CN109688388A - A method of using the comprehensive real time monitoring of tunnel crusing robot - Google Patents
A method of using the comprehensive real time monitoring of tunnel crusing robot Download PDFInfo
- Publication number
- CN109688388A CN109688388A CN201910099459.4A CN201910099459A CN109688388A CN 109688388 A CN109688388 A CN 109688388A CN 201910099459 A CN201910099459 A CN 201910099459A CN 109688388 A CN109688388 A CN 109688388A
- Authority
- CN
- China
- Prior art keywords
- tunnel
- module
- crusing robot
- real time
- instruction
- 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
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/017—Detecting movement of traffic to be counted or controlled identifying vehicles
- G08G1/0175—Detecting movement of traffic to be counted or controlled identifying vehicles by photographing vehicles, e.g. when violating traffic rules
-
- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
- G08G1/054—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed photographing overspeeding vehicles
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/60—Control of cameras or camera modules
- H04N23/66—Remote control of cameras or camera parts, e.g. by remote control devices
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/80—Camera processing pipelines; Components thereof
Abstract
The invention discloses a kind of methods using the comprehensive real time monitoring of tunnel crusing robot, including step 1, transmission instruction；To conduct monitoring at all levels real-time in tunnel after step 2, the reception instruction of tunnel crusing robot, tunnel crusing robot realizes the comprehensive real time monitoring in tunnel by the modules carried, including illegal running, situations such as traffic accident, vehicle be crowded, road surface foreign matter, to reach the abnormal timely discovery with violation of law in tunnel and processing in time, reduce the supervision cost in tunnel, supervisory efficiency is improved, the traffic efficiency rate in tunnel is ensure that, improves the safety in tunnel.
Description
Technical field
The present invention relates to Tunnel testing technical field more particularly to a kind of use comprehensive real-time prisons of tunnel crusing robot
The method of control.
Background technique
Tunnel is an important location of road, carries most vehicle on road, the current safety in tunnel
Always one of the focus that pays attention to of traffic control department.Recently as the continuous development of urban construction, the continuous expansion of city size,
The continuous increase of traffic pressure！In Municipal engineering project, the quantity in urban transportation tunnel and high-speed transit tunnel and
Scale is constantly riseing, and tunnel operation security has attracted increasing attention！Illegal lane change in tunnel, hypervelocity, low speed, arbitrarily
The problems such as phenomena such as shedding rubbish frequently occurs, and is set to tunnel interior wall sweat can also cause traffic accident, therefore, in tunnel
Monitoring need biggish manpower and material resources, maintenance cost is higher, while manpower monitoring can not also be found in tunnel in time sometimes
Illegal and abnormal conditions cause many problems and violation of law not to handle in time, so that there are high safety is hidden in tunnel
Suffer from.
Summary of the invention
The present invention is in view of the shortcomings of the prior art, provide a kind of side using the comprehensive real time monitoring of tunnel crusing robot
Method, can effectively detect in tunnel includes the abnormal conditions such as violating the regulations, infiltration, while reminding traffic, guarantees tunnel safety,
Reduce cost of labor.
In order to solve the above technical problems, the present invention is addressed by the following technical programs: a kind of to use tunnel survey monitor
The method of the comprehensive real time monitoring of device people includes the following steps: step 1, sends instruction；Step 2, tunnel crusing robot receive
To conduct monitoring at all levels real-time in tunnel after instruction.
In above scheme, the polling module includes main control module, voice module, communication module, power module, movement mould
Block, monitoring modular, holder.
In above scheme, the monitoring modular includes 3D laser radar, the outer imaging device of heat, phase unit, capture machine.
In above scheme, in the step 1, sending instruction includes that the main control module in polling module is sent to motion module
Movement instruction, and foreign bodies detection instruction, violation snap-shooting instruction, infiltration detection instruction and high-definition image are sent to monitoring modular
Acquisition instructions.
In above scheme, in the step 2, the motion module drives tunnel inspection machine after receiving movement instruction
People runs along the track that is laid in tunnel, and each module starts to act, to completing comprehensive real time monitoring in tunnel.
In above scheme, the foreign bodies detection instruction is executed the following steps are included: monitoring data are collected: 3D laser radar
To the lower section pavement monitoring of process, and obtain the original point cloud data in road environment；Monitor situation analysis；To being obtained in step 2
The original point cloud data taken processes, and obtains data model, and judge whether there is exception information, and confirm exception information situation；
The response of inspection result: it is responded according to exception information.
In above scheme, executes the violation snap-shooting instruction and completed by capture machine.
In above scheme, the infiltration detection instruction is executed the following steps are included: persistently taking figure: in thermal imaging device
Thermal imaging system is persistently persistently taken figure to the metope of process when with inspection machine human action；Image conversion processing: it will take
The infrared image obtained convert and binary conversion treatment, and establishes gray scale threshold block；Image analysis: it is detected whether by fault block value
In the presence of infiltration region；Infiltration alarm: if being detected as seeping water, sending a signal to main control module, is referred to by main control module by sending
It enables to operating side and voice module, sounds an alarm.
In above scheme, the first calibration that the high-definition image acquisition instructions include the following steps: inspection device is executed；
Main control module in inspection device sends image capture instruction to high definition image-forming assembly；The initialization of high definition image-forming assembly；High definition at
As component adopts figure；High definition image-forming assembly adopts figure post-processing；Export panoramic picture.
Compared with prior art, the invention has the following beneficial effects: tunnel crusing robots to pass through each mould of carrying
Situations such as block realizes the comprehensive real time monitoring in tunnel, including illegal running, traffic accident, vehicle are crowded, road surface foreign matter, to reach
To the abnormal timely discovery with violation of law in tunnel and processing in time, the supervision cost in tunnel is reduced, supervisory efficiency is improved,
The traffic efficiency rate that ensure that tunnel, improves the safety in tunnel.
Detailed description of the invention
Fig. 1 is work flow diagram of the present invention.
Specific embodiment
Below with reference to Fig. 1, present invention is further described in detail with specific embodiment.
A method of using the comprehensive real time monitoring of tunnel crusing robot, including the following steps: that step 1, transmission refer to
It enables；After the booting of tunnel crusing robot, starting self-test, the main control module in polling module sends movement instruction to motion module,
Foreign bodies detection instruction, violation snap-shooting instruction, infiltration detection instruction and high-definition image acquisition instructions, inspection are sent to monitoring modular
Module includes main control module, voice module, communication module, power module, motion module, monitoring modular, holder, the monitoring mould
Block includes 3D laser radar, the outer imaging device of heat, phase unit, capture machine；Polling module built in step 2, tunnel crusing robot
Analysis receives instruction and to conduct monitoring at all levels real-time in tunnel.
When receiving is foreign bodies detection monitoring instruction, 3D laser radar obtains road to the lower section pavement monitoring of process
Original point cloud data in face ring border；Pose transformation and cluster segmentation are carried out to collected original point cloud data, by road surface side
Point cloud data other than edge filters out, and obtains the point cloud data for there was only information of road surface；Secondly, the information processing built in 3D laser radar
Device to treated, analyze by point cloud data, when identification data model, the concrete model feature that 3D laser radar can will identify that
It is transmitted to the trained model data comparison in deep learning module in advance, in tunnel, bicycle and pedestrian are not allow
It appears in tunnel, therefore, in deep learning, therefore bicycle and pedestrian, work as identification by as foreign matter model classifications
Data model be bicycle and pedestrian when, can model data comparison after directly be determined as foreign matter；When the foreign matter of detection is certainly
Driving or when pedestrian, the alarm switch triggering in monitoring modular, while alarm signal is sent to main control module by monitoring modular, it is main
It controls module communication control module and sends alarm signal to backstage manipulation end, send play signal to voice module, play pre- poster
Sound, perhaps remotely propagandas directed to communicate prompting personnel by voice module or cyclist leaves, and alarm is closed after leaving, is such as repeatedly propagandaed directed to communicate
Personnel or bicycle also do not leave, then treatment people to scene is sent to be handled, and alarm is closed after being disposed；If at identification
Data model be automobile when, the car model that 3D laser radar can will identify that is transmitted to instructs in deep learning module in advance
In the model data perfected, 3D laser radar persistently tracks the speed of vehicle driving, when car speeds all in detection zone are low
When 3~6km/h, then determine the abnormal conditions for traffic congestion；Alarm switch triggering in monitoring modular, while monitoring modular will be reported
Alert signal is sent to main control module, and main control module communication control module sends alarm signal to backstage manipulation end, to voice module
Play signal is sent, early warning voice is played, while holder shoots foreign matter point, related personnel is waited to carry out traffic guidance or scene
Processing；If the data model at identification is indefinite object, indefinite object model can be transmitted in advance by 3D laser radar
In deep learning module in trained model data, 3D laser radar persistently tracks the speed of indefinite object, works as speed
Lower than setting threshold value when, be determined as foreign matter, be 0~5km/h during threshold；When the foreign matter of detection is indefinite object, root
According to the automatic rotary platform camera of indefinite object space, foreign matter point is shot, foreign matter is checked according to shooting situation in remote control end
Details when foreign matter is lesser object, and will not affect greatly traffic, then long-range to close alarm, inspection device
Continue along guide rail inspection；If foreign matter is larger object, there are security risks for judgement, and will cause and seriously affect to traffic, then
Lasting alarm, and treatment people to scene is sent to be handled, alarm is closed after being disposed.
When receiving violation snap-shooting monitoring instruction, capture machine judges whether scan vehicle by built-in defined parameters
Meeting hypervelocity, illegal lane change, overtakes other vehicles, information is fed back the processing module in main capture machine if meeting by illegal parking parameter,
Processing module will be sent to main control module after information processing, be worked by main control module control capture machine and holder, capture machine carries out
Illegal photo is captured, holder starts to record illicit video evidence.
When receive infiltration detection instruction when: the thermal imaging system in thermal imaging device when with inspection machine human action,
Figure is persistently persistently taken to the metope of process；First the infrared image of acquirement is carried out to turn grayscale image, and binary conversion treatment, later
A gray threshold block is established, according to the data setting of acquirement, it will be slided the size of threshold block line by line, be examined when sliding into somewhere
When measuring abnormal, the sliding of more neighborhoods is carried out to determine whether for erroneous detection, if the neighborhood exception numerical value of this abnormal area reaches pre-
Setting parameter value is then determined as there is infiltration dewy phenomenon at this, then sends a signal to main control module, by main control module by sending instruction
To operating side and voice module, sound an alarm；If not up to preset parameter value continues to slide, until to most footline
The detection of least significant end, i.e. entire image finishes, no abnormal region, then continues to remove the reinspection of laying equal stress on of a figure and survey.
When receiving the high-definition image acquisition instructions: when inspection device install starting for the first time, needing to inspection dress
The first calibration set, first production gridiron pattern scaling board, are then fixed on phase in phase unit for the gridiron pattern scaling board made
The overlapping region of machine adjacent rotated position visual field；Figure is adopted in calibration, adopts figure respectively in the fixed region of above-mentioned gridiron pattern scaling board,
First image for being suitble to splicing is chosen, and determines the visual field being overlapped in the image, it, can be according to determining when turntable steering engine rotates
The visual field of overlapping carries out the calculating of rotational angle, takes second to scheme and determine the visual field being overlapped in the image, weight after rotateing in place
It is new to calculate rotational angle, it continues to rotate and removes a figure, when turntable steering engine rotate in place, focusing steering engine will do it rotation, according to
The clarity of camera shooting picture is compared, and stops in the clearest position of image；Homography matrix is calculated, by that will acquire
Image pre-processed after do Corner Detection, homography matrix H is calculated by the angular coordinates of two images, is calculated by H
The pixel focal length f and the transformed matrix H * M of translation of phase unit, and the image coordinate after perspective transform is calculated, to obtain
Translation vector L is taken, and these parameters are saved to high definition image-forming module.
After high definition image-forming assembly receives image capture instruction, position when being demarcated by preliminary examination will be in high definition image-forming assembly
Turntable steering engine go to the position of shooting, while adjust in high definition image-forming assembly focus steering engine on phase unit pixel；High definition at
As the phase unit in component adopts figure, it is necessary first to the quantity N for adopting figure is set, so that program can enter after acquisition
Next step, if when N=8, during picture collection, high definition image-forming module can continue detection and adopt whether figure quantity reaches default
Value 8, if not up to, phase unit meeting continuous collecting, until the detection of high-definition camera module reaches preset value termination；Adopting figure process
In, in order to reduce the cumulative errors as caused by the constraint between multiple images, picture obtained by calibrating is utilized to acquired image
Plain focal length f carries out cylindrical surface projecting preconditioning, then using original image is covered after bilinear interpolation deburring, until adopting figure
Terminate, high definition image-forming module directly reads the image sequence after projective transformation and deburring, obtains using in calibration
Translation transformation after matrix H * M carry out perspective transform, obtained translation vector L carrys out stitching image when recycling calibration, most laggard
Row image co-registration goes to the gap between processing stitching image, obtains stitching image, stitching image after the completion is imaged through high definition
Module exports to high definition camera device and is connected to server, so as to subsequent operation.
Protection scope of the present invention includes but is not limited to embodiment of above, and protection scope of the present invention is with claims
Subject to, replacement, deformation, the improvement that those skilled in the art that any pair of this technology is made is readily apparent that each fall within of the invention
Protection scope.
Claims (9)
1. a kind of method using the comprehensive real time monitoring of tunnel crusing robot, which comprises the steps of: step
1, instruction is sent；To conduct monitoring at all levels real-time in tunnel after step 2, the reception instruction of tunnel crusing robot.
2. a kind of method using the comprehensive real time monitoring of tunnel crusing robot according to claim 1, feature exist
In the polling module includes main control module, voice module, communication module, power module, motion module, monitoring modular, cloud
Platform.
3. a kind of method using the comprehensive real time monitoring of tunnel crusing robot according to claim 2, feature exist
In the monitoring modular includes 3D laser radar, the outer imaging device of heat, high definition image-forming assembly, capture machine.
4. a kind of method using the comprehensive real time monitoring of tunnel crusing robot according to claim 3, feature exist
In in the step 1, sending instruction includes that the main control module in polling module sends movement instruction, Yi Jixiang to motion module
Monitoring modular sends foreign bodies detection instruction, violation snap-shooting instruction, infiltration detection instruction and high-definition image acquisition instructions.
5. a kind of method using the comprehensive real time monitoring of tunnel crusing robot according to claim 4, feature exist
In in the step 2, the motion module, which receives, drives after movement instruction tunnel crusing robot along being laid in tunnel
Track operation, each module starts to act, to completing comprehensive real time monitoring in tunnel.
6. a kind of method using the comprehensive real time monitoring of tunnel crusing robot according to claim 4, feature exist
In executing the foreign bodies detection instruction the following steps are included: monitoring data are collected: lower section road surface of the 3D laser radar to process
Monitoring, and obtain the original point cloud data in road environment；Monitor situation analysis；To the original point cloud data obtained in step 2
It processes, obtains data model, and judge whether there is exception information, and confirm exception information situation；The response of inspection result: according to
Exception information responds.
7. a kind of method using the comprehensive real time monitoring of tunnel crusing robot according to claim 4, feature exist
In executing the violation snap-shooting instruction and pass through capture machine completion.
8. a kind of method using the comprehensive real time monitoring of tunnel crusing robot according to claim 4, feature exist
In executing the infiltration detection instruction the following steps are included: persistently taking figure: thermal imaging system in thermal imaging device is with patrolling
When examining robot motion, figure is persistently persistently taken to the metope of process；Image conversion processing: the infrared image of acquirement is carried out
Simultaneously binary conversion treatment is converted, and establishes gray scale threshold block；Image analysis: detect whether there is infiltration region by fault block value；It seeps
Water alarm: if being detected as seeping water, main control module is sent a signal to, by main control module by sending a command to operating side and language
Sound module, sounds an alarm.
9. a kind of method using the comprehensive real time monitoring of tunnel crusing robot according to claim 4, feature exist
In executing the first calibration that the high-definition image acquisition instructions include the following steps: inspection device；Master control in inspection device
Module sends image capture instruction to high definition image-forming assembly；The initialization of high definition image-forming assembly；High definition image-forming assembly adopts figure；High definition at
As component adopts figure post-processing；Export panoramic picture.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910099459.4A CN109688388B (en) | 2019-01-31 | 2019-01-31 | All-dimensional real-time monitoring method using tunnel inspection robot |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910099459.4A CN109688388B (en) | 2019-01-31 | 2019-01-31 | All-dimensional real-time monitoring method using tunnel inspection robot |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109688388A true CN109688388A (en) | 2019-04-26 |
| CN109688388B CN109688388B (en) | 2021-06-25 |
Family
ID=66195402
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910099459.4A Active CN109688388B (en) | 2019-01-31 | 2019-01-31 | All-dimensional real-time monitoring method using tunnel inspection robot |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109688388B (en) |
Cited By (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110278417A (en) * | 2019-07-25 | 2019-09-24 | 上海莫吉娜智能信息科技有限公司 | Monitoring device method for rapidly positioning and system based on millimetre-wave radar |
| CN110400468A (en) * | 2019-08-27 | 2019-11-01 | 宁波诠航机械科技有限公司 | A kind of low speed in long tunnel is with shooting system |
| CN110847972A (en) * | 2019-11-26 | 2020-02-28 | 成都轨道建设管理有限公司 | Tunnel safety detection early warning system for subway construction |
| CN111785084A (en) * | 2020-05-27 | 2020-10-16 | 诠航科技有限公司 | Tunnel patrol machine |
| CN111785081A (en) * | 2020-05-27 | 2020-10-16 | 诠航科技有限公司 | Guard bar patrol machine |
| CN111785079A (en) * | 2020-05-27 | 2020-10-16 | 诠航科技有限公司 | Traffic early warning system based on tunnel patrol machine |
| CN111785080A (en) * | 2020-05-27 | 2020-10-16 | 诠航科技有限公司 | Intelligent traffic early warning system and early warning method |
| CN112330930A (en) * | 2020-09-09 | 2021-02-05 | 北京潞电电气设备有限公司 | Urban tunnel traffic monitoring method, system and platform |
| CN112330938A (en) * | 2020-09-09 | 2021-02-05 | 北京潞电电气设备有限公司 | Traffic tunnel removes patrols and examines robot |
| CN112367478A (en) * | 2020-09-09 | 2021-02-12 | 北京潞电电气设备有限公司 | Tunnel robot panoramic image processing method and device |
| CN113012436A (en) * | 2019-12-18 | 2021-06-22 | 杭州海康威视数字技术股份有限公司 | Road monitoring method and device and electronic equipment |
| CN114187676A (en) * | 2021-12-02 | 2022-03-15 | 智慧起源机器人(苏州)有限公司 | Inspection method, device, equipment, system and storage medium |
| CN115273474A (en) * | 2022-08-02 | 2022-11-01 | 浙江安易信科技有限公司 | RPA patrols and examines robot and patrols and examines management system based on artificial intelligence |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103309324A (en) * | 2013-06-05 | 2013-09-18 | 广州供电局有限公司 | Mobile tunnel environment inspection equipment |
| WO2014174014A1 (en) * | 2013-04-24 | 2014-10-30 | Schöttler Markus | Apparatus and method for optically detecting flow movements in liquid and/or gaseous media |
| CN104809758A (en) * | 2015-05-08 | 2015-07-29 | 山东康威通信技术股份有限公司 | In-situ tunnel inspection and equipment control method based on three-dimensional real-scene roaming technique |
| CN106050309A (en) * | 2016-08-09 | 2016-10-26 | 北京铁路局北京科学技术研究所 | Monitoring and alarming system and method for falling object in tunnel |
| CN205721367U (en) * | 2016-05-03 | 2016-11-23 | 袁孝红 | Electric power tunnel intelligent inspection robot |
| CN106572325A (en) * | 2015-10-13 | 2017-04-19 | 上海宝信软件股份有限公司 | Virtual-reality-technology-based tunnel monitoring equipment inspection system |
| CN106679813A (en) * | 2016-11-21 | 2017-05-17 | 深圳供电局有限公司 | Intelligent detection system for tunnel power equipment |
| CN206195232U (en) * | 2016-11-21 | 2017-05-24 | 深圳供电局有限公司 | Tunnel intelligence is hung rail and is patrolled and examined monitored control system of robot |
| CN107202793A (en) * | 2017-05-16 | 2017-09-26 | 镇江市建科工程质量检测中心有限公司 | A kind of detecting system and method for detecting external wall mass defect |
| CN107703559A (en) * | 2017-09-07 | 2018-02-16 | 国网浙江省电力公司宁波供电公司 | Seep water infrared detecting device for a kind of cable tunnel |
| CN108107444A (en) * | 2017-12-28 | 2018-06-01 | 国网黑龙江省电力有限公司检修公司 | Substation's method for recognizing impurities based on laser data |
| CN108248635A (en) * | 2018-02-05 | 2018-07-06 | 刘春梅 | A kind of intelligent checking system for rail tunnel |
-
2019
- 2019-01-31 CN CN201910099459.4A patent/CN109688388B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2014174014A1 (en) * | 2013-04-24 | 2014-10-30 | Schöttler Markus | Apparatus and method for optically detecting flow movements in liquid and/or gaseous media |
| CN103309324A (en) * | 2013-06-05 | 2013-09-18 | 广州供电局有限公司 | Mobile tunnel environment inspection equipment |
| CN104809758A (en) * | 2015-05-08 | 2015-07-29 | 山东康威通信技术股份有限公司 | In-situ tunnel inspection and equipment control method based on three-dimensional real-scene roaming technique |
| CN106572325A (en) * | 2015-10-13 | 2017-04-19 | 上海宝信软件股份有限公司 | Virtual-reality-technology-based tunnel monitoring equipment inspection system |
| CN205721367U (en) * | 2016-05-03 | 2016-11-23 | 袁孝红 | Electric power tunnel intelligent inspection robot |
| CN106050309A (en) * | 2016-08-09 | 2016-10-26 | 北京铁路局北京科学技术研究所 | Monitoring and alarming system and method for falling object in tunnel |
| CN106679813A (en) * | 2016-11-21 | 2017-05-17 | 深圳供电局有限公司 | Intelligent detection system for tunnel power equipment |
| CN206195232U (en) * | 2016-11-21 | 2017-05-24 | 深圳供电局有限公司 | Tunnel intelligence is hung rail and is patrolled and examined monitored control system of robot |
| CN107202793A (en) * | 2017-05-16 | 2017-09-26 | 镇江市建科工程质量检测中心有限公司 | A kind of detecting system and method for detecting external wall mass defect |
| CN107703559A (en) * | 2017-09-07 | 2018-02-16 | 国网浙江省电力公司宁波供电公司 | Seep water infrared detecting device for a kind of cable tunnel |
| CN108107444A (en) * | 2017-12-28 | 2018-06-01 | 国网黑龙江省电力有限公司检修公司 | Substation's method for recognizing impurities based on laser data |
| CN108248635A (en) * | 2018-02-05 | 2018-07-06 | 刘春梅 | A kind of intelligent checking system for rail tunnel |
Cited By (15)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110278417A (en) * | 2019-07-25 | 2019-09-24 | 上海莫吉娜智能信息科技有限公司 | Monitoring device method for rapidly positioning and system based on millimetre-wave radar |
| CN110400468A (en) * | 2019-08-27 | 2019-11-01 | 宁波诠航机械科技有限公司 | A kind of low speed in long tunnel is with shooting system |
| CN110400468B (en) * | 2019-08-27 | 2021-08-31 | 诠航科技有限公司 | Low-speed in long tunnel is with clapping system |
| CN110847972A (en) * | 2019-11-26 | 2020-02-28 | 成都轨道建设管理有限公司 | Tunnel safety detection early warning system for subway construction |
| CN110847972B (en) * | 2019-11-26 | 2021-12-17 | 成都轨道建设管理有限公司 | Tunnel safety detection early warning system for subway construction |
| CN113012436A (en) * | 2019-12-18 | 2021-06-22 | 杭州海康威视数字技术股份有限公司 | Road monitoring method and device and electronic equipment |
| CN111785080A (en) * | 2020-05-27 | 2020-10-16 | 诠航科技有限公司 | Intelligent traffic early warning system and early warning method |
| CN111785079A (en) * | 2020-05-27 | 2020-10-16 | 诠航科技有限公司 | Traffic early warning system based on tunnel patrol machine |
| CN111785081A (en) * | 2020-05-27 | 2020-10-16 | 诠航科技有限公司 | Guard bar patrol machine |
| CN111785084A (en) * | 2020-05-27 | 2020-10-16 | 诠航科技有限公司 | Tunnel patrol machine |
| CN112330930A (en) * | 2020-09-09 | 2021-02-05 | 北京潞电电气设备有限公司 | Urban tunnel traffic monitoring method, system and platform |
| CN112330938A (en) * | 2020-09-09 | 2021-02-05 | 北京潞电电气设备有限公司 | Traffic tunnel removes patrols and examines robot |
| CN112367478A (en) * | 2020-09-09 | 2021-02-12 | 北京潞电电气设备有限公司 | Tunnel robot panoramic image processing method and device |
| CN114187676A (en) * | 2021-12-02 | 2022-03-15 | 智慧起源机器人(苏州)有限公司 | Inspection method, device, equipment, system and storage medium |
| CN115273474A (en) * | 2022-08-02 | 2022-11-01 | 浙江安易信科技有限公司 | RPA patrols and examines robot and patrols and examines management system based on artificial intelligence |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109688388B (en) | 2021-06-25 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109688388A (en) | A method of using the comprehensive real time monitoring of tunnel crusing robot | |
| CN101789177B (en) | Device and method for detecting and tracking vehicles crossing and pressing the yellow line and for capturing vehicle information | |
| CN103927878B (en) | A kind of automatic shooting device for parking offense and automatically grasp shoot method | |
| CN106940884B (en) | Motor train unit operation fault image detection system containing depth information and detection method | |
| CN108091142A (en) | For vehicle illegal activities Tracking Recognition under highway large scene and the method captured automatically | |
| CN109797691A (en) | Unmanned sweeper and its travelling-crane method | |
| CN106652551A (en) | Parking stall detection method and device | |
| CN109212513A (en) | Multiple target between radar data transmitting, data fusion and localization method is continuously tracked | |
| CN102759347B (en) | Online in-process quality control device and method for high-speed rail contact networks and composed high-speed rail contact network detection system thereof | |
| CN104464290A (en) | Road traffic parameter collecting and rule violation snapshot system based on embedded double-core chip | |
| CN108491758A (en) | A kind of track detection method and robot | |
| CN103455144A (en) | Vehicle-mounted man-machine interaction system and method | |
| CN107454296A (en) | A kind of eight camera pan police vehicles are downloaded from dynamic apparatus for obtaining evidence and method | |
| CN202422425U (en) | Video-detection-based intelligent signal control system for crossing | |
| CN110126820A (en) | Automated parking system, method of parking and vehicle | |
| CN102496285A (en) | Method for determining red-light running of vehicles at intersection based on video detection and signal control system | |
| KR101032495B1 (en) | Multi-function detecting system of illegally parked vehicles using digital ptz technique and method of detecting thereof | |
| CN113569914B (en) | Point cloud data fusion type power transmission line inspection method and system | |
| KR100820952B1 (en) | Detecting method at automatic police enforcement system of illegal-stopping and parking vehicle using single camera and system thereof | |
| CN104047248A (en) | Combined type rail pavement automatic cleaning vehicle system | |
| CN104036640A (en) | Panoramic image acquisition device and panoramic image acquisition method | |
| CN106683400A (en) | Method and a system for obtaining evidence by capturing vehicles at traffic crossing under panoramic video detection | |
| CN107798306A (en) | A kind of intelligent driving and remote visualization intelligence loss assessment system and method | |
| CN206074832U (en) | A kind of railcar roof pantograph foreign matter detection system | |
| CN104378539A (en) | Scene-adaptive video structuring semantic extraction camera and method thereof |
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 | ||
| CB02 | Change of applicant information |
Address after: Jiangshan Zhen Xia Shi Cun, Yinzhou District, Ningbo City, Zhejiang Province, 315000 Applicant after: Quanhang Technology Co.,Ltd. Address before: 315000 Jinxi Road, Nordic Industrial Zone, Zhenhai District, Ningbo City, Zhejiang Province Applicant before: NINGBO QUANHANG MACHINERY TECHNOLOGY Co.,Ltd. |
|
| CB02 | Change of applicant information | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |