CN115439951B - Abnormal fusing processing method and device, electronic equipment and medium - Google Patents
Abnormal fusing processing method and device, electronic equipment and medium Download PDFInfo
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Abstract
The disclosure relates to a processing method, a device, electronic equipment and a medium for abnormal fusing; wherein the method comprises the following steps: acquiring driving data of a full-quantity vehicle, wherein the driving data comprise current values during driving, and the full-quantity vehicle is used for representing a preset number of vehicles; based on a preset time detection window, establishing an abnormal fusing model of a preset number of current values when the vehicle runs, wherein the abnormal fusing model is used for predicting the working states of the fuses when the preset number of vehicles run; and processing the vehicle with the fuse in the abnormal state according to the abnormal fusing model. According to the embodiment of the disclosure, the fuse with the abnormal working state can be effectively predicted, so that an abnormal vehicle with the abnormal fuse can be processed, and the problem of driving safety caused by abnormal fuse blowing of the fuse is avoided.
Description
Technical Field
The disclosure relates to the technical field of data processing, and in particular relates to a processing method, a device, electronic equipment and a medium for abnormal fusing.
Background
The fuse is used as an important protection electric device of a battery pack in a vehicle, can effectively protect a battery core in the battery pack from over-current Shanghai, and can also avoid vehicle damage caused by internal faults of the battery pack; the fuse in the vehicle has a rated specification for limiting the current, and the fuse is blown when the current exceeds the specified specification.
However, the fuse needs to fully consider parameters such as battery pack working condition current, voltage and the like in the design and shape selection stage, a certain redundancy design is reserved, and the problem of consistency of product quality of the fuse in manufacturing can cause abnormal fusing in the running process of a vehicle, so that safety hazard is caused to personnel in the vehicle.
Disclosure of Invention
In order to solve the technical problems, the present disclosure provides a method, an apparatus, an electronic device, and a medium for processing abnormal fusing.
In a first aspect, the present disclosure provides a method for handling abnormal fusing, including:
acquiring driving data of a full-quantity vehicle, wherein the driving data comprise current values during driving, and the full-quantity vehicle is used for representing a preset number of vehicles;
based on a preset time detection window, establishing an abnormal fusing model of a preset number of current values when the vehicle runs, wherein the abnormal fusing model is used for predicting the working states of the fuses when the preset number of vehicles run;
and processing the abnormal vehicle with the fuse in the abnormal state according to the abnormal fusing model.
Optionally, before the abnormal fusing model of the current values of the vehicles in the preset number is established based on the preset time detection window, the abnormal fusing model further includes:
Determining identification information of each vehicle in a preset number of vehicles, wherein the identification information comprises a number;
the establishing an abnormal fusing model of a preset number of current values when the vehicle runs based on a preset time detection window comprises the following steps:
Determining the number of detection windows in which large current appears for each vehicle according to at least one current value corresponding to the preset time detection window based on a current threshold and a current overrun frequency threshold, wherein the current threshold is used for screening the large current in the driving data of each vehicle, the current threshold is determined by attribute information of a preset number of vehicles, and the attribute information comprises the type of the vehicle; the current overrun frequency threshold is used for representing the frequency of occurrence of large current of each vehicle in at least one preset time detection window;
And establishing an abnormal fusing model according to the number of detection windows of the large current of each vehicle and the identification information of each vehicle.
Optionally, the determining, based on the current threshold and the threshold of the number of times of current overrun, the number of detection windows in which the heavy current occurs in each vehicle according to the current value corresponding to at least one preset time detection window includes:
detecting that a current value of a target vehicle when running in a target time detection window exceeds a current threshold value, and determining that the target vehicle has large current in the target time detection window; the times of detecting that the target vehicle generates large current in the target time detection window are equal to a threshold value of times of exceeding current limit, and the target detection window is determined to be the detection window of the large current of the target vehicle;
and sequentially detecting the times of occurrence of heavy current of other vehicles in each time detection window, and determining the number of detection windows of occurrence of heavy current of each vehicle.
Optionally, the processing, according to the abnormal fusing model, the abnormal vehicle with the fuse in the abnormal state includes:
Determining inflection point information in the abnormal fusing model, wherein the inflection point information is used for representing the change degree of the number of the detection windows;
determining identification information of the fuse in an abnormal state according to the inflection point information;
And processing the abnormal vehicle corresponding to the identification information.
Optionally, the determining inflection point information in the abnormal fusing model includes:
based on a preset step length, determining a corresponding vehicle numbering period when the change rate of the number of detection windows in the abnormal fusing model is greater than a rate threshold;
And determining the target number in the vehicle number period as inflection point information, wherein the target number is the number corresponding to the intermediate value of the vehicle number period.
Optionally, the processing the abnormal vehicle corresponding to the identification information includes:
and generating an early warning prompt based on the identification information, wherein the early warning prompt is used for indicating to perform fuse abnormality early warning on the abnormal vehicle corresponding to the identification information.
Optionally, before the processing the abnormal vehicle corresponding to the identification information, the method further includes:
Storing the identification information into an abnormal information base, wherein the abnormal information base is used for recording and updating fuse abnormal information, and the fuse abnormal information is used for describing the serial number of a corresponding vehicle of a fuse;
and determining that the identification information is still stored in the abnormal information base within a preset period.
In a second aspect, the present disclosure provides an abnormal fusing processing apparatus, including:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring driving data of a total number of vehicles, the driving data comprise current values during driving, and the total number of vehicles are used for representing a preset number of vehicles;
The building module is used for building abnormal fusing models of a preset number of current values when the vehicle runs based on a preset time detection window, and the abnormal fusing models are used for predicting working states of the fuses when the preset number of vehicles run;
and the processing module is used for processing the abnormal vehicle with the fuse in the abnormal state according to the abnormal fusing model.
Optionally, the method further comprises: a determining module;
The determining module is used for determining the identification information of each vehicle in the preset number of vehicles, wherein the identification information comprises a number;
a setup module comprising: a first determination unit and a building unit;
The first determining unit is used for determining the number of detection windows in which large current appears for each vehicle according to at least one current value corresponding to the preset time detection window based on a current threshold value and a current overrun frequency threshold value, wherein the current threshold value is used for screening the large current in the driving data of each vehicle, the current threshold value is determined through attribute information of the preset number of vehicles, and the attribute information comprises the model number of the vehicle; the current overrun frequency threshold is used for representing the frequency of occurrence of large current of each vehicle in at least one preset time detection window;
the building unit is used for building an abnormal fusing model according to the number of detection windows of the large current of each vehicle and the identification information of each vehicle.
Optionally, the first determining unit is specifically configured to:
detecting that a current value of a target vehicle when running in a target time detection window exceeds a current threshold value, and determining that the target vehicle has large current in the target time detection window; the times of detecting that the target vehicle generates large current in the target time detection window are equal to a threshold value of times of exceeding current limit, and the target detection window is determined to be the detection window of the large current of the target vehicle;
and sequentially detecting the times of occurrence of heavy current of other vehicles in each time detection window, and determining the number of detection windows of occurrence of heavy current of each vehicle.
Optionally, the processing module includes: the device comprises a second determining unit, a third determining unit and a processing unit;
the second determining unit is used for determining inflection point information in the abnormal fusing model, and the inflection point information is used for representing the change degree of the number of the detection windows;
a third determining unit, configured to determine, according to the inflection point information, identification information that the fuse is in an abnormal state;
and the processing unit is used for processing the abnormal vehicle corresponding to the identification information.
Optionally, the second determining unit is specifically configured to:
based on a preset step length, determining a corresponding vehicle numbering period when the change rate of the number of detection windows in the abnormal fusing model is greater than a rate threshold;
And determining the target number in the vehicle number period as inflection point information, wherein the target number is the number corresponding to the intermediate value of the vehicle number period.
Optionally, the processing unit is specifically configured to:
and generating an early warning prompt based on the identification information, wherein the early warning prompt is used for indicating to perform fuse abnormality early warning on the abnormal vehicle corresponding to the identification information.
Optionally, the method further comprises: a storage module;
The storage module is used for storing the identification information into an abnormal information base, wherein the abnormal information base is used for recording and updating the abnormal information of the fuse, and the abnormal information of the fuse is used for describing the serial number of the corresponding vehicle of the fuse;
the determining module is further used for determining that the identification information is still stored in the abnormal information base within a preset period.
In a third aspect, the present disclosure also provides an electronic device, including:
one or more processors;
Storage means for storing one or more programs,
When the one or more programs are executed by the one or more processors, the one or more processors implement the method for handling abnormal fusing according to any one of the embodiments of the present invention.
In a fourth aspect, the present disclosure further provides a computer-readable storage medium having stored thereon a computer program that, when executed by a processor, implements the method for handling abnormal fusing according to any one of the embodiments of the present invention.
Compared with the prior art, the technical scheme provided by the embodiment of the disclosure has the following advantages: the method comprises the steps that driving data of a plurality of vehicles are obtained, wherein the driving data can comprise current values generated in real time when the vehicles run, a plurality of time detection windows can be preset, the plurality of current values are divided, an abnormal fusing model of the current values when the vehicles run is established based on the preset time detection windows, and the abnormal fusing model can be used for predicting the working state of a fuse of each vehicle in the running process, so that the fuse in the abnormal state is effectively predicted, the abnormal vehicles with the fuse in the abnormal state are processed, and the problem of driving safety caused by abnormal fusing of the fuse is avoided.
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The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments of the present disclosure or the solutions in the prior art, the drawings that are required for the description of the embodiments or the prior art will be briefly described below, and it will be obvious to those skilled in the art that other drawings can be obtained from these drawings without inventive effort.
FIG. 1 is a flow chart of a method for handling abnormal fusing according to an embodiment of the present disclosure;
FIG. 2 is a flowchart illustrating another method for handling abnormal fusing according to an embodiment of the present disclosure;
FIG. 3 is a graph of current overrun frequency based on an abnormal fuse model provided by an embodiment of the present disclosure;
FIG. 4 is a graph of another current overrun frequency distribution based on an abnormal fuse model provided by an embodiment of the present disclosure;
FIG. 5 is a graph of a current overrun count profile based on an abnormal fuse model, provided by an embodiment of the present disclosure;
FIG. 6 is a schematic structural diagram of an abnormal fusing processing apparatus according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.
Detailed Description
In order that the above objects, features and advantages of the present disclosure may be more clearly understood, a further description of aspects of the present disclosure will be provided below. It should be noted that, without conflict, the embodiments of the present disclosure and features in the embodiments may be combined with each other.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present disclosure, but the present disclosure may be practiced otherwise than as described herein; it will be apparent that the embodiments in the specification are only some, but not all, embodiments of the disclosure.
With the rapid development of the electric vehicle industry, the electric vehicle maintenance amount has become higher and higher, wherein the battery system (battery pack) is an important power supply part of the electric vehicle, and the safety thereof is particularly important.
The rated specification that sets up on the fuse can be under the condition of overcurrent, through the battery core damage in the effective protection battery package of fusing operation of fuse, simultaneously, can also avoid the serious injury that battery package internal failure arouses.
The main parameters of the fuse include rated current, rated voltage, ambient temperature, reaction speed, etc., and the realization of the capacity of the fuse is required to be performed under the condition of 25 ℃ ambient temperature, however, the service life of the fuse is inversely proportional to the working ambient temperature, that is, the higher the ambient temperature is, the higher the working temperature of the fuse is, the shorter the service life is.
In the design and model selection stage of the fuse, a plurality of parameters such as battery pack working condition current, voltage, working temperature range and the like need to be fully considered, a certain redundancy design needs to be reserved, and abnormal conditions are avoided, but the environment of a vehicle is changeable and complex in the driving process, and the designed fuse is difficult to effectively adapt to all vehicle environments; in addition, the consistency of the product quality of the fuse can also cause abnormal fusing, which leads to serious sit faults, so that the riding safety of personnel in the automobile is difficult to be effectively ensured.
The present disclosure provides a method, an apparatus, an electronic device, and a medium for processing abnormal fusing, where the method, the apparatus, the electronic device, and the medium are configured to obtain driving data of a plurality of vehicles, where the driving data may include current values generated in real time when the vehicles travel, and a plurality of time detection windows may be preset to divide the plurality of current values, and an abnormal fusing model of the plurality of current values when the vehicles travel is established based on the preset time detection windows, where the abnormal fusing model may be used to predict a working state of a fuse of each vehicle during traveling, so as to effectively predict a fuse of which the working state is in an abnormal state, to process an abnormal vehicle of which the fuse is in an abnormal state, and avoid a problem of driving safety caused by abnormal fusing of the fuse.
With particular reference to the exemplary illustration in fig. 1.
Fig. 1 is a flowchart illustrating a method for handling abnormal fusing according to an embodiment of the present disclosure. The method of the embodiment can be executed by an abnormally fused processing device, and the device can be realized in a hardware/software mode and can be configured in electronic equipment. The abnormal fusing processing method can be realized. As shown in fig. 1, the method specifically includes the following steps:
s110, acquiring driving data of the full-quantity vehicle, wherein the driving data comprise current values during driving.
Wherein, the full-quantity vehicle is used for representing a preset quantity of vehicles.
For example, there are 60000 vehicles for which fuse abnormality detection is required, the preset number for characterization is 60000, and the total number of vehicles is 60000 vehicles.
It should be noted that, in the same batch of detected vehicles, the vehicle model of each vehicle is similar, that is, the vehicle model of each vehicle in the total number of vehicles is similar, so that the validity of detection is effectively ensured.
The driving data of the full-quantity vehicle can be obtained through the reported information of the corresponding vehicle controllers, and each vehicle controller can acquire the current value responded by the vehicle in the normal driving process in real time.
It should be noted that, when the vehicle control is collecting the current value, the electric quantity value of the vehicle during running can be obtained based on the sampling period by setting a certain sampling period, so that the problems that the number of the obtained current values is too large, the detection difficulty is increased, and meanwhile, the sampling load is increased are avoided.
For example, the sampling period may be set to 1 s/time, i.e., the controller of vehicle a collects the current value of the vehicle every 1s during the running of vehicle a.
In addition, the reporting time of the information reported by the vehicle controller can also be set, for example, sampling information of the period is carried out in a fixed period every day; wherein, reporting time can be in units of hours/minute/day, which is not specifically limited in the present disclosure.
After the driving data of the full-quantity vehicle are acquired, the driving data can be cleaned, and detection is prevented from being influenced by abnormal current values; the data cleansing may include: current value null value elimination, current value repetition value deletion, and the like.
S120, based on a preset time detection window, establishing an abnormal fusing model of a preset number of current values when the vehicle runs.
The abnormal fusing model is used for predicting working states of the fuses when a preset number of vehicles run.
The preset time detection window may be used to characterize the dividing time of the current value, and if 5 minutes may be set as a dividing interval, then 5 minutes may be used as a data classifying period of the primary time detection window.
The preset time detection window may include a plurality of time detection windows.
For example, in a period of 15:00-16:00 of a certain day, 5 minutes is taken as a detection period, 12 time detection windows can be corresponding, and the time detection windows can be respectively ：15:00-15:05、15:05-15:10、15:10-15:15、15:15-15:20、15:20-15:25、15:25-15:30、15:30-15:35、15:35-15:40、15:40-15:45、15:45-15:50、15:50-15:55、15:55-16:00.
S130, processing the abnormal vehicle with the fuse in the abnormal state according to the abnormal fusing model.
According to the abnormal fusing model, an abnormal vehicle with the fuse in an abnormal state can be predicted, and abnormal processing such as vehicle factory return and vehicle early warning can be timely carried out.
According to the abnormal fusing processing method provided by the embodiment, the driving data of a plurality of vehicles are obtained, wherein the driving data can comprise current values generated in real time when the vehicles run, a plurality of time detection windows can be preset, the plurality of current values are divided, and an abnormal fusing model of the current values when the vehicles run is established based on the preset time detection windows, wherein the abnormal fusing model can be used for predicting the working state of a fuse in the running process of each vehicle, so that the fuse in the abnormal state is effectively predicted, the abnormal vehicle in the abnormal state of the fuse is processed, and the problem of running safety caused by the abnormal fusing of the fuse is avoided.
Fig. 2 is a flowchart illustrating another abnormal fusing processing method according to an embodiment of the present disclosure. The present embodiment is based on the foregoing embodiment, and further, before S120, the present embodiment may further include:
s111, determining identification information of each vehicle in a preset number of vehicles.
Wherein the identification information includes a number.
Wherein each vehicle may be numbered based on the number arrangement.
For example, the preset number 60000, 60000 vehicles may be numbered from the numbers 1-60000 (integers), wherein each number 1-60000 may correspond to a vehicle.
One possible implementation of S120 is as follows:
S1201, based on the current threshold value and the current overrun frequency threshold value, determining the number of detection windows in which large current appears in each vehicle according to the current value corresponding to at least one preset time detection window.
The current threshold is used for screening large currents in driving data of each vehicle, and the current overrun frequency threshold is used for representing the frequency of occurrence of the large currents of each vehicle in at least one preset time detection window.
The number of detection windows for each vehicle to generate large current is equal to the number of time detection windows corresponding to the threshold value of the current overrun times.
Wherein, optionally, the current threshold is determined by attribute information of a preset number of vehicles, and the attribute information may include a vehicle model, for example, may be set as: 500A, 550A, 600A, etc., thereby enabling different current thresholds to be set for different vehicle models, enhancing the flexibility of detection.
Wherein, the threshold value of the current overrun times can be set as follows: 2 or 3, etc.
In combination with the above example, when the time detection window is ：15:00-15:05、15:05-15:10、15:10-15:15、15:15-15:20、15:20-15:25、15:25-15:30、15:30-15:35、15:35-15:40、15:40-15:45、15:45-15:50、15:50-15:55、15:55-16:00, and the current overrun times threshold is 2 and the current threshold is 550A, the number of detection windows in which the vehicle a has a large current is 4 in the time periods 15:00-15:05, 15:20-15:25, 15:35-15:40 and 15:55-16:00, respectively, and the current values of the two times exceed 550A.
In this embodiment, optionally, based on the current threshold and the current overrun frequency threshold, determining the number of detection windows in which a large current occurs in each vehicle according to the current value corresponding to at least one preset time detection window includes:
detecting that the current value of the target vehicle when running in the target time detection window exceeds a current threshold value, and determining that the target vehicle has large current in the target time detection window; the number of times that the target vehicle generates large current in the target time detection window is equal to the threshold value of the current overrun number, and the target detection window is determined to be the detection window of the large current of the target vehicle;
and sequentially detecting the times of occurrence of heavy current of other vehicles in each time detection window, and determining the number of detection windows of occurrence of heavy current of each vehicle.
In combination with the above example, the current threshold is 550A, the current overrun frequency threshold is 2, the preset time detection windows are ：15:00-15:05、15:05-15:10、15:10-15:15、15:15-15:20、15:20-15:25、15:25-15:30、15:30-15:35、15:35-15:40、15:40-15:45、15:45-15:50、15:50-15:55、15:55-16:00, total vehicles respectively: vehicle 1, vehicle 2, and vehicle 60000, and the number of detection windows in which a large current appears in vehicle 1 (e.g., vehicle a described above) is 4, and then the same large current detection as described above is performed on vehicle 2, and vehicle 60000, so that the number of detection windows in which a large current appears in each of the total number of vehicles is effectively determined.
S1202, an abnormal fusing model is built according to the number of detection windows of large current of each vehicle and identification information of each vehicle.
The abnormal fusing model can be displayed in a two-dimensional coordinate inner curve display form, an abscissa can be a vehicle number, such as 1-60000, and an ordinate can be the number of detection windows for a large current when the vehicle appears for a preset number of times (a current overrun number threshold, such as 2/3).
For example, fig. 3 is a graph of a current overrun frequency distribution based on an abnormal fusing model, wherein the current overrun frequency threshold is 2 and the current threshold is 500A; the number of the vehicles is respectively: 1-60000, and time detection windows for high current occurrence are respectively: 0-500.
FIG. 4 is a graph of another current overrun frequency distribution based on an abnormal fusing model, wherein the current overrun frequency threshold is 3 and the current threshold is 600A; the number of the vehicles is respectively: 1-50000, and time detection windows for high current appear respectively: 0-350.
Based on the description of the above embodiment, in this embodiment, optionally, according to an abnormal fusing model, an abnormal vehicle in which a fuse is in an abnormal state is processed, including:
And determining inflection point information in the abnormal fusing model, wherein the inflection point information is used for representing the change degree of the number of the detection windows.
The inflection point information can effectively reflect the rapid increasing trend of the number of the detection windows, so that abnormal vehicles of the fuse can be effectively screened out.
In combination with the above example, the inflection point information is found on the basis of fig. 3, which can be seen as an example in fig. 5.
In fig. 5, a specific point corresponding to the selected inflection point information, such as point a, is defined by point a, the number of the vehicle corresponding to the left area (e.g., solid coil exit area) of point a is the normal vehicle, and the number of the vehicle corresponding to the right area (e.g., virtual coil exit area) of point a is the abnormal vehicle.
Determining identification information of the fuse in an abnormal state according to the inflection point information;
And processing the abnormal vehicle corresponding to the identification information.
Therefore, abnormal vehicles and normal vehicles can be effectively distinguished based on inflection point information, abnormal vehicles are screened out to be correspondingly processed, and processing timeliness is further improved.
In this embodiment, optionally, determining inflection point information in the abnormal fusing model includes:
Based on a preset step length, determining a corresponding vehicle numbering period when the change rate of the number of detection windows in the abnormal fusing model is greater than a rate threshold;
and determining the target number in the vehicle number period as inflection point information, wherein the target number is the number corresponding to the intermediate value of the vehicle number period.
If the change rate of the number of detection windows in the step interval is greater than the pre-designated rate threshold, it indicates that the fuse of the vehicle in the preset step has obvious change, and an abnormal condition exists (i.e. the vehicle has potential risk and needs to be warned), and the corresponding curve is steeper, such as the curve in the area to the right of the inflection point in fig. 4.
If the rate of change of the number of detection windows in the step interval is less than or equal to the pre-specified rate threshold (which can be ignored, and is usually smaller, for example, 0.005), it indicates that the fuse of the vehicle in the preset step is not significantly changed, and no abnormal condition exists, and the corresponding curve is more stable, for example, the curve in the area on the left of the inflection point in fig. 4.
Wherein, the number corresponding to the inflection point information can be determined in the determined vehicle number period.
For example, if the rate of change of the number of detection windows is greater than a pre-specified rate threshold of 0.005 in 30000-32000 steps, it may be determined that the number corresponding to the inflection point information is 31000.
Therefore, the inflection point information for distinguishing the abnormal vehicle from the normal vehicle can be effectively identified according to the change trend of the curve based on the curve corresponding to the abnormal fusing model.
In this embodiment, optionally, the processing of the abnormal vehicle corresponding to the identification information includes:
And generating an early warning prompt based on the identification information, wherein the early warning prompt is used for indicating to perform fuse abnormality early warning on the abnormal vehicle corresponding to the identification information.
When determining the number of the abnormal vehicle, the detection personnel can be informed in a warning prompt mode, so that the detection personnel can find out the abnormal vehicle in time and process the abnormal vehicle, and the processing mode can be as follows: vehicle recall, exception alert, etc.
It should be noted that, the abnormality alert for the abnormal vehicle may be by: the vehicle is executed by means of personal telephones, short messages, mails and the like.
In this embodiment, optionally, before the processing of the abnormal vehicle corresponding to the identification information, the method further includes:
Storing the identification information into an abnormal information base, wherein the abnormal information base is used for recording and updating abnormal information of the fuse, and the abnormal information of the fuse is used for describing the serial number of the corresponding vehicle of the fuse;
and determining that the identification information is still stored in the abnormal information base within a preset period.
Before the early warning prompt is generated based on the identification information, the vehicle can be recorded in a way of marking the vehicle, and whether the early warning prompt is generated or not can be determined according to the recorded condition of the vehicle within a period of time.
In combination with the above example, when it is determined that the number 35000 of the vehicle is an abnormal vehicle, the number of the vehicle or other identification information of the vehicle may be recorded into the abnormal information base, the vehicle is continuously monitored, if it is detected that the vehicle is still stored in the abnormal information base within a preset period (for example, two months), the vehicle is indicated to have a potential risk, and an early warning prompt is generated.
If the vehicle is detected to be not stored in the abnormal information base within the preset time period (such as two months), the vehicle is indicated to have no risk, and an early warning prompt is not required to be generated, so that the problem of false early warning caused by single detection errors is avoided.
It should be noted that, the abnormal information base stores the vehicle information (such as the number) with potential risk for human, wherein, the risk can be removed through detecting the vehicle again, the vehicle information in the abnormal information base can be updated in real time, which is convenient for optimizing the storage space and improving the real-time property of the stored information.
FIG. 6 is a schematic structural diagram of an abnormal fusing processing apparatus according to an embodiment of the present disclosure; the device is configured in the electronic equipment, and can realize the abnormal fusing processing method according to any embodiment of the application. The device specifically comprises the following steps:
an obtaining module 610, configured to obtain driving data of a total number of vehicles, where the driving data includes a current value during driving, and the total number of vehicles is used to represent a preset number of vehicles;
The establishing module 620 is configured to establish, based on a preset time detection window, a preset number of abnormal fusing models of current values when the vehicle runs, where the abnormal fusing models are used to predict working states of the fuses when the preset number of vehicles run;
and the processing module 630 is configured to process an abnormal vehicle in which the fuse is in an abnormal state according to the abnormal fusing model.
In this embodiment, optionally, the apparatus of this embodiment further includes: a determining module;
The determining module is used for determining the identification information of each vehicle in the preset number of vehicles, wherein the identification information comprises a number;
The setup module 620 includes: a first determination unit and a building unit;
The first determining unit is used for determining the number of detection windows in which large current appears for each vehicle according to at least one current value corresponding to the preset time detection window based on a current threshold value and a current overrun frequency threshold value, wherein the current threshold value is used for screening the large current in the driving data of each vehicle, the current threshold value is determined through attribute information of the preset number of vehicles, and the attribute information comprises the model number of the vehicle; the current overrun frequency threshold is used for representing the frequency of occurrence of large current of each vehicle in at least one preset time detection window;
the building unit is used for building an abnormal fusing model according to the number of detection windows of the large current of each vehicle and the identification information of each vehicle.
In this embodiment, optionally, the first determining unit is specifically configured to:
detecting that a current value of a target vehicle when running in a target time detection window exceeds a current threshold value, and determining that the target vehicle has large current in the target time detection window; the times of detecting that the target vehicle generates large current in the target time detection window are equal to a threshold value of times of exceeding current limit, and the target detection window is determined to be the detection window of the large current of the target vehicle;
and sequentially detecting the times of occurrence of heavy current of other vehicles in each time detection window, and determining the number of detection windows of occurrence of heavy current of each vehicle.
In this embodiment, optionally, the processing module 630 includes: the device comprises a second determining unit, a third determining unit and a processing unit;
the second determining unit is used for determining inflection point information in the abnormal fusing model, and the inflection point information is used for representing the change degree of the number of the detection windows;
a third determining unit, configured to determine, according to the inflection point information, identification information that the fuse is in an abnormal state;
and the processing unit is used for processing the abnormal vehicle corresponding to the identification information.
In this embodiment, optionally, the second determining unit is specifically configured to:
based on a preset step length, determining a corresponding vehicle numbering period when the change rate of the number of detection windows in the abnormal fusing model is greater than a rate threshold;
And determining the target number in the vehicle number period as inflection point information, wherein the target number is the number corresponding to the intermediate value of the vehicle number period.
In this embodiment, optionally, the processing unit is specifically configured to:
and generating an early warning prompt based on the identification information, wherein the early warning prompt is used for indicating to perform fuse abnormality early warning on the abnormal vehicle corresponding to the identification information.
In this embodiment, optionally, the apparatus of this embodiment further includes: a storage module;
The storage module is used for storing the identification information into an abnormal information base, wherein the abnormal information base is used for recording and updating the abnormal information of the fuse, and the abnormal information of the fuse is used for describing the serial number of the corresponding vehicle of the fuse;
the determining module is further used for determining that the identification information is still stored in the abnormal information base within a preset period.
According to the abnormal fusing processing device, the driving data of a plurality of vehicles are obtained, wherein the driving data can comprise current values generated in real time when the vehicles run, a plurality of time detection windows can be preset, the plurality of current values are divided, and an abnormal fusing model of the current values when the vehicles run is established based on the preset time detection windows, wherein the abnormal fusing model can be used for predicting the working state of a fuse in the running process of each vehicle, so that the fuse in the abnormal state is effectively predicted, the abnormal vehicles in the abnormal state of the fuse are processed, and the problem of driving safety caused by abnormal fusing of the fuse is avoided.
The processing device for abnormal fusing provided by the embodiment of the invention can execute the processing method for abnormal fusing provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
Fig. 7 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure. As shown in fig. 7, the electronic device includes a processor 710, a memory 720, an input device 730, and an output device 740; the number of processors 710 in the electronic device may be one or more, one processor 710 being taken as an example in fig. 7; the processor 710, memory 720, input device 730, and output device 740 in the electronic device may be connected by a bus or other means, for example in fig. 7.
The memory 720 is a computer readable storage medium, and may be used to store a software program, a computer executable program, and a module, such as a program instruction/module corresponding to the abnormal fusing processing method in the embodiment of the present invention. The processor 710 executes various functional applications of the electronic device and data processing by executing software programs, instructions and modules stored in the memory 720, that is, implements the method for processing abnormal fusing according to the embodiment of the present invention.
Memory 720 may include primarily a program storage area and a data storage area, wherein the program storage area may store an operating system, at least one application program required for functionality; the storage data area may store data created according to the use of the terminal, etc. In addition, memory 720 may include high-speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid-state storage device. In some examples, memory 720 may further include memory remotely located relative to processor 710, which may be connected to the electronic device via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 730 may be used to receive input numeric or character information and to generate key signal inputs related to user settings and function control of the electronic device, which may include a keyboard, mouse, etc. The output device 740 may include a display device such as a display screen.
The disclosed embodiments also provide a storage medium containing computer-executable instructions that, when executed by a computer processor, are used to implement the method for handling abnormal fusing provided by the embodiments of the present invention.
Of course, the storage medium containing the computer executable instructions provided in the embodiments of the present invention is not limited to the method operations described above, and may also perform the related operations in the method for handling abnormal fusing provided in any embodiment of the present invention.
From the above description of embodiments, it will be clear to a person skilled in the art that the present invention may be implemented by means of software and necessary general purpose hardware, but of course also by means of hardware, although in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a FLASH Memory (FLASH), a hard disk, or an optical disk of a computer, etc., and include several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the embodiments of the present invention.
It should be noted that, in the above-mentioned embodiments of the search apparatus, each unit and module included are only divided according to the functional logic, but not limited to the above-mentioned division, as long as the corresponding functions can be implemented; in addition, the specific names of the functional units are also only for distinguishing from each other, and are not used to limit the protection scope of the present invention.
It should be noted that in this document, relational terms such as "first" and "second" and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing is merely a specific embodiment of the disclosure to enable one skilled in the art to understand or practice the disclosure. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown and described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (9)
1. An abnormal fusing processing method is characterized by comprising the following steps:
acquiring driving data of a full-quantity vehicle, wherein the driving data comprise current values during driving, and the full-quantity vehicle is used for representing a preset number of vehicles;
based on a preset time detection window, establishing an abnormal fusing model of current values of a preset number of vehicles during running, wherein the abnormal fusing model is used for predicting working states of fuses of the preset number of vehicles during running;
According to the abnormal fusing model, processing an abnormal vehicle with the fuse in an abnormal state;
Before establishing an abnormal fusing model of a preset number of current values of the vehicle during running based on a preset time detection window, the method further comprises the following steps:
determining the identification information of each vehicle in a preset number of vehicles;
according to the abnormal fusing model, the abnormal vehicle with the fuse in the abnormal state is processed, and the method further comprises the following steps:
Determining inflection point information in the abnormal fusing model, wherein the inflection point information is used for representing the change degree of the number of detection windows; the number of the detection windows is the number of time detection windows corresponding to the threshold value of the current overrun times when the number of times of large current appears on each vehicle; when the current value of the target vehicle when the target vehicle is detected to run in the target time detection window exceeds a current threshold value, determining that the target vehicle has large current in the target time detection window; when the times of the occurrence of the large current of the target vehicle in the target time detection window is detected to be equal to the threshold value of the times of the current overrun, determining the target time detection window as the detection window of the occurrence of the large current of the target vehicle;
determining identification information of the fuse in an abnormal state according to the inflection point information;
and processing the abnormal vehicle corresponding to the identification information of the fuse in the abnormal state.
2. The method of claim 1, wherein the identification information of each vehicle includes a number; the establishing an abnormal fusing model of a preset number of current values of the vehicle during running based on a preset time detection window comprises the following steps:
Determining the number of detection windows in which large current appears for each vehicle according to at least one current value corresponding to the preset time detection window based on a current threshold and a current overrun frequency threshold, wherein the current threshold is used for screening the large current in the driving data of each vehicle, the current threshold is determined by attribute information of a preset number of vehicles, and the attribute information comprises the type of the vehicle; the current overrun frequency threshold is used for representing the frequency of occurrence of large current of each vehicle in at least one preset time detection window;
And establishing an abnormal fusing model according to the number of detection windows of the large current of each vehicle and the identification information of each vehicle.
3. The method according to claim 2, wherein the determining the number of detection windows in which a large current occurs for each vehicle based on the current threshold and the current overrun count threshold according to the current value corresponding to at least one of the preset time detection windows includes:
and sequentially detecting the times of occurrence of heavy current of other vehicles in each time detection window, and determining the number of detection windows of occurrence of heavy current of each vehicle.
4. The method of claim 1, wherein the determining inflection point information in the abnormal fuse model comprises:
based on a preset step length, determining a corresponding vehicle numbering period when the change rate of the number of detection windows in the abnormal fusing model is greater than a rate threshold;
And determining the target number in the vehicle number period as inflection point information, wherein the target number is the number corresponding to the intermediate value of the vehicle number period.
5. The method of claim 1, wherein the processing the abnormal vehicle corresponding to the identification information of the fuse in the abnormal state includes:
And generating an early warning prompt based on the identification information of the fuse in the abnormal state, wherein the early warning prompt is used for indicating to perform fuse abnormality early warning on an abnormal vehicle corresponding to the identification information of the fuse in the abnormal state.
6. The method of claim 5, wherein before the processing the abnormal vehicle corresponding to the identification information of the abnormal state of the fuse, further comprising:
Storing the identification information of the fuse in an abnormal state into an abnormal information base, wherein the abnormal information base is used for recording and updating the abnormal information of the fuse, and the abnormal information of the fuse is used for describing the serial number of the corresponding vehicle of the fuse;
and determining that the identification information of the fuse in the abnormal state within a preset period is still stored in the abnormal information base.
7. An abnormal fusing processing apparatus, comprising:
the system comprises an acquisition module, a control module and a control module, wherein the acquisition module is used for acquiring driving data of a total number of vehicles, the driving data comprise current values during driving, and the total number of vehicles are used for representing a preset number of vehicles;
The building module is used for building an abnormal fusing model of current values of a preset number of vehicles when the vehicles run based on a preset time detection window, and the abnormal fusing model is used for predicting working states of fuses of the preset number of vehicles when the vehicles run;
The processing module is used for processing the vehicle with the fuse in the abnormal state according to the abnormal fusing model;
the determining module is used for determining the identification information of each vehicle in the preset number of vehicles;
The processing module is further configured to:
Determining inflection point information in the abnormal fusing model, wherein the inflection point information is used for representing the change degree of the number of detection windows; the number of the detection windows is the number of time detection windows corresponding to the threshold value of the current overrun times when the number of times of large current appears on each vehicle; when the current value of the target vehicle when the target vehicle is detected to run in the target time detection window exceeds a current threshold value, determining that the target vehicle has large current in the target time detection window; when the times of the occurrence of the large current of the target vehicle in the target time detection window is detected to be equal to the threshold value of the times of the current overrun, determining the target time detection window as the detection window of the occurrence of the large current of the target vehicle;
determining identification information of the fuse in an abnormal state according to the inflection point information;
and processing the abnormal vehicle corresponding to the identification information of the fuse in the abnormal state.
8. An electronic device, comprising:
one or more processors;
Storage means for storing one or more programs,
The one or more programs, when executed by the one or more processors, cause the one or more processors to implement the method of handling abnormal fusing as recited in any one of claims 1-6.
9. A computer-readable storage medium, on which a computer program is stored, characterized in that the program, when executed by a processor, implements the method of handling abnormal blowing according to any one of claims 1 to 6.
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