CN105262989B - The aerial unmanned plane of railway line is patrolled and real time image collection transmission method automatically - Google Patents
The aerial unmanned plane of railway line is patrolled and real time image collection transmission method automatically Download PDFInfo
- Publication number
- CN105262989B CN105262989B CN201510644021.1A CN201510644021A CN105262989B CN 105262989 B CN105262989 B CN 105262989B CN 201510644021 A CN201510644021 A CN 201510644021A CN 105262989 B CN105262989 B CN 105262989B
- Authority
- CN
- China
- Prior art keywords
- node
- image
- location data
- program
- parameter
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Landscapes
- Closed-Circuit Television Systems (AREA)
Abstract
The invention discloses a kind of aerial unmanned planes of railway line to patrol and real time image collection transmission method automatically, this method can plan inspection flight path automatically, support vision guided navigation, image recognition and avoidance, parameter can be suitably changed in the case where not influenced by propagation delay, thus image recognition rate is improved, satellite communication network pattern is merged with conventional communication mode, the high speed that can solve large capacity image data exchanges, and has higher safety.
Description
Technical field
The present invention relates to unmanned planes to investigate field, and in particular to the aerial unmanned plane of railway line automatically with realtime graphic adopt by inspection
Collect transmission method.
Background technology
Railway line inspection is the groundwork of railway line daily maintenance, and inspection mode can be divided into artificial inspection, someone goes straight up to
Machine is patrolled and unmanned plane inspection.Although artificial inspection is most common inspection mode, always exist that efficiency is relatively slow, is bullied
The deficiencies of geographical environment restricts is waited, machine patrols mode and is just widely studied and applies, especially the safe and efficient characteristic of unmanned plane inspection,
The aerial unmanned plane of railway line has increasing application value.
The mission planning for the aerial unmanned plane inspection of railway line mostly uses greatly manually planning mode, Ci Zhongfang at present
Although formula ensures the flight safety of unmanned plane, but less efficient, cannot be satisfied the needs of extensive unmanned plane inspection, simultaneously
Manual planning mode is difficult to realize optimum programming in big region.The mission planning of UAV Intelligent line walking is firstly the need of to entire iron
All important nodes in diatom region build a kind of data structure, to carry out intelligent algorithm planning.
The passback of existing investigation video image, most of is to be based on analog video signal, fogging image, it is also necessary to one
The analog video signal of high-definition camera is actually just overlapped by a equipment for being known as IOSD, this equipment with flight parameter
Ground is returned, thus while what is stored on aircraft is high-definition image, but the image for passing back to ground is to be superimposed state of flight ginseng
Several analog images, and people generally require to see the high-definition digital image of aircraft photographs in real time.
UAV system includes that unmanned plane body platform, mission payload and data are wirelessly transferred three parts.Unmanned plane
The key that video data transmission application is realized is wireless transmission link means.Current Radio Transmission Technology mainly have including with
Lower technology：3G network (CDMA2000, WCDMA, TD-SCDMA), 4G (TD-LTE and FDD-LTE) network, WLAN
(WIFI), satellite, microwave etc..
Satellite and microwave technology are the traditional means of wireless video transmission, and the great advantage of communication technology of satellite is service
Range is wide, powerful, using flexible, is not influenced by geographical environment and other external environments, especially not by external electromagnetic
The influence of environment.But both technical costs are high, expensive initial expenditure of construction and communication fee often make one to hope and
Step back, can not be widely applied.
Invention content
A kind of aerial unmanned plane of railway line of present invention offer is patrolled and real time image collection transmission method automatically, this method energy
Enough automatic planning inspection flight paths, support vision guided navigation, image recognition and avoidance, can be in the case where not influenced by propagation delay
Parameter is suitably changed, image recognition rate is thus improved, satellite communication network pattern is merged with conventional communication mode,
The high speed that can solve large capacity image data exchanges, and has higher safety.
To achieve the goals above, the present invention provides the aerial unmanned plane of railway line inspection and real time image collection transmission automatically
Method, this method specifically comprise the following steps：
S1. inspection layout of roads module planning inspection route；
S2. central processing module starts monitoring programme, reads and execute above-mentioned intelligent planning circuit, the satellite navigation mould
Block starts GPS navigation program；
S3. high definition high power zoom motion video camera acquires video image, generator terminal image procossing according to the track of monitoring programme
Module handles image；
S4. the wireless transmission of picture signal is completed in video image wireless transmitter module and video image receiving module, cooperation
And reception；
S5. central site image processing module handles the picture signal received, and is shown on display terminal.
Preferably, in step sl, specifically comprise the following steps：
S11. unitary nonlinear regression prediction technique is used, railway track Node distribution is predicted, generates several
Node line, every node line cover several nodes；
In step S11, three-dimensional space model is simplified to two-dimensional spatial model first, it is pre- using unitary nonlinear regression
Survey method predicts railway track Node distribution；Prediction mode uses confidence interval mode, according to history node data
(response variable) is predicted and is judged to new input data (explanatory variable).
S12. the critical condition for utilizing Node distribution, makes several node lines be connected to form circuit connected graph；Wherein institute
Stating critical condition includes：Scissors crossing situation, the nearlyr parallelly distribute on situation of a plurality of circuit distance, node turn to situation, node point
Branch situation；
In step S12, occur special circumstances if reaching Node distribution and reach critical condition, carries out critical types and sentence
It is disconnected, and handled；The critical type of Node distribution is divided into following several：
Scissors crossing situation：Occur multiple points in forecast interval section, has exceeded setting number of nodes, and there are crosspoints；
The nearlyr parallelly distribute on situation of a plurality of circuit distance：Occur multiple points in forecast interval section, have exceeded setting number of nodes,
But without crosspoint；
Node turns to situation：Compared with predictive equation, occurs unique inflection point in forecast interval；
Node branch situation：Compared with predictive equation, occur multiple inflection points in forecast interval.
S13. it builds railway track inspection planning chart and stores.
Step S11 specifically comprises the following steps：
S111. dimension-reduction treatment：Dimension-reduction treatment is carried out to three-dimensional nodes geographical coordinate and is converted to two-dimensional coordinate；Set original A sections
Point three-dimensional coordinate is (xt,yt,zt),xtIndicate Nodes Three-dimensional space longitude coordinate, ytIndicate node latitude coordinate, ztIndicate node
Residing height above sea level, then A node coordinates are (x after dimensionality reductiont,yt)；
The establishment of S112 regression equations：One-variable linear regression prediction model formula applied to transmission line of electricity mission planning is such as
Under：
X in formulatIndicate t moment node longitude coordinate,Indicate t moment estimated latitude coordinate；
S113. it fetches and returns prediction step for N, obtain parameter a in regression equation, the solution equation of b is as follows：
Wherein,N is prediction moving step length；Since the distance between two base nodes are even up to a hundred at tens meters
Rice differs, and majority of case is formed by continuous more bases with node can near linear section.
Preferably, in step S113, step-length N is 5 meters -10 meters.
Preferably, step S11 further comprises step 114：Forecast interval is built, due to bent determined by actual node
There are a degree of deviations for line equation and predictive equation, therefore have carried out interval prediction to Y value, that is, build the prediction of average value
Section sets significance a according to Node distribution situation, and the confidence level for calculating Y average values is the forecast interval of 1-a.
Preferably, step S13 specifically comprises the following steps：
S131. node matrix equation, wherein ranks coordinate representation node number are established, matrix data is node geo-location information；
Node is divided into two types according to prediction result：Important node and insignificant node；Wherein important node includes circuit start-stop
Node and crossover node；Insignificant node is the internal node for only belonging to uniline；
S132. for important node, important node adjacency list is built；
S133. for insignificant node, matrix structure storage, the affiliated circuit of row matrix coordinate representation, row coordinates table are carried out
Show node number.
In step S132, for important node, since node data amount is larger, it is contemplated that algorithm memory space and algorithm effect
Rate, using Linked Storage Structure-adjacency list.
Preferably, in step s 2, monitoring programme includes at application layer program, real-time task scheduler and external interrupt
Manage program, hardware initialization program, hardware drive program, CAN communication protocol procedure, LAN (TCP/IP) communication protocol program, institute
It states application layer program to connect with real-time task scheduler and external interrupt processor, the real-time task scheduler and outer
Portion's interrupt handling routine is connect with hardware initialization program, and the hardware initialization program is connect with hardware drive program.
Preferably, the application layer program includes Applied layer interface program, power management and electric quantity monitoring program, flying refers to
Show lamp control program, security control program, visual spatial attention program, flight tracking control program, augmentation control program, remote control decoding journey
Sequence, communication processing program.
Preferably, in step s3, one or more of following steps can be used to handle video image：
S31：Data receipt unit reception includes image coded data and the image encoding stream of parameter；
S32：Index based on instruction image recognition accuracy changes parameter；
S33：Environmental information based on image received device changes parameter；
S34：Change parameter according to operating condition；
S35：Change the parameter of deblocking filter；
S36：Change quantization parameter；
S37：Change orthogonal transform coefficient.
Preferably, in step s 4, multichannel dissemination system is detected channel, selects optimal channel, priority
It is followed successively by：Short range wireless transmission, mobile communication transmission, satellite communication transmission.
Including following sub-step preferably, in step s 5,：
S51. video file dispenser is split video file；
S52. the file that video compression encoder completes segmentation compresses；
S53. operation is encrypted to the video file compressed in encryption device.
Preferably, in step s 5, video file is decrypted in the decryption device of central site image processing module
Afterwards, decoding device is decoded file, and display equipment carries out video real-time display.
The present invention has the following advantages and beneficial effect：(1) intelligent planning is carried out using to railway line, improves planning effect
Rate, by intelligent ergodic algorithm, the best patrol route of planning department in railway line road network meets in shortest tour apart from feelings
To the traversal of all important nodes in region under condition；(2) it supports high-definition digital image to pass ground back in real time, meets high-definition digital biography
Defeated requirement supports vision guided navigation, obstacle avoidance and images steganalysis tracking, meets development of new techniques requirement；It (3) can be not
Parameter is suitably changed in the case of being influenced by propagation delay, thus improves image recognition rate；(4) equipment is by by satellite
Communication network pattern is merged with conventional communication mode, it is only necessary to a set of Video Image Collecting System Based and multichannel distribution system
Two kinds of communication link bondings can be transmitted audio-video signals by system equipment so that emergency command communication bandwidth cost reduction, and
So that use scope is promoted.
Description of the drawings
Fig. 1 shows that a kind of aerial unmanned plane of railway line of the present invention is patrolled and real time image collection Transmission system automatically
Block diagram.
Fig. 2 shows a kind of aerial unmanned planes of railway line of the present invention to patrol and real time image collection transmission method stream automatically
Cheng Tu.
Specific implementation mode
Fig. 1 is to show that a kind of aerial unmanned plane of railway line of the present invention is patrolled automatically to be with real time image collection transmission
System.The system includes：Monitoring device 1 in unmanned plane and the video frequency transmitter 2 mounted on ground central station.
Wherein, monitoring device 1 includes：Central processing module 11, satellite navigation module 13 on unmanned plane, high definition
High power zoom motion video camera 12, generator terminal image processing module 14, video image wireless transmitter module 15 and inspection layout of roads
Module 16.
Wherein, the inspection layout of roads module 16 is used for the circuit of intelligent planning unmanned plane inspection, including：Unitary is non-thread
Property regression forecasting unit, line map connected unit and circuit structure and storage unit；The unitary nonlinear regression predicting unit
Railway track Node distribution is predicted, generate several node lines, every focus node circuit covers several nodes；Institute
The critical condition that line map connected unit utilizes Node distribution is stated, several node lines is made to be connected to form circuit connected graph；It patrols
Line inspection road is built and storage unit, circuit final structure and is stored for building inspection, and the central processing module is from the unit
It reads and executes inspection circuit.The node may include station, substation, road junction, crossing elimination point etc..
Three-dimensional space model is simplified to two-dimensional spatial model by the unitary nonlinear regression predicting unit, non-using unitary
Linear regression prediction method predicts the distribution of railway track important node；Prediction mode uses confidence interval mode, according to
History important node data (response variable) are predicted and are judged to new input data (explanatory variable).
The wherein described critical condition includes：Scissors crossing situation, the nearlyr parallelly distribute on situation of a plurality of circuit distance, important section
Point turns to situation, important node branch situation.
The inspection circuit structure and storage unit establish node matrix equation, wherein ranks coordinate representation node number, matrix function
According to for node geo-location information；Node is divided into two types according to prediction result：Important node and insignificant node, for
Important node builds important node adjacency list；For insignificant node, matrix structure storage, row matrix coordinate representation institute are carried out
Belong to circuit, row coordinate representation node number.
The central processing module 11 is also embedded with Ethernet switching chip (LANswitch), the Ethernet exchanging core
Piece (LANswitch) is connect with central processing module 11 (ARM) by LAN (LAN),
The generator terminal image processing module 14 is connect with 100 m ethernet mouth with the central processing module, in described
The Ethernet exchanging formula bus that the Ethernet switching chip (LANswitch) of centre processing module is extended receives high definition moving camera
The picture passed back, carry out image analysis resolve, and with light stream sensor, ultrasonic sensor, Inertial Measurement Unit data into
Row fusion carries out vision guided navigation, obstacle avoidance, images steganalysis tracking.
Data receipt unit receives grouped data, and image encoding stream is extracted from the grouped data.Image encoding stream
It is known as the coded image data of basic (elementary) stream.For example, some basic flows meet such as MPEG-2 (MPEG：
Motion picture expert group) and HEVC (high efficiency Video coding) coding standard H.264, have at least by sequence level and figure
The double-layer structure that piece level is constituted, each level includes header portion and data portion.Header portion contains various for encoding
Various parameters.It is decoded using the parameter as decoding parametric data portion by typical decoder.Parameter changes
Become unit to change the parameter in image encoding stream and the image encoding stream containing the parameter after change is supplied to decoder.Decoding
Device decodes the data portion of image encoding stream using the parameter after the change in image encoding stream as decoding parametric, to raw
At decoding image.Object etc. in image identification unit detection, identification, tracking decoding image.
Image identification unit calculates the index of instruction image recognition accuracy, parameter change unit in image recognition processes
What the index change based on the calculated instruction image recognition accuracy in image recognition processes was received by data receipt unit
Parameter.
The parameter change method of parameter change unit progress will be described in detail below.It will be by containing in image encoding stream
Parameter in header changes into another value from the value for being generated by cell encoder and being added.It is assumed that decoding image is checked for people
, cell encoder is generated and the parameter added is optimized to inhibit image deterioration.The parameter is simultaneously not always set in
Appropriate value for the identification in image identification unit.Thus, the image encoding stream that parameter change unit will be received by network
In parameter change in the header that contains be appropriate value for the identification in image identification unit.This can improve image recognition
Image recognition rate in unit.The parameter can rapidly be changed according to mode appropriate without the shadow for the propagation delay received
The case where sound, this is from the parameter value for changing encoder generation, is different.
At this point, image recognition unit calculates the index of instruction image recognition accuracy preferably in image recognition processes,
Then it is supplied to parameter change unit, parameter change unit to change advantageously according to the index of instruction image recognition accuracy index
Become the parameter.This is because can be directed to the image recognition that image recognition unit is implemented more suitably changes parameter value.
For example, the index of instruction image recognition accuracy refer to show image detection in image identification unit, identification and with
The index of the accuracy of the result of track is information or image recognition area information in relation to identification region.It can be according to instruction
The threshold value of similarity during each or according to by discriminator (discriminator) series determine identification and inspection
Survey the accuracy of result.It can utilize following for identification with the algorithm of detection and using determining identification and inspection by various methods
Survey the accuracy of result.
Decoding unit includes deblocking filter, and parameter change unit changes as the parameter received by data receipt unit
, indicate whether for image coded data using deblocking filter parameter and deblocking filter filter coefficient in extremely
It is one few.
Decoding unit includes inverse quantization unit, and the parameter contains included in the coding for being useful for generating image coded data
Quantization parameter.The quantization parameter contained in the parameter that parameter change unit change data receiving unit receives, then by the amount
Change parameter and is supplied to inverse quantization unit.
Decoding unit includes orthogonal inverse transform unit.The parameter, which contains, to be useful for generate performed by image coded data
Coding in include orthogonal transformation orthogonal transform coefficient.Parameter change unit changes the parameter received by data receipt unit
In the orthogonal transform coefficient that contains, the coefficient is then supplied to orthogonal inverse transform unit.
The central processing module 11 has image coding unit, the image obtained to high definition high power zoom motion video camera
It is encoded, then generator terminal image processing module receives the image generated by described image coding by data receipt unit and compiles
Code stream, the parameter that parameter change unit is received according to the operating condition change data receiving unit of unmanned plane.
The high definition high power zoom motion video camera 12 directly by Ethernet interface and central processing module 11 extended with
Too net switched-Fabric bus technology is attached, and supports the forwarding of multiple video flowings, will be high by Ethernet switching chip (LANswitch)
Clear video data is transmitted to generator terminal image processing module (DSP+ARM) and carries out image calculating.
15 compatible multi-signal emission mode of the video image wireless transmitter module, including short range wireless transmission,
Satellite-signal emission mode, 3G/4G movable signal emission modes etc..
The satellite navigation module 13 is that the GPS/ Big Dippeves receive chip, magnetic compass, microcontroller, goes out CAN bus and centre
It manages module (ARM) to connect, supports GPS and Beidou navigation positioning, support resolving of the magnetometer to attitude of flight vehicle, and and inertia
Measuring unit (IMU) carries out data fusion, finally resolves attitude of flight vehicle and position of aircraft by central processing module 11.
Video frequency transmitter 2 includes：Video image receiving module 21, multichannel distribution module 22, at central site image
Manage module 23 and display terminal 24.The video image receiving module 21, described in satellite network or mobile communications network reception
The picture signal of image transmitting module transmitting 14；For the multichannel distribution module 22 by video compression encoder, multichannel is logical
Believe discharge device, communication equipment, gateway device composition, the communication equipment includes wired transmission device, and short-distance wireless is logical
Believe equipment, mobile communication equipment, satellite communication equipment, by decoding device, image is shown to be set the center image processing system
Standby composition.
Multichannel dissemination system finds optimum channel, video compression encoder is to regarding by the detection for existing channel
The collected video of frequency image capturing system and image carry out compressed encoding, reduce file size, reduce channel pressure, by most
Good channel carries out video file transfer, by video file just, be transmitted to network server, the access of center image processing system
Internet public networks carry out real-time decoding to video file, and are shown on image display.
It is provided with encryption device on the multichannel discharge device, is provided on the central site image processing system
Decryption device, after this design, by the encryption for data, to ensure that the safety in data transmission procedure
Property, using hardware encryption and hardware decryption equipment so that it is very big that software cracks difficulty, even if someone has intercepted and captured relevant text
Part, but due to no corresponding hardware, it is also difficult to the decryption of file is carried out, ensure that the peace of transmission file to the greatest extent
Quan Xing.
The mobile communication equipment uses multiple network standard equipment, compatible 3G and 4G networks.Use it is this design with
Afterwards, national 3G is basicly stable, 4G high speed developments, is the stage that 3G and 4G coexist at this stage, two kinds of standards can expire
The demand of foot transmission audio-video document, because of the difference of its covering surface and coverage strength, the method using compatible 3G and 4G is most
The volume of transmitted data of good selection, 4G is bigger, but covering surface is poor, is suitble to carry out high quality in the place with 4G signals
Transmission of video, 3G covering surfaces are wider, but volume of transmitted data is smaller, and the place in no 4G signals is suitble to carry out video biography
It is defeated.
The satellite communication equipment includes satellite antenna, satellite power amplifier, LNB, and satellite modem is set using this
After meter, by the satellite communication equipment, video data may be implemented and be transmitted by satellite-signal, improves equipment and be applicable in
Range.
Fig. 2 shows a kind of aerial unmanned planes of railway line of the present invention to patrol and real time image collection transmission method automatically.
This method specifically comprises the following steps：
S1. inspection layout of roads module planning inspection route；
S2. central processing module starts monitoring programme, reads and execute above-mentioned intelligent planning circuit, the satellite navigation mould
Block starts GPS navigation program；
S3. high definition high power zoom motion video camera acquires video image, generator terminal image procossing according to the track of monitoring programme
Module handles image；
S4. the wireless transmission of picture signal is completed in video image wireless transmitter module and video image receiving module, cooperation
And reception；
S5. central site image processing module handles the picture signal received, and is shown on display terminal.
Preferably, in step sl, specifically comprise the following steps：
S11. unitary nonlinear regression prediction technique is used, railway track Node distribution is predicted, generates several
Node line, every node line cover several nodes；
In step S11, three-dimensional space model is simplified to two-dimensional spatial model first, it is pre- using unitary nonlinear regression
Survey method predicts railway track Node distribution；Prediction mode uses confidence interval mode, according to history node data
(response variable) is predicted and is judged to new input data (explanatory variable).Due to the particularity of Node distribution, it is summarized as spy
Different situation type, and the existence condition to determining each special circumstances, to classify during algorithm process.
S12. the critical condition for utilizing Node distribution, makes several node lines be connected to form circuit connected graph；Wherein institute
Stating critical condition includes：Scissors crossing situation, the nearlyr parallelly distribute on situation of a plurality of circuit distance, node turn to situation, node point
Branch situation；
In step S12, occur special circumstances if reaching Node distribution and reach critical condition, carries out critical types and sentence
It is disconnected, and handled；The critical type of Node distribution is divided into following several：
Scissors crossing situation：Occur multiple points in forecast interval section, has exceeded setting number of nodes, and there are crosspoints；
The nearlyr parallelly distribute on situation of a plurality of circuit distance：Occur multiple points in forecast interval section, have exceeded setting number of nodes,
But without crosspoint；
Node turns to situation：Compared with predictive equation, occurs unique inflection point in forecast interval；
Node branch situation：Compared with predictive equation, occur multiple inflection points in forecast interval.
S13. it builds railway track inspection planning chart and stores.
The present invention intelligently builds node connection by linear regression prediction algorithm in the case of only node geo coordinate
Figure, to carry out intelligent task planning.
Step S11 specifically comprises the following steps：
S111. dimension-reduction treatment：Dimension-reduction treatment is carried out to three-dimensional nodes geographical coordinate and is converted to two-dimensional coordinate；Set original A sections
Point three-dimensional coordinate is (xt,yt,zt),xtIndicate Nodes Three-dimensional space longitude coordinate, ytIndicate node latitude coordinate, ztIndicate node
Residing height above sea level, then A node coordinates are (x after dimensionality reductiont,yt)；
The establishment of S112 regression equations：One-variable linear regression prediction model formula applied to transmission line of electricity mission planning is such as
Under：
X in formulatIndicate t moment node longitude coordinate,Indicate t moment estimated latitude coordinate；
S113. it fetches and returns prediction step for N, obtain parameter a in regression equation, the solution equation of b is as follows：
Wherein,N is prediction moving step length；Since the distance between two base nodes are even up to a hundred at tens meters
Rice differs, and majority of case is formed by continuous more bases with node can near linear section.
According to another specific implementation mode of the present invention, in step S113, step-length N is 5 meters -10 meters.
According to another specific implementation mode of the present invention, step S11 further comprises step 114：Build forecast interval.Due to
There are a degree of deviations for curvilinear equation and predictive equation determined by actual node, therefore it is pre- to have carried out section to Y value
It surveys, that is, builds the forecast interval of average value.According to Node distribution situation, significance a is set, calculates the confidence of Y average values
Degree is the forecast interval of 1-a.
According to another specific implementation mode of the present invention, step S13 specifically comprises the following steps：
S131. node matrix equation, wherein ranks coordinate representation node number are established, matrix data is node geo-location information；
Node is divided into two types according to prediction result：Important node and insignificant node；Wherein important node includes circuit start-stop
Node and crossover node；Insignificant node is the internal node for only belonging to uniline；
S132. for important node, important node adjacency list is built；
S133. for insignificant node, matrix structure storage, the affiliated circuit of row matrix coordinate representation, row coordinates table are carried out
Show node number.
In step S132, for important node, since node data amount is larger, it is contemplated that algorithm memory space and algorithm effect
Rate, using Linked Storage Structure-adjacency list.
Preferably, in step s 2, further include following navigator fix step：
Central processing module 11 transmits the location data come to satellite navigation module 13 and judges：
If location data is in normal range (NR)：Then the location data received is stored in memory by central processing module 11
In；
The location data in normal range (NR) refers to：By the longitude of two neighboring sampled point, latitude in location data
Value, height value are compared two-by-two, if the difference of the longitude of two neighboring sampled point is no more than 0.0002 degree, and two neighboring are adopted
The difference of the latitude of sampling point is no more than 0.00018 degree, and the difference of the height of two neighboring sampled point is no more than 20 meters, and judgement is fixed
Position data are normal range (NR)；
If location data is abnormal：Then central processing module 11 recalls location data stored in memory, presses
Homeposition is returned to according to historical track；
The location data, which is abnormal, refers to：By the longitude of two neighboring sampled point, latitude value, height in location data
Angle value is compared two-by-two, if the difference that the difference of longitude is more than 0.0002 degree or latitude is more than 0.00018 degree or height
Difference is more than 20 meters, then judges that location data is abnormal.
Preferably, the location data is longitude information x, latitude information y, the elevation information of unmanned plane at every point of time
The set of z is denoted as { xt yt zt }；Wherein,
(x1y1z1) it is longitude, latitude, elevation information of the unmanned plane the 1st time point；
(x2y2z2) it is longitude, latitude, elevation information of the unmanned plane the 2nd time point；
And so on, (xt-1yt-1zt-1) is longitude, latitude, elevation information of the unmanned plane the t-1 time point；
(xt yt zt) is longitude, latitude, elevation information of the unmanned plane t-th of time point；
The interval at two neighboring time point takes 0.5 to 5.0 second；Each historical location data is stored in central processing module
In 11 memory；
The location data at t-th of time point is compared with the location data at the t-1 time point：
If xt-xt-1 ＜ 0.0002, and yt-yt-1 ＜ 0.00018, and 20 meters of zt-zt-1 ＜,
I.e. the difference of longitude is no more than 0.0002 degree, and the difference of latitude is no more than 0.00018 degree, and the difference of height does not surpass
When crossing 20 meters, the location data at t-th of time point of judgement belongs to normal range (NR), and the location data at t-th of time point is deposited
Enter the memory of central processing module 11；
If xt-xt-1 >=0.0002 or yt-yt-1 >=0.00018 or zt-zt-1 >=20 meter；That is the difference of longitude, latitude
Any of the difference of degree, difference of height exceed normal range (NR), and it is different to judge that the location data at t-th of time point has occurred
Often, namely think that exception has occurred in the flight of unmanned plane；
The location data at the t-1 time point in memory, the t-2 time point are determined by central processing module 11
Position data ... the location data at the 2nd time point, the location data at the 1st time point gradually read, and control unmanned flight
The departure place that device is returned according to original track.
Preferably, in step s 2, monitoring programme includes at application layer program, real-time task scheduler and external interrupt
Manage program, hardware initialization program, hardware drive program, CAN communication protocol procedure, LAN (TCP/IP) communication protocol program, institute
It states application layer program to connect with real-time task scheduler and external interrupt processor, the real-time task scheduler and outer
Portion's interrupt handling routine is connect with hardware initialization program, and the hardware initialization program is connect with hardware drive program.
Preferably, the application layer program includes Applied layer interface program, power management and electric quantity monitoring program, flying refers to
Show lamp control program, security control program, visual spatial attention program, flight tracking control program, augmentation control program, remote control decoding journey
Sequence, communication processing program.
Preferably, in step s3, one or more of following steps can be used to handle video image：
S31：Data receipt unit reception includes image coded data and the image encoding stream of parameter.
Data receipt unit reception includes image coded data and the image encoding stream of parameter.Parameter change unit can change
Become the parameter that data receipt unit receives.Decoding unit passes through the image coded data and ginseng to being received including data receipt unit
The image encoding stream that number changes the parameter that unit changes is decoded, and generates image decoding data.Image identification unit is to image
Decoding data executes image recognition.
Thus, it is possible to rapidly change parameter in a suitable manner in the case where not influenced by propagation delay, thus improve
Image recognition rate.This is because the parameter for including in image encoding stream is transmitted by the encoder in image transfer apparatus,
Then this can be appropriately changed as the parameter suitable for the image recognition in image received device.
S32：Index based on instruction image recognition accuracy changes parameter.
Image identification unit calculates the index of instruction image recognition accuracy in image recognition processes.Parameter change unit
What the index change based on the calculated instruction image recognition accuracy in image recognition processes was received by data receipt unit
Parameter.
This can more suitably change parameter for image recognition.
S33：Environmental information based on image received device changes parameter.
Environmental information of the parameter change unit based on image received device changes the parameter received by data receipt unit.
S34：Change parameter according to operating condition.
The parameter that parameter change unit is received according to the operating condition change data receiving unit of unmanned plane.
S35：Change the parameter of deblocking filter
Decoding unit includes deblocking filter.Parameter change unit changes as the parameter received by data receipt unit
, indicate whether for image coded data using deblocking filter parameter and deblocking filter filter coefficient in extremely
It is one few.
Thus, in the case where image recognition rate is not high enough, the intensity of deblocking filter is reduced to avoid to image
The inhibition of high fdrequency component, or inhibition level is reduced, thus improve discrimination.
S36：Change quantization parameter
Decoding unit includes inverse quantization unit.The parameter contains included in the coding for being useful for generating image coded data
Quantization quantization parameter.The quantization parameter contained in the parameter that parameter change unit change data receiving unit receives, then
The quantization parameter is supplied to inverse quantization unit.
Thus, in the case where image recognition rate is not high enough, quantization parameter is increased, to amplify and emphasize prediction error
Thus component improves discrimination.
S37：Change orthogonal transform coefficient
Decoding unit includes orthogonal inverse transform unit.The parameter, which contains, to be useful for generate performed by image coded data
Coding in include orthogonal transformation orthogonal transform coefficient.Parameter change unit changes the parameter received by data receipt unit
In the orthogonal transform coefficient that contains, the coefficient is then supplied to orthogonal inverse transform unit.
Thus, in the case where image recognition rate is not high enough, orthogonal transform coefficient can be changed, to improve discrimination.Example
Such as, the high-frequency range for deleting orthogonal transform coefficient, to allow the frequency component for the decoding image for being input to image identification unit
It is matched with the frequency component needed for image recognition.
Preferably, in step s 4, multichannel dissemination system is detected channel, selects optimal channel, priority
It is followed successively by：Short range wireless transmission, mobile communication transmission, satellite communication transmission.
Including following sub-step preferably, in step s 5,：
S51. video file dispenser is split video file；
S52. the file that video compression encoder completes segmentation compresses；
S53. operation is encrypted to the video file compressed in encryption device.
Preferably, in step s 5, video file is decrypted in the decryption device of central site image processing module
Afterwards, decoding device is decoded file, and display equipment carries out video real-time display.
Although as described above, being illustrated according to embodiment and attached drawing defined by embodiment, to the art
It can carry out various modifications and deform from above-mentioned record for technical staff with general knowledge.For example, according to explanation
Technology illustrated in method mutually different sequence carry out, and/or according to system, structure, device, the circuit etc. with explanation
The mutually different form of method illustrated by inscape is combined or combines, or is carried out according to other inscapes or equipollent
It replaces or displacement also may achieve effect appropriate.For those of ordinary skill in the art to which the present invention belongs, it is not taking off
Under the premise of from present inventive concept, several equivalent substitute or obvious modifications is made, and performance or use is identical, all should be considered as
It belongs to the scope of protection of the present invention.
Claims (6)
1. inspection and real time image collection transmission method, this method specifically comprise the following steps the aerial unmanned plane of railway line automatically：
S1. inspection layout of roads module planning inspection route；
S2. central processing module starts monitoring programme, reads and executes above-mentioned planning inspection circuit, satellite navigation module starts
GPS navigation program；
In step s 2, further include following navigator fix step：
The location data that central processing module carrys out satellite navigation module transmission judges：
If location data is in normal range (NR)：Then the location data received is stored in memory by central processing module；
The location data in normal range (NR) refers to：By the longitude of two neighboring sampled point, latitude value, height in location data
Angle value is compared two-by-two, if the difference of the longitude of two neighboring sampled point is no more than 0.0002 degree, and two neighboring sampled point
Latitude difference be no more than 0.00018 degree, and the difference of the height of two neighboring sampled point be no more than 20 meters, judgement position number
According to for normal range (NR)；
If location data is abnormal：Then central processing module recalls location data stored in memory, according to history
Track returns to homeposition；
The location data, which is abnormal, refers to：By the longitude of two neighboring sampled point, latitude value, height value in location data
It is compared two-by-two, if the difference that the difference of longitude is more than 0.0002 degree or latitude is more than the difference of 0.00018 degree or height
More than 20 meters, then judge that location data is abnormal；
The location data is the set of unmanned plane longitude information x at every point of time, latitude information y, elevation information z, note
For { xt yt zt }；Wherein,
(x1 y1 z1) is longitude, latitude, elevation information of the unmanned plane the 1st time point；
(x2 y2 z2) is longitude, latitude, elevation information of the unmanned plane the 2nd time point；
And so on, (xt-1 yt-1 zt-1) is longitude, latitude, elevation information of the unmanned plane the t-1 time point；
(xt yt zt) is longitude, latitude, elevation information of the unmanned plane t-th of time point；
The interval at two neighboring time point takes 0.5 to 5.0 second；Each historical location data is stored in central processing module 11
In memory；
The location data at t-th of time point is compared with the location data at the t-1 time point：
If xt-xt-1 ＜ 0.0002, and yt-yt-1 ＜ 0.00018, and 20 meters of zt-zt-1 ＜,
I.e. the difference of longitude is no more than 0.0002 degree, and the difference of latitude is no more than 0.00018 degree, and the difference of height is no more than 20
The location data of meter Shi, t-th of time point of judgement belong to normal range (NR), and will be in the deposit of the location data at t-th of time point
Entreat the memory of processing module 11；
If xt-xt-1 >=0.0002 or yt-yt-1 >=0.00018 or zt-zt-1 >=20 meter；That is the difference of longitude, latitude
Any of difference, difference of height exceed normal range (NR), judge that exception has occurred in the location data at t-th of time point,
Namely think that exception has occurred in the flight of unmanned plane；
By central processing module 11 by the location data at the t-1 time point in memory, the positioning number at the t-2 time point
According to ... location data, the location data at the 1st time point at the 2nd time point gradually read, and control unmanned vehicle and press
The departure place returned according to original track；
S3. high definition high power zoom motion video camera acquires video image, generator terminal image processing module according to the track of monitoring programme
Image is handled；
S4. video image wireless transmitter module and video image receiving module, cooperation are completed the wireless transmission of picture signal and are connect
It receives；
S5. central site image processing module handles the picture signal received, and is shown on display terminal；
In step s3, one or more of following steps can be used to handle video image：
S31：Data receipt unit reception includes image coded data and the image encoding stream of parameter；
S32：Index based on instruction image recognition accuracy changes parameter；
S33：Environmental information based on image received device changes parameter；
S34：Change parameter according to operating condition；
S35：Change the parameter of deblocking filter；
S36：Change quantization parameter；
S37：Change orthogonal transform coefficient；
In step s 5, including following sub-step：
S51. video file dispenser is split video file；
S52. the file that video compression encoder completes segmentation compresses；
S53. operation is encrypted to the video file compressed in encryption device；
In step sl, specifically comprise the following steps：
S11. unitary nonlinear regression prediction technique is used, railway track Node distribution is predicted, generates several nodes
Circuit, every node line cover several nodes；
In step S11, three-dimensional space model is simplified to two-dimensional spatial model first, using unitary nonlinear regression prediction side
Method predicts railway track Node distribution；Prediction mode uses confidence interval mode, according to (the response of history node data
Variable) new input data (explanatory variable) is predicted and judged；
S12. the critical condition for utilizing Node distribution, makes several node lines be connected to form circuit connected graph；It is wherein described to face
Boundary's situation includes：Scissors crossing situation, the nearlyr parallelly distribute on situation of a plurality of circuit distance, node turn to situation, node branch feelings
Condition；
In step S12, occur special circumstances if reaching Node distribution and reach critical condition, carries out critical types judgement, and
It is handled；The critical type of Node distribution is divided into following several：
Scissors crossing situation：Occur multiple points in forecast interval section, has exceeded setting number of nodes, and there are crosspoints；
The nearlyr parallelly distribute on situation of a plurality of circuit distance：Occur multiple points in forecast interval section, has exceeded setting number of nodes, but nothing
Crosspoint；
Node turns to situation：Compared with predictive equation, occurs unique inflection point in forecast interval；
Node branch situation：Compared with predictive equation, occur multiple inflection points in forecast interval；
S13. it builds railway track inspection planning chart and stores；
Step S11 specifically comprises the following steps：
S111. dimension-reduction treatment：Dimension-reduction treatment is carried out to three-dimensional nodes geographical coordinate and is converted to two-dimensional coordinate；Set original A nodes three
Dimension coordinate is (xt,yt,zt),xtIndicate Nodes Three-dimensional space longitude coordinate, ytIndicate node latitude coordinate, ztIt indicates residing for node
Height above sea level, then A node coordinates are (x after dimensionality reductiont,yt)；
S112. the establishment of regression equation：One-variable linear regression prediction model formula applied to transmission line of electricity mission planning is as follows：
X in formulatIndicate t moment node longitude coordinate,Indicate t moment estimated latitude coordinate；
S113. it fetches and returns prediction step for N, obtain parameter a in regression equation, the solution equation of b is as follows：
Wherein,N is prediction moving step length；Due to the distance between two base nodes tens meters even rice up to a hundred not
Deng, majority of case, formed with node by continuous more bases can near linear section.
2. the method as described in claim 1, which is characterized in that in step S113, step-length N is 5 meters -10 meters.
3. the method as described in claim 1, which is characterized in that step S11 further comprises step 114：Forecast interval is built,
Since there are a degree of deviations for curvilinear equation determined by actual node and predictive equation, area has been carried out to Y value
Between predict, that is, build the forecast interval of average value, according to Node distribution situation, set significance a, calculate Y average values
Confidence level is the forecast interval of 1-a.
4. the method as described in claim 1, which is characterized in that step S13 specifically comprises the following steps：
S131. node matrix equation, wherein ranks coordinate representation node number are established, matrix data is node geo-location information；According to
Node is divided into two types by prediction result：Important node and insignificant node；Wherein important node includes circuit start-stop node
And crossover node；Insignificant node is the internal node for only belonging to uniline；
S132. for important node, important node adjacency list is built；
S133. for insignificant node, matrix structure storage, the affiliated circuit of row matrix coordinate representation, row coordinate representation section are carried out
Period.
5. the method as described in claim 1, which is characterized in that in step s 2, monitoring programme include application layer program, in real time
Task dispatch and external interrupt processor, hardware initialization program, hardware drive program, CAN communication protocol procedure,
LAN communication protocol procedure, the application layer program are connect with real-time task scheduler and external interrupt processor, the reality
When task dispatch and external interrupt processor connect with hardware initialization program, the hardware initialization program and hardware
Driver connects.
6. the method as described in claim 1, which is characterized in that the application layer program includes Applied layer interface program, power supply
Management with electric quantity monitoring program, flight indicator light control program, security control program, visual spatial attention program, flight tracking control program,
Augmentation control program, remote control decoding program, communication processing program.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510644021.1A CN105262989B (en) | 2015-10-08 | 2015-10-08 | The aerial unmanned plane of railway line is patrolled and real time image collection transmission method automatically |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201510644021.1A CN105262989B (en) | 2015-10-08 | 2015-10-08 | The aerial unmanned plane of railway line is patrolled and real time image collection transmission method automatically |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN105262989A CN105262989A (en) | 2016-01-20 |
| CN105262989B true CN105262989B (en) | 2018-08-14 |
Family
ID=55102472
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201510644021.1A Active CN105262989B (en) | 2015-10-08 | 2015-10-08 | The aerial unmanned plane of railway line is patrolled and real time image collection transmission method automatically |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN105262989B (en) |
Families Citing this family (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105501248B (en) * | 2016-02-16 | 2018-03-20 | 株洲时代电子技术有限公司 | A kind of rail track cruising inspection system |
| CN106406343B (en) * | 2016-09-23 | 2020-07-10 | 北京小米移动软件有限公司 | Control method, device and system of unmanned aerial vehicle |
| CN108284855A (en) * | 2017-12-27 | 2018-07-17 | 河南辉煌信通软件有限公司 | A kind of rail polling system based on unmanned plane |
| CN109213196A (en) * | 2018-09-05 | 2019-01-15 | 福州日兆信息科技有限公司 | A kind of communication iron tower intelligent patrol detection unmanned plane device |
| CN109120900B (en) * | 2018-09-17 | 2019-05-24 | 武汉卓尔无人机制造有限公司 | Unmanned vehicle images processing system and its processing method |
| CN109510700B (en) * | 2018-12-20 | 2019-08-30 | 滨州学院 | A kind of data transmission system based on chaos encryption |
| CN111864618B (en) * | 2019-04-24 | 2021-09-10 | 广州煜煊信息科技有限公司 | Unmanned aerial vehicle inspection method and system for power system |
| CN110708830B (en) * | 2019-10-25 | 2021-06-08 | 湖南汇纳景观亮化工程有限公司 | Intelligent lamp inspection system |
| CN110658850B (en) * | 2019-11-12 | 2022-07-12 | 重庆大学 | Greedy strategy-based flight path planning method for unmanned aerial vehicle |
| CN111086452B (en) * | 2019-12-27 | 2021-08-06 | 合肥疆程技术有限公司 | Method, device and server for compensating lane line delay |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| FR2961601B1 (en) * | 2010-06-22 | 2012-07-27 | Parrot | METHOD FOR EVALUATING THE HORIZONTAL SPEED OF A DRONE, IN PARTICULAR A DRONE SUITABLE FOR AUTOPILOT STATIONARY FLIGHT |
| CN102183955A (en) * | 2011-03-09 | 2011-09-14 | 南京航空航天大学 | Transmission line inspection system based on multi-rotor unmanned aircraft |
| CN203773717U (en) * | 2013-11-12 | 2014-08-13 | 武汉大学 | Remote visual touch screen control system for unmanned plane |
| CN103606261A (en) * | 2013-11-29 | 2014-02-26 | 文杰 | Dynamic cell patrolling system based on aerial photography |
-
2015
- 2015-10-08 CN CN201510644021.1A patent/CN105262989B/en active Active
Also Published As
| Publication number | Publication date |
|---|---|
| CN105262989A (en) | 2016-01-20 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105262989B (en) | The aerial unmanned plane of railway line is patrolled and real time image collection transmission method automatically | |
| CN105208347B (en) | The aerial unmanned plane of railway line is patrolled and real time image collection transmitting, monitoring device automatically | |
| CN105208348B (en) | The aerial unmanned plane of railway line is patrolled and real time image collection Transmission system automatically | |
| CN105120240B (en) | The aerial high definition multidimensional of high power zoom unmanned plane investigates transmitting, monitoring device in real time | |
| CN105120232B (en) | Unmanned plane picture control and transmission method | |
| CN105208335B (en) | The aerial high definition multidimensional of high power zoom unmanned plane investigates Transmission system in real time | |
| CN105743004B (en) | A kind of Intelligent Mobile Robot cluster managing and control system | |
| CN105120230A (en) | Unmanned plane image monitoring and transmitting system | |
| US9082278B2 (en) | Surveillance system | |
| Nishio et al. | When wireless communications meet computer vision in beyond 5G | |
| CN112581590A (en) | Unmanned aerial vehicle cloud edge terminal cooperative control method for 5G security rescue networking | |
| CN106682592A (en) | Automatic image recognition system and method based on neural network method | |
| CN106205187A (en) | Parking lot storing cycle guidance system based on mobile little base station and implementation method | |
| CN110636255A (en) | Unmanned aerial vehicle image and video transmission and distribution system and method based on 4G network | |
| Minoli et al. | Internet of things applications for smart cities | |
| US20230239491A1 (en) | Three-dimensional data encoding method, three-dimensional data decoding method, three-dimensional data encoding device, and three-dimensional data decoding device | |
| CN105208336B (en) | The aerial high definition multidimensional of high power zoom unmanned plane investigates transmission method in real time | |
| US20220207782A1 (en) | Three-dimensional data encoding method, three-dimensional data decoding method, three-dimensional data encoding device, and three-dimensional data decoding device | |
| CN110351528A (en) | A kind of maneuvering platform based on the polymerization of ARization outdoor scene | |
| CN1937000A (en) | Remote monitoring method for city crossroads and vehicle flow identifying detection method | |
| CN107734305A (en) | It is a kind of to use remote speech commander and the electric power construction field informationization monitoring system of job site various dimensions solid show | |
| CN114325573A (en) | Method for rapidly detecting identity and position information of operation and maintenance personnel of transformer substation | |
| CN213120575U (en) | Indoor positioning navigation system and indoor power distribution equipment monitoring control system | |
| US20240005564A1 (en) | Three-dimensional data encoding method, three-dimensional data decoding method, three-dimensional data encoding device, and three-dimensional data decoding device | |
| CN111970728A (en) | AI (Artificial intelligence) public-private converged communication commonality technical architecture and method |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| C06 | Publication | ||
| PB01 | Publication | ||
| C10 | Entry into substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |