CN102881106B - Dual-detection forest fire identification system through thermal imaging video and identification method thereof - Google Patents
Dual-detection forest fire identification system through thermal imaging video and identification method thereof Download PDFInfo
- Publication number
- CN102881106B CN102881106B CN201210331547.0A CN201210331547A CN102881106B CN 102881106 B CN102881106 B CN 102881106B CN 201210331547 A CN201210331547 A CN 201210331547A CN 102881106 B CN102881106 B CN 102881106B
- Authority
- CN
- China
- Prior art keywords
- thermal imaging
- video
- image
- video image
- processing unit
- 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
Images
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A40/00—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production
- Y02A40/10—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture
- Y02A40/28—Adaptation technologies in agriculture, forestry, livestock or agroalimentary production in agriculture specially adapted for farming
Landscapes
- Fire-Detection Mechanisms (AREA)
- Alarm Systems (AREA)
- Image Analysis (AREA)
Abstract
The invention discloses a dual-detection forest fire identification system through a thermal imaging video and an identification method thereof. The identification system comprises a thermal imaging camera, a video camera and a processing unit, wherein both the thermal imaging camera and the video camera are in signal communication with the processing unit; the processing unit comprises a thermal imaging analysis unit and a video image analysis unit and calculates angular points of a heat source image and a video image as well as the affine equation between the thermal imaging camera and the video camera through matching the angular points to realize the mapping between a thermal imaging image and the video image; and the position corresponding to an abnormal heat source can be marked on the video image. The dual-detection forest fire identification system through the thermal imaging video and the identification method thereof are simple and practical, and have high identification accuracy and low missing and false report rate. In addition, the forest fire can be detected in low-speed cruising without adopting the fixed-point detection in a common pre-reserved point mode, the blind area of detection can be avoided, and the practicability is good.
Description
Technical field
The present invention relates to forest fires recognition system, be specifically related to a kind of thermal imaging video two mirror forest fires recognition system and recognition methods thereof.
Background technology
At present, in the automatic identification field of fire alarm, often adopt image recognition technology or thermal imaging to realize detection and the warning of fire alarm.Adopt image recognition technology to carry out fire alarm and detect and refer to and utilize monitor video, the feature in video and image according to smog or fire, adopts image processing techniques, a kind of fire alarm detection method of identifying.In order to improve recognition effect, need in advance background image to be learnt.Therefore monitoring preset point can be set conventionally, call monitoring preset point, by the priori of background image, smog and fire alarm be identified.This mode is identified and is had a large amount of blind areas, and coverage rate is not high, meanwhile, uses image recognition technology to carry out recognition correct rate also not high.Glow or time on fire, abnormal rising can occur temperature, therefore also can utilize this feature due to forest, adopt thermal imaging to monitor abnormal high temperature region.But, use thermal imaging to be subject to the interference of the thermals source such as vehicle motor.
Summary of the invention
Goal of the invention: for the deficiencies in the prior art, the object of this invention is to provide the two mirror of a kind of thermal imaging video forest fires recognition system, to improve the accuracy of identification, meet user demand.Another object of the present invention is to provide the recognition methods of the two mirror of a kind of above-mentioned thermal imaging video forest fires recognition system.
Technical scheme: in order to realize foregoing invention object, the technical solution used in the present invention is as follows:
The two mirror of a kind of thermal imaging video forest fires recognition system, comprises thermal imaging camera, video frequency pick-up head and processing unit; Described thermal imaging camera and video frequency pick-up head all carry out signal and communication with processing unit; Described processing unit has judged whether abnormal thermal source by the gray-scale value that detects graphic images, comprises thermal imaging analytic unit and video image analysis unit; Described processing unit calculates the angle point of thermal source image and video image, and by corners Matching and calculate the affine equation between thermal imaging camera and video frequency pick-up head, realize the mapping between graphic images and video image, can on video image, identify the position that abnormal thermal source is corresponding.
Described thermal imaging camera and video frequency pick-up head are all located on The Cloud Terrace.
The setting threshold of the gray-scale value of described graphic images is 600 degrees Celsius of corresponding gray-scale values.
Described thermal imaging analytic unit is for judging forest fires thermal source or vehicle thermal source according to the rhythm of the change of shape situation of thermal source image, light and shade and motion conditions, described video image analysis unit comprises Smoke Detection unit and fiery detecting unit, Smoke Detection unit is for judging the no generation that has smog according to the contrast metric of the extension movement feature of smog and smog, and whether fiery detecting unit has fire to occur for judging according to the variation rule of brightness, motion and light and shade.
The recognition methods of the two mirror of thermal imaging video forest fires recognition system: utilize the low speed inspection function of The Cloud Terrace to patrol and examine the forest zone of monitoring; Processing unit has judged whether abnormal thermal source by the gray-scale value that detects graphic images; When the temperature showing in graphic images exceedes 600 degrees Celsius, and region area is while being greater than 10 pixels, exits patrol mode, at thermograph image field, suspicious thermal source is analyzed, judge that suspicious thermal source is the probability of fire alarm, in video image territory, image is analyzed, judge the type of fire alarm.
The recognition methods of the two mirror of thermal imaging video forest fires recognition system, is specially:
1) image is processed and is completed by thermal imaging analytic unit and video image analysis unit;
2) before and after thermal imaging analytic unit, interval gathers multiple image, and extracts respectively the abnormal area of each two field picture;
3) judge in each frame mainly according to the change of shape situation of thermal source image, calculate the situation of change of the average gray value of each two field picture abnormal area by calculating the shape descriptor of each two field picture abnormal area, calculate the motion conditions of the abnormal thermal source of position judgment of the center of gravity of each two field picture abnormal area;
4) calculate the angle point of thermal imaging and video pictures, and mate, determine the mapping relations of pixel and video image pixel in graphic images;
5) video image is analyzed, realized the segmentation to type of alarm.
In step 3), when detection, the characteristics such as the maximum range value that the undulating quantity of the area of each frame abnormal area, front and back frame gray scale peak value, front and back frame abnormal area centre of gravity place are changed, as the input value of a support vector machine, are classified to abnormal area, and whether differentiate it is fire alarm.
In step 4), obtaining after the mapping relations of pixel and video image pixel in graphic images, user is on computers when playing image, and expression abnormal high temperature region, is convenient to staff and makes accurate judgement.
In step 5), video image analysis is specially: obtaining after the mapping relations of pixel and video image pixel in graphic images, the image of correspondence position in video image of the abnormal area in thermal imaging is analyzed; If the mean picture brightness value in this region is greater than the threshold value of setting, for naked light is reported to the police; Image to region top carries out optical flow analysis, if the image of this top, region there is optical flow field, and have the area image contrast of light stream to be less than adjacent domain, be pyrotechnics warning; Other situations are the warning of glowing.
The two mirror of this thermal imaging video forest fires recognition system, in the time of work, arranges The Cloud Terrace to work in the mode of patrolling and examining, and processing unit detects graphic images gray-scale value and judged whether abnormal thermal source.If note abnormalities, thermal source stops patrolling and examining, by graphic images, video image are carried out to image processing, and further judgement.Image is processed and is completed by thermal imaging analytic unit and video image analysis unit.Thermal imaging analytic unit is mainly the interference of the thermal source such as forest fires or vehicle according to the change of shape situation of thermal source image, the rhythm of light and shade, motion determination.Video image analysis unit is mainly divided into two large classes: Smoke Detection unit and fiery detecting unit.Smoke Detection unit is mainly the extension movement feature according to smog, and the contrast metric of smog etc. judges whether the generation of smog.Fire detecting unit is mainly to judge according to the variation rule of brightness, motion and light and shade.
Beneficial effect: compared with prior art, thermal imaging video of the present invention two mirror forest fires recognition system and recognition methods thereof, simple possible, the accuracy of identification is high, fails to report, rate of false alarm is low, can realize at the low speed middle detection forest fires that cruise, but not adopt common preset point mode to fix a point to detect, stop to detect blind area, there is good practicality, can produce good economic benefit and social effect.
Accompanying drawing explanation
Fig. 1 is the schematic diagram of the two mirror of thermal imaging video forest fires recognition system;
Fig. 2 is forest fires identification main flow chart;
Fig. 3 is thermal source graphical analysis process flow diagram.
Embodiment
Below in conjunction with accompanying drawing, the present invention is further illustrated.
As shown in Figure 1, the two mirror of thermal imaging video forest fires recognition system, major part comprises thermal imaging camera, video frequency pick-up head and processing unit, and thermal imaging camera and video frequency pick-up head all reach processing unit by image, and thermal imaging camera and video frequency pick-up head are all located on The Cloud Terrace.Processing unit comprises thermal imaging analytic unit and video image analysis unit; Thermal imaging analytic unit is for judging forest fires thermal source or vehicle thermal source according to the rhythm of the change of shape situation of thermal source image, light and shade and motion conditions; Video image analysis unit comprises Smoke Detection unit and fiery detecting unit, Smoke Detection unit is for judging the no generation that has smog according to the contrast metric of the extension movement feature of smog and smog, and whether fiery detecting unit has fire to occur for judging according to the variation rule of brightness, motion and light and shade.There is linear relationship in gray scale and the temperature of thermal imaging camera, can pass through in advance the calibration to thermal imaging camera, obtains 600 degrees Celsius of corresponding gray-scale values; In the time that the temperature value of thermal imaging camera mensuration is greater than 600 degrees Celsius, be judged as abnormal thermal source.
As shown in Figure 2, when system works, utilize the low speed inspection function of supervisory system to patrol and examine the forest zone of monitoring.This processing unit has judged whether abnormal thermal source by the gray-scale value that detects graphic images.When the temperature showing in graphic images exceedes 600 degrees Celsius, and when region area is greater than 10 pixels, exit patrol mode, at thermograph image field, suspicious thermal source is analyzed, judge that suspicious thermal source is the probability of fire alarm, in video image territory, image is analyzed, judge the type of fire alarm, as shown in Figure 3, be specially:
1) image is processed and is completed by thermal imaging analytic unit and video image analysis unit.
2) before and after thermal imaging analytic unit, interval gathers multiple image, and extracts respectively the abnormal area of each two field picture.
3) judge in each frame mainly according to the change of shape situation of thermal source image, calculate the situation of change of the average gray value of each two field picture abnormal area by calculating the shape descriptor of each two field picture abnormal area, calculate the motion conditions of the abnormal thermal source of position judgment of the center of gravity of each two field picture abnormal area.The feature of fire is that its shape is not often fixed, its temperature (gray-scale value that heat picture is corresponding) has obvious fluctuation, the position of abnormal area center of gravity not to have variation fast.And its shape of feature of the abnormal thermal source such as vehicle motor is fixed, its temperature does not have obvious fluctuation, between main combustion period, may there is large variation in the centre of gravity place of heat source region.When detection, the characteristics such as the maximum range value that the undulating quantity of the area of each frame abnormal area, front and back frame gray scale peak value, front and back frame abnormal area centre of gravity place are changed are as the input value of a support vector machine, whether abnormal area, differentiating it is fire alarm if being classified.
4) calculate the angle point of thermal imaging and video pictures, and mate, determine the mapping relations of pixel and video image pixel in graphic images.
5) video image is analyzed, realized the segmentation to type of alarm.Obtaining after the mapping relations of pixel and video image pixel in graphic images, the image of correspondence position in video image of the abnormal area in thermal imaging is analyzed.If the mean picture brightness value in this region is greater than the threshold value of setting, for naked light is reported to the police; Image to region top carries out optical flow analysis, if the image of this top, region there is optical flow field, and have the area image contrast of light stream to be less than adjacent domain, be pyrotechnics warning; Other situations are the warning of glowing.
Obtaining after the mapping relations of pixel and video image pixel in graphic images, user is on computers when playing image, and expression abnormal high temperature region, is convenient to staff and makes accurate judgement.
Claims (4)
1. the two mirror of a thermal imaging video forest fires recognition system, comprises thermal imaging camera, video frequency pick-up head and processing unit; Described thermal imaging camera and video frequency pick-up head all carry out signal and communication with processing unit; Described processing unit has judged whether abnormal thermal source by the gray-scale value that detects graphic images, comprises thermal imaging analytic unit and video image analysis unit; It is characterized in that: described processing unit calculates the angle point of thermal source image and video image, and by corners Matching and calculate the affine equation between thermal imaging camera and video frequency pick-up head, realize the mapping between graphic images and video image, can on video image, identify the position that abnormal thermal source is corresponding.
2. the two mirror of thermal imaging video according to claim 1 forest fires recognition system, is characterized in that: described thermal imaging camera and video frequency pick-up head are all located on The Cloud Terrace.
3. the two mirror of thermal imaging video according to claim 1 forest fires recognition system, is characterized in that: the setting threshold of the gray-scale value of described graphic images is 600 degrees Celsius of corresponding gray-scale values.
4. the two mirror of thermal imaging video according to claim 1 forest fires recognition system, it is characterized in that: described thermal imaging analytic unit is used for according to the change of shape situation of thermal source image, the rhythm of light and shade and motion conditions are judged forest fires thermal source or vehicle thermal source, described video image analysis unit comprises Smoke Detection unit and fiery detecting unit, Smoke Detection unit is for judging the no generation that has smog according to the contrast metric of the extension movement feature of smog and smog, fire detecting unit is used for according to brightness, whether the variation rule of motion and light and shade is judged has fire to occur.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210331547.0A CN102881106B (en) | 2012-09-10 | 2012-09-10 | Dual-detection forest fire identification system through thermal imaging video and identification method thereof |
| CN201410004366.6A CN103761826B (en) | 2012-09-10 | 2012-09-10 | The recognition methods of a kind of thermal imaging video two mirror forest fires recognition system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201210331547.0A CN102881106B (en) | 2012-09-10 | 2012-09-10 | Dual-detection forest fire identification system through thermal imaging video and identification method thereof |
Related Child Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410004366.6A Division CN103761826B (en) | 2012-09-10 | 2012-09-10 | The recognition methods of a kind of thermal imaging video two mirror forest fires recognition system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN102881106A CN102881106A (en) | 2013-01-16 |
| CN102881106B true CN102881106B (en) | 2014-07-02 |
Family
ID=47482413
Family Applications (2)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201210331547.0A Active CN102881106B (en) | 2012-09-10 | 2012-09-10 | Dual-detection forest fire identification system through thermal imaging video and identification method thereof |
| CN201410004366.6A Active CN103761826B (en) | 2012-09-10 | 2012-09-10 | The recognition methods of a kind of thermal imaging video two mirror forest fires recognition system |
Family Applications After (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201410004366.6A Active CN103761826B (en) | 2012-09-10 | 2012-09-10 | The recognition methods of a kind of thermal imaging video two mirror forest fires recognition system |
Country Status (1)
| Country | Link |
|---|---|
| CN (2) | CN102881106B (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111973914A (en) * | 2020-08-13 | 2020-11-24 | 深圳市朗驰欣创科技股份有限公司 | Transformer substation wheel type inspection robot with automatic fire extinguishing function |
Families Citing this family (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105450971A (en) * | 2014-08-15 | 2016-03-30 | 深圳Tcl新技术有限公司 | Privacy protection method and device of video call and television |
| CN107246913B (en) * | 2017-06-05 | 2019-11-08 | 山东神戎电子股份有限公司 | Based on the multiple forest fire protection detection method for differentiating mechanism |
| CN107481465A (en) * | 2017-08-21 | 2017-12-15 | 昆明理工大学 | A kind of aerial unmanned plane infrared monitoring method for early warning of forest adaptive cruise |
| CN108389352A (en) * | 2018-03-14 | 2018-08-10 | 青岛市光电工程技术研究院(中国科学院光电研究院青岛光电工程技术研究中心) | Fire source probing method and device |
| CN109445315A (en) * | 2018-08-21 | 2019-03-08 | 成都理工大学 | High-voltage test hall safety guard and method of controlling security |
| CN111539239B (en) * | 2019-01-22 | 2023-09-22 | 杭州海康微影传感科技有限公司 | Open fire detection method, device and storage medium |
| CN110390788A (en) * | 2019-08-21 | 2019-10-29 | 深圳云感物联网科技有限公司 | A kind of forest fire protection firework identification method and its system |
| CN110681097B (en) * | 2019-09-30 | 2021-04-16 | 张瑞祺 | Full-intelligent fire extinguishing system |
| CN111307291B (en) * | 2020-03-02 | 2021-04-20 | 武汉大学 | Surface temperature anomaly detection and positioning method, device and system based on unmanned aerial vehicle |
| CN112649095B (en) * | 2020-11-26 | 2022-09-09 | 江苏集萃未来城市应用技术研究所有限公司 | Large-range accurate temperature measurement system based on affine transformation and optical/infrared double lenses |
| CN113283276A (en) * | 2020-12-30 | 2021-08-20 | 四川弘和通讯有限公司 | Linkage thermal imaging self-learning fire point detection method and system |
| CN114792459A (en) * | 2021-01-25 | 2022-07-26 | 杭州申弘智能科技有限公司 | Remote fire monitoring management system and smoke detection method |
| CN113029878B (en) * | 2021-03-08 | 2023-11-14 | 湖南中冶长天节能环保技术有限公司 | Method for detecting high temperature of active carbon and giving alarm in grading manner |
| CN113177496A (en) * | 2021-05-10 | 2021-07-27 | 浙江大华技术股份有限公司 | Fire point detection method, device, equipment and storage medium |
| CN113554845B (en) * | 2021-06-25 | 2022-09-30 | 东莞市鑫泰仪器仪表有限公司 | Be used for forest fire prevention thermal imaging device |
| CN113506419B (en) * | 2021-06-30 | 2022-08-19 | 中标慧安信息技术股份有限公司 | Indoor safety state analysis method and system based on video data |
| CN117671914B (en) * | 2023-10-26 | 2024-06-04 | 广州成至智能机器科技有限公司 | Unmanned aerial vehicle multi-sensor forest fire identification method, device and system |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101175202A (en) * | 2007-10-31 | 2008-05-07 | 天津市亚安科技电子有限公司 | Video monitoring apparatus based on double optical band |
| CN101673448A (en) * | 2009-09-30 | 2010-03-17 | 青岛科恩锐通信息技术有限公司 | Method and system for detecting forest fire |
| CN101833838A (en) * | 2010-05-27 | 2010-09-15 | 王巍 | Large-range fire disaster analyzing and early warning system |
| CN102280005A (en) * | 2011-06-09 | 2011-12-14 | 广州飒特电力红外技术有限公司 | Early warning system for fire prevention of forest based on infrared thermal imaging technology and method |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20050162515A1 (en) * | 2000-10-24 | 2005-07-28 | Objectvideo, Inc. | Video surveillance system |
| CA2392410A1 (en) * | 2002-07-04 | 2004-01-04 | Dan Keith Andersen | Method of aerial monitoring of forests |
| US20050104771A1 (en) * | 2003-09-17 | 2005-05-19 | Spectrotech, Inc. | Airborne imaging spectrometry system and method |
| US8912978B2 (en) * | 2009-04-02 | 2014-12-16 | GM Global Technology Operations LLC | Dynamic vehicle system information on full windshield head-up display |
-
2012
- 2012-09-10 CN CN201210331547.0A patent/CN102881106B/en active Active
- 2012-09-10 CN CN201410004366.6A patent/CN103761826B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101175202A (en) * | 2007-10-31 | 2008-05-07 | 天津市亚安科技电子有限公司 | Video monitoring apparatus based on double optical band |
| CN101673448A (en) * | 2009-09-30 | 2010-03-17 | 青岛科恩锐通信息技术有限公司 | Method and system for detecting forest fire |
| CN101833838A (en) * | 2010-05-27 | 2010-09-15 | 王巍 | Large-range fire disaster analyzing and early warning system |
| CN102280005A (en) * | 2011-06-09 | 2011-12-14 | 广州飒特电力红外技术有限公司 | Early warning system for fire prevention of forest based on infrared thermal imaging technology and method |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111973914A (en) * | 2020-08-13 | 2020-11-24 | 深圳市朗驰欣创科技股份有限公司 | Transformer substation wheel type inspection robot with automatic fire extinguishing function |
Also Published As
| Publication number | Publication date |
|---|---|
| CN103761826A (en) | 2014-04-30 |
| CN103761826B (en) | 2016-03-30 |
| CN102881106A (en) | 2013-01-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN102881106B (en) | Dual-detection forest fire identification system through thermal imaging video and identification method thereof | |
| JP4705090B2 (en) | Smoke sensing device and method | |
| CN108734125B (en) | Smoking behavior identification method for open space | |
| US10133937B2 (en) | Crowd monitoring system | |
| CN105046868A (en) | Fire early warning method based on infrared thermal imager in narrow environment | |
| CN105512667A (en) | Method for fire identification through infrared and visible-light video image fusion | |
| JP5218906B2 (en) | Smoke detection device and smoke detection method | |
| CN104598895A (en) | Method and device for flame detection based on video image analysis | |
| CN111179279A (en) | Comprehensive flame detection method based on ultraviolet and binocular vision | |
| CN104410830A (en) | Device based on video smoke detection, and method based on video smoke detection | |
| CN109074713B (en) | Smoke detection device, method for detecting smoke of fire, and storage medium | |
| CN108399359A (en) | Fire detection method for early warning in real time under a kind of video sequence | |
| CN111008998A (en) | Automatic fire water monitor flame detection method based on binocular vision | |
| CN114386493A (en) | Fire detection method, system, device and medium based on flame vision virtualization | |
| CN101930540A (en) | Video-based multi-feature fusion flame detecting device and method | |
| JP4111660B2 (en) | Fire detection equipment | |
| CN109841028B (en) | Thermal infrared imager-based heat source detection method and system and storage medium | |
| CN101916380B (en) | Video-based device and method for detecting smog | |
| US20110205360A1 (en) | Supervising system for image | |
| CN202795630U (en) | Thermal imagery video double-identification forest fire recognition system | |
| CN102305603B (en) | Method for automatically detecting inclination of steel needle of injector by machine vision system | |
| CN101930541A (en) | Video-based flame detecting device and method | |
| KR20230064388A (en) | Composite image based fire detection system | |
| Jiayun | Real-time visual detection of early manmade fire | |
| Luo et al. | Effective dynamic object detecting for video-based forest fire smog recognition |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| C53 | Correction of patent for invention or patent application | ||
| CB03 | Change of inventor or designer information |
Inventor after: He Tiejun Inventor after: Chen Weilong Inventor after: Feng Xiaoqiang Inventor before: He Tiejun Inventor before: Feng Xiaoqiang |
|
| COR | Change of bibliographic data |
Free format text: CORRECT: INVENTOR; FROM: HE TIEJUN FENG XIAOQIANG TO: HE TIEJUN CHEN WEILONG FENG XIAOQIANG |
|
| C14 | Grant of patent or utility model | ||
| GR01 | Patent grant |