Risk inspection methods, devices and equipment for communication base stations

Abstract

This disclosure relates to a risk inspection method, apparatus, and equipment for communication base stations. The method includes: dividing the communication cabinet plane into multiple grids; determining the risk values ​​of multiple risk factors for a target device in each grid; determining multiple combinations of correlation factors among the risk factors based on their influence relationships; wherein each group of correlation factors includes at least two risk factors; adjusting the initial weight of a second risk factor based on the risk value of a first risk factor for each correlation factor; determining a synergistic risk based on the risk values ​​of at least two risk factors exhibiting a synergistic effect; and determining the comprehensive risk value of the target device based on the synergistic risk, the risk values ​​of each risk factor, and their weights. This disclosure improves the accuracy of the comprehensive risk value and achieves precise quantification of the comprehensive risk of the target device.

Description

Technical Field

[0001] This disclosure relates to the field of base station inspection technology, and in particular to a risk inspection method, apparatus and equipment for communication base stations. Background Technology

[0002] Railway communication systems require "zero interruptions," and malfunctions in base station equipment (such as core switches) can lead to disruptions in dispatching signals. Currently, railway communication base station inspections primarily rely on manual on-site operations. Due to the high density of equipment within cabinets and the remote and complex locations of field base stations, manual inspections suffer from issues such as missed equipment and incomplete risk factor inspections, resulting in poor equipment risk assessment outcomes. Summary of the Invention

[0003] To address the aforementioned technical issues, this disclosure provides a risk inspection method, apparatus, and equipment for communication base stations.

[0004] According to one aspect of this disclosure, a risk inspection method for a communication base station is provided, the method comprising:

[0005] The communication cabinet plane is divided into multiple grids;

[0006] For each target device in the grid, risk values ​​of multiple risk factors are determined for the target device; wherein, the risk factors include: device importance, historical failure rate, temperature risk factor, voltage stability, current fluctuation and operating time;

[0007] Based on the influence relationships between the risk factors, multiple combinations of correlation factors are determined among the risk factors; wherein each group of correlation factors includes at least two of the risk factors;

[0008] For the aforementioned correlation factor, the initial weight of the second risk factor is adjusted based on the risk value of the first risk factor; wherein, the first risk factor is the risk factor as the independent variable, and the second risk factor is the target risk factor as the dependent variable.

[0009] The synergistic risk is determined based on the risk values ​​of at least two of the aforementioned risk factors that exhibit a synergistic effect;

[0010] The comprehensive risk value of the target equipment is determined based on the collaborative risk, the risk value of each risk factor, and their weights.

[0011] According to another aspect of this disclosure, a risk inspection device for a communication base station is also provided, the device comprising:

[0012] The grid division module is used to divide the communication cabinet plane into multiple grids;

[0013] The risk value determination module is used to determine the risk value of multiple risk factors for each target device in the grid; wherein the risk factors include: device importance, historical failure rate, temperature risk factor, voltage stability, current fluctuation and operating time;

[0014] The correlation module is used to determine multiple combinations of correlation factors among the risk factors based on the influence relationships between the risk factors; wherein each group of correlation factors includes at least two of the risk factors;

[0015] The weight adjustment module is used to adjust the initial weight of the second risk factor based on the risk value of the first risk factor for the associated factor; wherein the first risk factor is the risk factor as the independent variable, and the second risk factor is the target risk factor as the dependent variable.

[0016] A coordination risk determination module is used to determine the synergistic risk based on the risk values ​​of at least two of the risk factors that have a synergistic effect.

[0017] The comprehensive risk value determination module is used to determine the comprehensive risk value of the target equipment based on the collaborative risk, the risk value of each of the risk factors and their weights.

[0018] This disclosure also provides an electronic device, the electronic device comprising:

[0019] processor;

[0020] Memory used to store the processor's executable instructions;

[0021] The processor is configured to read the executable instructions from the memory and execute the instructions to implement the above method.

[0022] This disclosure also provides a computer-readable storage medium storing a computer program for performing the above-described methods.

[0023] The technical solution provided in this disclosure has the following advantages compared with the prior art:

[0024] The technical solutions provided in this disclosure include:

[0025] The technical solution provided in this disclosure divides the communication cabinet plane into multiple grids, using each grid as an inspection unit to inspect the target devices within the grid. This effectively overcomes the problem of missed inspections, addressing the high device density within the cabinet and improving the comprehensiveness of device inspection. For each target device in the grid, risk values ​​are determined based on multiple dimensions of risk factors, including device importance, historical failure rate, temperature risk factor, voltage stability, current fluctuation, and operating time. This enhances the inspection dimensions and the comprehensiveness of risk factors, ensuring that the final calculated overall risk value comprehensively considers these multiple risk factors, thus improving the accuracy of risk value assessment. Instead of using pre-set, fixed weights for each risk factor, the weights are dynamically adjusted, taking into full account the correlation and coupling effects between risk factors. This ensures that the adjusted weights dynamically adapt to the actual inspection status of the equipment, improving the accuracy of the weights for each risk factor and consequently increasing the sensitivity of the overall risk value. Furthermore, it captures the synergistic risks between risk factors exhibiting synergistic effects, further increasing the accuracy of the overall risk value and achieving precise quantification of the overall risk of the target device. Attached Figure Description

[0026] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0027] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a flowchart of the risk inspection method for communication base stations described in the embodiments of this disclosure;

[0029] Figure 2 This is a schematic diagram illustrating the risk factors and their weights as described in the embodiments of this disclosure;

[0030] Figure 3 This is a normalized schematic diagram of the comprehensive risk value described in the embodiments of this disclosure;

[0031] Figure 4 This is a schematic diagram of the visualized heatmap described in the embodiments of this disclosure;

[0032] Figure 5 This is a schematic diagram of the structure of the electronic device described in an embodiment of this disclosure. Detailed Implementation

[0033] To better understand the above-mentioned objectives, features, and advantages of this disclosure, the solutions disclosed herein will be further described below. It should be noted that, unless otherwise specified, the embodiments and features described herein can be combined with each other.

[0034] Numerous specific details are set forth in the following description in order to provide a full understanding of this disclosure, but this disclosure may also be implemented in other ways different from those described herein; obviously, the embodiments in the specification are only some, and not all, of the embodiments of this disclosure.

[0035] This disclosure provides a risk inspection method, apparatus, and device for communication base stations. For ease of understanding, the embodiments of this disclosure are described below.

[0036] First, this embodiment introduces the inspection system used in the risk inspection method for communication base stations.

[0037] Regarding the inspection system: Railway communication systems require "zero interruption." Failures in base station equipment (such as core switches) can lead to disruptions in dispatch signals. This disclosed inspection system employs a multi-layered protection approach, combining "global fallback + targeted reinforcement + point-to-point emergency response." Due to the high density of equipment within cabinets, traditional single-method inspections struggle to balance efficiency and accuracy. A tiered strategy optimizes resource allocation through "broad coverage + in-depth diagnosis." Furthermore, the remote and complex locations of field base stations necessitate automated inspections to avoid frequent manual intervention, significantly reducing maintenance costs.

[0038] Manual inspections carry the risk of missing faults. Global inspections, utilizing automated equipment, achieve 100% physical coverage, avoiding hidden faults caused by human oversight. Fixed-cycle inspections cannot handle dynamic changes in equipment status (such as increased power module failure rates during hot summer months). Targeted inspections, through risk models, adjust strategies in real time, reducing fault warning lead time from an average of 24 hours to 4 hours. Manual fault response time is typically >30 minutes; the 5-second trigger mechanism of targeted inspections can buy crucial time for handling emergencies such as fires and short circuits, reducing accident losses.

[0039] Based on the above inspection system, this disclosure can perform global inspections, targeted inspections, and fixed-point inspections.

[0040] The global inspection is used to achieve a basic scan of the entire communication base station coverage. Specifically, it is automatically triggered according to a preset cycle (e.g., once a day). The three-axis moving platform moves from top to bottom along the Y-axis (vertical), from left to right along the X-axis (horizontal), and automatically adjusts the focus along the Z-axis (depth) according to the installation depth of the base station equipment to be inspected, ensuring that the distance between the camera and the surface of the base station equipment remains at a preset distance (generally 15-20cm). Dual cameras simultaneously acquire visible light images (main camera) and depth data (TOF camera). Each image covers an area of ​​approximately 20cm × 20cm, and a panoramic view of the entire cabinet is generated by image stitching. ≥200 standardized images are generated, and environmental data such as temperature, humidity, voltage, and current are recorded simultaneously to form a basic status database. A single inspection usually takes no more than 30 minutes and covers 100% of the entire cabinet area.

[0041] Targeted inspection is used to achieve risk-driven intelligent optimization of communication base stations. Specifically, risk is quantified by calculating multi-factor risk values, and inspection tasks are dynamically generated based on a risk heatmap (e.g., grid risk values ​​≥0.5 are marked as high risk). For example, the inspection frequency for high-risk areas (such as power modules) is automatically increased to twice per day, while the frequency for low-risk areas (such as backup ports) is reduced to once per week. Inspection paths are determined using relevant algorithms (an improved algorithm incorporating risk factor weights). A single targeted inspection takes ≤8 minutes, focusing on 20% of high-risk equipment and covering 80% of potential faults. This disclosure will primarily describe this targeted inspection.

[0042] Fixed-point inspection is used to achieve in-depth response to fault linkage. Specifically, through MODBUS protocol integration, it deeply links with inverter systems, high-frequency switching power supply systems, intelligent surge protection systems, lithium battery packs, and environmental monitoring systems. When a relevant event is detected in the corresponding equipment (the event can be set according to customer needs), in-depth inspection of the equipment is triggered within a preset time (e.g., 5 seconds). For example: inverter system output voltage fluctuation exceeding ±10%; lithium battery pack single-cell voltage difference >0.3V or temperature >55℃; intelligent surge protection module alarm indicator light turning red; environmental monitoring system smoke / water immersion sensor alarm, etc. The main camera photographs the faulty equipment; if necessary, close-up shots can be taken; the infrared temperature measurement module generates a thermal image to locate temperature anomalies (resolution 0.1℃); simultaneously, the equipment's QR code is read, and a diagnostic report is generated by associating it with historical fault records. Fixed-point inspection typically takes no more than half a minute, focusing on fault risk investigation.

[0043] Based on the above embodiments, refer to Figure 1This disclosure provides a risk inspection method for communication base stations. This risk inspection method for communication base stations can be applied to scenarios involving the inspection of railway communication base stations. The risk inspection method for communication base stations can be executed by a risk inspection device for the communication base station, which can be implemented using software and / or hardware.

[0044] Reference Figure 1 The risk inspection method for communication base stations provided in this embodiment may include the following steps.

[0045] S102 divides the communication cabinet plane into multiple grids.

[0046] In this embodiment, the communication cabinet plane is divided into multiple grids according to physical coordinates. For example, each grid is a 10cm × 10cm unit. Each grid corresponds to a specific area within the communication cabinet, such as the equipment surface or cable trays. The equipment to be inspected within each grid is referred to as the target equipment. A precise mapping between physical location and inspection data is achieved through grid indexing, providing a spatial basis for subsequent risk quantification.

[0047] S104, for each target device in the grid, determine the risk values ​​of multiple risk factors for the target device; wherein, the risk factors include, but are not limited to: device importance, historical failure rate, temperature risk factor, voltage stability, current fluctuation, and operating time. The following embodiments describe each risk factor and its risk value in detail.

[0048] In this embodiment, the risk factor is device importance (L). Device importance is a static parameter, and its initial importance is updated when the target device is replaced. Device importance represents the criticality of the target device in the communication system; in other words, its initial value is determined based on the criticality of the target device in the communication system. The higher the device importance value, the more severe the impact of the target device failure on the system. For example, the device importance of a lithium battery pack is 5, the device importance of a switch is 7, and the device importance of a transmission module is 10. Correspondingly, the severity of the impact of the failure on the system from low to high is: lithium battery pack, switch, transmission module.

[0049] This embodiment determines the risk value of the target device's importance, including: obtaining the initial importance of the target device; obtaining the preset initial importance range of the target device as [L]. min L max (e.g., [1, 10]); using linear mapping formula one and the initial importance range, the initial importance is standardized and converted into the standard importance of the interval [0,1].

[0050] Formula 1

[0051] For example, if the initial importance of a switch is L=7, then the initial importance is standardized to the standard importance L using the formula above. norm =(7-1) / (10-1)=0.67. The converted standard importance is the risk value of the equipment importance risk factor.

[0052] In this embodiment, the risk factor is the historical failure rate (R). The historical failure rate reflects the stability trend of the target device. The data refresh cycle for the historical failure rate is, for example, monthly rolling updates, while retaining data for a preset time period (such as the past 12 months). Based on the data refresh cycle, the average monthly number of failures R of the target device over the past 12 months is calculated. cnt And the maximum monthly average number of failures R for each device in the rack. max Referring to normalization formula two, based on the target equipment's average monthly failure rate R... cnt and maximum monthly average number of failures R max Determine the risk value R of the historical failure rate. norm :

[0053] Formula 2

[0054] For example: if the switch experiences an average of 2 failures per month, and the maximum average monthly failures of all devices in the rack are 5, then the risk value R of the switch's historical failure rate is... norm =2 / 5=0.4. Furthermore, if the average monthly number of failures R of the target equipment... cnt =0, then the risk value R of the historical failure rate norm =0.

[0055] In this embodiment, the risk factor is the temperature risk factor (T). The data refresh cycle for the temperature risk factor is typically short; if real-time data collection is possible, the risk value of the temperature risk factor is automatically refreshed after each inspection. Each device in the communication cabinet has a corresponding temperature threshold set, such as a temperature threshold of 35°C for the high-frequency switching power supply module and 45°C for the transmission module. The higher the deviation of the temperature collected in real-time from the temperature threshold, the higher the temperature risk level.

[0056] This embodiment determines the risk value of the temperature risk factor for the target equipment, which may include:

[0057] The surface temperature of the target device is collected. Specifically, the surface temperature of the device can be collected in real time using an infrared temperature measurement module.

[0058] Referring to Formula 3, when the surface temperature T does not exceed the preset temperature threshold T of the target device th hour( The risk value of the temperature risk factor of the target equipment is determined to be 0 (i.e., T). risk =0); when the surface temperature T exceeds the temperature threshold Tth hour( Based on the degree of deviation of the surface temperature from the temperature threshold, the risk value T of the temperature risk factor is determined. risk .

[0059] Formula 3

[0060] Among them, T max The maximum safe temperature preset for the target device.

[0061] For example: The surface temperature of the switch is 40℃, and the temperature threshold is T. th =35℃, maximum safe temperature is T max =65℃, then the risk value T of the temperature risk factor of the switch. risk =(40-35) / (65-35)=0.17.

[0062] The risk factor in this embodiment is voltage stability (V), which is used to monitor the input voltage of the target device in real time to reflect the risk of abnormal power supply to the target device.

[0063] This embodiment determines the risk value of voltage stability for the target device, which may include:

[0064] Acquire the input voltage of the target device; specifically, the input voltage V of the target device can be monitored in real time (e.g., once per second) using a voltage sensor. real .

[0065] Obtain the target device's preset maximum voltage fluctuation range and stable operating voltage fluctuation range. For example, the target device's preset rated voltage is V. nom The maximum allowable voltage fluctuation range of the target device is determined to be V. nom ±20%, meaning the target equipment will not function properly if it deviates from this range; the stable operating voltage fluctuation range of the target equipment is determined to be V. nom ±5%. Regarding the preset rated voltage V of the target equipment. nom In one example of DC power supply, the rated voltage V nom For example, -48 V; in an example powered by AC, the rated voltage V nom For example, 220 V. Of course, the above only refers to the rated voltage (V). nom For example, in practical applications, other voltage values ​​can also be used as the rated voltage V. nom Alternatively, a voltage value within a preset voltage fluctuation range can be used as the rated voltage V. nom .

[0066] Referring to Formula 4, when the input voltage V real Within the range of stable operating voltage fluctuations (i.e.) When the risk value for voltage stability of the target device is determined to be 0 (i.e., ...), the risk value is determined to be 0. ).

[0067] When the input voltage exceeds the maximum voltage fluctuation range (i.e.) When ), the risk value for voltage stability is determined to be 1 (i.e. ).

[0068] When the input voltage is between the stable operating voltage fluctuation range and the maximum voltage fluctuation range (i.e. When this occurs, the risk value for voltage stability is determined based on the input voltage and the preset rated voltage of the target device. Specifically: .

[0069] Formula 4

[0070] The risk factor in this embodiment is current fluctuation (I), which is used to monitor the input current of the target device in real time to reflect the risk of abnormal load on the target device.

[0071] This embodiment determines the risk value of current fluctuations in the target device. It calculates the risk value of current fluctuations by combining historical current baseline values ​​and current detection values ​​over specific time periods, considering normal current fluctuations caused by changes in the target device's operating intensity. The implementation process is shown below.

[0072] The system collects current detection values ​​from the target device within a preset time window. Specifically, it monitors the input current of the target device in real time using a current sensor, collecting a large number of input current data points within a preset time window (e.g., a 1-hour sliding time window). For example, with a sampling frequency of 1Hz, a total of 3600 input current data points can be collected within a 1-hour time window. Then, the average value of all input currents within the time window is calculated as the current detection value I for each time period. avg .

[0073] The average current of the target device over the current time and the preset time period prior to it is determined as the current reference value I. nom .

[0074] Specifically, when initially determining the current reference value, an empirical value can be used; for example, based on the equipment model manual, the initial current reference value of the target equipment can be set to I. nom =10A. As the system generates more current data, the current reference value can be dynamically calibrated. The dynamic calibration method is to calculate the average current value over the current time and a preset time period (such as the past month) and use it as the updated current reference value.

[0075] The current reference value can be set with an update cycle, such as automatic calibration once a day, to ensure the current reference value I. nom The current reference value is dynamically adapted to changes in the long-term operating status of the target equipment (such as aging), thereby improving the accuracy of the current reference value.

[0076] Refer to Formula 5 to determine the current detection value I for the current period. avg and current reference value I nom relative deviation of current between .

[0077] Formula 5

[0078] Referring to Formula 6, based on the relative deviation of the current Determine the risk value I of current fluctuations in the target device. risk .

[0079] Formula Six

[0080] Specifically, when the relative deviation of the current is less than or equal to the first deviation value (e.g., When the risk value of current fluctuation is determined to be 0, I risk =0.

[0081] When the relative deviation of the current is greater than or equal to the second deviation value (e.g.) When the risk value of current fluctuation is determined to be 1, I risk= 1.

[0082] When the relative deviation of the current is between the first deviation value and the second deviation value (e.g.) When determining the risk value of current fluctuations, .

[0083] In this embodiment, the risk factor is runtime (D), which reflects the aging risk of the target equipment. The risk value of runtime (D) risk The data refresh cycle is, for example, monthly rolling updates.

[0084] This embodiment may include determining a risk value for the runtime of the target device, which could include:

[0085] Collect the cumulative runtime of the target device; specifically, the cumulative runtime D can be obtained through the power-on record of the target device or the inspection-related information bound to the QR code.

[0086] Referring to Formula 7, based on the target equipment's preset lifespan D... life And the cumulative runtime D, determine the risk value D for the target device's runtime. risk Taking a switch as an example, its lifespan D life It is generally 60 months.

[0087] Formula 7

[0088] Specifically, when the cumulative runtime is less than or equal to a preset percentage of the preset lifespan (e.g., D≤0.5D)... life When ignoring the risk of aging, D risk =0; when the cumulative runtime exceeds the preset percentage of the preset lifespan (e.g., D≤0.5D). life But it has not yet reached its preset lifespan (e.g.) When the runtime risk value increases linearly with the cumulative runtime, it reaches 1 when the preset lifespan is reached.

[0089] In one embodiment, the risk values ​​of the above-mentioned multiple risk factors can be weighted and summed with reference to Formula 8 to obtain the comprehensive risk value of the target device.

[0090] Formula 8

[0091] Weights of each risk factor It can be set based on operational experience, such as Figure 2 The provided example =0.15, =0.25, =0.2, =0.1, =0.1, =0.2.

[0092] Considering that the weighted summation method described above is insufficient to reflect the correlation and coupling effects between risk factors (for example, the combined risk of "high temperature and abnormal current" is far greater than the sum of the individual risk factors of temperature and current fluctuation), and the amplifying effect of coupling (for example, the harm of voltage fluctuations increases significantly when the temperature rises sharply), this embodiment provides the steps shown in S106 and S108. Through factor multiplication and threshold triggering mechanisms, the weights of high-risk correlated factors are strengthened, achieving dynamic adjustment of the weights of risk factors.

[0093] S106, Based on the influence relationships between risk factors, determine multiple combinations of associated factors among risk factors; wherein each group of associated factors includes at least two risk factors.

[0094] S108, For the associated factors, the initial weights of the second risk factors are adjusted according to the risk value of the first risk factor; wherein, the first risk factor is the risk factor as the independent variable, and the second risk factor is the target risk factor as the dependent variable.

[0095] For steps S106 and S108, the initial weight vectors of each risk factor are first determined: In this study, a non-linear weight is applied to the runtime (D). This reflects the aging characteristic of "low in the early stage and high in the late stage"; therefore, the initial weight of runtime... Nonlinear weight calculation methods can include:

[0096] Based on the preset nonlinear weighting function and the cumulative runtime D of the target device, the initial weights for the runtime are determined. The nonlinear weighting function represents the accelerating increase in the weight of runtime as the cumulative runtime increases, as shown in Formula 9 below.

[0097] Formula Nine

[0098] The initial weights of the other risk factors are pre-set values.

[0099] In this embodiment, for the correlation factor, if the risk value of the first risk factor is greater than the preset risk threshold, the initial weight of the second risk factor is increased and adjusted.

[0100] In one example, when the temperature of the target equipment exceeds a certain temperature limit, the failure rate and the degree of equipment aging will increase. Based on this, the temperature risk factor, historical failure rate, and runtime form a correlation factor. In this set of correlation factors, the temperature risk factor is the independent variable, i.e., the first risk factor, while the historical failure rate and runtime are the dependent variables, i.e., the second risk factor. If the risk value of the temperature risk factor is greater than or equal to a preset risk threshold, the weights of the historical failure rate and runtime are appropriately increased to improve the sensitivity of the overall risk value; specifically, for example, if the risk value T of the temperature risk factor... risk If the value is ≥0.6, the weight of the historical failure rate will be adjusted to... And, adjust the weight of runtime to .

[0101] Similarly, in another example, voltage fluctuations exceeding a certain voltage limit may lead to an increased equipment failure rate. Based on this, voltage stability and historical failure rate form a correlation factor. In this set of correlation factors, voltage stability is the first risk factor as the independent variable, and historical failure rate is the second risk factor as the dependent variable. If the risk value of voltage stability is greater than or equal to a preset risk threshold (e.g., V...), the equipment failure rate may be affected. risk If the value is ≥ 0.5, then the weight of the historical failure rate will be adjusted to... .

[0102] For example, when the current exceeds a certain current limit, it indicates that the equipment is under heavy load, which will significantly affect the equipment temperature. Based on this, if the risk factor of current fluctuation is greater than or equal to the preset risk threshold (such as I...), risk If the value is ≥ 0.5, then the weight of the temperature risk factor will be adjusted to... .

[0103] For example, when the cumulative runtime D of a device approaches the end of its lifespan, device aging can lead to increased operating temperature and failure rate. Therefore, if the risk factor of runtime is greater than or equal to a preset risk threshold (such as D), risk If the value is ≥ 0.8, then the weight of the temperature risk factor is increased as follows: 1+0.5D), and the weight for increasing the historical failure rate is 1+0.5D).

[0104] According to the above embodiments, in each group of associated factors, when the risk value of the first risk factor triggers its corresponding risk threshold, the weight of the second risk factor affected by it will be increased, thereby strengthening the weight of the high-risk second risk factor, realizing dynamic adjustment of the weight of risk factors, and improving the sensitivity of the comprehensive risk value.

[0105] S110, determine the synergistic risk based on the risk values ​​of at least two risk factors that have a synergistic effect.

[0106] This embodiment considers that some risk factors may influence each other, and it is necessary to strengthen the synergistic risk between physically related risk factors and capture the coupling effect between risk factors.

[0107] As an example, there is a synergistic effect between temperature risk factors and current fluctuations, a synergistic effect between voltage stability and current fluctuations, and a synergistic effect between runtime and historical failure rate.

[0108] Based on this, referring to Formula 10 below, the risk value of the temperature risk factor with synergistic effect is determined. Risk value of current fluctuation Risk value of voltage stability Risk value of runtime and historical failure rate Risk value, determine collaborative risk .

[0109] Formula 10

[0110] In the above formula, These are all interaction coefficients, for example, they can all be 0.1. Of course, the specific values ​​of each interaction coefficient can be adjusted appropriately according to the actual situation, but they should generally not be set too large.

[0111] S112. Determine the comprehensive risk value of the target equipment based on the collaborative risk, the risk value of each risk factor and its weight.

[0112] Referring to Formula 11, based on the collaborative risk, the risk values ​​of each risk factor, and their weights, determine the comprehensive risk value of the target equipment:

[0113] Formula Eleven

[0114] in, This represents the overall risk value of the target equipment; This represents the risk value of risk factor i; Indicates collaborative risk; This represents the adjusted weight of risk factor i; it's understandable that some risk factors are influenced by other risk factors, so their weights... The final weights are the weights after adjusting the initial weights; some risk factors are not affected by other risk factors, therefore, their weights... This means initializing the weights, or in other words, using the initial weights as the final weights. .

[0115] Because this embodiment incorporates dynamic weight adjustment and introduces collaborative risk, the maximum value of the overall risk will be greater than 1. Based on this, referring to... Figure 3 This embodiment can normalize the comprehensive risk value.

[0116] In one possible example, the overall risk value determined for the target device is 1.875. This is considering that the original overall risk value has a Risk... raw Given the range characteristic of ∈[0,2], this embodiment can optimize the parameters of the conventional Sigmoid function to achieve a complete mapping from 0 to 1 within this range, while enhancing the discriminative power of the medium-risk range (0.5~1.5), as shown in Formula XII:

[0117] Formula 12

[0118] in, This represents the original composite risk value, Risk. raw The final comprehensive risk value after normalization.

[0119] In the above embodiments, by applying nonlinear weights to the runtime (D), the aging characteristics of "low in the early stage and high in the late stage" are reflected; the weights are dynamically adjusted based on key thresholds; the synergistic effect between risk factors is captured; and the final comprehensive risk value is normalized to [0,1] by the Sigmoid function, which directly guides the inspection strategy and achieves accurate quantification of the comprehensive risk of the target equipment.

[0120] Based on the above embodiments, after determining the comprehensive risk value of the target device, this embodiment may further include:

[0121] Obtain the risk level mapping relationship; wherein the risk level mapping relationship includes the correspondence between at least two of the following: risk value, risk level, color, inspection frequency and alarm; based on the risk level mapping relationship and the comprehensive risk value of the target device in each grid, perform color mapping on each grid of the communication cabinet plane to generate a visual heat map corresponding to the communication cabinet plane.

[0122] In a specific example, the risk level mapping relationship can be seen in the following table.

[0123]

[0124] like Figure 4 As shown in the table above, the color corresponding to the comprehensive risk value of the target device in each grid is determined by referring to the risk level mapping relationship. This allows for color mapping of each grid on the communication cabinet plane, generating a visual heatmap of the communication cabinet plane.

[0125] In practical applications, when the risk value of any risk factor in a certain grid changes by more than a certain percentage (such as 10%), the risk value of that risk factor in that grid is automatically recalculated, and the color display of the heatmap is updated.

[0126] For risk levels of high risk or above, and for risk values ​​of risk factors that change by more than a certain percentage, these can be pushed to the operation and maintenance system simultaneously.

[0127] In summary, the risk inspection method for communication base stations provided in this disclosure includes: dividing the communication cabinet plane into multiple grids; determining the risk values ​​of multiple risk factors for the target equipment in each grid; wherein the risk factors include: equipment importance, historical failure rate, temperature risk factor, voltage stability, current fluctuation, and operating time; determining multiple combinations of correlation factors among the risk factors based on the influence relationships between them; wherein each group of correlation factors includes at least two risk factors; adjusting the initial weight of the second risk factor based on the risk value of the first risk factor for the correlation factor; wherein the first risk factor is the risk factor as the independent variable, and the second risk factor is the target risk factor as the dependent variable; determining the synergistic risk based on the risk values ​​of at least two risk factors that have a synergistic effect; and determining the comprehensive risk value of the target equipment based on the synergistic risk, the risk values ​​of each risk factor, and their weights.

[0128] This technical solution divides the communication cabinet plane into multiple grids, using each grid as an inspection unit to inspect the target devices within that grid. This effectively overcomes the problem of missed inspections, addressing the high device density within the cabinet and improving the comprehensiveness of equipment inspection. For each target device in the grid, risk values ​​are determined based on multiple dimensions of risk factors, including device importance, historical failure rate, temperature risk factors, voltage stability, current fluctuations, and operating time. This enhances the inspection dimensions and the comprehensiveness of risk factors, ensuring that the final calculated overall risk value comprehensively considers these multiple risk factors, thus improving the accuracy of risk assessment. Instead of using pre-set, fixed weights for each risk factor, the solution dynamically adjusts the weights, taking into full account the correlation and coupling effects between risk factors. This ensures that the adjusted weights dynamically adapt to the actual inspection status of the equipment, improving the accuracy of the weights for each risk factor and consequently increasing the sensitivity of the overall risk value. Furthermore, it captures the synergistic risks between risk factors exhibiting synergistic effects, further increasing the accuracy of the overall risk value and achieving precise quantification of the overall risk of the target equipment.

[0129] This disclosure provides a risk inspection device for a communication base station, which is used to implement the risk inspection method for a communication base station provided in the above embodiments. The risk inspection device for a communication base station may include the following modules:

[0130] The grid division module is used to divide the communication cabinet plane into multiple grids;

[0131] The risk value determination module is used to determine the risk value of multiple risk factors for each target device in the grid; wherein the risk factors include: device importance, historical failure rate, temperature risk factor, voltage stability, current fluctuation and operating time;

[0132] The correlation module is used to determine multiple combinations of correlation factors among the risk factors based on the influence relationships between the risk factors; wherein each group of correlation factors includes at least two of the risk factors;

[0133] The weight adjustment module is used to adjust the initial weight of the second risk factor based on the risk value of the first risk factor for the associated factor; wherein the first risk factor is the risk factor as the independent variable, and the second risk factor is the target risk factor as the dependent variable.

[0134] A coordination risk determination module is used to determine the synergistic risk based on the risk values ​​of at least two of the risk factors that have a synergistic effect.

[0135] The comprehensive risk value determination module is used to determine the comprehensive risk value of the target equipment based on the collaborative risk, the risk value of each of the risk factors and their weights.

[0136] The device provided in this embodiment has the same implementation principle and technical effect as the aforementioned method embodiment. For the sake of brevity, any parts not mentioned in the device embodiment can be referred to the corresponding content in the aforementioned method embodiment.

[0137] Figure 5 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this disclosure. Figure 5 As shown, the electronic device 500 includes one or more processors 501 and memory 502.

[0138] The processor 501 may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 500 to perform desired functions.

[0139] The memory 502 may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage medium, and the processor 501 may execute the program instructions to implement the communication base station risk inspection method of the embodiments of this disclosure described above and / or other desired functions. Various contents such as input signals, signal components, and noise components may also be stored in the computer-readable storage medium.

[0140] In one example, the electronic device 500 may also include an input device 503 and an output device 504, which are interconnected via a bus system and / or other forms of connection mechanism (not shown).

[0141] In addition, the input device 503 may also include, for example, a keyboard, a mouse, etc.

[0142] The output device 504 can output various information to the outside, including determined distance information, direction information, etc. The output device 504 may include, for example, a display, a speaker, a printer, and a communication network and its connected remote output devices, etc.

[0143] Of course, for the sake of simplicity, Figure 5 Only some of the components of the electronic device 500 relevant to this disclosure are shown, omitting components such as buses, input / output interfaces, etc. In addition, the electronic device 500 may include any other suitable components depending on the specific application.

[0144] Furthermore, this embodiment also provides a computer-readable storage medium storing a computer program for executing the above-described communication base station risk inspection method.

[0145] The computer program product of the communication base station risk inspection method, device, electronic device and medium provided in this disclosure includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the methods described in the preceding method embodiments. For specific implementation, please refer to the method embodiments, which will not be repeated here.

[0146] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0147] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments described herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A risk inspection method for a communication base station, characterized in that, The method includes: The communication cabinet plane is divided into multiple grids; For each target device in the grid, risk values ​​of multiple risk factors are determined for the target device; wherein, the risk factors include: device importance, historical failure rate, temperature risk factor, voltage stability, current fluctuation and operating time; Based on the influence relationships between the risk factors, multiple combinations of correlation factors are determined among the risk factors; wherein each group of correlation factors includes at least two of the risk factors; For the aforementioned correlation factor, the initial weight of the second risk factor is adjusted based on the risk value of the first risk factor; wherein, the first risk factor is the risk factor as the independent variable, and the second risk factor is the target risk factor as the dependent variable. The synergistic risk is determined based on the risk values ​​of at least two of the aforementioned risk factors that exhibit a synergistic effect; The comprehensive risk value of the target equipment is determined based on the collaborative risk, the risk value of each risk factor, and their weights.

2. The method according to claim 1, characterized in that, Determining the risk value of the temperature risk factor for the target equipment includes: The surface temperature of the target device is collected; When the surface temperature does not exceed the preset temperature threshold of the target device, the risk value of the temperature risk factor of the target device is determined to be 0; When the surface temperature exceeds the temperature threshold, the risk value of the temperature risk factor is determined based on the degree of deviation of the surface temperature from the temperature threshold.

3. The method according to claim 1, characterized in that, Determining the risk value for voltage stability of the target device includes: Collect the input voltage of the target device; Obtain the preset maximum voltage fluctuation range and stable operating voltage fluctuation range of the target device; When the input voltage is within the range of the stable operating voltage fluctuation, the risk value of the voltage stability of the target device is determined to be 0; When the input voltage exceeds the maximum voltage fluctuation range, the risk value of the voltage stability is determined to be 1; When the input voltage is between the stable operating voltage fluctuation range and the maximum voltage fluctuation range, the risk value of the voltage stability is determined based on the input voltage and the preset rated voltage of the target device.

4. The method according to claim 1, characterized in that, Determining the risk value of current fluctuations for the target device includes: Collect the current detection values ​​of the target device within a preset time window; The average current of the target device during the current time and the preset time period before that time is determined as the current reference value; Determine the relative deviation of the current between the detected value during the current period and the current reference value; The risk value of current fluctuation in the target device is determined based on the relative deviation of the current.

5. The method according to claim 1, characterized in that, The risk values ​​for determining the runtime of the target device include: Collect the cumulative runtime of the target device; Based on the preset lifespan of the target device and the cumulative runtime, a risk value for determining the runtime of the target device is determined.

6. The method according to claim 1, characterized in that, The initial weight of the runtime includes: The initial weight of the runtime is determined based on a preset nonlinear weight function and the cumulative runtime of the target device; wherein the nonlinear weight function is used to indicate that the weight of the runtime increases at an accelerating rate with the cumulative runtime.

7. The method according to claim 1, characterized in that, The step of adjusting the initial weight of the second risk factor based on the risk value of the first risk factor for the correlation factor includes: For the correlation factor, if the risk value of the first risk factor is greater than the preset risk threshold, the initial weight of the second risk factor is increased and adjusted.

8. The method according to claim 1, characterized in that, The method further includes: Obtain the risk level mapping relationship; wherein, the risk level mapping relationship includes the correspondence between at least two of the following: risk value, risk level, color, inspection frequency, and alarm; Based on the risk level mapping relationship and the comprehensive risk value of the target device in each grid, color mapping is performed on each grid of the communication cabinet plane to generate a visual heat map corresponding to the communication cabinet plane.

9. A risk inspection device for a communication base station, characterized in that, The device includes: The grid division module is used to divide the communication cabinet plane into multiple grids; The risk value determination module is used to determine the risk value of multiple risk factors for each target device in the grid; wherein the risk factors include: device importance, historical failure rate, temperature risk factor, voltage stability, current fluctuation and operating time; The correlation module is used to determine multiple combinations of correlation factors among the risk factors based on the influence relationships between the risk factors; wherein each group of correlation factors includes at least two of the risk factors; The weight adjustment module is used to adjust the initial weight of the second risk factor based on the risk value of the first risk factor for the associated factor; wherein the first risk factor is the risk factor as the independent variable, and the second risk factor is the target risk factor as the dependent variable. A coordination risk determination module is used to determine the synergistic risk based on the risk values ​​of at least two of the risk factors that have a synergistic effect. The comprehensive risk value determination module is used to determine the comprehensive risk value of the target equipment based on the collaborative risk, the risk value of each of the risk factors and their weights.

10. An electronic device, characterized in that, The electronic device includes: processor; Memory used to store the processor's executable instructions; The processor is configured to read the executable instructions from the memory and execute the instructions to implement the method described in any one of claims 1-8.

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