Data acquisition method of subway terminal

Abstract

The invention provides a data acquisition method for a subway terminal, and the method comprises the steps: classifying data, and obtaining sudden fault type data and periodic acquisition type data; suddenly fault type data conforming to the suddenly fault rule and periodic acquisition type data conforming to the periodic acquisition rule are reserved; uploading the reserved sudden fault type data and the reserved periodic acquisition type data to a transmission network; wherein the sudden fault rule is used for determining whether sudden fault type data is reserved or not according to a fault alarm condition; the periodic acquisition rule is used for determining whether the periodic acquisition type data is reserved or not according to the change condition of the periodic acquisition type data. The invention further provides a data acquisition device and equipment of the subway terminal and a storage medium.

Description

Technical Field

[0001] The present disclosure relates to the field of urban rail transit, and more particularly to a method for collecting data of subway terminals. Background Art

[0002] Currently, the intelligent operation and maintenance business of urban rail transit has developed rapidly. The basis of intelligent operation and maintenance comes from the support of operation and maintenance data. The number of subway terminal devices is huge and they are widely distributed. The operation and maintenance data generated and collected by terminal devices has the characteristics of large volume, high redundancy, and high processing cost. A large amount of redundant data increases the data storage and maintenance costs of the operation entity in one aspect; increases the cost of carrying out intelligent operation and maintenance data analysis in the second aspect; and brings new inconveniences to the operation personnel in dealing with various types of information in the third aspect.

[0003] To solve this problem, generally, the collection frequency, collection range, and collection data determination threshold of terminal collection devices are adjusted manually to adjust the generation and collection volume of data. Although such methods improve the problem of data redundancy to a certain extent, they do not fundamentally process the screening and cleaning of redundant data. Summary of the Invention

[0004] In view of the above problems, the present disclosure provides a method for collecting data of subway terminals to reduce data redundancy.

[0005] The present disclosure provides a method for collecting data of subway terminals, including: classifying data to obtain sudden failure type data and periodic collection type data; retaining the sudden failure type data that conforms to the sudden failure rule and the periodic collection type data that conforms to the periodic collection rule; uploading the retained sudden failure type data and the retained periodic collection type data to a transmission network; wherein, the sudden failure rule is used to determine whether to retain the sudden failure type data according to the fault alarm situation; the periodic collection rule is used to determine whether to retain the periodic collection type data according to the change situation of the periodic collection type data.

[0006] According to an embodiment of the present disclosure, retaining the sudden failure type data that conforms to the sudden failure rule and the periodic collection type data that conforms to the periodic collection rule includes: screening the sudden failure type data by using the fault alarm condition to obtain the first data to be retained; screening the first data to be retained by using the fault self-recovery condition to obtain the second data to be retained; screening the second data to be retained by using the data redundancy condition to obtain the retained sudden failure type data; screening the periodic collection type data by using the data change amount condition to obtain the retained periodic collection type data; wherein, the fault alarm condition is used to judge whether an alarm is needed; the fault self-recovery condition is used to judge whether the fault has self-recovered; the data redundancy condition is used to judge whether it is a repeated alarm; the data change amount condition is used to judge whether the periodic collection type data is redundant.

[0007] According to an embodiment of the present disclosure, filtering the sudden fault type data by using the fault warning condition to obtain the first data to be retained, including: in response to no fault warning condition being set, determining whether the sudden fault type data is non-enumerable data; if so, setting the warning threshold of the fault warning condition; if not, setting the warning enumeration value of the fault warning condition; filtering the sudden fault type data through the relative relationship between the sudden fault type data and the warning threshold or the consistency between the sudden fault type data and the warning enumeration value to obtain the first data to be retained.

[0008] According to an embodiment of the present disclosure, filtering the first data to be retained by using the fault self-recovery condition to obtain the second data to be retained, including: in response to no fault self-recovery condition being set, setting the first preset time and the preset number of times of the fault self-recovery condition; determining whether the fault corresponding to the first data to be retained has occurred the preset number of times within the first preset time; if so, discarding the first data to be retained; if not, using the first data to be retained as the second data to be retained.

[0009] According to an embodiment of the present disclosure, filtering the second data to be retained by using the data redundancy condition to obtain the retained sudden fault type data, including: in response to no data redundancy condition being set, setting the second preset time of the data redundancy condition; determining whether the fault corresponding to the second data to be retained has been reported within the second preset time; if so, discarding the second data to be retained; if not, using the second data to be retained as the retained sudden fault type data.

[0010] According to an embodiment of the present disclosure, filtering the periodic acquisition type data by using the data change amount condition to obtain the retained periodic acquisition type data, including: in response to no data change amount condition being set, setting the preset change amount of the data change amount condition; calculating the difference between the periodic acquisition type data and the periodic acquisition type data collected at the previous time point; filtering the periodic acquisition type data through the relative relationship between the difference and the preset change amount to obtain the retained periodic acquisition type data.

[0011] According to an embodiment of the present disclosure, classifying the data to obtain the sudden fault type data and the periodic acquisition type data, including: setting the classification condition; the classification condition includes at least the parameters included in the sudden fault type data and the parameters included in the periodic acquisition type data; classifying the collected data according to the classification condition to obtain the sudden fault type data and the periodic acquisition type data.

[0012] The second aspect of the present disclosure provides a data acquisition device for subway terminals, which can be used to implement the data acquisition method for subway terminals, including: an original data determination module for classifying data to obtain sudden failure type data and periodic acquisition type data; a rule determination module for retaining the sudden failure type data that conforms to the sudden failure rule and the periodic acquisition type data that conforms to the periodic acquisition rule; wherein, the sudden failure rule is used to determine whether to retain the sudden failure type data according to the fault alarm situation; the periodic acquisition rule is used to determine whether to retain the periodic acquisition type data according to the change situation of the periodic acquisition type data; a data upload module for uploading the retained sudden failure type data and the retained periodic acquisition type data to the transmission network.

[0013] The third aspect of the present disclosure provides an electronic device, including: one or more processors; a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors execute the above-mentioned data acquisition method for subway terminals.

[0014] The fourth aspect of the present disclosure further provides a computer-readable storage medium, on which executable instructions are stored, and when the instructions are executed by a processor, the processor executes the above-mentioned data acquisition method for subway terminals.

[0015] According to the data acquisition method for subway terminals provided by the present disclosure, by classifying the acquired data into sudden failure type data and periodic acquisition type data, it helps to adopt different processing methods according to the characteristics of different data; and by using rules to control which data needs to be acquired and uploaded. Since the upload of redundant data is avoided, at least part of the technical problem of a large amount of redundant data being acquired by subway terminal devices is solved, achieving the technical effects of reducing the network burden, effectively reducing the redundancy of data acquisition by subway terminal devices, reducing the storage and analysis costs of data, and facilitating the operation and maintenance personnel to carry out operation and maintenance work better and faster. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 Schematically shows a flowchart of the data acquisition method for subway terminals according to an embodiment of the present disclosure;

[0017] Figure 2 Schematically shows a composition diagram of a data lightweight processing device according to an embodiment of the present disclosure;

[0018] Figure 3 Schematically shows a working flowchart of a fault alarm module according to an embodiment of the present disclosure;

[0019] Figure 4 Schematically shows a working flowchart of a data change amount module according to an embodiment of the present disclosure;

[0020] Figure 5 Schematically shows the working flowchart of the fault self - recovery module according to an embodiment of the present disclosure;

[0021] Figure 6 Schematically shows the working flowchart of the data redundancy module according to an embodiment of the present disclosure;

[0022] Figure 7 Schematically shows an implementation example for burst - fault - type data according to an embodiment of the present disclosure;

[0023] Figure 8 Schematically shows the structural block diagram of the data acquisition device of the subway terminal according to an embodiment of the present disclosure;

[0024] Figure 9 Schematically shows the block diagram of an electronic device suitable for implementing the data acquisition method of the subway terminal according to an embodiment of the present disclosure. Detailed implementation manners

[0025] Hereinafter, embodiments of the present disclosure will be described with reference to the accompanying drawings. However, it should be understood that these descriptions are merely exemplary and are not intended to limit the scope of the present disclosure. In the following detailed description, for the sake of explanation, many specific details are set forth to provide a comprehensive understanding of the embodiments of the present disclosure. However, obviously, one or more embodiments can also be implemented without these specific details. In addition, in the following description, descriptions of well - known structures and technologies are omitted to avoid unnecessarily confusing the concepts of the present disclosure.

[0026] The terms used herein are merely for describing specific embodiments and are not intended to limit the present disclosure. The terms "including", "comprising", etc. used herein indicate the presence of the described features, steps, operations, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, or components.

[0027] All terms used herein (including technical and scientific terms) have the meanings commonly understood by those skilled in the art, unless otherwise defined. It should be noted that the terms used herein should be interpreted as having a meaning consistent with the context of this specification and should not be interpreted in an idealized or overly rigid manner.

[0028] In the case of using expressions such as "at least one of A, B, and C, etc.", generally, it should be interpreted according to the meaning commonly understood by those skilled in the art (for example, "a system having at least one of A, B, and C" should include, but is not limited to, a system having only A, only B, only C, having A and B, having A and C, having B and C, and / or having A, B, and C, etc.).

[0029] It should be noted that the data acquisition method of the subway terminal in the present disclosure relates to the field of urban rail transit, and is specifically applied to the field of intelligent operation and maintenance of urban rail transit.

[0030] Figure 1 Schematically shows a flowchart of the data acquisition method of the subway terminal according to an embodiment of the present disclosure, as Figure 1 shown, the embodiment of the present disclosure provides a data acquisition method for a subway terminal, including: classifying data to obtain burst fault type data and periodic acquisition type data; retaining burst fault type data that conforms to the burst fault rule and periodic acquisition type data that conforms to the periodic acquisition rule; uploading the retained burst fault type data and the retained periodic acquisition type data to a transmission network; wherein, the burst fault rule is used to determine whether to retain the burst fault type data according to the fault alarm situation; the periodic acquisition rule is used to determine whether to retain the periodic acquisition type data according to the change situation of the periodic acquisition type data.

[0031] It should be noted that in the data lightweight acquisition method of the present disclosure, it does not target a specific system or device, and is applicable to terminals with state data acquisition functions. When the data collected by the acquisition terminal device at a certain moment meets the retention trigger condition, a data lightweight processing instruction is triggered. In the data lightweight acquisition method of the present disclosure, it does not target a specific data type or format, and is applicable to various types of voice, image data, analog quantity, and digital quantity data. When the collected data meets the retention trigger condition, a data lightweight processing instruction is triggered. The trigger conditions for different types of data can be set by oneself.

[0032] It should be noted that in the data lightweight acquisition method and device of the present disclosure, the method and device are applied to the edge side of urban rail transit, that is, on-site locations such as stations, sections, and depots where data acquisition is required. The deployment methods are: one is to add software algorithms to existing terminal devices, and the other is to deploy in the form of an independent functional device between existing acquisition terminals and the transmission network.

[0033] Through the embodiments of the present disclosure, the purpose of the present disclosure is to effectively reduce the redundancy of data acquisition of subway terminal devices through a data lightweight acquisition method, reduce the storage and analysis costs of data, and facilitate the operation and maintenance personnel to carry out operation and maintenance work better and faster. Specifically, different processing methods are adopted according to the characteristics of different data, and combined with the characteristics of data acquisition thresholds, frequencies, redundancy, etc., lightweight acquisition of data from terminal facilities and equipment is realized, realizing the functions of retaining valuable data and removing redundant data, and reducing the data upload volume.

[0034] Based on the above embodiments, the burst fault class data that conforms to the burst fault rule and the periodic acquisition class data that conforms to the periodic acquisition rule are retained, including: screening the burst fault class data using the fault alarm condition to obtain the first data to be retained; screening the first data to be retained using the fault self-recovery condition to obtain the second data to be retained; screening the second data to be retained using the data redundancy condition to obtain the retained burst fault class data; screening the periodic acquisition class data using the data change amount condition to obtain the retained periodic acquisition class data; wherein, the fault alarm condition is used to judge whether an alarm is needed; the fault self-recovery condition is used to judge whether the fault self-recovers; the data redundancy condition is used to judge whether it is a repeated alarm; the data change amount condition is used to judge whether the periodic acquisition class data is redundant.

[0035] Figure 2 Schematically shows a composition diagram of a data lightweight processing device according to an embodiment of the present disclosure. In the data lightweight acquisition method and device, the fault alarm condition, the data redundancy condition, the fault self-recovery condition, and the data change amount condition can be iteratively optimized by adjusting control parameters. There are two ways to adjust the rule parameters: one is manual adjustment; the other is to automatically adjust the parameter rules of the data lightweight disposal device deployed on the terminal side according to the needs of central urban rail transit cloud-edge-end architecture analysis and fault handling in combination with the current urban rail transit cloud-edge-end architecture.

[0036] The data lightweight processing device consists of 7 modules: the original data determination module completes the determination of the data type, one is burst fault class data, and the other is periodic acquisition data; if it is determined to be burst fault class data, it enters the fault alarm module for processing; if it is determined to be periodic data, it enters the data change amount module for processing.

[0037] The fault alarm module determines whether the collected burst fault class data triggers retention. If it is determined that it can be retained, it enters the fault self-recovery module. If it is determined that it cannot be retained, the collected data is discarded; the data change amount module determines whether the collected periodic acquisition data triggers retention. If it is determined that it can be retained, the data is uploaded to the upper-level system device; otherwise, the data to be retained is discarded; the fault self-recovery module determines the data to be retained according to the retention rule (fault self-recovery condition). If it meets the set retention rule, the data to be retained enters the data redundancy determination. Otherwise, the data is discarded; the data redundancy module determines the convergence of the data to be retained according to the data redundancy condition. If it meets the data redundancy condition, the data to be retained is confirmed to be retained and the data is uploaded to the upper-level data processing system; otherwise, the data to be retained is discarded. The data upload module completes uploading the processed lightweight data to the upper-level data processing system.

[0038] The present disclosure discloses a method for lightweight data acquisition and a device for lightweight data processing for subway terminals. Compared with the existing terminal acquisition methods, the data redundancy is effectively reduced by filtering out the data with the same information within a short period of time. This method and device can be flexibly set on the subway edge-side terminal devices, and at the same time, combined with the current cloud-edge-end architecture, the determination conditions and rules can be flexibly configured, having the advantages of simple deployment and sustainable optimization.

[0039] Figure 7 Schematically shows an implementation example of data for emergency fault types according to an embodiment of the present disclosure; in combination with Figure 7 , the implementation manner of the emergency fault data is introduced. First, it is assumed that various rules have been set in the Figure 7 manner. Whether the data acquisition value is greater than 20, that is, if the status data parameter is greater than 20, it is considered that a fault has occurred and the alarm condition is met; whether the abnormal data has occurred 5 times within 3 minutes, that is, to determine whether the fault parameter has occurred multiple times. This setting rule is mainly used to exclude several self-recoverable faults that occur to the device from which the data is collected due to various reasons. The system has the ability to self-recover for such faults, so no alarm is generated; whether the same alarm data has been retained within 5 minutes, that is, to determine whether there is a situation of repeated reporting of the fault alarm. This setting rule is mainly used to screen out multiple repeated alarms, reduce the volume of uploaded data, and better guide the maintenance personnel to carry out fault troubleshooting work.

[0040] Through the embodiments of the present disclosure, in order to solve the problem of a large amount of redundant data collected by subway terminal devices, a lightweight data processing method and device for fault alarm data are proposed by combining means such as threshold determination, acquisition frequency determination, and redundancy determination. Specifically, through threshold determination, frequency determination, and redundancy determination, the fault data with the same information in the short term can be filtered out, solving the problem that maintenance personnel receive a large number of ineffective fault alarms during the operation and maintenance stage, and effectively improving the accuracy of facility and equipment alarms; for periodic data, the data redundancy can be effectively reduced by comparing the change amount with relevant time, reducing the volume of uploaded data, and reducing the data storage cost.

[0041] Figure 3 Schematically shows a working flowchart of a fault alarm module according to an embodiment of the present disclosure, as Figure 3 shown, using the fault alarm conditions to screen the data for emergency fault types to obtain the first data to be retained, including: in response to the failure to set the fault alarm conditions, determining whether the data for emergency fault types is non-enumerable data; if so, setting the alarm threshold of the fault alarm conditions; if not, setting the alarm enumeration value of the fault alarm conditions; screening the data for emergency fault types through the relative relationship between the data for emergency fault types and the alarm threshold or the consistency between the data for emergency fault types and the alarm enumeration value to obtain the first data to be retained.

[0042] As Figure 3As shown, the fault warning condition is to determine whether the collected data is eligible for retention. The setting method of condition i is the relative relationship with a certain threshold. For example, for non-enumerable data, condition i is set to not be higher than a certain threshold m or not be lower than a certain threshold; for enumerable data, condition i is a specific enumerable value. This module is mainly used to determine whether the collected data meets the warning conditions.

[0043] Among them, non-enumerable data includes analog quantities: physical quantities (voltage, current,...), crack size, surface flatness, curvature, etc. For example: for voltage, the trigger condition i is that the voltage value should be between -57.00V and -40.00V. The rest are listed. Enumerable data mainly includes digital quantities: switch quantities (such as the opening and closing states of a switch machine, either open or closed). This kind of enumerable data is mainly combined with other relevant quantities for correlation fault analysis.

[0044] Through the embodiments of the present disclosure, a flexible screening mechanism can set thresholds or enumerable values according to different fault situations, ensuring the accuracy of warnings. Avoid false alarms for less serious faults and reduce resource waste.

[0045] Figure 5 Schematically shows the working flowchart of the fault self-recovery module according to an embodiment of the present disclosure, as Figure 5 shown, using the fault self-recovery condition to screen the first proposed retention data to obtain the second proposed retention data, including: in response to the failure to set the fault self-recovery condition, setting the first preset time and preset number of times for the fault self-recovery condition; determining whether the fault corresponding to the first proposed retention data has occurred a preset number of times within the first preset time; if so, discarding the first proposed retention data; if not, using the first proposed retention data as the second proposed retention data.

[0046] As Figure 5 shown, for the first retention data of sudden fault types, the fault self-recovery condition s is to determine whether the collected data meets the set fault self-recovery condition. The setting method of rule s is: whether the above-mentioned fault data has occurred n times within x time. If it meets rule s, it enters the data redundancy module; otherwise, the data is discarded. This module is mainly used to filter out fault warnings that the device system can recover by itself.

[0047] Through the embodiments of the present disclosure, faults that can be recovered by themselves several times due to various reasons in the device where the data is collected are excluded. This type of fault system has the ability to recover by itself, so no warning occurs.

[0048] Figure 6 Schematically shows the working flowchart of the data redundancy module according to an embodiment of the present disclosure, as Figure 6As shown in the figure, the second data to be retained is screened using the data redundancy condition to obtain the retained sudden fault data, including: in response to the data redundancy condition not being set, setting the second preset time for the data redundancy condition; determining whether the fault corresponding to the second data to be retained has been reported within the second preset time; if so, discarding the second data to be retained; if not, using the second data to be retained as the retained sudden fault data.

[0049] As Figure 6 shown in the figure, for the second retained data of the sudden fault type, the data redundancy condition z is to determine whether the collected data meets the set data redundancy condition, and the rule z setting method is: no warning of the same type has been reported within x time. If the rule z is met, it enters the data upload module, otherwise the data is discarded. This module is mainly used to screen out repeatedly reported warning data.

[0050] Through the embodiments of the present disclosure, repeated upload of the same fault information in a short time is avoided, waste of system resources is reduced, and data transmission is ensured to be more timely and effective.

[0051] Figure 4 Schematically shows the working flowchart of the data change amount module according to the embodiments of the present disclosure, as Figure 4 shown in the figure, the periodic collection data is screened using the data change amount condition to obtain the retained periodic collection data, including: in response to the data change amount condition not being set, setting the preset change amount for the data change amount condition; calculating the difference between the periodic collection data and the periodic collection data collected at the previous time point; screening the periodic collection data through the relative relationship between the difference and the preset change amount to obtain the retained periodic collection data.

[0052] As Figure 4 shown in the figure, for periodic data, the data change amount condition i is to determine whether the collected data is eligible for retention, and the setting method of condition i is the relative relationship with a certain change increment. For example, condition i is that the change amount of the status value is not greater than m; this module is mainly used to determine that the collected periodic data meets the storage conditions and screen out redundant data carrying the same information.

[0053] In this embodiment, such periodic data can be defined by the user according to the specific scenario. For example, for parameters such as illuminance and current, the user can define which data needs to be periodically collected, what the collection period is, and what the threshold is according to the importance of various parameters to the system operation.

[0054] Through the embodiments of the present disclosure, the periodic collection data is screened by setting the change amount threshold, and only when the data changes greatly is it uploaded, avoiding the upload of a large amount of repeated data without actual changes. In this way, the efficiency of data collection and transmission can be effectively improved.

[0055] On the basis of the above embodiment, data is classified to obtain sudden fault data and periodic collection data, including: setting classification conditions; the classification conditions at least include parameters included in the sudden fault data and parameters included in the periodic collection data; and the collected data is classified according to the classification conditions to obtain sudden fault data and periodic collection data.

[0056] Through the embodiments of the present disclosure, clear classification helps to manage data more accurately, ensuring that each type of data is screened and processed in a targeted manner according to its characteristics without causing confusion. At the same time, it also facilitates subsequent data analysis and fault diagnosis.

[0057] Based on the above data collection method for subway terminals, the present disclosure also provides a data collection device for subway terminals. Figure 8 The device is described in detail.

[0058] Figure 8 The structural block diagram of the data acquisition device according to the embodiment of the present disclosure is schematically shown.

[0059] like Figure 8 As shown, the data acquisition device of this embodiment includes an original data determination module, a rule determination module and a data uploading module.

[0060] The original data determination module is used to classify data to obtain sudden fault data and periodic collection data; the rule determination module is used to retain the sudden fault data that conforms to the sudden fault rules and the periodic collection data that conforms to the periodic collection rules; wherein the sudden fault rules are used to determine whether to retain the sudden fault data according to the fault alarm situation; the periodic collection rules are used to determine whether to retain the periodic collection data according to the changes in the periodic collection data; the data upload module is used to upload the retained sudden fault data and the retained periodic collection data to the transmission network.

[0061] Figure 9 A block diagram of an electronic device suitable for implementing a data collection method for a subway terminal according to an embodiment of the present disclosure is schematically shown.

[0062] like Figure 9As shown, an electronic device 900 according to an embodiment of the present disclosure includes a processor 901, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 902 or a program loaded from a storage section 908 into a random access memory (RAM) 903. The processor 901 may include, for example, a general-purpose microprocessor (e.g., CPU), an instruction set processor, and / or a related chipset, and / or a dedicated microprocessor (e.g., an application-specific integrated circuit (ASIC)), etc. The processor 901 may also include on-board memory for caching purposes. The processor 901 may include a single processing unit or multiple processing units for performing different actions of the method flow according to an embodiment of the present disclosure.

[0063] In the RAM 903, various programs and data required for the operation of the electronic device 900 are stored. The processor 901, the ROM 902, and the RAM 903 are connected to each other via a bus 904. The processor 901 performs various operations of the method flow according to an embodiment of the present disclosure by executing the program in the ROM 902 and / or the RAM 903. It should be noted that the program may also be stored in one or more memories other than the ROM 902 and the RAM 903. The processor 901 may also perform various operations of the method flow according to an embodiment of the present disclosure by executing the program stored in the one or more memories.

[0064] According to an embodiment of the present disclosure, the electronic device 900 may further include an input / output (I / O) interface 905, and the input / output (I / O) interface 905 is also connected to the bus 904. The electronic device 900 may further include one or more of the following components connected to the I / O interface 905: an input section 906 including a keyboard, a mouse, etc.; an output section 907 including a cathode ray tube (CRT), a liquid crystal display (LCD), etc. and a speaker, etc.; a storage section 908 including a hard disk, etc.; and a communication section 909 including a network interface card such as a LAN card, a modem, etc. The communication section 909 performs communication processing via a network such as the Internet. A drive 910 is also connected to the I / O interface 905 as needed. A removable medium 911, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 910 as needed so that a computer program read from it can be installed into the storage section 908 as needed.

[0065] The present disclosure also provides a computer-readable storage medium, which may be included in the device / device / system described in the above embodiment; or may exist separately without being assembled into the device / device / system. The above computer-readable storage medium carries one or more programs, and when the one or more programs are executed, the method according to an embodiment of the present disclosure is implemented.

[0066] Embodiments of the present disclosure also include a computer program product, which includes a computer program containing program code for performing the method shown in the flowchart. When the computer program product runs in a computer system, the program code is used to cause the computer system to implement the method provided by the embodiments of the present disclosure.

[0067] According to embodiments of the present disclosure, the program code for executing the computer program provided by the embodiments of the present disclosure can be written in any combination of one or more programming languages. Specifically, these computing programs can be implemented using high-level procedural and / or object-oriented programming languages, and / or assembly / machine languages. The programming languages include, but are not limited to, such as Java, C++, Python, the "C" language, or similar programming languages. The program code can be executed entirely on the user computing device, partially on the user device, partially on a remote computing device, or entirely on a remote computing device or server. In the case of a remote computing device, the remote computing device can be connected to the user computing device through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computing device (for example, by connecting through the Internet using an Internet service provider).

[0068] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram can represent a module, a program segment, or a part of code, and the above-mentioned module, program segment, or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram or flowchart, and the combination of blocks in the block diagram or flowchart, can be implemented by a dedicated hardware-based system for performing the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0069] Those skilled in the art can understand that the features recited in the various embodiments and / or claims of the present disclosure can be combined or combined in various ways, even if such combinations or combinations are not explicitly recited in the present disclosure. In particular, without departing from the spirit and teachings of the present disclosure, the features recited in the various embodiments and / or claims of the present disclosure can be combined and combined in various ways. All such combinations and / or combinations fall within the scope of the present disclosure.

[0070] The embodiments of the present disclosure have been described above. However, these embodiments are for illustrative purposes only and are not intended to limit the scope of the present disclosure. Although the embodiments have been described separately above, this does not mean that the measures in each embodiment cannot be used advantageously in combination. The scope of the present disclosure is defined by the appended claims and their equivalents. Without departing from the scope of the present disclosure, those skilled in the art can make various substitutions and modifications, and these substitutions and modifications should all fall within the scope of the present disclosure.

Claims

1. A data collection method for a subway terminal, characterized in that: include: Classify the data to obtain sudden failure data and periodic collection data; retaining the sudden fault data that complies with the sudden fault rule and the periodic collection data that complies with the periodic collection rule; Uploading the retained sudden fault data and the retained periodic collection data to a transmission network; The sudden fault rule is used to determine whether to retain the sudden fault data according to the fault alarm situation; the periodic collection rule is used to determine whether to retain the periodic collection data according to the change of the periodic collection data.

2. The method according to claim 1, wherein: The sudden fault data that complies with the sudden fault rule and the periodic collection data that complies with the periodic collection rule are retained, including: The sudden fault type data is screened using the fault alarm condition to obtain first intended to be retained data; the first intended to be retained data is screened using the fault self-recovery condition to obtain second intended to be retained data; the second intended to be retained data is screened using the data redundancy condition to obtain retained sudden fault type data; Filtering the periodic collection data using the data change amount condition to obtain the retained periodic collection data; Among them, the fault alarm condition is used to determine whether an alarm is required; the fault self-recovery condition is used to determine whether the fault is self-recovered; the data redundancy condition is used to determine whether it is a repeated alarm; the data change condition is used to determine whether the periodic collection data is redundant.

3. The method according to claim 2, wherein: The sudden fault data is screened using the fault alarm condition to obtain first data to be retained, including: In response to the failure alarm condition not being set, determining whether the sudden failure type data is non-enumerable data; if so, setting an alarm threshold of the failure alarm condition; if not, setting an alarm enumeration value of the failure alarm condition; The sudden fault type data is screened according to the relative relationship between the sudden fault type data and the alarm threshold or the consistency between the sudden fault type data and the alarm enumeration value to obtain the first data to be retained.

4. The method according to claim 2, wherein: The first intended-to-retain data is screened by using the fault self-recovery condition to obtain the second intended-to-retain data, including: In response to not setting the fault self-recovery condition, setting a first preset time and a preset number of times of the fault self-recovery condition; Determine whether the fault corresponding to the first data to be retained has occurred a preset number of times within a first preset time; if so, discard the first data to be retained; if not, use the first data to be retained as the second data to be retained.

5. The method according to claim 2, wherein: The second data to be retained is screened by using the data redundancy condition to obtain retained sudden failure data, including: In response to the data redundancy condition not being set, setting a second preset time of the data redundancy condition; Determine whether the fault corresponding to the second data to be retained has been reported within a second preset time; if so, discard the second data to be retained; if not, use the second data to be retained as the retained sudden fault type data.

6. The method according to claim 2, wherein: The periodic collection data is filtered using the data change condition to obtain the retained periodic collection data, including: In response to the data change amount condition not being set, setting a preset change amount of the data change amount condition; Calculate the difference between the periodic collection data and the periodic collection data collected at the previous time point; The periodic collection data is screened through the relative relationship between the difference and the preset variation to obtain the retained periodic collection data.

7. The method according to claim 1, wherein: Classify the data to obtain sudden failure data and periodic collection data, including: Setting classification conditions; the classification conditions at least include parameters included in the sudden fault data and parameters included in the periodic acquisition data; The collected data is classified according to the classification conditions to obtain sudden fault data and periodic collection data.

8. A data collection device for a subway terminal, characterized in that: The device can be used to implement the method according to any one of claims 1 to 7, and the device comprises: The original data determination module is used to classify the data and obtain the sudden fault data and periodic collection data; A rule determination module, used to retain the sudden fault data that complies with the sudden fault rule and the periodic collection data that complies with the periodic collection rule; wherein the sudden fault rule is used to determine whether to retain the sudden fault data according to the fault alarm situation; and the periodic collection rule is used to determine whether to retain the periodic collection data according to the change of the periodic collection data; The data uploading module is used to upload the reserved sudden fault data and the reserved periodic collection data to the transmission network.

9. An electronic device, comprising: one or more processors; a storage device for storing one or more programs, When the one or more programs are executed by the one or more processors, the one or more processors are enabled to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having executable instructions stored thereon, which, when executed by a processor, causes the processor to execute the method according to any one of claims 1 to 7.

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