Security arrangement decision method and system based on distributed optical fiber

Abstract

The application provides a security and protection layout decision method and system based on distributed optical fibers, relates to the technical field of security and protection, and first extracts common migration rules of multi-source domain distributed optical fiber security and protection layout to generate a source domain migration rule set, then collects target pre-security and protection area characteristic data, combines the source domain migration rule set to generate an initial target domain layout scheme; inputs the initial target domain layout scheme into a simulation system to generate simulated sensing and migration adaptation deviation data; corrects rule set parameters according to the simulated sensing and migration adaptation deviation data; optimizes the initial scheme based on the corrected rule set, and determines a final layout decision scheme through multi-round verification. The application can fully utilize multi-source domain experience, quickly generate a layout scheme adapted to a target area, and improve security and protection sensing effect.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of security and defense technology, in particular to a security and defense layout decision method and system based on distributed optical fiber. BACKGROUND

[0002] In the field of security and defense, distributed optical fiber sensing technology is widely used in security and defense layout of various regions due to its advantages of long distance, high sensitivity, and anti-electromagnetic interference. However, the geographical environment, interference factors, and security and defense needs of different regions differ significantly, which brings great challenges to the reasonable layout of distributed optical fiber.

[0003] At present, existing distributed optical fiber security and defense layout methods are mostly designed based on a single region or a specific scene. These methods often lack comprehensive utilization of multi-source domain experience, and when facing a new target pre-security region, a large amount of field research and testing needs to be conducted, consuming a large amount of manpower, material resources, and time cost. For example, in the security and defense layout of some mountainous and urban areas, due to different terrains and interference sources, directly applying the layout scheme of other regions may result in poor optical fiber sensing effect and inability to accurately perceive potential security threats. Moreover, existing methods lack effective simulation verification and dynamic adjustment mechanisms in the process of developing layout schemes, making it difficult to ensure the optimality of the layout scheme and unable to meet complex and changing security and defense needs. SUMMARY

[0004] In view of the above-mentioned problems, in combination with the first aspect of the present application, the embodiments of the present application provide a security and defense layout decision method based on distributed optical fiber, which comprises:

[0005] Extracting commonality transfer rules of multi-source domain distributed optical fiber security and defense layout, the commonality transfer rules including the association relationship between interference characteristics and layout parameters, generating a source domain transfer rule set;

[0006] Collecting feature data of a target pre-security region, combining the source domain transfer rule set for scene adaptation adjustment, generating an initial target domain layout scheme, the feature data of the target pre-security region including interference feature data, terrain feature data, and security and defense demand data;

[0007] Inputting the initial target domain layout scheme into a distributed optical fiber transfer effect simulation system to generate simulated perception data and transfer adaptation deviation data;

[0008] According to the transfer adaptation deviation data, correcting the association relationship parameters in the source domain transfer rule set to generate a corrected source domain transfer rule set;

[0009] Optimizing the initial target domain layout scheme based on the corrected source domain transfer rule set, and determining a final distributed optical fiber security and defense layout decision scheme through multiple rounds of transfer effect verification.

[0010] In still another aspect, the embodiments of the present application also provide a security arrangement decision system based on distributed optical fiber, comprising:

[0011] a processor; a machine readable storage medium for storing machine executable instructions of the processor; wherein the processor is configured to execute the above-mentioned security arrangement decision method based on distributed optical fiber by executing the machine executable instructions.

[0012] In still another aspect, the embodiments of the present application also provide a computer program product, the computer program product comprising machine executable instructions stored in a computer readable storage medium, a processor of a computer device reading the machine executable instructions from the computer readable storage medium, the processor executing the machine executable instructions, so that the computer device executes the above-mentioned security arrangement decision method based on distributed optical fiber.

[0013] Based on the above aspects, by extracting the common migration rules of multi-source domain distributed optical fiber security arrangement, generating a source domain migration rule set, then collecting the feature data of the target pre-security area and combining the source domain migration rule set to generate an initial target domain arrangement scheme, inputting the initial target domain arrangement scheme into the distributed optical fiber migration effect simulation system, generating simulated perception data and migration adaptation deviation data, correcting the correlation parameters in the source domain migration rule set according to the migration adaptation deviation data, generating the corrected source domain migration rule set, realizing the dynamic updating and optimization of the rule set, so that it can better adapt to the characteristics of different areas. Based on the corrected rule set, the initial target domain arrangement scheme is optimized, and the final distributed optical fiber security arrangement decision scheme is determined through multiple rounds of migration effect verification, ensuring the scientificity and optimality of the arrangement scheme, which can effectively improve the security perception effect of distributed optical fiber in the target area. BRIEF DESCRIPTION OF DRAWINGS

[0014] Figure 1 is the execution flow diagram of the security arrangement decision method based on distributed optical fiber provided by the embodiments of the present application.

[0015] Figure 2 is the schematic diagram of exemplary hardware and software components of the security arrangement decision system based on distributed optical fiber provided by the embodiments of the present application. DETAILED DESCRIPTION

[0016] The present application will be described in detail below with reference to the accompanying drawings of the specification, Figure 1 is the flow diagram of the security arrangement decision method based on distributed optical fiber provided by an embodiment of the present application, which will be described in detail below.

[0017] Step S110: Extract the common migration rule of multi-source domain distributed optical fiber security layout, the common migration rule includes the association relationship between the interference characteristics and the layout parameters, and generate the source domain migration rule set.

[0018] In this embodiment, a certain large-scale comprehensive industrial park is taken as the target pre-security area, which covers industrial production area, warehouse area, office area and surrounding perimeter, and there are complex interference environment and diversified security needs. In order to generate a distributed optical fiber security layout decision scheme suitable for this area, it is necessary to extract the common migration rule from the multi-source domain first. The multi-source domain specifically includes industrial park source domain, civil park source domain and border line source domain. These source domains have accumulated a large amount of historical data in the long-term distributed optical fiber security layout process, including interference characteristic parameters, layout parameters and corresponding perception effect verification data in different scenarios. Through analysis and mining of the above data, the stable association relationship between the interference characteristics and the layout parameters, i.e. the common migration rule, can be found, and then the source domain migration rule set is formed.

[0019] Step S111: Call the historical data of distributed optical fiber security layout of multi-source domain, the multi-source domain includes industrial park source domain, civil park source domain and border line source domain, and the historical data of each source domain includes interference characteristic parameters, layout parameters and perception effect verification data.

[0020] In the process of extracting the common migration rule, the historical data of multi-source domain is called first. For the industrial park source domain, the interference characteristic parameters in the historical data mainly come from the vibration generated by various production equipment in operation and the electromagnetic interference generated by industrial electromagnetic equipment, the layout parameters involve the node spacing setting of optical fiber in the park and the anti-interference configuration for industrial electromagnetic environment, and the perception effect verification data is the perception ability evaluation result of different interference obtained by long-term monitoring. The historical data of civil park source domain, the interference characteristic parameters are mainly related to the vibration generated by personnel activities and the electromagnetic signals generated by communication equipment in the park, the layout parameters include the density arrangement of optical fiber branches and the corresponding signal processing parameters, and the perception effect verification data reflects the monitoring effect of events such as intrusion in the personnel-intensive environment. The historical data of border line source domain, the interference characteristic parameters mainly come from the vibration generated by natural environment such as wind and rain and environmental factors such as extreme temperature and humidity, the layout parameters involve the laying depth of optical fiber and the protection measures of nodes, and the perception effect verification data reflects the stability and reliability of optical fiber security system in complex natural environment. By calling the historical data of the above three source domains, the data foundation is laid for subsequent extraction of association relationship.

[0021] Step S112: Extract the correlation between the interference characteristic parameters and the layout parameters from the industrial plant source domain historical data. The interference characteristic parameters of the industrial plant source domain include equipment operation vibration parameters and industrial electromagnetic parameters. The layout parameters include optical fiber node spacing parameters and anti-interference configuration parameters. The corresponding relationship between the equipment operation vibration parameters and the optical fiber node spacing parameters is established, and the corresponding relationship between the industrial electromagnetic parameters and the anti-interference configuration parameters is established.

[0022] In the industrial plant source domain historical data, the equipment operation vibration parameter is an important interference characteristic parameter. For example, a large machine tool will produce vibration of a certain frequency and amplitude when it is running. These vibrations will propagate along the ground and affect the sensing signal of the optical fiber. Through analysis of historical data, it is found that when the frequency of the equipment operation vibration is high and the amplitude is large, in order to accurately capture these vibration signals and distinguish normal vibration from abnormal intrusion vibration, the optical fiber node spacing parameter needs to be reduced. Because smaller node spacing can improve the spatial resolution of vibration signals and avoid attenuation or distortion of vibration signals in the propagation process due to excessive node spacing. Thus, the corresponding relationship between the equipment operation vibration parameters and the optical fiber node spacing parameters is established, that is, the frequency and amplitude values of the equipment operation vibration are associated with the specific values of the optical fiber node spacing. The higher the frequency and the greater the amplitude, the smaller the node spacing. At the same time, there are a large number of industrial electromagnetic equipment in the industrial plant, such as frequency converters and motors, which will produce strong industrial electromagnetic parameter interference and affect the transmission quality of the optical fiber signal. In order to resist the above electromagnetic interference, corresponding anti-interference parameters need to be configured, such as using optical fiber cables with electromagnetic shielding function, setting filter circuits, etc. By analyzing the relationship between the strength, frequency, etc. of the industrial electromagnetic parameters and the anti-interference configuration parameters, when the strength of the industrial electromagnetic parameters is greater and the frequency is closer to the frequency of the optical fiber signal, the level of the anti-interference configuration parameters needs to be higher, such as increasing the thickness of the shielding layer, improving the filtering accuracy of the filter, etc., thereby establishing the corresponding relationship between the industrial electromagnetic parameters and the anti-interference configuration parameters.

[0023] Step S113: Extract the correlation between the interference characteristic parameters and the layout parameters from the civil garden source domain historical data. The interference characteristic parameters of the civil garden source domain include personnel activity vibration parameters and communication electromagnetic parameters. The layout parameters include optical fiber branch density parameters and signal processing parameters. The corresponding relationship between the personnel activity vibration parameters and the optical fiber branch density parameters is established, and the corresponding relationship between the communication electromagnetic parameters and the signal processing parameters is established.

[0024] In the source domain of a civilian park, personnel activities are one of the main sources of interference. Personnel walking, running, and other activities can generate personnel activity vibration parameters. The intensity of personnel activities varies in different areas. For example, in areas such as main roads and squares in the park, personnel activities are frequent, and vibration signals are complex. In areas such as green belts and remote corners, personnel activities are less frequent, and vibration signals are relatively simple. In order to effectively monitor personnel activities, the fiber branch density parameter needs to be adjusted according to the personnel activity vibration parameters. In areas with high personnel activity, in order to improve the ability to capture weak vibration signals and positioning accuracy, the fiber branch density parameter needs to be increased, i.e. more fiber branches are laid out, so that each branch covers a smaller area, thereby more accurately sensing the location and behavior of personnel activities. Conversely, in areas with less personnel activity, the fiber branch density parameter can be appropriately reduced to reduce costs and reduce data processing volume. Through analysis of historical data of the source domain of the civilian park, a corresponding relationship between personnel activity vibration parameters (such as frequency range, amplitude variation, duration, etc.) and fiber branch density parameters (such as the number of fiber branches per unit area) is established. In addition, there are a large number of communication equipment in the civilian park, such as mobile phone base stations, Wi-Fi routers, etc. These devices will generate communication electromagnetic parameter interference. The strength, frequency, and other characteristics of the communication electromagnetic parameters will affect the transmission of the fiber signal, causing an increase in signal noise. In order to improve the quality of the fiber signal, the signal needs to be processed, so a corresponding relationship between the communication electromagnetic parameters and the signal processing parameters needs to be established. For example, when the strength of the communication electromagnetic parameter is large, more complex signal filtering algorithms, higher signal amplification factors, and other signal processing parameters need to be used to enhance the useful signal and suppress noise.

[0025] Step S114: Extract the association relationship between the interference feature parameters and the layout parameters from the historical data of the border line source domain. The interference feature parameters of the border line source domain include natural environment vibration parameters and extreme environment parameters. The layout parameters include fiber laying depth parameters and node protection parameters. The corresponding relationship between the natural environment vibration parameters and the fiber laying depth parameters is established, and the corresponding relationship between the extreme environment parameters and the node protection parameters is established.

[0026] The environment of the border line source domain is relatively harsh, and the natural environment vibration parameters are important interference characteristics. For example, strong wind, earthquake and other natural phenomena will produce relatively large vibration. If the above vibration signal is too strong, it may cause the optical fiber to break or the sensing signal to be distorted. In order to reduce the influence of natural environment vibration on the optical fiber, it is necessary to reasonably set the optical fiber laying depth parameter. Through the analysis of the historical data of the border line source domain, it is known that the greater the strength of the natural environment vibration parameter, the deeper the optical fiber needs to be laid. Because the deeper laying depth can utilize the attenuation effect of soil, rock and other media on vibration, the influence of vibration on the optical fiber is reduced. For example, in the area where strong wind often occurs, the surface vibration is large, and the optical fiber laying depth parameter needs to be set larger; while in the relatively stable area, the optical fiber laying depth parameter can be appropriately reduced. Thus, the corresponding relationship between the natural environment vibration parameters (such as the maximum acceleration of vibration, vibration frequency, etc.) and the optical fiber laying depth parameter is established. At the same time, the border line source domain also has extreme environment parameters, such as extreme high temperature, low temperature, high humidity, strong ultraviolet, etc. These extreme environments will cause damage to the optical fiber nodes and affect the normal work of the nodes. Therefore, corresponding node protection parameters need to be set, such as using high-temperature-resistant, low-temperature-resistant, waterproof, and ultraviolet-resistant node shell materials, increasing the sealing performance of the node, etc. Through the analysis of the specific indicators of the extreme environment parameters (such as temperature range, humidity size, ultraviolet intensity, etc.) and the relationship between the node protection parameters, when the severity of the extreme environment parameters is higher, the level of the node protection parameters needs to be higher, thereby establishing the corresponding relationship between the extreme environment parameters and the node protection parameters.

[0027] Step S115: comparing the correlation relationships of various source domains, identifying the common correlation logic of the device operation vibration parameters, the personnel activity vibration parameters, the natural environment vibration parameters and the corresponding laying parameters, which is linearly corresponding to the vibration frequency parameters and the laying parameter adjustment amplitude.

[0028] Step S1151: extracting the feature dimensions of the device operation vibration parameters from the correlation relationship of the industrial plant source domain, the feature dimensions including the vibration frequency interval, the vibration duration, the vibration propagation speed, and extracting the adjustment dimensions of the corresponding optical fiber node spacing parameters, the adjustment dimensions including the spacing reduction amplitude, the spacing expansion amplitude and the spacing maintenance amplitude.

[0029] Step S1152: extracting the feature dimensions of the personnel activity vibration parameters from the correlation relationship of the civil park source domain, the feature dimensions including the vibration frequency interval, the vibration duration, the vibration propagation speed, and extracting the adjustment dimensions of the corresponding optical fiber branch density parameters, the adjustment dimensions including the density increase amplitude, the density decrease amplitude and the density maintenance amplitude.

[0030] Step S1153, extract the characteristic dimensions of the natural environment vibration parameters from the association relationship of the border line source domain, the characteristic dimensions include vibration frequency interval, vibration duration, vibration propagation speed, extract the adjustment dimensions corresponding to the fiber laying depth parameter, the adjustment dimensions include depth increase amplitude, depth decrease amplitude, and depth maintenance amplitude.

[0031] Step S1154, align the characteristic dimensions of the vibration parameters in each source domain, so that the characteristic dimension names of the equipment operation vibration parameters, the personnel activity vibration parameters, and the natural environment vibration parameters are consistent with the division standard.

[0032] Step S1155, classify the adjustment dimensions of the laying parameters in each source domain into three types of adjustment types: adjustment positively correlated with vibration frequency, adjustment positively correlated with vibration duration, and adjustment negatively correlated with vibration propagation speed.

[0033] Step S1156, count the occurrence frequency of each type of adjustment type in the association relationship of each source domain, if a type of adjustment type appears in each source domain and the occurrence frequency accounts for more than half, the type of adjustment type is taken as a candidate common adjustment type.

[0034] Step S1157, analyze the corresponding relationship between the candidate common adjustment type and the vibration parameter characteristic dimensions, for the adjustment type positively correlated with the vibration frequency, verify whether the adjustment amplitude of the laying parameter increases with the increase of the vibration frequency in each source domain. For the adjustment type positively correlated with the vibration duration, verify whether the adjustment amplitude of the laying parameter increases with the extension of the vibration duration in each source domain. For the adjustment type negatively correlated with the vibration propagation speed, verify whether the adjustment amplitude of the laying parameter decreases with the acceleration of the vibration propagation speed in each source domain.

[0035] Step S1158, if the verification results of whether the adjustment amplitude of the laying parameter increases with the increase of the vibration frequency in each source domain, whether the adjustment amplitude of the laying parameter increases with the extension of the vibration duration in each source domain, and whether the adjustment amplitude of the laying parameter decreases with the acceleration of the vibration propagation speed in each source domain are all correct, then the candidate common adjustment type is associated with the corresponding vibration parameter characteristic dimensions to form the common association logic of the vibration parameters and the laying parameters.

[0036] Step S1159, integrate all effective common association logics to form a common association logic set of the equipment operation vibration parameters, the personnel activity vibration parameters, the natural environment vibration parameters, and the corresponding laying parameters.

[0037] Step S116: identify the common association logic of industrial electromagnetic parameters, communication electromagnetic parameters, and corresponding laying parameters, which is expressed as the stepwise correspondence between electromagnetic intensity parameters and laying parameter protection levels.

[0038] Industrial electromagnetic parameters and communication electromagnetic parameters belong to electromagnetic interference characteristic parameters. The association relationship between them and corresponding layout parameters is analyzed to find out the common association logic. In the industrial plant source domain, the strength of industrial electromagnetic parameters is different, and the protection level of corresponding anti-interference configuration parameters is also different. When the strength of industrial electromagnetic parameters is low, the basic anti-interference protection level can meet the demand. With the increase of electromagnetic strength, the protection level of anti-interference configuration parameters needs to be improved gradually, from the basic level to the intermediate level, and then to the high level. In the civil park source domain, the strength change of communication electromagnetic parameters also leads to the ladder adjustment of signal processing parameter protection level. When the strength of communication electromagnetic parameters is weak, the signal processing parameter adopts the conventional protection level. When the electromagnetic strength is enhanced to a certain degree, the protection level of signal processing parameter is improved by one step, and higher filtering and amplification processing is adopted. When the electromagnetic strength is further increased, the protection level is improved again. Through comparison, it can be found that the common association logic of industrial electromagnetic parameters and communication electromagnetic parameters and corresponding layout parameters is that the electromagnetic strength parameter and the protection level of layout parameter are corresponding by steps, that is, when the electromagnetic strength parameter reaches a certain threshold, the protection level of layout parameter is improved by one step, so as to ensure that the optical fiber system can work stably in different electromagnetic strength environment.

[0039] Step S117: identifying the common association logic of extreme environment parameters and other source domain environment parameters, which is that the interval corresponding of environment change amplitude parameter and layout parameter adaptation range.

[0040] Extreme environmental parameters come from the border line source domain, while other source domains such as industrial plants and civil gardens also have certain environmental parameter changes, such as daily fluctuations in temperature and humidity. By analyzing the correlation between extreme environmental parameters and border line source domain layout parameters (node protection parameters), as well as the relationship between environmental parameter changes in industrial plants and civil gardens and the corresponding layout parameters, common correlation logic can be identified. In the border line source domain, the change range of extreme environmental parameters is relatively large, such as temperature may rise or fall sharply in a short time, and humidity may also fluctuate greatly, so the node protection parameters need to have a wide range of adaptation to cope with the above large changes. In industrial plants, the temperature and humidity of some production workshops also have relatively large fluctuations, and the adaptation range of the corresponding layout parameters (such as fiber node protection measures) also needs to be adjusted according to the environmental change range. Although the environment in civil gardens is relatively stable, there are still seasonal environmental changes, and the layout parameters also need to be adjusted within a certain adaptation range. In summary, there is an interval corresponding relationship between the environmental change range parameter and the adaptation range of the layout parameter, that is, when the environmental change range parameter is within a certain interval, the adaptation range of the layout parameter is set to the corresponding interval to ensure that the fiber system can operate normally under this environmental change range. When the environmental change range parameter exceeds this interval, the adaptation range of the layout parameter also needs to be adjusted to a larger interval.

[0041] Step S118: classify and integrate all common correlation logics according to interference types, common correlation logics of vibration interference type are classified into vibration rule subset, common correlation logics of electromagnetic interference type are classified into electromagnetic rule subset, and common correlation logics of environmental interference type are classified into environmental rule subset.

[0042] After identifying the common correlation logics of various interference characteristic parameters and layout parameters, they need to be classified and integrated according to the interference types. Vibration interference types include equipment operation vibration, personnel activity vibration and natural environment vibration, and their common correlation logic is the linear correspondence between vibration frequency parameter and layout parameter adjustment range, which is classified into vibration rule subset. Electromagnetic interference types include industrial electromagnetic and communication electromagnetic, and their common correlation logic is the step correspondence between electromagnetic intensity parameter and layout parameter protection level, which is classified into electromagnetic rule subset. Environmental interference types mainly involve extreme environmental parameters and environmental parameter changes in other source domains, and their common correlation logic is the interval correspondence between environmental change range parameter and layout parameter adaptation range, which is classified into environmental rule subset. Through the above classification and integration, the source domain migration rules are more clear and orderly, which facilitates the subsequent quick matching of corresponding rule subsets according to different types of interference characteristic data in the target domain.

[0043] Step S119: add applicable scenario identification to each rule subset, vibration rule subset is labeled with vibration interference scenario, electromagnetic rule subset is labeled with electromagnetic interference scenario, and environmental rule subset is labeled with environmental interference scenario.

[0044] In order to make the classified integrated rule subsets accurately applied to different scenes, the applicable scene identification needs to be added for each rule subset. The vibration rule subset is mainly applicable to the scene with vibration interference, and is therefore marked as a vibration interference scene. When the target pre-security area has vibration interference, the rule subset can be preferentially applied. The electromagnetic rule subset is applicable to the scene with electromagnetic interference, and is therefore marked as an electromagnetic interference scene. When the target domain has electromagnetic interference problems, the rule subset can be called to determine the layout parameters. The environment rule subset is marked as an environmental interference scene, and is used to guide the formulation of the layout scheme for coping with environmental change interference in the target domain. After adding the applicable scene identification, the application scene of the rule subset is more clear, which can improve the efficiency and accuracy of subsequent scene adaptation adjustment.

[0045] Step S1110: The classified and integrated rule subsets are associated and stored with the applicable scene identification to form a structured data set containing the interference type field, the layout parameter field, the associated logic field and the scene identification field, which is used as the source domain migration rule set.

[0046] After completing the classification and integration of the rule subsets and adding the applicable scene identification, they need to be associated and stored. Each entry of the structured data set contains the interference type field, the layout parameter field, the associated logic field and the scene identification field. The interference type field clearly indicates the interference type corresponding to the rule subset, such as vibration interference, electromagnetic interference or environmental interference; the layout parameter field records the specific layout parameters, such as the optical fiber node spacing parameter, the anti-interference configuration parameter, etc.; the associated logic field describes the association relationship between the interference characteristic parameters and the layout parameters, such as linear correspondence, step correspondence, interval correspondence, etc.; and the scene identification field marks the applicable scene. Through the above structured storage method, the source domain migration rule set is formed.

[0047] Step S120: Collecting the characteristic data of the target pre-security area, combining the source domain migration rule set for scene adaptation adjustment, and generating an initial target domain layout scheme, wherein the characteristic data of the target pre-security area includes the interference characteristic data, the terrain characteristic data and the security demand data.

[0048] After obtaining the source domain migration rule set, the feature data of the target pre-security area (a large comprehensive industrial park) needs to be collected. The feature data of the target pre-security area includes interference feature data, terrain feature data, and security requirement data, which are the basis for generating the initial target domain layout scheme. The interference feature data reflects the situation of various interferences in the industrial park, the terrain feature data describes the topographic features of the park, and the security requirement data clearly defines the functional requirements of the distributed optical fiber security system. After the collection is completed, the above feature data is adjusted for scene adaptation in combination with the source domain migration rule set, that is, the correlation in the source domain migration rule set is adjusted and optimized according to the actual situation of the target domain, so that it can be better applied to the target pre-security area, and finally the initial target domain layout scheme is generated.

[0049] Step S121: retrieve the interference feature data of the target pre-security area, the interference feature data including vibration interference feature data, electromagnetic interference feature data, and environmental interference feature data, the vibration interference feature data including vibration frequency distribution data and vibration propagation range data, the electromagnetic interference feature data including electromagnetic intensity distribution data and electromagnetic wave period data, and the environmental interference feature data including temperature variation period data, humidity distribution data, and vegetation coverage density data.

[0050] For the target pre-prevention area (a large-scale comprehensive industrial park), the retrieval of interference characteristic data is the primary step of scene adaptation adjustment. In terms of vibration interference characteristic data, there are various vibration sources in the park, such as vibration generated by the operation of mechanical equipment in production workshops, vibration generated by the driving of transport vehicles, and vibration generated by personnel activities, etc. Through long-term monitoring and data collection, vibration frequency distribution data is obtained, which reflects the vibration frequency situation of different areas and different time periods in the park. For example, the vibration frequency of the production workshop area is mainly concentrated in the medium-high frequency band, while the vibration frequency of the park trunk road covers the medium-low frequency band. The vibration propagation range data shows the propagation distance and influence range of vibration generated by different vibration sources in the park. The vibration propagation range of large equipment is relatively wide, while the vibration propagation range of personnel activities is relatively small. Electromagnetic interference characteristic data, industrial electromagnetic equipment (such as motors, transformers) and communication equipment (such as communication base stations, Wi-Fi hotspots) in the park will produce electromagnetic interference. Electromagnetic intensity distribution data records the electromagnetic intensity at different positions in the park. The electromagnetic intensity in the production area is significantly higher than that in the office and residential areas. Electromagnetic fluctuation period data reflects the law of electromagnetic intensity change with time. For example, the electromagnetic interference of some equipment has periodic fluctuations, while the electromagnetic interference of communication equipment may fluctuate with the change of usage. Environmental interference characteristic data, the temperature change period data of the park presents the change law of day cycle and year cycle. The temperature is higher in the daytime and lower at night, higher in summer and lower in winter. The humidity distribution data shows the humidity difference in different areas of the park. For example, the humidity is higher near the water source, while the humidity is lower in the dry production workshop. The vegetation coverage density data reflects the vegetation distribution of the green area in the park. The area with high vegetation coverage density may have a certain attenuation effect on the propagation of vibration.

[0051] Step S122: Retrieve the topographic feature data of the target pre-prevention area, which includes slope distribution data, ground material distribution data, and obstacle position distribution data in the area. The slope distribution data includes slope change trend data of different areas, the ground material distribution data includes soil type distribution data and rock distribution data, and the obstacle position distribution data includes building position data and natural obstacle position data.

[0052] The terrain feature data is crucial for the planning of the distributed optical fiber laying path and the selection of the laying method. In terms of slope distribution data, through the measurement and analysis of the terrain of the park, the slope change trend data of different areas is obtained. There may be flat areas (such as the location of the production workshop), gentle slope areas (such as the green belt), and steep slope areas (such as the natural terrain at the edge of the park) in the park. The slope change trend of different areas will affect the laying difficulty and stability of the optical fiber. Special fixing measures are needed in areas with large slopes. The ground material distribution data shows that the ground material in the park is diverse. The soil type distribution data shows the soil types in different areas of the park, such as clay areas and sandy soil areas. The bearing capacity and protection of the optical fiber are different for different soil types. The rock distribution data indicates the location and distribution range of the rock outcrops in the park. Different construction methods are needed for laying optical fiber in rock areas. The obstacle position distribution data includes the specific location and outline of all buildings (such as production workshops, office buildings, warehouses, etc.) in the park. These buildings are the main obstacles for optical fiber laying. The natural obstacle position data includes the location of lakes, rivers, and large trees in the park. These obstacles need to be avoided or appropriate crossing measures need to be taken when planning the optical fiber path.

[0053] Step S123: retrieve the security demand data of the target pre-security area, the security demand data including perimeter intrusion monitoring demand data, specified monitoring area guard demand data, and global coverage demand data. The perimeter intrusion monitoring demand data includes boundary length data and intrusion response time data. The specified monitoring area guard demand data includes specified monitoring area quantity data and monitoring accuracy data. The global coverage demand data includes coverage area data and perception continuity data.

[0054] The security demand data specifies the functions and performance indicators that the distributed optical fiber security system needs to achieve. The perimeter intrusion monitoring demand data requires the entire perimeter of the industrial park to be monitored comprehensively to prevent illegal intrusion, as the boundary length data of the industrial park is relatively long. The intrusion response time data requires the system to issue an alarm and provide intrusion location information within a specified time after detecting an intrusion, so that security personnel can respond promptly. The specified monitoring area guard demand data indicates that multiple key areas in the park need to be monitored, such as the key equipment area of the production workshop and the storage area of the warehouse. The specified monitoring area quantity data indicates the number of these key areas. The monitoring accuracy data requires the system to accurately identify abnormal behavior in the specified monitoring area, such as illegal entry of personnel and abnormal movement of equipment, with positioning accuracy meeting certain standards. The global coverage demand data requires the optical fiber system to cover every corner of the park, as the coverage area data of the park is relatively large. The perception continuity data requires the system to continuously monitor at any time without blind spots or interruptions, ensuring comprehensive and continuous protection of the park.

[0055] Step S124: Extract all rule subsets from the source domain migration rule set, match the interference feature data of the target pre-security area with the interference type field of each rule subset, filter out the rule subsets consistent with the target domain interference type, and form the target adaptive rule subset.

[0056] After obtaining the interference feature data of the target pre-security area, all rule subsets need to be extracted from the source domain migration rule set, including vibration rule subsets, electromagnetic rule subsets and environmental rule subsets. Then, the interference feature data of the target pre-security area (vibration interference feature data, electromagnetic interference feature data, environmental interference feature data) is matched with the interference type field of each rule subset. The interference type field of the vibration rule subset is vibration interference, which is matched with the vibration interference feature data of the target domain; the interference type field of the electromagnetic rule subset is electromagnetic interference, which is matched with the electromagnetic interference feature data of the target domain; the interference type field of the environmental rule subset is environmental interference, which is matched with the environmental interference feature data of the target domain. Through the above matching process, all rule subsets consistent with the target domain interference type are filtered out, and these rule subsets together constitute the target adaptive rule subset, which will be the main basis for subsequent scene adaptation adjustment.

[0057] Step S125: Analyze the similarity of the scene identification field of the target adaptive rule subset and the scene feature of the target pre-security area, and the scene feature includes interference type proportion, terrain type proportion, and security demand type proportion. Calculate the scene similarity value of each target adaptive rule subset and the target domain.

[0058] The target adaptation rule subset matches the target domain in terms of interference type, but different rule subsets come from different source domains, and the scene represented by the scene identification field of the rule subset may be different from the actual scene of the target pre-prevention area. Therefore, it is necessary to analyze the similarity between the scene identification field and the scene characteristics of the target domain. The scene characteristics of the target domain include the proportion of interference types, the proportion of terrain types, and the proportion of security demand types. The proportion of interference types refers to the proportion of vibration interference, electromagnetic interference, and environmental interference in the total interference of the target domain. The proportion of terrain types refers to the proportion of flat terrain, slope terrain, and rock terrain in the terrain of the target domain. The proportion of security demand types refers to the proportion of perimeter intrusion monitoring demand, designated monitoring area guard demand, and global coverage demand in the total security demand. For each target adaptation rule subset (vibration rule subset, electromagnetic rule subset, and environmental rule subset), the scene identification field also implies the scene characteristics of the corresponding source domain. By comparing the scene characteristics of the target domain with the scene characteristics represented by the scene identification field of each rule subset, the similarity between them, i.e., the scene similarity value, is calculated. For example, the vibration rule subset comes from industrial plant, civil garden, and border line source domains, and the interference type proportion, terrain type proportion, and security demand type proportion in the scene characteristics corresponding to the scene identification field are compared with the actual scene characteristics of the target domain. Through certain algorithms (such as cosine similarity algorithm, Euclidean distance algorithm, etc.), the similarity value is calculated. The greater the similarity value, the more similar the scene of the rule subset to the scene of the target domain.

[0059] Step S1251: Extract the scene characteristic parameters in the scene identification field of the target adaptation rule subset. The scene characteristic parameters of the vibration rule subset include the proportion of vibration interference types, vibration interference intensity range, and vibration interference duration period. The scene characteristic parameters of the electromagnetic rule subset include the proportion of electromagnetic interference types, electromagnetic interference intensity range, and electromagnetic interference duration period. The scene characteristic parameters of the environmental rule subset include the proportion of environmental interference types, environmental interference intensity range, and environmental interference duration period.

[0060] When calculating the scene similarity value, first, the specific scene feature parameters need to be extracted from the scene identification field of the target adaptation rule subset. For the vibration rule subset, the scene identification field is marked as a vibration interference scene, and the extracted scene feature parameters include the vibration interference type proportion, i.e., the proportion of vibration interference in the total interference in the source domain from which the rule subset comes; the vibration interference intensity range, i.e., the maximum and minimum range of vibration interference intensity in the source domain; the vibration interference duration period, i.e., the time law of vibration interference occurring continuously in the source domain, such as continuous existence during the day, intermittent occurrence, etc. The scene identification field of the electromagnetic rule subset is an electromagnetic interference scene, and the extracted scene feature parameters include the electromagnetic interference type proportion, i.e., the proportion of electromagnetic interference in the total interference in the source domain; the electromagnetic interference intensity range, i.e., the variation interval of electromagnetic interference intensity in the source domain; the electromagnetic interference duration period, i.e., the time distribution law of electromagnetic interference in the source domain. The scene identification field of the environmental rule subset is an environmental interference scene, and the extracted scene feature parameters include the environmental interference type proportion, i.e., the proportion of environmental interference in the total interference in the source domain; the environmental interference intensity range, i.e., the range of environmental interference (such as temperature and humidity variation amplitude) in the source domain; the environmental interference duration period, i.e., the duration time law of environmental interference in the source domain.

[0061] Step S1252: Extracting scene feature parameters in the target pre-protection region scene feature, the scene feature parameters including an interference type proportion, an interference intensity range, and an interference duration period, wherein the interference type proportion is respectively counted according to vibration interference, electromagnetic interference, and environmental interference, the interference intensity range is respectively divided according to different intensity levels, and the interference duration period is respectively divided according to different duration periods.

[0062] Meanwhile, scene feature parameters in the target pre-protection region scene feature need to be extracted. The interference type proportion is respectively counted according to three types of vibration interference, electromagnetic interference, and environmental interference, and the percentage of each type of interference in the total interference in the target domain is calculated. The interference intensity range is divided according to the preset intensity level, for example, the vibration interference intensity can be divided into three levels of low, medium, and high, and the electromagnetic interference intensity and the environmental interference intensity also adopt similar level division methods to clearly define the intensity range level of each type of interference in the target domain. The interference duration period is divided into different types according to the time law of interference occurrence in the target domain, such as continuous duration type (interference exists for 24 hours a day), intermittent duration type (interference periodically appears in a specific time period), random duration type (interference occurs at an unfixed time), etc., and the duration period type of each type of interference is counted.

[0063] Step S1253: Normalizing each scene characteristic parameter, converting the interference type proportion into a dimensionless percentage value, converting the interference intensity range into a dimensionless relative value based on a preset intensity benchmark, and converting the interference duration period into a dimensionless relative value based on a preset period benchmark.

[0064] In order to make the different scene characteristic parameters comparable, the extracted target adaptation rule subset and the scene characteristic parameters of the target pre-prevention area need to be normalized. For the interference type proportion, it is proportional data itself and can be directly converted into a dimensionless percentage value. For example, the vibration interference type proportion of a certain rule subset is sixty percent, and the vibration interference type proportion of the target domain is fifty percent. For the interference intensity range, it is converted into a dimensionless relative value based on a preset intensity benchmark. The preset intensity benchmark is a standard value of each type of interference intensity determined according to multi-source domain data. The actual interference intensity range is compared with the preset intensity benchmark to obtain a relative value. For example, the vibration interference intensity range of the target domain is one point two times the preset intensity benchmark, and the normalized relative value is one point two. For the interference duration period, it is also converted into a dimensionless relative value based on a preset period benchmark. The preset period benchmark is a standard duration time. The actual interference duration period is compared with the preset period benchmark to obtain a relative value. For example, a certain interference duration period is zero point eight times the preset period benchmark, and the normalized relative value is zero point eight.

[0065] Step S1254: Calculating the difference value of the normalized same type scene characteristic parameters of the target adaptation rule subset and the target pre-prevention area. The difference value of the vibration interference type proportion normalized value of the vibration rule subset and the vibration interference type proportion normalized value of the target domain, the difference value of the vibration interference intensity range normalized value and the vibration interference intensity range normalized value of the target domain, and the difference value of the vibration interference duration period normalized value and the vibration interference duration period normalized value of the target domain are calculated.

[0066] After the normalization is completed, the difference value of the same type scene characteristic parameters of the target adaptation rule subset and the target pre-prevention area is calculated. Taking the vibration rule subset as an example, the vibration interference type proportion normalized value of the vibration rule subset is subtracted from the vibration interference type proportion normalized value of the target domain to obtain the difference value of the two in the interference type proportion. Similarly, the difference value of the vibration interference intensity range normalized value of the vibration rule subset and the vibration interference intensity range normalized value of the target domain, and the difference value of the vibration interference duration period normalized value and the vibration interference duration period normalized value of the target domain are calculated. For the electromagnetic rule subset and the environmental rule subset, the normalized difference values of the corresponding same type scene characteristic parameters (electromagnetic interference type proportion, electromagnetic interference intensity range, electromagnetic interference duration period; environmental interference type proportion, environmental interference intensity range, environmental interference duration period) of the target domain are also calculated.

[0067] Step S1255: Assign a preset weight to each scene feature parameter.

[0068] Since different scene feature parameters have different influences on the scene similarity, a preset weight needs to be assigned to each scene feature parameter. The preset weight is determined according to domain knowledge and experience. For example, the interference type proportion is relatively important in scene matching, and a higher weight is assigned; the importance of the interference duration period is relatively low, and a lower weight is assigned. For the vibration rule subset, the vibration interference type proportion, the vibration interference intensity range, and the vibration interference duration period are respectively assigned corresponding preset weights; the scene feature parameters of the electromagnetic rule subset and the environment rule subset are also assigned preset weights.

[0069] Step S1256: Multiply the difference value of each scene feature parameter by the corresponding weight to obtain the weighted difference value of each scene feature parameter.

[0070] After obtaining the difference value and the preset weight of each scene feature parameter, the difference value of each scene feature parameter is multiplied by the corresponding weight to calculate the weighted difference value of each scene feature parameter. For example, the vibration interference type proportion difference value of the vibration rule subset is 5%, and the preset weight is 0.4, so the weighted difference value of this parameter is 5% multiplied by 0.4; the vibration interference intensity range difference value is 0.2, the preset weight is 0.3, and the weighted difference value is 0.2 multiplied by 0.3; the vibration interference duration period difference value is 0.1, the preset weight is 0.3, and the weighted difference value is 0.1 multiplied by 0.3.

[0071] Step S1257: Sum the weighted difference values of all scene feature parameters to obtain the total difference value of the target adaptation rule subset and the target domain.

[0072] The weighted difference values of all scene feature parameters of the target adaptation rule subset are summed to obtain the total difference value of the rule subset and the target pre-prevention area scene feature. The total difference value reflects the overall difference degree between the rule subset scene and the target domain scene. The smaller the total difference value, the higher the similarity between the two.

[0073] Step S1258: Calculate the scene similarity value according to the total difference value. The closer the total difference value is to 0, the closer the scene similarity value is to 1, and the closer the total difference value is to 1, the closer the scene similarity value is to 0; output the effective scene similarity value of each target adaptation rule subset and the target domain.

[0074] The total difference value is used to calculate the scene similarity value, and the value range of the total difference value is set to be between 0 and 1. When the total difference value is 0, it means that the rule subset scene is completely consistent with the target domain scene, and the scene similarity value is 1. When the total difference value is 1, the difference between the two is the largest, and the scene similarity value is 0. The total difference value is converted into the scene similarity value through a certain function relationship (such as the scene similarity value being equal to 1 minus the total difference value). After the calculation is completed, the effective scene similarity value of each target adaptation rule subset (vibration rule subset, electromagnetic rule subset, and environment rule subset) and the target domain is output. These values will be used for subsequent allocation of adaptation weights.

[0075] Step S126: Assign adaptation weights to each target adaptation rule subset according to the scene similarity value. The scene similarity value and the adaptation weight ratio are positively correlated, and the adaptation weight is allocated according to the preset correlation between the scene similarity value and the adaptation weight ratio.

[0076] After obtaining the scene similarity value of each target adaptation rule subset and the target domain, adaptation weights are assigned to them according to the scene similarity value. Since the scene similarity value and the adaptation weight ratio are positively correlated, that is, the higher the scene similarity value of a rule subset, the greater the role it should play in the target domain adaptation, and therefore a higher adaptation weight ratio is allocated. The preset correlation can be a linear relationship, for example, the adaptation weight ratio is equal to the scene similarity value divided by the sum of the scene similarity values of all target adaptation rule subsets. Assuming that the scene similarity value of the vibration rule subset is 0.8, the scene similarity value of the electromagnetic rule subset is 0.7, and the scene similarity value of the environment rule subset is 0.6, the sum of the three is 2.1, then the adaptation weight ratio of the vibration rule subset is 0.8 divided by 2.1, the adaptation weight ratio of the electromagnetic rule subset is 0.7 divided by 2.1, and the adaptation weight ratio of the environment rule subset is 0.6 divided by 2.1, thereby obtaining the adaptation weight of each rule subset.

[0077] Step S127: Adjust the associated logic parameters of the target adaptation rule subset based on the adaptation weight. For the vibration rule subset, the corresponding relationship of the optical fiber node spacing parameter is corrected according to the difference between the target domain vibration frequency distribution data and the source domain vibration frequency parameter, combined with the adaptation weight. For the electromagnetic rule subset, the corresponding relationship of the anti-interference configuration parameter is corrected according to the difference between the target domain electromagnetic intensity distribution data and the source domain electromagnetic intensity parameter, combined with the adaptation weight. For the environment rule subset, the corresponding relationship of the optical fiber laying depth parameter is corrected according to the difference between the target domain temperature change period data and the source domain environment parameter, combined with the adaptation weight.

[0078] After the adaptive weight is assigned, the associated logic parameters of the target adaptive rule subset are adjusted based on the adaptive weight. For the vibration rule subset, the associated logic parameters are the linear correspondence relationship between the vibration frequency parameter and the fiber node spacing parameter. The vibration frequency distribution data of the target domain and the vibration frequency parameter of the source domain are different, for example, the average vibration frequency of the target domain is higher than that of the source domain. According to the above difference, and combined with the adaptive weight of the vibration rule subset, the corresponding relationship of the fiber node spacing parameter is corrected. The higher the adaptive weight, the closer the rule subset to the target domain scene, and the correction amplitude is relatively small; the lower the adaptive weight, the greater the correction amplitude needs to be corrected according to the difference, so that the corrected fiber node spacing parameter correspondence is more in line with the vibration frequency distribution of the target domain. For the electromagnetic rule subset, the associated logic parameters are the stepwise correspondence relationship between the electromagnetic intensity parameter and the anti-interference configuration parameter. Compare the electromagnetic intensity distribution data of the target domain with the electromagnetic intensity parameter of the source domain, and find the difference points, such as the electromagnetic intensity of some areas of the target domain exceeds the range of the electromagnetic intensity parameter of the source domain. Combined with the adaptive weight of the electromagnetic rule subset, the corresponding relationship of the anti-interference configuration parameter is corrected, the electromagnetic intensity threshold of each step and the corresponding anti-interference configuration level are adjusted, to ensure that the anti-interference configuration parameter can play an effective role in the electromagnetic environment of the target domain. For the environment rule subset, the associated logic parameters are the interval correspondence relationship between the environmental change amplitude parameter and the fiber laying depth parameter. The temperature change period data of the target domain and the temperature change parameter in the source domain environment parameter are different, such as the temperature change amplitude of the target domain is greater than that of the source domain. According to the above difference and the adaptive weight of the environment rule subset, the corresponding relationship of the fiber laying depth parameter is corrected, the environmental change amplitude interval and the corresponding fiber laying depth interval are adjusted, so that the fiber laying depth can adapt to the temperature change and other environmental interference of the target domain.

[0079] Step S128: combined with the adjusted associated logic parameters and the topographic feature data of the target pre-prevention area, the fiber path direction parameter is optimized to avoid the area corresponding to the obstacle position distribution data in the topographic feature data, and the path is planned along the gentle area in the slope distribution data.

[0080] The adjusted associated logic parameters determine the node spacing of the optical fiber, the anti-interference configuration, the laying depth and the like. On this basis, the optical fiber path parameters are optimized in combination with the terrain feature data of the target pre-security area. The obstacle position distribution data in the terrain feature data clearly indicates the positions of the buildings and natural obstacles in the park. When planning the optical fiber path, the areas corresponding to these obstacles need to be avoided to reduce the construction difficulty and avoid damage to the obstacles. For example, the building position data shows that there is a large production plant in the park, and the optical fiber path should bypass the plant instead of passing through the plant. The lake in the natural obstacle position data also needs to be bypassed when planning the path. At the same time, the gentle area in the slope distribution data is more suitable for the laying of the optical fiber, which can reduce the construction difficulty and cost, and is conducive to the stable operation of the optical fiber and reduces the stretching or damage of the optical fiber due to large slope. Therefore, the optical fiber path parameters should be planned along the gentle area with smaller slope in the slope change trend data, such as along the sides of the roads in the park (the roads are usually gentle) or the flat green belts.

[0081] Step S129: in combination with the adjusted associated logic parameters and the security demand data of the target pre-security area, the optical fiber branch density parameter is optimized, the branch density is increased in the specified monitoring area corresponding to the specified monitoring area value guard demand data, and the branch density is kept uniform in the global coverage area corresponding to the global coverage demand data.

[0082] The specified monitoring area value guard demand data in the security demand data indicates the key monitoring areas in the park. For these specified monitoring areas, in order to meet the demand for monitoring accuracy and response speed, the optical fiber branch density parameter needs to be increased. For example, in the key equipment area of the production workshop, more optical fiber branches need to be laid to make the coverage range of each branch smaller, so that the abnormal conditions of the area can be more accurately monitored. For the global coverage area corresponding to the global coverage demand data, although it also needs to be fully covered, it does not need as high branch density as the specified monitoring area, and the branch density should be kept uniform to control the cost and data processing amount while ensuring the coverage effect. For example, the ordinary roads, green belts and the like of the park are global coverage areas, which are laid according to the uniform branch density to ensure that each position can be sensed by the optical fiber, but the number of branches is relatively small compared with the specified monitoring area.

[0083] Step S1210: integrate the optimized optical fiber node spacing parameter, anti-interference configuration parameter, optical fiber laying depth parameter, optical fiber path parameter and optical fiber branch density parameter to generate an initial target area layout scheme.

[0084] After the optimization and adjustment of various parameters, the optimized fiber node spacing parameters, anti-interference configuration parameters, fiber laying depth parameters, fiber path direction parameters and fiber branch density parameters are integrated. The above parameters are related to each other and influence each other, and together constitute the laying scheme of the distributed optical fiber security system in the target pre-security area. For example, the fiber path direction parameter determines the overall laying route of the fiber, the fiber node spacing parameter and the fiber branch density parameter are used to arrange the nodes and branches on the route, the fiber laying depth parameter determines the laying depth of each position according to the terrain and environmental conditions on the path, and the anti-interference configuration parameter is configured according to the electromagnetic interference on the path. The above parameters are integrated to form an initial target domain laying scheme, which can initially meet the interference environment, terrain conditions and security requirements of the target pre-security area.

[0085] Step S130: input the initial target domain laying scheme into the distributed optical fiber migration effect simulation system to generate simulation sensing data and migration adaptation deviation data.

[0086] After the initial target domain laying scheme is generated, the migration effect needs to be simulated and evaluated. The scheme is input into the distributed optical fiber migration effect simulation system, which can simulate the actual operation of the distributed optical fiber in the target pre-security area. By simulating the optical fiber sensing process under different interference environments, simulation sensing data is generated, which reflects the sensing ability of the optical fiber system under the initial laying scheme. At the same time, the simulation sensing data can also be compared with the sensing performance benchmark data of the target pre-security area to calculate the difference between the two, i.e. migration adaptation deviation data, which can reflect the gap between the initial laying scheme and the actual requirements of the target domain.

[0087] Step S131: construct a distributed optical fiber migration effect simulation system, which includes a scene modeling module, a laying simulation module, a sensing test module and a deviation analysis module.

[0088] The distributed optical fiber migration effect simulation system includes four main modules: a scene modeling module, a layout simulation module, a perception test module, and a deviation analysis module. The function of the scene modeling module is to construct a three-dimensional virtual scene similar to the actual region according to the topographic feature data and interference feature data of the target pre-defense region, which can accurately reflect the topography, distribution of interference sources, and other conditions of the region. The layout simulation module performs virtual layout of the optical fiber in the three-dimensional virtual scene according to the input initial target domain layout scheme, and places the optical fiber model in the virtual scene according to the optical fiber path direction parameters, node spacing parameters, and laying depth parameters in the scheme. The perception test module is used to simulate the influence of the actual interference environment on the optical fiber system after the virtual layout is completed, generate virtual interference signals, and collect the perception data of the optical fiber system under these virtual interference signals. The deviation analysis module is responsible for comparing and analyzing the collected simulation perception data with the preset perception performance benchmark data, and calculating the migration adaptation deviation data.

[0089] Step S132: input the topographic feature data of the target pre-defense region into the scene modeling module, and generate a three-dimensional simulation scene consistent with the actual topography of the target domain, which includes a slope model, a ground material model, and an obstacle model corresponding to the topographic feature data.

[0090] After the simulation system is constructed, the topographic feature data of the target pre-defense region is input into the scene modeling module. The slope distribution data in the topographic feature data is used to generate the slope model of the three-dimensional simulation scene, which accurately presents the slope change of different regions in the park, such as the distribution of flat areas, gentle slope areas, and steep slope areas. The ground material distribution data is used to construct the ground material model, and different soil types and rock distributions are represented by different textures and attributes in the model, such as the ground material of clay area and the ground material of sandy area, which have obvious differences in the model. The obstacle position distribution data is used to create the obstacle model, and the building position data corresponds to generate a three-dimensional building model, whose position, shape, and height are consistent with the actual buildings in the park; the natural obstacle position data generates three-dimensional models of natural obstacles such as lakes and large rocks. Through the construction of the above models, the scene modeling module generates a three-dimensional simulation scene consistent with the actual topography of the target domain.

[0091] Step S133: input the initial target domain layout scheme into the layout simulation module, and perform virtual layout in the three-dimensional simulation scene according to the optical fiber path direction parameters, optical fiber node spacing parameters, and optical fiber laying depth parameters in the initial target domain layout scheme, to generate a virtual layout model.

[0092] After receiving the initial target domain deployment scheme, the deployment simulation module plans the laying route of the optical fiber in the three-dimensional simulation scene according to the optical fiber path direction parameters in the scheme. The laying route is consistent with the path designed in the initial target domain deployment scheme, and obstacles and unsuitable laying areas are avoided. Then, the optical fiber nodes are set on the planned path according to the optical fiber node spacing parameters. The distance between the nodes is strictly arranged according to the parameter requirements to ensure that the node distribution is uniform and meets the sensing requirements. At the same time, the optical fiber model is placed at the corresponding depth below the ground surface of the three-dimensional simulation scene according to the optical fiber laying depth parameters. The laying depth of different areas is adjusted according to the terrain and environmental conditions according to the parameters, such as the laying depth may be shallow in the rock distribution area, and the laying depth is deep in the soil area. Through the above operations, the deployment simulation module completes the virtual deployment of the optical fiber in the three-dimensional simulation scene, and generates a virtual deployment model. The virtual deployment model intuitively shows the deployment situation of the optical fiber in the target pre-defense area.

[0093] Step S134: Load the interference feature data of the target pre-defense area in the virtual deployment model to simulate the actual interference environment. The vibration interference feature data corresponds to generate a virtual vibration signal, the electromagnetic interference feature data corresponds to generate a virtual electromagnetic signal, and the environmental interference feature data corresponds to generate a virtual environmental influence signal.

[0094] After the virtual deployment model is generated, the interference feature data of the target pre-defense area needs to be loaded in it to simulate the actual interference environment. The vibration frequency distribution data and vibration propagation range data in the vibration interference feature data are used to generate a virtual vibration signal. In the three-dimensional simulation scene, according to the position of the vibration source and the vibration propagation range, the optical fiber in the virtual deployment model is subjected to a vibration signal with a corresponding frequency and amplitude, simulating the vibration generated by production equipment operation, personnel activity, etc. The electromagnetic intensity distribution data and electromagnetic wave period data in the electromagnetic interference feature data are used to generate a virtual electromagnetic signal. In the simulation scene, an electromagnetic interference field with corresponding intensity and periodic fluctuation is generated at the corresponding position, acting on the optical fiber model, simulating the electromagnetic interference generated by industrial electromagnetic equipment and communication equipment. The temperature change period data, humidity distribution data and vegetation coverage density data in the environmental interference feature data generate virtual environmental influence signals. These signals will affect the transmission characteristics of the optical fiber, such as temperature change will cause the refractive index of the optical fiber to change, humidity will affect the insulation performance of the optical fiber, and vegetation coverage may attenuate the propagation of the vibration signal. The influence of the actual environment on the optical fiber system is simulated through the above virtual environmental influence signals.

[0095] Step S135: Start the perception test module, collect the perception data of the virtual layout model in the virtual interference environment, the perception data includes vibration signal capture data, electromagnetic interference resistance data, and environment adaptive perception data, the vibration signal capture data includes signal recognition data under different vibration frequencies, the electromagnetic interference resistance data includes signal stability data under different electromagnetic intensities, and the environment adaptive perception data includes perception continuity data under different temperatures and humidities.

[0096] After loading the virtual interference environment, start the perception test module. The perception test module monitors the running condition of the virtual layout model in the virtual interference environment and collects perception data. The collection of vibration signal capture data records the recognition of the virtual vibration signal by the fiber system under different vibration frequencies, i.e., signal recognition data, including whether the existence of the vibration signal, the frequency and amplitude estimation value of the vibration signal can be accurately recognized, etc. The collection of electromagnetic interference resistance data records the transmission of the optical fiber signal under the action of virtual electromagnetic signals with different electromagnetic intensities, i.e., signal stability data, such as bit error rate, signal-to-noise ratio, etc., to evaluate the resistance of the optical fiber system to electromagnetic interference. The collection of environment adaptive perception data monitors the perception continuity of the optical fiber system under the influence of virtual environment signals with different temperatures and humidities, i.e., perception continuity data, such as whether the signal is interrupted, whether the perception sensitivity changes, etc., to judge the adaptability of the optical fiber system to environmental changes.

[0097] Step S136: Organize the collected perception data into simulated perception data, and store the simulated perception data according to the interference type, the perception data corresponding to vibration interference is classified into a vibration perception subset, the perception data corresponding to electromagnetic interference is classified into an electromagnetic perception subset, and the perception data corresponding to environmental interference is classified into an environmental perception subset.

[0098] After the perception test module collects a large amount of perception data, it needs to be organized into simulated perception data. During the organization process, the perception data is classified and stored according to the interference type. The perception data related to vibration interference (vibration signal capture data) is classified into a vibration perception subset, which contains signal recognition results under different vibration frequencies. The perception data related to electromagnetic interference (electromagnetic interference resistance data) is classified into an electromagnetic perception subset, which contains signal stability data under different electromagnetic intensities. The perception data related to environmental interference (environmental adaptive perception data) is classified into an environmental perception subset, which contains perception continuity data under different temperatures and humidities. Through classified storage, the simulated perception data is more organized, which is convenient for subsequent comparison and analysis with the perception performance benchmark data.

[0099] Step S137: retrieve the sensing performance benchmark data of the target pre-security area, the sensing performance benchmark data including vibration signal capture benchmark data, electromagnetic interference resistance benchmark data, and environment adaptive sensing benchmark data, the vibration signal capture benchmark data including minimum recognition standard data at different vibration frequencies, the electromagnetic interference resistance benchmark data including minimum stability standard data at different electromagnetic intensities, and the environment adaptive sensing benchmark data including minimum continuity standard data at different temperature and humidity.

[0100] In order to evaluate the performance of the simulated sensing data, the sensing performance benchmark data of the target pre-security area needs to be retrieved. The sensing performance benchmark data is formulated according to the security requirements of the target domain, and is used to measure the minimum standard of the sensing capability of the optical fiber system. The vibration signal capture benchmark data specifies the minimum recognition standard data that the optical fiber system should achieve for different vibration frequencies, for example, at a certain vibration frequency, the accuracy rate of signal recognition cannot be lower than ninety-five percent, and the recognition delay cannot exceed a certain time. The electromagnetic interference resistance benchmark data sets the minimum standard data of signal stability at different electromagnetic intensities, for example, when the electromagnetic intensity is a certain value, the bit error rate of the signal cannot be higher than one per thousand, and the signal-to-noise ratio cannot be lower than a certain value. The environment adaptive sensing benchmark data specifies the minimum standard data of sensing continuity for different temperature and humidity conditions, for example, in a high temperature and high humidity environment, the sensing interruption time of the optical fiber system cannot exceed one minute, and the sensing sensitivity cannot decrease by more than ten percent.

[0101] Step S138: input the simulated sensing data and the sensing performance benchmark data into the deviation analysis module, calculate the deviation value of the vibration sensing subset and the vibration signal capture benchmark data, which is the difference between the recognition data of each frequency in the vibration sensing subset and the minimum recognition standard data of the corresponding frequency in the benchmark data; calculate the deviation value of the electromagnetic sensing subset and the electromagnetic interference resistance benchmark data, which is the difference between the stability data of each intensity in the electromagnetic sensing subset and the minimum stability standard data of the corresponding intensity in the benchmark data; calculate the deviation value of the environment sensing subset and the environment adaptive sensing benchmark data, which is the difference between the continuity data of each temperature and humidity in the environment sensing subset and the minimum continuity standard data of the corresponding temperature and humidity in the benchmark data.

[0102] After receiving the simulation sensing data and the sensing performance benchmark data, the deviation analysis module starts to calculate the deviation values. For the vibration sensing subset, the signal recognition data corresponding to each vibration frequency is compared with the minimum recognition standard data corresponding to the frequency in the vibration signal capture benchmark data, and the difference between the two is calculated, which is the vibration deviation value. For example, the signal recognition accuracy at a certain frequency is 98%, and the minimum recognition standard data is 95%, so the vibration deviation value is 3%. For the electromagnetic sensing subset, the stability data (such as bit error rate) corresponding to each electromagnetic intensity is compared with the minimum stability standard data (such as the maximum allowed bit error rate) corresponding to the intensity in the electromagnetic interference resistance benchmark data, and the difference is calculated to obtain the electromagnetic deviation value. For example, the bit error rate at a certain electromagnetic intensity is 0.5 per thousand, and the minimum stability standard data is 1 per thousand, so the electromagnetic deviation value is -0.5 per thousand (indicating better than the benchmark). For the environmental sensing subset, the continuity data (such as sensing interruption time) corresponding to each temperature and humidity is compared with the minimum continuity standard data (such as the maximum allowed interruption time) corresponding to the temperature and humidity in the environmental adaptation sensing benchmark data, and the difference is calculated to obtain the environmental deviation value. For example, the sensing interruption time at a certain temperature and humidity is 30 seconds, and the minimum continuity standard data is 1 minute, so the environmental deviation value is -30 seconds.

[0103] Step S139: Integrate the vibration deviation value, the electromagnetic deviation value, and the environmental deviation value to generate migration adaptation deviation data, which contains the interference type identifier, the parameter identifier, and the deviation value corresponding to each deviation value.

[0104] After calculating the vibration deviation value, the electromagnetic deviation value, and the environmental deviation value, the above deviation values are integrated to generate migration adaptation deviation data. In the migration adaptation deviation data, each deviation value is added with the corresponding interference type identifier (such as "vibration interference", "electromagnetic interference", "environmental interference"), parameter identifier (such as "vibration signal capture data", "electromagnetic interference resistance data", "environmental adaptation sensing data"), and specific deviation value. For example, the interference type identifier corresponding to a certain vibration deviation value is "vibration interference", the parameter identifier is "mid-frequency vibration recognition accuracy", and the deviation value is 3%. Through the above integration method, the migration adaptation deviation data can clearly reflect the gap between the initial target domain deployment scheme and the sensing performance benchmark under different interference types and parameters.

[0105] Step S140: According to the migration adaptation deviation data, correct the correlation relationship parameters in the source domain migration rule set to generate a corrected source domain migration rule set.

[0106] The migration adaptation deviation data reflects the deficiencies of the initial target domain deployment scheme, which can be caused by the fact that the correlation parameters in the source domain migration rule set do not completely match the actual situation of the target domain. Therefore, the correlation parameters in the source domain migration rule set need to be corrected according to the migration adaptation deviation data, so as to improve the adaptability of the rule set to the target domain and generate a corrected source domain migration rule set, thereby laying a foundation for optimizing the initial target domain deployment scheme.

[0107] Step S141: Analyze the migration adaptation deviation data, extract the interference type identifier, parameter identifier and deviation value corresponding to each deviation value, the vibration deviation value corresponds to the vibration interference type identifier and the fiber node spacing parameter identifier, the electromagnetic deviation value corresponds to the electromagnetic interference type identifier and the anti-interference configuration parameter identifier, and the environmental deviation value corresponds to the environmental interference type identifier and the fiber laying depth parameter identifier.

[0108] First, the migration adaptation deviation data is analyzed to extract detailed information of each deviation value. For the vibration deviation value, the corresponding interference type identifier is "vibration interference", and the parameter identifier is "fiber node spacing parameter", which indicates that the deviation is caused by improper setting of the fiber node spacing parameter under vibration interference; the electromagnetic deviation value corresponds to the "electromagnetic interference" interference type identifier and the "anti-interference configuration parameter" parameter identifier, which indicates that the anti-interference configuration parameter needs to be adjusted under electromagnetic interference environment; the environmental deviation value corresponds to the "environmental interference" interference type identifier and the "fiber laying depth parameter" parameter identifier, which indicates that there is a problem with the fiber laying depth parameter under environmental interference. At the same time, the specific deviation value of each deviation value is extracted, and the size and sign of these values reflect the degree and direction of the deviation, for example, a positive vibration deviation value indicates that the signal recognition data is higher than the baseline, and a negative electromagnetic deviation value indicates that the signal stability data is lower than the baseline.

[0109] Step S142: Retrieve the correlation parameters corresponding to the interference type identifier and the parameter identifier from the source domain migration rule set, the node spacing correlation parameters in the vibration rule subset corresponding to the vibration interference type identifier and the fiber node spacing parameter identifier, the anti-interference correlation parameters in the electromagnetic rule subset corresponding to the electromagnetic interference type identifier and the anti-interference configuration parameter identifier, and the laying depth correlation parameters in the environmental rule subset corresponding to the environmental interference type identifier and the fiber laying depth parameter identifier.

[0110] According to the interference type identifier and the parameter identifier obtained by analysis, the corresponding correlation parameter is retrieved from the source domain migration rule set. The vibration interference type identifier and the fiber node spacing parameter identifier correspond to the node spacing correlation parameter in the vibration rule subset, which describes the linear correspondence between the vibration frequency parameter and the fiber node spacing parameter. The electromagnetic interference type identifier and the anti-interference configuration parameter identifier correspond to the anti-interference correlation parameter in the electromagnetic rule subset, which specifies the stepwise correspondence between the electromagnetic intensity parameter and the anti-interference configuration parameter protection level. The environmental interference type identifier and the fiber laying depth parameter identifier correspond to the laying depth correlation parameter in the environmental rule subset, which defines the interval correspondence between the environmental change amplitude parameter and the fiber laying depth parameter.

[0111] Step S143: Establish a correction mapping between the deviation value and the correlation parameter. When the vibration deviation value is positive, the adjustment amplitude of the node spacing parameter is reduced; when the vibration deviation value is negative, the adjustment amplitude of the node spacing parameter is increased; when the electromagnetic deviation value is positive, the protection level of the anti-interference configuration parameter is improved; when the electromagnetic deviation value is negative, the protection level of the anti-interference configuration parameter is reduced; when the environmental deviation value is positive, the adjustment amplitude of the fiber laying depth parameter is increased; when the environmental deviation value is negative, the adjustment amplitude of the fiber laying depth parameter is reduced.

[0112] According to the positive and negative and size of the deviation value, a correction mapping relationship between the deviation value and the correlation parameter is established. For the vibration deviation value, if it is positive, it means that the current node spacing parameter adjustment amplitude makes the signal recognition data higher than the reference, in order to avoid resource waste or excessive sensitivity, the adjustment amplitude of the node spacing parameter can be appropriately reduced; if the vibration deviation value is negative, it means that the signal recognition data is lower than the reference, and the adjustment amplitude of the node spacing parameter needs to be increased to improve the capture ability of the vibration signal. For the electromagnetic deviation value, a positive value indicates that the signal stability data is better than the reference, at which time the protection level of the anti-interference configuration parameter can be appropriately reduced to reduce the cost; if it is negative, the signal stability data does not reach the reference, and the protection level of the anti-interference configuration parameter needs to be improved to enhance the anti-interference ability. For the environmental deviation value, a positive value means that the perception continuity data is better than the reference, and the adjustment amplitude of the fiber laying depth parameter can be reduced; a negative value indicates that the perception continuity data is insufficient, and the adjustment amplitude of the fiber laying depth parameter needs to be increased to improve the environmental adaptability.

[0113] Step S144: Adjust the corresponding correlation parameters according to the revised mapping result. For the node spacing correlation parameters in the vibration rule subset, adjust the linear correspondence between the vibration frequency parameter and the node spacing parameter according to the absolute value proportion of the vibration deviation value. For example, if the absolute value of the vibration deviation value is large, it means that the current correspondence deviates greatly from the target domain, so the adjustment proportion is increased accordingly, so that the amplitude of the change of the node spacing parameter with the vibration frequency is more in line with the requirements of the target domain. For the anti-interference correlation parameters in the electromagnetic rule subset, adjust the stepwise correspondence between the electromagnetic intensity parameter and the anti-interference configuration parameter protection level according to the absolute value proportion of the electromagnetic deviation value. The larger the absolute value of the deviation, the greater the adjustment amplitude of the protection level, so as to ensure that the anti-interference configuration parameter can achieve the expected effect under different electromagnetic intensities. For the laying depth correlation parameters in the environmental rule subset, adjust the interval correspondence between the environmental change amplitude parameter and the laying depth parameter according to the absolute value proportion of the environmental deviation value. The larger the absolute value of the deviation, the greater the adjustment amplitude of the laying depth parameter, so that the optical fiber laying depth better adapts to environmental changes.

[0114] According to the revised mapping result, the corresponding correlation parameters are adjusted. For the node spacing correlation parameters in the vibration rule subset, the linear correspondence between the vibration frequency parameter and the node spacing parameter is adjusted according to the absolute value proportion of the vibration deviation value. For example, if the absolute value of the vibration deviation value is large, it means that the current correspondence deviates greatly from the target domain, so the adjustment proportion is increased accordingly, so that the amplitude of the change of the node spacing parameter with the vibration frequency is more in line with the requirements of the target domain. For the anti-interference correlation parameters in the electromagnetic rule subset, adjust the stepwise correspondence between the electromagnetic intensity parameter and the anti-interference configuration parameter protection level according to the absolute value proportion of the electromagnetic deviation value. The larger the absolute value of the deviation, the greater the adjustment amplitude of the protection level, so as to ensure that the anti-interference configuration parameter can achieve the expected effect under different electromagnetic intensities. For the laying depth correlation parameters in the environmental rule subset, adjust the interval correspondence between the environmental change amplitude parameter and the laying depth parameter according to the absolute value proportion of the environmental deviation value. The larger the absolute value of the deviation, the greater the adjustment amplitude of the laying depth parameter, so that the optical fiber laying depth better adapts to environmental changes.

[0115] Step S145: Integrate the adjusted vibration rule subset, electromagnetic rule subset and environmental rule subset to form a revised source domain migration rule set. The revised source domain migration rule set retains the original scene identification field and adds a revision identification field to mark the revision time and revision basis of each parameter.

[0116] After adjusting the correlation parameters of each rule subset, the adjusted vibration rule subset, electromagnetic rule subset and environmental rule subset are integrated to form a revised source domain migration rule set. In this rule set, the original scene identification field is retained to clearly indicate the applicable scene of the rule for subsequent use. At the same time, a revision identification field is added for each parameter, which marks the revision time (such as the specific revision date and time) and revision basis (i.e. which migration adaptation deviation data is used for revision) of each correlation parameter. By adding the revision identification field, the revision history of the rule set can be traced and managed, facilitating further optimization and maintenance of the rule set.

[0117] Step S150: Optimize the initial target domain layout scheme based on the revised source domain migration rule set, and determine the final distributed optical fiber security layout decision scheme through multiple rounds of migration effect verification.

[0118] The modified source domain migration rule set has higher adaptability and accuracy, and the initial target domain layout scheme is optimized based on the rule set. By applying the modified correlation parameter to the layout scheme, adjusting various layout parameters, and then performing migration effect simulation again, new migration adaptation deviation data is generated. Through multiple rounds of the above optimization and simulation verification process, the source domain migration rule set is continuously modified and the layout scheme is continuously optimized until the migration adaptation deviation data meets the preset requirements, and finally the distributed optical fiber security layout decision scheme most suitable for the target pre-security area is determined.

[0119] Step S151: input the modified source domain migration rule set into the target domain adaptation module, re-extract the rule subset matched with the target pre-security area interference feature data, and generate an optimized adaptation rule subset.

[0120] The modified source domain migration rule set is input into the target domain adaptation module, which re-extracts the rule subset matched with the target pre-security area interference feature data from the modified rule set according to a similar process as before. Since the source domain migration rule set has been modified, its correlation parameters are closer to the actual situation of the target domain, so the re-extracted rule subset (optimized adaptation rule subset) has a higher matching degree with the target domain, which can better guide the optimization of the layout scheme.

[0121] Step S152: adjust the parameters in the initial target domain layout scheme based on the optimized adaptation rule subset, adjust the optical fiber node spacing parameter according to the modified node spacing correlation parameter, adjust the anti-interference configuration parameter according to the modified anti-interference correlation parameter, and adjust the optical fiber laying depth parameter according to the modified laying depth correlation parameter.

[0122] The optimized adaptation rule subset includes the modified node spacing correlation parameter, anti-interference correlation parameter, and laying depth correlation parameter. According to the above modified correlation parameters, the corresponding parameters in the initial target domain layout scheme are adjusted. According to the modified node spacing correlation parameter, the optical fiber node spacing parameter is re-determined so that the node spacing can more accurately correspond to the vibration frequency distribution of the target domain; according to the modified anti-interference correlation parameter, the protection level of the anti-interference configuration parameter is adjusted to better resist electromagnetic interference in the target domain; and according to the modified laying depth correlation parameter, the optical fiber laying depth parameter is adjusted to improve the adaptability of the optical fiber system to environmental changes.

[0123] Step S153: combine the topographic feature data and security demand data of the target pre-security area to optimize the optical fiber path direction parameter and the optical fiber branch density parameter again, the path direction parameter avoids the area where the modified laying depth parameter is not adapted, and the branch density parameter is re-distributed according to the modified node spacing parameter.

[0124] After the parameter adjustment, the path direction parameters and the fiber branch density parameters are re-optimized in combination with the terrain feature data and the security requirement data of the target pre-security area. For the path direction parameters, in addition to avoiding the areas corresponding to the original obstacle position distribution data, the areas where the corrected laying depth parameters are not suitable are also needed to be avoided, for example, due to geological conditions, some areas cannot reach the depth required by the corrected laying depth parameters, at this time, the path direction needs to be adjusted to bypass these areas. For the fiber branch density parameters, according to the corrected node spacing parameters, the node spacing is re-distributed, the node spacing is smaller, the corresponding branch density needs to be increased to ensure effective coverage and monitoring under smaller node spacing; the node spacing is larger, the branch density can be appropriately reduced.

[0125] Step S154: input the adjusted target domain layout scheme into the distributed optical fiber migration effect simulation system, repeat the simulation of the perception data acquisition and the migration adaptation deviation data calculation process, and generate the second round of migration adaptation deviation data.

[0126] After completing the parameter adjustment and re-optimization, the adjusted target domain layout scheme is input into the distributed optical fiber migration effect simulation system, and the previous simulation of the perception data acquisition (loading interference feature data, starting the perception test module to collect perception data) and the migration adaptation deviation data calculation (comparing with the perception performance benchmark data to calculate the deviation value) process is repeated, and the second round of migration adaptation deviation data is generated. The second round of migration adaptation deviation data is used to evaluate whether the performance of the optimized layout scheme has improved.

[0127] Step S155: compare the deviation value changes of the second round of migration adaptation deviation data and the first round of migration adaptation deviation data, if all the deviation values are reduced and within the preset deviation range, it means that the current adjusted target domain layout scheme has met the migration adaptation requirements; if there are deviation values that are not reduced or exceed the preset deviation range, the associated relationship parameters in the source domain migration rule set need to be corrected again according to the second round of migration adaptation deviation data, and the initial target domain layout scheme is re-optimized.

[0128] The change in the deviation values in the second round of migration adaptation deviation data and the first round of migration adaptation deviation data is compared. If all the deviation values in the second round are reduced compared to the first round, and are within the preset deviation range (which is an acceptable deviation interval set according to the security requirements of the target domain and the performance indicators of the fiber system), it means that the adjusted target domain layout scheme has met the migration adaptation requirements and does not need further optimization. If there are deviation values that have not been reduced, or even increased, or some deviation values are still outside the preset deviation range, it means that the layout scheme still needs to be improved, and the associated relationship parameters in the source domain migration rule set need to be corrected again according to the second round of migration adaptation deviation data, and then the process of optimizing the initial target domain layout scheme is repeated, i.e. re-extracting the rule subset, adjusting the parameters, optimizing the path and branch density, and performing simulation verification, etc.

[0129] Step S156: Repeat the steps of optimizing the initial target domain layout scheme based on the corrected source domain migration rule set and inputting the optimized target domain layout scheme into the distributed fiber migration effect simulation system to generate simulated perception data and migration adaptation deviation data until all the deviation values in the latest generated migration adaptation deviation data are within the preset deviation range, and obtain the multi-round optimized target domain layout scheme.

[0130] According to the above optimization and simulation process, repeat for multiple rounds. In each round, the source domain migration rule set is corrected according to the migration adaptation deviation data of the previous round, the target domain layout scheme is optimized, and simulation verification is performed. After multiple iterations, when all the deviation values in the generated migration adaptation deviation data are within the preset deviation range, the iteration is stopped, and the multi-round optimized target domain layout scheme is obtained. This target domain layout scheme achieves good results in interference adaptation, terrain matching, and security requirement satisfaction, etc.

[0131] Step S157: Finally match the multi-round optimized target domain layout scheme with the security requirement data of the target pre-security area, and confirm that the fiber branch density parameters in the multi-round optimized target domain layout scheme meet the specified monitoring area value requirement, the fiber path direction parameters meet the perimeter intrusion monitoring requirement, and the fiber coverage range meets the global coverage requirement.

[0132] The target domain layout scheme after multiple rounds of optimization needs to be finally matched with the security demand data of the target pre-security area to ensure that the scheme fully meets all security demands. First, confirm whether the optical fiber branch density parameter meets the specified monitoring area value demand, check whether the optical fiber branch density can achieve accurate monitoring and rapid response to key areas within the specified monitoring area. Second, confirm whether the optical fiber path parameter meets the perimeter intrusion monitoring demand, check whether the optical fiber path is laid along the perimeter of the park and can effectively monitor the intrusion behavior of the boundary, and whether the response timeliness meets the requirements. Finally, confirm whether the optical fiber coverage range meets the global coverage demand, check whether the optical fiber system covers all areas of the park and whether the sensing is continuous and has blind areas.

[0133] For example, step S1571: extract the optical fiber branch density parameter in the target domain layout scheme after multiple rounds of optimization, which includes the number of branches, branch spacing, and branch coverage radius of each sub-region within the specified monitoring area.

[0134] When confirming whether the optical fiber branch density parameter meets the specified monitoring area value demand, first extract the optical fiber branch density parameter in the target domain layout scheme after multiple rounds of optimization. This optical fiber branch density parameter is refined for the specified monitoring area and includes the number of branches, branch spacing, and branch coverage radius of each sub-region (such as different sections of a production workshop or different storage areas of a warehouse) within the specified monitoring area. The number of branches refers to the total number of optical fiber branches laid in each sub-region; the branch spacing refers to the distance between two adjacent optical fiber branches; and the branch coverage radius refers to the radius of the circular area that each optical fiber branch can effectively sense signals.

[0135] Step S1572: extract the quantitative indicators in the specified monitoring area value demand data of the target pre-security area, which include the number of monitoring points required, monitoring coverage density requirement, and monitoring response speed requirement for each sub-region within the specified monitoring area.

[0136] At the same time, extract the quantitative indicators in the specified monitoring area value demand data of the target pre-security area. For each sub-region within the specified monitoring area, the quantitative indicators include the number of monitoring points required (the total number of monitoring points needed to be set in the sub-region), the monitoring coverage density requirement (the number of monitoring points per unit area), and the monitoring response speed requirement (the maximum allowed time for the monitoring signal to be transmitted to the control terminal from the occurrence).

[0137] Step S1573: Calculate the coverage area of each sub-region in the specified monitoring area, which is calculated by the number of branches and the coverage area of each branch, and the coverage area of each branch is determined based on the branch coverage radius; compare the calculated coverage area with the monitoring coverage density requirement of the sub-region, and when the coverage area can cover all monitoring points in the sub-region, it is determined that the branch density meets the requirement in the coverage dimension.

[0138] Calculate the coverage area of each sub-region in the specified monitoring area, which is calculated by the number of branches and the coverage area of each branch, and the coverage area of each branch is determined based on the branch coverage radius (such as the area of a circle equal to the square of the branch coverage radius multiplied by the constant pi), and then the number of branches in the sub-region is multiplied by the coverage area of each branch to obtain the total coverage area of the sub-region. Compare the calculated total coverage area with the monitoring coverage density requirement of the sub-region, and when the total coverage area can cover all monitoring points in the sub-region and the coverage area per unit area reaches the monitoring coverage density requirement, it is determined that the fiber branch density parameter meets the requirement in the coverage dimension.

[0139] Step S1574: Calculate the matching degree of the fiber branch spacing and the monitoring point spacing in each sub-region in the specified monitoring area, and when the branch spacing value is equal to the monitoring point spacing value, it is determined that the branch density meets the requirement in the monitoring accuracy dimension.

[0140] Calculate the matching degree of the fiber branch spacing and the monitoring point spacing in each sub-region in the specified monitoring area, and the monitoring point spacing is the distance between each monitoring point calculated according to the number of monitoring points and the area of the sub-region. When the fiber branch spacing value is equal to the monitoring point spacing value, it means that the distribution of the fiber branches completely matches the distribution of the monitoring points, which can ensure that each monitoring point is within the effective monitoring range of the fiber branches, and at this time it is determined that the branch density meets the requirement in the monitoring accuracy dimension.

[0141] Step S1575: Analyze the corresponding relationship between the number of fiber branches in each sub-region in the specified monitoring area and the monitoring response speed requirement, and when the time for monitoring signal transmission to the control terminal is equal to the required time, it is determined that the branch density meets the requirement in the response speed dimension.

[0142] Analyze the corresponding relationship between the number of fiber branches in each sub-region in the specified monitoring area and the monitoring response speed requirement, and the more the number of fiber branches, the shorter the signal transmission path and the less the time for transmission to the control terminal. By analyzing the topology structure and signal transmission characteristics of the fiber network, it is determined that the time for monitoring signal transmission from any position in the sub-region to the control terminal is equal to the time required for monitoring response speed. When the time is equal to the time required for monitoring response speed, it is determined that the branch density meets the requirement in the response speed dimension.

[0143] Step S1576: The matching results of all sub-regions in the specified monitoring region are summarized. If all sub-regions meet the requirements in the coverage dimension, the monitoring accuracy dimension, and the response speed dimension, it means that the fiber branch density parameter meets the specified monitoring region value guard requirement. If there is a sub-region that does not meet the requirement of any one dimension, the fiber branch density parameter of the sub-region needs to be adjusted, the number of branches needs to be increased or the branch spacing needs to be reduced. After re-adjustment, the coverage area, matching degree, and response speed are calculated again until the sub-region meets all dimension requirements. Repeat the above adjustment and verification process until all sub-regions in the specified monitoring region meet the specified monitoring region value guard requirement, and complete the final matching of the fiber branch density parameter and the specified monitoring region value guard requirement.

[0144] The matching results of all sub-regions in the specified monitoring region in the coverage dimension, the monitoring accuracy dimension, and the response speed dimension are summarized. If all sub-regions meet the requirements in these three dimensions, it means that the fiber branch density parameter meets the specified monitoring region value guard requirement. If there is a sub-region that does not meet the requirement of any one dimension, such as insufficient coverage area or too slow response speed, the fiber branch density parameter of the sub-region needs to be adjusted, such as increasing the number of branches or reducing the branch spacing. After re-adjustment, the coverage area, matching degree of branch spacing and monitoring point spacing, and monitoring response speed of the sub-region are calculated again until the sub-region meets all dimension requirements. Repeat the above adjustment and verification process for each sub-region that does not meet the requirement until all sub-regions in the specified monitoring region meet the specified monitoring region value guard requirement, and complete the final matching of the fiber branch density parameter and the specified monitoring region value guard requirement.

[0145] Step S158: Confirm that the layout parameters in the target domain layout scheme after multiple rounds of optimization do not conflict with the terrain feature data, the fiber laying depth parameter adapts to the ground material data, and the fiber node position avoids the area corresponding to the obstacle position data.

[0146] After confirming that the security requirements are met, it is also necessary to confirm that the layout parameters in the target domain layout scheme after multiple rounds of optimization do not conflict with the terrain feature data. Check whether the fiber laying depth parameter is adapted to the ground material data, such as whether the fiber laying depth parameter is set shallow in the rock distribution area to avoid laying; whether the laying depth is appropriate in the soil area to ensure the stability of the fiber. At the same time, confirm whether the fiber node position avoids the area corresponding to the obstacle position data, such as buildings, natural obstacles, etc., to ensure that the node layout will not be affected by the obstacles, and to facilitate maintenance and management.

[0147] Step S159: integrating all confirmation results to generate a final distributed optical fiber security layout decision scheme, the final distributed optical fiber security layout decision scheme including the finally determined optical fiber node spacing parameter, anti-interference configuration parameter, optical fiber laying depth parameter, optical fiber path direction parameter and optical fiber branch density parameter.

[0148] After all the confirmation steps are completed, the confirmation results are integrated to generate a final distributed optical fiber security layout decision scheme. The distributed optical fiber security layout decision scheme includes the finally determined optical fiber node spacing parameter, anti-interference configuration parameter, optical fiber laying depth parameter, optical fiber path direction parameter and optical fiber branch density parameter. The above parameters are optimized and verified for multiple rounds, and can adapt to the interference environment, terrain conditions and security requirements of the target pre-security area.

[0149] Based on the same inventive concept, please refer to Figure 2 , which shows a structure schematic block diagram of a distributed optical fiber security layout decision system 100 provided by the embodiment of the present application for executing the above-mentioned distributed optical fiber security layout decision method. The distributed optical fiber security layout decision system 100 can include a communication unit 110, a machine readable storage medium 120 and a processor 130.

[0150] In the embodiment, the machine readable storage medium 120 and the processor 130 are both located in the distributed optical fiber security layout decision system 100 and are separately arranged. Alternatively, the machine readable storage medium 120 can also be integrated into the processor 130, and can communicate and interact with external systems through the communication unit 110. The machine readable storage medium 120 is used to store machine executable instructions for executing the scheme of the present application, and the processor 130 is used to execute the machine executable instructions stored in the machine readable storage medium 120 to realize the distributed optical fiber security layout decision method provided by the above-mentioned method embodiment.

[0151] It should be noted that, in order to simplify the description of the present application and help understand one or more embodiments of the present application, in the foregoing description of the embodiments of the present application, various features are sometimes combined into one embodiment, figure or description thereof.

Claims

1. A security deployment decision-making method based on distributed optical fiber, characterized in that, The method includes: Common migration rules for multi-source domain distributed optical fiber security deployment are extracted. These common migration rules include the correlation between interference features and deployment parameters, and a source domain migration rule set is generated. Collect feature data of the target pre-security area, combine it with the source domain migration rule set to perform scene adaptation adjustment, and generate an initial target domain deployment scheme. The feature data of the target pre-security area includes interference feature data, terrain feature data and security requirement data. The initial target domain deployment scheme is input into the distributed fiber optic migration effect simulation system to generate simulated sensing data and migration adaptation deviation data. The correlation parameters in the source domain migration rule set are corrected based on the migration adaptation deviation data to generate the corrected source domain migration rule set. The initial target domain deployment scheme is optimized based on the modified source domain migration rule set, and the final distributed fiber optic security deployment decision scheme is determined through multiple rounds of migration effect verification.

2. The security deployment decision-making method based on distributed optical fiber according to claim 1, characterized in that, The common migration rules for extracting multi-source domain distributed fiber optic security deployments include: Historical data on distributed fiber optic security deployment in multiple source domains are retrieved. These multiple source domains include industrial plant source domains, civilian park source domains, and border source domains. The historical data for each source domain includes interference characteristic parameters, deployment parameters, and sensing effect verification data. The correlation between interference characteristic parameters and deployment parameters is extracted from historical data of the source domain of industrial plants. The interference characteristic parameters of the source domain of industrial plants include equipment operating vibration parameters and industrial electromagnetic parameters. The deployment parameters include fiber optic node spacing parameters and anti-interference configuration parameters. The correspondence between equipment operating vibration parameters and fiber optic node spacing parameters, and the correspondence between industrial electromagnetic parameters and anti-interference configuration parameters are established. The correlation between interference characteristic parameters and deployment parameters is extracted from historical data of the source domain of civilian parks. The interference characteristic parameters of the source domain of civilian parks include personnel activity vibration parameters and communication electromagnetic parameters. The deployment parameters include fiber optic branch density parameters and signal processing parameters. The correspondence between personnel activity vibration parameters and fiber optic branch density parameters, and the correspondence between communication electromagnetic parameters and signal processing parameters are established. The correlation between interference characteristic parameters and deployment parameters is extracted from historical data of the border source domain. The interference characteristic parameters of the border source domain include natural environmental vibration parameters and extreme environmental parameters. The deployment parameters include optical fiber laying depth parameters and node protection parameters. The correspondence between natural environmental vibration parameters and optical fiber laying depth parameters, and the correspondence between extreme environmental parameters and node protection parameters are established. By comparing the correlations of various source domains, the common correlation logic between equipment operation vibration parameters, personnel activity vibration parameters, natural environment vibration parameters and corresponding deployment parameters is identified. This common correlation logic is manifested as a linear correspondence between vibration frequency parameters and the adjustment range of deployment parameters. Identify the common correlation logic between industrial electromagnetic parameters, communication electromagnetic parameters and corresponding deployment parameters. This common correlation logic is manifested as a stepwise correspondence between electromagnetic strength parameters and the protection level of deployment parameters. Identify the common correlation logic between extreme environmental parameters and other source domain environmental parameters. This common correlation logic is manifested as the interval correspondence between the environmental change amplitude parameter and the adaptation range of the deployment parameter. All common related logics are categorized and integrated according to interference type. Common related logics for vibration interference type are grouped into vibration rule subset, common related logics for electromagnetic interference type are grouped into electromagnetic rule subset, and common related logics for environmental interference type are grouped into environmental rule subset. Add applicable scenario identifiers to each rule subset: the vibration rule subset is labeled with vibration interference scenarios, the electromagnetic rule subset is labeled with electromagnetic interference scenarios, and the environmental rule subset is labeled with environmental interference scenarios. The categorized and integrated rule subset is associated with the applicable scenario identifier and stored to form a structured data set containing interference type field, deployment parameter field, association logic field, and scenario identifier field, which serves as the source domain migration rule set.

3. The security deployment decision-making method based on distributed optical fiber according to claim 1, characterized in that, The feature data of the collected target pre-security area is combined with the source domain migration rule set for scene adaptation adjustment to generate an initial target domain deployment scheme, including: Retrieve interference characteristic data of the target pre-security area. The interference characteristic data includes vibration interference characteristic data, electromagnetic interference characteristic data, and environmental interference characteristic data within the area. The vibration interference characteristic data includes vibration frequency distribution data and vibration propagation range data. The electromagnetic interference characteristic data includes electromagnetic intensity distribution data and electromagnetic wave period data. The environmental interference characteristic data includes temperature change period data, humidity distribution data, and vegetation cover density data. Retrieve terrain feature data of the target pre-security area. The terrain feature data includes slope distribution data, surface material distribution data, and obstacle location distribution data within the area. The slope distribution data includes slope change trend data for different areas. The surface material distribution data includes soil type distribution data and rock distribution data. The obstacle location distribution data includes building location data and natural obstacle location data. Retrieve security requirement data for the target pre-security area. The security requirement data includes perimeter intrusion monitoring requirement data, designated monitoring area duty requirement data, and full-area coverage requirement data. The perimeter intrusion monitoring requirement data includes boundary length data and intrusion response time data. The designated monitoring area duty requirement data includes the number of designated monitoring areas and monitoring accuracy data. The full-area coverage requirement data includes coverage area data and perception continuity data. Extract all rule subsets from the source domain migration rule set, match the interference feature data of the target pre-security area with the interference type field of each rule subset, and filter out the rule subsets that are consistent with the interference type of the target domain to form the target adaptation rule subset; Analyze the similarity between the scene identifier field of the target adaptation rule subset and the scene features of the target pre-security area. The scene features include the proportion of interference type, terrain type, and security requirement type. Calculate the scene similarity value between each target adaptation rule subset and the target domain. Adaptation weights are assigned to each subset of target adaptation rules based on scene similarity values. Scene similarity values ​​and the proportion of adaptation weights are positively correlated. Adaptation weights are assigned according to a preset correlation between scene similarity values ​​and the proportion of adaptation weights. Based on the adaptation weight, the associated logical parameters of the target adaptation rule subset are adjusted. For the vibration rule subset, the correspondence between the fiber node spacing parameters is corrected according to the difference between the vibration frequency distribution data of the target domain and the vibration frequency parameters of the source domain, combined with the adaptation weight. For the electromagnetic rule subset, the correspondence between the anti-interference configuration parameters is corrected according to the difference between the electromagnetic intensity distribution data of the target domain and the electromagnetic intensity parameters of the source domain, combined with the adaptation weight. For the environmental rule subset, the correspondence between the fiber laying depth parameters is corrected according to the difference between the temperature change period data of the target domain and the environmental parameters of the source domain, combined with the adaptation weight. By combining the adjusted correlation logic parameters with the terrain feature data of the target pre-security area, the fiber optic path routing parameters are optimized to avoid the areas corresponding to the obstacle location distribution data in the terrain feature data and to plan the path along the gentle areas in the slope distribution data. By combining the adjusted correlation logic parameters with the security requirements data of the target pre-security area, the fiber optic branch density parameters are optimized. The branch density is increased in the designated monitoring area corresponding to the monitoring area duty requirements data, and the branch density is kept uniform in the full coverage area corresponding to the full coverage requirements data. By integrating and optimizing the fiber node spacing parameters, anti-interference configuration parameters, fiber laying depth parameters, fiber path orientation parameters, and fiber branch density parameters, an initial target domain deployment scheme is generated.

4. The security deployment decision-making method based on distributed optical fiber according to claim 1, characterized in that, The process of inputting the initial target domain deployment scheme into the distributed fiber optic migration effect simulation system to generate simulated sensing data and migration adaptation deviation data includes: A distributed optical fiber migration effect simulation system is constructed, which includes a scene modeling module, a deployment simulation module, a perception testing module, and a deviation analysis module. The terrain feature data of the target pre-security area is input into the scene modeling module to generate a three-dimensional simulation scene that is consistent with the actual terrain of the target domain. The three-dimensional simulation scene includes a slope model, surface material model, and obstacle model corresponding to the terrain feature data. Input the initial target domain layout plan into the layout simulation module, and perform virtual layout in the three-dimensional simulation scene according to the fiber path direction parameters, fiber node spacing parameters, and fiber laying depth parameters in the initial target domain layout plan to generate a virtual layout model. In the virtual deployment model, the interference characteristic data of the target pre-security area is loaded to simulate the actual interference environment. The vibration interference characteristic data corresponds to the generation of virtual vibration signals, the electromagnetic interference characteristic data corresponds to the generation of virtual electromagnetic signals, and the environmental interference characteristic data corresponds to the generation of virtual environmental impact signals. The perception test module is activated to collect perception data of the virtual deployment model in a virtual interference environment. The perception data includes vibration signal capture data, electromagnetic interference resistance data, and environmental adaptation perception data. The vibration signal capture data includes signal identification data at different vibration frequencies, electromagnetic interference resistance data includes signal stability data at different electromagnetic intensities, and environmental adaptation perception data includes perception continuity data at different temperatures and humidity levels. The collected sensing data is organized into simulated sensing data. The simulated sensing data is stored according to the type of interference. The sensing data corresponding to vibration interference is classified into the vibration sensing subset, the sensing data corresponding to electromagnetic interference is classified into the electromagnetic sensing subset, and the sensing data corresponding to environmental interference is classified into the environmental sensing subset. Retrieve the perception performance benchmark data of the target pre-security area. The perception performance benchmark data includes vibration signal capture benchmark data, electromagnetic interference resistance benchmark data, and environmental adaptation perception benchmark data. The vibration signal capture benchmark data includes the minimum identification standard data under different vibration frequencies. The electromagnetic interference resistance benchmark data includes the minimum stability standard data under different electromagnetic intensities. The environmental adaptation perception benchmark data includes the minimum continuity standard data under different temperatures and humidity. The simulated sensing data and sensing performance benchmark data are input into the deviation analysis module to calculate the deviation value between the vibration sensing subset and the vibration signal capture benchmark data. This deviation value is the difference between the identification data corresponding to each frequency in the vibration sensing subset and the lowest identification standard data of the corresponding frequency in the benchmark data. Calculate the deviation between the electromagnetic sensing subset and the electromagnetic interference resistance reference data. This deviation is the difference between the stability data corresponding to each intensity in the electromagnetic sensing subset and the lowest stability standard data of the corresponding intensity in the reference data. Calculate the deviation between the environmental perception subset and the environmental adaptation perception baseline data. This deviation is the difference between the continuous data corresponding to each temperature and humidity in the environmental perception subset and the lowest continuous standard data of the corresponding temperature and humidity in the baseline data. Integrate vibration deviation values, electromagnetic deviation values, and environmental deviation values ​​to generate migration adaptation deviation data. The migration adaptation deviation data includes the interference type identifier, parameter identifier, and deviation value corresponding to each deviation value.

5. The security deployment decision-making method based on distributed optical fiber according to claim 1, characterized in that, The step of correcting the association parameters in the source domain migration rule set based on migration adaptation deviation data to generate a corrected source domain migration rule set includes: The migration adaptation deviation data is analyzed, and the interference type identifier, parameter identifier and deviation value corresponding to each deviation value are extracted. The vibration deviation value corresponds to the vibration interference type identifier and the fiber node spacing parameter identifier. The electromagnetic deviation value corresponds to the electromagnetic interference type identifier and the anti-interference configuration parameter identifier. The environmental deviation value corresponds to the environmental interference type identifier and the fiber laying depth parameter identifier. Retrieve the associated parameters corresponding to the interference type identifier and parameter identifier from the source domain migration rule set. The vibration interference type identifier and the fiber optic node spacing parameter identifier correspond to the node spacing associated parameters in the vibration rule subset. The electromagnetic interference type identifier and the anti-interference configuration parameter identifier correspond to the anti-interference associated parameters in the electromagnetic rule subset. The environmental interference type identifier and the fiber optic laying depth parameter identifier correspond to the laying depth associated parameters in the environmental rule subset. Establish a correction mapping between deviation values ​​and correlation parameters. When the vibration deviation value is positive, reduce the adjustment range of the node spacing parameter; when the vibration deviation value is negative, increase the adjustment range of the node spacing parameter. When the electromagnetic deviation value is positive, the protection level of the anti-interference configuration parameters is increased; when the electromagnetic deviation value is negative, the protection level of the anti-interference configuration parameters is decreased. When the environmental deviation value is positive, increase the adjustment range of the fiber optic laying depth parameter; when the environmental deviation value is negative, decrease the adjustment range of the fiber optic laying depth parameter. Based on the corrected mapping results, the corresponding correlation parameters are adjusted. For the node spacing correlation parameters in the vibration rule subset, the parameter correspondence is adjusted according to the absolute value of the vibration deviation value. For the anti-interference correlation parameters in the electromagnetic rule subset, the parameter protection level is adjusted according to the absolute value of the electromagnetic deviation value. For the laying depth correlation parameters in the environmental rule subset, the parameter depth amplitude is adjusted according to the absolute value of the environmental deviation value. The vibration rule subset, electromagnetic rule subset, and environmental rule subset are integrated and adjusted to form the modified source domain migration rule set. The modified source domain migration rule set retains the original scene identification field and adds a correction identification field to indicate the correction time and correction basis of each parameter.

6. The security deployment decision-making method based on distributed optical fiber according to claim 1, characterized in that, The optimization of the initial target domain deployment scheme based on the modified source domain migration rule set, and the determination of the final distributed fiber optic security deployment decision scheme through multiple rounds of migration effect verification, includes: The modified source domain migration rule set is input into the target domain adaptation module, and the rule subset that matches the interference feature data of the target pre-security area is extracted again to generate the optimized adaptation rule subset. Based on the optimized adaptation rule subset, adjust the parameters in the initial target domain deployment scheme, adjust the fiber node spacing parameters according to the corrected node spacing correlation parameters, adjust the anti-interference configuration parameters according to the corrected anti-interference correlation parameters, and adjust the fiber laying depth parameters according to the corrected laying depth correlation parameters. Combining terrain feature data and security requirement data of the target pre-security area, the fiber optic path direction parameters and fiber optic branch density parameters are optimized again. The path direction parameters avoid areas where the revised laying depth parameters are not suitable, and the branch density parameters are redistributed according to the revised node spacing parameters. The adjusted target domain deployment scheme is input into the distributed fiber optic migration effect simulation system to repeatedly simulate the process of sensing data acquisition and migration adaptation deviation data calculation, generating the second round of migration adaptation deviation data. Compare the changes in deviation values ​​between the second round of migration adaptation deviation data and the first round of migration adaptation deviation data. If all deviation values ​​have decreased and are within the preset deviation range, it indicates that the current adjusted target domain deployment scheme has met the migration adaptation requirements. If there are deviation values ​​that have not decreased or exceed the preset deviation range, it is necessary to adjust the correlation parameters in the source domain migration rule set again based on the second round of migration adaptation deviation data and repeat the optimization of the initial target domain deployment scheme. Repeat the steps of optimizing the initial target domain deployment scheme based on the modified source domain migration rule set and inputting the optimized target domain deployment scheme into the distributed optical fiber migration effect simulation system to generate simulated sensing data and migration adaptation deviation data, until all deviation values ​​in the latest generated migration adaptation deviation data are within the preset deviation range, and obtain the target domain deployment scheme after multiple rounds of optimization. The optimized target domain deployment scheme was finally matched with the security requirements data of the target pre-security area. It was confirmed that the fiber optic branch density parameter in the optimized target domain deployment scheme met the requirements of the designated monitoring area, the fiber optic path direction parameter met the requirements of the perimeter intrusion monitoring, and the fiber optic coverage met the requirements of the whole area coverage. It was confirmed that the deployment parameters in the target domain deployment scheme after multiple rounds of optimization did not conflict with the terrain feature data, the fiber optic laying depth parameters were adapted to the surface material data, and the fiber optic node positions avoided the areas corresponding to the obstacle position data. Integrate all confirmed results to generate the final distributed fiber optic security deployment decision scheme, which includes the final determined fiber node spacing parameters, anti-interference configuration parameters, fiber laying depth parameters, fiber path orientation parameters, and fiber branch density parameters.

7. The security deployment decision-making method based on distributed optical fiber according to claim 2, characterized in that, The comparison of the correlation relationships among various source domains, identifying the common correlation logic between equipment operating vibration parameters, personnel activity vibration parameters, natural environment vibration parameters, and corresponding deployment parameters, includes: The feature dimensions of equipment operation vibration parameters are extracted from the correlation of the source domain of the industrial plant. The feature dimensions include vibration frequency range, vibration duration and vibration propagation speed. The adjustment dimensions of the corresponding fiber optic node spacing parameters are extracted. The adjustment dimensions include spacing reduction range, spacing expansion range and spacing maintenance range. The feature dimensions of vibration parameters of personnel activities are extracted from the correlation of the source domain of the civilian park. The feature dimensions include vibration frequency range, vibration duration and vibration propagation speed. The adjustment dimensions of the corresponding optical fiber branch density parameters are extracted. The adjustment dimensions include density increase, density decrease and density maintenance. The feature dimensions of natural environmental vibration parameters are extracted from the correlation of the source domain of the border line. The feature dimensions include vibration frequency range, vibration duration and vibration propagation speed. The adjustment dimensions of the corresponding optical fiber laying depth parameters are extracted. The adjustment dimensions include depth increase, depth decrease and depth maintenance. The characteristic dimensions of vibration parameters in each source domain are aligned to ensure that the names of the characteristic dimensions of equipment operation vibration parameters, personnel activity vibration parameters, and natural environment vibration parameters are consistent with the classification standard. The adjustment dimensions of the parameters deployed in each source domain are classified into three types: adjustment that is positively correlated with vibration frequency, adjustment that is positively correlated with vibration duration, and adjustment that is negatively correlated with vibration propagation speed. Count the frequency of each type of adjustment in the relationships of each source domain. If a certain type of adjustment appears in all source domains and its frequency accounts for more than half, then this type of adjustment is regarded as a candidate common adjustment type. The correspondence between candidate common adjustment types and vibration parameter characteristic dimensions was analyzed. For adjustment types positively correlated with vibration frequency, it was verified whether the adjustment amplitude of the layout parameters increased with the increase of vibration frequency in each source domain. For adjustment types positively correlated with vibration duration, it was verified whether the adjustment amplitude of the layout parameters increased with the extension of vibration duration in each source domain. For adjustment types negatively correlated with vibration propagation velocity, it was verified whether the adjustment amplitude of the layout parameters decreased with the increase of vibration propagation velocity in each source domain. If the verification results are all true, such as whether the adjustment range of the layout parameters increases when the vibration frequency increases in each source domain, whether the adjustment range of the layout parameters increases when the vibration duration in each source domain increases, and whether the adjustment range of the layout parameters decreases when the vibration propagation speed in each source domain increases, then the candidate common adjustment type is associated with the corresponding vibration parameter feature dimension to form a common association logic between vibration parameters and layout parameters. Integrate all valid common correlation logics to form a set of common correlation logics for equipment operation vibration parameters, personnel activity vibration parameters, natural environment vibration parameters and corresponding deployment parameters.

8. The security deployment decision-making method based on distributed optical fiber according to claim 3, characterized in that, The analysis compares the similarity between the scene identifier field of the target adaptation rule subset and the scene features of the target pre-security area, and calculates the scene similarity value between each target adaptation rule subset and the target domain, including: Extract scene feature parameters from the scene identifier field of the target adaptation rule subset. The scene feature parameters of the vibration rule subset include the proportion of vibration interference type, the range of vibration interference intensity, and the duration of vibration interference. The scene feature parameters of the electromagnetic rule subset include the proportion of electromagnetic interference type, the range of electromagnetic interference intensity, and the duration of electromagnetic interference. The scene feature parameters of the environmental rule subset include the proportion of environmental interference type, the range of environmental interference intensity, and the duration of environmental interference. Scene feature parameters are extracted from the scene features of the target pre-security area. The scene feature parameters include the proportion of interference types, the range of interference intensity, and the duration of interference. The proportion of interference types is statistically analyzed separately for vibration interference, electromagnetic interference, and environmental interference. The range of interference intensity is divided into different intensity levels. The duration of interference is divided into different durations. Normalize the feature parameters of each scene, convert the proportion of interference types into dimensionless percentage values, convert the range of interference intensity into dimensionless relative values ​​based on a preset intensity benchmark, and convert the duration of interference into dimensionless relative values ​​based on a preset duration benchmark. The difference between the normalized feature parameters of the target adaptation rule subset and the target pre-security area is calculated. The difference between the normalized value of the vibration interference type ratio of the vibration rule subset and the normalized value of the vibration interference type ratio of the target domain, the difference between the normalized value of the vibration interference intensity range and the normalized value of the vibration interference intensity range of the target domain, and the difference between the normalized value of the vibration interference duration and the normalized value of the vibration interference duration of the target domain are calculated. Assign preset weights to each scene feature parameter; The difference between each scene feature parameter is multiplied by its corresponding weight to obtain the weighted difference between each scene feature parameter. The weighted differences of all scene feature parameters are summed to obtain the total difference between the subset of target adaptation rules and the target domain. The scene similarity value is calculated based on the total difference. The closer the total difference is to 0, the closer the scene similarity value is to 1. The closer the total difference is to 1, the closer the scene similarity value is to 0. Output the effective scene similarity value between each subset of target adaptation rules and the target domain.

9. The security deployment decision-making method based on distributed optical fiber according to claim 4, characterized in that, The activation of the perception test module collects perception data of the virtual deployment model under a virtual interference environment, including: A test cycle is set in the perception test module. The test cycle is divided according to the interference change pattern of the target pre-security area, including the interference intensity increase period, the interference intensity stable period, and the interference intensity decrease period. During periods of increased interference intensity, the frequency and amplitude of the virtual vibration signal, the intensity and fluctuation frequency of the virtual electromagnetic signal, and the temperature and humidity change amplitude of the virtual environmental influence signal are gradually increased at preset intervals. During periods of stable interference intensity, the parameters of the virtual vibration signal, virtual electromagnetic signal, and virtual environmental influence signal remain unchanged, and the interference signal is continuously output. During the period when the interference intensity decreases, the frequency and amplitude of the virtual vibration signal, the intensity and fluctuation frequency of the virtual electromagnetic signal, and the temperature and humidity change amplitude of the virtual environmental influence signal are gradually reduced at preset intervals. During each test period, vibration signal capture data of the virtual deployment model is collected at fixed time intervals. The vibration signal capture data includes the recognition success rate and recognition delay time of each fiber optic node for vibration signals of different frequencies. Collect electromagnetic interference resistance data of the virtual deployment model. The electromagnetic interference resistance data includes the signal transmission bit error rate and signal attenuation amplitude of each optical fiber segment under different electromagnetic intensities. Collect environmental adaptation perception data of the virtual deployment model. The environmental adaptation perception data includes the sensing response speed and sensing data integrity of the fiber optic nodes under different temperature and humidity conditions. The collected vibration signal capture data is classified and stored according to the test period and the fiber optic node location. The data of each node corresponds to a unique test period identifier and node location identifier. The collected electromagnetic interference resistance data are classified and stored according to the test period and fiber segment location. Each fiber segment data corresponds to a unique test period identifier and fiber segment location identifier. The collected environmental adaptation sensing data is stored according to the test period and temperature and humidity conditions. Each temperature and humidity condition data corresponds to a unique test period identifier and environmental parameter identifier. Duplicate data are removed from the categorized and stored sensory data, and identical data collected under the same test conditions are deleted. After removing duplicates, perform an integrity check on the perception data and supplement the perception data for missing test periods or locations to form a complete perception data set.

10. A security deployment decision system based on distributed optical fiber, characterized in that, include: processor; A machine-readable storage medium for storing machine-executable instructions of the processor; The processor is configured to execute the security deployment decision method based on any one of claims 1 to 9 by executing the machine-executable instructions.

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