CN110049317A - A kind of online fault detection method, system and the electronic equipment of video monitoring system - Google Patents
A kind of online fault detection method, system and the electronic equipment of video monitoring system Download PDFInfo
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- CN110049317A CN110049317A CN201910363338.6A CN201910363338A CN110049317A CN 110049317 A CN110049317 A CN 110049317A CN 201910363338 A CN201910363338 A CN 201910363338A CN 110049317 A CN110049317 A CN 110049317A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N17/00—Diagnosis, testing or measuring for television systems or their details
- H04N17/004—Diagnosis, testing or measuring for television systems or their details for digital television systems
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Abstract
A kind of online fault detection method, system and the electronic equipment of video monitoring system, wherein, this method carries out online fault detection based on the probe being arranged in video monitoring system at least one network node, comprising: obtains the video flow of at least one network node；Judge whether the video flow is normal；In the video flow exception, the fault type being abnormal is determined.So as to accurately learn fault type, detection efficiency is high, high sensitivity.
Description
Technical field
The invention belongs to the online fault detection method of field of video monitoring more particularly to a kind of video monitoring system, it is
System and electronic equipment.
Background technique
Video monitoring system is the important component of safety and protection system, intuitive with it, accurate, the timely and information content
The features such as abundant and be widely used in many occasions.In recent years, with computer, network and image procossing, transmission technology
Rapid development, there has also been quick development for Video Supervision Technique.
Compared with the fast development of video monitoring system, the fault detection of video monitoring system then relatively lags behind, existing
Fault detection method is the detection of periodic initiative, such as: there are 10,000 cameras in certain area, city, but can not position this 1
Ten thousand cameras which be it is good, which is bad, then will take the photograph from the 1st camera to the 10000th when detecting failure
As head is checked in turn, each camera is first usually connected into network, after being connected to the network successfully, then obtains video flowing, in turn
Image quality analysis is carried out to the video flowing got, if 10,000 cameras have all been analyzed, it may be necessary to and one day is even longer
Time, this is allowed for, and detection cycle is long, detection efficiency is low and insensitive.
In addition, traditional fault detection method is to establish to contact with video synthesis platform, some camera is transferred in real time
Data, if can recall, illustrate it is out of question, if adjust do not come out, can only illustrate it is problematic, but problem where, nothing
Method is learnt, if say the video blur of some camera, then the detection method of the prior art the result is that can only see fuzzy
It the problem of video, but not knowing is that network is obstructed, power issue or camera itself, can not be accurately positioned.Cause
This, needs the comprehensive fault detection system of one kind and goes investigation problem.
Summary of the invention
(1) goal of the invention
Real-time detection and the fault detection method and system of fault type can be determined the object of the present invention is to provide a kind of.
(2) technical solution
To solve the above problems, the first aspect of the present invention provides a kind of online fault detection side of video monitoring system
Method is arranged in the flow in video monitoring system at least one network node based on bypass and monitors the online failure inspection of module progress
It surveys, comprising: obtain the video flow of at least one network node；Judge whether the video flow is normal；In the view
When frequency Traffic Anomaly, determine that the video monitoring system breaks down, and determines fault type.
Further, in the video flow exception, fault type is determined, comprising: to the video monitoring system
Network link is detected；When the network link exception, determine that the fault type is that network link is abnormal.
Further, further includes: when the network link is normal, the camera is detected；Detecting
When stating camera exception, determine that the fault type is camera failure.
Further, further includes: when the video flow is normal, judge the video monitoring based on other judgment rules
Whether system breaks down；If the video monitoring system breaks down, it is determined that fault type.
Further, judge whether the video monitoring system is abnormal based on other judgment rules, comprising: obtain view
Frequency picture material；Quality testing is carried out to the video image content；If the abnormal quality of the video image content, determine
The fault type is that video image quality is abnormal.
Further, further includes: if the quality of the video image content is normal, based on the video flow to view
Frequency application carries out fault detection.
Further, fault detection is carried out to Video Applications based on the video flow, comprising: communicate based on Video Applications
Whether protocol format detects in the video flow comprising exception and fault message；If comprising abnormal in the video flow
And fault message, it is determined that the fault type is that the Video Applications are abnormal.
According to another aspect of the present invention, a kind of online fault detection system of video monitoring system is additionally provided,
It is characterized in that, comprising: video flow obtains module, for obtaining the video flow of at least one network node；Judge mould
Block, for judging whether the video flow is normal；Fault type determining module is used in the video flow exception, really
Surely the fault type being abnormal.
Other side according to an embodiment of the present invention provides a kind of non-transient computer readable storage medium, non-transient
Computer-readable recording medium storage computer instruction, computer instruction is for making computer execute any of the above-described kind of video monitoring
The online fault detection method of system.
Other side according to an embodiment of the present invention provides a kind of computer program product, computer program product packet
The computer program being stored in non-transient computer readable storage medium is included, computer program includes program instruction, works as program
When instruction is computer-executed, computer is made to execute the online fault detection method of any of the above-described kind of video monitoring system.
(3) beneficial effect
Above-mentioned technical proposal of the invention has following beneficial technical effect: passing through the network section in video monitoring system
Probe is arranged on point, the video data of transmission is acquired in real time, and the video flow acquired in real time is analyzed, it can
Accurate positionin is which camera goes wrong, and does not need to remove to check each camera in turn.In addition, by passively supervising in real time
Whether control has video flow to transmit, if transmitted without video flow, then it is assumed that breaks down, by further
Investigation can determine and can clearly arrive fault type, and detection efficiency is high, high sensitivity.
Detailed description of the invention
Fig. 1 is the hardware structure that a kind of online fault detection method of video monitoring system of the embodiment of the present invention is relied on
Schematic diagram；
Fig. 2 is a kind of flow chart of the online fault detection method of video monitoring system of the embodiment of the present invention；
Fig. 3 is the flow chart of the online fault detection method of another video monitoring system of the embodiment of the present invention；
Fig. 4 is the flow chart of the online fault detection method of another video monitoring system of the embodiment of the present invention；
Fig. 5 is the structural schematic diagram of the online fault detection system of another video monitoring system of the embodiment of the present invention；
Fig. 6 is the structural schematic diagram of a kind of electronic equipment of the embodiment of the present invention.
Specific embodiment
In order to make the objectives, technical solutions and advantages of the present invention clearer, With reference to embodiment and join
According to attached drawing, the present invention is described in more detail.It should be understood that these descriptions are merely illustrative, and it is not intended to limit this hair
Bright range.In addition, in the following description, descriptions of well-known structures and technologies are omitted, to avoid this is unnecessarily obscured
The concept of invention.
Fig. 1 is the hardware net that a kind of online fault detection method of video monitoring system of the embodiment of the present invention is relied on
Configuration diagram.
As shown in Figure 1, including that video acquisition end, the network switch, Video Storage System and video dispatching platform, video are adopted
Collect end and Video Storage System is connected to by the network switch, video data is stored into Video Storage System, video acquisition
End is also connected to video dispatching platform by the network switch, and video dispatching platform adjusts the request of access video data
Degree.Wherein, video acquisition end is that have the equipment of camera function, can be various types of camera.
On the basis of hardware structure shown in Fig. 1, a Network switch nodes, bypass are selected in video monitoring system
It disposes flow and monitors module, and then obtain video flow.Specifically, flow is monitored module and can be realized by probe.
Fig. 2 is a kind of flow chart of the online fault detection method of video monitoring system of the embodiment of the present invention.
As shown in Fig. 2, a kind of online fault detection method of video monitoring system, based on setting in video monitoring system
Probe at least one network node carries out online fault detection, and this method comprises the following steps:
S1 obtains the video flow of at least one network node；
Specifically acquiring the video flow by network node in real time by flow monitoring module, flow monitors module
Can there is following two implementation to obtain video flow:
In one embodiment, flow is monitored module and can be drawn in real time by the mirror image traffic engineering capability of the network switch
Video flow obtain video flow.
In another embodiment, it can be monitored in the network switch and flow and an optical splitter is set between module,
The video flow of the network switch is replicated by optical splitter, flow is then forwarded to and monitors module to obtain video flow.
Above two bypass deployment way will not impact the operation of video monitoring system itself, be not in by
Flow is monitored module and is serially accessed in video monitoring system, thus the problem of causing network Single Point of Faliure.
S2 judges whether video flow is normal；
S3a determines that video monitoring system breaks down, and determine fault type in video flow exception.
In one embodiment, the video flow acquired in step S1 is denoted as T1, then for video flow T1's
Abnormality detection can judge whether video flow is normal by judging whether T1 is equal to 0.If T1 is equal to 0, it is judged as view
Frequency Traffic Anomaly, while indicating that video monitoring system breaks down.
In another embodiment, judge whether video flow T1 is abnormal, can also be based on video flow baseline, i.e.,
Judge whether T1 deviates baseline value, if video flow T1 deviates baseline value, is judged as video flow exception, if video flowing
T1 is measured without departing from baseline value, then is judged as that video flow is normal.
Optionally, baseline value can take over the average value of multiple video flows in certain a period of time, such as take over 1
The average value of video flow per minute in a hour is also possible to take the video flow in history at least two days mutually in the same time
Average value, be averaged for example, 12 points of the same day of video flowing magnitude and historical daily 12 points of video flowing magnitude are cumulative.
Meanwhile screening rule can be set to the history value got, the history value for not meeting screening rule can weed out, and not receive
Enter the scope of statistics of baseline value.
Optionally, judge whether video flow T1 deviates baseline value, can also be at the time of video flow T1 is corresponded to
Every day, Mei Yizhou, the video flow of the phase in per January in the same time are compared in history, judge whether there is deviation.Certainly, originally
Exemplifications set out is not limit the calculation of baseline value to be easy to understand to baseline value in inventive embodiments.
Optionally, whether video flow T1 deviates baseline value, can be one preset deviation range of setting, such as 5%,
If video flow T1 deviates baseline value within ± 5%, then it is assumed that video flow T1 is without departing from baseline value, if video flow
It is more than ± 5% that T1, which deviates baseline value, then it is assumed that video flow T1 deviates from baseline value.Certainly, deviate range ± 5% only to illustrate
That does schematically illustrates, and is not defined to the scope of the present invention, and those skilled in the art can carry out according to actual needs
Adjustment.
In another embodiment, it is also based on standard video format (such as 4K video data format) and calculates flow value
Judge whether video flow T1 is abnormal, i.e., if video flow T1 and normal video flowmeter calculation value are inconsistent, then it is assumed that regard
Frequency Traffic Anomaly.
In one embodiment, as shown in figure 3, determining fault type in step S3a, include the following steps S3a1-
S3a2b:
Whether S3a1, the network link for detecting video monitoring system are normal；
S3a2a determines that fault type is that network link is abnormal when network link exception.
S3a2b, when network link is normal, detection camera whether failure；
Specifically, can be detection camera shooting head end and Video Storage System between network link, and camera shooting head end with
Network link between video dispatching platform.Wherein, network link includes: physical layer, network layer and application layer, when physical layer,
Any layer in network layer and application layer breaks down, and is all diagnosed as network link failure.In a specific embodiment, may be used
It is whether reachable with the IP for detecting camera and video dispatching platform or Video Storage System respectively by PING tool, if PING is not
It is reachable, then it is diagnosed as network link interruption, if PING is reachable, it is normal to be diagnosed as network link.Further, it is also possible to pass through
Whether the application service of Telnet tool detection video dispatching platform or Video Storage System can lead to, if Telnet is obstructed, examine
Break and is operating abnormally failure for Video Applications service (including video dispatching platform service and Video Storage System service).
S3a3 determines that fault type is camera failure when detecting camera exception.
Specifically, the power information of camera can be obtained by being connected to the network to camera, if camera supplies
Electricity interrupts, then is diagnosed as camera power supply power supply outage, if camera power supply is normal, further obtains the fortune of camera
Row status information is diagnosed as camera operation troubles if camera operating status is abnormal, certainly, the present invention is not limited to
Both the above mode, the working condition of camera can be obtained by other methods and confirm camera operation whether faulty side
Method is intended to be included within the scope.
In another embodiment, further includes: S3b is sentenced when the video flow is normal based on other judgment rules
Whether the video monitoring system of breaking breaks down, if the video monitoring system breaks down, it is determined that be abnormal
Fault type.Specifically, if T1 is not equal to 0, then it is assumed that video flow is normal, but video flow does not represent video normally
Monitoring system must be just trouble-free, therefore, it is also desirable to further judge that video monitoring system is by other judgment rules
It is no to break down, and if video monitoring system breaks down, need to further determine that the fault type being abnormal.Specifically
Ground judges whether the video monitoring system is abnormal based on other judgment rules, as shown in Figure 4, comprising:
S3b1 obtains video image content；
In one embodiment, obtaining for video image content can be carried out by the video flow obtained to step S1
Video decodes to obtain；
In another embodiment, video image content can also be directly acquired from Video Storage System, specifically,
It can be by calling the SDK software interface, RTSP agreement, Session Initiation Protocol or the GB28181 agreement that provide with video equipment manufacturer
Various ways are waited to obtain video image content from Video Storage System.Optionally, video is obtained from Video Storage System
Picture material can be real-time acquisition, be also possible to periodically acquire, such as: it was obtained at interval of 1 minute, 5 minutes or 1 hour
Take primary video picture material.
S3b2 detects the quality of the video image content with the presence or absence of abnormal；
Specifically, quality testing is to be examined using video image quality diagnosis algorithm to the corresponding index of video image
It surveys, such as: to the brightness of video image content, snowflake, no signal, freezes, colour cast, blocks, obscures, is striped, scene changes, right
It is detected than indexs such as degree, black and white, if the brightness of video image content, snowflake, no signal, freezing, colour cast, blocking, mould
Any of paste, striped, scene changes, contrast or Black-White are abnormal, then it is assumed that video image quality is abnormal.Video image
Quality diagnosis algorithm can realize using existing some algorithms, all views that can be realized above-mentioned image quality index detection
Frequency picture quality diagnosis algorithm is intended to be included within the scope.
S3b3a determines that the fault type is that video image quality is different if the abnormal quality of the video image content
Often.
S3b3b detects whether Video Applications break down if the quality of the video image content is normal.
In a kind of specific embodiment, fault detection is carried out to Video Applications based on the video flow, comprising:
S3b3b1 is based on Video Applications communications protocol format, detect in the video flow whether comprising exception information or
Person's fault message；
S3b3b2, if whether including exception information or fault message in the video flow, it is determined that the failure
Type is that the Video Applications are abnormal.
The online fault detection method and system of the video monitoring system of the embodiment of the present invention, can be to various faults type
It is diagnosed and is detected, comprising: video network failure, camera failure, video image quality failure, video network application failure
Deng.And the step of video fault diagnosis and detection simple, Yi Shixian.It, can be real-time for traditional fault detection
Detected online, do not needed poll and check each camera, therefore, can by the time rank of conventional video fault diagnosis from
" hour grade " is increased to " second grade ", greatly improves fault pre-alarming and disposing capacity in video monitoring system.
As shown in figure 5, additionally providing a kind of online fault detection system of video monitoring system, comprising: video flow obtains
Modulus block, for obtaining the video flow of at least one network node；Judgment module, for judging that the video flow is
It is no normal；Fault type determining module, for determining the fault type being abnormal in the video flow exception.
It should be noted that being and relating to the present invention also provides a kind of online fault detection system of video monitoring system
And a kind of one-to-one system of online fault detection method of video monitoring system of computer program process, due to it is preceding
Step process through the online fault detection method to a kind of video monitoring system is described in detail, herein no longer to one kind
The implementation process of the online fault detection system of video monitoring system is repeated.
The embodiment of the invention also provides a kind of non-transient computer readable storage medium, non-transient computer readable storages
Medium storing computer instruction, the method that computer instruction is used to that computer to be made to execute any of the above-described a embodiment.
It should be understood by those skilled in the art that, the embodiment of the present invention can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the present invention
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the present invention, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The present invention be referring to according to the method for the embodiment of the present invention, the process of equipment (system) and computer program product
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The system for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
As shown in fig. 6, a kind of electronic equipment for executing preceding method, including one or more processors 601 and with one
The memory 602 of a or multiple processor communications connection takes a processor as an example in Fig. 6.
Electronic equipment can also include: input unit 603 and output device 606, and input unit 603 refers to for inputting user
It enables, output device 606 is for exporting determining fault type and/or warning information.
Processor 601, memory 602, input unit 603 and output device 606 can pass through bus or other modes
It connects, in Fig. 6 for being connected by bus.
Memory 602 is used as a kind of non-transient computer readable storage medium.It can be used for storing non-transient software program, non-
Transient computer executable program, the online fault detection method such as one of embodiment of the present invention video monitoring system are corresponding
Software program, instruction and module.Processor 601 passes through the non-transient software program run storage in the memory 602, refers to
Order and module, execute the various function application and data processing of a kind of online fault detection system of video monitoring system,
Realize the method and step of above method embodiment.
Memory 602 may include storing program area and storage data area, wherein storing program area can store operation system
Application program required for system, at least one function；Storage data area can store the online event according to a kind of video monitoring system
Barrier detection system uses created data etc..In addition, memory 602 may include high-speed random access memory, may be used also
To include non-transient memory, a for example, at least disk memory, flush memory device or other non-transient solid-state memories
Part.In some embodiments, it includes the memory remotely located relative to processor 601 that memory 602 is optional, these are remotely deposited
Reservoir can pass through a kind of network connection to task processing system.The example of above-mentioned network includes but is not limited to internet, enterprise
Intranet, local area network, mobile radio communication and combinations thereof.
Input unit 603 can receive the user instruction of input, and generate the user setting and function control with input
Related key signals input.Input unit 603 may include touch screen, keyboard etc., also may include wireline interface, wireless interface
Deng.Output device 606 may include that display screen etc. shows equipment.
One or more software programs, instruction storage in the memory 602, are executed when by one or more processors 601
When, execute the online fault detection method of one of above-mentioned any means embodiment video monitoring system.
In embodiments of the present invention, one or more processors can: execute a kind of video of aforementioned any embodiment
The online fault detection method of monitoring system.
It should be understood that above-mentioned specific embodiment of the invention is used only for exemplary illustration or explains of the invention
Principle, but not to limit the present invention.Therefore, that is done without departing from the spirit and scope of the present invention is any
Modification, equivalent replacement, improvement etc., should all be included in the protection scope of the present invention.In addition, appended claims purport of the present invention
Covering the whole variations fallen into attached claim scope and boundary or this range and the equivalent form on boundary and is repairing
Change example.
Claims (10)
1. at least one is arranged in video monitoring system based on bypass in a kind of online fault detection method of video monitoring system
Flow on network node monitors module and carries out online fault detection characterized by comprising
Obtain the video flow of at least one network node；
Judge whether the video flow is normal；
In the video flow exception, determine that the video monitoring system breaks down, and determines fault type.
2. a kind of online fault detection method of video monitoring system as described in claim 1, which is characterized in that in the view
When frequency Traffic Anomaly, fault type is determined, comprising:
The network link of the video monitoring system is detected；
When the network link exception, determine that the fault type is that network link is abnormal.
3. a kind of online fault detection method of video monitoring system as claimed in claim 2, which is characterized in that further include:
When the network link is normal, the camera is detected；
When detecting the camera exception, determine that the fault type is camera failure.
4. a kind of online fault detection method of video monitoring system as described in claim 1, which is characterized in that further include:
When the video flow is normal, judge whether the video monitoring system breaks down based on other judgment rules；
If the video monitoring system breaks down, it is determined that fault type.
5. a kind of online fault detection method of video monitoring system as claimed in claim 4, which is characterized in that be based on other
Judgment rule judges whether the video monitoring system is abnormal, comprising:
Obtain video image content；
Quality testing is carried out to the video image content；
If the abnormal quality of the video image content, determine that the fault type is that video image quality is abnormal.
6. a kind of online fault detection method of video monitoring system as claimed in claim 5, which is characterized in that further include:
If the quality of the video image content is normal, fault detection is carried out to Video Applications based on the video flow.
7. a kind of online fault detection method of video monitoring system as claimed in claim 6, which is characterized in that based on described
Video flow carries out fault detection to Video Applications, comprising:
Based on Video Applications communications protocol format, whether detect in the video flow comprising exception and fault message；
If whether including exception and fault message in the video flow, it is determined that the fault type is the Video Applications
It is abnormal.
8. a kind of online fault detection system of video monitoring system characterized by comprising
Video flow obtains module, for obtaining the video flow of at least one network node；
Judgment module, for judging whether the video flow is normal；
Fault type determining module, for determining the fault type being abnormal in the video flow exception.
9. a kind of computer storage medium, which is characterized in that be stored with computer program, described program quilt on the storage medium
A kind of online fault detection method step of video monitoring described in any one of claim 1-7 is realized when processor executes.
10. a kind of electronic equipment, which is characterized in that including memory, processor and be stored on the memory and can be in institute
The computer program run on processor is stated, the processor realizes any one of claim 1-7 when executing described program
A kind of the step of online fault detection method of video monitoring.
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Application publication date: 20190723 |