CN112367637B - Method, device, computer storage medium and terminal for realizing early warning processing - Google Patents
Method, device, computer storage medium and terminal for realizing early warning processing Download PDFInfo
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Abstract
The embodiment of the application obtains train operation data corresponding to each calling service, and merges train operation data with an absolute value of the time difference larger than a preset duration threshold into section analysis data for operation section analysis by determining a time difference of operation time contained in adjacent train operation data; determining a running mileage section of each train according to the analysis data of each line of each train; the automatic early warning of the wireless overtime zone is realized for the running mileage zone meeting the early warning condition through the statistics of the number of zone data obtained by integration in a preset statistical period and the train corresponding to the zone data, and the running reliability of the high-speed train is improved.
Description
Technical Field
The present disclosure relates to, but not limited to, traffic communication technologies, and in particular, to a method, an apparatus, a computer storage medium, and a terminal for implementing early warning processing.
Background
With the rapid development of big data technology and artificial intelligence technology, more and more related applications are fully utilized in the internet field, but are limited by some factors, and in the traditional technical field, these advanced technologies are not fully utilized yet.
The CTCS-3 (C3 for short) system is a train operation control system which supports the highest train operation speed in China at present, and takes a communication network of a global system for mobile communications (GSM-R) for Railways as a train-ground bidirectional safe data transmission channel; the C3 system mainly comprises two major key components of train overspeed protection (ATP, automatic Train Protection) and ground radio block center (RBC, radio Blocking Center).
Most of the current railway maintenance level is still at the level of manually finding and manually analyzing faults, so that the faults cannot be predicted, wherein, how to predict the wireless timeout section provides a guarantee for the reliable operation of the C3 system is a problem to be solved.
Disclosure of Invention
The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.
The embodiment of the application provides a method, a device, a computer storage medium and a terminal for realizing early warning processing, which can realize automatic early warning of a wireless overtime section and improve the running reliability of a high-speed train.
The embodiment of the application provides a method for realizing early warning processing, which comprises the following steps:
for each call service, acquiring a group of train operation data;
for each group of train operation data, according to the operation time in the train operation data, combining two adjacent train operation data with the interval time length longer than a preset interval time length threshold value into one section analysis data for section analysis;
determining a mileage section of a train running continuously in a line according to kilometer posts for section analysis data in a preset time length of each line of each train, and integrating the determined mileage section and the section analysis data for determining the mileage section into one section data;
determining whether to perform wireless overtime early warning on the mileage section according to the number of section data obtained through integration in a preset statistical period and the statistics of trains corresponding to the section data;
the train operation data are sequenced according to time sequence; the train operation data includes: the running time T and kilometer post K of the train; the statistical period comprises N preset time periods, wherein N is an integer greater than or equal to 2; the determining the mileage section of the train running continuously in the line according to the kilometer post comprises the following steps: section analysis data of each line of each train within a preset time length are analyzed, and whether the mileage of running trains has intersection or not is determined according to kilometer posts in the section analysis data; when determining that the mileage of the train operation has an intersection, determining a mileage section of the train continuously running in the line according to the kilometer post in the section analysis data with the intersection; the starting kilometer post of the mileage section is: the mileage of train operation has the minimum kilometer post in all section analysis data of intersection; the termination kilometer post of the mileage zone is: the mileage of train operation has the maximum kilometer post in all section analysis data of intersection; determining whether the mileage of the train operation has an intersection or not according to the kilometer post in the section analysis data, wherein the section analysis data in the preset time length of each line of each train is selected for each time, and two of the section analysis data are compared as follows to determine whether the mileage of the train operation has the intersection or not: the method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a smaller kilometer label in selected second section analysis data and smaller than the larger kilometer label in selected second section analysis data, and when the smaller kilometer label in selected first section analysis data is smaller than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; the method comprises the steps that a larger kilometer label in selected second section analysis data is smaller than a larger kilometer label in selected first section analysis data, is larger than a smaller kilometer label in selected first section analysis data, and when the smaller kilometer label in selected first section analysis data is larger than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; the method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a larger kilometer label and a smaller kilometer label in selected second section analysis data, and when the smaller kilometer label in selected second section analysis data is larger than the smaller kilometer label in selected first section analysis data, the existence intersection of the mileage of the train operation is determined; and determining that the crossing sets exist in the mileage of the train when the larger kilometer label in the selected second section analysis data is larger than the larger kilometer label and the smaller kilometer label in the selected first section analysis data is larger than the smaller kilometer label in the selected second section analysis data.
On the other hand, the embodiment of the application also provides a computer storage medium, wherein a computer program is stored in the computer storage medium, and the method for realizing the early warning processing is realized when the computer program is executed by a processor.
In still another aspect, an embodiment of the present application further provides a terminal, including: a memory and a processor, the memory storing a computer program; wherein,,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by the processor, implements a method for implementing early warning processing as described above.
In still another aspect, an embodiment of the present application further provides an apparatus for implementing early warning processing, including: the system comprises an acquisition unit, a merging unit, an integrated mileage unit and an early warning unit; wherein,,
the acquisition unit is configured to: for each call service, acquiring a group of train operation data;
the merging unit is configured to: for each group of train operation data, according to the operation time in the train operation data, combining two adjacent train operation data with the interval time longer than the preset interval time threshold value into one section analysis data for section analysis
The integrated mileage unit is set as follows: determining a mileage section of a train running continuously in a line according to kilometer posts for section analysis data in a preset time length of each line of each train, and integrating the determined mileage section and the section analysis data for determining the mileage section into one section data; determining a mileage zone of continuous running of the train in the line according to the kilometer post, comprising: section analysis data of each line of each train in a preset time length are analyzed, and whether intersection exists in mileage of train operation is determined according to kilometer posts in the section analysis data; when determining that the mileage of the train running has an intersection, determining a mileage section of the train running continuously in the line according to the kilometer post in the section analysis data with the intersection; the starting kilometer label of the mileage zone is: the mileage of train operation has the minimum kilometer post in all section analysis data of intersection; the ending kilometers of the mileage zone are marked as: the mileage of train operation has the maximum kilometer post in all section analysis data of intersection; determining whether the mileage of the train operation has an intersection or not according to the kilometer post in the section analysis data, wherein the section analysis data in the preset time length of each line of each train is selected for each time, and two of the section analysis data are compared as follows to determine whether the mileage of the train operation has the intersection or not: the method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a smaller kilometer label in selected second section analysis data and smaller than the larger kilometer label in selected second section analysis data, and when the smaller kilometer label in selected first section analysis data is smaller than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; the method comprises the steps that a larger kilometer label in selected second section analysis data is smaller than a larger kilometer label in selected first section analysis data, is larger than a smaller kilometer label in selected first section analysis data, and when the smaller kilometer label in selected first section analysis data is larger than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; the method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a larger kilometer label and a smaller kilometer label in selected second section analysis data, and when the smaller kilometer label in selected second section analysis data is larger than the smaller kilometer label in selected first section analysis data, the existence intersection of the mileage of the train operation is determined; the method comprises the steps that a larger kilometer label in the selected second section analysis data is larger than a larger kilometer label and a smaller kilometer label in the selected first section analysis data, and when the smaller kilometer label in the selected first section analysis data is larger than the smaller kilometer label in the selected second section analysis data, the intersection of the mileage of the train running is determined;
the early warning unit is arranged as follows: determining whether to perform wireless overtime early warning on the mileage section according to the number of section data obtained through integration in a preset statistical period and the statistics of trains corresponding to the section data;
the train operation data are sequenced according to time sequence; the train operation data includes: the running time T and kilometer post K of the train; the statistical period comprises N preset time periods, and N is an integer greater than or equal to 2.
According to the embodiment of the application, train operation data corresponding to each call service are acquired, the time difference value of adjacent train operation data is determined, and the train operation data with the absolute value of the time difference value larger than the preset duration threshold value are combined into section analysis data for overtime early warning judgment; determining a mileage zone of train operation for zone analysis data of each line of each train; by counting the section data containing the mileage section in the counting period, the automatic early warning of the wireless overtime section is realized for the mileage section meeting the set early warning condition, and the running reliability of the high-speed train is improved.
Additional features and advantages of the application will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the application. The objectives and other advantages of the application will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings are included to provide a further understanding of the application and are incorporated in and constitute a part of this specification, illustrate and do not limit the application.
FIG. 1 is a flow chart of a method for implementing early warning processing according to an embodiment of the present application;
fig. 2 is a block diagram of a device for implementing early warning processing according to an embodiment of the present application.
Detailed Description
For the purpose of making the objects, technical solutions and advantages of the present application more apparent, embodiments of the present application will be described in detail hereinafter with reference to the accompanying drawings. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be arbitrarily combined with each other.
The steps illustrated in the flowchart of the figures may be performed in a computer system, such as a set of computer-executable instructions. Also, while a logical order is depicted in the flowchart, in some cases, the steps depicted or described may be performed in a different order than presented herein.
FIG. 1 is a flowchart of a method for implementing early warning processing according to an embodiment of the present application, as shown in FIG. 1, including:
step 101, obtaining a group of train operation data for each calling service;
in an exemplary embodiment, the call service of the embodiment of the present application includes: in the C3 system, vehicle train overspeed protection (ATP) carries out calling service to a ground Radio Block Center (RBC); the embodiment of the application can load the data corresponding to the call service according to the day in the communication interface for transmitting the call service from the C3 system. The train operation data may be obtained by those skilled in the art from packets of the call service containing train operation data according to protocol specifications, including but not limited to: an Application Protocol Data Unit (APDU) 136 packet or an APDU129 packet; the train operation data may include one or any combination of the following: train identity information, line information, train running time T and kilometer post K; the statistical period comprises N preset time periods. Here, the train identity information may include: calling mobile subscriber number (MSISDN); the line information may include: line identity number (ID).
In one illustrative example, each set of train operation data acquired in the practice of the present application is ordered within the set in chronological order.
102, combining two adjacent pieces of train operation data with interval time length longer than a preset interval time length threshold value into one piece of section analysis data for section analysis according to the operation time in each group of train operation data;
the method is characterized in that data which is frequently generated when train operation data are transmitted; in the process of calling service, the embodiment of the application generally distinguishes train operation data through sequence numbers including N_R; taking n_r as an example of a sequential number, two adjacent pieces of train operation data include: when the sequence number N_R1 is changed to N_R2, one piece of train operation data with the sequence number N_R1 and one piece of train operation data with the sequence number N_R2 are obtained; for train operation data with the same n_r, the specific selection of which one is used for making the judgment of the interval duration may be preset by those skilled in the art.
In one illustrative example, the interval duration of two adjacent pieces of train operation data may be calculated as follows:
acquiring the running time of a train in the running data of two adjacent trains;
taking an absolute value after the difference of the two obtained running times, and taking the absolute value as the interval duration.
Here, the merging of train operation data is only to perform the following simple data arrangement: removing the same part in the two pieces of train operation data; the different parts are reserved according to a preset arrangement sequence; for example, if the train identity information and the line information in the two pieces of train operation data are the same, any one of the two pieces of train operation data is reserved, and if the train operation time T and the kilometer post K are different, the two pieces of train operation data are reserved according to a preset arrangement sequence, including but not limited to the following arrangement sequence: sequencing the time T and the kilometer post K of train operation in the preceding train operation data, and sequencing the time T and the kilometer post K of train operation in the following train operation data; in an exemplary embodiment, the embodiment of the present application may also generate the section analysis data according to other set information arrangements.
In an exemplary embodiment, the interval duration threshold in the embodiment of the present application may be set by those skilled in the art according to the timeout duration of the section pre-warning; for example, if the mileage zone is considered to be at a security risk based on an empirical mileage zone wireless timeout of greater than 20 seconds, the interval duration threshold may be set to a value less than 20 seconds, such as 15 seconds.
Step 103, determining a mileage section of a train running continuously in a line according to kilometer posts for section analysis data in a preset time length of each line of each train, and integrating the determined mileage section and the section analysis data for determining the mileage section into one section data;
in one illustrative example, the train and route to which it belongs may be determined from train identity information and route information contained in the section analysis data.
In an exemplary embodiment, the preset time period may be determined according to an operation period of the high-speed railway; the preset time period may be set to one day in one illustrative example.
In one illustrative example, the zone data includes, in addition to the mileage zone, train identity information, route information, and the like in zone analysis data that determines the mileage zone.
Step 104, determining whether to perform wireless overtime early warning on the mileage section according to the number of section data obtained by integration in a preset statistical period and the statistics of trains corresponding to the section data;
in an exemplary embodiment, the statistical period of the embodiment of the present application includes N preset durations, where N is an integer greater than or equal to 2; for example, N is equal to 30, which can be set and adjusted empirically by those skilled in the art.
In one illustrative example, the train to which the zone data corresponds may be determined based on train identity information in the zone data.
According to the embodiment of the application, train operation data corresponding to each calling service are acquired, and the train operation data with the absolute value of the time difference larger than the preset duration threshold value are combined into section analysis data for operation section analysis by determining the time difference of operation time contained in adjacent train operation data; determining a running mileage section of each train according to the analysis data of each line of each train; the automatic early warning of the wireless overtime zone is realized for the running mileage zone meeting the early warning condition through the statistics of the number of zone data obtained by integration in a preset statistical period and the train corresponding to the zone data, and the running reliability of the high-speed train is improved.
In an exemplary embodiment, before step 102 is combined into a piece of section analysis data for section analysis, the method according to the embodiment of the present application further includes:
and respectively smoothing the acquired running data of each group of trains.
According to the embodiment of the application, the train operation data can be prevented from jumping by carrying out smooth processing on the train operation data.
In an exemplary embodiment, the train operation information in the embodiment of the present application further includes a speed S of train operation, and the smoothing process for the acquired train operation data includes:
of two adjacent train operation data, kilometer post K of the preceding train operation data is ordered 1 Kilometer post K equal to train operation data ordered later 2 At the time, set up:
kilometer post of train operation data sequenced later is equal to K 1 +（-1） i S 1 *（T 2 -T 1 ）；
The speed S1 of the preceding train operation data is equal to the speed S of the following train operation data 2 ；
Time T for sequencing preceding train operation data 1 Equal to time T of the train operation data ordered later 2 ；
Of two adjacent train operation data, kilometer post K of the preceding train operation data is ordered 1 Kilometer post K with sequence train operation data 2 When the train running data are not equal, keeping the train running data unchanged;
wherein, the subscript 1 is used for identifying train operation data sequenced in front, and the subscript 2 is used for identifying train operation data sequenced in back; when the train goes down, i is an even number, and when the train goes up, i is an odd number. Here, the down running of the train refers to the running direction of continuously increasing kilometer posts when the train runs; the upward movement of the train refers to the running direction of continuously decreasing kilometer posts when the train runs.
It should be noted that, the above rule for smoothing train operation data may be an optional example of the embodiment of the present application, and the embodiment of the present application may use other rules to smooth train operation data.
In one illustrative example, step 103 determines a mileage zone where the train is continuously running in the line based on the kilometer post, comprising:
section analysis data of each line of each train in a preset time length are analyzed, and whether intersection exists in mileage of train operation is determined according to kilometer posts in the section analysis data;
when determining that the mileage of the train running has an intersection, determining the mileage section of the train running continuously in the line according to the kilometer post in the section analysis data with the intersection.
In one exemplary embodiment, determining whether the mileage of the train operation has an intersection according to the kilometer post in the section analysis data comprises selecting two of the section analysis data within a preset time length of each line of each train at a time to perform the following comparison to determine whether the mileage of the train operation has an intersection:
the method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a smaller kilometer label in selected second section analysis data and smaller than the larger kilometer label in selected second section analysis data, and when the smaller kilometer label in selected first section analysis data is smaller than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; assume that kilometer scale in the first section analysis data is K 1n And K 2n ，K 1n Less than K 2n The kilometer sign in the second section analysis data is K 1m And K 2m ，K 1m Less than K 2m The relationship between the kilometer post sizes in the section analysis data can be expressed by the following formula: k (K) 1n <K 1m <K 2n <K 2m ；
The larger kilometer post in the analysis data of the selected second section is smaller than the analysis number of the selected first sectionDetermining that the mileage of the train running has intersection when the larger kilometer label is larger than the smaller kilometer label in the selected first section analysis data and the smaller kilometer label in the selected first section analysis data is larger than the smaller kilometer label in the selected second section analysis data; assume that kilometer scale in the first section analysis data is K 1n And K 2n ，K 1n Less than K 2n The kilometer sign in the second section analysis data is K 1m And K 2m ，K 1m Less than K 2m The relationship between the kilometer post sizes in the section analysis data can be expressed by the following formula: k (K) 1m <K 1n <K 2m <K 2n ；
The method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a larger kilometer label and a smaller kilometer label in selected second section analysis data, and when the smaller kilometer label in selected second section analysis data is larger than the smaller kilometer label in selected first section analysis data, the existence intersection of the mileage of the train operation is determined; assume that kilometer scale in the first section analysis data is K 1n And K 2n ，K 1n Less than K 2n The kilometer sign in the second section analysis data is K 1m And K 2m ，K 1m Less than K 2m The relationship between the kilometer post sizes in the section analysis data can be expressed by the following formula: k (K) 1n <K 1m <K 2m <K 2n ；
And determining that the crossing sets exist in the mileage of the train when the larger kilometer label in the selected second section analysis data is larger than the larger kilometer label and the smaller kilometer label in the selected first section analysis data is larger than the smaller kilometer label in the selected second section analysis data. Assume that kilometer scale in the first section analysis data is K 1n And K 2n ，K 1n Less than K 2n The kilometer sign in the second section analysis data is K 1m And K 2m ，K 1m Less than K 2m The kilometer post size in the section analysis dataThe relationship can be expressed by the following formula: k (K) 1m <K 1n <K 2n <K 2m 。
In one illustrative example, the starting kilometer post for the mileage zone of the present application is: the mileage of train operation has the minimum kilometer post in all section analysis data of intersection;
in one illustrative example, the ending kilometers of the mileage zones of the present application are marked as: the mileage of train operation has the maximum kilometer post in all section analysis data of intersection.
In one illustrative example, step 104 determines whether to wirelessly time out pre-warn the mileage section, including:
the method comprises the steps of counting the number of section data obtained through integration in a preset counting period and trains corresponding to the section data, and determining the number of section data with the same line information and mileage sections and the trains corresponding to the section data;
and when the number of the section data with the same line information and the mileage section is larger than a preset threshold value, and the section data corresponds to more than two trains, performing wireless overtime section early warning on the mileage section.
In an exemplary embodiment, the wireless timeout section early warning is performed on the mileage section, which comprises the following steps:
when the number of the section data with the same line information and mileage sections is about a preset threshold value, determining the duty ratio of the section data corresponding to each train in the section data with the same line information and mileage sections, and when the duty ratio of the section data corresponding to each train is smaller than the preset threshold value, performing wireless overtime section early warning on the mileage sections;
in an exemplary embodiment, the method of the embodiment of the present application further includes: and when the duty ratio of the section data corresponding to one train is larger than a preset percentage threshold value, carrying out safety early warning on the train.
In one illustrative example, the percentage threshold in embodiments of the present application may be set empirically by those skilled in the art.
Fig. 2 is a block diagram of a device for implementing early warning processing according to an embodiment of the present application, as shown in fig. 2, including: the system comprises an acquisition unit, a merging unit, an integrated mileage unit and an early warning unit; wherein,,
the acquisition unit is configured to: for each call service, acquiring a group of train operation data;
the merging unit is configured to: for each group of train operation data, according to the operation time in the train operation data, combining two adjacent train operation data with the interval time longer than the preset interval time threshold value into one section analysis data for section analysis
The integrated mileage unit is set as follows: determining a mileage section of a train running continuously in a line according to kilometer posts for section analysis data in a preset time length of each line of each train, and integrating the determined mileage section and the section analysis data for determining the mileage section into one section data;
the early warning unit is arranged as follows: determining whether to perform wireless overtime early warning on the mileage section according to the number of section data obtained through integration in a preset statistical period and the statistics of trains corresponding to the section data;
the train operation data are sequenced according to the time sequence; the train operation data includes: the running time T and kilometer post K of the train; the statistical period comprises N preset time periods, wherein N is an integer greater than or equal to 2.
According to the embodiment of the application, train operation data corresponding to the calling service are acquired, and the train operation data with the absolute value of the time difference larger than the preset duration threshold value are combined into section analysis data for operation section analysis by determining the time difference of the operation time contained in the adjacent train operation data; determining a running mileage section of each train according to the analysis data of each line of each train; the automatic early warning of the wireless overtime zone is realized for the running mileage zone meeting the early warning condition through the statistics of the number of zone data obtained by integration in a preset statistical period and the train corresponding to the zone data, and the running reliability of the high-speed train is improved.
In an exemplary embodiment, the apparatus of the embodiment of the present application further includes a smoothing processing unit configured to:
and respectively smoothing the acquired running data of each group of trains.
In an exemplary embodiment, the smoothing processing unit of the embodiment of the present application is configured to: of two adjacent train operation data, kilometer post K of the preceding train operation data is ordered 1 Kilometer post K equal to train operation data ordered later 2 At the time, set up:
kilometer post of train operation data sequenced later is equal to K 1 +（-1） i S 1 *（T 2 -T 1 ）；
Speed S of train operation data sequenced in front 1 Equal to the speed S of the train operation data ordered thereafter 2 ；
Time T for sequencing preceding train operation data 1 Equal to time T of the train operation data ordered later 2 ；
Of two adjacent train operation data, kilometer post K of the preceding train operation data is ordered 1 Kilometer post K with sequence train operation data 2 When the train running data are not equal, keeping the train running data unchanged;
wherein, the subscript 1 is used for identifying train operation data sequenced in front, and the subscript 2 is used for identifying train operation data sequenced in back; when the train goes down, i is an even number, and when the train goes up, i is an odd number.
In one illustrative example, an integrated mileage unit of the present application is configured to determine a mileage zone where a train continuously runs in a route according to a kilometer post, including:
section analysis data of each line of each train in a preset time length are analyzed, and whether intersection exists in mileage of train operation is determined according to kilometer posts in the section analysis data;
when determining that the mileage of the train running has an intersection, determining the mileage section of the train running continuously in the line according to the kilometer post in the section analysis data with the intersection.
In one illustrative example, an integrated mileage unit configured to determine whether an intersection exists in mileage of a train operation based on kilometer posts in section analysis data, includes: and analyzing data of the sections of each line of each train within a preset time length, and selecting two of the sections at each time to perform the following comparison so as to determine whether the mileage of the train running has intersection or not:
the method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a smaller kilometer label in selected second section analysis data and smaller than the larger kilometer label in selected second section analysis data, and when the smaller kilometer label in selected first section analysis data is smaller than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; assume that kilometer scale in the first section analysis data is K 1n And K 2n ，K 1n Less than K 2n The kilometer sign in the second section analysis data is K 1m And K 2m ，K 1m Less than K 2m The relationship between the kilometer post sizes in the section analysis data can be expressed by the following formula: k (K) 1n <K 1m <K 2n <K 2m ；
The method comprises the steps that a larger kilometer label in selected second section analysis data is smaller than a larger kilometer label in selected first section analysis data, is larger than a smaller kilometer label in selected first section analysis data, and when the smaller kilometer label in selected first section analysis data is larger than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; assume that kilometer scale in the first section analysis data is K 1n And K 2n ，K 1n Less than K 2n The kilometer sign in the second section analysis data is K 1m And K 2m ，K 1m Less than K 2m The relationship between the kilometer post sizes in the section analysis data can be expressed by the following formula: k (K) 1m <K 1n <K 2m <K 2n ；
The larger kilometer post in the first section analysis data is larger than the larger kilometer post in the second section analysis dataDetermining that the mileage of the train running has intersection when the smaller kilometer label in the second section analysis data is larger than the smaller kilometer label in the first section analysis data; assume that kilometer scale in the first section analysis data is K 1n And K 2n ，K 1n Less than K 2n The kilometer sign in the second section analysis data is K 1m And K 2m ，K 1m Less than K 2m The relationship between the kilometer post sizes in the section analysis data can be expressed by the following formula: k (K) 1n <K 1m <K 2m <K 2n ；
And determining that the crossing sets exist in the mileage of the train when the larger kilometer label in the selected second section analysis data is larger than the larger kilometer label and the smaller kilometer label in the selected first section analysis data is larger than the smaller kilometer label in the selected second section analysis data. Assume that kilometer scale in the first section analysis data is K 1n And K 2n ，K 1n Less than K 2n The kilometer sign in the second section analysis data is K 1m And K 2m ，K 1m Less than K 2m The relationship between the kilometer post sizes in the section analysis data can be expressed by the following formula: k (K) 1m <K 1n <K 2n <K 2m 。
In one illustrative example, the starting kilometer post for the mileage zone of the present application is: the mileage of train operation has the minimum kilometer post in all section analysis data of intersection;
in one illustrative example, the ending kilometers of the mileage zones of the present application are marked as: the mileage of train operation has the maximum kilometer post in all section analysis data of intersection.
In an exemplary embodiment, the early warning unit in the embodiment of the present application is configured to:
the method comprises the steps of counting the number of section data obtained through integration in a preset counting period and trains corresponding to the section data, and determining the number of section data with the same line information and mileage sections and the trains corresponding to the section data;
and when the number of the section data with the same line information and the mileage section is larger than a preset threshold value, and the section data corresponds to more than two trains, performing wireless overtime section early warning on the mileage section.
The embodiment of the application also provides a computer storage medium, wherein a computer program is stored in the computer storage medium, and the method for realizing the early warning processing is realized when the computer program is executed by a processor.
The embodiment of the application also provides a terminal, which comprises: a memory and a processor, the memory storing a computer program; wherein,,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by the processor, implements a method for implementing the early warning process as described above.
"one of ordinary skill in the art will appreciate that all or some of the steps, systems, functional modules/units in the apparatus, and methods disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed cooperatively by several physical components. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes both volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as known to those skilled in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer. Furthermore, as is well known to those of ordinary skill in the art, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. ".
Claims (7)
1. A method for implementing early warning processing, comprising:
for each call service, acquiring a group of train operation data;
for each group of train operation data, according to the operation time in the train operation data, combining two adjacent train operation data with the interval time length longer than a preset interval time length threshold value into one section analysis data for section analysis;
determining a mileage section of a train running continuously in a line according to kilometer posts for section analysis data in a preset time length of each line of each train, and integrating the determined mileage section and the section analysis data for determining the mileage section into one section data;
determining whether to perform wireless overtime early warning on the mileage section according to the number of section data obtained through integration in a preset statistical period and the statistics of trains corresponding to the section data;
the train operation data are sequenced according to time sequence; the train operation data includes: the running time T and kilometer post K of the train; the statistical period comprises N preset time periods, wherein N is an integer greater than or equal to 2; the determining the mileage section of the train running continuously in the line according to the kilometer post comprises the following steps: section analysis data of each line of each train within a preset time length are analyzed, and whether the mileage of running trains has intersection or not is determined according to kilometer posts in the section analysis data; when determining that the mileage of the train operation has an intersection, determining a mileage section of the train continuously running in the line according to the kilometer post in the section analysis data with the intersection; the starting kilometer post of the mileage section is: the mileage of train operation has the minimum kilometer post in all section analysis data of intersection; the termination kilometer post of the mileage zone is: the mileage of train operation has the maximum kilometer post in all section analysis data of intersection; determining whether the mileage of the train operation has an intersection or not according to the kilometer post in the section analysis data, wherein the section analysis data in the preset time length of each line of each train is selected for each time, and two of the section analysis data are compared as follows to determine whether the mileage of the train operation has the intersection or not: the method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a smaller kilometer label in selected second section analysis data and smaller than the larger kilometer label in selected second section analysis data, and when the smaller kilometer label in selected first section analysis data is smaller than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; the method comprises the steps that a larger kilometer label in selected second section analysis data is smaller than a larger kilometer label in selected first section analysis data, is larger than a smaller kilometer label in selected first section analysis data, and when the smaller kilometer label in selected first section analysis data is larger than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; the method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a larger kilometer label and a smaller kilometer label in selected second section analysis data, and when the smaller kilometer label in selected second section analysis data is larger than the smaller kilometer label in selected first section analysis data, the existence intersection of the mileage of the train operation is determined; and determining that the crossing sets exist in the mileage of the train when the larger kilometer label in the selected second section analysis data is larger than the larger kilometer label and the smaller kilometer label in the selected first section analysis data is larger than the smaller kilometer label in the selected second section analysis data.
2. The method of claim 1, wherein prior to merging into one piece of segment analysis data for segment analysis, the method further comprises:
and respectively carrying out smoothing processing on each group of acquired train operation data.
3. The method of claim 2, wherein the train operation data further includes a speed S of train operation, and wherein the smoothing comprises:
of the two adjacent train operation data, the kilometer post K of the train operation data which is sequenced in front is arranged 1 Kilometer post K equal to the train operation data arranged in sequence 2 At the time, set up:
the kilometer post of the train operation data sequenced later is equal to K 1 +（-1） i S 1 *（T 2 -T 1 ）；
Speed S of the train operation data ordered in front 1 Equal to the speed S of the train operation data ordered afterwards 2 ；
Time T of sequencing the preceding train operation data 1 Equal to the time T of the train operation data ordered later 2 ；
Of the two adjacent train operation data, the kilometer post K of the train operation data which is sequenced in front is arranged 1 Kilometer post K with the train operation data arranged in sequence 2 When the train running data are not equal, keeping the train running data unchanged;
wherein, subscript 1 is used for identifying the train operation data ranked in front, subscript 2 is used for identifying the train operation data ranked in rear; and when the train goes down, i is an even number, and when the train goes up, i is an odd number.
4. The method of any one of claims 1-3, wherein the determining whether to perform wireless timeout pre-warning for the mileage zone comprises:
the number of the section data and the statistics of trains corresponding to the section data, which are obtained through integration in a preset statistics period, are determined, and the number of the section data, which are the same in line information and the mileage section, and the number of trains corresponding to the section data are determined;
and when the number of the section data with the same line information and the mileage section is larger than a preset threshold value, and the section data corresponds to more than two trains, performing wireless overtime section early warning on the mileage section.
5. A computer storage medium having a computer program stored therein, which when executed by a processor, implements the method of implementing early warning processing according to any one of claims 1 to 4.
6. A terminal, comprising: a memory and a processor, the memory storing a computer program; wherein,,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by the processor, implements the method for implementing early warning processing according to any one of claims 1 to 4.
7. An apparatus for implementing early warning processing, comprising: the system comprises an acquisition unit, a merging unit, an integrated mileage unit and an early warning unit; wherein,,
the acquisition unit is configured to: for each call service, acquiring a group of train operation data;
the merging unit is configured to: for each group of train operation data, according to the operation time in the train operation data, combining two adjacent train operation data with the interval time longer than the preset interval time threshold value into one section analysis data for section analysis
The integrated mileage unit is set as follows: determining a mileage section of a train running continuously in a line according to kilometer posts for section analysis data in a preset time length of each line of each train, and integrating the determined mileage section and the section analysis data for determining the mileage section into one section data; determining a mileage zone of continuous running of the train in the line according to the kilometer post, comprising: section analysis data of each line of each train in a preset time length are analyzed, and whether intersection exists in mileage of train operation is determined according to kilometer posts in the section analysis data; when determining that the mileage of the train running has an intersection, determining a mileage section of the train running continuously in the line according to the kilometer post in the section analysis data with the intersection; the starting kilometer label of the mileage zone is: the mileage of train operation has the minimum kilometer post in all section analysis data of intersection; the ending kilometers of the mileage zone are marked as: the mileage of train operation has the maximum kilometer post in all section analysis data of intersection; determining whether the mileage of the train operation has an intersection or not according to the kilometer post in the section analysis data, wherein the section analysis data in the preset time length of each line of each train is selected for each time, and two of the section analysis data are compared as follows to determine whether the mileage of the train operation has the intersection or not: the method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a smaller kilometer label in selected second section analysis data and smaller than the larger kilometer label in selected second section analysis data, and when the smaller kilometer label in selected first section analysis data is smaller than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; the method comprises the steps that a larger kilometer label in selected second section analysis data is smaller than a larger kilometer label in selected first section analysis data, is larger than a smaller kilometer label in selected first section analysis data, and when the smaller kilometer label in selected first section analysis data is larger than the smaller kilometer label in selected second section analysis data, the intersection of the mileage of train operation is determined; the method comprises the steps that a larger kilometer label in selected first section analysis data is larger than a larger kilometer label and a smaller kilometer label in selected second section analysis data, and when the smaller kilometer label in selected second section analysis data is larger than the smaller kilometer label in selected first section analysis data, the existence intersection of the mileage of the train operation is determined; the method comprises the steps that a larger kilometer label in the selected second section analysis data is larger than a larger kilometer label and a smaller kilometer label in the selected first section analysis data, and when the smaller kilometer label in the selected first section analysis data is larger than the smaller kilometer label in the selected second section analysis data, the intersection of the mileage of the train running is determined;
the early warning unit is arranged as follows: determining whether to perform wireless overtime early warning on the mileage section according to the number of section data obtained through integration in a preset statistical period and the statistics of trains corresponding to the section data;
the train operation data are sequenced according to time sequence; the train operation data includes: the running time T and kilometer post K of the train; the statistical period comprises N preset time periods, and N is an integer greater than or equal to 2.
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