CN110687374B - System and method for analyzing on-board detection data of cab signal on-board equipment - Google Patents
System and method for analyzing on-board detection data of cab signal on-board equipment Download PDFInfo
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- 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
- G01R31/005—Testing of electric installations on transport means
- G01R31/008—Testing of electric installations on transport means on air- or spacecraft, railway rolling stock or sea-going vessels
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- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L15/00—Indicators provided on the vehicle or train for signalling purposes
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L15/00—Indicators provided on the vehicle or train for signalling purposes
- B61L15/0018—Communication with or on the vehicle or train
- B61L15/0027—Radio-based, e.g. using GSM-R
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B61—RAILWAYS
- B61L—GUIDING RAILWAY TRAFFIC; ENSURING THE SAFETY OF RAILWAY TRAFFIC
- B61L15/00—Indicators provided on the vehicle or train for signalling purposes
- B61L15/0081—On-board diagnosis or maintenance
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- G—PHYSICS
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- H04W4/12—Messaging; Mailboxes; Announcements
- H04W4/14—Short messaging services, e.g. short message services [SMS] or unstructured supplementary service data [USSD]
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Abstract
The invention provides a system and a method for analyzing on-board detection data of cab signal on-board equipment for improving safety, and belongs to the field of on-board detection of cab signal on-board equipment. The method comprises the steps of receiving detection data sent by an in-vehicle system, analyzing the detection data to obtain risk data, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to a client and the in-vehicle detection system; the database stores detection data, standard data and early warning information and alarm information data corresponding to risk events in the vehicle detection system, and the standard data is used for analysis by the data analysis module; the alarm information comprises introduction information of the risk event and a corresponding solution thereof; the early warning information includes possible problems brought by the risk event and a corresponding solution. The invention detects possible risk events of the cab signal vehicle-mounted equipment through continuous data analysis, greatly improves the safety of the cab signal vehicle-mounted equipment and reduces the labor cost.
Description
Technical Field
The invention relates to a data analysis system, in particular to an on-board detection data analysis system and method for locomotive signal on-board equipment, and belongs to the field of on-board detection of the locomotive signal on-board equipment.
Background
At present, the existing cab signal vehicle-mounted equipment is simply tested on a vehicle in a vehicle detection system, the result data after the test is displayed on a screen of a tester, and meanwhile, the test data is stored in a storage card of the detector.
The existing vehicle detection system has the following problems:
1. the data cannot be displayed on a PC, a mobile phone or a handheld device, so that the historical data is inconvenient to view;
2. due to the fact that the space of the memory card is limited, historical data of early-stage testing can be gradually covered by the latest data, the data retention amount is small, large data risk trend analysis cannot be conducted, the early warning and alarming functions cannot be achieved, reasonable solving measures cannot be provided for risk events, and risk tracking and management cannot be achieved.
Disclosure of Invention
In order to overcome the defects, the invention provides a system and a method for analyzing the on-board detection data of the cab signal on-board equipment, which are used for improving the safety of the cab signal on-board equipment.
The invention relates to an on-board detection data analysis system of locomotive signal on-board equipment, which comprises:
the data analysis module is used for receiving detection data sent by the in-vehicle system, analyzing the detection data to obtain risk data, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the in-vehicle detection system;
the database is connected with the data analysis module and used for storing detection data, standard data and early warning information and alarm information data corresponding to the risk events in the vehicle detection system, and the standard data is used for the data analysis module to analyze;
the alarm information comprises introduction information of risk events and corresponding solutions thereof;
the early warning information includes possible problems brought by the risk event and corresponding solutions thereof.
Preferably, the database is further used for storing historical data threshold values of the cab signal vehicle-mounted equipment;
the data analysis module includes:
the extraction module is used for extracting the in-vehicle detection data and the corresponding standard data from the database;
the standard judgment module is connected with the extraction module and used for comparing the in-vehicle detection data with corresponding standard data, determining the in-vehicle detection data as risk data if the in-vehicle detection data does not meet the standard data requirement, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the in-vehicle detection system;
and the threshold judgment module is connected with the standard judgment module and used for comparing the on-board detection data with the historical data threshold of the on-board equipment of the same cab signal when the on-board detection data meets the standard data requirement, determining the on-board detection data as risk data if the detection data does not meet the threshold requirement, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the on-board detection system.
Preferably, the historical data threshold is a fixed value set manually or a dynamic threshold obtained through autonomous learning;
the method for acquiring the dynamic threshold comprises the following steps:
continuously extracting all qualified historical data of corresponding test items of the same cab signal vehicle-mounted equipment to obtain feature points, eliminating data with large feature fluctuation, wherein the generated threshold value can approach to a certain value or a certain stable interval infinitely, and the certain value or the certain stable interval is used as a dynamic threshold value.
Preferably, the data analysis module is further configured to detect whether the in-vehicle detection system is online, and when it is detected that the in-vehicle detection system is not online, send the risk data, the early warning information corresponding to the risk event, and the alarm information to a mobile phone of an operator of the in-vehicle detection system in the form of a short message.
Preferably, the system further includes a risk tracking management module, configured to receive a determination signal sent by the client, where the determination signal indicates whether the solution solves the risk event, and if so, add 1 to a value of a stored in the database, where a represents the number of solution solutions to the risk event;
for receiving a new solution sent by the client, adding the solution to the database, and associating with the corresponding risk event.
The invention also provides an on-board detection data analysis method of the locomotive signal on-board equipment, which comprises the following steps:
s1, storing the standard data and the early warning information and the alarm information data corresponding to the risk event into a database;
the alarm information comprises introduction information of risk events and corresponding solutions thereof;
the early warning information comprises problems possibly brought by the risk event and a solution corresponding to the problems;
s2, receiving detection data sent by the vehicle detection system and storing the detection data in a database;
s3, extracting the in-vehicle detection data in the database, analyzing the in-vehicle detection data to obtain risk data, forming a risk event according to the risk data, and sending the risk data, the early warning information corresponding to the risk event and the warning information to the client and the in-vehicle detection system.
Preferably, the database also stores historical data threshold values of cab signal vehicle-mounted equipment;
the S3 includes:
s31, extracting the in-vehicle detection data and the corresponding standard data from the database;
s32, comparing the on-vehicle detection data to be detected with corresponding standard data, determining the on-vehicle detection data as risk data if the on-vehicle detection data does not meet the standard data requirements, forming a risk event according to the risk data, sending the risk data, early warning information and alarm information corresponding to the risk event to a client and an on-vehicle detection system, and turning to S33 if the on-vehicle detection data meets the standard data requirements;
s33, comparing the on-board detection data with the historical data threshold of the same cab signal on-board equipment, determining the on-board detection data as risk data if the detection data do not meet the threshold requirement, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the on-board detection system.
Preferably, the historical data threshold is a fixed value set manually or a dynamic threshold obtained through autonomous learning;
the method for acquiring the dynamic threshold comprises the following steps:
continuously extracting all qualified historical data of corresponding test items of the same cab signal vehicle-mounted equipment to obtain feature points, eliminating data with large feature fluctuation, wherein the generated threshold value can approach to a certain value or a certain stable interval infinitely, and the certain value or the certain stable interval is used as a dynamic threshold value.
Preferably, the S3 further includes:
and S34, detecting whether the in-vehicle detection system is on-line or not, and when the in-vehicle detection system is detected not to be on-line, sending the risk data, the early warning information corresponding to the risk event and the warning information to a mobile phone of an operator of the in-vehicle detection system in the form of short messages.
Preferably, the method further comprises:
s4, receiving a judgment signal whether the solution sent by the client solves the risk event, if so, adding 1 to the value of a stored in the database, wherein a represents the number of the solution solving risk event;
and S5, receiving the new solution sent by the client, adding the solution to the database, and associating the solution with the corresponding risk event.
The method has the advantages that the possible risk events of the cab signal vehicle-mounted equipment are detected through continuous data analysis, the safety of the cab signal vehicle-mounted equipment is greatly improved, and the labor cost is reduced. The invention has the following advantages:
1. the invention supports the display of the detection data at the client, and is convenient for checking the data;
2. the invention supports secondary threshold analysis, thereby obtaining more accurate test results;
3. the method supports risk trend analysis, and can find potential risks of the cab signal vehicle-mounted equipment;
4. the invention supports automatic early warning and alarming, and realizes timely reminding of workers;
5. the invention supports risk tracking management, realizes effective management and control of risks and improves the safety of cab signal vehicle-mounted equipment.
Drawings
FIG. 1 is a schematic view of a process for analyzing on-board detection data of cab signal on-board equipment according to the present invention;
fig. 2 is a schematic flow chart of the present invention for implementing short message reminding and risk tracking management.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
The invention is further described with reference to the following drawings and specific examples, which are not intended to be limiting.
The implementation mode is used for realizing the on-board detection data analysis system of the cab signal on-board equipment, the realization process comprises the on-board detection system, a server side and a client side, and the specific process is shown in figure 1;
in-vehicle detection system: the system is used for detecting the cab signal vehicle-mounted equipment and sending detection data to a server; receiving risk data of a server side for displaying and reminding; and the system is also used for providing a human-computer interaction interface for the user to actually solve the risk and sending the interaction data to the server.
The server side comprises:
the data analysis module is used for receiving detection data sent by the in-vehicle system, analyzing the detection data to obtain risk data, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the in-vehicle detection system;
the database is connected with the data analysis module and used for storing detection data, standard data and early warning information and alarm information data corresponding to the risk events in the vehicle detection system, and the standard data is used for the data analysis module to analyze;
the alarm information comprises introduction information of risk events and corresponding solutions thereof;
the early warning information includes possible problems brought by the risk event and corresponding solutions thereof.
The embodiment obtains standard data: and manually inputting the standard data of each test item into a database of the server according to the TB/T3287 standard.
Detection data acquisition: the locomotive signal vehicle-mounted equipment is detected by a locomotive signal vehicle-mounted equipment on-board detection system, detection data are sent to a server side in a wireless mode, and the server side stores the detection data into a database.
A client: the server side detection data are extracted and displayed; the risk data pushed by the server side is received, displayed and reminded in real time;
the on-vehicle detection system is connected to the Internet through the 4G wireless communication module, and the service end is connected to the Internet; the server and the client communicate by adopting the internet or a local area network. The Internet is accessed through the 4G wireless communication module, and the Internet is accessed through the service end; the server and the client communicate by adopting the internet or a local area network. The database of the present embodiment in the preferred embodiment is further configured to store historical data thresholds of the cab signal on-board devices;
the data analysis module of the present embodiment includes:
the extraction module is used for extracting the in-vehicle detection data and the corresponding standard data from the database;
the standard judgment module is connected with the extraction module and used for comparing the in-vehicle detection data with corresponding standard data, determining the in-vehicle detection data as risk data if the in-vehicle detection data does not meet the standard data requirement, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the in-vehicle detection system;
and the threshold judgment module is connected with the standard judgment module and used for comparing the on-board detection data with the historical data threshold of the on-board equipment of the same cab signal when the on-board detection data meets the standard data requirement, determining the on-board detection data as risk data if the detection data does not meet the threshold requirement, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the on-board detection system.
After the vehicle detection system receives the risk data pushed by the server, a prompt box containing the risk data pops up on a screen, and a user clicks the prompt box to display detailed risk information and a corresponding solution;
the historical data threshold value of the embodiment is a fixed value set manually or a dynamic threshold value obtained through autonomous learning; the method for acquiring the dynamic threshold comprises the following steps: continuously extracting all qualified historical data of corresponding test items of the same cab signal vehicle-mounted equipment to obtain feature points, eliminating data with large feature fluctuation, wherein the generated threshold value can approach to a certain value or a certain stable interval infinitely, and the certain value or the certain stable interval is used as a dynamic threshold value.
As shown in fig. 2, the data analysis module of this embodiment is further configured to detect whether the in-vehicle detection system is online, and when it is detected that the in-vehicle detection system is not online, send the risk data, the early warning information corresponding to the risk event, and the alarm information to a mobile phone of an operator of the in-vehicle detection system in the form of a short message. The client side receives the risk data pushed by the server side and then displays and reminds in real time, the server side also automatically calls a notification function of the vehicle detection system, if the vehicle detection system is off line, the server side automatically calls a short message platform and sends the risk data to a mobile phone using a detection system worker in a short message mode, the short message content comprises a website link of risk summary description and detailed risk information, and a user can check the detailed risk information and a solution by clicking the website link.
As shown in fig. 2, the present embodiment also has the functions of risk tracking management: after the server generates the risk event, all corresponding solutions (which are in the order of solving the risk in a large number of times) are provided to the client and the vehicle detection system by default. If the actual solution is not in the solutions listed in the vehicle detection system, the user inputs the actual solution of the risk through a human-computer interaction interface of the vehicle detection system, the vehicle detection system transmits the actual solution to the server, the server adds the solution to the database after receiving the actual solution, and notifies the client, and the client updates the risk information; if the actual solution exists in the solutions listed in the vehicle detection system, the server adds 1 to the number of times of solving the problem of the solution, and notifies the client, and the client updates the risk information; by continually enriching the solutions in the opinion base and continually optimizing the order of the list of solutions, it is achieved that the problem can be solved in practice by the first proposed solution in the given list. The method specifically comprises the following steps: the server of the embodiment further includes a risk tracking management module, configured to receive a determination signal indicating whether the solution sent by the client solves the risk event, and if so, add 1 to a value of a stored in the database, where a represents the number of solution solutions that solve the risk event, and further, receive a new solution sent by the client, add the solution to the database, and associate the solution with the corresponding risk event.
The method for analyzing the on-board detection data of the locomotive signal on-board equipment in the embodiment comprises the following steps:
s1, storing the standard data and the early warning information and the alarm information data corresponding to the risk event into a database;
the alarm information comprises introduction information of risk events and corresponding solutions thereof;
the early warning information comprises problems possibly brought by the risk event and a solution corresponding to the problems;
s2, receiving detection data sent by the vehicle detection system and storing the detection data in a database;
s3, extracting in-vehicle detection data in the database, analyzing the in-vehicle detection data to obtain risk data, forming a risk event according to the risk data, and sending the risk data, early warning information corresponding to the risk event and alarm information to the client and the in-vehicle detection system.
In a preferred embodiment, the database of the present embodiment further stores historical data thresholds of the cab signal on-board devices;
s3 of the present embodiment includes:
s31, extracting the in-vehicle detection data and the corresponding standard data from the database;
s32, comparing the in-vehicle detection data with corresponding standard data, determining the in-vehicle detection data as risk data if the in-vehicle detection data do not meet the standard data requirements, forming a risk event according to the risk data, sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the in-vehicle detection system, and turning to S33 if the in-vehicle detection data meet the standard data requirements;
s33, comparing the on-board detection data with the historical data threshold of the same cab signal on-board equipment, determining the on-board detection data as risk data if the detection data do not meet the threshold requirement, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the on-board detection system.
In a preferred embodiment, the historical data threshold value of the present embodiment is a fixed value set manually or a dynamic threshold value obtained through autonomous learning;
the method for acquiring the dynamic threshold comprises the following steps:
continuously extracting all qualified historical data of corresponding test items of the same cab signal vehicle-mounted equipment to obtain feature points, eliminating data with large feature fluctuation, wherein the generated threshold value can approach to a certain value or a certain stable interval infinitely, and the certain value or the certain stable interval is used as a dynamic threshold value.
In a preferred embodiment, S3 of the present embodiment further includes:
and S34, detecting whether the in-vehicle detection system is on-line or not, and when the in-vehicle detection system is detected not to be on-line, sending the risk data, the early warning information corresponding to the risk event and the warning information to a mobile phone of an operator of the in-vehicle detection system in the form of short messages.
The method of the present embodiment further comprises:
s4, receiving a judgment signal whether the solution sent by the client solves the risk event, if so, adding 1 to the value of a stored in the database, wherein a represents the number of the solution solving risk event;
and S5, receiving the new solution sent by the client, adding the solution to the database, and associating the solution with the corresponding risk event.
Although the invention herein has been described with reference to particular embodiments, it is to be understood that these embodiments are merely illustrative of the principles and applications of the present invention. It is therefore to be understood that numerous modifications may be made to the illustrative embodiments and that other arrangements may be devised without departing from the spirit and scope of the present invention as defined by the appended claims. It should be understood that features described in different dependent claims and herein may be combined in ways different from those described in the original claims. It is also to be understood that features described in connection with individual embodiments may be used in other described embodiments.
Claims (6)
1. An on-board detection data analysis system for a locomotive signal on-board device, the system comprising:
the data analysis module is used for receiving detection data sent by the in-vehicle system, analyzing the detection data to obtain risk data, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the in-vehicle detection system;
the database is connected with the data analysis module and used for storing detection data, standard data and early warning information and alarm information data corresponding to the risk events in the vehicle detection system, and the standard data is used for the data analysis module to analyze;
the alarm information comprises introduction information of risk events and corresponding solutions thereof;
the early warning information comprises problems possibly brought by the risk event and a solution corresponding to the problems;
the database is also used for storing historical data threshold values of cab signal vehicle-mounted equipment;
the data analysis module includes:
the extraction module is used for extracting the in-vehicle detection data and the corresponding standard data from the database;
the standard judgment module is connected with the extraction module and used for comparing the in-vehicle detection data with corresponding standard data, determining the in-vehicle detection data as risk data if the in-vehicle detection data does not meet the standard data requirement, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the in-vehicle detection system;
the threshold judging module is connected with the standard judging module and used for comparing the on-board detection data with a historical data threshold of the on-board equipment of the same cab signal when the on-board detection data meet the standard data requirement, determining the on-board detection data as risk data if the detection data do not meet the threshold requirement, forming a risk event according to the risk data, and sending the risk data, early warning information and warning information corresponding to the risk event to the client and the on-board detection system;
the historical data threshold is a dynamic threshold obtained through autonomous learning;
the method for acquiring the dynamic threshold comprises the following steps:
continuously extracting all qualified historical data of corresponding test items of the same cab signal vehicle-mounted equipment to obtain feature points, eliminating data with large feature fluctuation, wherein the generated threshold value can approach to a certain value or a certain stable interval infinitely, and the certain value or the certain stable interval is used as a dynamic threshold value.
2. The cab signal on-board equipment on-board detection data analysis system of claim 1, wherein the data analysis module is further configured to detect whether the on-board detection system is on-line, and when it is detected that the on-board detection system is not on-line, send the risk data, the early warning information corresponding to the risk event, and the alarm information to a mobile phone of an operator of the on-board detection system in the form of a short message.
3. The cab signal on-board equipment on-board detection data analysis system of claim 1, further comprising a risk tracking management module, configured to receive a judgment signal sent by the client whether the solution solves the risk event, and if so, add 1 to a value of a stored in the database, where a represents the number of solution risk events;
for receiving a new solution sent by the client, adding the solution to the database, and associating with the corresponding risk event.
4. The method for analyzing the on-board detection data of the locomotive signal on-board equipment is characterized by comprising the following steps of:
s1, storing the standard data and the early warning information and the alarm information data corresponding to the risk event into a database;
the alarm information comprises introduction information of risk events and corresponding solutions thereof;
the early warning information comprises problems possibly brought by the risk event and a solution corresponding to the problems;
s2, receiving detection data sent by the vehicle detection system and storing the detection data in a database;
s3, extracting in-vehicle detection data in the database, analyzing the in-vehicle detection data to obtain risk data, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to a client and an in-vehicle detection system;
the database also stores historical data threshold values of cab signal vehicle-mounted equipment;
the S3 includes:
s31, extracting the in-vehicle detection data and the corresponding standard data from the database;
s32, comparing the in-vehicle detection data to be detected with corresponding standard data, determining the in-vehicle detection data as risk data if the in-vehicle detection data do not meet the standard data requirements, forming a risk event according to the risk data, sending the risk data, early warning information and alarm information corresponding to the risk event to a client and an in-vehicle detection system, and turning to S33 if the in-vehicle detection data meet the standard data requirements;
s33, comparing the on-board detection data with the historical data threshold of the same cab signal on-board equipment, if the detection data do not meet the threshold requirement, determining the detection data as risk data, forming a risk event according to the risk data, and sending the risk data, early warning information and alarm information corresponding to the risk event to the client and the on-board detection system;
the historical data threshold is a dynamic threshold obtained through autonomous learning;
the method for acquiring the dynamic threshold comprises the following steps:
continuously extracting all qualified historical data of corresponding test items of the same cab signal vehicle-mounted equipment to obtain feature points, eliminating data with large feature fluctuation, wherein the generated threshold value can approach to a certain value or a certain stable interval infinitely, and the certain value or the certain stable interval is used as a dynamic threshold value.
5. The cab signal on-board device on-board detection data analysis method of claim 4, wherein the S3 further comprises:
and S34, detecting whether the in-vehicle detection system is on-line or not, and when the in-vehicle detection system is detected not to be on-line, sending the risk data, the early warning information corresponding to the risk event and the warning information to a mobile phone of an operator of the in-vehicle detection system in the form of short messages.
6. The cab signal in-vehicle equipment on-vehicle detection data analysis method of claim 4, further comprising:
s4, receiving a judgment signal whether the solution sent by the client solves the risk event, if so, adding 1 to the value of a stored in the database, wherein a represents the number of the solution solving risk event;
and S5, receiving the new solution sent by the client, adding the solution to the database, and associating the solution with the corresponding risk event.
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