On-site inspection and damage assessment data processing methods and systems

Abstract

This application provides a method and system for processing on-site survey and damage assessment data, relating to the field of data processing technology. The method includes: acquiring equipment fault records from a power grid monitoring platform and extracting the voltage level and loss extent from the equipment fault records; determining the damage assessment calculation path based on the voltage level and processing the equipment fault records according to the damage assessment calculation path to obtain a preliminary damage assessment value; sending the preliminary damage assessment value to an insurance brokerage server and receiving the reviewed damage assessment value returned by the insurance brokerage server; calculating the damage assessment offset between the preliminary damage assessment value and the reviewed damage assessment value, and generating a damage assessment statistics table based on the damage assessment offset. In this application, the automatic selection of the damage assessment calculation path improves the damage assessment accuracy for equipment at different voltage levels; the quantitative calculation of the damage assessment offset allows for automatic identification of errors in the damage assessment calculation path selection; establishing a damage assessment consensus in advance during the review process avoids later disputes; and the distribution pattern of the damage assessment offset can be used to diagnose the rationality of the calculation rules.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to methods and systems for processing data from on-site investigation and damage assessment. Background Technology

[0002] Power grid equipment can be damaged by natural disasters such as rain, snow, ice, floods, and typhoons, requiring compensation through an insurance claim process. This process includes stages such as damage assessment, loss estimation, on-site inspection by the insurance company, and confirmation of the damage figure. The process necessitates data exchange and collaboration between the power grid maintenance department, finance department, and insurance company.

[0003] In the existing insurance claims process, the estimated damage to equipment is assessed by the reporting personnel based on the extent of the damage. The personnel fill in the estimated damage data according to their judgment of the damaged equipment's condition, and the insurance company provides the verified damage data after on-site inspection. Power grid equipment includes various types such as transformers, switchgear, poles, and lines, with voltage levels ranging from 0.4kV to 220kV. The manual damage assessment process uses the same assessment method for equipment of different voltage levels, lacking calculation rules tailored to the differences in equipment voltage levels. This often leads to discrepancies between the reported estimated damage data and the data verified by the insurance company.

[0004] Therefore, existing technologies lack differentiated processing methods for equipment of different voltage levels, resulting in low accuracy in loss estimation. Summary of the Invention

[0005] This application provides a method for processing on-site survey and loss assessment data to address the problems in existing technologies where insurance loss assessments do not establish a mapping relationship between voltage levels and asset attributes, use a uniform calculation method leading to insufficient accuracy in loss assessments for different types of equipment, lack a quantitative identification method for loss assessment deviations, and make it difficult to trace loss assessment anomalies.

[0006] The first aspect of this application provides a method for processing on-site investigation and damage assessment data, including:

[0007] Obtain equipment fault records from the power grid monitoring platform, and extract the voltage level and loss extent from the equipment fault records;

[0008] Based on the voltage level, a damage estimation calculation path is determined, and the equipment fault records are processed according to the damage estimation calculation path to obtain a preliminary damage estimate.

[0009] The preliminary loss estimate is sent to the insurance brokerage server, and the reviewed loss estimate is received from the insurance brokerage server.

[0010] Calculate the loss estimation offset between the preliminary loss estimate and the verified loss estimate, and generate a loss estimation statistics table based on the loss estimation offset.

[0011] Optionally, in one possible implementation of the first aspect, the equipment type identifier, faulty equipment identifier, equipment technical level parameter, and geographical area identifier are extracted from the equipment fault record;

[0012] The step of determining the loss estimation calculation path based on the voltage level includes:

[0013] Based on the voltage level, the equipment type identifier, the degree of loss, and the equipment technical level parameters, the path fit degree values ​​of multiple candidate loss estimation calculation paths are calculated according to preset path fit rules.

[0014] The candidate loss calculation path with the highest path fit value is determined as the loss calculation path.

[0015] Optionally, in one possible implementation of the first aspect, the step of calculating the path fit degree values ​​of multiple candidate loss estimation calculation paths according to preset path fit rules includes:

[0016] For each candidate loss estimation calculation path, multiple adaptation evaluation parameters corresponding to the candidate loss estimation calculation path are obtained from the preset path adaptation rule base;

[0017] The first parameter value of the first adaptation evaluation parameter is determined based on the voltage level, the second parameter value of the second adaptation evaluation parameter is determined based on the equipment type identifier, the third parameter value of the third adaptation evaluation parameter is determined based on the degree of loss, and the fourth parameter value of the fourth adaptation evaluation parameter is determined based on the equipment technical level parameter.

[0018] Based on the first parameter value, the second parameter value, the third parameter value, and the fourth parameter value, the path fit value of the candidate loss estimation calculation path is determined according to the preset fit value calculation rule.

[0019] Optionally, in one possible implementation of the first aspect, the preset path adaptation rule base stores the correspondence between multiple candidate loss estimation calculation paths and adaptation evaluation parameters;

[0020] The multiple candidate loss estimation calculation paths include a first candidate path based on the asset depreciation model, a second candidate path based on the loss assessment standard library query, and a third candidate path based on the line loss estimation unit parameters;

[0021] The adaptation evaluation parameters corresponding to the first candidate path include a voltage level higher than a preset high voltage threshold, a high-tech equipment level parameter, and a severe loss level.

[0022] The adaptation evaluation parameters corresponding to the second candidate path include a voltage level lower than a preset low voltage threshold and a device type identifier indicating that it belongs to a standardized device;

[0023] The adaptation evaluation parameters corresponding to the third candidate path include the equipment type identifier belonging to the line type and the geographical area identifier belonging to the preset dense line area.

[0024] Optionally, in one possible implementation of the first aspect, processing the equipment fault records according to the damage calculation path to obtain a preliminary damage estimate includes:

[0025] When the loss calculation path corresponds to the first candidate path, the original set of asset parameters is obtained by querying the faulty equipment identifier, the asset depreciation parameters are determined based on the original set of asset parameters, and the preliminary loss estimate is determined based on the asset depreciation parameters and the degree of loss.

[0026] When the estimated damage calculation path corresponds to the second candidate path, standard estimated damage data is obtained from the equipment fault record as the preliminary estimated damage value.

[0027] When the estimated damage calculation path corresponds to the third candidate path, the loss quantity data is extracted from the equipment fault record, the line loss estimation unit parameters are queried according to the geographical area identifier, and the preliminary loss estimate is determined based on the line loss estimation unit parameters and the loss quantity data.

[0028] Optionally, in one possible implementation of the first aspect, obtaining equipment fault records from the power grid monitoring platform includes:

[0029] Obtain all fault records within a preset time period from the power grid monitoring platform;

[0030] Extract the fault cause attribute from all the fault records;

[0031] Perform a matching judgment operation between the fault cause attribute and the preset disaster type list, and use the fault record that is successfully matched as the equipment fault record.

[0032] Optionally, in one possible implementation of the first aspect, the identifier format type and the identifier source system type are identified from the faulty device identifier;

[0033] Based on the identifier format type and the identifier source system type, query the identifier conversion rule corresponding to the combination of the identifier format type and the identifier source system type from the preset identifier mapping rule library;

[0034] The faulty device identifier is converted into a standard device code according to the aforementioned identifier conversion rules;

[0035] Based on the standard equipment code, retrieve the equipment asset code and asset status parameter set from the asset management platform;

[0036] When the asset management platform returns multiple candidate asset records, the fault occurrence time is extracted from the equipment fault record, and a time matching verification is performed between the fault occurrence time and the valid asset time period of the candidate asset record. The candidate asset record that passes the time matching verification is selected to establish an association.

[0037] Optionally, in one possible implementation of the first aspect, after generating the estimated loss statistics table based on the estimated loss offset, the method further includes:

[0038] Extract the preliminary estimated damage value and the verified estimated damage value from the estimated damage statistics table for multiple equipment records;

[0039] The number of equipment records where the preliminary estimated damage value is greater than the verified estimated damage value is counted, and the overestimation percentage is determined based on the number of equipment records and the total number of equipment failure records.

[0040] If the overestimation percentage is greater than the preset overestimation percentage threshold, the loss calculation path corresponding to the preliminary loss estimate is extracted, and a path adjustment identifier is generated.

[0041] Modify the rule parameters in the loss calculation path based on the path adjustment identifier.

[0042] Optionally, in one possible implementation of the first aspect, after generating the estimated loss statistics table based on the estimated loss offset, the method further includes:

[0043] Send the estimated damage statistics table to the on-site investigation terminal;

[0044] The system receives exploration record data uploaded by the field exploration terminal, the exploration record data consisting of a list of exploration equipment and exploration confirmation results;

[0045] Compare the list of exploration equipment with the equipment failure records recorded in the estimated damage statistics table to generate an exploration comparison table;

[0046] Based on the survey confirmation results, the preliminary estimated loss value in the estimated loss statistics table is corrected to obtain the on-site verified loss value.

[0047] Optionally, in one possible implementation of the first aspect, it also includes:

[0048] Extract the power grid type attribute from the equipment fault records;

[0049] When the power grid type attribute is a main grid type, the full amount of survey record data uploaded by the field survey terminal is received;

[0050] When the power grid type attribute is distribution network type, the equipment fault records are hierarchically processed according to the geographical area identifier and the voltage level to obtain multiple equipment subsets;

[0051] For each subset of devices, the sampling survey record data uploaded by the field survey terminal is received, and the number of devices confirmed to be damaged and the number of survey devices in the sampling survey record data are counted to determine the damage rate of the subset;

[0052] The number of damaged devices in the subset is calculated based on the subset damage rate and the total number of devices corresponding to the subset. The total number of damaged devices in all the subsets is then summed to obtain the total number of damaged devices in the distribution network.

[0053] Optionally, in one possible implementation of the first aspect, the method further includes: after performing a correction operation on the preliminary estimated loss value in the estimated loss statistics table based on the survey confirmation results to obtain the on-site verified loss value, the method further includes:

[0054] The on-site damage assessment value is sent to a multi-party confirmation server;

[0055] Receive confirmation status data returned by the multi-party confirmation server;

[0056] If the value of the confirmed status data is equal to the preset pass mark, the on-site loss assessment value is used as the final loss assessment value, and a loss assessment confirmation document is generated.

[0057] Send the loss confirmation document to the insurance claims platform.

[0058] Optionally, in one possible implementation of the first aspect, the step of generating a loss estimation statistics table based on the loss estimation offset includes:

[0059] Create a data structure for a damage estimation statistics table, which consists of a set of equipment information fields, a set of damage estimation data fields, and a set of offset analysis fields.

[0060] Extract device identification information from the device fault records and write the device identification information into the device information field set;

[0061] Write the preliminary loss estimate into the first loss estimate field in the loss estimate data field set, and write the revised loss estimate into the second loss estimate field in the loss estimate data field set;

[0062] Write the estimated damage offset into the offset field of the offset analysis field set;

[0063] Based on the estimated loss offset and the preliminary estimated loss value, the offset rate data is determined and written into the offset rate field in the offset analysis field set.

[0064] A second aspect of this application provides a field survey and damage assessment data processing system, comprising: a data acquisition module, used to acquire equipment fault records from a power grid monitoring platform and extract the voltage level and loss extent from the equipment fault records;

[0065] The path determination module is used to determine the estimated damage calculation path based on the voltage level, and process the equipment fault records according to the estimated damage calculation path to obtain a preliminary estimated damage value.

[0066] The data interaction module is used to send the preliminary loss estimate to the insurance brokerage server and receive the verified loss estimate returned by the insurance brokerage server.

[0067] The statistics table generation module is used to calculate the loss offset between the preliminary loss estimate and the reviewed loss estimate, and generate a loss estimate statistics table based on the loss offset.

[0068] The on-site investigation and damage assessment data processing method provided in this application has the following beneficial effects:

[0069] 1. This application extracts the voltage level and loss extent from equipment fault records from the power grid monitoring platform, determines the loss estimation calculation path based on the voltage level, and processes the equipment fault records to obtain a preliminary loss estimate. By triggering different loss estimation calculation paths based on the voltage level, high-voltage equipment, low-voltage equipment, and line equipment adopt calculation methods adapted to their respective characteristics, avoiding the loss estimation error caused by a unified assessment method failing to take into account the characteristics of equipment at different voltage levels. Furthermore, this application automatically selects the loss estimation calculation path, eliminating the need for manual judgment of equipment type and selection of calculation method, reducing the uncertainty of manual assessment, and improving the accuracy of the loss estimation data.

[0070] 2. This application sends the preliminary loss estimate to the insurance brokerage server and receives the reviewed loss estimate. It then calculates the loss deviation between the preliminary and reviewed loss estimates and generates a loss estimate statistics table. The review process is completed before the formal claim is filed, ensuring that the preliminary loss estimate has been verified before submission to the insurance company. This avoids repeated negotiations and claims delays caused by excessively large discrepancies in the loss estimate data after the claim is filed. The quantitative recording of the loss deviation quantifies the difference between the preliminary and reviewed loss estimates. When the overestimation percentage exceeds a preset overestimation percentage threshold, the selection deviation of the loss calculation path can be identified, and the rule parameters can be corrected. This allows the loss calculation rules to self-adjust based on actual deviations, reducing the accumulation of loss estimates for subsequent batches of equipment. Attached Figure Description

[0071] Figure 1 This is an overall flowchart of the on-site investigation and damage assessment data processing method provided in the embodiments of this application;

[0072] Figure 2This is an application environment diagram of the on-site investigation and damage assessment data processing method provided in the embodiments of this application;

[0073] Figure 3 This is a schematic diagram of the structure of the on-site investigation and damage assessment data processing system provided in the embodiments of this application;

[0074] Figure 4 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0075] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0076] The technical solutions of this application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0077] See Figure 1 This is an overall flowchart of the on-site investigation and damage assessment data processing method provided in the embodiments of this application. Figure 1 The execution entity of the method shown can be a software and / or hardware device. The execution entity of this application can include, but is not limited to, at least one of the following: user equipment, network equipment, etc. User equipment can include, but is not limited to, computers, smartphones, personal digital assistants (PDAs), and the aforementioned electronic devices. Network equipment can include, but is not limited to, a single network server, a server group consisting of multiple network servers, or a cloud based on cloud computing consisting of a large number of computers or network servers. Cloud computing is a type of distributed computing, consisting of a super virtual computer composed of a group of loosely coupled computers. This embodiment does not impose any limitations on this.

[0078] Reference Figure 2 The on-site investigation and damage assessment data processing method provided in this application embodiment can be applied to, for example... Figure 2The application environment is illustrated. In this environment, the field survey terminal communicates with the loss assessment server via a network. The loss assessment server interacts with the power grid monitoring platform, insurance brokerage server, asset management platform, multi-party confirmation server, and insurance claims platform via the network. The data storage system can store the loss assessment data, equipment failure records, survey records, and other data that the loss assessment server needs to process. The data storage system can be integrated into the loss assessment server or hosted on the cloud or other network servers. The loss assessment server obtains equipment fault records from the power grid monitoring platform, extracts the voltage level and loss extent from the equipment fault records; determines the loss assessment calculation path based on the voltage level, processes the equipment fault records according to the loss assessment calculation path to obtain a preliminary loss estimate; sends the preliminary loss estimate to the insurance brokerage server, and receives the reviewed loss estimate returned by the insurance brokerage server; calculates the loss assessment offset between the preliminary loss estimate and the reviewed loss estimate, and generates a loss assessment statistics table based on the loss assessment offset; sends the loss assessment statistics table to the field survey terminal, and receives the survey record data uploaded by the field survey terminal; determines the on-site loss assessment value based on the survey record data, sends the on-site loss assessment value to the multi-party confirmation server for multi-party confirmation, generates a loss assessment confirmation document, and sends it to the insurance claims platform.

[0079] The on-site investigation terminal can be, but is not limited to, various mobile devices such as smartphones, tablets, portable data acquisition terminals, industrial tablets, and ruggedized handheld terminals. The on-site investigation terminal can be equipped with a camera, GPS positioning module, and wireless communication module; used to record on-site investigation data such as photos of equipment damage, coordinates of the fault location, and investigation time. The loss assessment server can be a standalone physical server; a server cluster or distributed system composed of multiple physical servers; or a cloud server providing cloud computing services. The power grid monitoring platform includes a main grid equipment monitoring platform and a distribution network equipment monitoring platform; used to record the operating status and fault information of power grid equipment. The insurance brokerage server is a server deployed by a third-party insurance brokerage company; used to verify the preliminary loss estimate. The asset management platform is used to store and manage asset information of power grid equipment. The multi-party confirmation server is used to coordinate the confirmation of loss assessment data by multiple parties, including business departments, finance departments, insurance brokerage companies, and insurance companies. The insurance claims platform is an insurance claims processing platform deployed by insurance companies; used to receive loss assessment confirmation documents and conduct insurance claims processes.

[0080] Specifically, the on-site investigation and damage assessment data processing method provided in this application includes steps 100 to 400, as follows:

[0081] Step 100: Obtain equipment fault records from the power grid monitoring platform and extract the voltage level and loss degree from the equipment fault records.

[0082] The power grid monitoring platform includes a main grid equipment monitoring platform and a distribution network equipment monitoring platform. The main grid equipment monitoring platform records the operating status and fault information of main grid equipment such as substations and transformers, while the distribution network equipment monitoring platform records the operating status and fault information of distribution network equipment such as distribution lines and switching equipment. When natural disasters occur, power grid equipment may experience faults such as line tripping, equipment damage, and substation outages due to rain, snow, ice, floods, typhoons, etc. The power grid monitoring platform records information such as the equipment code of the faulty equipment, the time of the fault, the cause of the fault, and the location of the fault, forming a fault record.

[0083] The equipment fault record includes multiple data fields such as equipment code, fault time, fault cause, fault location, voltage level, and damage severity. The voltage level field records the rated voltage of the faulty equipment, with values ​​including 0.4kV, 10kV, 35kV, 110kV, and 220kV. The damage severity field records the extent of damage to the equipment, with different descriptions for different equipment types. For example, the damage severity for utility poles includes broken poles, fallen poles, leaning poles, and pole base damage; for transformers, it includes burnt-out, water damage, and casing damage; and for switchgear, it includes burnt-out, mechanical damage, and control failure.

[0084] It should be noted that the equipment type identifier, faulty equipment identifier, equipment technical level parameters, and geographical area identifier are extracted from the equipment fault records. The equipment type identifier is used to distinguish different types of power grid equipment, such as transformers, switchgear, poles, and lines. The faulty equipment identifier is a unique identifier recorded in the power grid monitoring platform and can consist of an equipment code or equipment name. The equipment technical level parameters include information such as the equipment's technical specifications, manufacturing year, and technical standard level, used to assess the equipment's value and depreciation. For example, the equipment technical level parameters for transformers include technical specifications such as transformer capacity, voltage level, manufacturing year, and insulation class. The geographical area identifier records the geographical location of the faulty equipment, including geographical level information such as county unit, power supply station, and substation.

[0085] Step 100 involves obtaining equipment fault records from the power grid monitoring platform, including steps 110 to 130:

[0086] Step 110: Obtain all fault records within the preset time period from the power grid monitoring platform.

[0087] The preset time period is the start and end time of the natural disaster emergency response. The start time is the time when the natural disaster warning is issued or when the natural disaster begins to affect the power grid operation, and the end time is the time when the natural disaster emergency response ends. Within the preset time period, all fault records recorded by the power grid monitoring platform include equipment faults caused by natural disasters, as well as equipment faults caused by equipment aging, operational errors, and other reasons.

[0088] It should be noted that the total volume of fault records is substantial, including many faults unrelated to natural disasters. Traditional methods directly use all fault records for loss estimation, leading to an expanded scope of estimation and including equipment losses not caused by natural disasters in insurance claims, thus reducing the accuracy of the estimated data. For example, during a typhoon, if a transformer fails due to aging, traditional methods would include this equipment loss in the typhoon damage loss, resulting in an inflated estimated loss. Therefore, it is necessary to filter out equipment fault records caused by natural disasters in subsequent steps.

[0089] Step 120: Extract the fault cause attribute from all fault records.

[0090] The fault cause attribute is recorded in the fault cause field of the fault record. The value of the fault cause field includes natural disaster-related causes and non-natural disaster-related causes. Natural disaster-related causes include causes such as rain, snow, ice, floods, typhoons, lightning strikes, and geological disasters. Non-natural disaster-related causes include causes such as equipment aging, operational errors, and external damage.

[0091] Understandably, the values ​​of the fault cause field are read one by one from all fault records to obtain the fault cause attribute corresponding to each fault record, providing basic data for subsequent matching and judgment operations. For example, if the fault cause field value of a certain fault record is "Typhoon caused the power pole to collapse", the extracted fault cause attribute is "Typhoon".

[0092] Step 130: Perform a matching judgment operation between the fault cause attribute and the preset disaster type list, and use the fault records that are successfully matched as equipment fault records.

[0093] The preset disaster type list stores the type identifiers of natural disasters, including rain, snow, ice, floods, typhoons, lightning strikes, and geological disasters. A string matching operation is performed between the fault cause attribute and each type identifier in the preset disaster type list. When the fault cause attribute matches any type identifier in the preset disaster type list, the matching operation is considered successful, and the corresponding fault record is recorded as an equipment fault record.

[0094] Understandably, the matching and judgment operation filters out equipment failure records caused by natural disasters, excluding failure records caused by other reasons such as equipment aging or operational errors. This avoids including equipment losses caused by non-natural disasters in the damage assessment scope, thereby ensuring the accuracy of the damage assessment data. For example, when the failure cause attribute is "typhoon," it matches the "typhoon" type identifier in the preset disaster type list, and the failure record is recorded as an equipment failure record; when the failure cause attribute is "equipment aging," it does not match any type identifier in the preset disaster type list, and the failure record is excluded.

[0095] It should be noted that the embodiments of this application also include steps A1 to A5:

[0096] Step A1: Extract the power grid type attribute from the equipment fault record.

[0097] The power grid type attribute is used to distinguish between main grid equipment and distribution network equipment. Main grid equipment includes substations, transformers with voltage levels of 110kV and above, and lines with voltage levels of 35kV and above. Distribution network equipment includes distribution lines with voltage levels of 10kV and below, public transformers, and switchgear.

[0098] Understandably, the power grid type attribute is extracted from the voltage level field of the equipment fault record. When the voltage level field value is 35kV or above, the power grid type attribute is identified as a main grid type; when the voltage level field value is 10kV or below, the power grid type attribute is identified as a distribution network type. For example, when the voltage level field value is 110kV, the power grid type attribute is identified as a main grid type; when the voltage level field value is 10kV, the power grid type attribute is identified as a distribution network type.

[0099] Step A2: If the power grid type attribute is the main grid type, receive the full amount of survey record data uploaded by the field survey terminal.

[0100] It should be noted that main grid equipment has high voltage levels and high value, and its failure has a wide-ranging impact on grid operation. Therefore, a comprehensive survey of the damage to each piece of main grid equipment is necessary. For example, a 110kV transformer has a high asset valuation, so its failure could lead to a power outage across the entire area, affecting tens of thousands of households. Thus, the location and extent of damage to each piece of main grid equipment must be recorded in detail. Traditional methods use the same sampling survey approach for both main grid and distribution network equipment, resulting in some high-value main grid equipment being overlooked, leading to inaccurate damage assessment data and affecting the fairness of insurance claims.

[0101] The on-site investigation terminal is carried by investigators to the site of the faulty equipment to record the actual damage condition of the equipment, including equipment code, damaged location, degree of damage, and on-site photos. The full-volume investigation record data refers to the investigation record data uploaded after conducting on-site investigations of all equipment fault records of the main grid type.

[0102] Step A3: When the power grid type attribute is distribution network type, perform a hierarchical operation on the equipment fault records according to the geographical area identifier and voltage level to obtain multiple equipment subsets.

[0103] It should be noted that the large number and wide distribution of distribution network equipment make a comprehensive survey of all equipment extremely labor-intensive and time-consuming. For example, a typhoon disaster might damage 3,000 power poles and cause 500 distribution transformers to malfunction in a county. If a comprehensive survey of each device were conducted, at a rate of 50 devices per day, the survey period could take up to 70 days, impacting insurance claims processing. Traditional methods either require a comprehensive survey of all distribution network equipment, leading to a long survey period, or use a uniform sampling ratio for all distribution network equipment, resulting in significant differences in the accuracy of damage assessment across different regions and voltage levels.

[0104] Understandably, equipment fault records are categorized by geographical region (different county units, different power supply stations) and by voltage level (10kV, 0.4kV, etc.). Using a combination of geographical region and voltage level as a stratification condition, the equipment fault records are divided into multiple subsets, each containing fault records with the same geographical region and voltage level. For example, 10kV pole fault records from a certain county power supply company could be considered as one subset, and 0.4kV distribution transformer fault records from the same company as another.

[0105] Step A4: For each equipment subset, receive the sampled survey record data uploaded by the field survey terminal, and determine the subset damage rate by counting the number of confirmed damaged devices and the number of survey devices in the sampled survey record data.

[0106] Specifically, for each equipment subset, a portion of equipment fault records are extracted from the equipment subset for on-site investigation according to a preset sampling ratio. The preset sampling ratio is determined based on the total number of equipment in the equipment subset and the investigation resources.

[0107] For example, when the total number of devices in the device subset is less than 100, the preset sampling ratio can be set to 50%; when the total number of devices in the device subset is greater than 100 and less than 500, the preset sampling ratio can be set to 30%; and when the total number of devices in the device subset is greater than 500, the preset sampling ratio can be set to 20%.

[0108] The sampling survey record data consists of survey records uploaded after on-site surveys of equipment failure records extracted from the equipment subset. The number of devices confirmed to be damaged is counted from the sampling survey record data, denoted as the confirmed damaged device number. The total number of devices surveyed is counted, denoted as the surveyed device number. The ratio of the confirmed damaged device number to the surveyed device number is used as the subset damage rate.

[0109] Step A5: Calculate the number of damaged devices in the subset based on the subset damage rate and the total number of devices corresponding to the subset. Summarize the number of damaged devices in all device subsets to obtain the total number of damaged devices in the distribution network.

[0110] Understandably, the product of the subset damage rate and the total number of devices corresponding to the subset is used as the number of devices with assessed damage within that subset. The total number of devices corresponding to the subset is the total number of device fault records within that subset. The total number of devices with assessed damage across all subsets is then accumulated to obtain the overall number of devices with assessed damage in the distribution network.

[0111] It is easy to understand that by using sampling surveys and proportional extrapolation, the overall damage assessment of distribution network equipment can be estimated while reducing the workload of surveys. This balances the allocation of survey resources between full surveys of main grid equipment and sampling surveys of distribution network equipment, ensuring the accuracy of damage assessments for high-value main grid equipment while controlling the survey costs of distribution network equipment.

[0112] In summary, step 100 obtains all fault records within a preset time period from the power grid monitoring platform, filters out equipment fault records caused by natural disasters by matching fault cause attributes with a preset list of disaster types, and extracts data fields such as voltage level, loss degree, equipment type identifier, fault equipment identifier, equipment technical level parameters, geographical area identifier, and power grid type attribute from the equipment fault records. Based on the power grid type attribute, it determines that the main grid equipment adopts a full survey method and the distribution network equipment adopts a stratified sampling survey method, providing basic data for determining the loss calculation path in step 200.

[0113] Step 200: Determine the damage calculation path based on the voltage level, and process the equipment fault records according to the damage calculation path to obtain the preliminary damage estimate.

[0114] It should be noted that power grid equipment is diverse, and the methods for calculating losses differ across voltage levels and equipment types. Traditional methods apply a uniform loss calculation method to all equipment, such as calculating the loss value based on a fixed percentage of the equipment's original value. This leads to the neglect of depreciation factors for high-voltage equipment, the failure to utilize loss assessment standards for standardized equipment, and the non-application of unit parameter calculations for line-type equipment, resulting in significant discrepancies between estimated loss data and actual equipment losses. Therefore, this application determines the loss calculation path based on voltage level, enabling equipment with different characteristics to use loss calculation methods adapted to their specific features.

[0115] Specifically, step 200 includes steps 210 and 220:

[0116] Step 210: Determine the loss calculation path based on the voltage level.

[0117] The damage calculation path refers to the method and path used to calculate the preliminary damage estimate of the equipment. Different damage calculation paths employ different data sources and calculation rules. The voltage level refers to the value of the voltage level field in the equipment fault record, which is used to trigger the selection of the damage calculation path.

[0118] Furthermore, step 210 includes steps 211 and 212:

[0119] Step 211: Based on voltage level, equipment type identifier, loss degree and equipment technical level parameters, calculate the path fit degree values ​​of multiple candidate loss estimation calculation paths according to the preset path fit rules.

[0120] Among them, the candidate loss estimation calculation path is a selectable loss estimation calculation method path, and the path fit value is used to quantify the degree of matching between the candidate loss estimation calculation path and the current equipment fault record. The preset path fit rules define the fit conditions of different candidate loss estimation calculation paths for voltage level, equipment type identification, loss degree, and equipment technical level parameters.

[0121] Understandably, the voltage level, equipment type identifier, loss degree, and equipment technical level parameters extracted from the equipment fault records are used as input parameters and compared with the adaptation conditions of each candidate loss estimation calculation path. The path adaptation value of the candidate loss estimation calculation path is calculated. The larger the path adaptation value, the more suitable the candidate loss estimation calculation path is for the loss estimation calculation of the current equipment fault record.

[0122] Step 211 calculates the path fit values ​​of multiple candidate loss estimation paths according to preset path fit rules, including steps 2111 to 2113:

[0123] Step 2111: For each candidate loss calculation path, obtain multiple adaptation evaluation parameters corresponding to the candidate loss calculation path from the preset path adaptation rule library.

[0124] The preset path adaptation rule base stores the correspondence between candidate damage estimation calculation paths and adaptation evaluation parameters. The adaptation evaluation parameters are the judgment conditions for evaluating whether a candidate damage estimation calculation path is applicable to the current equipment fault record. For each candidate damage estimation calculation path, the corresponding adaptation evaluation parameters are read from the preset path adaptation rule base. The adaptation evaluation parameters include a first adaptation evaluation parameter, a second adaptation evaluation parameter, a third adaptation evaluation parameter, and a fourth adaptation evaluation parameter.

[0125] For example, the first adaptive evaluation parameter corresponding to a certain candidate loss estimation calculation path is "voltage level is higher than the preset high voltage threshold", the second adaptive evaluation parameter is "equipment technical level parameter belongs to high technology level", the third adaptive evaluation parameter is "loss degree belongs to severe loss", and the fourth adaptive evaluation parameter is "equipment type identifier belongs to transformer type".

[0126] Step 2112: Determine the first parameter value of the first adaptation evaluation parameter based on the voltage level, determine the second parameter value of the second adaptation evaluation parameter based on the equipment type identifier, determine the third parameter value of the third adaptation evaluation parameter based on the degree of loss, and determine the fourth parameter value of the fourth adaptation evaluation parameter based on the equipment technical level parameter.

[0127] Among them, the values ​​of the first parameter, the second parameter, the third parameter, and the fourth parameter represent the degree of matching of the current device fault record with the first, second, third, and fourth matching evaluation parameters, respectively. The values ​​range from 0 to 1, and the larger the value, the higher the degree of matching.

[0128] Understandably, the voltage level in the equipment fault record is compared with the conditions of the first adaptation evaluation parameter. When the voltage level meets the conditions of the first adaptation evaluation parameter, the value of the first parameter is set to 1; otherwise, it is set to 0. For example, if the first adaptation evaluation parameter is "voltage level is higher than the preset high voltage threshold", and the preset high voltage threshold is set to 35kV, when the voltage level in the equipment fault record is 110kV, the voltage level is higher than the preset high voltage threshold, and the value of the first parameter is set to 1; when the voltage level in the equipment fault record is 10kV, the voltage level is lower than the preset high voltage threshold, and the value of the first parameter is set to 0.

[0129] Similarly, the equipment type identifier in the equipment fault record is compared with the conditions of the second adaptation evaluation parameter to determine the value of the second parameter; the degree of loss in the equipment fault record is compared with the conditions of the third adaptation evaluation parameter to determine the value of the third parameter; and the equipment technical level parameter in the equipment fault record is compared with the conditions of the fourth adaptation evaluation parameter to determine the value of the fourth parameter.

[0130] Step 2113: Based on the values ​​of the first parameter, the second parameter, the third parameter, and the fourth parameter, determine the path fit value of the candidate loss estimation calculation path according to the preset fit calculation rules.

[0131] The preset adaptation calculation rule defines the method for calculating the path adaptation value, which combines the values ​​of the first parameter, the second parameter, the third parameter, and the fourth parameter to obtain the path adaptation value.

[0132] In some embodiments, the preset adaptability calculation rule uses a parameter priority determination method to determine the path adaptability value. The determination is made according to the priority order of the first parameter value, the second parameter value, the third parameter value, and the fourth parameter value. When the first parameter value is 1, the path adaptability value is set to a high adaptability level; when the first parameter value is 0 but the second parameter value is 1, the path adaptability value is set to a medium adaptability level; and when both the first and second parameter values ​​are 0 but either the third or fourth parameter value is 1, the path adaptability value is set to a low adaptability level. For example, when the first parameter value is 1, regardless of the values ​​of the second, third, and fourth parameters, the path adaptability value is set to a high adaptability level, indicating that the candidate loss estimation calculation path meets the adaptability conditions in the voltage level dimension, and this candidate loss estimation calculation path is selected first.

[0133] In other embodiments, the preset adaptability calculation rule uses a parameter matching degree accumulation method to determine the path adaptability value. The first, second, third, and fourth parameter values ​​are combined with preset parameter weights to accumulate and calculate the path adaptability value. The preset parameter weights are determined based on the degree of influence of the adaptability evaluation parameters on the loss estimation calculation path selection. Voltage level has the greatest influence on the loss estimation calculation path selection, and the preset parameter weight corresponding to the first parameter value is the highest. Equipment type identifier has the next greatest influence, and the preset parameter weight corresponding to the second parameter value is the second highest. The degree of loss and equipment technical level parameters have relatively less influence on the loss estimation calculation path selection, and the preset parameter weights corresponding to the third and fourth parameter values ​​are relatively low. By setting the preset parameter weights, the path adaptability value can comprehensively reflect the matching situation of multiple adaptability evaluation parameters, avoiding path selection deviations caused by matching a single parameter.

[0134] It is easy to understand that by designing diverse pre-set adaptation calculation rules, one can either use a priority judgment method to highlight the decisive role of key parameters, or use a matching degree accumulation method to comprehensively consider the influence of multiple parameters, making the selection of loss estimation calculation path more flexible and accurate.

[0135] It should be noted that the preset path adaptation rule base stores the correspondence between multiple candidate loss calculation paths and adaptation evaluation parameters.

[0136] Multiple candidate loss estimation calculation paths include a first candidate path based on the asset depreciation model, a second candidate path based on the loss assessment standard library query, and a third candidate path based on the line loss estimation unit parameters.

[0137] The first candidate path is suitable for high-voltage, high-tech, and heavily damaged equipment. It calculates the depreciated value of the equipment based on the asset depreciation model by querying the equipment's original asset parameter set, and then determines the preliminary loss estimate based on the degree of loss. The second candidate path is suitable for low-voltage, highly standardized equipment. It obtains standard loss estimate data for the equipment from the loss assessment standard library as the preliminary loss estimate. The third candidate path is suitable for line equipment. It calculates the preliminary loss estimate based on the loss quantity data by querying the line loss assessment unit parameters.

[0138] The adaptation evaluation parameters corresponding to the first candidate path include a voltage level higher than the preset high voltage threshold, equipment technical level parameters belonging to the high technical level, and loss degree belonging to the severe loss.

[0139] The preset high-voltage threshold is used to distinguish between high-voltage and low-voltage equipment. The preset high-voltage threshold can be set to 35kV or 20kV. High-tech level refers to equipment with higher technical specifications, manufacturing processes, and technical standards. For example, a high-tech level transformer includes features such as a capacity greater than 10000kVA, the use of imported technology, and compliance with international standards. Severe loss refers to the degree of damage to the equipment. For example, severe losses to a transformer include damage such as burnout and insulation breakdown.

[0140] Understandably, when the voltage level recorded in the equipment fault record is higher than the preset high-voltage threshold, the equipment's technical level parameters are of a high technical level, and the degree of loss is a severe loss, the path fit value of the first candidate path is high, and the first candidate path is more likely to be selected as the loss estimation calculation path. The first candidate path calculates the depreciated value of the equipment through an asset depreciation model, so that the estimated loss value can reflect the actual asset status of the equipment and avoid the loss estimation deviation caused by calculating according to a fixed proportion of the original value of the equipment.

[0141] The adaptation evaluation parameters for the second candidate path include a voltage level lower than the preset low voltage threshold and a device type identifier indicating that it belongs to standardized equipment.

[0142] The preset low-voltage threshold is used to distinguish between low-voltage and high-voltage equipment. The preset low-voltage threshold can be set to 20kV or 10kV. Standardized equipment refers to equipment with a high degree of standardization in specifications, models, and technical parameters, and with a large market circulation, such as distribution transformers, switchgear, and surge arresters.

[0143] Understandably, when the voltage level of the equipment fault record is lower than the preset low-voltage threshold and the equipment type is identified as standardized equipment, the path fit value of the second candidate path is higher, and the second candidate path is more likely to be selected as the damage estimation calculation path. The damage estimation data of standardized equipment is already recorded in the damage assessment standard library. By querying the damage assessment standard library to obtain standard damage estimation data as the initial damage estimation value, the calculation efficiency is high and the damage estimation data is accurate, avoiding the inefficiency and data deviation caused by manual assessment or complex calculation.

[0144] The adaptation evaluation parameters for the third candidate path include the equipment type identifier belonging to the line type and the geographical area identifier belonging to the preset dense line area.

[0145] The types of lines include cables, cable joints, cable terminations, hardware, conductors, and other line-related equipment. Pre-defined densely populated areas refer to geographical areas with a high density of lines and long line lengths, such as urban centers and industrial parks.

[0146] Understandably, when the equipment type identifier in the equipment fault record belongs to the line type and the geographical area identifier belongs to the preset dense line area, the path fit value of the third candidate path is high, and the third candidate path is more likely to be selected as the loss calculation path. The loss calculation of line-type equipment adopts a method that combines line loss estimation unit parameters with loss quantity data. The line loss estimation unit parameters distinguish the differences between different geographical areas based on the geographical area identifier, so that the loss value can reflect the cost differences of geographical areas and avoid the loss estimation deviation caused by using uniform parameters for calculation.

[0147] Step 212: Determine the candidate loss calculation path with the largest path fit value as the loss calculation path.

[0148] Understandably, the path fit values ​​of multiple candidate loss estimation paths are compared, and the candidate loss estimation path with the highest path fit value is selected as the loss estimation path. For example, if the path fit value of the first candidate path corresponds to a high fit level, the path fit value of the second candidate path corresponds to a low fit level, and the path fit value of the third candidate path corresponds to a medium fit level, then the first candidate path is determined as the loss estimation path.

[0149] It's easy to understand that by calculating and comparing path fit values, the automatic selection of damage calculation paths is achieved. This ensures that equipment fault records with different characteristics use the most suitable damage calculation method, avoiding estimation errors caused by using a uniform method. The quantitative evaluation of path fit values ​​makes the selection of damage calculation paths traceable and adjustable. When an inappropriate damage calculation path is found, the path selection logic can be corrected by adjusting preset path fit rules or preset parameter weights.

[0150] Step 220: Process the equipment fault records according to the damage calculation path to obtain the preliminary damage estimate.

[0151] The preliminary loss estimate is the loss estimate data obtained by calculating the equipment failure records according to the loss estimate calculation path. The preliminary loss estimate serves as the initial basis for insurance claims and is used before being submitted to the insurance brokerage server for review.

[0152] Specific step 220 includes steps 221 to 223:

[0153] Step 221: If the loss calculation path corresponds to the first candidate path, query and obtain the original set of asset parameters based on the faulty equipment identifier, determine the asset depreciation parameters based on the original set of asset parameters, and determine the preliminary loss estimate based on the asset depreciation parameters and the degree of loss.

[0154] It should be noted that high-voltage equipment has a high original asset value and a long service life, and depreciation occurs during its use. Traditional methods calculate the estimated loss value based on a fixed percentage of the original asset value, without considering depreciation, resulting in an estimated loss value higher than the actual net asset value of the equipment. This application, by querying the original asset parameter set of the equipment and calculating the asset depreciation parameters based on an asset depreciation model, ensures that the preliminary estimated loss value reflects the actual net asset value of the equipment, avoiding insurance claim disputes caused by an overestimation of the loss value.

[0155] The faulty equipment identifier is a unique identifier for the equipment recorded in the equipment fault log. The original asset parameter set includes asset information such as the original value of the equipment, the date of recording, the estimated useful life, and the depreciation method. The original asset parameter set is retrieved from the asset management platform based on the faulty equipment identifier.

[0156] Asset depreciation parameters are used to calculate the net asset value of equipment after depreciation. These parameters include accumulated depreciation, depreciation rate, and years of use. Based on the original value, accounting date, estimated useful life, and depreciation method in the asset's original parameter set, the asset depreciation parameters are determined according to the depreciation calculation rules.

[0157] In some embodiments, the depreciation calculation rule adopts the straight-line depreciation method, and the accumulated depreciation amount is calculated from the original value, the estimated useful life, and the years used. The years used are calculated from the time difference between the current date and the accounting date.

[0158] In other embodiments, the depreciation calculation rule adopts the straight-line depreciation method or the double-declining balance method, and the depreciation calculation rule is determined according to the depreciation method field in the original parameter set of the asset.

[0159] The preliminary loss estimate is determined based on asset depreciation parameters and the degree of loss. In some embodiments, the preliminary loss estimate is calculated using the original value, accumulated depreciation, and the loss percentage corresponding to the degree of loss. The loss percentage corresponding to the degree of loss is determined based on the value of the loss degree field; for example, the loss percentage is 100% for a loss degree of "burnt," 60% for a loss degree of "water damage," and 20% for a loss degree of "damaged casing."

[0160] It is easy to understand that by calculating the preliminary loss value through the asset depreciation model, the loss value can reflect the actual net asset value and degree of loss of the equipment, avoiding the overestimation of loss caused by calculating it as a fixed percentage of the original value of the equipment, and providing a more accurate basis for insurance claims.

[0161] It should be noted that the embodiments of this application also include steps B1 to B5:

[0162] Step B1: Identify the identifier format type and identifier source system type from the faulty device identifier.

[0163] It should be noted that the power grid monitoring platform comprises multiple subsystems, and the fault equipment identifiers recorded by different subsystems have different formats. For example, the fault equipment identifier recorded by the main grid equipment monitoring platform is a 12-digit numerical code, while the fault equipment identifier recorded by the distribution network equipment monitoring platform is a string combining the equipment name and geographical location. Traditional methods cannot recognize fault equipment identifiers in different formats, leading to query failures or inaccurate query results when retrieving the original parameter set of assets from the asset management platform, affecting the calculation of the preliminary loss estimate. This application identifies the identifier format type and the identifier source system type, and converts the fault equipment identifier into a standard equipment code according to the identifier conversion rules, enabling fault equipment identifiers in different formats to be accurately queried in the asset management platform, avoiding query failures caused by differences in identifier formats.

[0164] The identifier format type is used to distinguish the encoding format of faulty equipment identifiers. Identifier format types include numeric encoding formats, string combination formats, and mixed encoding formats. The identifier source system type is used to distinguish the source system of faulty equipment identifiers. Identifier source system types include main network equipment monitoring platforms, distribution network equipment monitoring platforms, asset management platforms, etc.

[0165] Understandably, the identifier format type can be identified by analyzing the character composition, character length, and separators of the faulty device identifier. The source system type can be identified by analyzing the data source field of the device fault record or the prefix of the faulty device identifier. For example, if the faulty device identifier is "110234567890", with a character length of 12 digits and consisting entirely of numbers, the identifier format type is identified as a numeric encoding format. Based on the prefix "110", the source system type is identified as the main network device monitoring platform.

[0166] Step B2: Based on the identifier format type and the identifier source system type, query the preset identifier mapping rule library for the identifier conversion rule corresponding to the combination of identifier format type and identifier source system type.

[0167] The preset identifier mapping rule base stores the correspondence between identifier format type, identifier source system type, and identifier conversion rules. The identifier conversion rules define the conversion method for converting faulty device identifiers into standard device codes.

[0168] Understandably, the identified identifier format type and identifier source system type are used as query conditions to retrieve the corresponding identifier conversion rule from the preset identifier mapping rule library. For example, if the identifier format type is a digital encoding format and the identifier source system type is the main network equipment monitoring platform, the retrieved identifier conversion rule would be "extract the last 10 digits of the faulty equipment identifier as the standard equipment code".

[0169] Step B3: Convert the faulty device identifier into a standard device code according to the identifier conversion rules.

[0170] The standard equipment code is a unique identifier for equipment recorded in the asset management platform. The standard equipment code has a unified and standardized format and can be used to query the asset information of equipment from the asset management platform.

[0171] Understandably, the faulty device identifier is processed according to the identifier conversion rules to obtain the standard device code. For example, if the faulty device identifier is "110234567890", the identifier conversion rule is "to extract the last 10 digits of the faulty device identifier as the standard device code", and the standard device code "0234567890" is obtained by extracting the last 10 digits according to the identifier conversion rules.

[0172] Step B4: Query the asset management platform to obtain the equipment asset code and asset status parameter set based on the standard equipment code.

[0173] Among them, the equipment asset code is a unique identifier for the asset recorded in the asset management platform, and the asset status parameter set includes asset information such as the original value of the asset, the date of recording, the estimated useful life, the depreciation method, and the asset status.

[0174] Understandably, the standard equipment code is used as a query condition to retrieve the corresponding equipment asset code and asset status parameter set from the asset database of the asset management platform. Upon successful query, the equipment asset code and asset status parameter set are returned as components of the original asset parameter set.

[0175] Step B5: If the asset management platform returns multiple candidate asset records, extract the fault occurrence time from the equipment fault record, perform time matching verification between the fault occurrence time and the valid asset time period of the candidate asset record, and establish a relationship between the candidate asset records that pass the time matching verification.

[0176] It should be noted that some equipment may undergo replacement or modification during use, resulting in multiple candidate asset records corresponding to the same standard equipment code, with different valid asset time periods for each record. Traditional methods cannot distinguish between multiple candidate asset records, leading to inaccurate sets of original asset parameters and affecting the accuracy of asset depreciation calculations and preliminary loss estimates. This application addresses this issue by using a time-matching verification between the fault occurrence time and the asset's valid time period. Candidate asset records that pass the time-matching verification are selected, ensuring that the retrieved set of original asset parameters accurately reflects the actual asset status of the equipment at the time of the fault, thus avoiding loss estimation errors caused by incorrect asset record selection.

[0177] The candidate asset records are multiple asset records returned by the asset management platform. Each candidate asset record includes an asset validity period field, which records the start and end times of the asset record's validity. The fault occurrence time is extracted from the fault time field of the equipment fault record.

[0178] Understandably, the time of the failure is compared with the valid time period of each candidate asset record. When the time of the failure is within the valid time period of the asset, the time matching verification is deemed to be successful. The candidate asset record that has passed the time matching verification is selected to establish an association, and the equipment asset code and asset status parameter set of the candidate asset record are used as the original asset parameter set.

[0179] For example, the asset management platform returns two candidate asset records. The first candidate asset record has a valid asset period from January 1, 2010 to December 31, 2020, and the second candidate asset record has a valid asset period from January 1, 2021 to December 31, 2030. The failure occurred on August 1, 2024. The failure occurred within the valid asset period of the second candidate asset record. The second candidate asset record is selected to establish an association.

[0180] Step 222: If the damage calculation path corresponds to the second candidate path, obtain the standard damage estimation data based on the equipment fault record as the preliminary damage estimation value.

[0181] It should be noted that low-voltage, highly standardized equipment is frequently used in insurance claims. Insurance companies have established a loss assessment standard database to record standard loss estimates for different equipment types, specifications, and levels of loss. Traditional methods for determining loss estimates for standardized equipment still rely on manual assessment or complex calculations, which is inefficient and results in discrepancies between the estimated loss values ​​and the standard loss estimates in the database, affecting the consistency and efficiency of insurance claims. This application directly queries the loss assessment standard database to obtain standard loss estimates as preliminary loss values, avoiding the inefficiency caused by manual assessment or complex calculations. This ensures that the loss estimates for standardized equipment are consistent with the insurance company's loss assessment standards, reducing loss assessment disputes during the insurance claims process.

[0182] The damage assessment standard database stores the correspondence between equipment type identifiers, equipment specifications, damage levels, and standard damage assessment data. The standard damage assessment data serves as a reference for equipment damage assessment determined by insurance companies based on factors such as market conditions, repair costs, and replacement costs.

[0183] Understandably, the equipment type identifier, equipment specifications, and degree of damage are extracted from the equipment failure records. These identifiers are then used as query criteria to retrieve the corresponding standard damage assessment data from the damage assessment standard library, which is then used as the preliminary damage assessment value.

[0184] It is easy to understand that by querying the damage assessment standard library to obtain standard damage assessment data, the damage assessment calculation process for standardized equipment is simplified, the damage assessment efficiency is improved, and the damage assessment value is consistent with the damage assessment standards of insurance companies, thus providing a guarantee for the smooth progress of insurance claims.

[0185] Step 223: When the loss calculation path corresponds to the third candidate path, extract the loss quantity data from the equipment fault record, query the line loss estimation unit parameters according to the geographical area identifier, and determine the preliminary loss estimate based on the line loss estimation unit parameters and the loss quantity data.

[0186] It should be noted that the loss calculation for line equipment differs from that for other equipment, and the estimated loss value for line equipment is directly related to the quantity of loss. Traditional methods use a holistic approach to assess line equipment, failing to differentiate between line unit parameters across different geographical regions, leading to significant discrepancies between estimated and actual losses. For instance, construction and material costs are higher in urban centers, resulting in higher estimated loss unit parameters compared to suburban areas. Traditional methods using uniform line loss unit parameters lead to underestimation of losses in urban centers and overestimation in suburban areas. This application queries line loss unit parameters based on geographical region identifiers, ensuring that line equipment in different geographical regions uses line loss unit parameters that align with the cost level of that region. This avoids the estimation bias caused by using uniform line loss unit parameters, ensuring that the estimated loss value accurately reflects the actual losses in different geographical regions.

[0187] The loss quantity data records the number of losses of line-type equipment, such as 2 cable intermediate joints, 3 cable terminal heads, and 10 sets of hardware. The loss quantity data is extracted from the quantity field of the equipment failure records.

[0188] The line damage estimation unit parameters include unit numerical data for different geographical regions and line types. The corresponding unit numerical data is retrieved from the line damage estimation unit parameter database based on the geographical region identifier. For example, if the geographical region identifier is "city center" and the line type is "cable joint," the retrieved unit numerical data will be the correct value.

[0189] Understandably, the preliminary loss estimate is obtained by combining the unit value data in the line loss estimation unit parameters with the loss quantity data.

[0190] In summary, step 200 calculates the path fit values ​​of multiple candidate loss calculation paths according to preset path adaptation rules based on the voltage level, equipment type identifier, loss degree, and equipment technical level parameters in the equipment fault record. The candidate loss calculation path with the highest path fit value is determined as the loss calculation path. When the loss calculation path corresponds to the first candidate path, the original asset parameter set is queried through the faulty equipment identifier, and a preliminary loss value is determined based on the asset depreciation parameters and loss degree. This ensures that the loss value of high-voltage equipment can reflect the actual net asset value of the equipment, avoiding overestimation caused by calculating based on a fixed percentage of the original equipment value. When the loss calculation path corresponds to the second candidate path, standard loss data is queried from the loss assessment standard library as the preliminary loss value, improving the loss calculation efficiency of standardized equipment and ensuring that the loss value is consistent with the insurance company's loss assessment standards. When the loss calculation path corresponds to the third candidate path, a preliminary loss value is determined based on the line loss assessment unit parameters and loss quantity data, ensuring that the loss value of line-type equipment can reflect cost differences in different geographical areas. Different loss calculation paths are adapted to the loss calculation needs of high-voltage equipment, standardized equipment, and line equipment, respectively, avoiding loss calculation errors caused by using a uniform loss calculation method, and providing accurate loss calculation data for sending the preliminary loss value to the insurance brokerage server in step 300.

[0191] Step 300: Send the preliminary loss estimate to the insurance brokerage server and receive the verified loss estimate returned by the insurance brokerage server.

[0192] The insurance brokerage server is a server deployed by a third-party insurance brokerage company. The insurance brokerage company reviews the initial loss estimate based on insurance claim requirements and provides the reviewed loss estimate as a reference for insurance claims. The reviewed loss estimate is the loss estimate data given by the insurance brokerage company after evaluating factors such as the initial loss estimate, equipment failure records, and insurance claim standards.

[0193] Understandably, the preliminary loss estimate calculated in step 200 is sent to the insurance brokerage server via a data interface. The sent data includes the preliminary loss estimate, equipment type identifier from the equipment failure record, voltage level, degree of loss, and geographical region identifier. After receiving the preliminary loss estimate and related information, the insurance brokerage server's professionals review the preliminary loss estimate based on their insurance claims experience and loss assessment standards to evaluate its reasonableness and accuracy.

[0194] It should be noted that during the review process, insurance brokerage companies may discover discrepancies between the initial loss estimates for some equipment and the insurance claim standards. For example, the initial loss estimates for some equipment may exceed the insurance company's maximum loss assessment limit, or the assessment of the extent of loss for some equipment may not match the actual situation. Based on the review results, the insurance brokerage company adjusts the initial loss estimates, generates a reviewed loss estimate, and returns it through a data interface.

[0195] The system receives the reviewed loss estimate returned by the insurance brokerage server, associates and stores the reviewed loss estimate with the preliminary loss estimate, and provides a data basis for calculating the loss estimate offset in step 400.

[0196] It is easy to understand that by sending the preliminary loss estimate to the insurance broker's server for review, the loss estimate is verified before the formal claim is filed. This allows for a consensus between the preliminary loss estimate and the insurance company's loss assessment standards in advance, avoiding repeated negotiations and delays in claims processing due to excessive deviations in the loss estimate data after the claim is filed. This provides accurate review loss estimate data for the calculation of the loss estimate offset and the generation of the loss estimate statistics table in step 400.

[0197] In summary, step 300 sends the preliminary loss estimate to the insurance brokerage server and receives the verified loss estimate returned by the insurance brokerage server. The verification process ensures that the preliminary loss estimate is verified before the formal claim is filed, providing data support for the calculation of the loss estimate offset.

[0198] Step 400: Calculate the loss offset between the preliminary loss estimate and the verified loss estimate, and generate a loss estimate statistics table based on the loss offset.

[0199] It should be noted that there is a discrepancy between the preliminary loss estimate and the reviewed loss estimate. The magnitude and distribution of this discrepancy reflect the accuracy of the loss calculation path selection and the rationality of the loss calculation rules. Traditional methods do not quantitatively analyze the discrepancy between the preliminary and reviewed loss estimates, resulting in the inability to identify errors in the loss calculation path selection and the failure to promptly detect and correct deviations in the loss calculation rules. This application quantifies and visualizes the discrepancy between the preliminary and reviewed loss estimates by calculating the loss offset and generating a loss statistics table, providing data support for adjusting the loss calculation path and optimizing the loss calculation rules.

[0200] Specifically, step 400 includes steps 410 and 420:

[0201] Step 410: Calculate the loss offset between the preliminary loss estimate and the verified loss estimate.

[0202] The estimated loss offset is the difference between the preliminary estimated loss value and the reviewed estimated loss value. The value of the estimated loss offset reflects the accuracy of the preliminary estimated loss value. When the estimated loss offset is positive, it means that the preliminary estimated loss value is higher than the reviewed estimated loss value; when the estimated loss offset is negative, it means that the preliminary estimated loss value is lower than the reviewed estimated loss value; when the estimated loss offset is zero, it means that the preliminary estimated loss value and the reviewed estimated loss value are consistent.

[0203] Understandably, for each equipment failure record, the preliminary estimated damage value calculated in step 200 is compared with the verified estimated damage value received in step 300, and the difference between the preliminary estimated damage value and the verified estimated damage value is calculated to obtain the estimated damage offset.

[0204] Step 420: Generate a loss estimation statistics table based on the estimated loss offset.

[0205] The estimated damage statistics table is a data table that records information such as equipment failure records, preliminary estimated damage values, verified estimated damage values, and estimated damage offsets. The estimated damage statistics table is used to store and display estimated damage data, providing data support for estimated damage analysis and claims processes.

[0206] Specifically, step 420 includes steps 421 to 425:

[0207] Step 421: Create the data structure for the estimated damage statistics table. The data structure for the estimated damage statistics table consists of a set of equipment information fields, a set of estimated damage data fields, and a set of offset analysis fields.

[0208] The equipment information field set stores basic information about equipment fault records, including equipment identification, equipment type identification, voltage level, degree of damage, and geographical area identification. The damage estimation data field set stores damage estimation calculation results, including the first damage estimation field and the second damage estimation field. The offset analysis field set stores analytical data such as damage estimation offset and offset rate, including the offset field and the offset rate field.

[0209] Understandably, a damage estimation statistics table is created according to the preset data table structure definition, and field spaces are allocated for the equipment information field set, the damage estimation data field set, and the offset analysis field set to provide data structure support for data writing.

[0210] Step 422: Extract equipment identification information from equipment fault records and write the equipment identification information into the equipment information field set.

[0211] The equipment identification information includes information used to identify the equipment, such as faulty equipment identification, equipment type identification, voltage level, degree of loss, and geographical area identification.

[0212] Understandably, equipment identification information is extracted from the equipment fault records obtained in step 100 and written into the equipment information field set of the damage estimation statistics table, enabling the damage estimation statistics table to record the basic information of each equipment fault record. For example, the fault equipment identifier "0234567890", equipment type identifier "distribution transformer", voltage level "10kV", loss degree "water damage", and geographical area identifier "a certain county power supply company" are extracted from the equipment fault records, and this equipment identification information is written into the equipment information field set.

[0213] Step 423: Write the preliminary loss estimate into the first loss estimate field in the loss estimate data field set, and write the verified loss estimate into the second loss estimate field in the loss estimate data field set.

[0214] The first loss estimate field is used to store the initial loss estimate, and the second loss estimate field is used to store the verification loss estimate.

[0215] It is understandable that the preliminary estimated loss value calculated in step 200 is written into the first estimated loss field in the estimated loss data field set of the estimated loss statistics table, and the reviewed estimated loss value received in step 300 is written into the second estimated loss field in the estimated loss data field set.

[0216] Step 424: Write the estimated loss offset into the offset field of the offset analysis field set.

[0217] The offset field is used to store the estimated loss offset calculated in step 410.

[0218] It is understandable that the estimated loss offset calculated in step 410 is written into the offset field of the offset analysis field set in the estimated loss statistics table.

[0219] Step 425: Determine the offset rate data based on the estimated loss offset and the preliminary estimated loss value, and write the offset rate data into the offset rate field in the offset analysis field set.

[0220] The offset rate data is the ratio of the estimated loss offset to the initial loss estimate, reflecting the relative deviation of the initial loss estimate. The offset rate field is used to store the offset rate data.

[0221] It is understandable that the ratio of the estimated loss offset to the initial estimated loss value is used as the offset rate data, and the offset rate data is written into the offset rate field in the offset analysis field set of the estimated loss statistics table.

[0222] It's easy to understand that by creating a damage estimation statistics table data structure and writing equipment identification information, preliminary damage estimates, verified damage estimates, damage offsets, and offset rates, the damage estimation data is stored in a structured manner, providing data support for querying, analyzing, and displaying the damage estimation data. The offset and offset rate fields in the damage estimation statistics table quantify the damage estimation deviation, providing a quantitative basis for adjusting the damage estimation calculation path and optimizing the damage estimation calculation rules.

[0223] It should be noted that, in an optional implementation, after generating the estimated loss statistics table based on the estimated loss offset in step 420, steps C1 to C4 are further included:

[0224] Step C1: Extract the preliminary and verification loss values ​​from multiple equipment records in the loss estimation statistics table.

[0225] Among them, multiple equipment records are all equipment failure records recorded in the damage estimation statistics table. Each equipment record includes equipment identification information, preliminary damage estimate, verified damage estimate, damage offset, offset rate data, and other information.

[0226] Understandably, retrieving the preliminary and verified damage estimates from all equipment records in the damage estimate statistics table provides a data basis for the statistical analysis of damage estimate deviations.

[0227] Step C2: Count the number of equipment records whose preliminary damage estimate is greater than the verified damage estimate, and determine the overestimation percentage based on the number of equipment records and the total number of equipment failure records.

[0228] It should be noted that when the preliminary loss estimate is greater than the verified loss estimate, it indicates an overestimation tendency in the selection of the loss calculation path or the loss calculation rule. Traditional methods do not perform statistical analysis on this overestimation tendency, resulting in the inability to identify biases in the selection of the loss calculation path and to detect overestimation tendencies in the loss calculation rule in a timely manner. This application quantifies the accuracy of the loss calculation path selection by statistically analyzing the number of equipment records where the preliminary loss estimate is greater than the verified loss estimate and calculating the overestimation percentage. When the overestimation percentage exceeds a preset overestimation percentage threshold, an adjustment to the loss calculation path is triggered, enabling automatic identification and correction of errors in the selection of the loss calculation path.

[0229] The equipment record count refers to the number of equipment records whose initial estimated damage value is greater than the verified estimated damage value. The total number of equipment failure records refers to the total number of equipment failure records recorded in the damage estimation statistics table. The overestimation percentage is the ratio of the equipment record count to the total number of equipment failure records.

[0230] Understandably, the preliminary loss estimate is compared with the verified loss estimate item by item in the loss estimate statistics table. When the preliminary loss estimate is greater than the verified loss estimate, the equipment record is added to the equipment record count. After the statistics are completed, the ratio of the number of equipment records to the total number of equipment failure records is used as the overestimation percentage.

[0231] Step C3: If the overestimation percentage is greater than the preset overestimation percentage threshold, extract the loss calculation path corresponding to the preliminary loss estimate and generate a path adjustment identifier.

[0232] The preset overestimation percentage threshold is used to determine whether the loss calculation path needs to be adjusted. The preset overestimation percentage threshold is determined according to the accuracy requirements of insurance claims and can be set to 50%, 60%, or 70%. The path adjustment identifier is used to mark the loss calculation path that needs to be adjusted.

[0233] Understandably, the overestimation percentage is compared with a preset overestimation threshold. When the overestimation percentage exceeds the threshold, the corresponding loss calculation path is extracted from the loss estimation statistics table for equipment records whose preliminary loss estimate is greater than the reviewed loss estimate. The distribution of these loss calculation paths is analyzed, and frequently occurring loss calculation paths are identified, generating path adjustment flags for these paths. For example, if the preset overestimation threshold is 60% and the overestimation percentage is 70%, 70 equipment records with preliminary loss estimates greater than the reviewed loss estimate are extracted from the loss estimation statistics table. It is found that 50 of these records use the first candidate path, and path adjustment flags are generated for the first candidate path.

[0234] Step C4: Modify the rule parameters in the loss calculation path based on the path adjustment identifier.

[0235] It should be noted that the overestimation tendency in loss calculation paths may stem from improper rule parameter settings, such as setting the depreciation rate too low or the loss ratio too high. Traditional methods cannot automatically adjust rule parameters based on the distribution of loss offsets, resulting in a persistent overestimation tendency in loss calculation paths and affecting the accuracy of loss estimation data. This application identifies the loss calculation path requiring adjustment using path adjustment markers, analyzes the correlation between the rule parameters of this loss calculation path and the loss offset, and modifies the rule parameters to correct the overestimation tendency of the loss calculation path, thereby improving the accuracy of loss estimation data.

[0236] Among them, the rule parameters are the parameters that affect the calculation of the preliminary loss value in the loss calculation path, such as the depreciation rate and loss ratio in the first candidate path, the standard loss data in the second candidate path, and the line loss unit parameters in the third candidate path.

[0237] Understandably, based on the path adjustment identifier, the estimated loss calculation path that needs adjustment is located. The estimated loss offset and offset rate data corresponding to this path are extracted from the estimated loss statistics table. The distribution characteristics of the estimated loss offset and offset rate data are analyzed to identify the rule parameters that lead to overestimation. These rule parameters are then modified, such as reducing the loss ratio, increasing the depreciation rate, or adjusting the line estimated loss unit parameters, so that the modified rule parameters can reduce the estimated loss offset and lower the overestimation percentage.

[0238] It is easy to understand that by statistically analyzing the overestimation rate and generating path adjustment indicators, errors in the selection of loss calculation paths can be automatically identified. By modifying rule parameters, the overestimation tendency of loss calculation paths can be corrected, forming a self-adjusting capability for loss calculation paths and improving the accuracy of loss data and the rationality of loss calculation rules.

[0239] In another optional implementation, after generating the estimated loss statistics table based on the estimated loss offset, steps D1 to D5 are further included:

[0240] Step D1: Send the estimated damage statistics table to the on-site survey terminal.

[0241] Among them, the field survey terminal is a mobile terminal device carried by the survey personnel. The field survey terminal is used to receive the damage estimation statistics table, record the field survey data, and upload the survey record data.

[0242] Understandably, sending the estimated damage statistics table to the field survey terminal via the data interface allows surveyors to view equipment identification information, preliminary estimated damage value, and verified estimated damage value in the estimated damage statistics table during the field survey process, providing data reference for the field survey.

[0243] Step D2: Receive the exploration record data uploaded by the field exploration terminal. The exploration record data consists of a list of exploration equipment and exploration confirmation results.

[0244] It should be noted that on-site investigation is a crucial step in the insurance claims process. Investigators arrive at the site of the faulty equipment to verify the actual damage, and the investigation results serve as the basis for determining the assessed loss. Traditional methods separate investigation records from the estimated loss statistics table, making it impossible to directly link the two and increasing the workload of data integration. This application addresses this by uploading investigation record data through an on-site investigation terminal, automatically linking the data with the estimated loss statistics table, and providing data support for investigation comparison and loss assessment determination.

[0245] The equipment list is a list of equipment actually inspected by the surveying personnel during the on-site survey. The equipment list includes equipment identification information, survey time, and survey location. The survey confirmation result is the surveying personnel's confirmation of the equipment damage situation. The survey confirmation result includes information such as damage confirmation, damage extent confirmation, and on-site photos.

[0246] Understandably, during the on-site exploration process, the exploration personnel record the list of exploration equipment and the exploration confirmation results through the on-site exploration terminal. After the exploration is completed, they upload the exploration record data through the data interface and receive the exploration record data uploaded by the on-site exploration terminal.

[0247] Step D3: Compare the equipment failure records in the exploration equipment list with those in the estimated damage statistics table to generate an exploration comparison table.

[0248] It should be noted that the equipment failure records in the estimated damage statistics table originate from the power grid monitoring platform. Some equipment failure records may contain false alarms or duplicate records, leading to discrepancies between the number of equipment in the estimated damage statistics table and the actual number of damaged equipment. Traditional methods do not compare the equipment failure records in the estimated damage statistics table with the equipment identified during on-site investigation, resulting in the inability to identify false alarms or duplicate records and affecting the accuracy of the damage assessment data. This application compares the equipment failure records in the estimated damage statistics table with the list of investigated equipment, identifying equipment not investigated in the estimated damage statistics table and equipment in the list of investigated equipment not recorded in the estimated damage statistics table, generating an investigation comparison table. This directly presents the differences between the estimated damage statistics table and the on-site investigation records, providing a basis for correcting the estimated damage data.

[0249] The exploration comparison table is a data table that records the equipment failure records in the estimated damage statistics table and the list of explored equipment. The exploration comparison table includes information such as the list of explored equipment, the list of unexplored equipment, and the list of newly explored equipment.

[0250] Understandably, the equipment identification information in the exploration equipment list is compared one by one with the equipment identification information in the equipment failure records of the estimated damage statistics table. When a corresponding record exists in the estimated damage statistics table for the equipment identification information in the exploration equipment list, the equipment record is marked as explored equipment and added to the explored equipment list. When no corresponding record exists in the exploration equipment list for the equipment failure record in the estimated damage statistics table, the equipment record is marked as unexplored equipment and added to the unexplored equipment list. When no corresponding record exists in the estimated damage statistics table for the equipment identification information in the exploration equipment list, the equipment record is marked as newly added exploration equipment and added to the newly added exploration equipment list. After the comparison is completed, the explored equipment list, the unexplored equipment list, and the newly added exploration equipment list are integrated to generate an exploration comparison table.

[0251] Step D4: Based on the survey and confirmation results, perform a correction operation on the preliminary loss estimate in the loss estimate statistics table to obtain the on-site loss verification value.

[0252] It should be noted that both the preliminary and verified damage estimates are based on equipment failure records and have not been verified through on-site inspection. Therefore, they may deviate from the actual damage to the equipment. On-site inspection involves physically verifying the damaged parts, extent, and range of the equipment to obtain actual damage data. The inspection results serve as the basis for determining the verified damage value. Traditional methods directly use the preliminary or verified damage estimates as the verified damage value without correcting them based on the inspection results, leading to discrepancies between the verified damage value and the actual damage. This application corrects the preliminary damage estimates in the damage statistics table based on the inspection results, ensuring that the verified damage value reflects the actual damage to the equipment, improving the accuracy of the verified damage data and the fairness of insurance claims.

[0253] Among them, the on-site loss assessment value is the loss assessment data obtained after correcting the preliminary loss estimate based on the investigation and confirmation results. The on-site loss assessment value serves as the basis for loss assessment in insurance claims.

[0254] Understandably, the investigation confirmation results are extracted from the investigation record data and correlated with the preliminary loss estimates recorded in the loss estimate statistics table. When the investigation confirmation results show that the actual damage to the equipment is consistent with the loss extent recorded in the loss estimate statistics table, the preliminary loss estimate is kept unchanged and used as the on-site loss assessment value. When the investigation confirmation results show that the actual damage to the equipment is inconsistent with the loss extent recorded in the loss estimate statistics table, the loss assessment value is recalculated based on the actual damage extent in the investigation confirmation results, and the recalculated loss assessment value is used as the on-site loss assessment value.

[0255] It should be noted that after step D4 corrects the preliminary loss estimate in the loss estimate table based on the survey confirmation results to obtain the on-site loss verification value, it also includes:

[0256] The on-site damage assessment value is sent to a multi-party confirmation server.

[0257] Among them, the multi-party confirmation server is a server that coordinates multiple parties, such as business departments, finance departments, insurance brokerage companies, and insurance companies, to confirm the loss assessment data. The multi-party confirmation server receives the on-site loss assessment value and distributes the on-site loss assessment value to each party for confirmation.

[0258] Understandably, the on-site loss assessment value is sent to a multi-party confirmation server via a data interface. The multi-party confirmation server then distributes the on-site loss assessment value to various parties, including the business department, finance department, insurance brokerage company, and insurance company. Each party reviews and confirms the on-site loss assessment value based on information such as the on-site loss assessment value, survey record data, and insurance claim standards.

[0259] Receive confirmation status data returned by the multi-party confirmation server.

[0260] Among them, the confirmation status data is the confirmation conclusion returned by all parties after reviewing and confirming the on-site loss assessment value. The value of the confirmation status data indicates whether all parties agree that the on-site loss assessment value is the final loss assessment value.

[0261] Understandably, after all parties have completed the on-site loss assessment and confirmation, they submit the confirmation conclusions to the multi-party confirmation server. The multi-party confirmation server then aggregates the confirmation conclusions from all parties to generate confirmation status data, which is returned through a data interface.

[0262] If the value of the confirmed status data is equal to the preset pass mark, the on-site loss verification value is used as the final loss verification value, and a loss verification confirmation document is generated.

[0263] The system includes a pre-defined identifier indicating the agreed-upon on-site loss assessment value by all parties involved. The final loss assessment value, confirmed by all parties, serves as the basis for insurance claims. The loss assessment confirmation document is a formal document recording the final loss assessment value, equipment failure records, survey data, and confirmation opinions from all parties. This document serves as an attachment to the insurance claim application.

[0264] Understandably, the value of the confirmed status data is compared with the preset pass indicator. When the value of the confirmed status data equals the preset pass indicator, it means that all parties agree on the on-site loss assessment value. The on-site loss assessment value is then used as the final loss assessment value. A loss assessment confirmation document is generated according to the preset document template. The loss assessment confirmation document contains information such as the final loss assessment value, equipment failure records, survey record data, and confirmation opinions from all parties.

[0265] Send the loss assessment confirmation document to the insurance claims platform.

[0266] Among them, the insurance claims platform is the insurance claims business processing platform deployed by the insurance company. The insurance claims platform receives loss verification confirmation documents and carries out the insurance claims process.

[0267] Understandably, the loss verification document is sent to the insurance claims platform via a data interface. After receiving the loss verification document, the insurance claims platform conducts insurance claims review and claims payment disbursement processes based on information such as the final loss value, equipment failure records, and survey record data in the loss verification document.

[0268] It is easy to understand that by going through multiple confirmation stages, all parties involved, including the business department, finance department, insurance brokerage company, and insurance company, can reach a consensus on the assessed loss figures. This avoids delays in the insurance claims process caused by disputes over the assessed loss figures. The assessed loss confirmation document serves as the official basis for insurance claims and provides document support for the smooth progress of the insurance claims process.

[0269] In summary, step 400 calculates the loss deviation between the preliminary loss estimate and the verified loss estimate, generates a loss estimate statistics table based on the loss deviation, and quantifies the loss deviation through the offset and offset rate fields, providing a quantitative basis for the analysis of loss estimate data. In one optional implementation, by statistically analyzing the overestimation percentage and generating a path adjustment identifier, errors in the selection of the loss estimate calculation path can be automatically identified, and the overestimation tendency of the loss estimate calculation path can be corrected by modifying the rule parameters. In another optional implementation, the loss estimate statistics table is sent to the field investigation terminal and the investigation record data is received. The differences between the loss estimate statistics table and the field investigation records are directly presented through an investigation comparison table. Based on the investigation confirmation results, the preliminary loss estimate is corrected to obtain the on-site verified loss value. Through a multi-party confirmation process, all parties reach a consensus on the verified loss value, generate a verification confirmation document, and send it to the insurance claims platform, providing verification data and document support for the smooth progress of the insurance claims process.

[0270] Based on the above steps, this application also includes the following embodiments:

[0271] See Figure 3 This is a schematic diagram of the structure of the on-site investigation and damage assessment data processing system provided in this application embodiment. The on-site investigation and damage assessment data processing system includes:

[0272] The data acquisition module is used to obtain equipment fault records from the power grid monitoring platform and extract the voltage level and loss degree from the equipment fault records;

[0273] The path determination module is used to determine the damage calculation path based on the voltage level, and process the equipment fault records according to the damage calculation path to obtain the preliminary damage estimate.

[0274] The data interaction module is used to send the preliminary loss estimate to the insurance brokerage server and receive the verified loss estimate returned by the insurance brokerage server.

[0275] The statistics table generation module is used to calculate the loss offset between the preliminary loss estimate and the verified loss estimate, and to generate a loss statistics table based on the loss offset.

[0276] Figure 3 The apparatus of the illustrated embodiment can be used to perform corresponding actions. Figure 1 The steps in the method embodiments shown are implemented in a similar manner and have similar technical effects, and will not be repeated here.

[0277] See Figure 4 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. The electronic device 40 includes: a processor 41, a memory 42, and a computer program; wherein...

[0278] The memory 42 is used to store computer programs, and the memory may also be flash memory. Computer programs may be, for example, application programs or functional modules that implement the methods described above.

[0279] The processor 41 is used to execute the computer program stored in the memory to implement the various steps performed by the device in the above method. For details, please refer to the relevant descriptions in the preceding method embodiments.

[0280] Alternatively, the memory 42 can be either standalone or integrated with the processor 41.

[0281] When the memory 42 is a device independent of the processor 41, the device may also include:

[0282] Bus 43 is used to connect memory 42 and processor 41.

[0283] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application.

Claims

1. A method for processing nuclear damage data from a site survey, characterized in that, The method comprises the following steps: obtaining a device failure record from a power grid monitoring platform, and extracting a voltage level and a loss degree in the device failure record; extracting a device type identifier, a failure device identifier, a device technical level parameter, and a geographic area identifier from the device failure record; determining an estimated loss calculation path according to the voltage level, comprising: calculating path adaptation degree values of multiple candidate estimated loss calculation paths according to a preset path adaptation rule based on the voltage level, the device type identifier, the loss degree, and the device technical level parameter, comprising: for each candidate estimated loss calculation path, obtaining multiple adaptation evaluation parameters corresponding to the candidate estimated loss calculation path from a preset path adaptation rule library; determining a first parameter value of a first adaptation evaluation parameter based on the voltage level, a second parameter value of a second adaptation evaluation parameter based on the device type identifier, a third parameter value of a third adaptation evaluation parameter based on the loss degree, and a fourth parameter value of a fourth adaptation evaluation parameter based on the device technical level parameter; determining the path adaptation degree value of the candidate estimated loss calculation path according to a preset adaptation degree calculation rule based on the first parameter value, the second parameter value, the third parameter value, and the fourth parameter value; determining the candidate estimated loss calculation path with the largest path adaptation degree value as the estimated loss calculation path; the preset path adaptation rule library stores a corresponding relationship between multiple candidate estimated loss calculation paths and adaptation evaluation parameters; the multiple candidate estimated loss calculation paths include a first candidate path based on an asset depreciation model, a second candidate path based on a loss standard library query, and a third candidate path based on a line estimated loss unit parameter; the adaptation evaluation parameters corresponding to the first candidate path include a voltage level higher than a preset high-voltage threshold, a device technical level parameter belonging to a high technical level, and a loss degree belonging to a severe loss; the adaptation evaluation parameters corresponding to the second candidate path include a voltage level lower than a preset low-voltage threshold and a device type identifier belonging to a standardized device; the adaptation evaluation parameters corresponding to the third candidate path include a device type identifier belonging to a line type and a geographic area identifier belonging to a preset line dense area; processing the device failure record according to the estimated loss calculation path to obtain a preliminary estimated loss value, comprising: in the case of the estimated loss calculation path corresponding to the first candidate path, obtaining an asset original parameter set according to the failure device identifier, determining an asset depreciation parameter based on the asset original parameter set, and determining the preliminary estimated loss value based on the asset depreciation parameter and the loss degree; in the case of the estimated loss calculation path corresponding to the second candidate path, obtaining standard estimated loss data as the preliminary estimated loss value according to the device failure record; in the case of the estimated loss calculation path corresponding to the third candidate path, extracting loss quantity data from the device failure record, querying line estimated loss unit parameters according to the geographic area identifier, and determining the preliminary estimated loss value based on the line estimated loss unit parameters and the loss quantity data; sending the preliminary estimated loss value to an insurance brokerage server and receiving a reviewed estimated loss value returned by the insurance brokerage server; calculating an estimate offset between the preliminary estimate and the recheck estimate, generating an estimate statistics table based on the estimate offset; after the generating of the estimate statistics table based on the estimate offset, further comprising: extracting the preliminary estimate and the recheck estimate of a plurality of device records from the estimate statistics table; counting a number of device records whose preliminary estimate is greater than the recheck estimate, determining an overestimation proportion value based on the number of device records and the total number of device failure records; in a case where the overestimation proportion value is greater than a preset overestimation proportion threshold, extracting the estimate calculation path corresponding to the preliminary estimate, and generating a path adjustment identifier; modifying a rule parameter in the estimate calculation path based on the path adjustment identifier.

2. The method of claim 1, wherein: the obtaining of the device failure records from the power grid monitoring platform comprises: obtaining all failure records in a preset time period from the power grid monitoring platform; extracting a failure cause attribute from the all failure records; performing a matching judgment operation on the failure cause attribute and a preset disaster type list, and taking the failure record with a matching success result of the matching judgment operation as the device failure record.

3. The method of claim 1, wherein, further comprising: identifying an identification format type and an identification source system type from the failure device identifier; querying an identification conversion rule corresponding to a combination of the identification format type and the identification source system type from a preset identification mapping rule library according to the identification format type and the identification source system type; converting the failure device identifier into a standard device code according to the identification conversion rule; querying and obtaining a device asset code and an asset state parameter set from an asset management platform according to the standard device code; in a case where a plurality of candidate asset records are returned by the asset management platform, extracting a failure occurrence time from the device failure record, performing a time matching verification on the failure occurrence time and an asset valid time period of the candidate asset record, and selecting a candidate asset record with a time matching verification pass to establish an association relationship.

4. The method of claim 1, wherein, after the generating of the estimate statistics table based on the estimate offset, further comprising: sending the estimate statistics table to a field investigation terminal; receiving investigation record data uploaded by the field investigation terminal, the investigation record data being composed of an investigation device list and an investigation confirmation result; performing a comparison operation on the investigation device list and the device failure record recorded in the estimate statistics table to generate an investigation comparison table; performing a correction operation on the preliminary estimate in the estimate statistics table according to the investigation confirmation result to obtain a field damage value.

5. The method of claim 1, wherein, further comprising: extracting a power grid type attribute from the device failure record; in a case where the power grid type attribute is a main grid type, receiving full-amount investigation record data uploaded by the field investigation terminal; in a case where the power grid type attribute is a distribution network type, performing a hierarchical operation on the device failure record according to a geographical area identifier and the voltage level to obtain a plurality of device subsets; For each of the device subsets, receive the sampling survey record data uploaded by the field survey terminal, count the number of damaged devices and the number of surveyed devices in the sampling survey record data to determine a subset damage rate; Based on the subset damage rate and the total number of devices corresponding to the device subset, calculate the number of subset damaged devices, and aggregate the number of subset damaged devices of all the device subsets to obtain the overall network damage device number.

6. The method of claim 4, wherein, After the preliminary damage estimation value in the damage estimation statistics table is corrected based on the survey confirmation result to obtain the field damage value, the method further includes: sending the field damage value to a multi-party confirmation server; receiving confirmation state data returned by the multi-party confirmation server; in a case where the value of the confirmation state data is equal to a preset pass identifier, taking the field damage value as a final damage value, and generating a damage confirmation document; sending the damage confirmation document to an insurance claim settlement platform.

7. The method of claim 1, wherein: generating a damage estimation statistics table based on the damage estimation offset includes: creating a damage estimation statistics table data structure composed of a device information field set, a damage estimation data field set, and an offset analysis field set; extracting device identification information from the device fault record and writing the device identification information into the device information field set; writing the preliminary damage estimation value into a first damage estimation field in the damage estimation data field set and writing the rechecked damage estimation value into a second damage estimation field in the damage estimation data field set; writing the damage estimation offset into an offset field in the offset analysis field set; determining offset rate data based on the damage estimation offset and the preliminary damage estimation value, and writing the offset rate data into an offset rate field in the offset analysis field set.

8. A field survey nuclear damage data processing system using the field survey nuclear damage data processing method according to any one of claims 1 to 7, characterized by includes: a data acquisition module configured to obtain device fault records from a power grid monitoring platform and extract voltage levels and loss degrees from the device fault records; a path determination module configured to determine an estimation calculation path based on the voltage levels and process the device fault records according to the estimation calculation path to obtain a preliminary damage estimation value; a data interaction module configured to send the preliminary damage estimation value to an insurance brokerage server and receive a rechecked damage estimation value returned by the insurance brokerage server; a statistics table generation module configured to calculate a damage estimation offset between the preliminary damage estimation value and the rechecked damage estimation value, and generate a damage estimation statistics table based on the damage estimation offset.

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