Base station safety monitoring method and system based on data relevance verification

Abstract

The invention provides a base station safety monitoring method and system based on data relevance verification, and relates to the technical field of telecommunication base station safety management, and the method comprises the steps: obtaining the electrical parameter data of a telecommunication base station, and carrying out the preprocessing operation of the electrical parameter data; setting a threshold range for each piece of electrical parameter data, comparing the preprocessed electrical parameter data with the threshold range, and judging whether each piece of electrical parameter data is abnormal or not; and when an abnormality occurs, sending alarm electronic information to an administrator, and sending an alarm sound on the site where the telecommunication base station is located. According to the method, the node data is acquired based on the sensors, meanwhile, the accuracy verification is performed on the data, the correlation relationship between the monitoring nodes is established by using the base station circuit mesh diagram, and then the result with the maximum probability is determined by adopting a voting form, so that misjudgment caused by data exception due to local and certain sensor exception can be prevented, and the accuracy of the data is improved. And the early warning precision is improved.

Description

Technical Field

[0001] The present application relates to the technical field of telecommunication base station security management, and in particular to a base station security monitoring method and system based on data correlation verification. Background Art

[0002] With the rapid development of 5G technology, the security of telecommunications base stations, as key infrastructure of communication networks, has received increasing attention. Traditional base station security monitoring systems rely on video surveillance and simple alarm mechanisms, which can only issue alarms after damage occurs and cannot provide early warnings, making it difficult to avoid losses. In addition, base stations are mostly located in remote areas, making it difficult for personnel to patrol and inspect, and the monitoring efficiency is low. With the development of the field of artificial intelligence, existing technologies use artificial intelligence to replace manual monitoring and realize automatic monitoring and early warning functions, which has been widely used.

[0003] For example, the patent with patent publication number CN117437746A discloses a security management and early warning system based on artificial intelligence, and the security management and early warning system includes a detection unit, a control and processing unit, an early warning feedback unit and a security execution unit; the detection unit is used to detect various environments in the park, refine the detection results, and convert them into electrical signals, and then transmit them to the control and processing unit; the control and processing unit is used to receive the electrical signal of the detection unit, and then analyze and process the signal based on artificial intelligence, and start the early warning feedback unit and the security execution unit accordingly according to the processing result; the early warning feedback unit is used to receive the control command of the control and processing unit, and according to the command, trigger the early warning signal, and perform the early warning operation, and at the same time feed back the early warning working status to the control and processing unit; the security execution unit is used to receive the control command of the control and processing unit, and according to the command, perform security remediation or security protection operations, and then cooperate with the detection unit to re-detect the execution result of the security execution unit.

[0004] The problems and defects of the existing technology in base station security monitoring mainly include:

[0005] 1. Use sensors to obtain node information, and then make judgments based on the monitoring information. However, when the sensor obtains node information, the data obtained by the sensor may be inaccurate due to sensor performance degradation, abnormal damage, etc., which will affect the final decision and cause the defect of low warning accuracy;

[0006] 2. Sensor performance degradation and abnormal damage: When the sensor obtains node information, performance degradation or abnormal damage may cause the acquired data to be inaccurate, affecting the final decision and causing the defect of low warning accuracy.

[0007] 3. High false alarm rate: In a diverse communication environment, the communication data processed by telecommunications base stations will be interfered by noise and easily be mistaken for security anomalies, resulting in warning errors.

[0008] 4. Poor adaptability of denoising technology: Telecommunication base stations process various types of communication data, which requires denoising technology to have good adaptive characteristics. Traditional adaptive filtering methods (such as the LMS algorithm) use a fixed learning rate, which cannot adapt to the diverse characteristics of communication data and affects the denoising effect.

[0009] These problems and defects indicate that the existing base station safety monitoring technology needs further development and improvement to improve the accuracy of early warnings, reduce false alarm rates, adapt to diverse communication data, reduce the impact of electromagnetic radiation, enhance the security of physical equipment and operating systems, and improve the intelligent management and control capabilities of construction safety. Summary of the invention

[0010] The present application shows a base station security monitoring method and system based on data correlation verification.

[0011] In a first aspect, the present application shows a base station security monitoring method based on data relevance verification, the method comprising:

[0012] Acquiring electrical parameter data of a telecommunication base station and performing a preprocessing operation on the electrical parameter data;

[0013] Setting a threshold range for each of the electrical parameter data, and comparing the preprocessed electrical parameter data with the threshold range to determine whether each of the electrical parameter data is abnormal;

[0014] When an abnormality occurs, an alarm electronic message is sent to the administrator, and an alarm sound is sounded on site where the telecommunication base station is located.

[0015] Furthermore, the preprocessing operation on the electrical parameter data includes: filling missing values, removing duplicate values ​​and verifying the accuracy of the electrical parameter data.

[0016] Furthermore, the step of filling missing values ​​includes:

[0017] Establishing a two-dimensional coordinate system with the time axis as the horizontal axis and the electrical parameter data as the vertical axis;

[0018] Taking the frequency at which the sensor collects the electrical parameter data as a period, selecting corresponding nodes on the horizontal axis;

[0019] Fill the newly acquired electrical parameter data into the vertical coordinate of each node. If the sensor does not collect the electrical parameter data of the current node, the vertical coordinate of the current node is left blank.

[0020] According to the formula or Fill in the missing electrical parameter data x at the i-th node i , where x i-1 represents the electrical parameter data of the i-1th node, x i+1 represents the electrical parameter data of the i+1th node, m represents the number of samples taken forward, n represents the number of samples taken backward, and x o Represents the electrical parameter data of the oth node.

[0021] Furthermore, the step of removing duplicate values ​​includes:

[0022] Deleting repeated electrical parameter data to form a blank value;

[0023] Follow the steps for filling missing values ​​to fill in the missing values.

[0024] Furthermore, the accuracy verification step includes:

[0025] According to the mesh diagram of the telecommunication base station circuit, the correlation relationship between each monitoring node is established to obtain the correlation function M of the current monitoring node i and its related n correlation monitoring nodes i =f(M1, M2, ...M n );

[0026] For the monitoring node whose electrical parameter data is to be verified, the electrical parameter data of n monitoring nodes that are correlated with the monitoring node are obtained, and the theoretical electrical parameter data of the monitoring node to be verified is reversely calculated using the correlation to obtain the reversed theoretical electrical parameter data of the n monitoring nodes;

[0027] If the electrical parameter data of the monitoring node to be verified is equal to the theoretical electrical parameter data of the currently relevant monitoring node, the voting result of the currently relevant monitoring node on the monitoring node to be verified is "accurate", otherwise the voting result is "wrong";

[0028] All "accurate" and "wrong" voting results are counted, and the result with the highest frequency is taken as the final result;

[0029] If the final result is judged as "accurate", the actual electrical parameter data will be used as the electrical parameter data of the monitoring node to be verified; if the final result is judged as "wrong", the average of the theoretical electrical parameter data inferred from all relevant n monitoring nodes with a voting result of "wrong" will be used as the electrical parameter data of the monitoring node to be verified.

[0030] Further, determining whether each of the electrical parameter data is abnormal includes:

[0031] dividing the areas of all said telecommunication base stations into different independent areas;

[0032] Acquiring the electrical parameter data and the threshold range of all the telecommunication base stations in each independent area;

[0033] If the electrical parameter data is within the threshold range, the output result is "0";

[0034] If the electrical parameter data is less than the lower limit of the threshold range, the output result is:

[0035]

[0036] in, is the electrical parameter data of the ith node, X max and X min are the upper and lower limits of the threshold range, respectively;

[0037] If the electrical parameter data is greater than the upper limit of the threshold range, the output result is:

[0038]

[0039] Sum the weights of the voting results and set the result threshold If the result of the weighted sum is greater than the result threshold It is judged as abnormal, otherwise it is judged as normal.

[0040] In a second aspect, the present application shows a base station security monitoring system based on data relevance verification, the system comprising:

[0041] A data preprocessing module, used to obtain electrical parameter data of a telecommunication base station and perform preprocessing operations on the electrical parameter data;

[0042] A data analysis module, used to set a threshold range for each of the electrical parameter data, and compare the pre-processed electrical parameter data with the threshold range to determine whether each of the electrical parameter data is abnormal;

[0043] The alarm module is used to send an alarm electronic message to the administrator when an abnormality occurs, and to send an alarm sound at the site where the telecommunication base station is located.

[0044] Furthermore, the data preprocessing module is used to fill missing values, remove duplicate values ​​and verify the accuracy of the electrical parameter data.

[0045] Furthermore, the data preprocessing module is specifically used for:

[0046] Establishing a two-dimensional coordinate system with the time axis as the horizontal axis and the electrical parameter data as the vertical axis;

[0047] Taking the frequency at which the sensor collects the electrical parameter data as a period, selecting corresponding nodes on the horizontal axis;

[0048] Fill the newly acquired electrical parameter data into the vertical coordinate of each node. If the sensor does not collect the electrical parameter data of the current node, the vertical coordinate of the current node is left blank.

[0049] According to the formula or Fill in the missing electrical parameter data x at the i-th node i , where x i-1 represents the electrical parameter data of the i-1th node, x i+1 represents the electrical parameter data of the i+1th node, m represents the number of samples taken forward, n represents the number of samples taken backward, and x o Represents the electrical parameter data of the oth node.

[0050] Furthermore, the data preprocessing module is specifically used for:

[0051] Deleting repeated electrical parameter data to form a blank value;

[0052] Follow the steps for filling missing values ​​to fill in the missing values.

[0053] The technical solution provided by this application may have the following beneficial effects:

[0054] The base station security monitoring method based on data correlation verification provided in this application provides effective protection for the safe operation of the base station by improving data accuracy, reducing false alarm rate, quickly responding to abnormalities, saving energy and reducing consumption, and digital management. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] Figure 1 is a flowchart of the steps of the application method;

[0056] Figure 2 It is a flow chart of this application system;

[0057] Figure 3 This is an architecture diagram of a base station security monitoring system based on data correlation verification provided by this application;

[0058] Figure 4 is a block diagram of an electronic device of the present application;

[0059] Figure 5 It is a block diagram of a computer-readable storage medium of the present application. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0061]

Term explanation

[0062] SRv6 SFC (Segment Routing over IPv6 Service Function Chain): is a technology that adds SRv6 path information to the original message to guide the message to pass through the application layer service device in sequence along the specified path.

[0063] SC (Service Classifier): Located at the edge of the SRV6 SFC service chain network, it is the source node of the service chain path. SC can use different diversion methods to introduce service data into the SRV6 TE Policy tunnel for forwarding.

[0064] Reference Figure 1 , shows a base station security monitoring method based on data association verification of the present application, which can be applied to electronic devices, and the method includes the following steps:

[0065] Step 101, obtaining electrical parameter data of a telecommunication base station through a sensor module, and performing a preprocessing operation on the electrical parameter data, wherein the sensor module includes an ammeter, a voltmeter, a power meter, and a wave sensor;

[0066] Specifically, the preprocessing operation on the electrical parameter data includes: filling missing values, removing duplicate values, and verifying the accuracy of the electrical parameter data.

[0067] Specifically, the step of filling missing values ​​includes:

[0068] A two-dimensional coordinate system is established with the time axis as the horizontal axis and the electrical parameter data as the vertical axis. Specifically, the horizontal axis represents the time point t, and the vertical axis represents the electrical parameter data x.

[0069] The acquisition frequency of the electrical parameter data collected by the sensor is taken as the period, and the corresponding node is selected on the horizontal axis. Specifically, the acquisition frequency of the sensor is set to f s (For example, once per second), the interval between each node is 1 / f s Second;

[0070] The newly acquired electrical parameter data is filled into the vertical coordinate of each node. If the sensor does not collect the electrical parameter data of the current node, the vertical coordinate of the current node is left blank. Specifically, if at a certain time point t i If no data is collected, the electrical parameter value x at this point i is empty;

[0071] For the missing electrical parameter data x of the i-th node i , calculate x by one of the following two methods i Values:

[0072] Linear interpolation:

[0073]

[0074] Among them, x i-1 is the electrical parameter data of the i-1th node, x i+1 is the electrical parameter data of the i+1th node. The linear interpolation method is applicable to x i The case where there is valid electrical parameter data on both sides.

[0075] Moving average method:

[0076]

[0077] Where m represents the number of samples taken forward (i.e., the number of samples from im to i-1), n ​​represents the number of samples taken backward (i.e., the number of samples from i+1 to i+n), and x o represents the electrical parameter data of the oth node. The moving average method can calculate x in a wider context i , especially when there is no directly adjacent valid electrical parameter data on one or both sides.

[0078] Specifically, the step of removing duplicate values ​​includes:

[0079] Deleting repeated electrical parameter data to form a blank value;

[0080] Follow the steps for filling missing values ​​to fill in the missing values.

[0081] Specifically, the accuracy verification step includes:

[0082] According to the mesh diagram of the telecommunication base station circuit, the correlation relationship between each monitoring node is established to obtain the correlation function M of the current monitoring node i and its related n correlation monitoring nodes i =f(M1, M2, ...M n), for example, in a series circuit, the currents of the two nodes are the same, and the voltage is proportional to the resistance of the nodes. In a parallel circuit, the voltage between the two nodes is the same, and the current is inversely proportional to the resistance. In a single link of information transmission, the wave signal frequency of the two nodes remains unchanged, and the amplitude difference is proportional to the line length of the two nodes. This is the transmission loss.

[0083] The correlation function M is given by the following example i =f(M1, M2, ...M n ) is described as follows:

[0084] Correlation function M i =f(M1, M2, ...M n ), taking into account three types of circuits: series circuits, parallel circuits, and information transmission links, a weighted average is performed.

[0085] The first is a series circuit, as shown below:

[0086] In a series circuit, the current at all nodes is the same, and the voltage is proportional to the resistance. Let R i is the resistance of the ith node, V i is the voltage drop at the i-th node, I is the current through the circuit, then:

[0087] V i =I·R i

[0088] The correlation function between the ith node and its adjacent nodes is established, using the voltage ratio as the criterion, namely:

[0089]

[0090] Among them, V j represents the voltage on the jth node connected to the i-th node, Represents the sum of all relevant node resistances, R k represents the resistance of the kth node.

[0091] The second type, the parallel circuit, is as follows:

[0092] In a parallel circuit, the voltage at all nodes is the same, and the current is inversely proportional to the resistance. Let G i =1 / R i is the conductance of the ith node, V is the common voltage, I i is the current flowing through the i-th node, then:

[0093] I i =V·G i

[0094] For the correlation function in parallel circuits, the current ratio can be used:

[0095]

[0096] Among them, I j represents the current on the jth node connected to the i-th node, represents the sum of conductances of all relevant nodes.

[0097] The third type is the information transmission link, as shown below:

[0098] In a single link of information transmission, the wave signal frequency remains unchanged, and the amplitude difference is proportional to the line length between the two nodes. i is the amplitude at the ith node, L ij is the line length from the i-th node to the j-th node, then the amplitude difference ΔA ij It can be calculated using the following formula:

[0099] ΔA ij =A i -A j = k·L ij

[0100] Where k is a constant representing the amplitude attenuation rate per unit length.

[0101] For the correlation function on the information transmission link, it can be defined based on the amplitude loss:

[0102]

[0103] in, It represents the sum of the lengths of the lines between the ith node and all other related nodes.

[0104] Finally, the three circuits are weighted, with a total weight of 1, and M is calculated. i Similarities:

[0105]

[0106] Among them, w1, w2 and w3 are the weight coefficients set for the series circuit, parallel circuit and information transmission link respectively, ensuring that their sum is 1.

[0107] For the monitoring node whose electrical parameter data is to be verified, the electrical parameter data of n monitoring nodes that are correlated with the monitoring node are obtained, and the theoretical electrical parameter data of the monitoring node to be verified is reversely calculated using the correlation to obtain the reversed theoretical electrical parameter data of the n monitoring nodes;

[0108] If the electrical parameter data of the monitoring node to be verified is equal to the theoretical electrical parameter data of the currently relevant monitoring node, that is,

[0109]

[0110] The voting result of the currently relevant monitoring nodes on the monitoring nodes to be verified is "accurate". If x i for

[0111]

[0112] If one of them is found, the voting result is "wrong";

[0113] All "accurate" and "wrong" voting results are counted, and the result with the highest frequency is taken as the final result;

[0114] If the final result is determined to be "accurate", the actual electrical parameter data is used as the electrical parameter data of the monitoring node to be verified, that is,

[0115]

[0116] If the final result is judged as "error", the mean of the theoretical electrical parameter data inferred from all the relevant n monitoring nodes whose voting results are "error" is used as the electrical parameter data of the monitoring node to be verified, that is,

[0117]

[0118] Where q represents The number of wrong votes.

[0119] Step 102, setting a threshold range for each of the electrical parameter data, and comparing the preprocessed electrical parameter data with the threshold range to determine whether each of the electrical parameter data is abnormal;

[0120] Specifically, determining whether each of the electrical parameter data is abnormal includes:

[0121] dividing the areas of all said telecommunication base stations into different independent areas;

[0122] Acquiring the electrical parameter data and the threshold range of all the telecommunication base stations in each independent area;

[0123] If the electrical parameter data is within the threshold range, the output result is "0";

[0124] If the electrical parameter data is less than the lower limit of the threshold range, the output result is:

[0125]

[0126] in, is the electrical parameter data of the ith node, X max and X min are the upper and lower limits of the threshold range, respectively;

[0127] If the electrical parameter data is greater than the upper limit of the threshold range, the output result is:

[0128]

[0129] Sum the weights of the voting results and set the result threshold (For example If the result of the weighted sum is greater than the result threshold It is judged as abnormal, otherwise it is judged as normal.

[0130] Preferably, a weight coefficient is set for each node It represents the weight of the i-th node;

[0131] According to the formula The calculation results are as follows: is the weight of the i-th node is the output result of the i-th node.

[0132] Step 103, when an abnormality occurs, an alarm electronic message is sent to the administrator, and an alarm sound is sounded at the site where the telecommunication base station is located.

[0133] In one case, when an abnormal situation occurs, the security warning module sends an electronic alarm message to the administrator and uses an audible and visual alarm to issue an on-site alarm.

[0134] While acquiring node data based on sensors, the present application verifies the accuracy of the data, uses the base station circuit mesh diagram to establish the correlation relationship between each monitoring node, and then uses voting to determine the result with the highest probability, thereby preventing misjudgment caused by data anomalies caused by local and sensor anomalies, thereby increasing the accuracy of early warning; by filling missing values ​​and removing duplicate values ​​for the acquired data, the uniqueness of the acquired data time series can be guaranteed, the reliable implementation of the subsequent analysis process can be guaranteed, and the reliability of the system can be increased; for result analysis, the form of "voting" is adopted, and the probability is further used to select the result output, thereby further increasing the accuracy of early warning; by further weighting the results of "voting" and then judging in the form of threshold control, the weight can be designed in a targeted manner according to the importance of the node data to the actual abnormal situation, thereby having strong practicality. Accuracy measurement: Through data preprocessing operations, including missing value filling, duplicate value removal and accuracy verification, the integrity and accuracy of electrical parameter data can be improved, thereby improving the accuracy of base station safety monitoring.

[0135] 1. Abnormal detection and early warning: The system can determine whether the electrical parameters are abnormal by setting the threshold range and comparing the pre-processed data, and issue an alarm in time when an abnormality is detected, which helps to promptly discover and respond to potential safety issues.

[0136] 2. Reduce the false alarm rate: Utilize data correlation verification, determine the final result through correlation function and reverse calculation of theoretical electrical parameter data, and combine voting mechanism to effectively reduce the false alarm rate and improve the reliability of safety monitoring.

[0137] 3. Improve response speed: When the system detects an abnormality, it can quickly send an alarm electronic message to the administrator and sound an alarm on site, which helps to quickly respond to and handle security incidents.

[0138] 4. Energy saving and cost-effectiveness: The system uses intelligent management, such as automatic control of air conditioners and fans, and the use of natural cooling to achieve energy saving of air conditioning electricity in base stations, reduce energy consumption, and reduce operating costs.

[0139] 5. Digital and intelligent management: The system supports digital and intelligent remote management of base station electricity consumption, including monitoring of electrical parameters, statistical energy consumption data and real-time warning of abnormalities, which helps to improve the efficiency and intelligence level of base station management.

[0140] 6. Preventive maintenance: Through real-time monitoring of base station equipment, the system can predict and warn of possible failures, such as overtemperature or fire, thereby achieving preventive maintenance and reducing unexpected downtime and repair costs.

[0141] 7. Simple structure and low cost: The monitoring system has a simple structure and low cost. It not only ensures the safety of the base station, but also reduces the cost of deployment and maintenance.

[0142] In summary, the base station security monitoring method and system provide effective protection for the safe operation of the base station by improving data accuracy, reducing false alarm rate, quickly responding to abnormalities, saving energy and reducing consumption, and digital management.

[0143] like Figure 3 , shows a base station security monitoring system based on data relevance verification of the present application, the system comprising:

[0144] A data preprocessing module, used to obtain electrical parameter data of a telecommunication base station and perform preprocessing operations on the electrical parameter data;

[0145] A data analysis module, used to set a threshold range for each of the electrical parameter data, and compare the pre-processed electrical parameter data with the threshold range to determine whether each of the electrical parameter data is abnormal;

[0146] The alarm module is used to send an alarm electronic message to the administrator when an abnormality occurs, and to send an alarm sound at the site where the telecommunication base station is located.

[0147] The data preprocessing module is used to fill missing values, remove duplicate values ​​and verify the accuracy of the electrical parameter data.

[0148] The data preprocessing module is specifically used for:

[0149] A two-dimensional coordinate system is established with the time axis as the horizontal axis and the electrical parameter data as the vertical axis. Specifically, the horizontal axis represents the time point t, and the vertical axis represents the electrical parameter data x.

[0150] The acquisition frequency of the electrical parameter data collected by the sensor is taken as the period, and the corresponding node is selected on the horizontal axis. Specifically, the acquisition frequency of the sensor is set to f s (For example, once per second), the interval between each node is 1 / f s Second;

[0151] The newly acquired electrical parameter data is filled into the vertical coordinate of each node. If the sensor does not collect the electrical parameter data of the current node, the vertical coordinate of the current node is left blank. Specifically, if at a certain time point t i If no data is collected, the electrical parameter value x at this point i is empty;

[0152] For the missing electrical parameter data x of the i-th node i, calculate x by one of the following two methods i Values:

[0153] Linear interpolation:

[0154]

[0155] Among them, x i-1 is the electrical parameter data of the i-1th node, x i+1 is the electrical parameter data of the i+1th node. The linear interpolation method is applicable to x i The case where there is valid electrical parameter data on both sides.

[0156] Moving average method:

[0157]

[0158] Where m represents the number of samples taken forward (i.e., the number of samples from im to i-1), n ​​represents the number of samples taken backward (i.e., the number of samples from i+1 to i+n), and x o represents the electrical parameter data of the oth node. The moving average method can calculate x in a wider context i , especially when there is no directly adjacent valid electrical parameter data on one or both sides.

[0159] The data preprocessing module is specifically used for:

[0160] Deleting repeated electrical parameter data to form a blank value;

[0161] Follow the steps for filling missing values ​​to fill in the missing values.

[0162] As for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0163] The present application discloses a base station safety monitoring system based on data correlation verification, which verifies the accuracy of the data while acquiring node data based on sensors, establishes the correlation relationship between each monitoring node using the base station circuit mesh diagram, and then determines the result with the highest probability by voting, thereby preventing misjudgment caused by data anomalies caused by local and sensor anomalies, and increasing the accuracy of early warning; by filling missing values ​​and removing duplicate values ​​from the acquired data, the uniqueness of the acquired data time series can be guaranteed, and the reliable implementation of the subsequent analysis process can be guaranteed, thereby increasing the reliability of the system; for result analysis, the form of "voting" is adopted, and the probability is further used to select the result output, thereby further increasing the accuracy of early warning; by further weighting and summing the results of "voting", and then judging in the form of threshold control, the weight can be designed in a targeted manner according to the importance of the node data to the actual abnormal situation, thereby having strong practicality and accuracy: through data preprocessing operations, including missing value filling, duplicate value removal and accuracy verification, the integrity and accuracy of electrical parameter data can be improved, thereby improving the accuracy of base station safety monitoring.

[0164] Optionally, an embodiment of the present application further provides an electronic device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the computer program is executed by the processor, the various processes of the above-mentioned method embodiment are implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0165] The embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, each process of the above method embodiment is implemented, and the same technical effect can be achieved. To avoid repetition, it is not repeated here. The computer-readable storage medium is, for example, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0166] FIG4 is a block diagram of an electronic device 800 shown in the present application. For example, the electronic device 800 may be a mobile phone, a computer, a digital broadcast terminal, a messaging device, a game console, a tablet device, a medical device, a fitness device, a personal digital assistant, etc.

[0167] Reference Figure 4 , the electronic device 800 may include one or more of the following components: a processing component 802 , a memory 804 , a power component 806 , a multimedia component 808 , an audio component 810 , an input / output (I / O) interface 812 , a sensor component 814 , and a communication component 816 .

[0168] The processing component 802 generally controls the overall operation of the electronic device 800, such as operations associated with display, phone calls, data communications, camera operations, and recording operations. The processing component 802 may include one or more processors 820 to execute instructions to complete all or part of the steps of the above method. In addition, the processing component 802 may include one or more modules to facilitate the interaction between the processing component 802 and other components. For example, the processing component 802 may include a multimedia module to facilitate the interaction between the multimedia component 808 and the processing component 802.

[0169] The memory 804 is configured to store various types of data to support operations on the device 800. Examples of such data include instructions for any application or method operating on the electronic device 800, contact data, phone book data, messages, images, videos, etc. The memory 804 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0170] The power supply component 806 provides power to the various components of the electronic device 800. The power supply component 806 may include a power management system, one or more power supplies, and other components associated with generating, managing, and distributing power for the electronic device 800.

[0171] The multimedia component 808 includes a screen that provides an output interface between the electronic device 800 and the user. In some embodiments, the screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen may be implemented as a touch screen to receive input signals from the user. The touch panel includes one or more touch sensors to sense touch, slide, and gestures on the touch panel. The touch sensor may not only sense the boundaries of the touch or slide action, but also detect the duration and pressure associated with the touch or slide operation. In some embodiments, the multimedia component 808 includes a front camera and / or a rear camera. When the device 800 is in an operating mode, such as a shooting mode or a video mode, the front camera and / or the rear camera may receive external multimedia data. Each front camera and the rear camera may be a fixed optical lens system or have a focal length and optical zoom capability.

[0172] The audio component 810 is configured to output and / or input audio signals. For example, the audio component 810 includes a microphone (MIC), and when the electronic device 800 is in an operating mode, such as a call mode, a recording mode, and a voice recognition mode, the microphone is configured to receive an external audio signal. The received audio signal can be further stored in the memory 804 or sent via the communication component 816. In some embodiments, the audio component 810 also includes a speaker for outputting audio signals.

[0173] I / O interface 812 provides an interface between processing component 802 and peripheral interface modules, such as keyboards, click wheels, buttons, etc. These buttons may include but are not limited to: home button, volume button, start button, and lock button.

[0174] The sensor assembly 814 includes one or more sensors for providing various aspects of status assessment for the electronic device 800. For example, the sensor assembly 814 can detect the open / closed state of the device 800, the relative positioning of components, such as the display and keypad of the electronic device 800, and the sensor assembly 814 can also detect the position change of the electronic device 800 or a component of the electronic device 800, the presence or absence of contact between the user and the electronic device 800, the orientation or acceleration / deceleration of the electronic device 800, and the temperature change of the electronic device 800. The sensor assembly 814 may include a proximity sensor configured to detect the presence of nearby objects without any physical contact. The sensor assembly 814 may also include an optical sensor, such as a CMOS or CCD image sensor, for use in imaging applications. In some embodiments, the sensor assembly 814 may also include an accelerometer, a gyroscope sensor, a magnetic sensor, a pressure sensor, or a temperature sensor.

[0175] The communication component 816 is configured to facilitate wired or wireless communication between the electronic device 800 and other devices. The electronic device 800 can access a wireless network based on a communication standard, such as WiFi, a carrier network (such as 2G, 3G, 4G or 5G), or a combination thereof. In an exemplary embodiment, the communication component 816 receives a broadcast signal or broadcast operation information from an external broadcast management system via a broadcast channel. In an exemplary embodiment, the communication component 816 also includes a near field communication (NFC) module to facilitate short-range communication. For example, the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology and other technologies.

[0176] In an exemplary embodiment, the electronic device 800 may be implemented by one or more application-specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), controllers, microcontrollers, microprocessors, or other electronic components to perform the above methods.

[0177] In an exemplary embodiment, a non-transitory computer-readable storage medium including instructions is also provided, such as a memory 804 including instructions, and the instructions can be executed by a processor 820 of an electronic device 800 to perform the above method. For example, the non-transitory computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0178] Figure 5 19 is a block diagram of a computer-readable storage medium 1900 shown in the present application. For example, the computer-readable storage medium 1900 may be provided as a server.

[0179] Reference Figure 5 , the computer-readable storage medium 1900 includes a processing component 1922, which further includes one or more processors, and a memory resource represented by a memory 1932 for storing instructions, such as an application, that can be executed by the processing component 1922. The application stored in the memory 1932 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 1922 is configured to execute instructions to perform the above method.

[0180] The computer readable storage medium 1900 may also include a power supply component 1926 configured to perform power management of the computer readable storage medium 1900, a wired or wireless network interface 1950 configured to connect the computer readable storage medium 1900 to a network, and an input / output (I / O) interface 1958. The computer readable storage medium 1900 may operate based on an operating system stored in the memory 1932, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™ or the like.

[0181] It should be noted that, in this article, the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the sentence "comprises a ..." does not exclude the existence of other identical elements in the process, method, article or device including the element.

[0182] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, a magnetic disk, or an optical disk), and includes a number of instructions for a terminal (which can be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to execute the methods described in each embodiment of the present application.

[0183] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present application, ordinary technicians in this field can also make many forms without departing from the purpose of the present application and the scope of protection of the claims, all of which are within the protection of the present application.

[0184] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed in the present application can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0185] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0186] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0187] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0188] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0189] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as USB flash drives, mobile hard drives, ROM, RAM, magnetic disks, or optical disks.

[0190] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A base station security monitoring method based on data correlation verification, characterized in that: The method comprises: Acquiring electrical parameter data of a telecommunication base station and performing a preprocessing operation on the electrical parameter data; Setting a threshold range for each of the electrical parameter data, and comparing the preprocessed electrical parameter data with the threshold range to determine whether each of the electrical parameter data is abnormal; When an abnormality occurs, an alarm electronic message is sent to the administrator, and an alarm sound is sounded on site where the telecommunication base station is located.

2. A base station security monitoring method based on data correlation verification as claimed in claim 1, characterized in that: The preprocessing operation on the electrical parameter data includes: filling missing values, removing duplicate values ​​and verifying the accuracy of the electrical parameter data.

3. A base station security monitoring method based on data correlation verification as claimed in claim 2, characterized in that: The steps of filling missing values ​​include: Establishing a two-dimensional coordinate system with the time axis as the horizontal axis and the electrical parameter data as the vertical axis; Taking the frequency at which the sensor collects the electrical parameter data as a period, selecting corresponding nodes on the horizontal axis; Fill the newly acquired electrical parameter data into the vertical coordinate of each node. If the sensor does not collect the electrical parameter data of the current node, the vertical coordinate of the current node is left blank. According to the formula or Fill in the missing electrical parameter data x at the i-th node i , where x i-1 represents the electrical parameter data of the i-1th node, x i+1 represents the electrical parameter data of the i+1th node, m represents the number of samples taken forward, n represents the number of samples taken backward, and x o Represents the electrical parameter data of the oth node.

4. A base station security monitoring method based on data correlation verification as claimed in claim 3, characterized in that: The step of removing duplicate values ​​comprises: Deleting repeated electrical parameter data to form a blank value; Follow the steps for filling missing values ​​to fill in the missing values.

5. A base station security monitoring method based on data correlation verification as claimed in claim 1, characterized in that: The steps of accuracy verification include: According to the mesh diagram of the telecommunication base station circuit, the correlation relationship between each monitoring node is established to obtain the correlation function M of the current monitoring node i and its related n correlation monitoring nodes i =f(M1, M2, ...M n ); For the monitoring node whose electrical parameter data is to be verified, the electrical parameter data of n monitoring nodes that are correlated with the monitoring node are obtained, and the theoretical electrical parameter data of the monitoring node to be verified is reversely calculated using the correlation to obtain the reversed theoretical electrical parameter data of the n monitoring nodes; If the electrical parameter data of the monitoring node to be verified is equal to the theoretical electrical parameter data of the currently relevant monitoring node, the voting result of the currently relevant monitoring node on the monitoring node to be verified is "accurate", otherwise the voting result is "wrong"; All "accurate" and "wrong" voting results are counted, and the result with the highest frequency is taken as the final result; If the final result is judged as "accurate", the actual electrical parameter data will be used as the electrical parameter data of the monitoring node to be verified; if the final result is judged as "wrong", the average of the theoretical electrical parameter data inferred from all relevant n monitoring nodes with a voting result of "wrong" will be used as the electrical parameter data of the monitoring node to be verified.

6. A base station security monitoring method based on data correlation verification as claimed in claim 1, characterized in that: Determining whether each of the electrical parameter data is abnormal includes: dividing the areas of all said telecommunication base stations into different independent areas; Acquiring the electrical parameter data and the threshold range of all the telecommunication base stations in each independent area; If the electrical parameter data is within the threshold range, the output result is "0"; If the electrical parameter data is less than the lower limit of the threshold range, the output result is: in, is the electrical parameter data of the ith node, X max and X min are the upper and lower limits of the threshold range, respectively; If the electrical parameter data is greater than the upper limit of the threshold range, the output result is: Sum the weights of the voting results and set the result threshold If the result of the weighted sum is greater than the result threshold It is judged as abnormal, otherwise it is judged as normal.

7. A base station security monitoring system based on data correlation verification, characterized in that: The system comprises: A data preprocessing module, used to obtain electrical parameter data of a telecommunication base station and perform preprocessing operations on the electrical parameter data; A data analysis module, used to set a threshold range for each of the electrical parameter data, and compare the pre-processed electrical parameter data with the threshold range to determine whether each of the electrical parameter data is abnormal; The alarm module is used to send an alarm electronic message to the administrator when an abnormality occurs, and to send an alarm sound at the site where the telecommunication base station is located.

8. A base station security monitoring system based on data correlation verification as claimed in claim 7, characterized in that: The data preprocessing module is used to fill missing values, remove duplicate values ​​and verify the accuracy of the electrical parameter data.

9. A base station security monitoring system based on data correlation verification as claimed in claim 8, characterized in that: The data preprocessing module is specifically used for: Establishing a two-dimensional coordinate system with the time axis as the horizontal axis and the electrical parameter data as the vertical axis; Taking the frequency at which the sensor collects the electrical parameter data as a period, selecting corresponding nodes on the horizontal axis; Fill the newly acquired electrical parameter data into the vertical coordinate of each node. If the sensor does not collect the electrical parameter data of the current node, the vertical coordinate of the current node is left blank. According to the formula or Fill in the missing electrical parameter data x at the i-th node i , where x i-1 represents the electrical parameter data of the i-1th node, x i+1 represents the electrical parameter data of the i+1th node, m represents the number of samples taken forward, n represents the number of samples taken backward, and x o Represents the electrical parameter data of the oth node.

10. A base station security monitoring system based on data correlation verification as claimed in claim 9, characterized in that: The data preprocessing module is specifically used for: Deleting repeated electrical parameter data to form a blank value; Follow the steps for filling missing values ​​to fill in the missing values.

Images