CN109683058A - A kind of urban rail transit contact network method for comprehensive detection based on big data - Google Patents
A kind of urban rail transit contact network method for comprehensive detection based on big data Download PDFInfo
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- CN109683058A CN109683058A CN201811585391.2A CN201811585391A CN109683058A CN 109683058 A CN109683058 A CN 109683058A CN 201811585391 A CN201811585391 A CN 201811585391A CN 109683058 A CN109683058 A CN 109683058A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60M—POWER SUPPLY LINES, AND DEVICES ALONG RAILS, FOR ELECTRICALLY- PROPELLED VEHICLES
- B60M1/00—Power supply lines for contact with collector on vehicle
- B60M1/12—Trolley lines; Accessories therefor
- B60M1/28—Manufacturing or repairing trolley lines
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- Engineering & Computer Science (AREA)
- Manufacturing & Machinery (AREA)
- Mechanical Engineering (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Current-Collector Devices For Electrically Propelled Vehicles (AREA)
- Train Traffic Observation, Control, And Security (AREA)
Abstract
The present invention provides a kind of urban rail transit contact network method for comprehensive detection based on big data, comprising: comprehensive detection S1, is carried out to bow net information by detection system, and will test information and be sent to big data analysis system and complex datahandling centre；S2, comprehensive analysis is carried out to the information detected by big data analysis system, the Classification and Identification of " normal ", " failure " is realized for feature；S3, creation experts database；S4, big data sample database is created in conjunction with experts database, for carrying out intelligent recognition to subsequent bow net information；The expert info stored in new collected bow net information and experts database is compared identification by S5, complex datahandling centre.Urban rail transit contact network method for comprehensive detection of the present invention based on big data realizes comprehensive analysis, integrated treatment function to contact net, pantograph data；The detection of railway traffic contact network is set gradually to realize automation, intelligence, synthesization.
Description
Technical field
The invention belongs to technical field of rail traffic, contact more particularly, to a kind of urban track traffic based on big data
Net method for comprehensive detection.
Background technique
As a kind of environmentally protective, economic comfortable public transportation means, urban track traffic has become China city
The important tool of city people trip, plays increasingly important role to the development in city.Contact net is urban track traffic weight
The power supply facilities wanted, and due to its particularity, no stand-by facility will cause withdrawal of train, to cause once contact net damages
Heavy economic losses.And pantograph obtains the important component of electric energy as train from contact net, when damage, not only may cause column
Vehicle is stopped transport, and is also possible to that contact net can be damaged when serious.Therefore, contact net is often detected and is tieed up with pantograph needs
Shield, to generate a large amount of detection datas, these data carry the important information of contact net, pantograph.Previous contact net inspection
Survey device due to respectively it is independent, homologous ray not cannot achieve information sharing, cannot unify using these data progress comprehensive analysis,
It cannot achieve the effective use of information.
Summary of the invention
In view of this, the present invention is directed to propose a kind of urban rail transit contact network comprehensive detection side based on big data
Method can not achieve information sharing to solve the problem of that the detection of previous contact net can only carry out independent detection.
In order to achieve the above objectives, the technical scheme of the present invention is realized as follows:
A kind of urban rail transit contact network method for comprehensive detection based on big data, comprising:
S1, comprehensive detection is carried out to bow net information by detection system, and will test information and is sent to big data analysis system
System and complex datahandling centre；
S2, comprehensive analysis is carried out to the information that detects by big data analysis system, and based on the analysis results in spy
Sign establishes corresponding feature database, and the Classification and Identification of " normal ", " failure " is realized for feature；
S3, creation experts database, " normal " that big data analysis network analysis identifies, " failure " result are deposited into specially respectively
In family library；
S4, big data sample database is created in conjunction with experts database, for carrying out intelligent recognition to subsequent bow net information；
S5, complex datahandling centre carry out the expert info stored in new collected bow net information and experts database pair
Than identification, to realize to the intelligent recognition of bow net state and display, warning function.
Further, the detection system in the step S1 includes vehicle-mounted detection unit, and the vehicle-mounted detection unit is mounted in
It runs on vehicle, for acquiring received contact net relevant information on vehicle.
Further, the vehicle-mounted detection unit includes optical pickup, ultraviolet light photo sensing device, infrared measurement of temperature dress
It sets, integrated positioning device, Data Analysis Services and display device；Contact net position data, contact net during realization train operation
The acquisition of the data such as temperature data, bow net arcing image and data, suspension image；And by Data Analysis Services system into
Row preliminary analysis, to import big data analysis system；
Big data analysis system in step S2 extracts each section of contact net according to the collection result of vehicle-mounted detection unit
Correlated characteristic establishes contact net information characteristics library, and the Classification and Identification of " normal ", " failure " is realized for feature, imports expert
Library.
Further, in the step S1, the detection system further includes ground detection unit, the ground detection unit
It is mounted on ground fixed position, for collecting the pantograph image information for carrying out train.
Further, the ground detection unit includes front-end collection equipment and background analysis analysis；Front-end collection equipment
Including photoelectric trigger device, high-definition camera, high definition camera, flash lamp, light compensating lamp, control device, power supply；It adopts the front end
Collection equipment is for taking the pantograph image for carrying out vehicle；Background analysis equipment is for storing pantograph image and tentatively being divided
Analysis is to import big data analysis system；
Big data analysis system in step S2 is according to the testing result of ground detection unit, for every kind of model pantograph
Pantograph feature database is established, and realizes the Classification and Identification of " normal ", " failure " for feature, imports experts database.
Further, the big data analysis system in the step S2 includes server and floor array.
Further, the creation big data sample database in the step S4 includes the foundation of training sample database, the training
The method for building up of sample database is as follows:
It is carried out firstly the need of the collected mass data of vehicle-mounted detection unit and ground detection unit that will test in system
Normal information is put into normal library by manual identified, and exception information is put into fault database, and is built by support vector machines (SVM) algorithm
Vertical SVM classifier, forms training sample database.
Further, in the step S4, the method for building up of big data sample database is as follows:
In the operation of contact net comprehensive detection system, the contact net of acquisition, pantograph information extract after pretreatment
Contact net correlated characteristic, pantograph correlated characteristic, and classified by trained SVM classifier, obtained normal contact
Net, pantograph information are put into normal library, and abnormal contact net, pantograph information are put into fault database, as sample is continuously increased constantly
Correct library and fault database sample are enriched, and improves SVM classifier automatically, forms big data sample database.
Compared with the existing technology, the urban rail transit contact network method for comprehensive detection of the present invention based on big data
It has the advantage that
Urban rail transit contact network method for comprehensive detection of the present invention based on big data with realize to contact net,
Comprehensive analysis, the integrated treatment function of pantograph data；The detection of railway traffic contact network is set gradually to realize automation, intelligence
Change, synthesization.
Detailed description of the invention
The attached drawing for constituting a part of the invention is used to provide further understanding of the present invention, schematic reality of the invention
It applies example and its explanation is used to explain the present invention, do not constitute improper limitations of the present invention.In the accompanying drawings:
Fig. 1 is the urban rail transit contact network method for comprehensive detection system based on big data described in the embodiment of the present invention
Architecture diagram；
Fig. 2 is the visioning procedure figure of training sample database described in the embodiment of the present invention；
Fig. 3 is the visioning procedure figure of big data sample database described in the embodiment of the present invention.
Specific embodiment
It should be noted that in the absence of conflict, the feature in embodiment and embodiment in the present invention can phase
Mutually combination.
In the description of the present invention, it is to be understood that, term " center ", " longitudinal direction ", " transverse direction ", "upper", "lower",
The orientation or positional relationship of the instructions such as "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outside" is
It is based on the orientation or positional relationship shown in the drawings, is merely for convenience of description of the present invention and simplification of the description, rather than instruction or dark
Show that signified device or element must have a particular orientation, be constructed and operated in a specific orientation, therefore should not be understood as pair
Limitation of the invention.In addition, term " first ", " second " etc. are used for description purposes only, it is not understood to indicate or imply phase
To importance or implicitly indicate the quantity of indicated technical characteristic.The feature for defining " first ", " second " etc. as a result, can
To explicitly or implicitly include one or more of the features.In the description of the present invention, unless otherwise indicated, " multiple "
It is meant that two or more.
In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, term " installation ", " phase
Even ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；It can
To be mechanical connection, it is also possible to be electrically connected；It can be directly connected, can also can be indirectly connected through an intermediary
Connection inside two elements.For the ordinary skill in the art, above-mentioned term can be understood by concrete condition
Concrete meaning in the present invention.
The present invention will be described in detail below with reference to the accompanying drawings and embodiments.
As shown in Figure 1, a kind of urban rail transit contact network method for comprehensive detection based on big data, comprising:
S1, comprehensive detection is carried out to bow net information by detection system, and will test information and is sent to big data analysis system
System and complex datahandling centre；
S2, comprehensive analysis is carried out to the information that detects by big data analysis system, and based on the analysis results in spy
Sign establishes corresponding feature database, and the Classification and Identification of " normal ", " failure " is realized for feature；
S3, creation experts database, " normal " that big data analysis network analysis identifies, " failure " result are deposited into specially respectively
In family library；
S4, big data sample database is created in conjunction with experts database, for carrying out intelligent recognition to subsequent bow net information；
S5, complex datahandling centre carry out the expert info stored in new collected bow net information and experts database pair
Than identification, to realize to the functions such as the intelligent recognition of bow net state and display, alarm.
Detection system in the step S1 includes vehicle-mounted detection unit, and the vehicle-mounted detection unit is mounted in operation vehicle
On, for acquiring received contact net relevant information on vehicle.
The vehicle-mounted detection unit includes optical pickup, ultraviolet light photo sensing device, infrared temperature measurement apparatus, integrates and determine
Position device, Data Analysis Services and display device；Realize train operation during contact net position data, contact net temperature data,
The acquisition of the data such as bow net arcing image and data, suspension image；And tentatively divided by Data Analysis Services system
Analysis, to import big data analysis system；
Big data analysis system in step S2 extracts each section of contact net according to the collection result of vehicle-mounted detection unit
Correlated characteristic establishes contact net information characteristics library, and the Classification and Identification of " normal ", " failure " is realized for feature, imports expert
Library.
In the step S1, the detection system further includes ground detection unit, and the ground detection unit is mounted on ground
Position is fixed in face, for collecting the pantograph image information for carrying out train.
The ground detection unit includes front-end collection equipment and background analysis analysis；Front-end collection equipment includes photoelectricity touching
Transmitting apparatus, high-definition camera, high definition camera, flash lamp, light compensating lamp, control device, power supply；The front-end collection equipment is used for
Take the pantograph image for carrying out vehicle；Background analysis equipment is big to import for storing pantograph image and carrying out preliminary analysis
Data analysis system；
Big data analysis system in step S2 is according to the testing result of ground detection unit, for every kind of model pantograph
Pantograph feature database is established, and realizes the Classification and Identification of " normal ", " failure " for feature, imports experts database.
Big data analysis system in the step S2 includes server and floor array.
As shown in Fig. 2, the creation big data sample database in the step S4 includes the foundation of training sample database, the training
The method for building up of sample database is as follows:
It is carried out firstly the need of the collected mass data of vehicle-mounted detection unit and ground detection unit that will test in system
Normal information is put into normal library by manual identified, and exception information is put into fault database, and is built by support vector machines (SVM) algorithm
Vertical SVM classifier, forms training sample database.
As shown in figure 3, the method for building up of big data sample database is as follows in the step S4:
In the operation of contact net comprehensive detection system, the contact net of acquisition, pantograph information extract after pretreatment
Contact net correlated characteristic, pantograph correlated characteristic, and classified by trained SVM classifier, obtained normal contact
Net, pantograph information are put into normal library, and abnormal contact net, pantograph information are put into fault database, as sample is continuously increased constantly
Correct library and fault database sample are enriched, and improves SVM classifier automatically, forms big data sample database.
Automation, intelligent, synthesization are the directions of following development of urban rail transit contact network detection, and big data is
Push Contact Line Detection System automation, intelligent, synthesization development favourable conditions.Due to the limitation of technical level, China
The development of track transportation industry big data is also in the elementary step, and experts database is there are also to be improved, as track traffic synthetic detects
Systematic difference and improvement, contact net informix processing capacity will obtain bigger development.
The foregoing is merely illustrative of the preferred embodiments of the present invention, is not intended to limit the invention, all in essence of the invention
Within mind and principle, any modification, equivalent replacement, improvement and so on be should all be included in the protection scope of the present invention.
Claims (8)
1. a kind of urban rail transit contact network method for comprehensive detection based on big data characterized by comprising
S1, by detection system to bow net information carry out comprehensive detection, and will test information be sent to big data analysis system and
Complex datahandling centre；
S2, comprehensive analysis is carried out to the information that detects by big data analysis system, and based on the analysis results in feature build
Corresponding feature database is found, the Classification and Identification of " normal ", " failure " is realized for feature；
S3, creation experts database, are deposited into experts database for " normal " that big data analysis network analysis identifies, " failure " result respectively
In；
S4, big data sample database is created in conjunction with experts database, for carrying out intelligent recognition to subsequent bow net information；
The expert info stored in new collected bow net information and experts database is compared knowledge by S5, complex datahandling centre
Not, to realize to the intelligent recognition of bow net state and display, warning function.
2. the urban rail transit contact network method for comprehensive detection according to claim 1 based on big data, feature exist
In: the detection system in the step S1 includes vehicle-mounted detection unit, and the vehicle-mounted detection unit is used on operation vehicle
Acquire received contact net relevant information on vehicle.
3. the urban rail transit contact network method for comprehensive detection according to claim 2 based on big data, feature exist
In: the vehicle-mounted detection unit includes optical pickup, ultraviolet light photo sensing device, infrared temperature measurement apparatus, comprehensive positioning dress
It sets, Data Analysis Services and display device；Contact net position data, contact net temperature data, bow net during realization train operation
The acquisition of the data such as arcing image and data, suspension image；And preliminary analysis is carried out by Data Analysis Services system, with
Import big data analysis system；
Big data analysis system in step S2 is extracted each section of contact net related according to the collection result of vehicle-mounted detection unit
Feature establishes contact net information characteristics library, and the Classification and Identification of " normal ", " failure " is realized for feature, imports experts database.
4. the urban rail transit contact network method for comprehensive detection according to claim 1 based on big data, feature exist
In: in the step S1, the detection system further includes ground detection unit, and the ground detection unit is mounted on ground and fixes
Position, for collecting the pantograph image information for carrying out train.
5. the urban rail transit contact network method for comprehensive detection according to claim 4 based on big data, feature exist
In: the ground detection unit includes front-end collection equipment and background analysis analysis；Front-end collection equipment includes photoelectricity triggering dress
It sets, high-definition camera, high definition camera, flash lamp, light compensating lamp, control device, power supply；The front-end collection equipment is for shooting
The pantograph image of arrival vehicle；Background analysis equipment is for storing pantograph image and carrying out preliminary analysis to import big data
Analysis system；
Big data analysis system in step S2 is established according to the testing result of ground detection unit for every kind of model pantograph
Pantograph feature database, and for feature realization " normal ", the Classification and Identification of " failure ", import experts database.
6. the urban rail transit contact network method for comprehensive detection according to claim 1 based on big data, feature exist
In: the big data analysis system in the step S2 includes server and floor array.
7. the urban rail transit contact network method for comprehensive detection according to claim 1 based on big data, feature exist
In: the creation big data sample database in the step S4 includes the foundation of training sample database, the foundation side of the training sample database
Method is as follows:
It is carried out firstly the need of the collected mass data of vehicle-mounted detection unit and ground detection unit that will test in system artificial
Identification, is put into normal library for normal information, exception information is put into fault database, and establishes SVM by support vector machines (SVM) algorithm
Classifier forms training sample database.
8. the urban rail transit contact network method for comprehensive detection according to claim 1 based on big data, feature exist
In in the step S4, the method for building up of big data sample database is as follows:
In the operation of contact net comprehensive detection system, the contact net of acquisition, pantograph information extract contact after pretreatment
Net correlated characteristic, pantograph correlated characteristic, and classified by trained SVM classifier, obtained normal contact net, by
Pantograph information is put into normal library, and abnormal contact net, pantograph information are put into fault database, constantly enriches just as sample is continuously increased
True library and fault database sample, and SVM classifier is improved automatically, form big data sample database.
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| CN116228170A (en) * | 2023-05-06 | 2023-06-06 | 中铁电气化勘测设计研究院有限公司 | Data intercommunication construction method for project data integrated management platform |
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Application publication date: 20190426 |