CN115439951A - 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 present disclosure relates to a method, an apparatus, an electronic device, and a medium for processing abnormal fusing; wherein, the method comprises the following steps: the method comprises the steps that driving data of all vehicles are obtained, wherein the driving data comprise current values during driving, and the all vehicles are used for representing a preset number of vehicles; establishing an abnormal fusing model of current values when a preset number of vehicles run based on a preset time detection window, wherein the abnormal fusing model is used for predicting the working states of 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. The fuse protector with the abnormal working state can be effectively predicted, so that abnormal vehicles with the fuse protector in the abnormal working state can be processed, and the problem of driving safety caused by abnormal fusing of the fuse protector is avoided.
Description
Technical Field
The present disclosure relates to the field of data processing technologies, and in particular, to a method and an apparatus for processing abnormal fusing, an electronic device, and a medium.
Background
The fuse is used as an important protective electric device of a battery pack in a vehicle, can effectively protect a battery core in the battery pack from being in the Shanghai where overcurrent happens, and can also avoid vehicle damage caused by internal faults of the battery pack; in the vehicle, a fuse has a rated specification for limiting current, and the fuse is fused when the current exceeds the specified specification.
However, the fuse needs to fully consider parameters such as working condition current and voltage of the battery pack in the design and model selection stage, a certain redundancy design is reserved, and the problem of product quality consistency of the fuse during manufacturing can cause abnormal fusing in the driving process of the vehicle, so that safety hazards are caused to personnel in the vehicle.
Disclosure of Invention
In order to solve the technical problem, 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 processing abnormal fusing, including:
the method comprises the steps that driving data of a full quantity of vehicles are obtained, wherein the driving data comprise current values during driving, and the full quantity of vehicles are used for representing a preset number of vehicles;
establishing abnormal fusing models of current values when a preset number of vehicles run on the basis of a preset time detection window, wherein the abnormal fusing models are used for predicting working states of 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 step of establishing a preset number of abnormal fusing models of the current values when the vehicle runs based on the preset time detection window, the method further includes:
determining identification information of each vehicle in a preset number of vehicles, wherein the identification information comprises a serial number;
the method comprises the following steps of establishing a preset number of abnormal fusing models of current values when the vehicle runs on the basis of a preset time detection window, wherein the abnormal fusing models comprise:
determining the number of detection windows with large current of each vehicle according to a current value corresponding to at least one preset time detection window based on a current threshold and a current overrun 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 vehicle models; the current overrun time threshold is used for representing the times 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 with large current of each vehicle and the identification information of each vehicle.
Optionally, the determining, based on the current threshold and the current threshold for the number of times of current overrun, the number of detection windows in which a large current occurs in each vehicle according to a current value corresponding to at least one preset time detection window includes:
detecting that the current value of a target vehicle during running in a target time detection window exceeds a current threshold value, and determining that a large current appears in the target time detection window; the times of detecting that the target vehicle has the large current in the target time detection window are equal to a current overrun time threshold value, and the target detection window is determined to be the detection window of the target vehicle with the large current;
and sequentially detecting the times of the occurrence of the large current of other vehicles in each time detection window, and determining the number of the detection windows of each vehicle in which the large current occurs.
Optionally, the processing, according to the abnormal fusing model, an abnormal vehicle with a fuse in an abnormal state includes:
determining inflection point information in the abnormal fusing model, wherein the inflection point information is used for representing the variation degree of the number of the detection windows;
according to the inflection point information, determining identification information of the fuse in an abnormal state;
and processing the abnormal vehicle corresponding to the identification information.
Optionally, the determining inflection point information in the abnormal fusing model includes:
determining a corresponding vehicle number time period when the change rate of the number of the detection windows in the abnormal fusing model is greater than a rate threshold value based on a preset step length;
and determining that a target number in the vehicle number time period is inflection point information, wherein the target number is a number corresponding to a middle value of the vehicle number time 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 that fuse abnormity early warning is carried out on the abnormal vehicle corresponding to the identification information.
Optionally, before 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 vehicle corresponding to the fuse;
and determining that the identification information is still stored in the abnormal information base within a preset time period.
In a second aspect, the present disclosure provides an apparatus for processing abnormal fusing, including:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring driving data of a total number of vehicles, the driving data comprises a current value during driving, and the total number of vehicles is used for representing a preset number of vehicles;
the system comprises an establishing module, a judging module and a judging module, wherein the establishing module is used for establishing abnormal fusing models of current values when a preset number of vehicles run based on a preset time detection window, and the abnormal fusing models are used for predicting working states of 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 includes: a determination module;
the system comprises a determining module, a judging module and a judging module, wherein the determining module is used for determining identification information of each vehicle in a preset number of vehicles, and the identification information comprises a serial number;
an establishment module comprising: a first determining unit and a establishing unit;
the first determining unit is used for determining the number of detection windows with large current of each vehicle according to a current value corresponding to at least one preset time detection window based on a current threshold and a current overrun 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 the vehicles with preset number, and the attribute information comprises vehicle models; the current overrun time threshold is used for representing the times of occurrence of large current of each vehicle in at least one preset time detection window;
and the establishing unit is used for establishing an abnormal fusing model according to the number of the detection windows with large current of each vehicle and the identification information of each vehicle.
Optionally, the first determining unit is specifically configured to:
detecting that the current value of a target vehicle during running in a target time detection window exceeds a current threshold value, and determining that a large current appears in the target time detection window; the frequency of detecting that the target vehicle generates the large current in the target time detection window is equal to a current overrun frequency threshold value, and the target detection window is determined to be the detection window of the target vehicle generating the large current;
and sequentially detecting the times of the occurrence of the large current of other vehicles in each time detection window, and determining the number of the detection windows of each vehicle in which the large current occurs.
Optionally, the processing module includes: a second determining unit, a third determining unit and a processing unit;
a second determining unit, configured to determine inflection point information in the abnormal fusing model, where the inflection point information is used to represent a variation 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:
determining a corresponding vehicle number time period when the change rate of the number of the detection windows in the abnormal fusing model is greater than a rate threshold value based on a preset step length;
and determining that the target number in the vehicle number time period is inflection point information, wherein the target number is a number corresponding to the middle value of the vehicle number time 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 that fuse abnormity early warning is carried out on the abnormal vehicle corresponding to the identification information.
Optionally, the method further includes: a storage module;
the storage module is used for storing the identification information to an abnormal information base, 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 vehicle corresponding to the fuse;
and the determining module is further used for determining that the identification information is still stored in the abnormal information base within a preset time period.
In a third aspect, the present disclosure also provides an electronic device, including:
one or more processors;
a storage device to store 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 the exception fusing according to any one of the embodiments of the present invention.
In a fourth aspect, the present disclosure also provides a computer-readable storage medium, on which a computer program is stored, which, 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 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 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 of each vehicle in the running process, so that the fuse of which the working state is in the abnormal state is effectively predicted, the abnormal vehicles of which the fuses are in the abnormal state are processed, and the problem of driving safety caused by abnormal fusing of the fuses is avoided.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure.
In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present disclosure, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without inventive exercise.
FIG. 1 is a flowchart illustrating a method for processing an abnormal fuse according to an embodiment of the present disclosure;
FIG. 2 is a flowchart illustrating another abnormal fusing processing method according to an embodiment of the disclosure;
FIG. 3 is a diagram of a current overrun distribution based on an abnormal fusing model according to an embodiment of the disclosure;
FIG. 4 is a diagram of another current overrun count distribution based on an abnormal fusing model according to an embodiment of the disclosure;
FIG. 5 is a diagram of a current overrun distribution based on an abnormal fusing model according to an embodiment of the disclosure;
FIG. 6 is a schematic structural diagram of an apparatus for processing abnormal fusing according to an embodiment of the present disclosure;
fig. 7 is a schematic structural diagram of an electronic device provided in 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, aspects of the present disclosure will be further described below. It should be noted that the embodiments and features of the embodiments of the present disclosure may be combined with each other without conflict.
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 is to be understood that the embodiments disclosed in the specification are only a few embodiments of the present disclosure, and not all embodiments.
With the rapid development of the electric vehicle industry, the electric vehicle inventory becomes higher and higher, wherein the safety of a battery system (battery pack) is particularly important as an important power supply part of the electric vehicle.
The rated specification that sets up on the fuse can be under the circumstances of overcurrent, and the electric core damage in the battery package is effectively protected in the fusing operation through the fuse, simultaneously, can also avoid the serious injury that the battery package internal fault arouses.
The main parameters of the fuse include rated current, rated voltage, ambient temperature, reaction speed and the like, the realization of the electric quantity bearing capacity of the fuse needs to be carried out under the ambient temperature condition of 25 ℃, however, the service life of the fuse is in inverse proportion 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 the working condition current, the voltage, the working temperature range and the like of a battery pack need to be fully considered, a certain redundancy design needs to be reserved, and abnormal conditions are avoided, but the environment of a vehicle in the driving process is variable and complex, and the designed fuse is difficult to effectively adapt to all vehicle environments; in addition, the product quality uniformity of fuse also can cause unusual fusing, leads to serious nest fault of lying prone to, be difficult to effectively ensure personnel's in the car security of riding.
The abnormal fusing model can be used for predicting the working state of a fuse in the driving process of each vehicle, so that the fuse in the abnormal state can be effectively predicted, the abnormal vehicle with the fuse in the abnormal state can be processed, and the problem of driving safety caused by abnormal fusing of the fuse can be avoided.
With particular reference to the exemplary illustration in fig. 1.
Fig. 1 is a schematic flowchart of a method for processing abnormal fusing according to an embodiment of the present disclosure. The method of the embodiment may be performed by an abnormal fusing processing apparatus, which may be implemented in hardware and/or software and may be configured in an electronic device. The method for processing the abnormal fusing in any embodiment of the application can be realized. As shown in fig. 1, the method specifically includes the following steps:
and S110, acquiring running data of the whole vehicle, wherein the running data comprises a current value during running.
Wherein the full number of vehicles is used to characterize a preset number of vehicles.
For example, if 60000 vehicles need to perform fuse abnormality detection, the preset number for characterization is 60000, and 60000 vehicles are full-scale vehicles.
It should be noted that, in the same batch of detected vehicles, the vehicle models of each vehicle are similar, that is, the vehicle models of each vehicle in the total number of vehicles are similar, thereby effectively ensuring the validity of detection.
The running data of the whole quantity of vehicles 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 running process in real time.
It should be noted that when the vehicle is controlled to collect the current value, a certain sampling period can be set, and the electric quantity value of the vehicle during running can be obtained based on the sampling period, so that the problems that the quantity of the obtained current values is too large, the detection difficulty is increased, and the sampling load is increased are solved.
For example, the sampling period may be set to 1 s/time, that is, the controller of the vehicle a collects the current value of the vehicle every 1s during the running of the vehicle a.
In addition, the reporting time of the information reported by the vehicle controller can also be set, for example, the sampling information of the time interval is carried out every day in a fixed time interval; the reporting time may be in units of hours/minutes/day, which is not specifically limited by the present disclosure.
After the driving data of all vehicles are obtained, the driving data can be cleaned, and the current value abnormity is avoided from influencing detection; the data cleansing may include: current value null value elimination, current value repeated value deletion and the like.
And S120, establishing an abnormal fusing model of current values when a preset number of vehicles run on the basis of a preset time detection window.
The abnormal fusing model is used for predicting the working states of the fuses when a preset number of vehicles run.
The preset time detection window can be used for representing the dividing time of the current value, and if 5 minutes can be set as a primary dividing interval, the 5 minutes can be used as a data classification time period of the primary time detection window.
The preset time detection window may include a plurality of windows.
For example, at 15-00-16, 5 minutes on a day for a detection period, 12 time detection windows can be corresponded, which can be: 15-15.
And 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 return, vehicle early warning and the like can be timely performed.
The processing method for abnormal fusing provided by this embodiment obtains driving data of a plurality of vehicles, where the driving data may include current values generated in real time when the vehicles are driving, and may preset a plurality of time detection windows, divide the plurality of current values, and establish an abnormal fusing model of the current values when the vehicles are driving based on the preset time detection windows, where the abnormal fusing model may be used to predict a working state of a fuse in a driving process of each vehicle, so as to effectively predict the fuse in an abnormal state, so as to process an abnormal vehicle in which the fuse is in an abnormal state, and avoid a problem of driving safety caused by abnormal fusing of the fuse.
Fig. 2 is a schematic flowchart of another abnormal fusing processing method according to an embodiment of the present disclosure. On the basis of the foregoing embodiment, further before S120, the present embodiment may further include:
and S111, determining identification information of each vehicle in a preset number of vehicles.
Wherein the identification information comprises a number.
Wherein each vehicle may be numbered based on the arrangement of numbers.
For example, if the predetermined number is 60000, 60000 vehicles may be numbered from the numbers 1-60000 (integers), where each number in 1-60000 may correspond to a vehicle.
Wherein, one possible implementation manner of S120 is as follows:
s1201, determining the number of detection windows of each vehicle with large current according to the current value corresponding to at least one preset time detection window based on the current threshold and the current overrun threshold.
The current threshold is used for screening large currents in the driving data of each vehicle, and the current overrun time threshold is used for representing the times of occurrence of the large currents of each vehicle in at least one preset time detection window.
The number of the detection windows in which the large current occurs in each vehicle is that the number of times of the large current occurring in each vehicle is equal to the number of the time detection windows corresponding to the current overrun number threshold.
Optionally, the current threshold is determined by attribute information of a preset number of vehicles, where the attribute information may include vehicle models, and may be set as: 500A, 550A, 600A, etc., thereby, different current thresholds can be set for different vehicle types, enhancing the flexibility of detection.
Wherein, the threshold value of the current overrun times can be set as: 2 or 3, etc.
With reference to the above example, the time detection windows are: 15-00-15.
In this embodiment, optionally, determining the number of detection windows in which a large current occurs in each vehicle according to a current value corresponding to at least one preset time detection window based on the current threshold and the current overrun threshold includes:
detecting that the current value of the target vehicle in the target time detection window exceeds a current threshold value when the target vehicle runs, and determining that the target vehicle has large current in the target time detection window; the frequency of detecting that the target vehicle generates the large current in the target time detection window is equal to the current overrun frequency threshold value, and the target detection window is determined to be the detection window of the target vehicle generating the large current;
and sequentially detecting the times of the occurrence of the large current of other vehicles in each time detection window, and determining the number of the detection windows of each vehicle in which the large current occurs.
With reference to the above example, the current threshold is 550A, the current overrun threshold is 2, and the preset time detection windows respectively are: 15-15: if the number of detection windows for the large current of the vehicle 1 (such as the vehicle a) is 4, the large current detection of the vehicles 2, 60000 is continued in the same manner as described above, and thus the number of detection windows for the large current of each of the entire number of vehicles is effectively determined.
S1202, establishing an abnormal fusing model according to the number of detection windows with large current of each vehicle and the identification information of each vehicle.
The abnormal fusing model can be displayed in a two-dimensional coordinate inner curve display mode, the abscissa can be a vehicle number, such as 1-60000, and the ordinate can be the number of detection windows of a vehicle with a large current for a preset number of times (a current overrun threshold, such as 2/3).
For example, fig. 3 is a distribution diagram of current overrun times based on the abnormal fusing model, in which the current overrun time threshold is 2 and the current threshold is 500A; the vehicle numbers are: 1-60000, time detection windows of occurrence of large current are respectively: 0-500.
FIG. 4 is another abnormal fusing model based current overrun number distribution diagram, wherein the current overrun number threshold is 3, and the current threshold is 600A; the vehicle numbers are respectively: 1-50000, time detection windows of large current respectively: 0-350.
Based on the description of the foregoing embodiment, in this embodiment, optionally, processing an abnormal vehicle with an abnormal fuse according to an abnormal fusing model includes:
and determining inflection point information in the abnormal fusing model, wherein the inflection point information is used for representing the variation degree of the number of the detection windows.
The inflection point information can effectively reflect the sharp increasing trend of the number of the detection windows, so that vehicles with abnormal fuses can be effectively screened out.
In connection with the above example, on the basis of fig. 3, the inflection point information is found, which can be seen in fig. 5 as an example.
In fig. 5, the specific point corresponding to the selected inflection point information is defined as point a, the vehicle number corresponding to the left area of point a (i.e., the area circled with a solid line) is the normal vehicle, and the vehicle number corresponding to the right area of point a (i.e., the area circled with a dotted line) is the abnormal vehicle.
According to the inflection point information, determining the identification information of the fuse in an abnormal state;
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, so that abnormal vehicles can be screened out to be correspondingly processed, and the processing timeliness is further improved.
In this embodiment, optionally, determining inflection point information in the abnormal fusing model includes:
determining a corresponding vehicle number time period when the change rate of the number of the detection windows in the abnormal fusing model is greater than a rate threshold value based on a preset step length;
and determining that the target number in the vehicle number time period is inflection point information, wherein the target number is a number corresponding to the middle value of the vehicle number time period.
If the change rate of the number of the detection windows in the step interval is greater than a pre-specified rate threshold, it indicates that the fuse of the vehicle in the preset step changes significantly, and there is an abnormal condition (i.e., the vehicle has a potential risk and needs to be warned), and the curve corresponding to the change rate is steeper, as shown in the curve in the area on the right of the inflection point in fig. 4.
If the change rate of the number of the detection windows in the step interval is less than or equal to a pre-specified rate threshold (which is negligible, and the rate threshold is usually small, e.g., 0.005), it indicates that the fuse of the vehicle in the preset step length does not change significantly, and there is no abnormal condition, and the curve corresponding to the fuse is more stable, as shown in the curve in the left area of the inflection point in fig. 4.
And determining a number corresponding to the inflection point information in the determined vehicle number time period.
For example, in steps 30000-32000, if the rate of change of the number of detection windows is greater than a pre-specified rate threshold of 0.005, the inflection point information corresponding to number 31000 can be determined.
Therefore, 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 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 that fuse abnormity early warning is carried out on the abnormal vehicle corresponding to the identification information.
Wherein, when determining the serial number of unusual vehicle, the detection personnel is informed to the mode of accessible early warning suggestion, and the detection personnel of being convenient for can in time find out unusual vehicle to handle unusual vehicle, the processing mode can be: vehicle recall, exception reminders, etc.
Note that the abnormal vehicle can be notified of an abnormality by: the vehicle belongs to the people, such as telephone, short message, mail, etc.
In this embodiment, optionally, before 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 abnormal information of the fuse protector, and the abnormal information of the fuse protector is used for describing the number of a vehicle corresponding to the fuse protector;
and determining that the identification information in the preset time period is still stored in the abnormal information base.
Before the early warning prompt is generated based on the identification information, the vehicle can be recorded in a mode of marking a label on the vehicle, and whether the early warning prompt is generated or not is determined according to the recording condition of the vehicle within a period of time.
With reference to the above example, when it is determined that the serial number 35000 of the vehicle is an abnormal vehicle, the serial number of the vehicle or other identification information of the vehicle may be recorded in the abnormal information base, and the vehicle is continuously monitored, and if it is detected that the vehicle is still stored in the abnormal information base within a preset time period (e.g., two months), it is indicated that the vehicle has 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 a preset time period (such as two months), the vehicle is indicated to have no risk, and an early warning prompt does not need to be generated, so that the problem of false early warning caused by single detection error is avoided.
It should be noted that vehicle information (such as a serial number) with potential risks is stored in the abnormal information base, wherein the risk can be eliminated by detecting the vehicle again, and the vehicle information in the abnormal information base can be updated in real time, so that the storage space is optimized, and the real-time performance of the stored information is improved.
FIG. 6 is a schematic structural diagram of an apparatus for processing abnormal fusing according to an embodiment of the present disclosure; the device is configured in the electronic equipment, and can realize the processing method of the abnormal fusing in any embodiment of the application. The device specifically comprises the following steps:
the obtaining module 610 is 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 abnormal fusing models of a preset number of current values when the vehicles run based on a preset time detection window, where the abnormal fusing models are used to predict working states of fuses when the preset number of vehicles run;
and the processing module 630 is configured to process the abnormal vehicle with the fuse in the abnormal state according to the abnormal fusing model.
In this embodiment, optionally, the apparatus of this embodiment further includes: a determination module;
the system comprises a determining module, a judging module and a judging module, wherein the determining module is used for determining identification information of each vehicle in a preset number of vehicles, and the identification information comprises a serial number;
the establishing module 620 includes: a first determining unit and a establishing unit;
the first determining unit is used for determining the number of detection windows with large current of 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 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 the vehicles with preset number, and the attribute information comprises vehicle models; the current overrun time threshold is used for representing the times of occurrence of large current of each vehicle in at least one preset time detection window;
and the establishing unit is used for establishing an abnormal fusing model according to the number of the detection windows with 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 the current value of a target vehicle during running in a target time detection window exceeds a current threshold value, and determining that a large current appears in the target time detection window; the frequency of detecting that the target vehicle generates the large current in the target time detection window is equal to a current overrun frequency threshold value, and the target detection window is determined to be the detection window of the target vehicle generating the large current;
and sequentially detecting the times of the occurrence of the large current of other vehicles in each time detection window, and determining the number of the detection windows of each vehicle in which the large current occurs.
In this embodiment, optionally, the processing module 630 includes: a second determining unit, a third determining unit and a processing unit;
a second determining unit, configured to determine inflection point information in the abnormal fusing model, where the inflection point information is used to represent a variation 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:
determining a corresponding vehicle number time period when the change rate of the number of the detection windows in the abnormal fusing model is greater than a rate threshold value based on a preset step length;
and determining that a target number in the vehicle number time period is inflection point information, wherein the target number is a number corresponding to a middle value of the vehicle number time 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 that fuse abnormity early warning is carried out 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 to an abnormal information base, 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 vehicle corresponding to the fuse;
and the determining module is further used for determining that the identification information is still stored in the abnormal information base within a preset time period.
According to the processing device for abnormal fusing, the driving data of the 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 current values are divided, and an abnormal fusing model of the current values when the vehicles run is established on the basis of the preset time detection windows, wherein 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 with the working state 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.
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 apparatus includes a processor 710, a memory 720, an input device 730, and an output device 740; the number of the processors 710 in the electronic device may be one or more, and one processor 710 is taken as an example in fig. 7; the processor 710, the memory 720, the input device 730, and the output device 740 in the electronic apparatus may be connected by a bus or other means, and the connection by the bus is exemplified in fig. 7.
The memory 720 is a computer-readable storage medium, and can be used for storing software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the method for handling abnormal fusing according to the embodiment of the present invention. The processor 710 executes various functional applications and data processing of the electronic device by executing software programs, instructions and modules stored in the memory 720, that is, implements the method for handling abnormal fusing according to the embodiment of the present invention.
The memory 720 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal, and the like. Further, the 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, the memory 720 can further include memory located remotely from the processor 710, which can be connected to electronic devices over 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 generate key signal inputs related to user settings and function control of the electronic device, and may include a keyboard, a mouse, and the like. The output device 740 may include a display device such as a display screen.
The embodiment of the disclosure also provides a storage medium containing computer executable instructions, and the computer executable instructions are used for realizing the processing method of abnormal fusing provided by the embodiment of the invention when being executed by a computer processor.
Of course, the storage medium containing the computer-executable instructions provided by the embodiments of the present invention is not limited to the method operations described above, and may also perform related operations in the method for processing abnormal fusing provided by any embodiment of the present invention.
From the above description of the embodiments, it is obvious for those skilled in the art that the present invention can be implemented by software and necessary general hardware, and certainly, can also be implemented by hardware, but the former is a better embodiment in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as a floppy disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a FLASH Memory (FLASH), a hard disk or an optical disk of a computer, and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.
It should be noted that, in the embodiment of the above search apparatus, each included unit and module are merely divided according to functional logic, but are not limited to the above division as long as the corresponding functions can be implemented; in addition, specific names of the functional units are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present invention.
It is noted that, in this document, relational terms such as "first" and "second," and the like, may be 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. Also, 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 a … …" does not exclude the presence of another identical element in a process, method, article, or apparatus that comprises the element.
The foregoing are merely exemplary embodiments of the present disclosure, which enable those skilled in the art to understand or practice the present 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 herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (10)
1. A method for processing abnormal fusing is characterized by comprising the following steps:
the method comprises the steps of obtaining driving data of all vehicles, wherein the driving data comprise current values during driving, and the all vehicles are used for representing a preset number of vehicles;
establishing abnormal fusing models of current values when a preset number of vehicles run on the basis of a preset time detection window, wherein the abnormal fusing models are used for predicting working states of 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.
2. The method according to claim 1, wherein before establishing the abnormal fusing model of the current values when the vehicle runs for a preset number of times based on a preset time detection window, the method further comprises:
determining identification information of each vehicle in a preset number of vehicles, wherein the identification information comprises a serial number;
the method comprises the following steps of establishing a preset number of abnormal fusing models of current values when the vehicle runs on the basis of a preset time detection window, wherein the abnormal fusing models comprise:
determining the number of detection windows with large current of each vehicle according to a current value corresponding to at least one preset time detection window based on a current threshold and a current overrun 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 vehicle models; the current overrun time threshold is used for representing the times 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 with large current of each vehicle and the identification information of each vehicle.
3. The method according to claim 2, wherein the determining, based on the current threshold and the current overrun threshold, the number of detection windows for each vehicle with a large current according to the current value corresponding to at least one of the preset time detection windows includes:
detecting that the current value of a target vehicle during running in a target time detection window exceeds a current threshold value, and determining that a large current appears in the target time detection window; the frequency of detecting that the target vehicle generates the large current in the target time detection window is equal to a current overrun frequency threshold value, and the target detection window is determined to be the detection window of the target vehicle generating the large current;
and sequentially detecting the times of the occurrence of the large current of other vehicles in each time detection window, and determining the number of the detection windows of each vehicle in which the large current occurs.
4. The method according to claim 2 or 3, wherein the processing of the abnormal vehicle in which the fuse is in the abnormal state according to the abnormal fusing model includes:
determining inflection point information in the abnormal fusing model, wherein the inflection point information is used for representing the variation degree of the number of the detection windows;
according to the inflection point information, determining identification information of the fuse in an abnormal state;
and processing the abnormal vehicle corresponding to the identification information.
5. The method of claim 4, wherein the determining inflection point information in the abnormal fusing model comprises:
determining a corresponding vehicle number time period when the change rate of the number of the detection windows in the abnormal fusing model is greater than a rate threshold value based on a preset step length;
and determining that a target number in the vehicle number time period is inflection point information, wherein the target number is a number corresponding to a middle value of the vehicle number time period.
6. The method according to claim 4, wherein the processing the abnormal vehicle corresponding to the identification information comprises:
and generating an early warning prompt based on the identification information, wherein the early warning prompt is used for indicating that fuse abnormity early warning is carried out on the abnormal vehicle corresponding to the identification information.
7. The method according to claim 6, wherein before processing the abnormal vehicle corresponding to the identification information, the method further comprises:
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 vehicle corresponding to the fuse;
and determining that the identification information is still stored in the abnormal information base within a preset time period.
8. An apparatus for handling abnormal fusing, comprising:
the system comprises an acquisition module, a storage module and a control module, wherein the acquisition module is used for acquiring driving data of a total number of vehicles, the driving data comprises a current value during driving, and the total number of vehicles is used for representing a preset number of vehicles;
the system comprises an establishing module, a judging module and a judging module, wherein the establishing module is used for establishing abnormal fusing models of current values when a preset number of vehicles run based on a preset time detection window, and the abnormal fusing models are used for predicting working states of fuses when the preset number of vehicles run;
and the processing module is used for processing the vehicle with the fuse in the abnormal state according to the abnormal fusing model.
9. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement a method of handling exception blowing as recited in any one of claims 1-7.
10. A computer-readable storage medium on which a computer program is stored, the program implementing the method for processing abnormal fusing according to any one of claims 1 to 7 when executed by a processor.
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