 | 2020-06-19 | 深圳市大疆创新科技有限公司 | Inspection control method of movable platform and movable platform |
| CN111611989A (en) * | 2020-05-22 | 2020-09-01 | 四川智动木牛智能科技有限公司 | Multi-target accurate positioning identification method based on autonomous robot |
| CN111899373A (en) * | 2020-08-05 | 2020-11-06 | 中国工商银行股份有限公司 | Method and device for determining inspection point of machine room, robot and storage medium |
| CN112258682A (en) * | 2020-10-19 | 2021-01-22 | 合肥科大智能机器人技术有限公司 | Transformer substation robot inspection system and inspection method thereof |
| CN112703504A (en) * | 2018-10-19 | 2021-04-23 | 深圳新物种科技有限公司 | Object identification method and device, electronic equipment and computer readable storage medium |
| CN113342061A (en) * | 2021-04-22 | 2021-09-03 | 云南电网有限责任公司昆明供电局 | Meter image identification dynamic correction method for transformer substation inspection robot |
| CN113334373A (en) * | 2021-05-14 | 2021-09-03 | 广西电网有限责任公司电力科学研究院 | Control method for indoor automatic inspection robot system of transformer substation |
| CN113593249A (en) * | 2021-07-12 | 2021-11-02 | 浙江中烟工业有限责任公司 | Dynamic parking space vehicle line pressing identification method based on mobile platform |
Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101247030A (en) * | 2007-08-01 | 2008-08-20 | 北京深浪电子技术有限公司 | Overhead network obstacle detouring inspection robot and its obstacle detouring control method |
| CN202075624U (en) * | 2011-04-12 | 2011-12-14 | 中国科学院沈阳自动化研究所 | Transformer station track type intelligent inspection robot |
| CN102280826A (en) * | 2011-07-30 | 2011-12-14 | 山东鲁能智能技术有限公司 | Intelligent robot inspection system and intelligent robot inspection method for transformer station |
| CN202167775U (en) * | 2011-07-30 | 2012-03-14 | 山东电力研究院 | Transformer station inspection robot remote data acquisition system based on mobile communication technology |
| CN202423926U (en) * | 2012-02-24 | 2012-09-05 | 山东鲁能智能技术有限公司 | Transformer substation polling robot gesture driving system based on electronic map |
| CN202985567U (en) * | 2013-01-11 | 2013-06-12 | 山东鲁能智能技术有限公司 | Intelligent detection robot for insulator string |
| CN103226711A (en) * | 2013-03-28 | 2013-07-31 | 四川长虹电器股份有限公司 | Quick Haar wavelet feature object detecting method |
| CN103714337A (en) * | 2012-10-09 | 2014-04-09 | 鸿富锦精密工业（深圳）有限公司 | Object feature identification system and method |
| CN104318588A (en) * | 2014-11-04 | 2015-01-28 | 北京邮电大学 | Multi-video-camera target tracking method based on position perception and distinguish appearance model |
-
2015
- 2015-02-13 CN CN201510080758.5A patent/CN104615147A/en active Pending
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101247030A (en) * | 2007-08-01 | 2008-08-20 | 北京深浪电子技术有限公司 | Overhead network obstacle detouring inspection robot and its obstacle detouring control method |
| CN202075624U (en) * | 2011-04-12 | 2011-12-14 | 中国科学院沈阳自动化研究所 | Transformer station track type intelligent inspection robot |
| CN102280826A (en) * | 2011-07-30 | 2011-12-14 | 山东鲁能智能技术有限公司 | Intelligent robot inspection system and intelligent robot inspection method for transformer station |
| CN202167775U (en) * | 2011-07-30 | 2012-03-14 | 山东电力研究院 | Transformer station inspection robot remote data acquisition system based on mobile communication technology |
| CN202423926U (en) * | 2012-02-24 | 2012-09-05 | 山东鲁能智能技术有限公司 | Transformer substation polling robot gesture driving system based on electronic map |
| CN103714337A (en) * | 2012-10-09 | 2014-04-09 | 鸿富锦精密工业（深圳）有限公司 | Object feature identification system and method |
| CN202985567U (en) * | 2013-01-11 | 2013-06-12 | 山东鲁能智能技术有限公司 | Intelligent detection robot for insulator string |
| CN103226711A (en) * | 2013-03-28 | 2013-07-31 | 四川长虹电器股份有限公司 | Quick Haar wavelet feature object detecting method |
| CN104318588A (en) * | 2014-11-04 | 2015-01-28 | 北京邮电大学 | Multi-video-camera target tracking method based on position perception and distinguish appearance model |
Non-Patent Citations (9)
| Title |
|---|
| 刘瑶: "220~500kV无人值班变电站履带式巡视机器人", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
| 李应: "变电站巡检机器人嵌入式导航系统研究", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
| 柳维长: "RFID与物联网", 《信息与电脑》 * |
| 柳维长: "快速发展中的RFID", 《信息与电脑》 * |
| 王鲁单等: "一种输电线路巡检机器人控制系统的设计与实现", 《机器人》 * |
| 肖鹏等: "变电站智能巡检机器人激光导航系统研究", 《自动化与仪表》 * |
| 肖鹏等: "基于激光定位的变电站智能巡检机器人导航系统设计", 《计算机测量与控制》 * |
| 许湘明等: "变电站机器人视觉伺服系统研究", 《西南科技大学学报》 * |
| 陈聪: "基于RFID技术的电力通信设备巡检系统研究", 《中国优秀硕士学位论文全文数据库 工程科技II辑》 * |
Cited By (27)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105137995B (en) * | 2015-09-11 | 2017-09-22 | 云南电网有限责任公司电力科学研究院 | A kind of transformer station's X-ray detection target identification method based on RFID technique |
| CN105137995A (en) * | 2015-09-11 | 2015-12-09 | 云南电网有限责任公司电力科学研究院 | Transformer substation X ray detection object identification method based on RFID technology |
| CN105445752A (en) * | 2015-12-16 | 2016-03-30 | 上海倍肯机电科技有限公司 | Power transmission line protection device and power transmission line protection method based on laser three-dimensional imaging |
| CN107219235A (en) * | 2016-10-27 | 2017-09-29 | 中新红外科技（武汉）有限公司 | A kind of wind energy infra-red inspection instrument and its operating system |
| CN107092905A (en) * | 2017-03-24 | 2017-08-25 | 重庆邮电大学 | A kind of instrument localization method to be identified of electric inspection process robot |
| CN107092905B (en) * | 2017-03-24 | 2020-04-14 | 重庆邮电大学 | Method for positioning instrument to be identified of power inspection robot |
| CN107505049A (en) * | 2017-08-10 | 2017-12-22 | 国家电网公司 | A kind of transformer station's infrared detection method and system |
| CN107703956A (en) * | 2017-09-28 | 2018-02-16 | 山东鲁能智能技术有限公司 | A kind of virtual interaction system and its method of work based on inertia capturing technology |
| CN107941342A (en) * | 2017-10-19 | 2018-04-20 | 上海电力学院 | Comprehensive distance and the electric inspection process robot infrared temperature measurement apparatus and method at visual angle |
| CN107764405A (en) * | 2017-10-19 | 2018-03-06 | 上海电力学院 | Electric inspection process robot infrared temperature measurement apparatus based on laser ranging and viewing angle compensation |
| CN107679775A (en) * | 2017-10-31 | 2018-02-09 | 合肥天鹰高科技有限公司 | A kind of power networks risk control platform |
| CN107807645A (en) * | 2017-10-31 | 2018-03-16 | 合肥天鹰高科技有限公司 | A kind of intelligent substation management method based on automatic guided vehicle |
| CN108362203A (en) * | 2018-03-02 | 2018-08-03 | 中信重工开诚智能装备有限公司 | A kind of automatic positioning detectable substance system and method for wheeled crusing robot |
| CN108548527A (en) * | 2018-06-27 | 2018-09-18 | 云南电网有限责任公司昆明供电局 | Xun Wei robots of substation measurement point auxiliary device |
| CN108548527B (en) * | 2018-06-27 | 2023-08-01 | 云南电网有限责任公司昆明供电局 | Substation inspection robot measuring point auxiliary device |
| CN109119923A (en) * | 2018-08-03 | 2019-01-01 | 合肥工业大学 | Transformer and distribution station device intelligence cruising inspection system and its method for inspecting |
| CN109238241B (en) * | 2018-09-30 | 2021-04-20 | 国网智能科技股份有限公司 | Vehicle-mounted automatic inspection system and inspection method for distribution line |
| CN109238241A (en) * | 2018-09-30 | 2019-01-18 | 国网山东省电力公司电力科学研究院 | A kind of vehicle-mounted automatic tour inspection system of distribution line and its method for inspecting |
| CN112703504A (en) * | 2018-10-19 | 2021-04-23 | 深圳新物种科技有限公司 | Object identification method and device, electronic equipment and computer readable storage medium |
| CN111316185A (en) * | 2019-02-26 | 2020-06-19 | 深圳市大疆创新科技有限公司 | Inspection control method of movable platform and movable platform |
| CN111611989A (en) * | 2020-05-22 | 2020-09-01 | 四川智动木牛智能科技有限公司 | Multi-target accurate positioning identification method based on autonomous robot |
| CN111899373A (en) * | 2020-08-05 | 2020-11-06 | 中国工商银行股份有限公司 | Method and device for determining inspection point of machine room, robot and storage medium |
| CN112258682A (en) * | 2020-10-19 | 2021-01-22 | 合肥科大智能机器人技术有限公司 | Transformer substation robot inspection system and inspection method thereof |
| CN113342061A (en) * | 2021-04-22 | 2021-09-03 | 云南电网有限责任公司昆明供电局 | Meter image identification dynamic correction method for transformer substation inspection robot |
| CN113334373A (en) * | 2021-05-14 | 2021-09-03 | 广西电网有限责任公司电力科学研究院 | Control method for indoor automatic inspection robot system of transformer substation |
| CN113334373B (en) * | 2021-05-14 | 2023-03-14 | 广西电网有限责任公司电力科学研究院 | Control method for indoor automatic inspection robot system of transformer substation |
| CN113593249A (en) * | 2021-07-12 | 2021-11-02 | 浙江中烟工业有限责任公司 | Dynamic parking space vehicle line pressing identification method based on mobile platform |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN104615147A (en) | Method and system for accurately positioning polling target of transformer substation | |
| US10930015B2 (en) | Method and system for calibrating multiple cameras | |
| CN109029257B (en) | Large-scale workpiece pose measurement system and method based on stereoscopic vision and structured light vision | |
| US20220077820A1 (en) | Method and system for soar photovoltaic power station monitoring | |
| US9134127B2 (en) | Determining tilt angle and tilt direction using image processing | |
| CN106595630B (en) | It is a kind of that drawing system and method are built based on laser navigation Intelligent Mobile Robot | |
| CN106408601B (en) | A kind of binocular fusion localization method and device based on GPS | |
| CN105184776A (en) | Target tracking method | |
| US20130176432A1 (en) | Automatic calibration of ptz camera system | |
| KR102016636B1 (en) | Calibration apparatus and method of camera and rader | |
| CN105424006A (en) | Unmanned aerial vehicle hovering precision measurement method based on binocular vision | |
| US20130304374A1 (en) | Apparatus and method for recognizing position of moving object | |
| CN103256920A (en) | Determining tilt angle and tilt direction using image processing | |
| KR102217549B1 (en) | Method and system for soar photovoltaic power station monitoring | |
| CN205333067U (en) | Laser photogrammetric survey system | |
| CN110488838B (en) | Accurate repeated positioning method for indoor autonomous navigation robot | |
| CN113226952A (en) | Article position management device, article position management system, article position management method, and program | |
| CN110490932A (en) | The infrared coplanar cursor iteration optimization measurement driving boom spatial pose method of monocular | |
| EP3690390A1 (en) | Electronic nose positioning device and positioning method | |
| CN108932732B (en) | Method and device for acquiring data information of monitored object | |
| Zhang et al. | Development and implementation of a robotic inspection system for power substations | |
| EP3904993B1 (en) | Positioning apparatus and moving body | |
| CN109146936B (en) | Image matching method, device, positioning method and system | |
| CN207923179U (en) | Intelligent patrol detection vehicle | |
| CN112611344B (en) | Autonomous mobile flatness detection method, device and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| RJ01 | Rejection of invention patent application after publication |
Application publication date: 20150513 |
|
| RJ01 | Rejection of invention patent application after publication |