CN115828112A

CN115828112A - Fault event response method and device, electronic equipment and storage medium

Info

Publication number: CN115828112A
Application number: CN202211540327.9A
Authority: CN
Inventors: 刘港
Original assignee: Delian Yikong Technology Beijing Co ltd
Current assignee: Delian Yikong Technology Beijing Co ltd
Priority date: 2022-12-02
Filing date: 2022-12-02
Publication date: 2023-03-21
Anticipated expiration: 2042-12-02
Also published as: CN115828112B

Abstract

The application is applicable to the technical field of data processing, and provides a response method and device of a fault event, electronic equipment and a storage medium, wherein the method comprises the following steps: receiving event data of a fault event to be processed; generating a plurality of event tags associated with the fault event from event data and generating an object representation of an accident object based on the event tags; respectively calculating portrait similarities of the object portrait and a plurality of historical portraits in an object database, and determining at least one historical fault event matched with the accident object based on the portrait similarities; and generating a fault response report corresponding to the fault event based on the response process report corresponding to the historical fault event. By adopting the method, the stability of the fault flow can be greatly improved, and the fault response report can be automatically generated in a mode of matching with the object database under the condition of dealing with a large number of fault events, so that the efficiency of generating the response fault report is greatly improved.

Description

Fault event response method and device, electronic equipment and storage medium

Technical Field

The present application belongs to the technical field of vehicle management, and in particular, to a method and an apparatus for responding to a fault event, an electronic device, and a storage medium.

Background

With the continuous promotion of socialization, the social population is increasing. In the process of daily life, unexpected fault events such as traffic accidents, medical accidents and the like occur more or less, and when the fault events are responded, relevant personnel can designate corresponding response processes to respond to the fault events so as to reduce the loss of the fault events to people. Therefore, how to quickly respond to the fault event becomes an urgent problem to be solved.

The existing response technology of the fault event needs a worker to know the fault event on site and appoint a corresponding response flow according to processing experience. However, the quality of the corresponding response flow is also uneven due to the processing experience of different workers, and in the case of a large number of fault events, the worker needs to determine the response flow for a long time, and the response efficiency is low. Therefore, the conventional response method for the fault event has the problems that the generation quality of the response flow is unstable and the response efficiency is low.

Disclosure of Invention

The embodiment of the application provides a fault event response method, a fault event response device, electronic equipment and a storage medium, and can solve the problems that the generation quality of a response process is unstable and the response efficiency is low in the existing fault event response method.

In a first aspect, an embodiment of the present application provides a method for responding to a fault event, including:

receiving event data of a fault event to be processed; the event data includes: accident object information and accident scene information;

generating a plurality of event tags associated with the fault event from event data and generating an object representation of an accident object based on the event tags;

respectively calculating portrait similarities of the object portrait and a plurality of historical portraits in an object database, and determining at least one historical fault event matched with the accident object based on the portrait similarities; each historical image corresponds to one historical fault event;

and generating a fault response report corresponding to the fault event based on the response process report corresponding to the historical fault event.

In a possible implementation manner of the first aspect, the event tag includes: a traffic scene tag and an accident object tag; the traffic scene tag includes: an event type tag, an event reason tag, a vehicle type tag and a scene place tag which are determined based on the accident scene information; the incident object tag includes: an occupation label and an age label determined based on the accident object information;

the generating a plurality of event tags associated with the fault event from event data and generating an object representation of an incident object based on the event tags, comprising:

determining label keywords contained in the event data according to preset label keywords with multiple label dimensions, and obtaining the event labels based on the contained label keywords;

importing the event type label, the event reason label and the scene place label into a preset accident simulation model, and constructing a fault simulation scene corresponding to the fault event;

determining the road type associated with the fault event according to the scene place tag, and determining the vehicle speed of the fault vehicle at the moment of the fault event based on the rated speed interval associated with the road type;

calculating a safety factor of the failed vehicle based on the vehicle type label;

constructing a corresponding vehicle model in the fault simulation scene according to the safety coefficient of the fault vehicle and the vehicle speed;

controlling the vehicle model to move in the fault simulation scene, generating fault restoration data, and generating a collision dimensionality score of the accident object through the fault restoration data;

generating an object representation of the accident object according to the collision dimension score, the occupation label and the age label.

In a possible implementation manner of the first aspect, the generating an object representation of the accident object according to the collision dimension score, the occupation label, and the age label includes:

determining a body basal score for the accident subject based on the occupation label and the age label;

determining the disease type associated with the occupation label through a preset corresponding relation between occupation and common diseases, and determining the existing disease dimension score of the accident object based on the disease type;

receiving event description voice fed back by the accident object, and determining an emotion dimension score based on the event description language;

generating the object representation according to the body basis score, the existing disease dimension score, the collision dimension score and the emotion dimension score; the object representation is used for predicting the injury of the accident object.

In a possible implementation manner of the first aspect, the receiving event description speech fed back by the accident object and determining an emotion dimension score based on the event description language includes:

extracting historical object voice related to the accident object from an object voice library, and determining a basic decibel value according to the historical voice amplitude of the historical object voice; the base decibel value is used for determining the voice decibel of the accident object in the emotional steady state;

determining a decibel characteristic parameter set according to the event description voice; the decibel characteristic parameter set comprises: decibel extreme value, decibel mean value and decibel mean square error;

obtaining at least one candidate emotion type based on the decibel characteristic parameter set and the basic decibel value;

matching the event description voice with the standard voice waveform of each candidate emotion type to determine a target emotion type;

determining the emotion dimension score according to the target emotion type.

In a possible implementation manner of the first aspect, the event tag includes: a traffic scene tag and an accident object tag;

before the separately calculating the portrait similarities of the object portrait with the plurality of historical portraits within the object database and determining at least one historical failure event matching the accident object based on the portrait similarities, further comprising:

calling a plurality of first parallel threads related to the number of first labels corresponding to the traffic scene labels, and extracting first object data corresponding to each traffic scene label from the object database; each first parallel stroke corresponds to one traffic scene label;

performing data intersection identification on all the first object data to obtain a first object group;

calling a plurality of second parallel threads related to the number of second tags corresponding to the accident object tags, and extracting second object data corresponding to each accident object tag from the object database; each second parallel thread corresponds to one accident object label;

performing data intersection identification on all the second object data to obtain a second object group;

determining a candidate object group according to the first object group and the second object group;

constructing a multi-dimensional fusion vector about the fault event according to all the traffic scene labels and the accident object labels;

extracting a target historical object matched with the multi-dimensional fusion vector from the candidate object group; the historian profile is generated based on historical failure events of the target historian object.

In a possible implementation manner of the first aspect, the receiving event data of the fault event to be processed includes:

receiving original event data fed back by a recording person of the fault event; the original event data is obtained based on the natural language description of the recorder; the original event data contains a plurality of degree parameters of event description dimensionality;

extracting a degree correction algorithm associated with the person identification of the recording person from a correction algorithm library; the degree correction algorithm is generated after training through difference information between the historical description language of the recording personnel and the historical fault events;

respectively importing the degree parameters corresponding to the event description dimensions into the degree correction algorithm to obtain correction parameters of the event description dimensions;

generating the event data based on the correction parameters for all of the event description dimensions.

In a possible implementation manner of the first aspect, the generating a fault response report corresponding to the fault event based on the response flow report corresponding to the historical fault event includes: respectively acquiring a response flow report corresponding to each historical fault event;

performing flow clustering on all the response flow reports to obtain at least one flow group; the flow similarity between the response flow reports in each flow group is greater than a preset similarity threshold;

calculating recommendation confidence degrees corresponding to the process groups according to the image similarity of the accident object corresponding to each process group;

determining the display priority of each flow group according to the descending order of the recommendation confidence degrees;

and generating the fault response report according to the display priority and the recommended response flow corresponding to the flow group.

In a second aspect, an embodiment of the present application provides a device for responding to a fault event, including:

the event data receiving unit is used for receiving event data of fault events to be processed; the event data includes: accident object information and accident scene information;

an object representation generation unit for generating a plurality of event tags associated with the fault event from event data and generating an object representation about an accident object based on the event tags;

an object representation matching unit for respectively calculating representation similarities of the object representation and a plurality of historical representations in an object database, and determining at least one historical fault event matched with an accident object based on the representation similarities; each historical image corresponds to one historical fault event;

and the fault response report generating unit is used for generating a fault response report corresponding to the fault event based on the response process report corresponding to the historical fault event.

In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor, when executing the computer program, implements the method according to any one of the above first aspects.

In a fourth aspect, embodiments of the present application provide a computer-readable storage medium, in which a computer program is stored, and the computer program, when executed by a processor, implements the method according to any one of the above first aspects.

In a fifth aspect, embodiments of the present application provide a computer program product, which when run on a server, causes the server to perform the method of any one of the first aspect.

Compared with the prior art, the embodiment of the application has the advantages that: the method comprises the steps of receiving event data related to a fault event to be processed, analyzing the event data to obtain a plurality of event labels related to the fault event, generating an object portrait of an accident object related to the fault event according to the event labels, calculating portrait similarity of the object portrait and each historical portrait in an object database, determining at least one historical fault event matched with the object portrait according to the portrait similarity, and generating a fault response report corresponding to the fault event according to a response flow report which can be correlated with the historical fault event because the historical fault event is an already processed event. Compared with the existing fault response technology, the method and the device have the advantages that the response process is judged through experience of workers, the historical fault event similar to the current fault event is identified, and the response process report of the historical fault event is reused, so that the stability of the fault process can be greatly improved, the fault response report can be automatically generated in a mode of being matched with the object database under the condition of dealing with a large number of fault events, and the generation efficiency of the response fault report is greatly improved.

Drawings

In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present application, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.

Fig. 1 is a schematic diagram illustrating an implementation of a method for responding to a fault event according to an embodiment of the present application;

FIG. 2 is a schematic diagram of an object representation according to an embodiment of the present application;

fig. 3 is a flowchart illustrating a specific implementation of a method S102 for responding to a fault event according to a second embodiment of the present application;

fig. 4 is a flowchart illustrating a specific implementation of a method S1027 for responding to a fault event according to a third embodiment of the present application;

fig. 5 is a flowchart illustrating a specific implementation of a method for responding to a fault event according to a fourth embodiment of the present disclosure;

fig. 6 is a flowchart of a specific implementation of a method S101 for responding to a fault event according to a fifth embodiment of the present application;

fig. 7 is a flowchart illustrating a specific implementation of a method S104 for responding to a fault event according to a sixth embodiment of the present application;

FIG. 8 is a schematic structural diagram of a response device for a fault event according to an embodiment of the present application;

fig. 9 is a schematic structural diagram of an electronic device provided in an embodiment of the present application.

Detailed Description

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system structures, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.

It will be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.

Furthermore, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used for distinguishing between descriptions and not necessarily for describing or implying relative importance.

The response method for the fault event provided by the embodiment of the application can be applied to electronic equipment which can generate a fault response report corresponding to the fault event, such as a smart phone, a server, a tablet computer, a notebook computer, an ultra-mobile personal computer (UMPC), a netbook and the like. The embodiment of the present application does not set any limit to the specific type of the electronic device.

In a possible implementation manner, the electronic device may be an intelligent terminal, such as a smart phone, used by a worker to whom event data of a fault event is recorded, in which case, the intelligent terminal may be installed with a corresponding client program, and the client program may collect event data corresponding to the fault event, so as to generate a corresponding fault response report.

In a possible implementation manner, the electronic device may also be a server deployed at the cloud end, in this case, a user may install a client program corresponding to the cloud end server in a local user terminal, and import corresponding event data in the client program, for example, a worker using the client program is a worker who collects event data at a site where a fault event occurs, the worker records corresponding event data at an accident site, the user terminal may establish a communication connection with the cloud end server through the client program, and upload the received event data to the cloud end server (i.e., an execution main body provided in the embodiment of the present application), and then the cloud end server may generate a fault response report corresponding to the fault event through subsequent steps and feed the fault response report back to the user terminal used by the worker at the site, so that the worker can respond to the fault event according to the fault response report.

Referring to fig. 1, fig. 1 is a schematic diagram illustrating an implementation of a method for responding to a fault event according to an embodiment of the present application, where the method includes the following steps:

in S101, event data of a fault event to be processed is received; the event data includes: accident object information and accident scene information.

In this embodiment, when a fault event occurs, event data corresponding to the fault event may be acquired according to a preset data acquisition module. The data acquisition template is internally recorded with a plurality of information dimensions for acquiring related information about the fault event under different dimensions, wherein the information dimensions comprise an object for determining the fault event, namely an accident object dimension, and a scene where the fault event occurs, namely an accident scene dimension, and based on the two information dimensions, corresponding accident object information and accident scene information can be obtained, and the information of the two dimensions is packaged, so that event data for describing the specific condition of the fault event can be obtained.

For example, a traffic accident is taken as an example, and in the case of a traffic accident at a certain destination, there corresponds to a fault event. The accident object is specifically an injured person in the traffic accident, such as a driver driving a vehicle in the traffic accident and passengers in the vehicle, and of course, in some application scenarios, the accident object may also be an accident vehicle in the traffic accident. The accident scene may include information related to the scene where the traffic accident occurs, such as time, place, vehicle type, vehicle number, and the like, and the type of the scene information to be collected may be selected according to the actual situation.

For example, taking a device failure as an example, if a device failure occurs in a certain device, such as a portable computer failure or an automobile failure, a current failure event is identified. The accident object is a device with a fault, such as a computer or an automobile. The accident scene may include location information, temperature information, and related device operating parameters when a fault occurs, and a specific type of scene information to be collected may be determined according to a device type, which is not limited herein.

In a possible implementation manner, the electronic device may be configured with a microphone module, and the microphone module acquires a description voice signal of the accident object for the fault event, performs voice recognition on the description voice signal, converts the description voice signal into corresponding description text data, and performs keyword extraction based on the description text data to generate event data corresponding to the fault event.

In one possible implementation, a worker may collect raw data corresponding to a failure event. The raw data may be generated based on a natural language description of the worker. After receiving the original data fed back by the staff, the electronic device can perform data cleaning on the original data, perform data division on the original data according to preset data dimensions defined in a preset data template to obtain subdata associated with each data dimension, and then introduce each subdata into a field corresponding to the associated data dimension, so as to generate the event data and complete corresponding data cleaning. Optionally, in order to improve the confidentiality of the event data, the electronic device may further encrypt the event data and store the event data in the blockchain, so as to improve the confidentiality and reliability of the event data.

In S102, a plurality of event tags associated with the fault event are generated from event data, and an object representation of an accident object is generated based on the event tags.

In this embodiment, after obtaining event data of a fault event, the electronic device may perform label extraction on the fault event to obtain a plurality of event labels for describing the fault event. Different event labels can correspond to different event description dimensions, so that a user can roughly know about a fault event through the event labels, and extraction of key information is achieved.

Illustratively, the fault event is a traffic accident event. The event tags include, but are not limited to: the system comprises a wounded occupation, the native place of the wounded, the age of the wounded, the sex of the wounded, the type of the accident, the reason of the accident, the place of the accident, the traffic mode of the wounded, the collision direction, the riding position of the wounded, a target vehicle type, a target vehicle body type, a target vehicle year money, three vehicle types, a three vehicle body type and a three vehicle year money. Optionally, the electronic device may further process the generated event tags, classify the event tags into a first tag group related to the accident object, a second tag group related to the accident vehicle, and a third tag group related to the accident environment, process the event tags in each tag group, and generate a cluster tag, so as to generate an accident, a wounded person, and a vehicle tag.

In this embodiment, after the electronic device determines the event tags corresponding to different dimensions, the electronic device may determine the dimension score corresponding to the dimension according to the content of the event tag corresponding to the dimension, and construct the corresponding object portrait according to the dimension scores corresponding to all the dimensions. Illustratively, FIG. 2 shows a schematic diagram of an object representation provided by an embodiment of the present application. Referring to fig. 2, the failure event is specifically a traffic accident, and the object representation is used for determining the injury condition of the injured person of the traffic accident, wherein the object representation includes a vehicle speed dimension, a vehicle impact depth dimension, an injury degree dimension, an injured person physical condition dimension (before injury), an injured person mental state dimension and the like, and different dimensions can determine corresponding dimension scores according to corresponding contents, so as to construct and obtain the injury condition for determining the injured person after the traffic accident.

In this embodiment, the electronic device stores an event tag score conversion function, the event tag conversion function is bound to corresponding dimensions, the electronic device determines a dimension type corresponding to the event tag, extracts a conversion function associated with the dimension type from the database, introduces the event tag into the associated conversion function, and can determine a dimension score corresponding to the event tag, so as to generate an object representation of the accident object based on the dimension scores of all the dimensions.

If there are multiple accident objects, that is, two or more accident objects exist in a single fault event, the electronic device may establish a corresponding object image for each accident object according to the number of accident objects, so as to determine an associated fault response report for different accident objects.

In S103, respectively calculating the portrait similarity of the object portrait and a plurality of historical portraits in an object database, and determining at least one historical fault event matched with an accident object based on the portrait similarity; each of the historical images corresponds to one of the historical fault events.

In this embodiment, the electronic device may store a response flow report corresponding to the historical failure event. Since fault events are similar to fault conditions, response reports that were processed once can be used as a reference to guide how to respond to the current fault event. In this case, the electronic device may extract a historical fault event with a higher similarity to the current fault event from the object database by performing similarity calculation with the object image, so as to generate a fault response report of the current fault event based on a response flow report of the associated historical fault time.

In this embodiment, when each historical failure event is responded, the execution flow is consistent with the failure event occurring this time, and a corresponding historical portrait is also generated. The electronic device associates the historical imagery with the historical fault events and stores the historical imagery in an object database. After generating the object portrait corresponding to the fault event needing to be processed at this time, the electronic equipment can calculate the similarity between the object portrait and the historical portrait.

In a possible implementation manner, the calculating the similarity between the object image and the historical image may be: the electronic equipment can draw the object portrait and the historical portrait in a preset coordinate system so as to calculate the contact ratio between the two portrait, and the contact ratio is weighted and calculated according to the corresponding dimension weight of each dimension so as to calculate the weighted contact ratio to be used as the similarity. If the coincidence degree between two images is higher, the corresponding similarity degree is higher.

In this embodiment, the electronic device may determine the historical portrait associated with the object portrait according to the similarity corresponding to each historical portrait, and use a historical failure event bound to the associated historical portrait as a historical failure event associated with the current to-be-processed failure time. Alternatively, the electronic device may set a similarity threshold, and identify a historical representation having a similarity greater than the similarity threshold as matching the object representation, thereby determining a historical failure event associated with the failure event.

In S104, a fault response report corresponding to the fault event is generated based on the response flow report corresponding to the historical fault event.

In this embodiment, a response flow report corresponding to each historical failure event may be stored in the object database of the electronic device. The response flow report is specifically a response flow actually executed when handling the historical failure event. Taking a traffic accident as an example, the response flow reports a mediation plan and an optimal tracking time for the injured person, that is, a process flow for determining how to treat a disease condition after the injured person is injured, a process flow for settling a loss of an injury, and the like.

For example, the fault event is an equipment fault event, and the response process report may be a fault diagnosis for the equipment and a corresponding actual maintenance process. In this case, the actual repair process may include a repair mode in the repair process for the faulty device, and tools required for repair, such as software tools and hardware tools.

In this embodiment, the electronic device may cluster and sort the response flow reports corresponding to the fault events, so that a fault response report having a guiding meaning for the fault events can be generated, and a worker may respond to the fault events according to the fault response report.

As can be seen from the above, in the response method for the fault event provided in the embodiment of the present application, event data related to the fault event to be processed is received, the event data is analyzed to obtain a plurality of event tags related to the fault event, an object portrait of an accident object related to the fault event is generated according to the plurality of event tags, portrait similarity calculation is performed on the object portrait and each historical portrait in an object database, at least one historical fault event matching the object portrait is determined according to portrait similarity, since the historical fault event is an already processed event and corresponds to an associated response flow, a fault response report corresponding to the fault event is generated according to a response flow report that can be associated with the historical fault event, and a purpose of automatically generating the fault response report is achieved. Compared with the existing fault response technology, the method and the device have the advantages that the response process is judged through experience of workers, the historical fault event similar to the current fault event is identified, and the response process report of the historical fault event is reused, so that the stability of the fault process can be greatly improved, the fault response report can be automatically generated in a mode of being matched with the object database under the condition of dealing with a large number of fault events, and the generation efficiency of the response fault report is greatly improved.

Fig. 3 shows a flowchart of a specific implementation of the method S102 for responding to a fault event according to the second embodiment of the present invention. Referring to fig. 3, with respect to the embodiment described in fig. 1, in the method for responding to a fault event provided in this embodiment, S102 includes: s1021 to S1027 are specifically described as follows:

further, the event tag includes: a traffic scene tag and an accident object tag; the traffic scene tag includes: an event type tag, an event reason tag, a vehicle type tag and a scene place tag which are determined based on the accident scene information; the incident object tag includes: an occupation label and an age label determined based on the accident object information;

in S1021, according to preset tag keywords of multiple tag dimensions, tag keywords included in the event data are determined, and the event tag is obtained based on the included tag keywords.

In the present embodiment, the above-mentioned failure event is a traffic accident, so it is necessary to determine the corresponding related event label from two aspects. Respectively, a label related to a traffic scene and a label of an accident object related to the current traffic accident. The two types of labels also comprise corresponding sub-labels, and traffic accidents can be restored according to the sub-labels of different types.

In this embodiment, after obtaining the event data, the electronic device may extract an event tag from the event data. The extraction process specifically matches the event data with the tag keywords of each tag dimension, so as to obtain the tag content corresponding to the fault event in the corresponding tag dimension. Wherein, different label dimensions can correspond to one or more label keywords. Taking scene place tags as an example, the tag keywords include but are not limited to: mountain roads, urban roads, expressways and the like to distinguish corresponding scene places in different geographic environments. The electronic equipment detects the label key words contained in the event data, so that specific label content corresponding to the corresponding label dimension of the fault event can be determined, the label key words contained in the event data are used as event labels corresponding to the label dimension, and identification of the event labels is achieved.

Wherein the identified event tag comprises: the system comprises an accident scene information determination module, an accident type label, an accident reason label, a vehicle type label and a scene place label which are determined based on the accident scene information, and further comprises an occupation label and an age label which are determined based on the accident object information.

In S1022, the event type label, the event reason label, and the scene location label are imported into a preset accident simulation model, and a fault simulation scene corresponding to the fault event is constructed.

In this embodiment, the electronic device may restore the accident occurrence situation through the event type tag and the event reason tag, and determine the physical scene situation when the accident occurs through the scene location tag, for example, determine that the accident occurs in a corresponding city, country, expressway, mountain land, and the like, so that the electronic device may import the three types of event tags into a preset accident simulation model, thereby being capable of constructing an accident simulation scene corresponding to the traffic accident.

In S1023, the road type associated with the fault event is determined according to the scene location tag, and the vehicle speed of the fault vehicle at the moment of the fault event is determined based on the rated speed section associated with the road type.

In this embodiment, the electronic device may determine a road type corresponding to the occurrence of the fault event according to the scene location tag, and since different roads have corresponding rated speed intervals, after the occurrence of the traffic accident, the vehicle is often in a damaged state, the corresponding driving record may not be directly obtained or may be recovered only after a long time, so as to reduce the waiting time required for generating the fault response report, the electronic device may predict the vehicle speed when the traffic accident occurs according to the road type. Thus, the electronic device may determine the corresponding road type by the scene location tag, for example: the method comprises the steps of determining urban roads, rural roads, interior roads, urban expressways, mountain roads and the like, respectively determining rated speed sections associated with different road types, and predicting the speed of the current fault vehicle according to the rated speed sections, wherein for example, the upper limit of the section of the rated speed section is used as the speed of the vehicle, or the corresponding speed of the vehicle can be calculated based on a preset overspeed coefficient and the rated speed section, and the specific calculation mode can be set according to the actual situation.

In S1024, a safety factor of the failed vehicle is calculated based on the vehicle type tag.

In this embodiment, when a traffic accident occurs, in addition to being related to the vehicle speed, the electronic device has a strong relationship with the structure of the vehicle itself, and in order to be able to more accurately simulate the traffic accident, the electronic device may determine the safety factor corresponding to the failed vehicle in which the traffic accident occurs through the vehicle type tag. Specifically, the mode of determining the safety factor may be: the vehicle type tag may be used to determine: the target vehicle model, the target vehicle service year and other information, and then the vehicle safety factor of the vehicle can be determined through the information of the type.

In S1025, a corresponding vehicle model within the fault simulation scenario is constructed from the safety factor of the faulty vehicle and the vehicle speed.

In this embodiment, after obtaining the safety factor and the vehicle speed of the faulty vehicle, the electronic device may construct a vehicle model corresponding to the faulty vehicle in a fault simulation scene, where an appearance of the vehicle model may be determined according to a vehicle type tag, a rigidity of the vehicle model may be determined according to the safety factor, and a motion trajectory of the vehicle simulation in the fault simulation scene may be restored according to the vehicle speed, so that the simulation of a fault event may also be completed under the condition that video data of the faulty vehicle when the faulty vehicle occurs cannot be quickly retrieved or a blind spot is monitored.

In S1026, the vehicle model is controlled to move in the fault simulation scene, fault restoration data is generated, and the collision dimension score of the accident object is generated through the fault restoration data.

In this embodiment, the electronic device may control the vehicle model to move along the motion trajectory in the fault simulation scene according to the determined motion trajectory, so as to obtain collision data when a collision occurs, determine relevant information such as a collision depth, a collision direction, and a collision strength corresponding to the occurrence of the current traffic accident, and determine a corresponding collision dimension score. Due to the high degree of collision, the degree of injury of the accident object is directly and strongly correlated, and in order to improve the accuracy of recognition of subsequent object images, a corresponding collision dimension score needs to be determined.

At S1027, a subject representation of the accident subject is generated based on the collision dimension score, the occupation label, and the age label.

In this embodiment, the electronic device may determine a body basis score of the accident object according to the occupation label and the age label of the accident object, so as to generate an object representation of the accident object based on the collision dimension score and the body basis score.

In the embodiment of the application, the fault event is restored through the plurality of event labels, so that the corresponding collision dimensionality score can be obtained, the fault response method can be suitable for a larger scene, the event restoration can be completed without acquiring a traffic video of three parties, the waiting time of a fault response report is reduced, and the fault response efficiency is greatly improved.

Fig. 4 shows a flowchart of a specific implementation of a method S1027 for responding to a fault event according to a third embodiment of the present invention. Referring to fig. 4, with respect to the embodiment shown in fig. 3, in the method for responding to a fault event provided in this embodiment, S1027 includes: s401 to S404 are specifically detailed as follows:

in S401, a body base score of the accident subject is determined from the occupation label and the age label.

In this embodiment, the electronic device may predict the exercise condition of the user in the daily life process according to the professional label corresponding to the accident object, for example, if the accident object is a sports teacher or a fitness coach, a certain exercise may be kept in the working life process, and based on this, the corresponding physical quality is high; on the contrary, if the accident object is a programmer or a game developer, the work intensity is high, the exercise is less, and the corresponding physical quality can be low. Of course, the physical quality of the accident subject is also correlated with age, so the physical basic score of the accident subject can be determined based on the two tags.

In a possible implementation manner, different career labels may correspond to one score weighted value, different age ranges may also correspond to one score basic value, and the electronic device may determine the score weighted value of the accident object according to the career labels, determine the score basic value corresponding to the range of the accident object according to the age labels, and superimpose the score weighted value on the score basic value, so as to calculate the body basic score.

In S402, determining a disease type associated with the occupation label according to a preset corresponding relationship between occupation and common diseases, and determining a dimensional score of existing diseases of the accident object based on the disease type.

In this embodiment, the electronic device stores a corresponding relationship between occupation and common diseases, and after determining the occupation label of the accident object, the electronic device may predict the possible occupation diseases of the accident object through the corresponding relationship, so as to determine the disease type associated with the occupation label, and determine to obtain the corresponding existing disease dimensional score.

In S403, the event description speech fed back by the accident object is received, and an emotional dimension score is determined based on the event description language.

In this embodiment, in the process of acquiring event data, a worker may simultaneously acquire an event description voice of an accident object corresponding to the current fault event. Since the actual condition of the fault event is most known about the accident object, in order to improve the understanding degree of the fault event condition, the electronic device may collect event description voices and may not generate corresponding event data based on the event description voices.

In this embodiment, the voice signal may also represent other information besides the text, that is, emotion information of the accident object, besides the situation of the fault event, and the electronic device may extract a voice voiceprint corresponding to the event description voice, and analyze the voice voiceprint to determine an emotion dimension score corresponding to the accident object.

Further, as another embodiment of the present application, the above manner of determining the emotion dimension score may adopt the following steps:

step 1: determining a decibel characteristic parameter set according to the event description voice; the decibel characteristic parameter set comprises: decibel extremum, decibel mean, and decibel mean square error.

Step 2: and obtaining at least one candidate emotion type based on the decibel characteristic parameter set and the basic decibel value.

And step 3: and matching the event description voice with the standard voice waveform of each candidate emotion type to determine a target emotion type.

And 4, step 4: determining the emotion dimension score according to the target emotion type.

In this embodiment, the electronic device may perform signal analysis on the event description speech to generate a signal waveform corresponding to the event description speech, where the signal waveform is the signal waveform in the time domain, and thus the corresponding signal amplitude is a decibel value of the speech signal, and then the decibel characteristic parameter set may be determined according to the signal waveform. The decibel characteristic parameter set specifically includes a decibel extreme value, a decibel mean value and a decibel mean square error. The electronic equipment can store a corresponding basic decibel value in a calm state, the electronic equipment can compare the decibel characteristic parameter with the basic decibel value, and the voice decibel has corresponding characteristics under different emotions of people, so that the electronic equipment can compare the basic decibel value with the basic decibel value in the calm state, can determine at least one candidate emotion type, and can perform primary evaluation on the emotion of an accident object.

In a possible implementation manner, the above basic decibel value may be obtained before an accident occurs, and a worker may contact the accident object and may collect the decibel value collected by the user in a daily process during the contact. Namely, the basic decibel values corresponding to different users are different.

In this embodiment, the electronic device may obtain a standard voice waveform corresponding to each candidate emotion type, and respectively calculate a voiceprint signal of each event description voice and the standard voice waveform to perform similarity calculation, so as to calculate a matching degree corresponding to each candidate emotion type, and select the candidate emotion type with the highest matching degree as the target emotion type corresponding to the accident object. The electronic device can determine a corresponding emotion dimension score according to the target emotion type.

In the embodiment of the application, the event description voice of the accident object is collected and analyzed, so that the corresponding target emotion type can be accurately determined, the emotion dimensionality score is obtained, and the accuracy of the emotion dimensionality score is improved.

In S404, generating the object representation according to the body base score, the existing illness dimension score, the collision dimension score and the emotion dimension score; the object representation is used for predicting the injury of the accident object.

In this embodiment, the object representation of the accident object may be generated based on the body basis score, the existing disease dimension score, the collision dimension score, and the emotion dimension score of the accident object, so that injury of the accident event by the object representation may be predicted.

In the embodiment of the application, the body condition of the user is predicted through the accident object label, so that a plurality of dimension scores related to the accident object can be obtained, the corresponding object portrait can be determined, and the accuracy of the object portrait is improved.

Fig. 5 is a flowchart illustrating a specific implementation of a method for responding to a failure event according to a fourth embodiment of the present invention. Referring to fig. 5, with respect to the embodiment shown in fig. 1, the method for responding to a fault event according to this embodiment further includes, before S103: S501-S507 are detailed as follows:

further, the event tag includes: a traffic scene tag and an accident object tag;

in S501, a plurality of first parallel lines associated with the number of first tags corresponding to the traffic scene tag are called, and first object data corresponding to each of the traffic scene tags is extracted from the object database; each first parallel stroke corresponds to one traffic scene label;

in S502, data intersection identification is performed on all the first object data to obtain a first object group.

In this embodiment, in order to reduce unnecessary matching operations of object representations, the electronic device may extract a target history object with a high correlation to a failure event. Because the data in the object database is more, in order to improve the searching efficiency, the electronic equipment can carry out multi-thread synchronous searching through parallel threads. The traffic scene tag and the accident object tag are independent from each other, so that the search task of the accident object tag can be executed while the search is performed based on the traffic scene tag. The electronic device may therefore create two parallel thread groups, one of which is a first parallel thread for searching for traffic scene tags and the other of which is a second parallel thread for searching for accident object tags.

In this embodiment, the history object data in the object database may be associated with a corresponding history tag, and the history tag may be used as index information of the history object data to improve the efficiency of subsequent search. Therefore, the rate of the electronic device for performing label matching through the thread is greater than the rate of content matching after data analysis, and therefore the efficiency of target historical object identification can be improved.

In this embodiment, the electronic device creates a plurality of first parallel threads associated with the number of first tags, where each first parallel thread is used to extract historical object data of a traffic scene tag including a certain tag dimension, that is, the first object data, from an object database. For example, a traffic scenario tag for a fault event includes: the three traffic scene tags of "vehicle type a", "vehicle age 4 years" and "urban road" may be called by the electronic device, and the electronic device may search the object database for the first object data including the tag of "vehicle type a", the first object data including the tag of "vehicle age 4 years", and the first object data including the tag of "urban road", respectively. Then, the electronic device may perform intersection identification on the three first object data, extract the first object data simultaneously including the three traffic scene tags, and obtain a first object group.

In S503, calling a plurality of second parallel threads associated with a second tag number corresponding to the accident object tag, and extracting second object data corresponding to each accident object tag from the object database; each second parallel thread corresponds to one accident object label.

In S504, data intersection identification is performed on all the second object data to obtain a second object group.

In this embodiment, similar to searching for the first object group related to the traffic scene tag, when determining the second object group, the electronic device may also invoke a plurality of second parallel threads, where each second parallel thread is configured to search for historical object data of an accident object tag including any tag dimension, so as to obtain second object data corresponding to the accident object tag, and then perform intersection identification on all the second object data, so as to obtain the second object group.

In S505, a candidate object group is determined according to the first object group and the second object group.

In this embodiment, after determining the object groups corresponding to the two dimensions, that is, the first object group and the second object group, the electronic device may also perform intersection identification, so as to determine a candidate object group including an event label that is the same as that of the failure event.

In S506, a multidimensional fusion vector related to the fault event is constructed according to all the traffic scene labels and the accident object labels.

In this embodiment, the electronic device may perform vectorization processing on the traffic scene tag and the accident object tag, so as to construct and obtain a corresponding fault event multidimensional fusion vector. The multidimensional fusion vector is specifically used for determining the content of a key event of the fault event, namely, the vector obtained by extracting the features of event data.

In S507, extracting a target history object matched with the multidimensional fusion vector from the candidate object group; the historical representation is generated based on historical failure events of the target historical object.

In this embodiment, the electronic device may perform content matching on the multidimensional fusion vector and the historical object data recorded in the candidate object group, calculate a content association degree, and if the content association degree is greater than a preset association threshold, identify the historical object data in the candidate object group as the target historical object matched with the fault event. Because the time for calculating the content relevance is longer than the time for matching the labels, the extraction efficiency of the target historical object can be improved by determining the candidate object group and then calculating the content relevance.

Fig. 6 shows a flowchart of a specific implementation of a method S101 for responding to a fault event according to a fifth embodiment of the present invention. Referring to fig. 6, with respect to the embodiment described in any one of fig. 1 to 5, in the method for responding to a fault event provided by this embodiment, S101 includes: s1011 to S1014 are specifically described as follows:

in S1011, receiving raw event data fed back by a recording person of the fault event; the original event data is obtained based on the natural language description of the recorder; the original event data contains a plurality of degree parameters of event description dimensions.

In S1012, extracting a degree correction algorithm associated with the person identification of the recording person from a correction algorithm library; the degree correction algorithm is generated after training through difference information between the historical description language of the recording personnel and historical fault events.

In S1013, the degree parameters corresponding to the event description dimensions are respectively imported into the degree correction algorithm to obtain correction parameters of the event description dimensions.

In this embodiment, different recorders may have a certain difference in description of the same event, and in order to improve accuracy of event data, the electronic device may perform data cleaning on original event data fed back by the recorders, so as to reduce influence on the event data due to subjective factors. Based on the method, the electronic equipment can construct a corresponding program correction algorithm according to the description habits of different recording personnel. The description habit of the recording personnel can be determined according to the historical description language acquired by the recording personnel in historical time and the difference degree between the historical fault events determined according to actual conditions.

Illustratively, if the fault event is a traffic accident event, if a certain event description dimension is an impact depth of a vehicle, in the current fault event, the impact depth is 0.5m, a certain recording person describes the depth as being "deeper" and another recording person describes the depth as being "shallower", so that descriptions of different recording persons for the same phenomenon may also differ, and based on this, the electronic device may perform data correction through a degree correction algorithm.

In this embodiment, the electronic device may import each degree parameter into the degree correction algorithm, so as to perform de-subjectivity processing on each degree parameter to obtain a corresponding correction parameter.

In S1014, the event data is generated based on the correction parameters of all the event description dimensions.

In this embodiment, the electronic device may encapsulate all the correction parameters to obtain corresponding event data, so as to improve the accuracy of the subsequently generated event tag.

In the embodiment of the application, the corresponding degree correction algorithm is established for different recording personnel, and the original event data collected by the recording personnel can be subjected to data cleaning through the degree correction algorithm, so that the event data with reduced subjective factors can be obtained, and the accuracy of subsequent processing is improved.

Fig. 7 shows a flowchart of a specific implementation of the method S104 for responding to a failure event according to the sixth embodiment of the present invention. Referring to fig. 7, with respect to the embodiment described in any one of fig. 1 to 5, in the method for responding to the fault event provided by this embodiment, S104 includes: s1041 to S1045 are specifically detailed as follows:

in S1041, respectively obtaining a response flow report corresponding to each historical failure event;

in S1042, process clustering is performed on all the response process reports to obtain at least one process group; the flow similarity between the response flow reports in each flow group is greater than a preset similarity threshold;

in S1043, calculating a recommendation confidence corresponding to each flow group according to the image similarity of the accident object corresponding to each flow group;

in S1044, determining a display priority of each flow group according to a descending order of the recommended confidence;

in S1045, the failure response report is generated according to the display priority and the recommended response flow corresponding to the flow group.

In this embodiment, in order to improve readability of the fault response report, the electronic device may perform clustering processing on the response flow reports associated with the historical fault events, and encapsulate the response flow reports with higher flow similarity in the same flow group, so that all the response flow reports can be grouped. Then, the electronic device may determine, according to the association degree between each flow group and the fault event, a recommendation confidence corresponding to the response flow report corresponding to the flow group. The recommendation confidence is related to the image similarity corresponding to the process group, and the higher the image similarity with the accident object, i.e. the more similar the accident event, the higher the corresponding recommendation confidence. The electronic equipment can be used as the display priority corresponding to the response flow report according to the magnitude order of the recommendation confidence, so that a user can conveniently view the response flow report corresponding to the flow group with high relevance, and the viewing efficiency of the user is improved.

Fig. 8 is a block diagram illustrating a structure of a device for responding to a failure event according to an embodiment of the present invention, where the device for responding to a failure event includes units for executing steps implemented by an encryption device in the corresponding embodiment of fig. 1. Please refer to fig. 1 and fig. 1 for the corresponding description of the embodiment. For convenience of explanation, only the portions related to the present embodiment are shown.

Referring to fig. 8, the response means of the failure event includes:

an event data receiving unit 81 for receiving event data of a fault event to be processed; the event data includes: accident object information and accident scene information;

an object representation generation unit 82 for generating a plurality of event tags associated with the fault event from the event data and generating an object representation relating to the fault object based on the event tags;

an object representation matching unit 83 for calculating representation similarities of the object representation and a plurality of historical representations in the object database, respectively, and determining at least one historical failure event matching the accident object based on the representation similarities; each historical image corresponds to one historical fault event;

a fault response report generating unit 84, configured to generate a fault response report corresponding to the fault event based on the response procedure report corresponding to the historical fault event.

Optionally, the event tag comprises: a traffic scene tag and an accident object tag; the traffic scene tag includes: an event type tag, an event reason tag, a vehicle type tag and a scene place tag which are determined based on the accident scene information; the incident object tag includes: an occupation label and an age label determined based on the accident object information;

the object representation generating unit 82 comprises:

the tag keyword extraction unit is used for determining tag keywords contained in the event data according to tag keywords of a plurality of preset tag dimensions, and obtaining the event tags based on the contained tag keywords;

the fault simulation scene construction unit is used for importing the event type label, the event reason label and the scene place label into a preset accident simulation model and constructing a fault simulation scene corresponding to the fault event;

the vehicle speed determining unit is used for determining the road type associated with the fault event according to the scene place tag, and determining the vehicle speed of the fault vehicle at the moment of the fault event based on the rated speed section associated with the road type;

the safety coefficient determining unit is used for calculating the safety coefficient of the vehicle with the fault based on the vehicle type label;

the vehicle model building unit is used for building a corresponding vehicle model in the fault simulation scene according to the safety coefficient of the fault vehicle and the vehicle speed;

the collision dimension score determining unit is used for controlling the vehicle model to move in the fault simulation scene, generating fault restoration data and generating a collision dimension score of the accident object through the fault restoration data;

and the first portrait construction unit is used for generating an object portrait of the accident object according to the collision dimension score, the occupation label and the age label.

Optionally, the first portrait construction unit includes:

a body base score determining unit for determining a body base score of the accident subject according to the occupation label and the age label;

the disease dimension score determining unit is used for determining the disease type associated with the occupation label through the preset corresponding relation between occupation and common diseases, and determining the existing disease dimension score of the accident object based on the disease type;

the emotion dimension score determining unit is used for receiving the event description voice fed back by the accident object and determining an emotion dimension score based on the event description language;

a second portrait construction unit, configured to generate the object portrait according to the body basic score, the existing disease dimension score, the collision dimension score, and the emotion dimension score; the object representation is used for predicting the injury of the accident object.

Optionally, the emotion dimension score determining unit includes:

a basic decibel value determining unit, configured to extract a historical object voice associated with the accident object from an object voice library, and determine a basic decibel value according to a historical voice amplitude of the historical object voice; the base decibel value is used for determining the voice decibel of the accident object in the emotional steady state;

a feature parameter set determining unit, configured to determine a decibel feature parameter set according to the event description speech; the decibel characteristic parameter set comprises: decibel extreme value, decibel mean value and decibel mean square error;

a candidate emotion type determination unit, configured to obtain at least one candidate emotion type based on the decibel feature parameter set and the basic decibel value;

the target emotion type determining unit is used for matching the event description voice with the standard voice waveform of each candidate emotion type to determine a target emotion type;

and the emotion dimension score determining unit is used for determining the emotion dimension score according to the target emotion type.

Optionally, the event tag comprises: a traffic scene tag and an accident object tag; the response means further comprises:

a first parallel unit, configured to invoke a plurality of first parallel threads associated with a first tag number corresponding to the traffic scene tag, and extract first object data corresponding to each of the traffic scene tags from the object database; each first parallel stroke corresponds to one traffic scene label;

the first object group determining unit is used for performing data intersection identification on all the first object data to obtain a first object group;

a second parallel unit, configured to invoke a plurality of second parallel threads associated with a second tag number corresponding to the accident object tag, and extract second object data corresponding to each of the accident object tags from the object database; each second parallel thread corresponds to one accident object label;

the second object group determining unit is used for performing data intersection identification on all the second object data to obtain a second object group;

a candidate object group determination unit configured to determine a candidate object group based on the first object group and the second object group;

the multi-dimensional fusion vector generating unit is used for constructing a multi-dimensional fusion vector related to the fault event according to all the traffic scene labels and the accident object labels;

a target history object determination unit for extracting a target history object matched with the multi-dimensional fusion vector from the candidate object group; the historical representation is generated based on historical failure events of the target historical object.

Optionally, the event data receiving unit 81 includes:

the original event data receiving unit is used for receiving original event data fed back by a recording person of the fault event; the original event data is obtained based on the natural language description of the recorder; the original event data contains a plurality of degree parameters of event description dimensionality;

a correction algorithm determination unit for extracting a degree correction algorithm associated with the person identification of the recording person from a correction algorithm library; the degree correction algorithm is generated after being trained through difference information between the historical description language of the recording personnel and the historical fault event;

the correction unit is used for respectively importing the degree parameters corresponding to the event description dimensions into the degree correction algorithm to obtain the correction parameters of the event description dimensions;

and the correction parameter packaging unit is used for generating the event data based on the correction parameters of all the event description dimensions.

Optionally, the fault response report generating unit 84 includes: a response flow report determination unit, configured to obtain response flow reports corresponding to the historical fault events respectively;

the flow group dividing unit is used for carrying out flow clustering on all the response flow reports to obtain at least one flow group; the flow similarity between the response flow reports in each flow group is greater than a preset similarity threshold;

a recommendation confidence determining unit, configured to calculate a recommendation confidence corresponding to each flow group according to the image similarity of the accident object corresponding to each flow group;

the display priority determining unit is used for determining the display priority of each flow group according to the descending order of the recommendation confidence degrees;

and generating a report according to the display priority and the recommended response flow corresponding to the flow group to generate the fault response report.

Therefore, the response device for the fault event provided by the embodiment of the invention can also receive the event data about the fault event to be processed, analyze the event data to obtain a plurality of event tags related to the fault event, generate the object portrait of the fault object related to the fault event according to the event tags, calculate the portrait similarity between the object portrait and each historical portrait in the object database, and determine at least one historical fault event matched with the object portrait according to the portrait similarity. Compared with the existing fault response technology, the method and the device have the advantages that the response process is judged through experience of workers, historical fault events similar to the current fault events are identified, and the response process reports of the historical fault events are reused, so that the stability of the fault process can be greatly improved, the fault response reports can be automatically generated in a mode of being matched with the object database under the condition of dealing with a large number of fault events, and the generation efficiency of the response fault reports is greatly improved.

It should be understood that, in the structural block diagram of the fault event response apparatus shown in fig. 8, each module is used to execute each step in the embodiment corresponding to fig. 1 to fig. 7, and each step in the embodiment corresponding to fig. 1 to fig. 7 has been explained in detail in the above embodiment, and specific reference is made to the relevant description in the embodiments corresponding to fig. 1 to fig. 7 and fig. 1 to fig. 7, which is not repeated herein.

Fig. 9 is a block diagram of an electronic device according to another embodiment of the present application. As shown in fig. 9, the electronic apparatus 900 of this embodiment includes: a processor 910, a memory 920, and a computer program 930, such as a program for a response method to a failure event, stored in the memory 920 and executable in the processor 910. The processor 910, when executing the computer program 930, implements the steps in the embodiments of the response method for each fault event described above, such as S101 to S104 shown in fig. 1. Alternatively, the processor 910, when executing the computer program 930, implements the functions of the modules in the embodiment corresponding to fig. 8, for example, the functions of the units 81 to 84 shown in fig. 8, please refer to the related description in the embodiment corresponding to fig. 8.

Illustratively, the computer program 930 may be partitioned into one or more modules, which are stored in the memory 920 and executed by the processor 910 to accomplish the present application. One or more of the modules may be a series of computer program instruction segments capable of performing certain functions, the instruction segments being used to describe the execution of computer program 930 in electronic device 900. For example, the computer program 930 may be divided into respective unit modules, and the respective modules may be specifically functioned as described above.

The electronic device 900 may include, but is not limited to, a processor 910, a memory 920. Those skilled in the art will appreciate that fig. 9 is merely an example of an electronic device 900 and does not constitute a limitation of the electronic device 900 and may include more or fewer components than shown, or some components may be combined, or different components, e.g., the electronic device may also include input-output devices, network access devices, buses, etc.

The processor 910 may be a central processing unit, but may also be other general purpose processors, digital signal processors, application specific integrated circuits, off-the-shelf programmable gate arrays or other programmable logic devices, discrete hardware components, and the like. A general purpose processor may be a microprocessor or any conventional processor or the like.

The storage 920 may be an internal storage unit of the electronic device 900, such as a hard disk or a memory of the electronic device 900. The memory 920 may also be an external storage device of the electronic device 900, such as a plug-in hard disk, a smart card, a flash memory card, etc. provided on the electronic device 900. Further, the memory 920 may also include both internal storage units and external storage devices of the electronic device 900.

The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present application and are intended to be included within the scope of the present application.

Claims

1. A method of responding to a fault event, comprising:

2. The response method of claim 1, wherein the event tag comprises: a traffic scene tag and an accident object tag; the traffic scene tag includes: an event type tag, an event reason tag, a vehicle type tag and a scene place tag which are determined based on the accident scene information; the incident object tag includes: an occupation label and an age label determined based on the accident object information;

3. The response method of claim 2, wherein generating the object representation of the incident object based on the collision dimension score, the occupation label, and the age label comprises:

4. The response method of claim 3, wherein the receiving event description speech fed back by the incident object and determining an emotional dimension score based on the event description language comprises:

determining the emotion dimension score according to the target emotion type.

5. The response method of claim 1, wherein the event tag comprises: a traffic scene tag and an accident object tag;

extracting a target historical object matched with the multi-dimensional fusion vector from the candidate object group; the historical representation is generated based on historical failure events of the target historical object.

6. A response method according to any of claims 1-5, wherein said receiving event data of a pending fault event comprises:

extracting a degree correction algorithm associated with the personnel identification of the recording personnel from a correction algorithm library; the degree correction algorithm is generated after training through difference information between the historical description language of the recording personnel and the historical fault events;

7. The response method according to any one of claims 1 to 5, wherein the generating a fault response report corresponding to the fault event based on the response flow report corresponding to the historical fault event comprises: respectively acquiring a response flow report corresponding to each historical fault event;

8. An apparatus for generating a vehicle report, comprising:

the event data receiving unit is used for receiving event data of a fault event to be processed; the event data includes: accident object information and accident scene information;

an object representation generation unit for generating a plurality of event tags associated with the fault event from event data and generating an object representation relating to an accident object based on the event tags;

an object representation matching unit to calculate representation similarities for the object representation and a plurality of historical representations within an object database, respectively, and determine at least one historical failure event matching an incident object based on the representation similarities; each historical image corresponds to one historical fault event;

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method of any of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1 to 7.