Base station equipment data fuzzy analysis method and system

Abstract

The invention provides a base station equipment data fuzzy analysis method and system, and relates to the technical field of data analysis, and the method comprises the steps: obtaining base station equipment data; acquiring a data message and a fluctuation reference range of message parameters in the data message based on the base station equipment data; determining a target parameter interval of N message parameters in the data message; n is any positive integer; obtaining a target message parameter in the data message according to a target parameter interval; based on the target message parameter, acquiring a change trend of M message parameters; m < = N, and M is any positive integer; if the change trends are consistent, acquiring a fluctuation range of M message parameters, and judging whether the fluctuation range is within the fluctuation reference range or not; and if yes, analyzing the data message to obtain data information, so as to solve the problem that the existing base station equipment data analysis mode can only perform data analysis on the intelligent equipment in the normal operation process.

Description

Technical Field

[0001] This application relates to the technical field of data parsing, and particularly relates to a method and system for fuzzy parsing of base station equipment data. Background Art

[0002] With the continuous development of communication technologies, the types of intelligent devices in base station computer rooms are increasing, and the complexity of data communication is also continuously increasing. Devices produced by different manufacturers use different data message formats to transmit information, which requires the monitoring system to accurately identify and parse these diverse message formats, so as to extract the operating data of the devices and achieve comprehensive monitoring of the devices.

[0003] Currently, the operating data of intelligent devices in base station computer rooms is extracted by parsing the messages in the operating data, determining whether the start symbol and end symbol are included in the message, verifying whether the length of the operating data is correct, and judging whether the operating data is correct and complete through cyclic redundancy check, so as to achieve the monitoring of intelligent devices in base station computer rooms.

[0004] However, the above method can only monitor intelligent devices during normal operation. However, there are still many intelligent devices with abnormal operation in the base station computer room site. For example, when an intelligent device is severely interfered by the environment during communication, such as electromagnetic interference, radio frequency interference, etc., although the frame format byte count of the message can be normally verified, the data frame of the message cannot be normally verified, resulting in the inability to parse the operating data according to the above message parsing rules. Summary of the Invention

[0005] This application provides a method and system for fuzzy parsing of base station equipment data to solve the technical problem that the existing data parsing method for base station equipment can only perform data parsing on intelligent devices during normal operation.

[0006] The first aspect of this application provides a method for fuzzy parsing of base station equipment data, including: Obtain base station equipment data; Based on the base station equipment data, obtain a data message and the fluctuation reference range of message parameters in the data message; Determine the target parameter interval of N message parameters in the data message; N is any positive integer; Obtain the target message parameters in the data message according to the target parameter interval; Based on the target message parameters, obtain the change trend of M message parameters; M ≤ N, M is any positive integer; If the change trends are consistent, obtain the fluctuation range of M message parameters, and judge whether the fluctuation range is within the fluctuation reference range; if so, parse the data message to obtain data information.

[0007] In some embodiments, the step of obtaining base station device data includes: Collect base station device data into a cache library; Determine whether the collection time interval of the base station device data is greater than or equal to a preset time interval. If so, obtain the base station device data and clear the base station device data in the cache library; If not, retain the base station device data in the cache library until the collection time interval of the base station device data in the cache library is greater than or equal to the preset time interval.

[0008] In some embodiments, the step of determining the target parameter interval of N message parameters in the data packet includes: Define the parameter interval of N message parameters in the data packet; Determine whether the N message parameters in the data packet can be obtained using the parameter interval. If so, based on the parameter interval, determine the target parameter interval; If not, adjust the parameter interval until the N message parameters in the data packet can be obtained using the parameter interval.

[0009] In some embodiments, after the step of obtaining the change trend of M message parameters based on the target message parameters, it includes: If the change trends are inconsistent, determine whether an alarm message is received; the alarm message is the message parameter for which the change trend has not been obtained among the M message parameters; If so, according to the alarm message, determine the number of message parameters for which the change trend has not been obtained; Determine the value of M according to the number of message parameters.

[0010] In some embodiments, after the step of determining whether an alarm message is received, it includes: If so, send the alarm message to a set device; the set device is an electronic device capable of receiving the alarm message.

[0011] In some embodiments, after the step of determining whether an alarm message is received, it further includes: If not, re-execute the step of determining the target parameter interval of N message parameters in the data packet.

[0012] In some embodiments, after the step of determining whether the fluctuation range is within the fluctuation reference range, it further includes: If not, re-execute the step of determining the target parameter interval of N message parameters in the data packet.

[0013] In some embodiments, the method further includes: Determine the data frame of the base station device data; Judge whether the data packet structures in the data frame are the same. If so, store the data packet structure and the position characteristics for obtaining M packet parameters correspondingly; the data packet structure is the parameter interval of the packet parameters in the data packet. Wherein, when obtaining data frames with the same data packet structure, obtain the fluctuation range of M packet parameters according to the position characteristics, and judge whether the fluctuation range is within the fluctuation reference range; if so, parse the data packet to obtain data information.

[0014] In some embodiments, the method further includes: Store the data packet structure and the position characteristics for obtaining M packet parameters correspondingly into a database; After the step of obtaining the data packet and the fluctuation reference range of the packet parameters in the data packet based on the base station device data, it further includes: Judge whether the data packet structure of the base station device data is consistent with the data packet structure stored in the database. If so, obtain the data packet structure and the position characteristics for obtaining M packet parameters correspondingly, and obtain the fluctuation range of M packet parameters according to the position characteristics, and judge whether the fluctuation range is within the fluctuation reference range; if so, parse the data packet to obtain data information.

[0015] A second aspect of the present application provides a fuzzy parsing system for base station device data, including: An acquisition module, which is configured to acquire base station device data; Based on the base station device data, obtain a data packet and the fluctuation reference range of the packet parameters in the data packet; A determination module, which is configured to determine the target parameter interval of N packet parameters in the data packet; N is any positive integer; Obtain the target packet parameters in the data packet according to the target parameter interval; An analysis module, which is configured to obtain the change trend of M packet parameters based on the target packet parameters; M≤N, and M is any positive integer; If the change trends are consistent, obtain the fluctuation range of M packet parameters, and judge whether the fluctuation range is within the fluctuation reference range; if so, parse the data packet to obtain data information.

[0016] The present application provides a method and system for fuzzy parsing of base station device data. The method includes: obtaining base station device data; based on the base station device data, obtaining a data packet and a fluctuation reference range of packet parameters in the data packet; determining a target parameter interval of N packet parameters in the data packet, where N is any positive integer; obtaining target packet parameters in the data packet according to the target parameter interval; based on the target packet parameters, obtaining a change trend of M packet parameters, where M ≤ N and M is any positive integer; if the change trends are consistent, obtaining a fluctuation range of the M packet parameters and determining whether the fluctuation range is within the fluctuation reference range; if so, parsing the data packet to obtain data information, so as to solve the problem that the current base station device data parsing method can only parse data of intelligent devices during normal operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the present application, the drawings required for the embodiments will be briefly introduced below. Obviously, for those of ordinary skill in the art, other drawings can also be obtained based on these drawings without creative efforts.

[0018] Figure 1 It is a flowchart of the method for fuzzy parsing of base station device data in the present application; Figure 2 It is a flowchart of the method for obtaining base station device data in the present application; Figure 3 It is a flowchart of the method for determining the target parameter interval of N packet parameters in the data packet in the present application; Figure 4 It is a flowchart of the method for interaction between base station device data and a database in the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0019] In order to enable those skilled in the art to better understand the technical solutions in the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present application.

[0020] Since in some technologies, the base station device data parsing method can only parse data of intelligent devices during normal operation, to solve this technical problem, the present application provides a method and system for fuzzy parsing of base station device data. The method and system for fuzzy parsing of base station device data will be described below: Exemplarily, there are the following two common data packet formats in intelligent devices: The YDT-1363 frame format specified by the Ministry of Information Industry in 2005 is as follows: SOI + VER + ADR + CID1 + CID2 + LENGTH + INFO + CHKSUM + EOI; where, SOI - start bit flag, VER - communication protocol version number, ADR - device address, CID1 - control code, CID2 - command (or response RTN), LENGTH - length and length check, INFO - command or response, CHKSUM - checksum, EOI - end code. The above data format is clearly defined.

[0021] The ModBus format proposed by Modicon in 1979: start bit (idle interval) + device address + function code + data field + CRC checksum + end bit (idle interval). The message structure of the above data format is simple and the information transfer is efficient.

[0022] Exemplarily, in industrial automation, the Internet of Things (IoT), and various device monitoring systems, accurately and efficiently obtaining the operating data of devices is the basis for realizing advanced functions such as remote device monitoring, fault warning, and performance optimization. To ensure that the data extracted from the device is accurate and can be correctly parsed and utilized by the monitoring system, generally, in accordance with the data message format provided by the manufacturer, a comprehensive and detailed integrity verification is performed on the received data, including but not limited to the correctness of the start symbol, the matching of the end symbol, the reasonableness of the data length, and the accuracy of the checksum.

[0023] Among them, the start symbol is the beginning identifier of the data message, and its function is to inform the receiving party of the start position of the data stream. Different devices or protocols may use different start symbols, such as specific characters, byte sequences, or flag bits. Verifying the correctness of the start symbol can ensure that the received data is indeed sent by the target device and is parsed from the correct position.

[0024] The end symbol marks the termination of the data message, and it helps the receiving party determine the complete boundary of the data. Similar to the start symbol, the form of the end symbol also varies depending on the device or protocol. By checking the end symbol, it can be ensured that the received data has not been truncated or additional content has been added due to transmission errors or interference.

[0025] The data length refers to the number of valid data bytes actually contained in the data message. When the manufacturer defines the data message format, it usually clearly specifies the length of each field and the expected length of the entire message. Verifying the data length can prevent buffer overflow problems caused by overly large data packets and also ensure that errors do not occur during the parsing process due to insufficient data.

[0026] A checksum (also known as a check code, CRC check, etc.) is a mechanism used to detect errors that occur during data transmission. Before sending data, the sender calculates the checksum of the data according to a certain algorithm and attaches it to the end of the data packet. After receiving the data, the receiver recalculates the checksum and compares it with the received checksum. If the two are consistent, it is considered that no error has occurred during data transmission; if they are inconsistent, it indicates that the data may have been corrupted and needs to be retransmitted or discarded. The above steps verify the integrity of the data, and the monitoring system can ensure that the device operation data extracted is accurate, thereby realizing real-time monitoring of the device status, timely discovery and handling of faults, and continuous optimization of device performance.

[0027] However, there are still many abnormal intelligent devices on the site of the base station computer room. For example: 1. Communication is severely interfered by the environment. The number of bytes in the frame format can be verified, but the data frame can never be verified and cannot be parsed according to the normal rules; 2. The format bytes cannot be normally verified, but they are regular, and valuable data can be found; 3. The listening device is foreign, has been used for a long time, has no technical support and no information can be found, and data cannot be collected, and only regular data packets can be listened to.

[0028] As Figure 1 shown, it is the flowchart of the method for fuzzy parsing of base station device data in this application.

[0029] In view of the above problems, the first aspect of this application provides a method for fuzzy parsing of base station device data, including the following steps: S100: Obtain base station device data; The base station device is a key infrastructure that constitutes a mobile communication network and is responsible for functions such as wireless signal transceiver, processing, and connection to the core network.

[0030] As Figure 2 shown, it is the flowchart of the method for obtaining base station device data in this application.

[0031] The step of obtaining base station device data includes the following sub-steps: S110: Collect base station device data into the cache library; The cache library is used to cache the base station device data.

[0032] S120: Determine whether the acquisition time interval of the base station device data is greater than or equal to the preset time interval T[n]. If so, obtain the base station device data and clear the base station device data in the buffer library; S130: If not, retain the base station device data in the buffer library until the acquisition time interval of the base station device data in the buffer library is greater than or equal to the preset time interval T[n]. It can be understood that regardless of whether the data content contains garbled characters, error codes or is missing, as long as data is received within the defined time period, i.e., the preset time interval T[n] (such as 10 seconds, 1 minute), the obtained data can be vaguely considered to be complete.

[0033] S200: Based on the base station device data, obtain the data packet and the fluctuation reference range of the packet parameters in the data packet; The packet parameter is a field in the protocol header or data body used to describe, control or identify the characteristics of the packet, and the packet parameter is used to help both communication parties understand the packet content and behavior. Among them, the packet parameters generally fluctuate within the fluctuation reference range. Due to the real-time changes in the network environment (such as channel quality, load, delay), the packet parameters need to be dynamically adjusted to maintain the communication quality.

[0034] S300: Determine the target parameter interval D[n] of N packet parameters in the data packet; N is any positive integer; Since some protocols in the base station device data strictly define the parameter interval (such as fixed-length fields, delimiters), the packet parameter interval can be completely determined at this time. Therefore, by setting the target parameter interval D[n] of N packet parameters in the data packet in advance, N packet parameters in the data packet can be selected for data fuzzy analysis. For example: The A-phase voltage value is about 220V, the B-phase voltage value is about 220V, and the C-phase voltage value is about 220V. The position intervals D1 and D2 of fixed byte lengths should be in the message frame, and the data position can be basically determined. It can be understood that due to the influence on communication, the data packet is affected to a certain extent. Therefore, the data packet cannot be parsed according to the current packet parsing method, and only a fuzzy parsing method can be adopted, that is, by selecting several packet parameters (not interfered) in the data packet for parsing.

[0035] Exemplarily, the packet parameter is a field or data item in the data packet used to transmit information, control behavior or identify characteristics, and is a core component of the communication protocol. Its role is to carry the data that both communication parties need to exchange (such as user requests, device status), guide the receiving party on how to process the packet (such as whether an answer is required, timeout time), and uniquely identify the packet or communication entity (such as source / destination address, session ID).

[0036] As Figure 3 shown, it is the method flow chart for determining the target parameter interval of N packet parameters in this application.

[0037] The step of determining the target parameter interval of N message parameters in the data packet includes the following sub-steps: S310: Define the parameter interval of N message parameters in the data packet; the N message parameters can be defined in advance through the position interval, i.e., the parameter interval, between the message parameters.

[0038] S320: Determine whether the N message parameters in the data packet can be obtained using the parameter interval. If so, based on the parameter interval, determine the target parameter interval; after selecting the parameter interval of the N message parameters, it is necessary to test in advance whether the N message parameters in the data packet can be obtained using the parameter interval. If so, it means that the selected parameter interval value is correct and can be used as the target parameter interval for message fuzzy parsing work.

[0039] S330: If not, adjust the parameter interval until the N message parameters in the data packet can be obtained using the parameter interval. If the N message parameters in the data packet cannot be obtained through the defined parameter interval, it is necessary to adjust the parameter interval of the N message parameters again until the N message parameters in the data packet can be obtained using the parameter interval, and output the corresponding target parameter interval.

[0040] S400: Obtain the target message parameters in the data packet according to the target parameter interval; after determining the target parameter interval, the target message parameters in the data packet can be obtained according to the target parameter interval, laying a foundation for subsequent data packet fuzzy parsing.

[0041] S500: Obtain the change trend of M message parameters based on the target message parameters; M ≤ N, and M is any positive integer; for example: two groups of batteries will charge and discharge simultaneously, and the change direction of the current value is the same; the same type of values collected by multiple adjacent probes should also have consistency in the change direction. It can be understood that when multiple parameters are driven by the same physical process, their change directions must be the same. Among them, due to the influence of interference in the message data, the change trend of individual message parameters may change. Therefore, by obtaining the change trend of M message parameters among the N message parameters, it is possible to determine whether the message parameters are affected by interference, thereby further improving the accuracy of the selected target message parameters and providing accurate and interference-free target message parameters for subsequent data fuzzy parsing.

[0042] After the step of obtaining the change trend of M message parameters based on the target message parameters, it includes the following sub-steps: S510: If the change trends are inconsistent, determine whether an alarm message is received; the alarm message is the message parameter for which the change trend has not been obtained among the M message parameters; generally, the change trend data of the message parameter is analyzed by the analysis module of the processor (such as a single-chip microcomputer, FPGA or embedded system) to calculate the numerical change of the message parameter in the time series and obtain the change rate of the parameter, so as to obtain the change trend of the message parameter. However, occasionally, there may be a situation where an individual analysis module in the processor is damaged, resulting in the inability to analyze the change trend of the message parameter at the corresponding position. Generally, the processor will have a special self-check module to check the analysis module in real time. When an individual analysis module in the processor is damaged, the self-check module will send an alarm message to the set device to remind the maintenance personnel to replace or repair the processor in time.

[0043] After the step of determining whether the alarm message is received, the following steps are included: S511: If so, send the alarm message to the set device; the set device is an electronic device capable of receiving the alarm message. The electronic device includes, but is not limited to, electronic devices such as mobile phones and monitors that can display electronic information. By sending the alarm message to the set device, the maintenance personnel can replace or repair the processor in time to prevent the fuzzy parsing work of the data message from being affected.

[0044] After the step of determining whether the alarm message is received, the following steps are further included: S512: If not, re-execute the step of determining the target parameter interval of the N message parameters in the data message. If the alarm message is not received, it means that the processor is not damaged, and it is possible that the corresponding target message parameter is interfered. Therefore, it is necessary to re-select the message parameter until the selected target message parameter conforms to the characteristic of consistent change trend.

[0045] S520: If so, according to the alarm message, determine the number of message parameters for which the change trend has not been obtained; since the maintenance personnel cannot immediately replace or repair the processor, but the fuzzy parsing work of the data message still needs to be carried out, it is necessary to reduce the value of M, that is, reduce the number of analysis modules in the processor, to avoid the influence of the damaged analysis module in the processor on the analysis result of the message parameter change trend.

[0046] S530: Determine the value of M according to the number of message parameters. For example, if the number of message parameters is 1, the updated M 新 = M - 1.

[0047] S600: If the change trends are consistent, obtain the fluctuation range of M message parameters, and determine whether the fluctuation range is within the fluctuation reference range F[n]; if so, parse the data message to obtain data information. For example, the mains frequency is generally around 50 Hz, and the total system voltage is generally around 53.5 V. If the adjacent data is the load current, then the total system voltage and the load current cannot change suddenly, and the values can only fluctuate slowly up and down. If data that conforms to the rule is found, it can be vaguely considered correct and the values can be extracted. Due to the slight deviation of the frequency of the hardware clock source (such as a crystal oscillator), the message sending / receiving time points fluctuate randomly. For example, in Ethernet, clock jitter may cause the message interval to fluctuate within ±50 ns. Therefore, message parameters generally fluctuate within a certain fluctuation reference range F[n].

[0048] After the step of determining whether the fluctuation range is within the fluctuation reference range F[n], the following steps are further included: S610: If not, re-execute the step of determining the target parameter interval of N message parameters in the data message. If the fluctuation range of the message parameters is not within the fluctuation reference range F[n], it is possible that the corresponding message parameters are interfered, so it is necessary to re-select the message parameters until the fluctuation range of the selected target message parameters is within the fluctuation reference range F[n].

[0049] The method further includes the following steps: S700: Determine the data frame of the base station device data; a data frame is a protocol data unit of the data link layer, including a frame header, a data part, and a frame tail. Among them, the frame header and the frame tail contain some necessary control information, such as synchronization information, address information, error control information, etc.; the data part contains the data passed down from the network layer, such as IP data packets, etc. Among them, the base station device data contains several data frames.

[0050] S800: Determine whether the data message structures in the data frames are the same. If so, store the data message structure and the position characteristics corresponding to obtaining M message parameters; the data message structure is the parameter interval of the message parameters in the data message; among them, when data frames with the same data message structure are obtained, obtain the fluctuation range of M message parameters according to the position characteristics, and determine whether the fluctuation range is within the fluctuation reference range; if so, parse the data message to obtain data information. Utilize the regularity of the device data. For example, there are a total of 8 different data messages, and after 8 frames, the previous data frame structure messages will appear again in the previous order. When the data frame messages appear and repeat according to a known rule, refer to the retained frame structure characteristics of the previous parsing, and directly and vaguely parse the data; thereby improving the speed of fuzzy parsing of data messages.

[0051] It can be understood that the data packet structures in the base station device data in each data frame may be the same. If the data packet structures are the same, there is no need to gradually perform fuzzy parsing on the data packets of the corresponding data frames from the step of defining the parameter intervals of the packet parameters. Instead, it can be directly analyzed according to the packet parameter fuzzy parsing method in the previous data frames with the same structure. For example, the target packet parameters can be directly selected according to the positions of the target packet parameters selected in the previous data frames with the same structure, so as to perform fuzzy parsing on the data through the target packet parameters.

[0052] As Figure 4 shown, it is a flowchart of the method for the interaction between the base station device data and the database in this application.

[0053] The method further includes the following steps: S900: Store the data packet structure and the position features corresponding to obtaining M packet parameters in the database; the database is used to store the data packet structures of the base station device data and the position features of the M packet parameters selected in each data frame, that is, the parameter intervals of the M packet parameters.

[0054] After the step of obtaining the data packet and the fluctuation reference range of the packet parameters in the data packet based on the base station device data, the following steps are further included: S1000: Determine whether the data packet structure of the base station device data is consistent with the data packet structure stored in the database. If so, obtain the data packet structure and the position features corresponding to obtaining M packet parameters, and obtain the fluctuation ranges of the M packet parameters according to the position features, and determine whether the fluctuation ranges are within the fluctuation reference range; if so, parse the data packet to obtain data information. The data packet structures in the base station device data in each data frame may be the same. If the data packet structures are the same, there is no need to gradually perform fuzzy parsing on the data packets of the corresponding data frames from the step of defining the parameter intervals of the packet parameters. Instead, the position features of the M packet parameters with the same data packet structure can be obtained from the database to perform fuzzy parsing on the data, thereby improving the fuzzy parsing efficiency of the data.

[0055] It should be noted that the base station device data fuzzy parsing method provided in this application can solve the problem of packet parsing of interfered devices and is also applicable to standard data packets, achieving the purpose of monitoring base station intelligent devices and maintaining the safe operation of the base station.

[0056] Since the data of base station equipment may be interfered and the packets in the data cannot be parsed according to the normal parsing rules, the present application provides a fuzzy parsing method for base station equipment data. First, by determining the target parameter intervals of N packet parameters in the data packet, the positions of the packet parameters can be accurately obtained, and the target packet parameters in the data packet are obtained according to the target parameter intervals. Secondly, based on the target packet parameters, the change trends of M packet parameters are obtained. If the change trends are consistent, the fluctuation ranges of the M packet parameters are obtained, and it is judged whether the fluctuation ranges are within the fluctuation reference ranges. If so, the data packet is normally parsed to obtain data information. If the change trends are inconsistent, or the fluctuation ranges are not within the fluctuation reference ranges, the target parameter intervals of N packet parameters in the data packet are re-determined until the fluctuation ranges are within the fluctuation reference ranges, and the data packet is normally parsed to obtain data information. According to the rule that the same type of data packets of base station equipment will appear repeatedly at intervals, the characteristics of non-standard data packets are found, a dedicated data packet structure is customized, and a fuzzy parsing method is used to extract data information.

[0057] The present application provides a fuzzy parsing method for base station equipment data, which has the following effects: 1. Strong adaptability: For non-standard format packets, interfered packets or packets without format definition of intelligent equipment in the base station computer room, a fuzzy parsing method can be used to achieve monitoring.

[0058] 2. Strong customization: According to the data rules of specific equipment, dedicated fuzzy parsing parameters are configured. The longer the equipment is monitored, the more reliable the fuzzy parsing parameters are.

[0059] 3. Reduced maintenance cost of equipment: For equipment with serious communication environment interference and old equipment without data and technical support, data monitoring can also be realized, reducing the equipment procurement cost and maintaining the safe operation of the base station.

[0060] 4. Low engineering implementation difficulty: Only need to remotely upgrade the foreground monitoring program, adjust and customize the parameters of multiple related data and adjacent data according to the prompts, and save the correctly parsed data structure to achieve fuzzy parsing.

[0061] 5. Strong feasibility: No matter what type of dynamic environment monitoring base station, the fuzzy parsing method for base station equipment data provided by the present application can be adopted.

[0062] The second aspect of the present application provides a fuzzy parsing system for base station equipment data, including: An acquisition module, which is configured to acquire base station equipment data; Based on the base station equipment data, acquire the data packet and the fluctuation reference range of the packet parameters in the data packet; A determination module, configured to determine a target parameter interval of N message parameters in the data packet; N is any positive integer; Obtain the target message parameters in the data packet according to the target parameter interval; An analysis module, configured to obtain the change trends of M message parameters based on the target message parameters; M ≤ N, and M is any positive integer; If the change trends are consistent, obtain the fluctuation ranges of the M message parameters, and determine whether the fluctuation ranges are within the fluctuation reference ranges; if so, analyze the data packet to obtain data information.

[0063] It should be noted that for the effects during the operation of the above system embodiment, reference can be made to the effects of the above method embodiment, which will not be elaborated here.

[0064] The above specific implementation manners further elaborate on the objectives, technical solutions, and beneficial effects of the embodiments of the present application. It should be understood that the above are only the specific implementation manners of the embodiments of the present application, and are not used to limit the protection scope of the embodiments of the present application. Any modifications, equivalent replacements, improvements, etc. made on the basis of the technical solutions of the embodiments of the present application shall be included in the protection scope of the embodiments of the present application.

Claims

1. A method for fuzzy parsing of base station equipment data, characterized in that: include: Get base station equipment data; Based on the base station equipment data, obtaining a data message and a fluctuation reference range of a message parameter in the data message; Determining target parameter intervals of N message parameters in the data message; N is any positive integer; Obtaining target message parameters in the data message according to the target parameter interval; Based on the target message parameters, obtaining the change trends of M message parameters; M≤N, M is any positive integer; If the change trends are consistent, obtain the fluctuation ranges of the M message parameters, and determine whether the fluctuation ranges are within the fluctuation reference range; if so, parse the data message to obtain data information.

2. A method for fuzzy parsing of base station equipment data according to claim 1, characterized in that: The step of obtaining base station equipment data includes: Collect base station equipment data into the cache library; Determine whether the base station equipment data collection time interval is greater than or equal to a preset time interval, and if so, obtain the base station equipment data and clear the base station equipment data in the cache library; If not, the base station equipment data is retained in the cache library until the collection time interval of the base station equipment data in the cache library is greater than or equal to the preset time interval.

3. A method for fuzzy parsing of base station equipment data according to claim 1, characterized in that: The step of determining target parameter intervals of N message parameters in the data message comprises: Defining parameter intervals of N message parameters in the data message; Determine whether the N message parameters in the data message can be obtained by using the parameter interval, and if so, determine a target parameter interval based on the parameter interval; If not, adjust the parameter interval until N message parameters in the data message can be obtained using the parameter interval.

4. A method for fuzzy parsing of base station equipment data according to claim 1, characterized in that: After the step of obtaining the change trends of M message parameters based on the target message parameters, the method further comprises: If the change trends are inconsistent, determine whether an alarm message is received; the alarm message is a message parameter of the M message parameters that has not obtained a change trend; If yes, determining the number of message parameters for which no change trend has been obtained according to the alarm information; The value of M is determined according to the number of message parameters.

5. A method for fuzzy parsing of base station equipment data according to claim 4, characterized in that: After the step of determining whether the alarm information is received, the following steps are included: If so, the alarm information is sent to a setting device; the setting device is an electronic device capable of receiving the alarm information.

6. A method for fuzzy parsing of base station equipment data according to claim 4, characterized in that: After the step of determining whether the alarm information is received, the method further includes: If not, the step of determining the target parameter interval of the N message parameters in the data message is re-executed.

7. A method for fuzzy parsing of base station equipment data according to claim 1, characterized in that: After the step of determining whether the fluctuation range is within the fluctuation reference range, the method further includes: If not, the step of determining the target parameter interval of the N message parameters in the data message is re-executed.

8. A method for fuzzy parsing of base station equipment data according to claim 1, characterized in that: The method further comprises: Determine a data frame of the base station equipment data; Determine whether the data message structures in the data frames are the same, and if so, store the data message structures and the corresponding position features of the M message parameters; the data message structure is the parameter interval of the message parameters in the data message; Among them, when obtaining a data frame with the same data message structure, the fluctuation range of M message parameters is obtained according to the position feature, and it is determined whether the fluctuation range is within the fluctuation reference range; if so, the data message is parsed to obtain data information.

9. A method for fuzzy parsing of base station equipment data according to claim 1, characterized in that: The method further comprises: The data message structure and the corresponding location features of the M message parameters are stored in a database; After the step of acquiring the data message and the fluctuation reference range of the message parameter in the data message based on the base station equipment data, the method further includes: Determine whether the data message structure of the base station equipment data is consistent with the data message structure stored in the database. If so, obtain the data message structure and the corresponding position characteristics of M message parameters, and obtain the fluctuation range of the M message parameters according to the position characteristics, and determine whether the fluctuation range is within the fluctuation reference range; if so, parse the data message to obtain data information.

10. A base station equipment data fuzzy analysis system, characterized in that: include: An acquisition module, wherein the acquisition module is configured to acquire base station equipment data; Based on the base station equipment data, obtaining a data message and a fluctuation reference range of a message parameter in the data message; A determination module, the determination module is configured to determine a target parameter interval of N message parameters in the data message; N is any positive integer; Obtaining target message parameters in the data message according to the target parameter interval; A parsing module, wherein the parsing module is configured to obtain a change trend of M message parameters based on the target message parameters; M≤N, M is any positive integer; If the change trends are consistent, obtain the fluctuation ranges of the M message parameters, and determine whether the fluctuation ranges are within the fluctuation reference range; if so, parse the data message to obtain data information.

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