Method and system for detecting strength of internal frame of optical cable distribution box

Abstract

The invention provides an optical cable distribution box internal frame strength detection method and system, and relates to the technical field of strength detection, and the key points of the technical scheme are that the method comprises the steps: obtaining a first group of structural characteristic parameters of an optical cable distribution box internal frame before operation and maintenance operation; monitoring a preset dynamic characteristic signal generated by the framework; acquiring a second group of structural characteristic parameters of the framework; and based on the difference quantity between the obtained first group of structural characteristic parameters and the obtained second group of structural characteristic parameters and in combination with a preset dynamic characteristic signal monitored in the operation and maintenance operation process, comprehensively judging the structural strength state of the framework after the operation and maintenance operation. The method and system for detecting the strength of the internal frame of the optical cable distribution box have the advantages that the structural strength state of the internal frame of the optical cable distribution box after operation and maintenance operation can be evaluated more accurately, and false alarms are reduced.

Description

Technical Field

[0001] This application relates to the technical field of strength detection, and more particularly, to a method and system for detecting the strength of the internal frame of an optical cable distribution box. Background Art

[0002] The optical cable distribution box is a key infrastructure in the optical fiber communication network. Its internal frame undertakes the important functions of fixing and protecting core components such as optical cables, optical fiber splice points, and optical splitters. These distribution boxes are usually deployed in various complex environmental conditions, such as outdoor poles, walls, or corridors, and are subject to the influence of environmental factors such as temperature, humidity, wind load, and potential external vibrations for a long time. To ensure the stable and reliable operation of the optical fiber network, it is particularly important to effectively monitor and evaluate the structural strength of the internal frame of the optical cable distribution box. Currently, a common monitoring strategy is to install vibration sensors and strain gauges at key structural parts of the frame. The vibration sensor is used to capture the dynamic response characteristics of the frame under different excitations, such as its natural frequency and mode shape changes; the strain gauge directly measures the deformation of the surface of the frame material, thereby reflecting its current stress state. By comprehensively analyzing the data collected by these two types of sensors, the health status of the frame can be evaluated, and the structural strength degradation caused by reasons such as material fatigue, loosening of connectors, corrosion, or accidental external force impacts can be detected in a timely manner, thereby effectively preventing potential network failures.

[0003] During the entire service life cycle of the optical cable distribution box, in addition to daily exposure to environmental loads, the operation and maintenance unit will also perform regular or ad-hoc operation and maintenance operations on the distribution box according to actual needs, such as user growth, service adjustment, or network upgrade. These operations cover various tasks such as adding or removing optical cables, reconfiguring optical fiber jumpers, replacing or adding optical splitters, and repairing faulty optical cables. During the execution of these operation and maintenance operations, the operation and maintenance personnel will inevitably apply various forms of mechanical forces to the internal frame of the optical cable distribution box. For example, when introducing or replacing an optical cable, the fixed points of the optical cable and the frame connection will be subjected to tensile, torsional, or bending forces; when installing or adjusting internal devices (such as optical splitter modules, splicing trays), actions such as tightening screws and clamping modules will also cause local areas of the frame to be subjected to pressure or shear forces. The forces generated by these operation and maintenance operations are significantly different from the daily environmental stresses, and often feature short action times, concentrated action points, and relatively high intensities.

[0004] When the operation and maintenance operations are in progress, the vibration sensors and strain gauges installed on the frame will immediately respond to these forces and record data patterns that are significantly different from the normal operating state. The vibration sensors may capture impact signals generated by using tools (such as tightening with a screwdriver, plugging and unplugging modules), or vibrations caused by component friction during the operation; the strain gauges will measure the rapid changes in strain caused by local forces. These sensor responses during the operation are, on the one hand, the normal mechanical feedback of the frame to the currently applied forces; on the other hand, these operating stresses may also play a role in "detecting flaws". That is to say, they may cause existing but unapparent minor defects in the frame, such as microcracks, virtual solder joints or loose connections, to expand, slip or further reveal under the action of these higher stresses, and may even directly cause new micro-damage to the frame due to improper operations (such as excessive force, improper angle).

[0005] However, most of the existing methods for detecting the strength of the internal frame of the optical cable distribution box rely on the "healthy baseline model" established under the normal operating state of the distribution box and the preset damage alarm threshold. When the data collected by the sensors, whether it is vibration characteristics (such as frequency offset, abnormal amplitude) or strain values (such as exceeding the safe range), or the analysis results of a certain combination of both, exceed the preset normal range, the monitoring system will determine that the frame strength is abnormal. This mechanism faces serious challenges when dealing with the operation and maintenance operation scenarios. The data characteristics (such as strain peaks, vibration intensity) of the stress response caused by the operation and maintenance operations are very likely to exceed the alarm threshold set for the daily working conditions within a short period of time. If the analysis algorithm cannot accurately identify that the current optical cable distribution box is in this special working condition of operation and maintenance operations, it will misjudge these temporary and recoverable stress fluctuations caused by the operation as structural damage, resulting in a large number of false alarms. This will not only interfere with the normal operation and maintenance process, increase unnecessary on-site verification work, but also gradually reduce the trust of the operation and maintenance personnel in the monitoring system itself.

[0006] After the operation and maintenance operations are completed, the stress state and structural characteristics of the frame may not immediately return to the original state before the operation. Some operations, such as the tension introduced by newly added optical cables, the re-tightening of components, etc., may cause the redistribution of internal stress in the frame, or permanently or semi-permanently change the pre-tightening force of the connectors. This transitional state after the operation, whose vibration and strain characteristics are neither the same as the healthy state before the operation nor the clear damage state, can be called the "stress adjustment period" or "structural adaptation period". If the detection system cannot effectively identify and adapt to this structural fine-tuning process introduced by the operation, it may give incorrect evaluation results for a quite long time after the operation. For example, the system may fail to identify the minor damage introduced by improper operation that poses a potential threat to the long-term stability; or conversely, misjudge the normal stress release or benign stress redistribution phenomenon after the operation as a structural risk.

[0007] In addition, factors such as the operation habits of operation and maintenance personnel, their skill proficiency, and the type and condition of the tools they use will all lead to significant uncertainties and individual differences in aspects such as the magnitude, duration, action mode, and loading rate of the force acting on the frame. This means that even for the same type of operation and maintenance operation, the sensor data patterns generated when executed by different operation and maintenance personnel at different times may not be the same. This poses higher requirements for those analysis methods that rely on fixed pattern recognition algorithms or fixed thresholds, and requires the algorithm to have stronger adaptability and robustness to operation disturbances. If the data characteristics in this special scenario of operation and maintenance operations cannot be properly handled, the role of existing detection methods in improving the monitoring accuracy of the internal frame strength of optical cable distribution boxes will be greatly reduced, and it may even lose its practical application value due to frequent false alarms or critical missed alarms, unable to provide reliable data support for operation and maintenance decisions, and it is also difficult to ensure the long-term stable operation of the optical fiber network in a dynamic operation and maintenance environment.

[0008] In view of the above problems, the existing technology urgently needs to be improved. Summary of the Invention

[0009] The purpose of this application is to provide a method and system for detecting the strength of the internal frame of an optical cable distribution box, which has the advantages of being able to more accurately evaluate the structural strength state of the internal frame of the optical cable distribution box after operation and maintenance operations, reducing false alarms, and improving the reliability of detection.

[0010] In the first aspect, this application provides a method for detecting the strength of the internal frame of an optical cable distribution box, and the technical solution is as follows: Obtain a first set of structural characteristic parameters of the internal frame of the optical cable distribution box before the operation and maintenance operation; During the operation and maintenance operation, monitor a preset dynamic characteristic signal generated on the frame due to the operation force, and the preset dynamic characteristic signal characterizes an immediate structural damage of the frame; After the operation and maintenance operation ends and after the internal stress state of the frame caused by the operation force is adjusted to be relatively stable, obtain a second set of structural characteristic parameters of the frame; Based on the difference between the obtained first set of structural characteristic parameters and the obtained second set of structural characteristic parameters, and combined with the preset dynamic characteristic signal monitored during the operation and maintenance operation, comprehensively determine the structural strength state of the frame after the operation and maintenance operation.

[0011] Further, in this application, the step of comprehensively determining the structural strength state of the frame after the operation and maintenance operation based on the difference between the obtained first set of structural characteristic parameters and the obtained second set of structural characteristic parameters, and combined with the preset dynamic characteristic signal monitored during the operation and maintenance operation includes: When the preset dynamic characteristic signal is detected during the operation and maintenance operation, the preset dynamic characteristic signal is used as the priority determination information indicating the occurrence of immediate structural damage to the framework; Calculate the difference amount between the obtained first set of structural characteristic parameters and the obtained second set of structural characteristic parameters; Compare the difference amount with at least one preset structural change evaluation threshold to obtain a parameter difference evaluation result; According to the existence of the priority determination information and the parameter difference evaluation result, perform a fusion judgment to determine the structural strength state of the framework after the operation and maintenance operation. The fusion judgment includes: if the priority determination information indicates the existence of immediate structural damage, then based on the parameter difference evaluation result, determine the influence degree of the immediate structural damage on the structural characteristics of the framework or identify the structural changes indicated by the difference amount; if the priority determination information does not indicate the existence of immediate structural damage, then based on the parameter difference evaluation result, determine whether the structural strength of the framework has changed.

[0012] Further, in the present application, the step of performing a fusion judgment according to the existence of the priority determination information and the parameter difference evaluation result to determine the structural strength state of the framework after the operation and maintenance operation includes: If the priority determination information indicates the existence of immediate structural damage, then further make the following judgment according to the parameter difference evaluation result: When the parameter difference evaluation result indicates that the difference amount of the structural characteristic parameters is lower than the first structural change determination threshold, determine the structural strength state of the framework as the first preset evaluation state; When the parameter difference evaluation result indicates that the difference amount of the structural characteristic parameters is not lower than the first structural change determination threshold, determine the structural strength state of the framework as the second preset evaluation state, where the structural damage influence degree represented by the second preset evaluation state is higher than that of the first preset evaluation state; If the priority determination information does not indicate the existence of immediate structural damage, then further make the following judgment according to the parameter difference evaluation result: When the parameter difference evaluation result indicates that the difference amount of the structural characteristic parameters is higher than the second structural change determination threshold, determine the structural strength state of the framework as the third preset evaluation state.

[0013] Further, in the present application, after the step of determining the structural strength state of the framework as the first preset evaluation state, it further includes: Obtain the preset damage type information corresponding to the immediate structural damage that causes the structural strength state of the framework to be determined as the first preset evaluation state; Obtain preset structure importance level information corresponding to the occurrence location of the instant structural damage; Based on the difference amount of the structural characteristic parameters and the first structural change determination threshold, calculate a quantization proximity parameter between the difference amount of the structural characteristic parameters and the first structural change determination threshold; According to the obtained preset damage type information, the obtained preset structure importance level information, and the calculated quantization proximity parameter, perform risk adjustment on the first preset evaluation state to generate an adjusted first preset evaluation state or a risk indicator associated with the first preset evaluation state.

[0014] Further, in the present application, the step of performing risk adjustment on the first preset evaluation state according to the obtained preset damage type information, the obtained preset structure importance level information, and the calculated quantization proximity parameter to generate an adjusted first preset evaluation state or a risk indicator associated with the first preset evaluation state includes: Obtain at least one predefined specific risk factor combination pattern, where the specific risk factor combination pattern is composed of specific preset damage type information, specific preset structure importance level information, and specific quantization proximity parameter or its parameter interval, and each specific risk factor combination pattern is associated with a preset risk correction rule or a preset corrected risk level; Match the current risk factor combination composed of the currently obtained preset damage type information, the preset structure importance level information, and the calculated quantization proximity parameter with the at least one predefined specific risk factor combination pattern to obtain a matching result; According to the matching result, if the current risk factor combination matches any of the specific risk factor combination patterns, apply the preset risk correction rule associated with the matched specific risk factor combination pattern or directly adopt its preset corrected risk level to perform risk adjustment on the first preset evaluation state to generate the adjusted first preset evaluation state or the risk indicator associated with the first preset evaluation state.

[0015] Further, in the present application, the step of obtaining at least one predefined specific risk factor combination pattern, where the specific risk factor combination pattern is composed of specific preset damage type information, specific preset structure importance level information, and specific quantization proximity parameter or its parameter interval, and each specific risk factor combination pattern is associated with a preset risk correction rule or a preset corrected risk level includes: Access a preset knowledge base or rule engine, where the knowledge base or rule engine stores: at least one predefined specific risk factor combination pattern, which is composed of specific preset damage type information, specific preset structural importance level information, and specific quantified proximity parameters or their parameter ranges, and each of the specific risk factor combination patterns is associated with a preset risk correction rule or a preset corrected risk level; According to the currently obtained preset damage type information, preset structural importance level information, and the calculated quantified proximity parameter, retrieve in the preset knowledge base or rule engine the specific risk factor combination pattern that matches the current risk factor combination composed of the currently obtained preset damage type information, preset structural importance level information, and the calculated quantified proximity parameter, to obtain a matching specific risk factor combination pattern; Extract from the matching specific risk factor combination pattern its associated preset risk correction rule or preset corrected risk level, as the obtained predefined specific risk factor combination pattern and its associated risk correction rule or corrected risk level.

[0016] Further, in the present application, the knowledge base or rule engine is implemented based on a relational database, and the specific risk factor combination pattern and its associated risk correction rule or corrected risk level are stored in a table of the relational database.

[0017] Further, in the present application, the step of, according to the currently obtained preset damage type information, preset structural importance level information, and the calculated quantified proximity parameter, retrieving in the preset knowledge base or rule engine the specific risk factor combination pattern that matches the current risk factor combination composed of the currently obtained preset damage type information, preset structural importance level information, and the calculated quantified proximity parameter, to obtain a matching specific risk factor combination pattern includes: According to the currently obtained preset damage type information, preset structural importance level information, and the calculated quantified proximity parameter, perform a matching operation in the preset knowledge base or rule engine to find the specific risk factor combination pattern that matches the current risk factor combination composed of the currently obtained preset damage type information, preset structural importance level information, and the calculated quantified proximity parameter, to obtain a matching result; If the matching result indicates that no exactly matching specific risk factor combination pattern is found, calculate the similarity between the current risk factor combination and the at least one predefined specific risk factor combination pattern, and determine at least one similar matching pattern based on a preset similarity threshold; If the matching result indicates the existence of multiple matching patterns, and the multiple matching patterns include the exact matching pattern and / or the similar matching pattern, then determine a final matching pattern from the multiple matching patterns according to a preset pattern selection rule; If the matching result indicates that the specific risk factor combination pattern of the exact match cannot be found and there is no any similar matching pattern, then extract a preset general risk correction rule or a preset general corrected risk level associated with the preset damage type information and the preset structural importance level information; If the matching result indicates that the final matching pattern is determined, then extract the preset risk correction rule or the preset corrected risk level associated with the final matching pattern.

[0018] Further, in the present application, the first set of structural characteristic parameters and the second set of structural characteristic parameters include the static strain baseline and the dynamic modal parameters of the frame.

[0019] In a second aspect, the present application also provides an internal frame strength detection system for an optical cable splitting box, and the system includes: A first parameter acquisition module, configured to acquire a first set of structural characteristic parameters of the internal frame of the optical cable splitting box before the operation and maintenance operation; A dynamic signal monitoring module, configured to monitor, during the operation and maintenance operation, a preset dynamic characteristic signal generated on the frame due to the applied operation force, where the preset dynamic characteristic signal characterizes an immediate structural damage of the frame; A second parameter acquisition module, configured to, after the operation and maintenance operation and after the internal stress state of the frame caused by the operation force is adjusted to be relatively stable, acquire a second set of structural characteristic parameters of the frame; A strength state determination module, configured to comprehensively determine the structural strength state of the frame after the operation and maintenance operation based on the difference between the acquired first set of structural characteristic parameters and the acquired second set of structural characteristic parameters, and in combination with the preset dynamic characteristic signal monitored during the operation and maintenance operation.

[0020] As can be seen from the above, an internal frame strength detection method and system for an optical cable splitting box provided by the present application comprehensively determine the structural strength state of the frame after the operation and maintenance operation by combining the dynamic signal monitoring during the operation and maintenance operation and the analysis of the difference in the structural characteristic parameters before and after the operation, and has the advantages of being able to more accurately evaluate the structural strength state of the internal frame of the optical cable splitting box after the operation and maintenance operation, reducing false alarms, and improving the detection reliability. Description of the Drawings

[0021] Figure 1It is a schematic flow chart of a method for detecting the strength of the internal frame of an optical cable fiber distribution box provided by this application.

[0022] Figure 2 It is a schematic structural diagram of a device for detecting the strength of the internal frame of an optical cable fiber distribution box provided by this application.

[0023] In the figure: 1. The first parameter acquisition module; 2. The dynamic signal monitoring module; 3. The second parameter acquisition module; 4. The strength state determination module. Specific implementation manners

[0024] Next, the technical solutions in this application will be clearly and completely described in conjunction with the drawings in this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. Usually, the components of this application described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the drawings is not intended to limit the scope of the claimed application, but only represents the selected embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative efforts fall within the protection scope of this application.

[0025] It should be noted that: Similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings. At the same time, in the description of this application, the terms "first", "second", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0026] Referring to Figure 1 , this application proposes a method for detecting the strength of the internal frame of an optical cable fiber distribution box, including: S110. Obtain the first set of structural characteristic parameters of the internal frame of the optical cable fiber distribution box before the operation and maintenance operation; S120. During the operation and maintenance operation, monitor the preset dynamic characteristic signals generated on the frame due to the applied operation force. The preset dynamic characteristic signals characterize the immediate structural damage of the frame; S130. After the operation and maintenance operation and after the internal stress state of the frame caused by the operation force is adjusted to be relatively stable, obtain the second set of structural characteristic parameters of the frame; S140. Based on the difference between the obtained first set of structural characteristic parameters and the obtained second set of structural characteristic parameters, and in combination with the preset dynamic characteristic signals monitored during the operation and maintenance operation, comprehensively determine the structural strength state of the frame after the operation and maintenance operation.

[0027] Among them, in the solution of this application, the first set of structural characteristic parameters and the second set of structural characteristic parameters include the static strain baseline and dynamic modal parameters of the frame.

[0028] The static strain baseline of the frame refers to the strain distribution measured by sensors such as strain gauges when the frame is in a static or quasi-static state before operation and maintenance operations. This reflects the internal stress level and distribution characteristics of the frame in the initial state. The role of obtaining the static strain baseline is to provide a benchmark for subsequent comparison of whether the operation and maintenance operations cause irreversible plastic deformation or stress redistribution in the frame.

[0029] The dynamic modal parameters refer to the parameters obtained through vibration tests (such as environmental vibration excitation or specific excitation) that can characterize the dynamic characteristics of the frame. This usually includes the multi-order natural frequencies of the frame and the vibration modes under the excitation of each order of natural frequencies (for example, described by the amplitude and phase relationship of the vibration responses at each measuring point). The dynamic modal parameters are very sensitive to the stiffness, mass distribution, and boundary conditions of the structure, etc. The role of obtaining the dynamic modal parameters is to provide a benchmark for subsequent comparison of whether the operation and maintenance operations cause changes in the overall or local stiffness of the frame, changes in the connection state, or other structural damages. For example, a decrease in the natural frequency usually means a decrease in the structural stiffness.

[0030] Among them, the preset dynamic characteristic signal refers to a specific instantaneous signal generated by the frame due to force during the operation and maintenance operations. Specifically, it can be achieved by monitoring impact signals, abnormal vibration modes, high-frequency transient signals, etc. using devices such as vibration sensors and acoustic emission sensors.

[0031] Among them, the difference amount refers to the numerical or pattern difference between the first set of structural characteristic parameters and the second set of structural characteristic parameters. Specifically, it can be achieved by calculating the absolute difference, relative difference, change rate of the parameters or performing pattern comparison.

[0032] Among them, the comprehensive determination refers to judging the structural strength state of the frame after operation by combining the parameter difference amount and the preset dynamic characteristic signal. Specifically, it can be achieved by methods such as preset rules and decision trees.

[0033] The core innovation of this application lies in comprehensively evaluating the strength state of the frame by combining the instant dynamic signals during the operation process with the changes in the structural characteristic parameters before and after the operation.

[0034] This method aims to solve the technical problem of how to accurately evaluate the structural strength state of the internal frame of the optical cable fiber distribution box during operation and maintenance operations. By combining the instant dynamic response during the operation process with the changes in the structural characteristic parameters before and after the operation, this method can more comprehensively and accurately judge whether the frame is damaged or structurally changed due to the operation, thereby improving the reliability of detection and reducing misjudgment.

[0035] Specifically, the method first obtains a first set of structural characteristic parameters of the internal framework of the optical cable distribution box before the operation and maintenance operation. Obtaining the structural characteristic parameters before the operation, such as natural frequency, mode shape, local stiffness, etc., is to establish the baseline data of the framework in the normal and healthy state, providing a reference starting point for evaluating the impact of subsequent operations on the structural characteristics of the framework.

[0036] Next, during the operation and maintenance operation, monitor the preset dynamic characteristic signals generated on the framework due to the applied operation force. Monitor the preset dynamic characteristic signals, such as impact signals, abnormal vibration modes, or specific frequency responses, which are preset to characterize the signs of immediate structural damage to the framework, such as brittle fracture of materials, instantaneous slip of connectors, etc. Capturing such instantaneous signals in real time during the operation can timely detect the immediate and possibly irreversible damage that may be caused by improper operation or the exposure of original defects in the framework under stress, which provides key and priority-indicating information for subsequent comprehensive judgment.

[0037] Then, after the operation and maintenance operation is completed and after the internal stress state of the framework caused by the operation force has adjusted to a relatively stable state, obtain a second set of structural characteristic parameters of the framework. The second set of structural characteristic parameters obtained after the operation is also the natural frequency, mode shape, local stiffness, etc. of the framework, which is used to reflect the final state of the structural characteristics of the framework after the operation is completed. Waiting for the internal stress state of the framework caused by the operation force to adjust to a relatively stable state before obtaining the parameters is to exclude the transient response and stress release process at the end of the operation and obtain the structural characteristics of the framework in the new equilibrium state, so as to more accurately evaluate the long-term or semi-permanent impact of the operation on the overall or local structure of the framework.

[0038] Finally, based on the difference between the first set of structural characteristic parameters obtained and the second set of structural characteristic parameters obtained, and combined with the preset dynamic characteristic signals monitored during the operation and maintenance operation, comprehensively judge the structural strength state of the framework after the operation and maintenance operation. Relying solely on the parameter differences before and after the operation may not be able to distinguish the normal stress redistribution caused by the operation from the actual damage, and relying solely on the dynamic signals during the operation may miss the cumulative or non-instantaneous structural changes caused by the operation.

[0039] By combining the difference in structural characteristic parameters before and after an operation (reflecting the impact of the operation on the overall or local structural characteristics of the framework) with the instantaneous damage dynamic characteristic signal monitored during the operation (reflecting whether an instantaneous damage event occurs during the operation), a more refined judgment can be made. For example, if an instantaneous damage signal is monitored, even if the parameter difference is small, it may indicate the existence of micro-damage; if no instantaneous damage signal is monitored, the evaluation of whether the operation has caused significant structural changes mainly depends on the parameter difference. This comprehensive analysis method can effectively distinguish the normal response, stress adjustment caused by the operation from the actual structural damage, thereby improving the accuracy of judgment, avoiding false alarms and missed judgments in the traditional method in the operation and maintenance scenario, and providing a more reliable basis for the health management of the internal framework of the optical cable distribution box.

[0040] Specifically, in some of the above solutions of the present application, a method for comprehensively determining the structural strength state of the framework after an operation and maintenance operation is proposed based on the difference between the first set of structural characteristic parameters obtained and the second set of structural characteristic parameters obtained, and in combination with the preset dynamic characteristic signal monitored during the operation and maintenance operation. However, in this process, how to effectively integrate the instantaneous dynamic characteristic signal (indicating instantaneous damage) and the difference in structural characteristic parameters after the operation (indicating the structural change in the stable state after the operation) to accurately distinguish the temporary response caused by the operation from the real structural damage, avoid false alarms and missed judgments, and thus improve the accuracy of determining the structural strength state of the framework in the operation and maintenance operation scenario has become a problem.

[0041] In response to this, the present application further proposes that the steps for comprehensively determining the structural strength state of the framework after an operation and maintenance operation based on the difference between the first set of structural characteristic parameters obtained and the second set of structural characteristic parameters obtained, and in combination with the preset dynamic characteristic signal monitored during the operation and maintenance operation include: when a preset dynamic characteristic signal is monitored during the operation and maintenance operation, using the preset dynamic characteristic signal as the priority determination information indicating that the framework has an instantaneous structural damage; calculating the difference between the first set of structural characteristic parameters obtained and the second set of structural characteristic parameters obtained; comparing the difference with at least one preset structural change evaluation threshold to obtain a parameter difference evaluation result; and making a fusion judgment based on the existence of the priority determination information and the parameter difference evaluation result to determine the structural strength state of the framework after the operation and maintenance operation. The fusion judgment includes: if the priority determination information indicates the existence of instantaneous structural damage, determining the degree of influence of the instantaneous structural damage on the structural characteristics of the framework or identifying the structural change indicated by the difference based on the parameter difference evaluation result; if the priority determination information does not indicate the existence of instantaneous structural damage, determining whether the structural strength of the framework has changed based on the parameter difference evaluation result.

[0042] Among them, when a preset dynamic characteristic signal is detected during the operation and maintenance operation, the preset dynamic characteristic signal is used as the priority determination information indicating an immediate structural damage of the frame. The preset dynamic characteristic signal can be data collected by monitoring devices such as vibration sensors or strain gauges. For example, a short-term high-amplitude vibration signal or a rapidly changing strain signal is detected. Using these signals as the priority determination information means that once such instantaneous anomalies are detected, the system will first consider the possibility of immediate structural damage. This is combined with the basic steps of obtaining the first set of structural characteristic parameters before the operation, monitoring the dynamic signals during the operation, and obtaining the second set of structural characteristic parameters after the operation, providing a key instantaneous event marker for subsequent judgments. For example, an acceleration peak threshold can be set, and when the detected acceleration peak exceeds this threshold, a priority determination information flag is generated.

[0043] Calculate the difference between the first set of structural characteristic parameters obtained and the second set of structural characteristic parameters obtained. The first set of structural characteristic parameters is obtained before the operation and maintenance operation, and the second set of structural characteristic parameters is obtained after the operation and maintenance operation and when the frame stress state is adjusted to be relatively stable. The structural characteristic parameters can include natural frequency, modal damping, static stiffness, etc. For example, calculate the percentage decrease in the natural frequency of the frame after the operation relative to the natural frequency before the operation. This difference reflects the long-term or semi-permanent impact of the operation on the stable state of the frame and is the core data for evaluating the real structural changes, complementing the instantaneous dynamic signals during the operation.

[0044] Compare the difference with at least one preset structural change evaluation threshold to obtain a parameter difference evaluation result. The preset structural change evaluation threshold can be determined according to the design specifications, material properties, or historical data of the frame. For example, a natural frequency decrease threshold can be set, such as 2%. If the calculated percentage decrease in the natural frequency exceeds 2%, the parameter difference evaluation result indicates a significant structural change; if it is less than 2%, it indicates an insignificant change. By comparing with the threshold, the continuous difference is converted into a discrete evaluation result, providing a standardized input for subsequent fusion judgments.

[0045] Based on the existence of the priority determination information and the parameter difference evaluation result, perform a fusion judgment to determine the structural strength state of the frame after the operation and maintenance operation. The instantaneous information (priority determination information) during the operation is fused with the stable state information (parameter difference evaluation result) after the operation. This fusion method is not a simple superposition but a logical judgment based on priority, aiming to distinguish the temporary response caused by the operation from the real structural damage.

[0046] The fusion judgment includes two branches: If the priority judgment information indicates the existence of an immediate structural damage, the degree of influence of the immediate structural damage on the characteristics of the frame structure is determined based on the parameter difference evaluation result, or the structural changes indicated by the difference amount are identified; If the priority judgment information does not indicate the existence of an immediate structural damage, it is determined whether the structural strength of the frame has changed based on the parameter difference evaluation result. When the system detects the priority judgment information indicating an immediate damage, it has initially considered that there may be a problem. At this time, the parameter difference evaluation result is used to further quantify or confirm the consequences of this immediate damage. For example, if the instantaneous signal is strong (generating the priority judgment information), but the parameter difference after the operation is small (the parameter difference evaluation result indicates that the change is not significant), it may be determined as an instantaneous response caused by the operation, with limited impact on the long-term structural characteristics. If the instantaneous signal is strong and the parameter difference after the operation is large (the parameter difference evaluation result indicates a significant change), it may be determined that the immediate damage has caused significant structural changes. The magnitude of the parameter difference directly reflects the degree of influence. When no dynamic characteristic signal indicating an immediate damage is detected during the operation and maintenance process (the priority judgment information does not indicate the existence), the system considers the operation process to be relatively stable. At this time, the main basis for judging the frame strength state returns to the parameter difference of the structural characteristics before and after the operation. If the difference is large (the parameter difference evaluation result indicates a significant change), it is determined that the structural strength has changed; if the difference is small (the parameter difference evaluation result indicates that the change is not significant), it is considered that the structural strength has basically not changed. This case-by-case judgment logic improves the accuracy of the judgment result in the complex scenario of operation and maintenance, avoids misjudging the instantaneous high response caused by the operation as damage, and can also identify the structural changes that are not instantaneously captured.

[0047] Specifically, in some of the above solutions of the present application, a method for performing a fusion judgment based on the existence of the priority judgment information and the parameter difference evaluation result to determine the structural strength state of the frame after the operation and maintenance is proposed, so as to comprehensively consider the immediate damage signal and the structural parameter changes before and after the operation to evaluate the frame state. However, in this process, there is a lack of clear judgment criteria and corresponding evaluation state divisions for how to specifically determine the structural strength state based on the parameter difference evaluation result, especially in different situations where the immediate structural damage signal exists or does not exist. This may lead to the evaluation result being not fine enough or ambiguous, and it is difficult to accurately reflect the actual damage degree or structural change situation of the frame.

[0048] In response to this, the present application further proposes that the steps for performing a fusion judgment based on the existence of the priority judgment information and the parameter difference evaluation result to determine the structural strength state of the frame after the operation and maintenance include: If the priority judgment information indicates the existence of an immediate structural damage, then further make the following judgment based on the parameter difference evaluation result: When the result of the parameter difference evaluation indicates that the difference amount of the structural characteristic parameters is lower than the first structural change determination threshold, the structural strength state of the frame is determined as the first preset evaluation state; When the result of the parameter difference evaluation indicates that the difference amount of the structural characteristic parameters is not lower than the first structural change determination threshold, the structural strength state of the frame is determined as the second preset evaluation state, where the degree of structural damage impact characterized by the second preset evaluation state is higher than that of the first preset evaluation state; If the priority determination information does not indicate the existence of immediate structural damage, the following judgment is further made according to the result of the parameter difference evaluation: When the result of the parameter difference evaluation indicates that the difference amount of the structural characteristic parameters is higher than the second structural change determination threshold, the structural strength state of the frame is determined as the third preset evaluation state.

[0049] Among them, this step refines the process of fusing the priority determination information and the result of the parameter difference evaluation to determine the structural strength state of the frame. The core of this step is to use different judgment logics and thresholds to interpret the result of the parameter difference evaluation according to the priority determination information of whether there is immediate structural damage, so as to obtain a more targeted structural strength evaluation state.

[0050] Specifically, the method first obtains the first set of structural characteristic parameters of the frame before the operation and maintenance operation, and monitors the preset dynamic characteristic signal during the operation, and this signal characterizes the occurrence of immediate structural damage of the frame. After the operation ends, after the stress state of the frame is adjusted to be relatively stable, the second set of structural characteristic parameters is obtained. Based on the difference amount between the first set and the second set of parameters, and combined with the monitored preset dynamic characteristic signal, the structural strength state of the frame after the operation and maintenance operation is comprehensively determined. This comprehensive determination includes using the preset dynamic characteristic signal as the priority determination information indicating immediate structural damage, calculating the parameter difference amount, comparing the difference amount with at least one preset structural change evaluation threshold to obtain the result of the parameter difference evaluation. Then, a fusion judgment is made according to whether the priority determination information exists and the result of the parameter difference evaluation.

[0051] This fusion judgment step is further concretized as: If the priority determination information indicates the existence of immediate structural damage, this indicates that the frame may have been impacted or suffered micro-level damage instantaneously during the operation. In this case, even if there is a difference between the structural characteristic parameters after the operation and before the operation, the magnitude of this difference amount is crucial for evaluating the degree of impact of the immediate damage.

[0052] By introducing a first structural change determination threshold, the parameter difference amount is compared with this threshold. For example, the first structural change determination threshold can be preset to five percent of the change rate of structural characteristic parameters (such as natural frequency or strain at a specific position). When the parameter difference evaluation result indicates that the parameter difference amount is lower than the first structural change determination threshold, combined with the presence of an immediate damage signal, the frame state is determined to be the first preset evaluation state. This may indicate that immediate damage has occurred, but its impact on the overall structural characteristics is relatively small. For example, the first preset evaluation state can represent "minor damage". When the parameter difference evaluation result indicates that the parameter difference amount is not lower than the first structural change determination threshold, it is determined to be the second preset evaluation state. For example, the second preset evaluation state can represent "moderate damage". The degree of structural damage characterized by the second preset evaluation state is higher than that of the first preset evaluation state. This method of grading and evaluating the impact degree of immediate damage based on the parameter difference amount enables the potential harmfulness to be judged when immediate damage is detected.

[0053] On the other hand, if the priority determination information does not indicate the presence of an immediate structural damage signal, this may mean that the operation process itself has not caused instant and detectable damage to the frame. In this case, the parameter difference amount of the structural characteristic parameters before and after the operation more reflects the stress redistribution, connection component state change, or cumulative effect caused by the operation, etc. At this time, this solution introduces a second structural change determination threshold and uses it to judge whether the parameter difference amount is higher than this threshold. For example, the second structural change determination threshold can be preset to ten percent of the change rate of structural characteristic parameters, which is higher than the first structural change determination threshold. Only when the parameter difference amount is higher than this second threshold, the structural strength state of the frame is determined to be the third preset evaluation state. For example, the third preset evaluation state can represent "significant change in structural characteristics". This indicates that in the absence of an immediate damage signal, only when the structural parameters have changed significantly (i.e., the difference amount is higher than the second threshold), it is considered that the structural strength of the frame may have undergone a substantial change. By setting different thresholds (the first threshold is used for evaluating the impact degree when there is immediate damage, and the second threshold is used for determining the strength change when there is no immediate damage), and selecting different determination logics according to the presence or absence of an immediate damage signal, this solution can distinguish different causes and different degrees of structural state changes, avoid misjudging normal stress adjustments or minor changes caused by operations as problems, and at the same time can identify potential problems that have no immediate signal but result in significant parameter changes, thereby improving the accuracy and reliability of structural strength evaluation. This step, combined with the steps of obtaining the structural characteristic parameters before and after the operation and monitoring the dynamic signals during the operation process, realizes a refined evaluation of the structural strength state of the frame after the operation and maintenance operation by introducing different determination branches and different thresholds based on the presence of an immediate damage signal, and solves the problem of distinguishing between temporary stress responses and actual structural damage in the operation and maintenance operation scenario.

[0054] Specifically, in some of the above solutions of the present application, it is proposed that when an immediate structural damage is detected and the difference amount of the structural characteristic parameters is lower than the first structural change determination threshold, the structural strength state of the frame is determined as the first preset evaluation state for a preliminary evaluation of the strength state of the frame. However, this simple evaluation fails to fully consider the specific nature of the immediate damage (such as damage type, occurrence location) and the influence of the proximity of the parameter difference amount to the determination threshold on the actual risk, which may lead to an underestimation of certain potential risks or an over - attention to unimportant damages, making the preliminary evaluation result unable to finely distinguish different risk levels and affecting the accuracy and practicality of the evaluation.

[0055] In response to this, the present application further proposes that after the step of determining the structural strength state of the frame as the first preset evaluation state, it further includes: Obtaining preset damage type information corresponding to the immediate structural damage that causes the structural strength state of the frame to be determined as the first preset evaluation state; Obtaining preset structural importance level information corresponding to the occurrence location of the immediate structural damage; Based on the difference amount of the structural characteristic parameters and the first structural change determination threshold, calculating a quantitative proximity parameter between the difference amount of the structural characteristic parameters and the first structural change determination threshold; According to the obtained preset damage type information, the obtained preset structural importance level information, and the calculated quantitative proximity parameter, adjusting the risk of the first preset evaluation state to generate an adjusted first preset evaluation state or a risk indicator associated with the first preset evaluation state.

[0056] Among them, after the structural strength state of the frame is determined as the first preset evaluation state, first, the preset damage type information corresponding to the immediate structural damage is obtained. This information can be pre - stored in the system. For example, according to the monitored dynamic characteristic signal pattern or parameter difference characteristics, the system can automatically identify or infer the damage type, such as a micro - crack, fretting of a connecting piece, or slight deformation. Or, in some embodiments, this information can be input into the system by the operation and maintenance personnel after on - site inspection. Obtaining the damage type information enables subsequent evaluations to distinguish damages of different natures, even if they cause similar parameter change amplitudes.

[0057] Further, obtain the preset structural importance level information corresponding to the location where the immediate structural damage occurs. Different regions of the framework contribute differently to the overall structural strength, and the risks of damage occurring in critical load-bearing areas and non-critical areas are different. The preset structural importance level information can be stored in a structural model or database, associating different positions of the framework with different importance levels (e.g., high, medium, low). The system queries this information based on the detected damage occurrence location (e.g., the area determined based on sensor location or signal analysis). Obtaining the location importance information enables the assessment to consider the potential impact of the damage on the overall structural stability.

[0058] In addition, based on the difference amount of the structural characteristic parameters and the first structural change determination threshold, calculate the quantitative proximity parameter between the difference amount of the structural characteristic parameters and the first structural change determination threshold. This parameter quantifies the relative position of the parameter change degree within the range below the threshold. For example, this parameter can be calculated as the ratio of the difference amount to the threshold, or the difference between the difference amount and the threshold. A proximity parameter close to 1 (when calculated as a ratio) indicates that the difference amount is very close to the threshold, while a proximity parameter close to 0 indicates that the difference amount is much smaller than the threshold. Calculating this parameter provides a continuous and quantitative damage degree indicator for risk assessment, enabling the distinction of its relative magnitude even when the parameter change does not exceed the threshold.

[0059] Thus, based on the obtained preset damage type information, the obtained preset structural importance level information, and the calculated quantitative proximity parameter, perform risk adjustment on the preliminary first preset assessment status. This adjustment process can be implemented based on a predefined rule set or lookup table. For example, if the damage type is identified as a high-risk type, occurs at a location with a high structural importance level, and the quantitative proximity parameter indicates that the difference amount is close to the threshold, even if the preliminary assessment is the first preset assessment status, after adjustment, an adjusted assessment status indicating a higher risk may be generated, or a clear risk indicator may be associated, such as "further inspection required" or "risk level: medium". On the contrary, if the damage type is a low-risk type, occurs at a location with a low importance level, and the proximity parameter indicates that the difference amount is much smaller than the threshold, the adjusted assessment status or risk indicator may indicate a lower risk, such as "risk level: low, continuous monitoring". This adjustment process takes into account the specific nature, location, and degree of the damage, enabling the final assessment result or risk indicator to more accurately reflect the actual risk level, and is an effective supplement and refinement to the preliminary assessment based only on whether the parameter exceeds the threshold. This process, combined with the previous steps of identifying immediate damage and performing preliminary parameter difference assessment, jointly improves the accuracy and practicality of the framework strength assessment in the operation and maintenance scenario.

[0060] Specifically, in some of the above solutions of the present application, after initially determining that the strength state of the frame structure is in the first preset evaluation state (i.e., there is immediate structural damage but the difference in structural characteristic parameters is low), based on the obtained preset damage type information, preset structural importance level information, and the calculated quantitative proximity parameter, the risk of this first preset evaluation state is adjusted to generate an adjusted evaluation state or a risk indicator. However, how to systematically and accurately combine these three risk factors for refined risk adjustment to reflect the comprehensive risks of different damage types, different structural positions, and different degrees of damage (characterized by the quantitative proximity parameter) is a problem that needs to be solved. Simply adjusting according to these three factors may lack a unified standard and fine discrimination, and it is difficult to comprehensively cover various complex risk scenarios, which may lead to inaccurate risk assessment results and affect the effectiveness of subsequent maintenance decisions.

[0061] In response to this, the present application further proposes that the steps of adjusting the risk of the first preset evaluation state based on the obtained preset damage type information, the obtained preset structural importance level information, and the calculated quantitative proximity parameter to generate an adjusted first preset evaluation state or a risk indicator associated with the first preset evaluation state include: obtaining at least one predefined specific risk factor combination pattern, where the specific risk factor combination pattern is composed of specific preset damage type information, specific preset structural importance level information, and specific quantitative proximity parameter or its parameter range, and each specific risk factor combination pattern is associated with a preset risk correction rule or a preset corrected risk level; matching the current risk factor combination composed of the currently obtained preset damage type information, preset structural importance level information, and calculated quantitative proximity parameter with at least one predefined specific risk factor combination pattern to obtain a matching result; according to the matching result, if the current risk factor combination matches any specific risk factor combination pattern, then apply the preset risk correction rule associated with the matched specific risk factor combination pattern or directly adopt its preset corrected risk level to adjust the risk of the first preset evaluation state to generate an adjusted first preset evaluation state or a risk indicator associated with the first preset evaluation state.

[0062] Among them, this solution provides a method for systematically and refinedly adjusting the risk of immediate structural damage initially evaluated as the first preset evaluation state based on predefined knowledge or rules. By matching the current combination of damage type, structural importance level, and degree of damage (quantitative proximity) with predefined specific risk patterns and applying the corresponding correction rules or levels, it overcomes the inaccuracy and incompleteness problems that may be brought about by simple adjustment, and improves the accuracy and reliability of risk assessment.

[0063] Specifically, first, obtain at least one predefined specific risk factor combination pattern. These patterns are preset knowledge or rules, and each pattern is composed of a specific damage type, a specific structural importance level, and a specific quantification proximity parameter or its parameter interval, and each pattern is associated with a preset risk correction rule or a preset corrected risk level. This step establishes a structured risk assessment knowledge base, provides a basis for subsequent refined risk adjustment, and solves the problem of lack of standards and fineness in simple adjustment. By associating different risk factor combinations with specific correction rules or levels, the system can give different risk assessments for different damage situations. For example, a preset pattern can be defined as: "Damage type = crack, importance level = key load-bearing component, quantification proximity interval = [0.8, 1.0]", and the associated correction rule is "upgrade the assessment status by one level"; another pattern can be defined as: "Damage type = loosening of connecting parts, importance level = non-critical component, quantification proximity interval = [0.5, 0.7]", and the associated correction level is "low risk". These patterns can be stored in a database, a rule engine, or a configuration file.

[0064] Next, match the current risk factor combination composed of the currently obtained preset damage type information, preset structural importance level information, and calculated quantification proximity parameter with at least one predefined specific risk factor combination pattern to obtain a matching result. This step associates the actually detected damage situation with the predefined risk knowledge. By combining the type, location importance, and damage degree of the currently occurring damage, a "current risk factor combination" is formed and compared and matched with various predefined "specific risk factor combination patterns". For example, if the currently detected damage type is "crack", the importance level of the occurrence location is "key load-bearing component", and the calculated quantification proximity parameter is 0.95, then the current risk factor combination is (crack, key load-bearing component, 0.95). The system will compare this combination with the predefined patterns to find whether there is a completely matching or a pattern that meets the parameter interval. This matching process is the bridge for applying predefined knowledge for risk assessment, which enables the system to find the predefined risk pattern most relevant to the current actual situation, thus providing a basis for subsequent application of correction rules or levels. The matching can be achieved by means of exact matching, rule-based matching, or similarity-based fuzzy matching, etc.

[0065] Finally, based on the matching results, if the current risk factor combination matches any specific risk factor combination pattern, apply the preset risk correction rule associated with the matched specific risk factor combination pattern or directly adopt its preset corrected risk level to adjust the risk of the first preset assessment status, so as to generate an adjusted first preset assessment status or a risk indicator associated with the first preset assessment status. This step is the core of performing risk adjustment. Once the current risk factor combination successfully matches one or more predefined specific risk factor combination patterns, the system no longer relies on simple, unstructured adjustment methods, but directly applies the preset risk correction rule or corrected risk level associated with the matching pattern. Applying the risk correction rule can be to increase or decrease the first preset assessment status to a certain extent. For example, adjusting the "first preset assessment status" (presence of immediate damage, low difference amount) to "medium risk" or "high risk"; while directly adopting the corrected risk level may be to directly map the first preset assessment status to a more refined risk level, such as directly determining it as "immediate attention required". This method based on matching predefined patterns ensures the standardization, repeatability, and refinement of the risk adjustment process, can more accurately reflect the true risk level under different risk factor combinations, thereby generating more instructive assessment results or risk indicators, and overcomes the inaccuracy and incompleteness problems that may be brought by simple adjustments.

[0066] This solution is combined with the step of initially determining that the structural strength status of the framework is the first preset assessment status. On the basis of initially determining the presence of immediate damage and a low difference amount of structural characteristic parameters, three dimensions of damage type, structural importance level, and quantification proximity are further introduced, and structured matching and adjustment are performed through a predefined knowledge base. This enables the assessment results to no longer solely depend on whether the difference amount of parameters is lower than the threshold, but can distinguish the true risks of different types of damage at different positions and degrees. For example, a tiny crack in a key load-bearing member may have a much higher risk than a loose connection in a non-critical member, even if the difference amount of parameters is very small. Through the preset pattern, the system can identify this combined risk and adjust the initial "first preset assessment status" to a higher-level risk indicator, thus more accurately guiding subsequent maintenance and intervention measures. This refined adjustment mechanism based on multi-factor combination matching improves the accuracy and practicality of the risk assessment of immediate micro-damage in the operation and maintenance scenario, and solves the problems brought by simply relying on the difference amount of parameters for adjustment.

[0067] As a preferred embodiment, the solution of the present application is specifically implemented as follows: After initially determining that the strength state of the frame structure is in the first preset evaluation state, it is necessary to adjust the risk of this first preset evaluation state based on the obtained preset damage type information, the obtained preset structural importance level information, and the calculated quantitative proximity parameter.

[0068] Specifically, first obtain at least one predefined specific risk factor combination pattern. For example, a knowledge base can be defined that contains multiple patterns. One pattern can be defined as: the damage type is "microcrack", the structural importance level is "key load-bearing member", the quantitative proximity parameter interval is "0.7 to 1.0", and the risk correction rule associated with this pattern is "upgrade the evaluation state by one level"; another pattern can be defined as: the damage type is "slight loosening of the connection piece", the structural importance level is "secondary support member", the quantitative proximity parameter interval is "0.4 to 0.6", and the corrected risk level associated with this pattern is "low risk". These patterns and their associated rules or levels are stored in the system.

[0069] Next, match the current risk factor combination formed by the currently obtained preset damage type information, preset structural importance level information, and calculated quantitative proximity parameter with at least one predefined specific risk factor combination pattern. For example, assume that the currently detected damage type is "microcrack", the structural importance level of the occurrence location is "key load-bearing member", and the calculated quantitative proximity parameter is 0.85. Thus, the current risk factor combination (microcrack, key load-bearing member, 0.85) is formed. The system compares this combination with the predefined patterns.

[0070] According to the matching result, if the current risk factor combination matches any specific risk factor combination pattern, apply the preset risk correction rule associated with the matched specific risk factor combination pattern or directly adopt its preset corrected risk level to adjust the risk of the first preset evaluation state. For example, the current combination (microcrack, key load-bearing member, 0.85) matches the above-defined pattern one (the damage type is "microcrack", the structural importance level is "key load-bearing member", and the quantitative proximity parameter interval is "0.7 to 1.0"). The risk correction rule associated with this pattern is "upgrade the evaluation state by one level". If the initially evaluated first preset evaluation state is "slight damage", after applying this rule, the adjusted evaluation state may become "medium-risk damage". Or, if the matched pattern is associated with a corrected risk level, such as "high risk", then directly set the adjusted evaluation state or the associated risk indicator to "high risk". Thus, the adjusted first preset evaluation state or the risk indicator associated with the first preset evaluation state is generated.

[0071] Through the above technical solution, the present application provides a method for risk adjustment of immediate structural damage initially evaluated as the first preset evaluation state in a systematic and refined manner. By pre-defining specific risk factor combination patterns and associating corresponding correction rules or levels, a structured risk assessment knowledge system is established, overcoming the problems of lack of unified standards and fine discrimination in simple adjustment. Matching the current combination of damage type, structural importance level, and damage degree (quantification proximity) with the pre-defined patterns and applying the corresponding correction rules or levels enables the risk adjustment process to give differentiated evaluations for different damage situations, improving the accuracy and reliability of risk assessment. Thus, the generated adjusted evaluation state or risk indicator can more accurately reflect the true risk level under different combinations of risk factors, providing a more guiding basis for subsequent maintenance decisions.

[0072] The present application further proposes a step of obtaining at least one pre-defined specific risk factor combination pattern. The specific risk factor combination pattern is composed of specific pre-set damage type information, specific pre-set structural importance level information, and specific quantification proximity parameters or their parameter intervals, and each specific risk factor combination pattern is associated with a pre-set risk correction rule or a pre-set corrected risk level, including: accessing a pre-set knowledge base or rule engine, where the knowledge base or rule engine stores: at least one pre-defined specific risk factor combination pattern, the specific risk factor combination pattern is composed of specific pre-set damage type information, specific pre-set structural importance level information, and specific quantification proximity parameters or their parameter intervals, and each specific risk factor combination pattern is associated with a pre-set risk correction rule or a pre-set corrected risk level; according to the currently obtained pre-set damage type information, pre-set structural importance level information, and calculated quantification proximity parameters, retrieving in the pre-set knowledge base or rule engine a specific risk factor combination pattern that matches the current risk factor combination composed of the currently obtained pre-set damage type information, pre-set structural importance level information, and calculated quantification proximity parameters, to obtain the matching specific risk factor combination pattern; extracting from the matching specific risk factor combination pattern its associated pre-set risk correction rule or pre-set corrected risk level, so as to obtain the pre-defined specific risk factor combination pattern and its associated risk correction rule or corrected risk level.

[0073] First, by accessing a preset knowledge base or rule engine, which is used as a centralized storage and management platform where various specific risk factor combination patterns are pre-stored. Each pattern is defined by a specific damage type, structural importance level, and a quantified proximity parameter or range, and is associated with a specific risk modification rule or modified risk level. For example, a record can be stored in the knowledge base indicating that when the damage type is "microcrack", the structural importance level is "high", and the quantified proximity parameter is in the range of "0.8 - 1.0", the corresponding risk modification rule is to upgrade the assessment status by one level, or the modified risk level is "high risk". This structured storage method solves the problem of how to manage a large number of complex rule combinations.

[0074] Furthermore, according to the specific situation detected currently, that is, the obtained preset damage type information, preset structural importance level information, and the calculated quantified proximity parameter, these information are formed into a current risk factor combination. For example, currently, the detected damage type is "microcrack", the structural importance level is "medium", and the quantified proximity parameter is "0.7". Thus, this current risk factor combination is retrieved in the said knowledge base or rule engine. This retrieval process aims to quickly and accurately find the preset specific risk factor combination pattern that matches the current risk factor combination.

[0075] For example, the system will search in the knowledge base to check if there is a preset pattern with a damage type of "microcrack", a structural importance level of "medium", and a quantified proximity parameter that includes 0.7. This way of querying based on the current actual situation solves the problem of how to locate the applicable risk modification rule according to the current situation. Finally, once the matching specific risk factor combination pattern is found, the preset associated risk modification rule or modified risk level is extracted from this matching pattern. For example, if a matching pattern indicates that "microcrack", "medium importance", "0.6 - 0.8 proximity" corresponds to "risk level upgraded by half a level", then the rule of "risk level upgraded by half a level" is extracted. This extracted rule or level is the basis for subsequent risk adjustment of the first preset assessment status. This solution is combined with the previous steps. The previous steps provide the input information (damage type, importance, proximity) required for risk adjustment, while this solution provides a mechanism to obtain the rules or levels required for adjustment based on these input information. Thus, it ensures that the risk adjustment process is based on the preset knowledge or rules corresponding to specific risk factor combinations, improving the standardization and accuracy of risk assessment.

[0076] This application further proposes that the knowledge base or rule engine is implemented based on a relational database, and the specific risk factor combination patterns and their associated risk modification rules or modified risk levels are stored in the tables of the relational database.

[0077] The knowledge base or rule engine is implemented based on a relational database. The relational database provides data management, query optimization, and transaction processing capabilities. Implementing the knowledge base or rule engine based on a relational database provides a structured platform for storing and managing specific risk factor combination patterns and their associated rules or levels.

[0078] Specifically, by storing specific risk factor combination patterns and their associated risk correction rules or corrected risk levels in a structured manner in the tables of a relational database, the system can utilize the query and indexing functions of the database to quickly retrieve and extract matching patterns and their associated information based on the input risk factors, thereby supporting risk adjustment for the first preset assessment status.

[0079] This application further proposes steps for retrieving, in a preset knowledge base or rule engine, a specific risk factor combination pattern that matches the current risk factor combination formed by the currently obtained preset damage type information, preset structural importance level information, and calculated quantitative proximity parameter. The steps include: According to the currently obtained preset damage type information, preset structural importance level information, and calculated quantitative proximity parameter, perform a matching operation in the preset knowledge base or rule engine to find a specific risk factor combination pattern that matches the current risk factor combination formed by the currently obtained preset damage type information, preset structural importance level information, and calculated quantitative proximity parameter, and obtain a matching result; If the matching result indicates that no exactly matching specific risk factor combination pattern is found, calculate the similarity between the current risk factor combination and at least one predefined specific risk factor combination pattern, and determine at least one similar matching pattern based on a preset similarity threshold; If the matching result indicates that there are multiple matching patterns, and the multiple matching patterns include exact matching patterns and / or similar matching patterns, then determine a final matching pattern from the multiple matching patterns according to a preset pattern selection rule; If the matching result indicates that no exactly matching specific risk factor combination pattern is found and there are no any similar matching patterns, then extract the preset general risk correction rule or preset general corrected risk level associated with the preset damage type information and preset structural importance level information; If the matching result indicates that the final matching pattern is determined, then extract the preset risk correction rule or preset corrected risk level associated with the final matching pattern.

[0080] Among them, this solution elaborates in detail the specific process of retrieving and matching specific risk factor combination patterns in a knowledge base or rule engine. This process aims to solve the problems of insufficient exact matching or the existence of multiple matching options that may be encountered in practical applications, thereby improving the accuracy and applicability of risk adjustment.

[0081] First, based on the current risk factor combination composed of the currently obtained preset damage type information, preset structural importance level information, and calculated quantitative proximity parameter, perform a matching operation in the preset knowledge base or rule engine to find a specific risk factor combination pattern that matches this current risk factor combination and obtain a preliminary matching result. This step is a basic retrieval process that attempts to directly find a preset pattern that exactly corresponds to the current situation. For example, if the current risk factor combination is "slight crack, important area, proximity 0.1", the system will search in the knowledge base to see if there is a pattern entry that exactly matches "slight crack, important area, proximity 0.1". This matching operation can be implemented by means such as database query, rule engine reasoning, or knowledge graph matching.

[0082] If the preliminary matching result indicates that no exactly matching specific risk factor combination pattern is found, then further calculate the similarity between the current risk factor combination and at least one predefined specific risk factor combination pattern. This is to deal with the situation where the actual situation may have a certain difference from the preset patterns in the knowledge base. By calculating the similarity, preset patterns that are "close" to the current situation can be identified. For example, if there is no exact match for "slight crack, important area, proximity 0.1" in the knowledge base, but there are patterns such as "slight crack, important area, proximity 0.2" or "slight crack, sub-important area, proximity 0.15", the system will calculate the similarity between the current combination and these patterns. The calculation of similarity can adopt different methods according to the data type of the factors (such as classification, ordinal, numerical) and perform weighted combination. Then, based on a preset similarity threshold, determine at least one similar matching pattern. This step expands the scope of matching, so that even if there is no exact match, potentially relevant preset patterns can be found, increasing the robustness of the method. The calculation of this similarity and the determination of the similar matching pattern utilize the detailed risk factor information obtained from the previous steps (for example, the damage type, importance level, and calculated quantitative proximity parameter obtained after determining the first preset evaluation state), making the matching process more flexible and refined.

[0083] If the matching result indicates the existence of multiple matching patterns, these patterns may include exact matching patterns and / or similar matching patterns obtained through similarity calculation. In this case, it is necessary to determine a final matching pattern from these multiple matching patterns according to the preset pattern selection rules. For example, if an exact matching pattern and several similar matching patterns with relatively high similarity are found at the same time, the pattern selection rules can stipulate that the exact matching pattern is preferred; or if there are multiple similar matching patterns, the selection rules can be based on the similarity level (select the one with the highest similarity), the preset priority of the pattern, or the strategy defined by experts to determine the final pattern. This pattern selection rule ensures that when there are multiple possibilities, the most appropriate pattern can be selected for subsequent processing, improving the intelligence level of decision-making.

[0084] If the matching result indicates that no exact matching pattern of a specific combination of risk factors is found, and there are no similar matching patterns after similarity calculation (that is, the comprehensive similarity of all preset patterns is lower than the preset comprehensive similarity threshold), this indicates that the current combination of risk factors is not close enough to any specific pattern in the knowledge base. In this case, the system will extract the preset general risk correction rules or the preset general corrected risk levels associated with the preset damage type information and the preset structural importance level information. For example, if the current situation is "minor crack, important area" but no specific matching pattern is found, the system will search for the general rules preset in the knowledge base for the combination of "minor crack" and "important area". This is a fallback mechanism to ensure that when no specific rules can be found, a relatively general risk assessment or correction strategy can still be applied based on the two key factors of damage type and importance level, avoiding the complete inability to adjust risks and ensuring the integrity of the method. The extraction of this general rule utilizes the damage type and importance level information obtained from the previous steps, providing a basic basis for risk assessment even in the absence of specific pattern matching.

[0085] Finally, if the matching result indicates that a final matching pattern has been determined (whether it is an exact match or a similar matching pattern determined by the selection rule), then extract the preset risk correction rule or the preset corrected risk level associated with the final matching pattern. For example, if it is finally determined that the pattern "slight crack, important area, proximity 0.1" is matched, and the rule associated with this pattern is "increase the risk level by one level", then extract this rule. This extracted rule or level will be used to adjust the risk of the previously determined first preset evaluation status, thereby generating an adjusted evaluation status or an associated risk indicator. This step is the ultimate goal of the entire matching and retrieval process, that is, to obtain a specific basis for risk adjustment, so that the risk assessment result is more in line with the actual situation. Through this multi-level matching and selection process, combined with the detailed damage and structural information obtained from the previous steps, this solution can more accurately identify the risks associated with the immediate damage caused by the operation and maintenance operations, and make corresponding adjustments, thereby improving the reliability of the assessment of the strength state of the frame structure, helping to distinguish the temporary impact caused by the operation from the actual structural damage, and evaluating the final state after the operation.

[0086] In a second aspect, referring to Figure 2 , this application proposes an internal frame strength detection system for an optical cable distribution box, and the system includes: A first parameter acquisition module 1, configured to acquire a first set of structural characteristic parameters of the internal frame of the optical cable distribution box before the operation and maintenance operation; A dynamic signal monitoring module 2, configured to monitor, during the operation and maintenance operation, a preset dynamic characteristic signal generated on the frame due to the applied operation force, where the preset dynamic characteristic signal characterizes an immediate structural damage of the frame; A second parameter acquisition module 3, configured to acquire a second set of structural characteristic parameters of the frame after the operation and maintenance operation and after the internal stress state of the frame caused by the operation force is adjusted to be relatively stable; A strength state determination module 4, configured to comprehensively determine the structural strength state of the frame after the operation and maintenance operation based on the difference between the acquired first set of structural characteristic parameters and the acquired second set of structural characteristic parameters, and in combination with the preset dynamic characteristic signal monitored during the operation and maintenance operation.

[0087] By combining the dynamic signal monitoring during the operation and maintenance operation and the analysis of the difference in structural characteristic parameters before and after the operation, the structural strength state of the frame after the operation and maintenance operation is comprehensively determined, which has the advantages of being able to more accurately evaluate the structural strength state of the internal frame of the optical cable distribution box after the operation and maintenance operation, reducing false alarms, and improving the detection reliability.

[0088] In addition, in some preferred embodiments, an internal frame strength detection system for an optical cable distribution box proposed in this application can execute any one of the steps in the above method.

[0089] The above are only embodiments of the present application and are not intended to limit the protection scope of the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A method for detecting the strength of the internal frame of an optical cable fiber distribution box, characterized in that, Including: Obtaining a first set of structural characteristic parameters of the internal frame of the optical cable fiber distribution box before the operation and maintenance operation; During the operation and maintenance operation, monitoring a preset dynamic characteristic signal generated on the frame due to the applied operation force, where the preset dynamic characteristic signal characterizes an immediate structural damage to the frame; After the operation and maintenance operation and after the internal stress state of the frame caused by the operation force is adjusted to be relatively stable, obtaining a second set of structural characteristic parameters of the frame; Based on the difference between the obtained first set of structural characteristic parameters and the obtained second set of structural characteristic parameters, and in combination with the preset dynamic characteristic signal monitored during the operation and maintenance operation, comprehensively determining the structural strength state of the frame after the operation and maintenance operation.

2. The internal frame strength detection method of an optical cable fiber distribution box according to claim 1, characterized in that, The step of comprehensively determining the structural strength state of the frame after the operation and maintenance operation based on the difference between the obtained first set of structural characteristic parameters and the obtained second set of structural characteristic parameters, and in combination with the preset dynamic characteristic signal monitored during the operation and maintenance operation includes: When the preset dynamic characteristic signal is monitored during the operation and maintenance operation, using the preset dynamic characteristic signal as the priority determination information indicating an immediate structural damage to the frame; Calculating the difference between the obtained first set of structural characteristic parameters and the obtained second set of structural characteristic parameters; Comparing the difference with at least one preset structural change evaluation threshold to obtain a parameter difference evaluation result; According to the existence of the priority determination information and the parameter difference evaluation result, performing a fusion judgment to determine the structural strength state of the frame after the operation and maintenance operation. The fusion judgment includes: If the priority determination information indicates the existence of an immediate structural damage, determining the degree of influence of the immediate structural damage on the structural characteristics of the frame or identifying the structural change indicated by the difference based on the parameter difference evaluation result; If the priority determination information does not indicate the existence of an immediate structural damage, determining whether the structural strength of the frame has changed based on the parameter difference evaluation result.

3. A method for detecting the internal frame strength of an optical cable fiber distribution box according to claim 2, characterized in that, The step of performing a fusion judgment to determine the structural strength state of the frame after the operation and maintenance operation according to the existence of the priority determination information and the parameter difference evaluation result includes: If the priority determination information indicates the existence of an immediate structural damage, further making the following judgment according to the parameter difference evaluation result: When the parameter difference evaluation result indicates that the difference in the structural characteristic parameters is lower than the first structural change determination threshold, determining the structural strength state of the frame as the first preset evaluation state; When the parameter difference evaluation result indicates that the difference in the structural characteristic parameters is not lower than the first structural change determination threshold, determining the structural strength state of the frame as the second preset evaluation state, where the degree of structural damage characterized by the second preset evaluation state is higher than that of the first preset evaluation state; If the priority determination information does not indicate the existence of an immediate structural damage, further making the following judgment according to the parameter difference evaluation result: When the parameter difference evaluation result indicates that the difference amount of the structural characteristic parameters is higher than the second structural change determination threshold, determine the structural strength state of the frame as the third preset evaluation state.

4. A method for detecting the internal frame strength of an optical cable fiber distribution box according to claim 3, characterized in that, After the step of determining the structural strength state of the frame as the first preset evaluation state, the method further includes: Obtaining preset damage type information corresponding to the instant structural damage that causes the structural strength state of the frame to be determined as the first preset evaluation state; Obtaining preset structural importance level information corresponding to the location where the instant structural damage occurs; Calculating a quantization proximity parameter between the difference amount of the structural characteristic parameters and the first structural change determination threshold based on the difference amount of the structural characteristic parameters and the first structural change determination threshold; Performing risk adjustment on the first preset evaluation state according to the obtained preset damage type information, the obtained preset structural importance level information, and the calculated quantization proximity parameter, to generate an adjusted first preset evaluation state or a risk indicator associated with the first preset evaluation state.

5. A method for detecting the strength of the internal frame of an optical cable fiber distribution box according to claim 4, characterized in that, The step of performing risk adjustment on the first preset evaluation state according to the obtained preset damage type information, the obtained preset structural importance level information, and the calculated quantization proximity parameter, to generate an adjusted first preset evaluation state or a risk indicator associated with the first preset evaluation state includes: Obtaining at least one predefined specific risk factor combination pattern, where the specific risk factor combination pattern is composed of specific preset damage type information, specific preset structural importance level information, and specific quantization proximity parameter or its parameter range, and each specific risk factor combination pattern is associated with a preset risk correction rule or a preset corrected risk level; Matching the current risk factor combination composed of the currently obtained preset damage type information, the preset structural importance level information, and the calculated quantization proximity parameter with the at least one predefined specific risk factor combination pattern to obtain a matching result; According to the matching result, if the current risk factor combination matches any of the specific risk factor combination patterns, apply the preset risk correction rule associated with the matched specific risk factor combination pattern or directly adopt its preset corrected risk level to perform risk adjustment on the first preset evaluation state, so as to generate the adjusted first preset evaluation state or the risk indicator associated with the first preset evaluation state.

6. A method for detecting the internal frame strength of an optical cable fiber distribution box according to claim 5, characterized in that The step of obtaining at least one predefined specific risk factor combination pattern, where the specific risk factor combination pattern is composed of specific preset damage type information, specific preset structural importance level information, and specific quantization proximity parameter or its parameter range, and each specific risk factor combination pattern is associated with a preset risk correction rule or a preset corrected risk level includes: Access a preset knowledge base or rule engine, where the knowledge base or rule engine stores: at least one predefined specific risk factor combination pattern, which is composed of specific preset damage type information, specific preset structural importance level information, and specific quantitative proximity parameters or their parameter intervals, and each of the specific risk factor combination patterns is associated with a preset risk correction rule or a preset corrected risk level; According to the currently obtained preset damage type information, the preset structural importance level information, and the calculated quantitative proximity parameters, retrieve in the preset knowledge base or rule engine the specific risk factor combination pattern that matches the current risk factor combination composed of the currently obtained preset damage type information, the preset structural importance level information, and the calculated quantitative proximity parameters, to obtain the matching specific risk factor combination pattern; Extract from the matching specific risk factor combination pattern the associated preset risk correction rule or the preset corrected risk level, so as to obtain the predefined specific risk factor combination pattern and its associated risk correction rule or corrected risk level.

7. A method for detecting the internal frame strength of an optical cable fiber distribution box according to claim 6, characterized in that, The knowledge base or rule engine is implemented based on a relational database, and the specific risk factor combination pattern and its associated risk correction rule or corrected risk level are stored in a table of the relational database.

8. A method for detecting the strength of the internal frame of an optical cable fiber distribution box according to claim 6, characterized in that, The step of, according to the currently obtained preset damage type information, the preset structural importance level information, and the calculated quantitative proximity parameters, retrieving in the preset knowledge base or rule engine the specific risk factor combination pattern that matches the current risk factor combination composed of the currently obtained preset damage type information, the preset structural importance level information, and the calculated quantitative proximity parameters, to obtain the matching specific risk factor combination pattern includes: According to the currently obtained preset damage type information, the preset structural importance level information, and the calculated quantitative proximity parameters, perform a matching operation in the preset knowledge base or rule engine to find the specific risk factor combination pattern that matches the current risk factor combination composed of the currently obtained preset damage type information, the preset structural importance level information, and the calculated quantitative proximity parameters, to obtain a matching result; If the matching result indicates that no exactly matching specific risk factor combination pattern is found, calculate the similarity between the current risk factor combination and the at least one predefined specific risk factor combination pattern, and determine at least one similar matching pattern based on a preset similarity threshold; If the matching result indicates that there are multiple matching patterns, and the multiple matching patterns include the exact matching pattern and / or the similar matching pattern, then determine a final matching pattern from the multiple matching patterns according to a preset pattern selection rule; If the matching result indicates that the specific risk factor combination pattern with an exact match cannot be found and there is no such similar matching pattern, then extract the preset general risk correction rule or the preset general corrected risk level associated with the preset damage type information and the preset structural importance level information; If the matching result indicates that the final matching pattern is determined, then extract the preset risk correction rule or the preset corrected risk level associated with the final matching pattern.

9. A method for detecting the strength of the internal frame of an optical cable fiber distribution box according to claim 1, characterized in that, The first set of structural characteristic parameters and the second set of structural characteristic parameters include the static strain baseline and the dynamic modal parameters of the frame.

10. An internal frame strength detection system for an optical cable fiber distribution box, characterized in that, The system includes: A first parameter acquisition module, configured to acquire a first set of structural characteristic parameters of the internal frame of the optical cable distribution box before the operation and maintenance operation; A dynamic signal monitoring module, configured to monitor, during the operation and maintenance operation, a preset dynamic characteristic signal generated on the frame due to the applied operating force, where the preset dynamic characteristic signal characterizes an immediate structural damage to the frame; A second parameter acquisition module, configured to acquire a second set of structural characteristic parameters of the frame after the operation and maintenance operation and after the internal stress state of the frame caused by the operating force is adjusted to be relatively stable; A strength state determination module, configured to comprehensively determine the structural strength state of the frame after the operation and maintenance operation based on the difference between the acquired first set of structural characteristic parameters and the acquired second set of structural characteristic parameters, and in combination with the preset dynamic characteristic signal monitored during the operation and maintenance operation.

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