CN114566028B

CN114566028B - Electric vehicle charging risk monitoring method, device and storage medium

Info

Publication number: CN114566028B
Application number: CN202210158917.9A
Authority: CN
Inventors: 崔岩; 罗英; 刘云舒; 叶国栋; 冯丰; 刘丁丁; 樊一萍
Original assignee: China Merchants Shekou Digital City Technology Co ltd
Current assignee: China Merchants Shekou Digital City Technology Co ltd
Priority date: 2022-02-21
Filing date: 2022-02-21
Publication date: 2024-05-07
Anticipated expiration: 2042-02-21
Also published as: CN114566028A

Abstract

The invention discloses a method, a device and a storage medium for monitoring charging risks of an electric vehicle, which are characterized in that the charging areas of the electric vehicle are monitored in real time, first early warning information is generated when abnormal temperatures are monitored, real-time object monitoring is carried out on the charging areas of the electric vehicle, second early warning information is generated when abnormal objects are monitored, and then the first early warning information and the second early warning information are judged in a combined mode, so that risk warning is carried out according to the combined judging result; the invention defines the specific process of real-time risk monitoring on the charging area of the electric vehicle, monitors the related object of the charging area on the basis of monitoring the temperature of the charging area, combines the abnormal temperature early warning information and the abnormal object early warning information to determine whether the warning is needed, can reduce the false alarm condition, improves the warning accuracy, further reduces the workload of related personnel, and improves the risk management efficiency.

Description

Electric vehicle charging risk monitoring method, device and storage medium

Technical Field

The invention relates to the technical field of charging and battery replacement of electric vehicles, in particular to a method and a device for monitoring charging risks of electric vehicles and a storage medium.

Background

With the upgrade of new energy technology and the further expansion of the market scale of electric vehicles (including electric vehicles and electric motorcycles), the charging demand of electric vehicles is also gradually increased. And because the high density and the quality of the electric vehicle battery are uneven in level, the thermal runaway condition easily occurs in the charging process, and the charging area has spontaneous combustion and explosion risks with certain probability.

Therefore, in order to ensure the charging safety, risk monitoring needs to be carried out on the charging area, and abnormal temperature conditions of the charging area are timely found and alarm is given, so that related personnel can prevent and control spontaneous combustion and self-explosion risks of the electric vehicle. However, the existing risk monitoring means of the charging area is simpler, false alarms are easily generated by monitoring errors, the workload of related personnel is increased due to low alarm accuracy, and the risk management efficiency is reduced.

Disclosure of Invention

The invention provides a method, a device and a storage medium for monitoring charging risks of an electric vehicle, which are used for solving the problems that false alarm is easy to occur in the existing risk monitoring of a charging area, and the personnel workload is increased and the risk management efficiency is reduced due to low alarm accuracy.

The utility model provides an electric vehicle charging risk monitoring method, which comprises the following steps:

real-time temperature monitoring is carried out on the charging area of the electric vehicle, and first early warning information is generated when abnormal temperature is monitored;

Real-time object monitoring is carried out on the charging area of the electric vehicle, and second early warning information is generated when abnormal objects are monitored;

and carrying out joint judgment on the first early warning information and the second early warning information so as to carry out risk warning according to a joint judgment result.

Further, if the abnormal event of the second early warning information is that the first type of abnormal object is detected, the first early warning information and the second early warning information are jointly judged, so that risk warning is performed according to a joint judgment result, and the method comprises the following steps:

determining whether an abnormal temperature and an abnormal object are monitored at the same time according to the first early warning information and the second early warning information;

if the abnormal temperature and the abnormal object are monitored at the same time, determining whether the abnormal temperature and the existence area of the abnormal object coincide;

If the abnormal temperature is not overlapped with the existence area of the abnormal object, generating target early warning information and carrying out risk warning.

Further, after determining whether the abnormal temperature and the abnormal object are monitored at the same time according to the first early warning information and the second early warning information, the method further comprises:

if the abnormal temperature and the abnormal object are not monitored at the same time, generating target early warning information and carrying out risk warning.

Further, determining whether to monitor the abnormal temperature and the abnormal object at the same time according to the first early warning information and the second early warning information includes:

Determining an early warning period of the first early warning information according to the abnormal occurrence time of the first early warning information;

Determining whether the abnormal occurrence time of the second early warning information is in an early warning period;

if the abnormal occurrence time of the second early warning information is within the early warning period, determining that the abnormal temperature and the abnormal object are monitored at the same time;

If the abnormal occurrence time of the second early warning information is not in the early warning period, the determining bit monitors the abnormal temperature and the abnormal object at the same time.

Further, determining whether the abnormal temperature coincides with the existence region of the abnormal object includes:

Determining the region coincidence rate between the abnormal temperature existence region in the first early warning information and the abnormal object existence region in the second early warning information, and determining whether the region coincidence rate is smaller than a preset coincidence rate;

if the region coincidence rate is smaller than the preset coincidence rate, determining that the abnormal temperature coincides with the existence region of the abnormal object;

If the region overlapping rate is larger than or equal to the preset overlapping rate, determining that the abnormal temperature is not overlapped with the existing region of the abnormal object.

Further, if the abnormal temperature and the abnormal object are monitored at the same time, the method further comprises:

Determining early warning confidence according to the region coincidence rate between the abnormal temperature existence region in the first early warning information and the abnormal object existence region in the second early warning information;

if the early warning confidence coefficient is larger than the first confidence coefficient and smaller than the second confidence coefficient, generating target early warning information;

If the early warning confidence coefficient is larger than or equal to the second confidence coefficient and smaller than or equal to the third confidence coefficient, generating target early warning information and carrying out first-stage warning;

If the early warning confidence coefficient is greater than or equal to the third confidence coefficient, generating target early warning information and carrying out second-level warning, wherein the warning level of the second-level warning is greater than that of the first-level warning.

Further, if the abnormal event of the second early warning information is that a second class of abnormal object is detected, the first early warning information and the second early warning information are jointly judged, so that risk warning is performed according to a joint judgment result, and the method comprises the following steps:

Determining whether the abnormal temperature and the abnormal object are monitored at the same time according to the first early warning information and the second early warning information, and determining whether the abnormal temperature and the existence area of the abnormal object coincide;

If the abnormal temperature and the abnormal object are monitored at the same time and the abnormal temperature and the existence area of the abnormal object are overlapped, generating target early warning information and carrying out third-level warning, wherein the warning level of the third-level warning is greater than that of the second-level warning.

Provided is an electric vehicle charging risk monitoring device, including:

the temperature monitoring module is used for monitoring the temperature of the charging area of the electric vehicle in real time and generating first early warning information when abnormal temperature is monitored;

the object monitoring module is used for monitoring the object in real time in the charging area of the electric vehicle and generating second early warning information when abnormal objects are monitored;

And the joint judgment module is used for carrying out joint judgment on the first early warning information and the second early warning information so as to carry out risk warning according to the joint judgment result.

The electric vehicle charging risk monitoring device comprises a memory, a processor and a computer program which is stored in the memory and can run on the processor, wherein the processor realizes the steps of the electric vehicle charging risk monitoring method when executing the computer program.

There is provided a readable storage medium storing a computer program which, when executed by a processor, implements the steps of the electric vehicle charging risk monitoring method described above.

In one scheme provided by the method, the device and the storage medium for monitoring the charging risk of the electric vehicle, the first early warning information is generated when the abnormal temperature is monitored by monitoring the real-time temperature of the charging area of the electric vehicle, the real-time object monitoring is performed on the charging area of the electric vehicle, the second early warning information is generated when the abnormal object is monitored, and then the first early warning information and the second early warning information are jointly judged, so that risk warning is performed according to the joint judgment result; the invention defines the specific process of real-time risk monitoring on the charging area of the electric vehicle, monitors the related object of the charging area on the basis of monitoring the temperature of the charging area, combines the abnormal temperature early warning information and the abnormal object early warning information to determine whether the warning is needed, can reduce the false alarm condition, improves the warning accuracy, further reduces the workload of related personnel, and improves the risk management efficiency.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings that are needed in the description of the embodiments of the present invention will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of a charging risk monitoring system for an electric vehicle according to an embodiment of the present invention;

FIG. 2 is a flow chart of a method for monitoring risk of charging an electric vehicle according to an embodiment of the invention;

FIG. 3 is a flowchart illustrating an implementation of step S30 in FIG. 2;

FIG. 4 is a schematic flow chart of another implementation of step S30 in FIG. 2;

FIG. 5 is a schematic diagram illustrating a structure of an apparatus for monitoring risk of charging an electric vehicle according to an embodiment of the invention;

FIG. 6 is a schematic diagram of a computer device according to an embodiment of the invention.

Detailed Description

The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

The electric vehicle charging risk monitoring method provided by the embodiment of the invention can be applied to the electric vehicle charging risk monitoring system shown in fig. 1, wherein the electric vehicle charging risk monitoring system comprises a plurality of imaging devices with infrared imaging capability and an electric vehicle charging risk monitoring device, and the imaging devices are communicated with the electric vehicle charging risk monitoring device through a network. The electric vehicle charging risk monitoring device can be a cloud platform with safety management and property management capabilities, and the cloud platform can be realized by an independent server or a server cluster formed by a plurality of servers; the image capturing device is a device having video analysis capability, and for example, the image capturing device may be an intelligent camera having infrared capability, or may be a device formed by combining a general camera having infrared capability and an analysis server having an edge calculation algorithm.

After corresponding image pick-up devices are installed at different positions of an electric vehicle charging area, the image pick-up devices monitor the electric vehicle charging area in real time to obtain video information, then the image pick-up devices monitor the video information in real time based on infrared spectrums, generate first early warning information when abnormal temperatures are monitored and send the first early warning information to a cloud platform in real time, meanwhile, the image pick-up devices monitor the electric vehicle charging area in real time based on an object detection algorithm, generate second early warning information when abnormal objects are monitored and send the second early warning information to the cloud platform in real time, and the cloud platform jointly judges the first early warning information and the second early warning information after receiving the first early warning information and the second early warning information so as to carry out risk warning according to joint judging results, so that related personnel can carry out related processing measures according to warning. The embodiment defines a specific process of real-time risk monitoring on the charging area of the electric vehicle, monitors the temperature of the charging area, monitors related objects in the charging area, combines abnormal temperature early warning information and abnormal object early warning information to determine whether warning is needed, can reduce false alarm conditions, improves warning accuracy, further reduces workload of related personnel, and improves risk management efficiency.

In other embodiments, the imaging device may be a conventional infrared imaging apparatus without analysis capability. The method comprises the steps that an image pickup device monitors an electric vehicle charging area in time to obtain video information of the electric vehicle charging area, the video information is sent to an electric vehicle charging risk monitoring device in real time, after the electric vehicle charging risk monitoring device obtains the video information shot by the image pickup device, data conversion analysis is carried out on the video information to monitor the electric vehicle charging area in real time based on infrared spectrum, first early warning information is generated when abnormal temperature is monitored, real-time object monitoring is carried out on the electric vehicle charging area based on an object monitoring algorithm, second early warning information is generated when abnormal objects are monitored, and then joint judgment is carried out on the first early warning information and the second early warning information, so that risk warning is carried out according to joint judgment results; the embodiment defines a specific process of real-time risk monitoring on the charging area of the electric vehicle, monitors the temperature of the charging area, monitors related objects in the charging area, combines abnormal temperature early warning information and abnormal object early warning information to determine whether warning is needed, can reduce false alarm conditions, improves warning accuracy, further reduces workload of related personnel, and improves risk management efficiency.

In an embodiment, as shown in fig. 2, an electric vehicle charging risk monitoring method is provided, and the electric vehicle charging risk monitoring system in fig. 1 is taken as an example to illustrate the method, and the method includes the following steps:

s10: and monitoring the temperature of the charging area of the electric vehicle in real time, and generating first early warning information when the abnormal temperature is monitored.

In order to ensure the charging safety of the electric vehicle, real-time temperature monitoring is required to be carried out on a charging area of the electric vehicle, and first early warning information is generated when abnormal temperature is monitored. In the practical application process, a camera device installed in an electric vehicle charging area monitors the electric vehicle charging area to obtain video information of the electric vehicle charging area, then the camera device analyzes the video information, whether an abnormal temperature area exists in the video information is identified based on infrared spectrum, and if the abnormal temperature area exists is monitored, first early warning information is generated and sent to an electric vehicle charging risk monitoring device (such as a cloud platform).

It can be understood that the total energy of the infrared radiation emitted by the object is proportional to the fourth power of the temperature of the object, the imaging device detects the radiation energy from the object through the infrared imaging technology, the radiation energy is converted into a thermal image corresponding to the object through data conversion, the numerical value of each pixel on the thermal image represents the temperature of the corresponding position of the object, the temperature characteristic of the object can be determined through the thermal image, and the position with the temperature higher than a certain threshold value is identified. The camera device converts video information into a thermal imaging diagram based on infrared spectrum, determines whether an area exceeding a preset temperature threshold (such as 60 ℃) exists in the charging area of the electric vehicle, and if so, generates first early warning information. And when a plurality of areas with too high temperatures exist, a plurality of pieces of first early warning information are generated.

S20: and carrying out real-time object monitoring on the charging area of the electric vehicle, and generating second early warning information when the existence of an abnormal object is monitored.

Meanwhile, the camera device can also monitor the object in real time in the charging area of the electric vehicle, and generate second early warning information when abnormal objects exist. The image pickup device identifies whether an area of an abnormal object (namely, a preset object) exists in the video information based on an object detection algorithm, and if the area of the abnormal object exists, second early warning information is generated and sent to the electric vehicle charging risk monitoring device.

After obtaining the video information, splitting the video information into multiple frames of images, inputting each frame of images into a preset recognition model, enabling the preset recognition model to perform preset object recognition on the input images so as to determine whether preset objects exist in the input images, if the preset objects exist in the images, determining an area where abnormal objects exist in a charging area of the electric vehicle, generating second early warning information and sending the second early warning information to the electric vehicle charging risk monitoring device. The preset recognition model is a neural network model obtained by training according to sample data comprising a preset object.

The preset object may be an object capable of changing the temperature of the area to cause false alarm of temperature detection, and the object is a first type of object, such as a burnt cigarette and warm food, may change the temperature of the area to cause temperature monitoring, triggering and early warning, so that the preset object includes cigarettes and take-out (food). In addition, the preset objects can also be objects causing fire, such as dense smoke, flame and the like, and the objects are the second type of objects.

The early warning information comprises an abnormal event, an abnormal existence area, a video screenshot of the abnormal existence area and an abnormal occurrence time. The abnormal events comprise two events, namely abnormal temperature monitoring and abnormal object monitoring, wherein the abnormal object monitoring comprises two sub-events, namely first abnormal object monitoring and second abnormal object monitoring. For example, the first early warning information includes an abnormal event (i.e., abnormal temperature is monitored), an abnormal temperature existence region, a video screenshot of the abnormal temperature existence region, and an abnormal occurrence time; the second early warning information comprises an abnormal event (namely, an abnormal object is detected), an abnormal object existence area, a video screenshot of the abnormal object existence area and an abnormal occurrence moment. The abnormal occurrence time may be the time when the abnormal temperature or the abnormal object is detected, or the abnormal occurrence time may be the generation time of the early warning information, and since the abnormal temperature or the abnormal object is detected by the real-time monitoring, the early warning information is generated immediately, and the time when the abnormal temperature or the abnormal object is detected is about the generation time of the early warning information.

In the process of monitoring the electric vehicle charging area in real time and generating second early warning information when abnormal objects exist in the electric vehicle charging area, if the first type of objects exist in the video information, determining the area where the abnormal objects exist in the electric vehicle charging area to generate second early warning information, wherein an abnormal event in the second early warning information is that the first type of abnormal objects are monitored; if the second type of object exists in the video information, determining an area where the abnormal object exists in the charging area of the electric vehicle to generate second early warning information, wherein an abnormal event in the second early warning information is that the second type of abnormal object is detected.

S30: and carrying out joint judgment on the first early warning information and the second early warning information so as to carry out risk warning according to a joint judgment result.

After the first early warning information and the second early warning information are received, the electric vehicle charging risk monitoring device performs joint judgment on the first early warning information and the second early warning information so as to perform risk warning according to a joint judgment result. The target early warning information comprises an abnormal event, an abnormal existence area, a video screenshot of the abnormal existence area and an abnormal occurrence time, so that related personnel can timely determine risk occurrence conditions according to the target early warning information to perform safe operation.

The method comprises the steps of comparing abnormal occurrence moments in first early warning information and second early warning information, determining whether abnormal temperature and an abnormal object are monitored at the same time, and determining whether the abnormal temperature and the abnormal object exist area coincide according to the abnormal existence area in the first early warning information and the second early warning information; if the abnormal temperature and the abnormal object are monitored at the same time and the abnormal temperature coincides with the existence area of the abnormal object, the first early warning information may be generated by changing the temperature trigger early warning of the area by a preset object (such as cigarettes and takeaway), and the possibility of false alarm exists, whether the first type of abnormal object or the second type of abnormal object is monitored (determined by an abnormal event in the second early warning information) needs to be determined at the moment, and whether risk warning needs to be performed is judged according to the determination result. If the abnormal temperature and the abnormal object are monitored at the same time and the abnormal temperature coincides with the existence area of the abnormal object, and the abnormal event in the second early warning information is that the first type of abnormal object is monitored, the first early warning information is generated by changing the temperature triggering early warning of the area of the first type of object (such as cigarettes and takeaway), and risk warning is not needed; if the abnormal temperature and the abnormal object are monitored at the same time and the abnormal temperature coincides with the existence area of the abnormal object, and the abnormal event in the second early warning information is that the second type of abnormal object is monitored, the second early warning information is generated by triggering early warning of the second type of object (such as dense smoke and flame), at the moment, the spontaneous combustion risk of the electric vehicle is high, risk warning is needed, the warning level is the highest, at the moment, the target early warning information is generated and sent to related personnel, and power supply to charging equipment of the charging area is stopped.

If it is determined that the abnormal temperature and the abnormal object and/or the existence area of the abnormal temperature and the abnormal object are not monitored at the same time, the fact that the two abnormalities occur at different moments and/or the existence area is not coincident is indicated, the possibility that the temperature of the area is changed by a preset object (such as cigarettes and takeaway) to cause false alarm is not existed, and the electric vehicle or the charging pile may have spontaneous combustion risk, target early warning information is required to be generated and risk warning is required to be carried out so as to prompt related personnel to timely carry out risk prevention and control, for example, carrying out operations of informing the related personnel to go to the abnormal existence area for rechecking, carrying out power outage and the like. When the abnormal temperature and the abnormal object and/or the existence area of the abnormal object are not monitored at the same time, if the abnormal object is the first type of abnormal object, the first early warning information can be used as target early warning information; if the abnormal object is the second type abnormal object, the first early warning information and the second early warning information are respectively generated into target early warning information, so that related personnel can timely acquire the abnormal conditions of all areas, and risk prevention is carried out.

In the embodiment, the first early warning information and the second early warning information are jointly judged by monitoring the real-time temperature of the charging area of the electric vehicle and generating the first early warning information when the abnormal temperature is monitored, monitoring the real-time object of the charging area of the electric vehicle and generating the second early warning information when the abnormal object is monitored, so that risk warning is carried out according to the joint judging result; the invention defines the specific process of real-time risk monitoring on the charging area of the electric vehicle, monitors the temperature of the charging area, monitors the related objects in the charging area, combines the abnormal temperature early warning information and the abnormal object early warning information to determine whether the warning is needed, can reduce the false alarm condition, improves the warning accuracy, further reduces the workload of related personnel, thereby improving the efficiency of risk management, simultaneously can reduce the problem of untimely risk treatment caused by the sensitivity of a large number of false alarms for reducing the related personnel, and can timely and accurately prevent and control the spontaneous combustion and self-explosion risks of the electric vehicle, thereby ensuring the safety of the electric vehicle and the charging pile.

In an embodiment, if the abnormal event of the second early warning information is that the first abnormal object is detected. As shown in fig. 3, in step S30, the first early warning information and the second early warning information are jointly determined, so as to perform risk warning according to the joint determination result, which specifically includes the following steps:

S31: and determining whether the abnormal temperature and the abnormal object are monitored at the same time according to the first early warning information and the second early warning information.

After the first early warning information and the second early warning information are received, the electric vehicle charging risk monitoring device needs to determine whether an abnormal event of the second early warning information is an abnormal object of the first type, and if the abnormal event of the second early warning information is the abnormal object of the first type, whether the abnormal temperature and the abnormal object are monitored simultaneously is further determined according to the first early warning information and the second early warning information.

The abnormal temperature and the abnormal object can be determined whether to be monitored simultaneously or not by comparing the abnormal occurrence time of the first early warning information with the abnormal occurrence time of the second early warning information. If the abnormal occurrence time of the first early warning information is consistent with the abnormal occurrence time of the second early warning information or the error is within a preset value (for example, the error of the abnormal occurrence time is 5 seconds), determining that the abnormal temperature and the abnormal object are monitored at the same time; if the abnormal occurrence time of the first early warning information is inconsistent with the abnormal occurrence time of the second early warning information or the error is larger than a preset value (for example, the error of the abnormal occurrence time is larger than 5 seconds), determining that the abnormal temperature and the abnormal object are not monitored at the same time.

S32: if the abnormal temperature and the abnormal object are not monitored at the same time, generating target early warning information and carrying out risk warning.

If it is determined that the abnormal temperature and the abnormal object are not monitored at the same time, it is indicated that the two abnormalities occur at different moments, the possibility of false alarm caused by changing the temperature of the area by a preset object (such as a cigarette and a takeaway) is not existed, and the electric vehicle or the charging pile may have spontaneous combustion risk, then target early warning information needs to be generated and risk warning is performed, at this time, the first early warning information can be directly sent to related personnel as the target early warning information, so as to prompt the related personnel to timely perform risk prevention and control, for example, the related personnel is notified to go to the abnormal existence area for rechecking, power off and other operations. In this embodiment, first simply determine whether an abnormal temperature and an abnormal object are monitored at the same time, if the abnormal temperature and the abnormal object are not monitored at the same time, then directly generate target early warning information and perform risk warning, without performing complex abnormal region overlapping determination, thereby reducing data processing amount, improving warning speed, and performing timely preventive control.

S33: if the abnormal temperature and the abnormal object are monitored at the same time, determining whether the abnormal temperature and the existence area of the abnormal object are coincident.

After determining whether the abnormal temperature and the abnormal object are monitored at the same time according to the first early warning information and the second early warning information, if the abnormal temperature and the abnormal object are monitored at the same time, which means that the abnormal temperature and the abnormal object may be caused by the same factor, it is necessary to further determine whether the existence areas of the abnormal temperature and the abnormal object coincide.

The abnormal existence region of the first early warning information and the abnormal existence region of the second early warning information can be compared to determine whether the abnormal temperature coincides with the existence region of the abnormal object, wherein the abnormal existence region can be represented by a region coordinate position. If the abnormal existence area of the first early warning information and the abnormal existence area of the second early warning information are the same area, determining that the abnormal temperature coincides with the existence area of the abnormal object; if the abnormal existence area of the first early warning information is different from the abnormal existence area of the second early warning information, determining that the abnormal temperature is not overlapped with the existence area of the abnormal object.

S34: if the abnormal temperature is not overlapped with the existence area of the abnormal object, generating target early warning information and carrying out risk warning.

When the abnormal temperature and the abnormal object are monitored at the same time, if the abnormal temperature is determined to coincide with the existence area of the abnormal object, the abnormal temperature and the abnormal object are indicated to occur at the same time and occur in the same area, and the first early warning information is that the first type of preset object (such as cigarettes and takeaway) changes the temperature of the area to cause false alarm, so that no alarm is needed. When the abnormal temperature and the abnormal object are monitored at the same time, if the abnormal temperature is not coincident with the existence area of the abnormal object, the abnormal temperature and the abnormal object are indicated to be two abnormal events occurring at the same time, but the two abnormal events occur in different areas, the possibility that the first type of object (such as cigarettes and take-out) changes the temperature of the area to cause false alarm is not existed, and the electric vehicle or the charging pile may have spontaneous combustion risk, then the target early warning information needs to be generated and risk warning is carried out, and at the moment, the first early warning information can be directly sent to related personnel as the target early warning information so as to prompt the related personnel to timely carry out risk prevention and control. In this embodiment, first simply determine whether to monitor the abnormal temperature and the abnormal object at the same time, and when the abnormal temperature and the abnormal object are monitored at the same time, perform the overlapping determination of the existing area, so that on the basis of reducing the data processing amount and improving the alarm speed, the risk alarm can be accurately performed, and the alarm accuracy is ensured.

In the embodiment, according to the first early warning information and the second early warning information, whether the abnormal temperature and the abnormal object are monitored at the same time is determined, and if the abnormal temperature and the abnormal object are not monitored at the same time, target early warning information is generated and risk warning is carried out; if the abnormal temperature and the abnormal object are monitored at the same time, determining whether the abnormal temperature is coincident with the existing region of the abnormal object, if the abnormal temperature is not coincident with the existing region of the abnormal object, generating target early warning information and carrying out risk warning, determining the specific steps of carrying out risk warning on the first early warning information and the second early warning information according to the combined judging result, determining different combined judging modes according to different abnormal events, and if the abnormal event of the second early warning information is the abnormal object of the first type, carrying out warning only when the occurrence time of the temperature early warning and the occurrence time of the object early warning are coincident with the position of the abnormal region or the occurrence time of the temperature early warning and the occurrence time of the object early warning are not coincident with each other, thereby avoiding the possibility of false warning caused by triggering the temperature early warning by heat emitted by the first type of the object, improving the warning accuracy, further reducing the workload of related personnel, improving the efficiency of risk management, simultaneously, and also reducing the problem of untimely risk treatment caused by reducing the sensitivity of a large number of related personnel, and timely and accurately preventing and controlling the electric vehicle and self-explosion risk and ensuring the safety of the electric vehicle and the self-charging pile.

In one embodiment, in step S31, it is determined whether the abnormal temperature and the abnormal object are monitored at the same time according to the first warning information and the second warning information, and the method specifically includes the following steps:

S311: and determining the early warning period of the first early warning information according to the abnormal occurrence time of the first early warning information.

After the first early warning information is received, the electric vehicle risk monitoring device needs to determine the abnormal occurrence time in the first early warning information, and determines the early warning period of the first early warning information according to the abnormal occurrence time of the first early warning information.

The early warning period of the first early warning information may be a time zone formed by taking the abnormal occurrence time of the first early warning information as a midpoint time and a preset time period before and after the midpoint time. For example, the preset duration is 5 seconds, if the abnormality occurrence time of the first warning information is 10 minutes and 10 seconds, the first 5 seconds of 10 minutes and 10 seconds are 10 minutes and 01 minutes and 05 seconds, the last 5 seconds of 10 minutes and 10 seconds are 10 minutes and 01 minutes and 15 seconds, and the warning period is a time zone between 10 minutes and 01 minutes and 05 seconds and 10 minutes and 15 seconds.

In this embodiment, the preset duration of 5 seconds is only illustrated as an example, and in other embodiments, the preset duration may also be other durations, for example, 1 second, 3 seconds, 6 seconds, 7 seconds, 8 seconds, and 10 seconds, which are not described herein.

S312: and determining whether the abnormal occurrence time of the second early warning information is in the early warning period.

After the early warning period of the first early warning information is determined, determining the abnormal occurrence time in the second early warning information and determining whether the abnormal occurrence time of the second early warning information is within the early warning period.

S313: if the abnormal occurrence time of the second early warning information is within the early warning period, the abnormal temperature and the abnormal object are determined to be monitored simultaneously.

After determining whether the abnormal occurrence time of the second early warning information is within the early warning period, if the abnormal occurrence time of the second early warning information is within the early warning period, which means that the time interval between the monitored abnormal temperature and the abnormal object is shorter, it is determined that two abnormal events, namely the abnormal temperature and the abnormal object, occur simultaneously, and the abnormal temperature and the abnormal object are monitored simultaneously.

S314: if the abnormal occurrence time of the second early warning information is not in the early warning period, determining that the abnormal temperature and the abnormal object are not monitored at the same time.

After determining whether the abnormal occurrence time of the second early warning information is within the early warning period, if the abnormal occurrence time of the second early warning information is not within the early warning period, which means that the time interval between the detected abnormal temperature and the abnormal object is longer, it is determined that the two abnormal events of the abnormal temperature and the abnormal object are not simultaneous events, and it is determined that the abnormal temperature and the abnormal object are not monitored simultaneously.

In this embodiment, an early warning period of the first early warning information is determined according to an abnormal occurrence time of the first early warning information, whether the abnormal occurrence time of the second early warning information is within the early warning period or not is determined, and if the abnormal occurrence time of the second early warning information is within the early warning period, it is determined that the abnormal temperature and the abnormal object are monitored simultaneously; if the abnormal occurrence time of the second early warning information is not in the early warning period, it is determined that the abnormal temperature and the abnormal object are not monitored at the same time, the specific step of determining whether the abnormal temperature and the abnormal object are monitored at the same time or not according to the first early warning information and the second early warning information is determined, and through setting the early warning period, judgment caused by factors such as time recording errors and monitoring errors can be reduced, the judgment accuracy is improved, and the follow-up risk warning accuracy is further improved.

In one embodiment, in step S33, it is determined whether the abnormal temperature coincides with the existence region of the abnormal object, and the method specifically includes the following steps:

s331: and determining the region coincidence rate between the abnormal temperature existence region in the first early warning information and the abnormal object existence region in the second early warning information, and determining whether the region coincidence rate is smaller than a preset coincidence rate.

S332: if the region overlapping rate is smaller than the preset overlapping rate, determining that the abnormal temperature overlaps with the existing region of the abnormal object.

S333: if the region overlapping rate is larger than or equal to the preset overlapping rate, determining that the abnormal temperature is not overlapped with the existing region of the abnormal object.

In order to further ensure the accuracy of judging the region coincidence, the region coincidence rate between the abnormal temperature existence region in the first early warning information and the abnormal object existence region in the second early warning information can be determined, and whether the abnormal temperature and the abnormal object existence region coincide or not is determined according to the region coincidence rate. The abnormal existence region (including the abnormal temperature existence region and the abnormal object existence region) is represented by a relative coordinate region, which is a pixel region composed of a plurality of pixel coordinate points, and is generally represented by a rectangular frame. Calculating the region coincidence rate between the abnormal temperature existence region and the abnormal object existence region, namely calculating the coincidence region between the abnormal temperature existence region and the abnormal object existence region in the second early warning information, determining the smaller region of the abnormal temperature existence region and the abnormal object existence region, and dividing the coincidence region by the smaller region of the abnormal temperature existence region and the abnormal object existence region to obtain the region coincidence rate.

After determining the region coincidence rate between the abnormal temperature existence region in the first early warning information and the abnormal object existence region in the second early warning information, determining whether the region coincidence rate is smaller than a preset coincidence rate, and if the region coincidence rate between the abnormal existence region of the first early warning information and the abnormal existence region of the second early warning information is larger than or equal to the preset coincidence rate, determining that the abnormal temperature coincides with the existence region of the abnormal object; if the region coincidence rate between the abnormal existence region of the first early warning information and the abnormal existence region of the second early warning information is smaller than the preset coincidence rate, determining that the abnormal temperature coincides with the non-existence region of the abnormal object.

For example, an image of the entire electric vehicle charging area is divided into 100 pixel lattices, and coordinates of each pixel are (1, 1) to (10, 10) in sequence; the preset coincidence ratio is 33%, the relative coordinate area (abnormal temperature existence area) of the abnormal temperature is assumed to be [ 2, 2), (2, 3), (2, 4), (3, 2), (3, 3), (3, 4) ], if the relative coordinate area (abnormal object existence area) of the abnormal object is [ 3, 3), (3, 4), (4, 3), (4, 4), the coincidence area is two areas of (3, 3) and (3, 4), the coincidence ratio is 50%, the coincidence ratio of the area is more than 33% of the preset coincidence ratio, and the coincidence of the abnormal temperature and the existence area of the abnormal object is determined without risk warning; if the relative coordinate area (abnormal object existence area) of the abnormal object is (6, 6), the abnormal temperature existence area and the abnormal object existence area are not overlapped, the domain overlapping ratio is 0%, the area overlapping ratio is smaller than the preset overlapping ratio, and risk warning is needed.

In the embodiment, determining the region coincidence rate between the abnormal temperature existence region in the first early warning information and the abnormal object existence region in the second early warning information, and determining whether the region coincidence rate is smaller than a preset coincidence rate; if the region coincidence rate is smaller than the preset coincidence rate, determining that the abnormal temperature coincides with the existence region of the abnormal object; if the region coincidence rate is larger than or equal to the preset coincidence rate, determining that the abnormal temperature is not coincident with the existence region of the abnormal object, determining whether the abnormal temperature is coincident with the existence region of the abnormal object, and comparing the region coincidence rate with the preset coincidence rate by determining the region coincidence rate between the existence region of the abnormal temperature and the existence region of the abnormal object, so that whether the abnormal temperature is coincident with the existence region of the abnormal object can be intuitively and rapidly judged, the accuracy of a judging result is improved, the accuracy of subsequent risk warning is further improved, and the charging risk can be effectively prevented.

In an embodiment, after step S31, that is, after determining whether the abnormal temperature and the abnormal object are monitored at the same time according to the first warning information and the second warning information, if the abnormal temperature and the abnormal object are monitored at the same time, the method may further include the following steps:

s301: and determining the early warning confidence according to the region coincidence rate between the abnormal temperature existence region in the first early warning information and the abnormal object existence region in the second early warning information.

After determining whether the abnormal temperature and the abnormal object are monitored simultaneously according to the first early warning information and the second early warning information, if the abnormal temperature and the abnormal object are monitored simultaneously, determining the region coincidence rate between the abnormal temperature existence region in the first early warning information and the abnormal object existence region in the second early warning information, and determining the early warning confidence according to the region coincidence rate.

The higher the region coincidence rate, the lower the pre-warning confidence, wherein the region coincidence rate can be complementary to the pre-warning confidence, i.e. the region coincidence rate is a%, the pre-warning confidence can be 100% minus a%, e.g. the region coincidence rate is 10%, and the pre-warning confidence is 90%.

S302: and if the early warning confidence coefficient is larger than the first confidence coefficient and smaller than the second confidence coefficient, generating target early warning information.

S303: if the early warning confidence coefficient is larger than or equal to the second confidence coefficient and smaller than or equal to the third confidence coefficient, generating target early warning information and carrying out first-stage warning;

S304: if the early warning confidence coefficient is greater than or equal to the third confidence coefficient, generating target early warning information and carrying out second-level warning, wherein the warning level of the second-level warning is greater than that of the first-level warning.

After the early warning confidence coefficient is determined, whether risk warning is needed or not and the grade of the risk warning can be determined according to the magnitude of the early warning confidence coefficient. When the abnormal temperature and the abnormal object are monitored at the same time, if the early warning confidence coefficient is smaller than or equal to the first confidence coefficient (which can be 33%), the region coincidence rate between the abnormal temperature existence region and the abnormal object existence region is large, and the early warning information is that the first type of preset object (such as cigarettes and take-out) changes the temperature of the region to cause false alarm, then no alarm is needed; if the early warning confidence coefficient is larger than the first confidence coefficient and smaller than the second confidence coefficient (66 percent) and indicates that the region coincidence rate between the abnormal temperature region and the abnormal object region is general, and the possibility of false alarm exists, the risk alarm is not needed, but target early warning information is generated and sent to related personnel, so that risk prompt is carried out on the related personnel, and the related personnel recheck according to the prompt; if the early warning confidence coefficient is larger than or equal to the second confidence coefficient and smaller than or equal to the third confidence coefficient (which can be 99%), the region coincidence rate between the abnormal temperature existence region and the abnormal object existence region is small, and the spontaneous combustion risk exists in the charging region, generating target early warning information, sending the target early warning information to related personnel, and carrying out first-stage warning; if the early warning confidence is larger than or equal to the third confidence, the abnormal temperature existence area is basically not overlapped with the abnormal object existence area, the spontaneous combustion risk of the charging area is large, and then target early warning information is generated and sent to related personnel, and a second-stage warning is carried out.

The alarm level of the second-level alarm is larger than that of the first-level alarm, and the higher the alarm level is, the higher the alarm strength is. For example, the first level alert may be one or more of a pop-up message, an audible and a light alert; the second-level alarm can be based on the first-level alarm, and a telephone alarm is added, namely, a relevant person directly dials a telephone call and alarms in time; the second-level alarm may be to add an alarm association operation (e.g., power off) based on the second-level alarm, that is, directly turn off the power of the power supply device of the abnormal existence region based on the second-level alarm, and stop supplying power to the power supply device of the abnormal existence region.

In this embodiment, the first confidence is 33%, the second confidence is 66%, and the third confidence is 99% are merely exemplary, and in other embodiments, the first confidence, the second confidence, and the third confidence may be other values, for example, the first confidence is 30% and the third confidence is 40%; the second confidence is 60%, 70%; the third confidence was 95%, 98%, 100%.

In this embodiment, if the abnormal temperature and the abnormal object are monitored at the same time, determining the early warning confidence according to the region coincidence rate of the abnormal temperature existence region in the first early warning information and the abnormal object existence region in the second early warning information; if the early warning confidence coefficient is larger than the first confidence coefficient and smaller than the second confidence coefficient, generating target early warning information; if the early warning confidence coefficient is larger than or equal to the second confidence coefficient and smaller than or equal to the third confidence coefficient, generating target early warning information and carrying out first-stage warning; if the early warning confidence coefficient is greater than or equal to the third confidence coefficient, generating target early warning information and carrying out second-level warning, wherein the warning level of the second-level warning is greater than that of the first-level warning, determining the early warning confidence coefficient according to the region coincidence rate, carrying out risk warning of different warning levels according to the magnitude of the early warning confidence coefficient, and ensuring that related personnel receive the risk warning in time and carry out safety operation in time when the warning level is higher, so as to ensure the safety of charging of the electric vehicle.

In an embodiment, if the abnormal event of the second early warning information is that the second type of abnormal object is detected, as shown in fig. 4, in step S30, that is, the first early warning information and the second early warning information are jointly determined, so as to perform risk warning according to the joint determination result, the method specifically includes the following steps:

s01: and determining whether the abnormal temperature and the abnormal object are monitored at the same time or not according to the first early warning information and the second early warning information, and determining whether the abnormal temperature and the existence area of the abnormal object are coincident or not.

After the first early warning information and the second early warning information are received, the electric vehicle charging risk monitoring device needs to determine whether an abnormal event in the second early warning information is a first type abnormal object or a second type abnormal object, if the abnormal event in the second early warning information is a second type abnormal object, whether the abnormal temperature and the abnormal object are monitored at the same time or not needs to be determined according to the first early warning information and the second early warning information, and whether the abnormal temperature and the existence area of the abnormal object coincide or not is determined.

After determining whether the abnormal temperature and the abnormal object are monitored at the same time and determining whether the abnormal temperature and the existence area of the abnormal object are coincident, if the abnormal temperature and the abnormal object are not monitored at the same time and/or the existence area of the abnormal object is not coincident, two abnormal events occur at different moments and/or the existence area is not coincident, and the two abnormal events are independent events, respectively generating target alarm information for respectively alarming. The first type of object (dense smoke and flame) is more serious than the safety risk caused by temperature, so that if the abnormal temperature and the abnormal object and/or the existence area of the abnormal temperature and the abnormal object are not monitored at the same time, the first alarm information is generated into the target alarm information and the first level alarm is carried out, the second alarm information is generated into the target alarm information and the second level alarm is carried out, and related personnel carry out related safety operation according to the target alarm information and the alarm prompt. The alarm level of the second level alarm is greater than the alarm level of the first level alarm.

S02: if the abnormal temperature and the abnormal object are monitored at the same time and the abnormal temperature and the existence area of the abnormal object are overlapped, generating target early warning information and carrying out third-level warning.

If the abnormal temperature and the abnormal object are monitored at the same time, and the abnormal temperature is overlapped with the existence area of the abnormal object, the abnormal event indicated by the two early warning information is the same abnormal event, at the moment, the abnormal existence area is abnormal in temperature, and a first type of object (dense smoke and flame) is generated, the spontaneous combustion risk in the charging area of the electric vehicle is extremely high, and then the first early warning information and the second early warning information are jointly generated into target early warning information and a third-level warning is carried out. The alarm level of the third-level alarm is larger than that of the second-level alarm and the first-level alarm. And the third-level alarm directly turns off the power supply of the power supply equipment of the abnormal existence area on the basis of the second-level alarm, and stops supplying power to the power supply equipment of the abnormal existence area.

In this embodiment, if the abnormal event of the second early warning information is a second type of abnormal object, determining whether the abnormal temperature and the abnormal object are monitored at the same time according to the first early warning information and the second early warning information, and determining whether the abnormal temperature and the existence area of the abnormal object are coincident; if the abnormal temperature and the abnormal object are monitored at the same time and the abnormal temperature coincides with the existence area of the abnormal object, generating target early warning information and carrying out third-level warning, wherein the warning level of the third-level warning is greater than that of the second-level warning and the first-level warning; the method has the advantages that the first early warning information and the second early warning information are combined and judged definitely, so that risk warning is carried out according to the combined judging result, different combined judging modes are determined according to different abnormal object types, if the abnormal event of the second early warning information is a second type of abnormal object, third-level warning is carried out when the occurrence time of temperature early warning and the occurrence time of object early warning coincide and the positions of abnormal areas coincide, different-level accurate warning is carried out on different conditions, timely risk management and control are carried out on related personnel conveniently, warning accuracy is improved, further, the workload of the related personnel is reduced, the efficiency of risk management is improved, meanwhile, the problem that risk treatment is not timely due to the fact that a large number of false alarms reduce the sensitivity of the related personnel can be reduced can be solved, spontaneous combustion and self-explosion risks of the electric vehicle can be timely and accurately prevented, and safety of the electric vehicle and the charging pile is guaranteed.

It should be understood that the sequence number of each step in the foregoing embodiment does not mean that the execution sequence of each process should be determined by the function and the internal logic, and should not limit the implementation process of the embodiment of the present invention.

In an embodiment, an electric vehicle charging risk monitoring device is provided, where the electric vehicle charging risk monitoring device corresponds to the electric vehicle charging risk monitoring method in the above embodiment one by one. As shown in fig. 5, the electric vehicle charging risk monitoring device includes a temperature monitoring module 501, an object monitoring module 502, and a joint judging module 503. The functional modules are described in detail as follows:

the temperature monitoring module 501 is configured to monitor a real-time temperature of a charging area of the electric vehicle, and generate first early warning information when an abnormal temperature is monitored;

the object monitoring module 502 is configured to perform real-time object monitoring on the charging area of the electric vehicle, and generate second early warning information when an abnormal object is detected to exist;

and the joint judgment module 503 is configured to perform joint judgment on the first early warning information and the second early warning information, so as to perform risk warning according to the joint judgment result.

If the abnormal occurrence time of the second early warning information is not in the early warning period, determining that the abnormal temperature and the abnormal object are not monitored at the same time.

if the abnormal temperature and the abnormal object are monitored at the same time and the abnormal temperature and the existence area of the abnormal object are overlapped, generating target early warning information and carrying out third-level warning, wherein the warning level of the third-level warning is greater than that of the second-level warning and the first-level warning.

For specific limitation of the electric vehicle charging risk monitoring device, reference may be made to the limitation of the electric vehicle charging risk monitoring method hereinabove, and no further description is given here. All or part of each module in the electric vehicle charging risk monitoring device can be realized by software, hardware and a combination thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.

In one embodiment, an electric vehicle charging risk monitoring device is provided, which may be a computer device, and an internal structure diagram thereof may be shown in fig. 6. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a storage medium, an internal memory. The storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the storage media. The database of the computer equipment is used for storing data used or generated by the electric vehicle charging risk monitoring method, such as early warning information and the like. The network interface of the computer device is used for communicating with an external camera device through network connection. The computer program when executed by a processor is configured to implement a method for monitoring charging risk of an electric vehicle.

In one embodiment, a computer device is provided that includes a memory, a processor, and a computer program stored on the memory and executable on the processor, the processor implementing the steps of the electric vehicle charging risk monitoring method described above when executing the computer program.

In one embodiment, a readable storage medium is provided, on which a computer program is stored which, when executed by a processor, implements the steps of the above-described electric vehicle charging risk monitoring method.

Those skilled in the art will appreciate that implementing all or part of the above-described methods may be accomplished by way of a computer program stored on a computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (SYNCHLINK) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.

It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions.

The above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention, and are intended to be included in the scope of the present invention.

Claims

1. The electric vehicle charging risk monitoring method is characterized by comprising the following steps of:

Real-time temperature monitoring is carried out on the charging area of the electric vehicle, and first early warning information is generated when abnormal temperature is monitored, wherein the first early warning information comprises an abnormal event, an abnormal temperature existence area, a video screenshot of the abnormal temperature existence area and an abnormal occurrence time;

real-time object monitoring is carried out on the charging area of the electric vehicle, and second early warning information is generated when abnormal objects exist, wherein the second early warning information comprises abnormal events, abnormal object existence areas, video screenshots of the abnormal object existence areas and abnormal occurrence moments; if the first type of object is identified, the abnormal event in the generated second early warning information is that the first type of abnormal object is detected, and the first type of object is a preset object capable of changing the temperature of the area to cause temperature monitoring false alarm; if the second type of object is identified, the abnormal event in the generated second early warning information is that the second type of abnormal object is detected, and the second type of object is a preset object causing fire;

Performing joint judgment on the first early warning information and the second early warning information so as to perform risk warning according to a joint judgment result;

determining whether an abnormal temperature and an abnormal object are monitored at the same time or not by comparing abnormal occurrence moments in the first early warning information and the second early warning information, and determining whether the abnormal temperature and the abnormal object exist areas coincide or not according to the abnormal existence areas in the first early warning information and the second early warning information;

If the abnormal temperature and the abnormal object are monitored at the same time and the abnormal temperature coincides with the existence area of the abnormal object, determining that the monitored abnormal object is a first type abnormal object or a second type abnormal object, and judging whether risk warning is needed according to the determination result.

2. The method for monitoring risk of charging a motor car according to claim 1, wherein if the abnormal event of the second early warning information is that a first type of abnormal object is detected, the performing joint judgment on the first early warning information and the second early warning information to perform risk warning according to a joint judgment result includes:

Determining whether the abnormal temperature and the abnormal object are monitored at the same time according to the first early warning information and the second early warning information;

and if the abnormal temperature is not overlapped with the existence area of the abnormal object, generating target early warning information and carrying out risk warning.

3. The method for monitoring risk of charging a motor car according to claim 2, wherein after determining that the abnormal temperature and the abnormal object are monitored simultaneously according to the first warning information and the second warning information, the method further comprises:

And if the abnormal temperature and the abnormal object are not monitored at the same time, generating the target early warning information and carrying out risk warning.

4. The method for monitoring risk of charging a motor car according to claim 2, wherein determining whether the abnormal temperature and the abnormal object are monitored simultaneously according to the first warning information and the second warning information comprises:

determining whether the abnormal occurrence time of the second early warning information is within the early warning period;

if the abnormal occurrence time of the second early warning information is within the early warning period, determining that the abnormal temperature and the abnormal object are monitored simultaneously;

5. The method of risk monitoring motor car charging as set forth in claim 2, wherein the determining whether the abnormal temperature coincides with the existence area of the abnormal object includes:

and if the region coincidence rate is larger than or equal to the preset coincidence rate, determining that the abnormal temperature is not coincident with the existence region of the abnormal object.

6. The method for monitoring risk of motor vehicle charging as claimed in claim 2, wherein if the abnormal temperature and the abnormal object are monitored simultaneously, the method further comprises:

If the early warning confidence coefficient is larger than or equal to the second confidence coefficient and smaller than or equal to the third confidence coefficient, generating the target early warning information and carrying out first-stage warning;

And if the early warning confidence coefficient is greater than or equal to the third confidence coefficient, generating target early warning information and carrying out second-level warning, wherein the warning level of the second-level warning is greater than that of the first-level warning.

7. The method for monitoring risk of charging a motor car according to any one of claims 1 to 6, wherein if the abnormal event of the second early warning information is that a second type of abnormal object is detected, the performing joint judgment on the first early warning information and the second early warning information to perform risk warning according to a joint judgment result includes:

8. Electric motor car risk monitoring devices that charges, characterized in that includes:

The temperature monitoring module is used for monitoring the temperature of the charging area of the electric vehicle in real time and generating first early warning information when abnormal temperature is monitored, wherein the first early warning information comprises an abnormal event, an abnormal temperature existence area, a video screenshot of the abnormal temperature existence area and an abnormal occurrence time;

The object monitoring module is used for monitoring the electric vehicle charging area in real time and generating second early warning information when an abnormal object is monitored, wherein the second early warning information comprises an abnormal event, an abnormal object existence area, a video screenshot of the abnormal object existence area and an abnormal occurrence time; if the first type of object is identified, the abnormal event in the generated second early warning information is that the first type of abnormal object is detected, and the first type of object is a preset object capable of changing the temperature of the area to cause temperature monitoring false alarm; if the second type of object is identified, the abnormal event in the generated second early warning information is that the second type of abnormal object is detected, and the second type of object is a preset object causing fire;

the joint judgment module is used for carrying out joint judgment on the first early warning information and the second early warning information so as to carry out risk warning according to a joint judgment result;

9. An electric vehicle charging risk monitoring device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, realizes the steps of the electric vehicle charging risk monitoring method according to any one of claims 1 to 7.

10. A readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the electric vehicle charging risk monitoring method according to any one of claims 1 to 7.