Electric bicycle charging pile operation management method and system based on industrial cloud computing

Abstract

The application discloses an electric bicycle charging pile operation management method and system based on industrial cloud computing, relates to the technical field of operation management, and comprises a conversation recognition generation module, which is used for receiving charging event data and control event data uploaded by multiple networked charging piles, receiving reservation event data, queuing event data and account operation data recorded by an industrial cloud platform, constructing data segments formed during single plug-in to plug-out into original conversation records, and then merging multiple original conversation records with migration continuity into the same migration associated conversation. The industrial cloud platform of the application no longer passively waits for abnormal objects to randomly migrate among multiple stations, but actively arranges a differential access station sequence after identifying suspicious migration objects, takes the response difference of the same object in different station group states as the attribution basis, and then executes operation side closed-loop management based on the attribution result.

Description

Technical Field

[0001] This invention relates to the field of operation management technology, specifically to an operation management method and system for electric bicycle charging stations based on industrial cloud computing. Background Technology

[0002] As centralized charging facilities for electric bicycles continue to be connected to industrial cloud platforms, the platforms are now able to uniformly manage site locations, appointment queues, account access, charging process records, and maintenance tasks. Current network operation methods typically use a single charging record at a single charging station as the basic processing object, and based on this object, perform tasks such as appointment reservation, charging authorization, anomaly alerts, capacity updates, and maintenance record upkeep, thereby supporting centralized operation across multiple sites and workstations.

[0003] In centralized charging scenarios where older electric bicycles account for a high proportion and stable communication capabilities are lacking at the vehicle end, a rare but recurring situation arises: after the same faulty battery, charger, or wiring device triggers a protection action at a certain charging station, the user will quickly move to a nearby station to re-initiate charging, creating short-term, scattered charging segments across multiple stations. Current technologies typically treat these charging segments as independent sessions, failing to identify them as belonging to the same user, leading to three direct drawbacks. First, the platform cannot determine whether the anomaly originates from the charging device itself or from a single charging station, resulting in distorted attribution. Second, the same user repeatedly makes reservations, queues, and occupies charging spots within a short period, distorting the station capacity map and disrupting queue order. Third, the platform can only passively wait for anomalies to surface naturally, lacking a mechanism to proactively construct distinguishing conditions and failing to utilize station orchestration itself for more accurate risk attribution. How to proactively orchestrate the access sequence of workstations using an industrial cloud platform without relying on vehicle-side modifications, enabling the platform to perform attribution through differential responses of the same object in different workstation group states, and further drive workstation access, capacity correction, queue recovery, and maintenance dispatch, is a specific technical problem faced by those skilled in the art. Summary of the Invention

[0004] The purpose of this invention is to provide an operation and management method and system for electric bicycle charging stations based on industrial cloud computing, so as to solve the problems mentioned in the background art.

[0005] To address the aforementioned technical problems, this invention provides the following technical solution: an electric bicycle charging pile operation and management system based on industrial cloud computing, including a session recognition and generation module, used to receive charging event data and control event data uploaded by multiple networked charging piles, and to receive reservation event data, queuing event data, and account operation data recorded by the industrial cloud platform, constructing the data fragments formed during a single insertion and removal of the charging gun into an original session record, merging multiple original session records with migration continuity into the same migration-related session, and generating differential access diagnostic requirements when the migration-related session meets suspicious triggering conditions; The orchestration and attribution module is used to sequentially assign the corresponding migration-related sessions to the diagnostic workstations in different workstation group states according to the differential access diagnostic requirements, collect the response results of the migration-related sessions in each workstation group state, and complete object-side risk attribution, pile-side risk attribution, abnormal disturbance attribution caused by workstation group state differences, and composite risk attribution based on the differences between the response results. The correction execution module is used to perform diagnostic workstation access control, ordinary workstation recovery control, account restriction control, invalid occupancy release, site capacity correction, queue recovery, and operation and maintenance work order generation based on the attribution results, thereby forming a closed-loop management process from session identification, differential access, risk attribution to operation execution.

[0006] According to the above technical solution, the session identification and generation module includes: a session standardization unit, used to standardize continuous data segments between a single gun insertion event and the corresponding gun withdrawal event into an original session record; a suspicious trigger judgment unit, used to judge whether the original session record meets the suspicious trigger conditions based on the protection actions, fallback activation, and reconnection behavior in the original session record; a migration association unit, used to merge multiple original session records that meet the continuity conditions into the same migration association session within a preset time range and a preset spatial range; and a diagnostic requirement generation unit, used to generate differential access diagnostic requirements when the migration association session meets the suspicious trigger conditions. The orchestration and attribution module includes: a workstation group file unit for storing the workstation group status file of each workstation, the workstation group status file including the admission rule level, the upper limit of single authorization duration, the reconnection cooling interval, and the adjacent blanking rule; a sequence orchestration unit for sequentially assigning migration-related sessions to diagnostic workstations in different workstation group states according to a preset diagnostic order; a response extraction unit for extracting the protection triggering, start fallback, and reconnection behaviors of migration-related sessions in each workstation group state; and an attribution determination unit for outputting attribution results based on the response differences and pile concentration in each workstation group state. The correction execution module includes: an access control unit, used to perform diagnostic workstation access, normal workstation restoration, and account restrictions based on the attribution results; a capacity correction unit, used to identify duplicate reservation records, duplicate queuing records, and duplicate occupancy records formed by the same migration-related session, and release invalid occupancy resources; a queue restoration unit, used to advance the normal queue and waiting queue according to the corrected site capacity; and a work order generation unit, used to generate inspection work orders and maintenance work orders based on the risk attribution results at the pile entrance and the composite risk attribution results.

[0007] The operation and management method for electric bicycle charging stations based on industrial cloud computing includes the following steps: S1. Collect start events, stop events, protection action events and current change events uploaded by multiple networked charging piles, and collect reservation events, queuing events and account operation events recorded by the industrial cloud platform. Construct the data fragments formed during the period from plugging in the gun to unplugging the gun into the original session record, and at the same time determine whether the original session record meets the suspicious triggering conditions. S2. After the original session record meets the suspicious triggering conditions, search for candidate sessions adjacent to the original session record within a preset time range and a preset spatial range, merge multiple original session records that meet the migration continuity conditions into the same migration-related session, and generate differential access diagnostic requirements for the migration-related session. S3. Based on the differential access diagnostic requirements, the industrial cloud platform sequentially assigns the migration-related sessions to diagnostic workstations in different workstation groups according to a preset diagnostic order, and collects the response results of the migration-related sessions in each workstation group to form a differential access response sequence. S4. Based on the differential access response sequence, calculate the response difference between groups and the concentration of piles, complete the attribution of object-side risk, pile-side risk, workstation group status disturbance and composite risk, and execute diagnostic workstation access control, ordinary workstation recovery control and account restriction control according to the attribution results. S5. Identify duplicate resource records in the reservation queue, placeholder record and site capacity map for the same migration-related session, release invalid placeholder resources and correct the site's allocable capacity, restore the queue order based on the corrected site allocable capacity, and generate inspection work orders or maintenance work orders for piles that are attributed to pile-side risks or compound risks.

[0008] According to the above technical solution, steps S1 and S2 specifically include: S1-1. Construct the original session record for each continuous data segment between each gun insertion event and gun withdrawal event. The original session record This includes site identifier, pile head identifier, start time, end time, current sequence segment, control event sequence, account identifier, and terminal identifier; S1-2, Regarding the original session record Calculate suspicious trigger values ,in The protection trigger coefficient is the protection trigger coefficient. The frequency of protection actions is obtained by dividing the number of protection actions by the total duration of the original session record, and then normalized to the range of 0 to 1 according to a preset frequency upper limit. This frequency is used to characterize the density of protection actions in the original session record. The start-up drop-off coefficient is obtained by dividing the current drop-off amplitude within a preset short-term window after startup by a preset maximum drop-off amplitude, and is limited to the range of 0 to 1. It is used to characterize the degree of abnormal attenuation after startup. The reconnection coefficient is obtained by dividing the number of active reconnections corresponding to the original session record by the preset maximum number of reconnections, and is limited to the range of 0 to 1. It is used to characterize the degree of repeated access attempts. , , The weighted coefficients, and satisfying the condition that the sum of the three is 1, are used to determine whether the current original session record has the necessity to enter the differential access diagnostic process; S2-1, When the suspicious trigger value Not less than the trigger threshold At that time, within a preset time range, candidate original session records are retrieved, and the original session records are processed. With candidate original session records Calculate migration association values: ,in For the original session record With the original session record migration association value, For the original session record End time and original session record The time interval between the start times, It serves as a time decay scale, used to limit record pairs that exceed a reasonable migration duration; This corresponds to the spatial distance between the two pile openings. This is a spatial decay scale used to limit record pairs that exceed a reasonable migration distance. The current pattern similarity is calculated by combining the rising pattern during the startup phase, the fluctuation pattern during the stable phase, and the falling pattern before cutoff, with a value range of 0 to 1. For continuity marking, when the original session record With the original session record The value is 1 if the account identifiers are the same, 1 if the account identifier is missing but the two devices have the same terminal identifier, and 0 otherwise. , , , The weighted coefficients, and the sum of the four values ​​is 1, are used to characterize whether two original session records belong to the continuous access behavior of the same migration object; S2-2, When migrating associated values Not less than the associated threshold At that time, the original session record will be recorded. With the original session record Merge into the same migration-related session And for the migration-related session Generate differential access diagnostic requirements.

[0009] According to the above technical solution, step S3 specifically includes: S3-1. The industrial cloud platform establishes a workstation group status file for each workstation and divides the workstations into standard access workstation groups, enhanced protection workstation groups, and isolation verification workstation groups. The standard access workstation group corresponds to the regular access rules, the enhanced protection workstation group corresponds to the shorter single authorization duration limit and the longer reconnection cooling interval, and the isolation verification workstation group corresponds to the adjacent empty rule and the independent queuing rule. S3-2, Regarding migration-related sessions According to the preset diagnostic sequence, the devices are sequentially assigned to diagnostic workstations in the standard access workstation group, enhanced protection workstation group, and isolation verification workstation group, and migration-related sessions are extracted after each access is completed. Status of the corresponding workstation group response strength ,in To migrate associated sessions In workstation group status The protection trigger coefficient below, To migrate associated sessions In workstation group status The starting pullback coefficient is below. To migrate associated sessions In workstation group status The reconnection coefficients below, , , The three factors are weighted coefficients, and their sum is 1. The response intensity is used to uniformly characterize the strength of abnormal behavior of the same migration-related session in different workstation groups. , , The calculation methods for correspond to S1-2 respectively. , , The calculation method differs in that the statistical object is migration-related sessions. In workstation group status The following access segment; S3-3, When migrating associated sessions After completing the access for all preset workstation group states, a differential access response sequence is formed, which serves as the input for subsequent attribution determination.

[0010] According to the above technical solution, step S4 specifically includes: S4-1, Regarding migration-related sessions Calculate the average response strength ,in To migrate associated sessions The number of completed workstation group statuses, and the average response intensity is used to characterize the overall anomaly level of the same migration-related session across the entire differential access sequence; S4-2, Migration-related sessions Calculate the difference between groups The inter-group variability is used to characterize the degree of response dispersion of the same migration-related session in different workstation group states; when the inter-group variability is small and the average response intensity is large, it indicates that the anomaly is more likely to remain stable with the object itself; when the inter-group variability is large, it indicates that the anomaly is more likely to be affected by the workstation group state. S4-3, Pile Joint Calculate the concentration at the pile entrance ,in Connect to the pile within the task time window The number of different migration-related sessions For the different migration-related sessions, the response strength must be satisfied. Not less than the high response threshold The number of migration-related sessions; the concentration of the pile entrance is used to characterize whether anomalies repeatedly occur in a concentrated manner at a single pile entrance; S4-4, When the average response intensity Not less than the object threshold Intergroup differences Less than the difference threshold And the concentration of pile openings Less than the pile opening threshold When the corresponding migration-related session is identified as an object-side risk; when the average response strength Not less than the object threshold Intergroup differences Less than the difference threshold And the concentration of pile openings Not less than the pile opening threshold When the average response strength is high, the corresponding migration-related session is classified as a composite risk. Less than the object threshold And the concentration of pile openings Not less than the pile opening threshold When the corresponding migration-related session is identified as a risk on the site side; when the difference between groups is significant... Not less than the difference threshold And the concentration of pile openings Less than the pile opening threshold When this happens, the corresponding migration-related session will be identified as a workstation group status disturbance; S4-5. Implement access control based on the attribution results. Specifically, for object-side risks, the corresponding diagnostic workstations will continue to have restricted access; for compound risks, the corresponding diagnostic workstations will have restricted access plus account restrictions; for pile-side risks, the migration-related sessions will be restored to normal workstation access and locked to the pile that has the most high response intensity times within the task time window. New access, workstation group status disturbances correspond to migration associated session switching to improve response strength Minimize the number of workstations and remove unnecessary restrictions.

[0011] According to the above technical solution, the specific content regarding operational correction and queue recovery in step S5 includes: S5-1, Regarding migration-related sessions Calculate the execution limit value ,in For retry strength, the retry strength is achieved by migrating associated sessions. The result is obtained by dividing the number of active reconnections within the task time window by the preset maximum number of reconnections, and limiting it to the range of 0 to 1. , , The weighted coefficients, and satisfying the sum of the three conditions being 1, are used to determine whether the migration-related session should continue to have restricted access or have its access suspended. S5-2, When limiting execution value Not less than the limit threshold When the migration-related session is suspended, the account's eligibility to make another appointment within a preset time period is suspended; when the restriction execution value is... Less than the limit threshold At that time, the migration-related session is allowed to continue to have restricted access within the diagnostic workstation area; S5-3, Site Calculate the corrected allocable capacity ,in For the site The current number of available regular workstations. To identify the number of invalid placeholders released after repeated placeholders in the same migration-related session, This represents the number of workstations currently occupied by the diagnosed workstation sequence and not yet open to the regular queue. The corrected allocable capacity is used to restore the number of adjacent workstations temporarily occupied due to the adjacent vacancy rules of the isolation verification workstation group; when the calculation result is... When less than 0, Recorded as 0; S5-4, Based on the modified allocatable capacity Regenerate site The system sets the upper limit for regular reservations, the number of people allowed to advance in the queue, and the number of people allowed to be officially admitted from the waiting list. It also retains the earliest valid resource record formed in the same migration-related session and marks all subsequent reservation records, queue records, and placeholder records as invalid resource records.

[0012] According to the above technical solution, step S5 further includes a maintenance dispatch step for pile-side risks and compound risks, specifically including: S5-5, Pile Joint Calculate maintenance priority value ,in The affected session factor is the one affected by the stub within the task time window. The number of migration-related sessions affected is divided by the preset maximum number of affected sessions within the task's time window, and is limited to the range of 0 to 1, to characterize the scope of the fault's impact. The duration factor is determined by the pile head. The average duration of the abnormal state is divided by the preset maximum duration, and the result is limited to the range of 0 to 1. This value is used to characterize the duration of the fault. , , The weighted coefficients, with the sum of the three being 1, are used to uniformly map the degree of repeated anomalies at the pile entrance, the scope of impact, and the degree of persistence to the dispatch priority. S5-6, When maintenance priority value Not less than the operation and maintenance threshold When the maintenance priority value is reached, a maintenance work order is generated and the new connection to the corresponding pile is locked; Less than the operation and maintenance threshold When the time comes, generate an inspection work order and retain the started session to complete it according to the current controlled policy; S5-7. The maintenance work order and the patrol work order both include the pile port identifier, the corresponding migration associated session identifier, the differential access response sequence summary, the attribution result, the resource correction result, and the execution time period, so that the operation and maintenance personnel can directly review the basis for dispatching the work order.

[0013] Compared with existing technologies, the beneficial effects achieved by this invention are as follows: By importing suspicious migration objects into a pre-configured differential access station sequence, this invention enables the industrial cloud platform to proactively create distinguishable access conditions, thereby differentiating previously difficult-to-separate object-side risks, pile-side risks, and workstation group status disturbances, avoiding crude judgments based solely on single anomalies. Furthermore, this solution directly applies attribution results to diagnostic workstation access, ordinary workstation recovery, account access restrictions, invalid slot release, site capacity correction, queue advancement, and maintenance work order generation, ensuring that risk identification no longer stops at the analysis level but directly changes the on-site workstation status and site operation status. Compared with existing passive monitoring solutions, this solution can more accurately identify the source of migration object risks, restore true capacity more promptly, maintain queue order more stably, and reduce the probability of misattributing object-side anomalies as pile-side faults.

[0014] This invention does not perform post-hoc analysis of existing records after the charging process is complete. Instead, upon identifying suspicious migration targets, it directly utilizes an industrial cloud platform to orchestrate the access sequence of different workstation groups, proactively exposing previously difficult-to-distinguish anomalies during subsequent access processes. Conventional approaches typically rely on a single charging anomaly or a single workstation's performance for judgment. This approach easily confuses anomalies caused by the target itself, individual charging station anomalies, and anomalies resulting from changes in workstation conditions, leading to only coarse measures such as limiting charging, stopping charging, or maintenance. This invention transforms access orchestration itself into a diagnostic tool, enabling subsequent access control, capacity correction, queue recovery, and maintenance dispatching to be based on clearer attribution. Therefore, it not only improves the accuracy of anomaly detection but also avoids collateral damage to normal workstations and users. Attached Figure Description

[0015] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the overall modular structure of the present invention. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Please see Figure 1The present invention provides a technical solution: an electric bicycle charging pile operation and management system based on industrial cloud computing, including a session recognition and generation module, which is used to receive charging event data and control event data uploaded by multiple networked charging piles, and to receive reservation event data, queuing event data and account operation data recorded by the industrial cloud platform. The module constructs the data fragments formed during the period from inserting the charging gun to removing the charging gun into the original session record, and then merges multiple original session records with migration continuity into the same migration-related session, and generates differential access diagnostic requirements when the migration-related session meets the suspicious triggering conditions. The orchestration and attribution module is used to sequentially assign the corresponding migration-related sessions to the diagnostic workstations in different workstation groups according to the differential access diagnostic requirements, collect the response results of the migration-related sessions in each workstation group, and complete object-side risk attribution, pile-side risk attribution, abnormal disturbance attribution caused by differences in workstation group status, and composite risk attribution based on the differences between the response results. The correction execution module is used to perform diagnostic workstation access control, ordinary workstation recovery control, account restriction control, invalid occupancy release, site capacity correction, queue recovery, and operation and maintenance work order generation based on the attribution results, thereby forming a closed-loop management process from session identification, differential access, risk attribution to operation execution. The session identification and generation module includes: a session standardization unit, used to standardize continuous data segments between a single gun insertion event and the corresponding gun withdrawal event into original session records; a suspicious trigger judgment unit, used to determine whether the original session record meets the suspicious trigger conditions based on the protection actions, fallback activation, and reconnection behavior in the original session record; a migration association unit, used to merge multiple original session records that meet the continuity condition into the same migration association session within a preset time range and a preset spatial range; and a diagnostic requirement generation unit, used to generate differential access diagnostic requirements when the migration association session meets the suspicious trigger conditions. The orchestration and attribution module includes: a workstation group file unit, used to store the workstation group status file for each workstation, which includes the access rule level, single authorization duration limit, reconnection cooling interval, and adjacent blanking rules; a sequence orchestration unit, used to sequentially assign migration-related sessions to diagnostic workstations in different workstation group states according to a preset diagnostic order; a response extraction unit, used to extract the protection triggering, start fallback, and reconnection behaviors of migration-related sessions in each workstation group state; and an attribution determination unit, used to output attribution results based on the response differences and pile concentration in each workstation group state. The correction execution module includes: an access control unit, used to perform diagnostic workstation access, normal workstation restoration, and account restrictions based on attribution results; a capacity correction unit, used to identify duplicate reservation records, duplicate queuing records, and duplicate occupancy records formed by the same migration-related session, and release invalid occupancy resources; a queue restoration unit, used to advance the normal queue and waiting queue according to the corrected site capacity; and a work order generation unit, used to generate inspection work orders and maintenance work orders based on the risk attribution results at the pile entrance and the composite risk attribution results. The operation and management method for electric bicycle charging stations based on industrial cloud computing includes the following steps: S1. Collect start events, stop events, protection action events and current change events uploaded by multiple networked charging piles, and collect reservation events, queuing events and account operation events recorded by the industrial cloud platform. Construct the data fragments formed during the period from plugging in the gun to unplugging the gun into the original session record, and at the same time determine whether the original session record meets the suspicious triggering conditions. S2. After the original session record meets the suspicious triggering conditions, search for candidate sessions adjacent to the original session record within a preset time range and a preset spatial range, merge multiple original session records that meet the migration continuity conditions into the same migration-related session, and generate differential access diagnostic requirements for the migration-related session. This approach merges multiple original session records into a single migration-related session, not simply to reduce the number of records, but to restore abnormal behaviors originally scattered across multiple workstations to a single access object. Conventionally, those skilled in the art would process each insertion and removal of a device separately. While this facilitates single-instance billing and alarms, it breaks down continuous attempts to access the same abnormal object across different workstations into multiple independent events. This results in the platform seeing multiple seemingly sporadic abnormal fragments instead of a continuously migrating abnormal object. This solution first constructs the migration-related session, and all subsequent diagnostics, attribution, and operational controls revolve around this single migration object. This step effectively establishes a unified object foundation for subsequent differential access and attribution judgment. Without this step, even with subsequent workstation orchestration, multiple isolated records would be processed separately, making it difficult to generate stable and reliable attribution results.

[0018] S3. Based on the differential access diagnostic requirements, the industrial cloud platform sequentially assigns the migration-related sessions to the diagnostic workstations in different workstation groups according to the preset diagnostic order, and collects the response results of the migration-related sessions in each workstation group to form a differential access response sequence. S4. Calculate the response differences between groups and the concentration of piles based on the differential access response sequence, complete the attribution of object-side risks, pile-side risks, workstation group status disturbances and composite risks, and execute diagnostic workstation access control, ordinary workstation recovery control and account restriction control according to the attribution results. S5. Identify duplicate resource records in the reservation queue, placeholder record and site capacity map for the same migration-related session, release invalid placeholder resources and correct the site allocable capacity, restore queue order according to the corrected site allocable capacity, and generate inspection work order or maintenance work order for piles that are attributed to pile-side risk or compound risk. Steps S1 and S2 specifically include: S1-1. Construct the original session record for each continuous data segment between each gun insertion event and gun withdrawal event. Original session log This includes site identifier, pile head identifier, start time, end time, current sequence segment, control event sequence, account identifier, and terminal identifier; S1-2, Regarding the original session record Calculate suspicious trigger values ,in To protect the trigger coefficient, protect the trigger coefficient. The frequency of protection actions is obtained by dividing the number of protection actions by the total duration of the original session record, and then normalized to the range of 0 to 1 according to a preset frequency upper limit. This frequency is used to characterize the density of protection actions in the original session record. The start-up drop-off coefficient is obtained by dividing the current drop-off amplitude within a preset short-term window after startup by a preset maximum drop-off amplitude, and is limited to the range of 0 to 1. It is used to characterize the degree of abnormal attenuation after startup. The reconnection coefficient is obtained by dividing the number of active reconnections corresponding to the original session record by the preset maximum number of reconnections, and is limited to the range of 0 to 1. It is used to characterize the degree of repeated access attempts. , , The weighted coefficients, and the sum of the three is 1, are used to determine whether the current original session record is necessary to enter the differential access diagnostic process; S2-1, When a suspicious trigger value Not less than the trigger threshold At that time, within a preset time range, candidate original session records are retrieved, and the original session records are processed. With candidate original session records Calculate migration association values: ,in For the original session record With the original session record migration association value, For the original session record End time and original session record The time interval between the start times, It serves as a time decay scale, used to limit record pairs that exceed a reasonable migration duration; This corresponds to the spatial distance between the two pile openings. This is a spatial decay scale used to limit record pairs that exceed a reasonable migration distance. The current pattern similarity is calculated by combining the rising pattern during the start-up phase, the fluctuation pattern during the stable phase, and the falling pattern before cutoff. The value range is from 0 to 1. For continuity marking, when the original session record With the original session record The value is 1 if the account identifiers are the same, 1 if the account identifier is missing but the two devices have the same terminal identifier, and 0 otherwise. , , , The weighted coefficients, and satisfying the condition that the sum of the four is 1, are used to characterize whether two original session records belong to the same migration object for continuous access behavior. S2-2, When migrating associated values Not less than the associated threshold At that time, the original session record will be recorded. With the original session record Merge into the same migration-related session And for migration-related sessions Generate differential access diagnostic requirements; Step S3 specifically includes: S3-1. The industrial cloud platform establishes a workstation group status file for each workstation and divides the workstations into standard access workstation groups, enhanced protection workstation groups, and isolation verification workstation groups. The standard access workstation group corresponds to the regular access rules, the enhanced protection workstation group corresponds to the shorter single authorization duration limit and the longer reconnection cooling interval, and the isolation verification workstation group corresponds to the adjacent empty rule and the independent queuing rule. S3-2, Regarding migration-related sessions According to the preset diagnostic sequence, the devices are sequentially assigned to diagnostic workstations in the standard access workstation group, enhanced protection workstation group, and isolation verification workstation group, and migration-related sessions are extracted after each access is completed. Status of the corresponding workstation group response strength ,in To migrate associated sessions In workstation group status The protection trigger coefficient below, To migrate associated sessions In workstation group status The starting pullback coefficient is below. To migrate associated sessions In workstation group status The reconnection coefficients below, , , These are weighted coefficients, and the sum of the three is 1. The response strength is used to uniformly characterize the strength of abnormal behavior of the same migration-related session in different workstation groups. , , The calculation methods for correspond to S1-2 respectively. , , The calculation method differs in that the statistical object is migration-related sessions. In workstation group status The following access segment; The key to this step is not simply assigning an object to another idle workstation, but rather purposefully introducing the same migration-related sessions sequentially into different workstation group states, thus controlling the subsequent access conditions. Conventional methods, when faced with suspicious anomalies, typically only continue observing whether the object malfunctions again, or directly restrict its access eligibility. This approach essentially remains passively waiting for the anomaly to surface naturally; the platform cannot determine whether the anomaly arises with the object itself or is amplified only under a certain type of workstation condition. This solution, by pre-setting workstation group state files and access sequences, leaves comparable response differences for the same object under different access conditions. In this way, workstation orchestration is no longer just a scheduling action, but is transformed into a proactive diagnostic action that creates distinguishing conditions. The originality of this approach lies in the fact that it does not rely on adding vehicle-side hardware or external detection equipment to improve judgment capabilities, but directly utilizes the differences in the existing workstation operational states to further decompose the source of the anomaly on the platform side.

[0019] S3-3, When migrating associated sessions After completing the access in all preset workstation group states, a differential access response sequence is formed, which serves as the input for subsequent attribution determination. Step S4 specifically includes: S4-1, Regarding migration-related sessions Calculate the average response strength ,in To migrate associated sessions The number of completed workstation group statuses and the average response intensity are used to characterize the overall anomaly level of the same migration-related session across the entire differential access sequence. S4-2, Migration-related sessions Calculate the difference between groups Inter-group variability is used to characterize the degree of response dispersion of the same migration-related session in different workstation group states. When the inter-group variability is small and the average response strength is large, it indicates that the anomaly is more likely to remain stable with the object itself. When the inter-group variability is large, it indicates that the anomaly is more likely to be affected by the workstation group state. S4-3, Pile Joint Calculate the concentration at the pile entrance ,in Connect to the pile within the task time window The number of different migration-related sessions To meet response strength requirements in different migration-related sessions Not less than the high response threshold The number of migration-related sessions; the concentration of the point is used to characterize whether anomalies occur repeatedly and in a concentrated manner on a single point; S4-4, When the average response intensity Not less than the object threshold Intergroup differences Less than the difference threshold And the concentration of pile openings Less than the pile opening threshold When the corresponding migration-related session is identified as an object-side risk; when the average response strength Not less than the object threshold Intergroup differences Less than the difference threshold And the concentration of pile openings Not less than the pile opening threshold When the average response strength is high, the corresponding migration-related session is classified as a composite risk. Less than the object threshold And the concentration of pile openings Not less than the pile opening threshold When the corresponding migration-related session is identified as a risk on the site side; when the difference between groups is significant... Not less than the difference threshold And the concentration of pile openings Less than the pile opening threshold When this happens, the corresponding migration-related session will be identified as a workstation group status disturbance; This step doesn't simply classify the severity of anomalies; instead, it analyzes and identifies the source of the anomaly after differential access has been performed within the same migration-related session. Conventional methods typically only conclude that an object is high-risk or that a workstation has many anomalies, but these conclusions often fail to explain the driving factors behind the anomalies, thus failing to guide subsequent actions such as restricting objects, isolating workstations, or adjusting workstation configurations. This solution, after completing differential access, combines the response changes under different workstation group states and the concentration of anomalies at a single charging point to identify object-side risks, charging point-side risks, and workstation group state disturbances. The practical benefit of this is that it establishes a direct correlation between subsequent operational actions and the source of the anomaly: object-related problems no longer inadvertently affect normal workstations, single charging point problems are no longer misjudged as user-side anomalies, and anomalies affected by workstation states can be mitigated by switching workstation groups instead of directly stopping charging. In other words, this step truly improves not the anomaly identification rate itself, but the accuracy of subsequent handling.

[0020] S4-5. Implement access control based on the attribution results. Specifically, for object-side risks, the corresponding diagnostic workstations will continue to have restricted access; for compound risks, the corresponding diagnostic workstations will have restricted access plus account restrictions; for pile-side risks, the migration-related sessions will be restored to normal workstation access and locked to the pile that has the most high response intensity times within the task time window. New access, workstation group status disturbances correspond to migration associated session switching to improve response strength Minimize the number of workstations and remove unnecessary restrictions; The differentiated access control based on different attribution results is not intended to increase control layers, but rather to avoid mixing issues that should be handled separately into a single processing path. Using conventional methods, platforms often directly implement uniform measures such as stopping or limiting charging, or manual review upon detecting anomalies. While simple, this approach can easily freeze normally functioning workstations and misattribute anomalies not caused by the object itself to the user. In this solution, continued access restrictions on object-side risks allow for continued observation of whether the object itself remains stable and abnormal without complete liberalization. Account restrictions are applied to compound risks because both object-related and pile-related factors exist simultaneously, and adjusting a single workstation is insufficient to eliminate the risk. Restoring normal workstation access and locking abnormal piles for pile-side risks narrows the impact to the specific fault point. Workstation group status disturbances are addressed by switching to the workstation group with the least response to maintain service continuity. This one-to-one control approach reflects the direct driving relationship between attribution results and subsequent operational actions, rather than simply outputting general risk labels.

[0021] Step S5, concerning operational adjustments and queue recovery, specifically includes: S5-1, Regarding migration-related sessions Calculate the execution limit value ,in For retry strength, retry strength is achieved by migrating associated sessions. The result is obtained by dividing the number of active reconnections within the task time window by the preset maximum number of reconnections, and limiting it to the range of 0 to 1. , , The weighted coefficients, and satisfying the condition that the sum of the three is 1, limit the execution value to determine whether migration-related sessions should continue to have restricted access or have their access suspended; S5-2, When limiting execution value Not less than the limit threshold When the migration of the associated session's corresponding account is suspended, the account's eligibility to make another appointment within the preset time period will be suspended; when the restriction execution value is... Less than the limit threshold At that time, migration-related sessions are allowed to continue to have restricted access within the diagnostic workstation. S5-3, Site Calculate the corrected allocable capacity ,in For the site The current number of available regular workstations. To identify the number of invalid placeholders released after repeated placeholders in the same migration-related session, This represents the number of workstations currently occupied by the diagnosed workstation sequence and not yet open to the regular queue. To account for the number of adjacent workstations temporarily occupied due to the adjacent vacancy rules of the isolation verification workstation group, adjust the allocable capacity to restore the number of workstations that can actually be used in the site's normal queue; when the calculation results When less than 0, Recorded as 0; The focus of this step is not on general duplicate record cleanup, but on correcting site capacity distortion caused by repeated access attempts across workstations from the same migration-related session. Conventional queuing systems typically treat multiple reservations and multiple slot reservations as independent requests, releasing them one by one after a timeout. While this maintains basic operation, in scenarios with frequent migrations of abnormal objects, it causes the site to continuously underestimate the actual number of available workstations for a period of time, unnecessarily lengthening queues for legitimate users. This solution first constructs the migration-related session, then identifies which reservation, queuing, and slot reservation records are essentially duplicates of the same migration object, thus releasing workstations that shouldn't be occupied for extended periods. The purpose of this step is to truly transform the previous attribution results into a corrective capability for the site capacity map, enabling the platform not only to identify anomalies but also to restore the site's true operational order.

[0022] S5-4, Based on the modified allocatable capacity Regenerate site The system sets the upper limit for regular reservations, the number of queue entries, and the number of candidates who are put on the waiting list. It also retains the earliest valid resource record formed in the same migration-related session and marks all subsequent reservation records, queue records, and placeholder records as invalid resource records. Step S5 also includes the step of dispatching maintenance orders for risks and combined risks at the pile head, specifically including: S5-5, Pile Joint Calculate maintenance priority value ,in For affected session factors, affected session factors are those affected by stubs within the task time window. The number of migration-related sessions affected is divided by the preset maximum number of affected sessions within the task's time window, and is limited to the range of 0 to 1, to characterize the scope of the fault's impact. The duration factor is determined by the pile opening. The average duration of the abnormal state is divided by the preset maximum duration, and the result is limited to the range of 0 to 1. This value is used to characterize the duration of the fault. , , The weighted coefficients, with the sum of the three being 1, are used to uniformly map the degree of repeated anomalies at the pile entrance, the scope of impact, and the degree of persistence to the dispatch priority. S5-6, When maintenance priority value Not less than the operation and maintenance threshold When the maintenance priority value is reached, a maintenance work order is generated and the new connection to the corresponding pile is locked; Less than the operation and maintenance threshold When the time comes, generate an inspection work order and retain the started session to complete it according to the current controlled policy; S5-7, both maintenance work orders and patrol work orders include pile port identifier, corresponding migration associated session identifier, differential access response sequence summary, attribution result, resource correction result, and execution time period, so that operation and maintenance personnel can directly verify the basis for dispatching the work order.

[0023] The difference between this step and the conventional alarm dispatch is that the work order is not based on a single anomaly trigger, but rather on the aforementioned differential access and attribution results. Using conventional methods, if an anomaly occurs at a workstation during a charging session, a maintenance task might be generated directly. While this is a rapid response, it easily leads to misinterpreting the anomaly of the object itself as a problem with the charging station, resulting in duplicate visits, incorrect repairs, or ineffective replacements. This solution, before generating a work order, has already segmented the anomaly source through migration-related sessions and differential access response sequences. Therefore, the operations and maintenance team receives not a general anomaly notification, but a set of handling tasks with attribution context. This allows maintenance actions to be more focused on the charging stations that truly require attention, and inspection actions are easier to verify in conjunction with past access conditions, preventing the ineffective consumption of operations and maintenance resources on erroneous objects.

[0024] The most significant difference between this invention and conventional operation platforms lies in the fact that the platform no longer treats each charging session as an independent ordinary session, nor does it treat workstation scheduling merely as a resource allocation method. Instead, it first restores the continuous access behavior of the same object by migrating related sessions, then actively creates comparable access conditions through differential access workstation sequences, and finally determines subsequent access, correction, and dispatch actions based on the differences in response under different conditions. In other words, traditional platforms simply record anomalies and respond after they occur, while this invention connects object recovery, condition orchestration, attribution judgment, and operational execution into a continuous chain, embedding diagnostic capabilities directly into the operational process.

[0025] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "include," "contain," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus.

[0026] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An operation and management method for electric bicycle charging stations based on industrial cloud computing, characterized by: Includes the following steps: S1. Collect start events, stop events, protection action events and current change events uploaded by multiple networked charging piles, and collect reservation events, queuing events and account operation events recorded by the industrial cloud platform. Construct the data fragments formed during the period from plugging in the gun to unplugging the gun into the original session record, and at the same time determine whether the original session record meets the suspicious triggering conditions. S2. After the original session record meets the suspicious triggering conditions, search for candidate sessions adjacent to the original session record within a preset time range and a preset spatial range, merge multiple original session records that meet the migration continuity conditions into the same migration-related session, and generate differential access diagnostic requirements for the migration-related session. S3. Based on the differential access diagnostic requirements, the industrial cloud platform sequentially assigns the migration-related sessions to diagnostic workstations in different workstation groups according to a preset diagnostic order, and collects the response results of the migration-related sessions in each workstation group to form a differential access response sequence. S4. Based on the differential access response sequence, calculate the response difference between groups and the concentration of piles, complete the attribution of object-side risk, pile-side risk, workstation group status disturbance and composite risk, and execute diagnostic workstation access control, ordinary workstation recovery control and account restriction control according to the attribution results. S5. Identify duplicate resource records in the reservation queue, placeholder record and site capacity map for the same migration-related session, release invalid placeholder resources and correct the site's allocable capacity, restore the queue order based on the corrected site allocable capacity, and generate inspection work orders or maintenance work orders for piles that are attributed to pile-side risks or compound risks.

2. The method for operation and management of electric bicycle charging stations based on industrial cloud computing according to claim 1, characterized in that: Steps S1 and S2 specifically include: S1-1. Construct the original session record for each continuous data segment between each gun insertion event and gun withdrawal event. The original session record This includes site identifier, pile head identifier, start time, end time, current sequence segment, control event sequence, account identifier, and terminal identifier; S1-2, Original Session Record Calculate suspicious trigger values ,in To protect the triggering coefficient, the protection triggering coefficient The frequency of protection actions is obtained by dividing the number of protection actions by the total duration of the original session records, and then normalized to the range of 0 to 1 according to the preset frequency upper limit. The start-up drop factor is obtained by dividing the current drop amplitude within a preset short-term window after startup by a preset maximum drop amplitude, and limiting it to the range of 0 to 1. The reconnection coefficient is obtained by dividing the number of active reconnections corresponding to the original session record by the preset maximum number of reconnections, and is limited to the range of 0 to 1. It is used to characterize the degree of repeated access attempts. , , These are weighting coefficients, and the sum of the three is 1; S2-1, When the suspicious trigger value Not less than the trigger threshold At that time, within a preset time range, candidate original session records are retrieved, and the original session records are processed. With candidate original session records Calculate migration association values: ,in For the original session record With the original session record migration association value, For the original session record End time and original session record The time interval between the start times, The time decay scale; This corresponds to the spatial distance between the two pile openings. This is a spatial decay scale used to limit record pairs that exceed a reasonable migration distance. The current pattern similarity is calculated by combining the rising pattern during the startup phase, the fluctuation pattern during the stable phase, and the falling pattern before cutoff, with a value range of 0 to 1. For continuity marking, when the original session record With the original session record The value is 1 if the account identifiers are the same, 1 if the account identifier is missing but the two devices have the same terminal identifier, and 0 otherwise. , , , These are weighting coefficients, and the sum of the four is 1; S2-2, When migrating associated values Not less than the association threshold At that time, the original session record will be recorded. With the original session record Merge into the same migration-related session And for the migration-related session Generate differential access diagnostic requirements.

3. The method for operation and management of electric bicycle charging stations based on industrial cloud computing according to claim 2, characterized in that: Step S3 specifically includes: S3-1. The industrial cloud platform establishes a workstation group status file for each workstation and divides the workstations into standard access workstation groups, enhanced protection workstation groups, and isolation verification workstation groups. The standard access workstation group corresponds to the regular access rules, the enhanced protection workstation group corresponds to the shorter single authorization duration limit and the longer reconnection cooling interval, and the isolation verification workstation group corresponds to the adjacent empty rule and the independent queuing rule. S3-2, Regarding migration-related sessions According to the preset diagnostic sequence, the devices are sequentially assigned to diagnostic workstations in the standard access workstation group, enhanced protection workstation group, and isolation verification workstation group, and migration-related sessions are extracted after each access is completed. Status of the corresponding workstation group The response strength at the following ,in To migrate associated sessions In workstation group status The protection trigger coefficient below, To migrate associated sessions In workstation group status The starting pullback coefficient is below. To migrate associated sessions In workstation group status The reconnection coefficients are as follows: , , These are weighting coefficients, and the sum of the three is 1, where , , The calculation methods for correspond to S1-2 respectively. , , The calculation method differs in that the statistical object is migration-related sessions. In workstation group status The following access segment; S3-3, When migrating associated sessions After completing the access for all preset workstation group states, a differential access response sequence is formed, which serves as the input for subsequent attribution determination.

4. The method for operation and management of electric bicycle charging stations based on industrial cloud computing according to claim 3, characterized in that: Step S4 specifically includes: S4-1, Regarding migration-related sessions Calculate the average response strength ,in To migrate associated sessions The number of completed workstation group states, and the average response intensity is used to characterize the overall anomaly level of the same migration-related session across the entire differential access sequence; S4-2, Migration-related sessions Calculate the difference between groups The inter-group difference is used to characterize the degree of response dispersion of the same migration-related session in different workstation group states; S4-3, Pile Joint Calculate the concentration at the pile entrance ,in Connect to the pile within the task time window The number of different migration-related sessions For the different migration-related sessions, the response strength must be satisfied. Not less than the high response threshold The number of migration-related sessions; the concentration of the pile entrance is used to characterize whether anomalies repeatedly occur in a concentrated manner at a single pile entrance; S4-4, When the average response intensity Not less than the object threshold Intergroup differences Less than the difference threshold And the concentration of pile openings Less than the pile opening threshold When the corresponding migration-related session is identified as an object-side risk; when the average response strength Not less than the object threshold Intergroup differences Less than the difference threshold And the concentration of pile openings Not less than the pile opening threshold When the average response strength is high, the corresponding migration-related session is classified as a composite risk. Less than the object threshold And the concentration of pile openings Not less than the pile opening threshold When the corresponding migration-related session is identified as a risk on the pile-side; when the difference between groups is significant... Not less than the difference threshold And the concentration of pile openings Less than the pile opening threshold When this happens, the corresponding migration-related session will be identified as a workstation group status disturbance; S4-5. Implement access control based on the attribution results. Specifically, for object-side risks, the corresponding diagnostic workstations will continue to have restricted access; for compound risks, the corresponding diagnostic workstations will have restricted access plus account restrictions; for pile-side risks, the migration-related sessions will be restored to normal workstation access and locked to the pile that has the most high response intensity times within the task time window. New access, workstation group status disturbances correspond to migration associated session switching to improve response strength Minimize the number of workstations and remove unnecessary restrictions.

5. The method for operation and management of electric bicycle charging stations based on industrial cloud computing according to claim 4, characterized in that: The specific content regarding operational correction and queue restoration in step S5 includes: S5-1, Regarding migration-related sessions Calculate the execution limit value ,in For retry strength, the retry strength is achieved by migrating associated sessions. The result is obtained by dividing the number of active reconnections within the task time window by the preset maximum number of reconnections, and limiting it to the range of 0 to 1. , , The weighted coefficients, and satisfying the sum of the three conditions being 1, are used to determine whether the migration-related session should continue to have restricted access or have its access suspended. S5-2, When limiting execution value Not less than the limit threshold When the migration-related session is suspended, the account's eligibility to make another appointment within a preset time period is suspended; when the restriction execution value is... Less than the limit threshold At that time, the migration-related session is allowed to continue to have restricted access within the diagnostic workstation area; S5-3, Site Calculate the corrected allocable capacity ,in For the site The current number of available regular workstations. To identify the number of invalid placeholders released after repeated placeholders in the same migration-related session, This represents the number of workstations currently occupied by the diagnosed workstation sequence and not yet open to the regular queue. This refers to the number of adjacent workstations temporarily occupied due to the adjacent vacancy rule of the isolation verification workstation group; when the calculation result... When it is less than 0, Recorded as 0; S5-4, Based on the modified allocatable capacity Regenerate site The system sets the upper limit for regular reservations, the number of people allowed to advance in the queue, and the number of people allowed to be officially admitted from the waiting list. It also retains the earliest valid resource record formed in the same migration-related session and marks all subsequent reservation records, queue records, and placeholder records as invalid resource records.

6. The method for operation and management of electric bicycle charging stations based on industrial cloud computing according to claim 5, characterized in that: Step S5 also includes the step of dispatching maintenance orders for risks at the pile head and combined risks, specifically including: S5-5, Pile Joint Calculate maintenance priority value ,in The affected session factor is the one affected by the stub within the task time window. The number of migration-related sessions affected is divided by the preset maximum number of affected sessions within the task's time window, and is limited to the range of 0 to 1, to characterize the scope of the fault's impact. The duration factor is determined by the pile head. The average duration of the abnormal state is divided by the preset maximum duration, and the result is limited to the range of 0 to 1. This value is used to characterize the duration of the fault. , , These are weighted coefficients, and the sum of the three is 1; S5-6, When maintenance priority value Not less than the operation and maintenance threshold When the maintenance priority value is reached, a maintenance work order is generated and the new connection to the corresponding pile is locked; Less than the operation and maintenance threshold When the time comes, generate an inspection work order and retain the started session to complete it according to the current controlled policy; S5-7. The maintenance work order and the patrol work order both include the pile port identifier, the corresponding migration associated session identifier, the differential access response sequence summary, the attribution result, the resource correction result, and the execution time period, so that the operation and maintenance personnel can directly review the basis for dispatching the work order.

7. An electric bicycle charging pile operation and management system based on industrial cloud computing, wherein the system is applied to the method described in any one of claims 1-6, characterized in that: It includes a session recognition and generation module, which is used to receive charging event data and control event data uploaded by multiple networked charging piles, and to receive reservation event data, queuing event data and account operation data recorded by the industrial cloud platform. It constructs the data fragments formed during a single insertion and removal of the charging gun into the original session record, and then merges multiple original session records with migration continuity into the same migration-related session. When the migration-related session meets the suspicious triggering conditions, it generates differential access diagnostic requirements. The orchestration and attribution module is used to sequentially assign the corresponding migration-related sessions to the diagnostic workstations in different workstation group states according to the differential access diagnostic requirements, collect the response results of the migration-related sessions in each workstation group state, and complete object-side risk attribution, pile-side risk attribution, abnormal disturbance attribution caused by workstation group state differences, and composite risk attribution based on the differences between the response results. The correction execution module is used to perform diagnostic workstation access control, ordinary workstation recovery control, account restriction control, invalid occupancy release, site capacity correction, queue recovery, and operation and maintenance work order generation based on the attribution results, thereby forming a closed-loop management process from session identification, differential access, risk attribution to operation execution.

8. The electric bicycle charging pile operation and management system based on industrial cloud computing according to claim 7, characterized in that: The session identification and generation module includes: a session standardization unit, used to standardize continuous data segments between a single gun insertion event and the corresponding gun withdrawal event into an original session record; a suspicious trigger judgment unit, used to judge whether the original session record meets the suspicious trigger conditions based on the protection actions, fallback activation, and reconnection behavior in the original session record; a migration association unit, used to merge multiple original session records that meet the continuity condition into the same migration association session within a preset time range and a preset spatial range; and a diagnostic requirement generation unit, used to generate differential access diagnostic requirements when the migration association session meets the suspicious trigger conditions. The orchestration and attribution module includes: a workstation group file unit for storing the workstation group status file of each workstation, the workstation group status file including admission rules, single authorization duration limit, reconnection cooling interval, adjacent vacancy rules, and independent queuing rules; a sequence orchestration unit for sequentially assigning migration-related sessions to diagnostic workstations in different workstation group states according to a preset diagnostic order; a response extraction unit for extracting the protection triggering, start fallback, and reconnection behaviors of migration-related sessions in each workstation group state; and an attribution determination unit for outputting attribution results based on the response differences and pile concentration in each workstation group state. The correction execution module includes: an access control unit, used to perform diagnostic workstation access, normal workstation restoration, and account restrictions based on the attribution results; a capacity correction unit, used to identify duplicate reservation records, duplicate queuing records, and duplicate occupancy records formed by the same migration-related session, and release invalid occupancy resources; a queue restoration unit, used to advance the normal queue and waiting queue according to the corrected site capacity; and a work order generation unit, used to generate inspection work orders and maintenance work orders based on the risk attribution results at the pile entrance and the composite risk attribution results.

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