CN108234162A - TDCS/CTC system early warning methods based on port data flow monitoring - Google Patents
TDCS/CTC system early warning methods based on port data flow monitoring Download PDFInfo
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- CN108234162A CN108234162A CN201611154023.3A CN201611154023A CN108234162A CN 108234162 A CN108234162 A CN 108234162A CN 201611154023 A CN201611154023 A CN 201611154023A CN 108234162 A CN108234162 A CN 108234162A
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0631—Management of faults, events, alarms or notifications using root cause analysis; using analysis of correlation between notifications, alarms or events based on decision criteria, e.g. hierarchy, tree or time analysis
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0654—Management of faults, events, alarms or notifications using network fault recovery
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
- H04L41/06—Management of faults, events, alarms or notifications
- H04L41/0677—Localisation of faults
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L43/00—Arrangements for monitoring or testing data switching networks
- H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
- H04L43/0876—Network utilisation, e.g. volume of load or congestion level
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- Engineering & Computer Science (AREA)
- Computer Networks & Wireless Communication (AREA)
- Signal Processing (AREA)
- Environmental & Geological Engineering (AREA)
- Data Exchanges In Wide-Area Networks (AREA)
Abstract
The present invention relates to a kind of TDCS/CTC system early warning methods based on port data flow monitoring, daily detecting based on device port data traffic each to TDCS/CTC systems and statistical modeling, the flow and modeling data that currently acquire are compared, the early warning of the TDCS/CTC system failures and alarm are carried out according to the rule of setting.Compared with prior art, the present invention has many advantages, such as that technology is general, scale of investment is small, can find failure in advance.
Description
Technical field
The present invention relates to a kind of TDCS/CTC system early warnings methods, and port data flow monitoring is based on more particularly, to one kind
TDCS (Railway traffic control system)/CTC (Centralized Dispatching System) system early warning method.
Background technology
TDCS/CTC systems are important indispensable travelling facility, are indivisible in modernized railway dispatch control system
A part.Train dispatcher and other related work posts understand train operation and presence states, and lead to by TDCS/CTC systems
TDCS/CTC systems are crossed to assign Train operation plan, traffic order, row control speed limit order and handle route etc. automatically.Work as TDCS/CTC
During failure, dispatcher can not understand field condition, can not assign commander's instruction, will directly affect traffic safety in this way and driving is imitated
Rate influences transport benefits.
Meanwhile TDCS/CTC systems are an extensive wide area network systems, the TDCS/CTC systems of a Railway Bureau are generally wrapped
Thousands of station terminals, hundreds server, the hundreds network equipment and nearly thousand designated lanes are included, have that device category is more, structure
The characteristics of complicated, and and almost all of signalling arrangement all there are interfaces.So when the TDCS/CTC system failures, often
It is difficult to investigate processing, far can not meet maintenance requirement by traditional manual patrol, the mode checked.
Current each office has been already equipped with some TDCS/CTC maintained equipments and software, but efficient far from TDCS/CTC is met
The requirement of maintenance, main problem are the absence of integral systematicness design, are slapped together by the webmastering software of various different manufacturers, function
Aspect is also very single, mainly network channel monitoring and software process monitor, lacks the functions such as fault pre-alarming, intellectual analysis,
Often detect that system when carrying out failure has been in down state or maintenance system fails monitoring and is out of order but influenced business
Normal use.
Invention content
It is an object of the present invention to overcome the above-mentioned drawbacks of the prior art and provide a kind of technology is general, investment
Small scale, the TDCS/CTC system early warning methods based on port data flow monitoring that can find failure in advance, using to TDCS
It is monitored with CTC appliance services communication port data traffic, is formed and modeled, and will monitor in real time with the average value that normal discharge counts
Data are compared with modeling average value, by and the deviation of average value judge that system is working properly whether, and to maintenance personnel's progress
Alarm.
The purpose of the present invention can be achieved through the following technical solutions：
A kind of TDCS/CTC system early warning methods based on port data flow monitoring, based on respectively being set to TDCS/CTC systems
The daily detecting of standby port data flow and statistical modeling compare the flow and modeling data that currently acquire, according to setting
Rule carries out the early warning of the TDCS/CTC system failures and alarm.
The method for early warning includes the following steps：
(1) it monitors and counts each daily data traffic in business device port of TDCS/CTC systems；
(2) the daily data traffic of each business device of TDCS/CTC systems is modeled, forms what is be distributed according to the time period
Data traffic model；
(3) each business device port communication flow is monitored, is less than or more than day normal flow average value setting model when detecting
Early warning is carried out when enclosing, is less than or more than defined warning value when alarms；
(4) by early warning and warning message, bonding apparatus log information is analyzed and fault point, further excludes event
Barrier.
The method for early warning is specially：
1) objects of statistics that the appliance services communication port in TDCS/CTC systems is monitored as daily port flow is chosen；
2) using the period that daily port flow monitors as N seconds as the traffic statistics period；
3) data traffic that the port sends and receivees is counted within the traffic statistics period；
4) it is formed using measurement period as the time shaft (horizontal axis) of minimum time resolution ratio, to receive data traffic and send number
According to the data traffic figure sended and received that flow is data volume axis (longitudinal axis)；
5) the reception data traffic point line of continuous measurement period is formed into day statistics and receives data traffic curve；
6) the transmission data flow point line of continuous measurement period is formed into day statistics transmission data flow curve；
7) continuous statistics forms day statistics and receives data traffic average value curve and day statistics transmission data flow after D days
Average value curve；
8) it then needs to reject age at failure statistical data such as faulty generation in statistic processes；
9) it is counted using day and receives data traffic average value curve and day statistics transmission data flow average value curve, calculated
Each collection point receives and the normal distribution curve of transmission data flow, repeats step 2)~8) different periods are handled, shape
Into the data traffic model by period distribution where collection point；
10) current device port flow is monitored, day statistics is generated in real time and sends and receivees data traffic curve, go out when continuously
Existing M measurement period is less than or carries out early warning more than early warning value；
11) current device port flow is monitored, day statistics is generated in real time and sends and receivees data traffic curve, go out when continuously
Existing M measurement period is less than or alarms more than warning value；
12) according to early warning and warning message, device log analysis and positioning failure are called.
The N seconds are 10 seconds, and D days are 30 days, and M are 3.
Described continuous there is M measurement period and be less than or be specially more than early warning value：The day system of year-on-year same time period
Meter receives or the P% of transmission data flow average value, falls within data traffic model pre-warning section；
Described continuous there is M measurement period and be less than or be specially more than warning value：The day system of year-on-year same time period
Meter receives or the Q% of transmission data flow average value, falls within data traffic model alarm section.
The P% is 15%, Q% 30%.
Compared with prior art, the present invention has the following advantages：
1) the technology of the present invention is general, scale of investment is small, and the technology of the present invention is applicable in addition to suitable for TDCS/CTC systems
Whether normal detect road network all devices communications status；The present invention increases flow detection module, equipment on the basis of original system
Small investment.
2) present invention is applied widely, has the advantage that can find failure in advance.Since TDCS/CTC systems are in system-wide
It is universal, therefore the present invention may be used with nearly all circuits of system-wide.The present invention is according to TDCS/CTC system equipment service communications end
Mouthful data traffic monitoring, carry out intellectual analysis and make breakdown judge, it can be achieved that the giving warning in advance of failure, intervening in advance, have
Effect avoids the generation of failure and reduction later maintenance cost.
Description of the drawings
Fig. 1 generates flow chart for inventive flow alarm；
Fig. 2 handles schematic diagram for inventive flow alarming logic processing module；
Fig. 3 is the data traffic model schematic that the present invention is distributed according to the time period.
Specific embodiment
Below in conjunction with the attached drawing in the embodiment of the present invention, the technical solution in the embodiment of the present invention is carried out clear, complete
Site preparation describes, it is clear that described embodiment is the part of the embodiment rather than whole embodiments of the present invention.Based on this hair
Embodiment in bright, the every other reality that those of ordinary skill in the art are obtained under the premise of creative work is not made
Example is applied, should all belong to the scope of protection of the invention.
The appliance services communication port that the present invention is detected first in TDCS/CTC systems outputs and inputs flow, rejects failure
Data, according to collected normal stream magnitude initialization data discharge model.Then subsequent acquisition data traffic is handled
Analysis exports handling result.If data traffic normally if update the data flow model, if data exception, the output phase answer early warning,
Warning message deletes data.
As shown in Figure 1, specific method of the present invention is as follows：
1) the appliance services communication port in the TDCS/CTC systems for needing to detect installs flow detection module.
2) gathered data rejects fault data.
3) reception, transmission data discharge model are established according to normal data.
4) data analysis is carried out to port detection flows using data traffic model.
5) analysis result is exported, if normally going to step 6), if abnormal go to step 7).
6) data analysis is normal, updates the data flow model.
7) data analysis is abnormal, if abnormal data falls within early warning section, step 8) is gone to, if abnormal data falls within alarm
Section then goes to step 9).
8) Exception Type I exports warning information, maintenance personnel is reminded to pay attention to safeguarding, suppressing exception data.
9) Exception Type II exports warning message, maintenance personnel is reminded to be safeguarded, suppressing exception data.
10) terminate.
As shown in Fig. 2, the detailed process of data traffic model foundation of the present invention is as follows：
1) with 10 seconds for the traffic statistics period, statistics port flow receives, transmission data.
2) according to equipment running status, the statistical data during failure is rejected.
3) it by the reception data traffic point line of continuous measurement period, forms day statistics and receives days systems of data traffic Qu Xian
Count transmission data flow curve.
4) the day sending and receiving data traffic curve of 30 days is counted, calculating forms day statistics and receives data traffic average value curve
Transmission data flow average value curve is counted with day.
5) normal distribution curve of each collection point reception and transmission data flow is calculated, forms the data being distributed according to the time period
Discharge model, model foundation are completed.
As shown in figure 3, μ is flow mean value of a certain collection point after long-time counts in figure, δ is acquired for the time point
The variance of flow reacts the degree of scatter that the collection point flow deviates mean value.
The calculation formula of the μ is as follows：X in formulakData on flows is acquired for kth time,It is the distribution law of X, it is definite value that system, which completes E (X) value after initialization, as μ.Afterwards
Phase system operation time is longer, and μ values are more accurate, and the model of foundation also can be more accurate.
The calculation formula of the δ is as follows：Wherein P { X=xk}=pk, k=1,2 ...
It is the distribution law of X.System complete initialization after D (X) value be definite value, as δ.Later stage system operation time is longer, and δ values are got over
Accurately, the model of foundation also can be more accurate.
The data traffic model application that the present invention is distributed according to the time period is as follows：
1) the port input of N~N+2 continuous measurement periods, Output estimation data in any time period are inputted.
2) by three collection point gathered datas input corresponding periods receive day data traffic normal distribution curve and
Day transmission data flow normal distribution curve.
3) section where judging each collection point according to fig. 3, if 3 measurement period data perform step in normal interval
It is rapid 4), if 3 measurement period data perform step 5) in early warning section, if 3 measurement period data are in zone of alarm
Between, then step 6) is performed, other situations then update port input, output of the input data for N+1~N+3 continuous measurement periods
Flow detection data re-execute step 2), 3).
4) data output is normal, updates the data flow model.
5) data output abnormality carries out early warning to the port, maintenance personnel is reminded to safeguard that the port corresponds to equipment, is deleted
Except data.
6) data output abnormality, alarm is carried out to the port, and equipment where reminding the repaired port is deleted
Except data.
The above description is merely a specific embodiment, but protection scope of the present invention is not limited thereto, any
Those familiar with the art in the technical scope disclosed by the present invention, can readily occur in various equivalent modifications or replace
It changes, these modifications or substitutions should be covered by the protection scope of the present invention.Therefore, protection scope of the present invention should be with right
It is required that protection domain subject to.
Claims (6)
- A kind of 1. TDCS/CTC system early warning methods based on port data flow monitoring, which is characterized in that based on to TDCS/ The daily detecting of each device port data traffic of CTC system and statistical modeling compare the flow and modeling data that currently acquire, The early warning of the TDCS/CTC system failures and alarm are carried out according to the rule of setting.
- 2. a kind of TDCS/CTC system early warning methods based on port data flow monitoring according to claim 1, special Sign is that the method for early warning includes the following steps：(1) it monitors and counts each daily data traffic in business device port of TDCS/CTC systems；(2) the daily data traffic of each business device of TDCS/CTC systems is modeled, forms the data being distributed according to the time period Discharge model；(3) each business device port communication flow is monitored, is less than or during more than day normal flow average value setting range when detecting Early warning is carried out, is less than or more than defined warning value when alarms；(4) by early warning and warning message, bonding apparatus log information is analyzed and fault point, further fixes a breakdown.
- 3. a kind of TDCS/CTC system early warning methods based on port data flow monitoring according to claim 2, special Sign is that the method for early warning is specially：1) objects of statistics that the appliance services communication port in TDCS/CTC systems is monitored as daily port flow is chosen；2) using the period that daily port flow monitors as N seconds as the traffic statistics period；3) data traffic that the port sends and receivees is counted within the traffic statistics period；4) it is formed using measurement period as the time shaft of minimum time resolution ratio, to receive data traffic and transmission data flow as number According to the data traffic figure sended and received of amount axis；5) the reception data traffic point line of continuous measurement period is formed into day statistics and receives data traffic curve；6) the transmission data flow point line of continuous measurement period is formed into day statistics transmission data flow curve；7) continuous statistics forms day statistics reception data traffic average value curve and day statistics transmission data flow is averaged after D days It is worth curve；8) it then needs to reject age at failure statistical data such as faulty generation in statistic processes；9) it is counted using day and receives data traffic average value curve and count transmission data flow average value curve day, calculating is respectively adopted Collection point receives and the normal distribution curve of transmission data flow, repeats step 2)~8) different periods are handled, formation is pressed The data traffic model of period distribution where collection point；10) current device port flow is monitored, day statistics is generated in real time and sends and receivees data traffic curve, when continuously there is M A measurement period is less than or carries out early warning more than early warning value；11) current device port flow is monitored, day statistics is generated in real time and sends and receivees data traffic curve, when continuously there is M A measurement period is less than or alarms more than warning value；12) according to early warning and warning message, device log analysis and positioning failure are called.
- 4. a kind of TDCS/CTC system early warning methods based on port data flow monitoring according to claim 3, special Sign is that the N seconds are 10 seconds, and D days are 30 days, and M are 3.
- 5. a kind of TDCS/CTC system early warning methods based on port data flow monitoring according to claim 3, special Sign is, described continuous M measurement period occur and be less than or be specially more than early warning value：The day statistics of year-on-year same time period Reception or the P% of transmission data flow average value, fall within data traffic model pre-warning section；Described continuous there is M measurement period and be less than or be specially more than warning value：The day statistics of year-on-year same time period connects The Q% of receipts or transmission data flow average value falls within data traffic model alarm section.
- 6. a kind of TDCS/CTC system early warning methods based on port data flow monitoring according to claim 5, special Sign is that the P% is 15%, Q% 30%.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109271346A (en) * | 2018-08-21 | 2019-01-25 | 深圳市长龙铁路电子工程有限公司 | A kind of browsing method of railway signal analog quantity curve |
| CN109547283A (en) * | 2018-10-23 | 2019-03-29 | 日海通信服务有限公司 | A kind of intelligent communication service method and system |
| CN109787973A (en) * | 2019-01-11 | 2019-05-21 | 积成电子股份有限公司 | A kind of calculation method of network safety situation index system |
| CN113556241A (en) * | 2020-04-24 | 2021-10-26 | 北京淇瑀信息科技有限公司 | Upstream flow monitoring method and device and electronic equipment |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101155085A (en) * | 2006-09-29 | 2008-04-02 | 中兴通讯股份有限公司 | Method and device for real-time flux prediction and real-time flux monitoring and early warning |
| CN102122374A (en) * | 2011-03-03 | 2011-07-13 | 江苏方天电力技术有限公司 | Intelligent analysis system for flow abnormity of power automation system |
| CN105634850A (en) * | 2014-11-04 | 2016-06-01 | 中国移动通信集团广东有限公司 | Traffic modeling method and apparatus for PTN network |
-
2016
- 2016-12-14 CN CN201611154023.3A patent/CN108234162A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101155085A (en) * | 2006-09-29 | 2008-04-02 | 中兴通讯股份有限公司 | Method and device for real-time flux prediction and real-time flux monitoring and early warning |
| CN102122374A (en) * | 2011-03-03 | 2011-07-13 | 江苏方天电力技术有限公司 | Intelligent analysis system for flow abnormity of power automation system |
| CN105634850A (en) * | 2014-11-04 | 2016-06-01 | 中国移动通信集团广东有限公司 | Traffic modeling method and apparatus for PTN network |
Non-Patent Citations (2)
| Title |
|---|
| 邹柏贤: "一种网络异常实时检测方法", 《计算机学报》 * |
| 邹柏贤等: "基于ARMA模型的网络流量预测", 《计算机研究与发展》 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109271346A (en) * | 2018-08-21 | 2019-01-25 | 深圳市长龙铁路电子工程有限公司 | A kind of browsing method of railway signal analog quantity curve |
| CN109547283A (en) * | 2018-10-23 | 2019-03-29 | 日海通信服务有限公司 | A kind of intelligent communication service method and system |
| CN109547283B (en) * | 2018-10-23 | 2022-06-14 | 日海通信服务有限公司 | Intelligent communication service method and system |
| CN109787973A (en) * | 2019-01-11 | 2019-05-21 | 积成电子股份有限公司 | A kind of calculation method of network safety situation index system |
| CN113556241A (en) * | 2020-04-24 | 2021-10-26 | 北京淇瑀信息科技有限公司 | Upstream flow monitoring method and device and electronic equipment |
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