WO2022068285A1 - 一种数据处理的方法和装置 - Google Patents
一种数据处理的方法和装置 Download PDFInfo
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- WO2022068285A1 WO2022068285A1 PCT/CN2021/102165 CN2021102165W WO2022068285A1 WO 2022068285 A1 WO2022068285 A1 WO 2022068285A1 CN 2021102165 W CN2021102165 W CN 2021102165W WO 2022068285 A1 WO2022068285 A1 WO 2022068285A1
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- 238000003672 processing method Methods 0.000 title claims abstract description 15
- 238000000034 method Methods 0.000 claims abstract description 41
- 238000012545 processing Methods 0.000 claims description 24
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- 238000004590 computer program Methods 0.000 claims description 19
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- 238000012544 monitoring process Methods 0.000 description 8
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- 239000006096 absorbing agent Substances 0.000 description 4
- 238000006748 scratching Methods 0.000 description 4
- 230000002393 scratching effect Effects 0.000 description 4
- 230000035939 shock Effects 0.000 description 4
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0808—Diagnosing performance data
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C5/00—Registering or indicating the working of vehicles
- G07C5/08—Registering or indicating performance data other than driving, working, idle, or waiting time, with or without registering driving, working, idle or waiting time
- G07C5/0816—Indicating performance data, e.g. occurrence of a malfunction
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/10—Protocols in which an application is distributed across nodes in the network
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
Definitions
- the present invention relates to the technical field of vehicles, and in particular, to a data processing method and device.
- the bump prevention of the battery mainly focuses on passive protection measures, such as adding battery anti-collision beams and protective bottom plates, which can reduce the damage to the modules and cells when the battery is bumped to a certain extent.
- passive protection measures such as adding battery anti-collision beams and protective bottom plates, which can reduce the damage to the modules and cells when the battery is bumped to a certain extent.
- the vehicle end cannot accurately determine whether the vehicle chassis is scratched or bumped, so it is impossible to determine whether the battery is scratched or bumped.
- a method for data processing, applied to a vehicle comprising:
- a trigger result for the preset event is generated.
- the determining trigger probability information for a preset event according to the inertial data includes:
- trigger probability information for a preset event is determined.
- the method further includes:
- the event data is sent to the cloud platform.
- the event data includes event level information
- generating event data for the preset event includes:
- event level information for the preset event is generated according to the trigger probability information.
- the event data further includes target video data and/or target vehicle status data, and when the preset event is triggered, the event data for the preset event is generated, including:
- a data processing device applied to a vehicle comprising:
- an inertial data acquisition module for acquiring inertial data of the vehicle
- a trigger probability information determination module configured to determine trigger probability information for a preset event according to the inertial data
- a triggering result generating module configured to generate a triggering result for the preset event according to the triggering probability information.
- the trigger probability information determination module includes:
- a vehicle speed acquisition sub-module for acquiring the vehicle speed information of the vehicle
- a target inertial data determination submodule configured to determine target inertial data from the inertial data according to the vehicle speed information
- the trigger probability information determination sub-module is configured to determine trigger probability information for a preset event according to the target inertial data.
- a server includes a processor, a memory, and a computer program stored on the memory and capable of running on the processor, the computer program implementing the data processing method as described above when executed by the processor.
- a computer-readable storage medium stores a computer program on the computer-readable storage medium, and when the computer program is executed by a processor, implements the above-mentioned data processing method.
- the present invention by acquiring inertial data of the vehicle, determining trigger probability information for a preset event according to the inertial data, and generating a trigger result for the preset event according to the trigger probability information, the The inertial data determines the triggering result of the preset event, and the triggering result of the preset event is generated from the triggering probability information, which can accurately determine whether the chassis of the vehicle is scratched or bumped during the driving process of the vehicle.
- FIG. 1 is a flowchart of steps of a method for data processing provided by an embodiment of the present invention
- FIG. 3 is a flowchart of steps of another data processing method provided by an embodiment of the present invention.
- FIG. 5 is a schematic structural diagram of an apparatus for data processing provided by an embodiment of the present invention.
- FIG. 1 a flowchart of steps of a data processing method provided by an embodiment of the present invention is shown, which may specifically include the following steps:
- Step 101 acquiring inertial data of the vehicle
- the inertial data may include any one or more of the following:
- the vehicle chassis When the vehicle is driving in a complex road environment, the vehicle chassis is prone to scratches or bumps. When the vehicle chassis is scratched or bumped, the data collected by the sensors will change, such as abnormal values in inertial data.
- non-P gear which can be a gear other than the parking gear, such as drive gear, low gear, etc.
- inertial data can be obtained, and then it can be judged whether the vehicle chassis has occurred. scratches or bumps.
- inertial data can be obtained through sensors, specifically, inertial data can be obtained through inertial measurement sensors or other devices that can collect inertial data, and inertial measurement sensors or other devices that can collect inertial data can be installed on the vehicle chassis or battery.
- the upper position is close to the center of mass, the outside of the upper or lower shell of the battery is close to the center, and the inside of the battery is close to the center, so that the inertial data can be accurately measured to avoid data distortion during the transmission process.
- There must be no flexible links such as rubber shock absorbers between the inertial measurement sensor and the battery; if there is a rubber shock absorber between the battery and the chassis, the inertial measurement sensor can be mounted on the battery housing.
- the signal data collected by the sensor has the characteristics of obvious data characteristics and high stability, and through the vertical acceleration information and pitch angular velocity information, it can accurately identify whether the vehicle chassis is scratched or bumped.
- Step 102 determining trigger probability information for a preset event according to the inertial data
- the preset event may be a vehicle chassis rubbing event or a vehicle chassis bumping event.
- the trigger probability information of the preset event is determined by the data characteristics of the inertial data when the vehicle chassis is scratched or bumped.
- the trigger probability information of the vehicle chassis rubbing event and/or the vehicle chassis bumping event is 0%.
- Step 103 Generate a trigger result for the preset event according to the trigger probability information.
- the triggering result of the preset event may be that the preset event is triggered and the preset event is not triggered.
- the trigger result of the preset event may be generated according to the trigger probability information.
- the generated trigger result is that the preset event is not triggered, that is, the vehicle chassis is not scratched or bumped; when the trigger probability information is greater than or equal to the preset value, the generated trigger The result is to trigger a preset event, that is, the vehicle chassis is scratched or bumped.
- the present invention by acquiring inertial data of the vehicle, determining trigger probability information for a preset event according to the inertial data, and generating a trigger result for the preset event according to the trigger probability information, the The inertial data determines the triggering result of the preset event, and the triggering result of the preset event is generated from the triggering probability information, which can accurately determine whether the chassis of the vehicle is scratched or bumped during the driving process of the vehicle.
- FIG. 2 a flowchart of steps of another data processing method provided by an embodiment of the present invention is shown, which may specifically include the following steps:
- Step 201 acquiring inertial data of the vehicle
- the inertial data may include any one or more of the following:
- the vehicle chassis When the vehicle is driving in a complex road environment, the vehicle chassis is prone to scratches or bumps. When the vehicle chassis is scratched or bumped, the data collected by the sensors will change, such as abnormal values in inertial data.
- non-P gear which can be a drive gear, a low gear, or other gears other than the parking gear
- inertial data can be obtained, and then it can be judged whether the vehicle chassis has occurred. scratches or bumps.
- inertial data can be obtained through sensors, specifically, inertial data can be obtained through inertial measurement sensors or other devices that can collect inertial data, and inertial measurement sensors or other devices that can collect inertial data can be installed on the vehicle chassis or battery.
- the upper position is close to the center of mass, the outside of the upper or lower shell of the battery is close to the center, and the inside of the battery is close to the center, so that the inertial data can be accurately measured to avoid data distortion during the transmission process.
- There must be no flexible links such as rubber shock absorbers between the inertial measurement sensor and the battery; if there is a rubber shock absorber between the battery and the chassis, the inertial measurement sensor can be mounted on the battery housing.
- the signal data collected by the sensor has the characteristics of obvious data characteristics and high stability, and through the vertical acceleration information and pitch angular velocity information, it is possible to accurately identify whether the vehicle chassis is scratched or bumped.
- Step 202 obtaining vehicle speed information of the vehicle
- the vehicle speed signal After acquiring the inertial data, the vehicle speed signal can also be acquired.
- the vehicle speed signal may be obtained through a sensor (eg, a wheel speed sensor and other sensors) or other devices for obtaining the vehicle speed (the monitoring controller may calculate the vehicle speed according to the rotational speed of the motor).
- a sensor eg, a wheel speed sensor and other sensors
- the monitoring controller may calculate the vehicle speed according to the rotational speed of the motor.
- Step 203 Determine target inertial data from the inertial data according to the vehicle speed information
- inertial data There is a correlation between inertial data and vehicle speed information. With different vehicle speed information, the data characteristics of inertial data are different when the vehicle chassis is scratched or bumped. It is relatively obvious, but when the vehicle is running at high speed, a scratching event or a bumping event occurs, the inertial data is not very obvious, and it is not easy to judge the abnormal value.
- the parameters of the preset algorithm eg, filter algorithm
- filter parameters e.g. filter parameters
- the method before the determining the target inertial data from the inertial data according to the vehicle speed information, the method further includes:
- the inertial data Before determining the target inertial data from the inertial data, the inertial data can be filtered to obtain effective and drift-free target inertial data. And misjudgment occurred.
- the filtering of the inertial data may include:
- the inertial data After acquiring the inertial data, it can be determined whether the sensor or other equipment is operating normally by acquiring the operating data of the sensor or other equipment that acquires the inertial data. When the operation is normal, it can be determined that the acquired inertial data is valid data; when the operation is abnormal , it can be determined that the acquired inertial data is invalid data.
- the inertial data can be zero-drifted by the drift value of the vehicle in the non-moving state, and the drift value of the inertial data can be removed to obtain the target inertial data.
- Invalid data and drift values will actually make the inertial data larger or smaller, so that the abnormal data cannot be accurately extracted as the target inertial data. Therefore, by filtering the inertial data, the accuracy of the extracted target inertial data can be improved.
- Step 204 Determine trigger probability information for a preset event according to the target inertial data.
- trigger probability information for the preset event may be determined according to the target inertial data.
- the trigger probability information for the preset event can be determined according to the target inertial data through an expert experience model, a threshold value judgment method, or an intelligent algorithm such as a neural network or deep learning.
- Step 205 Generate a trigger result for the preset event according to the trigger probability information.
- the triggering result of the preset event may be that the preset event is triggered and the preset event is not triggered.
- the trigger result of the preset event may be generated according to the trigger probability information.
- the generated trigger result is that the preset event is not triggered, that is, the vehicle chassis is not scratched or bumped; when the trigger probability information is greater than or equal to the preset value, the generated trigger The result is to trigger a preset event, that is, the vehicle chassis is scratched or bumped.
- the vehicle speed information of the vehicle is obtained by acquiring the inertial data of the vehicle, and the target inertial data is determined from the inertial data according to the vehicle speed information, and the target inertial data is determined according to the target inertial data.
- the trigger probability information of the event According to the trigger probability information, the trigger result for the preset event is generated, so that the trigger result of the preset event is determined by inertial data, and the trigger result of the preset event is generated from the trigger probability information. Accurately determine whether the chassis of the vehicle is scratched or bumped.
- FIG. 3 a flowchart of steps of another data processing method provided by an embodiment of the present invention is shown, which may specifically include the following steps:
- Step 301 acquiring inertial data of the vehicle
- Step 302 determining trigger probability information for a preset event according to the inertial data
- Step 303 Generate a trigger result for the preset event according to the trigger probability information.
- Step 304 when triggering the preset event, generate event data for the preset event;
- the event data may include one or more of the following:
- Event level information For Event level information, target video data and/or target vehicle status data.
- event data for the preset event can be generated
- the event data includes event level information
- generating event data for the preset event includes:
- event level information for the preset event is generated according to the trigger probability information.
- a corresponding event level When triggering a preset event, a corresponding event level may be set in advance according to different trigger probability information gradients, so that event level information for the preset event may be generated according to the event trigger probability information.
- the probability level By using the probability level to evaluate the scratching event or bumping event of the vehicle chassis, it is possible to determine the severity of the scratching event or bumping event, the probability of scratching event or bumping event, and the like.
- the event data further includes target video data and/or target vehicle state data, and when the preset event is triggered, the event data for the preset event is generated, including:
- the flag bit information for the preset event can be generated immediately, and the flag bit information can determine the specific time when the preset event occurs. Therefore, from the collected video data, the corresponding flag bit information can be determined.
- the target video data that is, the video data for a period of time before and after the occurrence of the preset event, or the target vehicle status data corresponding to the flag information can be determined from the collected vehicle status data, that is, the entire vehicle for a period of time before and after the preset event occurs. status data.
- Step 305 sending the event data to the cloud platform.
- the event data is sent to the cloud platform.
- the event data generated when the vehicle chassis is scratched or bumped can be sent to the cloud platform for analysis and processing.
- the cloud platform can be set to continuously send event data to the cloud platform within a certain period of time.
- the cloud platform can generate a reminder message according to the event data, and can send the reminder message to the large screen of the vehicle for display, so as to remind the owner that the chassis of the vehicle is scratched or bumped, or The reminder message is sent to the user terminal.
- the embodiment of the present invention acquires inertial data of the vehicle, determines trigger probability information for a preset event according to the inertial data, generates a trigger result for the preset event according to the trigger probability information, and generates a trigger result for the preset event according to the trigger probability information.
- event data for the preset event is generated, so that the trigger result of the preset event is determined by inertial data, and the trigger result of the preset event is generated from the trigger probability information, which can accurately determine the trigger result of the preset event during the driving process of the vehicle. Determine whether the chassis of the vehicle is scratched or bumped.
- the vehicle may include: an inertial measurement sensor and a monitoring controller; wherein, the monitoring controller may include a signal processing module, a bottom knock monitoring probability calculation module, and an output signal processing module.
- the vehicle can also be connected to the cloud.
- the inertial measurement sensor at the position of the vehicle chassis can acquire the vertical acceleration information and/or the pitch angular velocity information (inertial data) in real time.
- the vehicle speed signal can be obtained in real time through sensors (such as sensors such as wheel speed sensors) or other devices for obtaining the vehicle speed (the monitoring controller can calculate the vehicle speed according to the motor speed).
- the specific data processing process may be to filter the vertical acceleration information and/or the pitch angular velocity information. (judging validity, zero drift processing, etc.), and adjusting the filter parameters according to the vehicle speed signal, and obtaining the target inertial data (vehicle state signal) through the filtering algorithm.
- the trigger probability information for the preset event can be determined according to the target inertial data through an expert experience model, a threshold value judgment method, or an intelligent algorithm such as a neural network or deep learning.
- the trigger result of the preset event can be generated according to the trigger probability information, and when the preset event is triggered, the corresponding event level can be set in advance according to different trigger probability information gradients, thereby Event level information for the preset event may be generated according to the event trigger probability information.
- FIG. 5 a schematic structural diagram of a data processing apparatus provided by an embodiment of the present invention is shown, which is applied to a vehicle and may specifically include the following modules:
- an inertial data acquisition module 501 configured to acquire inertial data of the vehicle
- a trigger probability information determination module 502 configured to determine trigger probability information for a preset event according to the inertial data
- a triggering result generating module 503 is configured to generate a triggering result for the preset event according to the triggering probability information.
- the trigger probability information determination module 502 may include:
- a vehicle speed acquisition sub-module for acquiring the vehicle speed information of the vehicle
- a target inertial data determination submodule configured to determine target inertial data from the inertial data according to the vehicle speed information
- the trigger probability information determination sub-module is configured to determine trigger probability information for a preset event according to the target inertial data.
- the trigger probability information determination module 502 may include:
- the filtering processing submodule is used for filtering the inertial data.
- the apparatus may include:
- an event data generation module configured to generate event data for the preset event when the preset event is triggered
- a sending module configured to send the event data to the cloud platform.
- the event data may include event level information
- the event data generating module includes:
- the event level information generating sub-module is configured to generate event level information for the preset event according to the trigger probability information when the preset event is triggered.
- the event data further includes target video data and/or target vehicle status data
- the event data generation module includes:
- a flag bit information generation submodule for generating flag bit information for the preset event when triggering the preset event
- a target video data determination submodule used for determining the target video data corresponding to the flag bit information from the collected video data
- the target vehicle state data determination sub-module is used for determining the target vehicle state data corresponding to the flag bit information from the collected vehicle state data.
- the present invention by acquiring inertial data of the vehicle, determining trigger probability information for a preset event according to the inertial data, and generating a trigger result for the preset event according to the trigger probability information, the The inertial data determines the triggering result of the preset event, and the triggering result of the preset event is generated from the triggering probability information, which can accurately determine whether the chassis of the vehicle is scratched or bumped during the driving process of the vehicle.
- An embodiment of the present invention also provides a server, which may include a processor, a memory, and a computer program stored in the memory and capable of running on the processor.
- a server which may include a processor, a memory, and a computer program stored in the memory and capable of running on the processor.
- An embodiment of the present invention further provides a computer-readable storage medium, where a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the above data processing method is implemented.
- embodiments of the present invention may be provided as a method, an apparatus, or a computer program product. Accordingly, embodiments of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present invention may take the form of a computer program product implemented on one or more computer-usable storage media having computer-usable program code embodied therein, including but not limited to disk storage, CD-ROM, optical storage, and the like.
- Embodiments of the present invention are described with reference to flowcharts and/or block diagrams of methods, terminal devices (systems), and computer program products according to embodiments of the present invention. It will be understood that each flow and/or block in the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to the processor of a general purpose computer, special purpose computer, embedded processor or other programmable data processing terminal equipment to produce a machine that causes the instructions to be executed by the processor of the computer or other programmable data processing terminal equipment Means are created for implementing the functions specified in the flow or flows of the flowcharts and/or the blocks or blocks of the block diagrams.
- These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing terminal equipment to operate in a particular manner, such that the instructions stored in the computer readable memory result in an article of manufacture comprising instruction means, the The instruction means implement the functions specified in the flow or flow of the flowcharts and/or the block or blocks of the block diagrams.
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Abstract
一种数据处理的方法和装置，方法包括：获取车辆的惯性数据；根据惯性数据，确定针对预设事件的触发概率信息；根据触发概率信息，生成针对预设事件的触发结果。可以在车辆行驶过程中，准确判断车辆底盘是否发生了剐蹭或磕碰。
Description
交叉引用
本申请要求2020年9月29日递交的发明名称为“一种数据处理的方法和装置”的申请号为202011058188.7的在先申请优先权，上述在先申请的内容以引入的方式并入本文本中。
本发明涉及车辆技术领域，特别是涉及一种数据处理的方法和装置。
电动汽车的动力电池系统大多设置在车辆底盘位置。当面对复杂的道路环境时，车辆底盘容易发生剐蹭或磕碰，从而可能会导致电池发生剐蹭或磕碰，在电池出现剐蹭或磕碰现象时，会造成电芯内部被挤压，容易造成安全事故。
目前，为保护电池不发生剐蹭或磕碰，对电池的磕碰预防目前主要集中在被动防护措施方面，比如增加电池防撞梁和防护底板，能够在一定程度上减少电池磕碰时对模组和电芯的损伤，但是，当车辆在复杂的道路环境行驶过程中，车端并不能准确判断车辆底盘是否存在剐蹭或磕碰现象，因此，也无法确定电池是否发生剐蹭或磕碰。
发明内容
鉴于上述问题，提出了以便提供克服上述问题或者至少部分地解决上述问题的一种数据处理的方法和装置，包括：
一种数据处理的方法，应用于车辆，所述方法包括：
获取所述车辆的惯性数据；
根据所述惯性数据，确定针对预设事件的触发概率信息；
根据所述触发概率信息，生成针对所述预设事件的触发结果。
可选地，所述根据所述惯性数据，确定针对预设事件的触发概率信息，包括：
获取所述车辆的车速信息；
根据所述车速信息，从所述惯性数据中，确定目标惯性数据；
根据所述目标惯性数据，确定针对预设事件的触发概率信息。
可选地，在所述根据所述车速信息，从所述惯性数据中，确定目标惯性数据之前，还包括：
对所述惯性数据进行过滤处理。
可选地，还包括：
在触发所述预设事件时，生成针对所述预设事件的事件数据；
将所述事件数据发送至云平台。
可选地，所述事件数据包括事件等级信息，所述在触发所述预设事件时，生成针对所述预设事件的事件数据，包括：
在触发所述预设事件时，根据所述触发概率信息，生成针对所述预设事件的事件等级信息。
可选地，所述事件数据还包括目标视频数据和/或目标整车状态数据，所述在触发所述预设事件时，生成针对所述预设事件的事件数据，包括：
在触发所述预设事件时，生成针对所述预设事件的标志位信息；
从采集的视频数据中，确定所述标志位信息对应的目标视频数据；
和/或，从采集的整车状态数据中，确定所述标志位信息对应的目标整车状态数据。
一种数据处理装置，应用于车辆，所述装置包括：
惯性数据获取模块，用于获取所述车辆的惯性数据；
触发概率信息确定模块，用于根据所述惯性数据，确定针对预设事件的触发概率信息；
触发结果生成模块，用于根据所述触发概率信息，生成针对所述预设事件的触发结果。
可选地，所述触发概率信息确定模块包括：
车速获取子模块，用于获取所述车辆的车速信息；
目标惯性数据确定子模块，用于根据所述车速信息，从所述惯性数据中，确定目标惯性数据；
触发概率信息确定子模块，用于根据所述目标惯性数据，确定针对预设事件的触发概率信息。
一种服务器，包括处理器、存储器及存储在所述存储器上并能够在所述处理器上运行的计算机程序，所述计算机程序被所述处理器执行时实现如上所述的数据处理的方法。
一种计算机可读存储介质，所述计算机可读存储介质上存储计算机程序，所述计算机程序被处理器执行时实现如上所述的数据处理的方法。
本发明实施例具有以下优点：
本发明实施例通过获取所述车辆的惯性数据，根据所述惯性数据，确定针对预设事件的触发概率信息，根据所述触发概率信息，生成针对所述预设事件的触发结果，实现了通过惯性数据确定预设事件的触发结果，由触发概率信息生成预设事件的触发结果，可以在车辆行驶过程中，准确判断车辆底盘是否发生了剐蹭或磕碰。
为了更清楚地说明本发明的技术方案，下面将对本发明的描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
图1是本发明一实施例提供的一种数据处理的方法的步骤流程图；
图2是本发明一实施例提供的另一种数据处理的方法的步骤流程图；
图3是本发明一实施例提供的又一种数据处理的方法的步骤流程图；
图4是本发明一实施例提供的一种数据处理的方法流程图；
图5是本发明一实施例提供的数据处理的装置的结构示意图。
为使本发明的上述目的、特征和优点能够更加明显易懂，下面结合附图和具体实施方式对本发明作进一步详细的说明。显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有作出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。
参照图1，示出了本发明一实施例提供的一种数据处理的方法的步骤流程图，具体可以包括如下步骤：
步骤101，获取所述车辆的惯性数据；
在一示例中，所述惯性数据可以包括以下任一项或多项：
垂向加速度信息、俯仰角速度信息。
当车辆在复杂的道路环境行驶时，车辆底盘容易发生剐蹭或磕碰，当车辆底盘发生剐蹭或磕碰时，会导致传感器采集的数据发生变化，如惯性数据会出现异常值。
在车辆处于上电状态且处于非P档(停车挡)时(非P档，可以是驱动档、低速档等除停车挡以外的档位)，可以获取惯性数据，进而可以判断是否发生车辆底盘的剐蹭或磕碰。
在一示例中，可以通过传感器获取惯性数据，具体的，可以通过惯性测量传感器或其他可以采集惯性数据的其他设备获取惯性数据，惯性测量传感器或采集惯性数据的其他设备可以安装在车辆底盘或电池上靠近质心位置、电池上壳体或下壳体外部接近中心位置、电池内部接近中心位置，进而可以准确测量惯性数据，避免传输过程中，发生数据失真等情况，惯性测量传感器或采集惯性数据的其他设备和电池或车辆底盘的连接之间没有柔性连接，全部为刚性固定，可以有效避免信号衰减，进一步确保获取的惯性数据的真实性。惯性测量传感器和电池之间不能有橡胶减震装置之类的柔性环节；如果电池和底盘之间有橡胶减震装置，则惯性测量传感器可以安装在电池壳体上。
通过传感器采集的信号数据具有数据特征明显、稳定性高的特点，而且 通过垂向加速度信息和俯仰角速度信息，可以准确识别车辆底盘是否存在剐蹭或磕碰。
步骤102，根据所述惯性数据，确定针对预设事件的触发概率信息；
在一示例中，所述预设事件可以是车辆底盘剐蹭事件、车辆底盘磕碰事件。
在获取惯性数据之后，通过惯性数据在车辆底盘发生剐蹭或磕碰时的数据特征，确定预设事件的触发概率信息。
例如：当车辆正常运行时，惯性数据不存在异常值，可以确定车辆底盘剐蹭事件和/或车辆底盘磕碰事件触发概率信息为0％。
步骤103，根据所述触发概率信息，生成针对所述预设事件的触发结果。
在一示例中，所述预设事件的触发结果可以是触发预设事件、未触发预设事件。
在确定预设事件的触发概率信息之后，可以根据触发概率信息生成所述预设事件的触发结果。
例如：当触发概率信息为零或小于预设值时，生成的触发结果为未触发预设事件，即车辆底盘未发生剐蹭或磕碰；当触发概率信息大于或等于预设值时，生成的触发结果为触发预设事件，即车辆底盘发生剐蹭或磕碰。
本发明实施例通过获取所述车辆的惯性数据，根据所述惯性数据，确定针对预设事件的触发概率信息，根据所述触发概率信息，生成针对所述预设事件的触发结果，实现了通过惯性数据确定预设事件的触发结果，由触发概率信息生成预设事件的触发结果，可以在车辆行驶过程中，准确判断车辆底盘是否发生了剐蹭或磕碰。
参照图2，示出了本发明一实施例提供的另一种数据处理的方法的步骤流程图，具体可以包括如下步骤：
步骤201，获取所述车辆的惯性数据；
在一示例中，所述惯性数据可以包括以下任一项或多项：
垂向加速度信息、俯仰角速度信息。
当车辆在复杂的道路环境行驶时，车辆底盘容易发生剐蹭或磕碰，当车辆底盘发生剐蹭或磕碰时，会导致传感器采集的数据发生变化，如惯性数据会出现异常值。
在车辆处于上电状态且处于非P档(停车档)时(非P档，可以是驱动档、低速档等除停车挡以外的档位)，可以获取惯性数据，进而可以判断是否发生车辆底盘的剐蹭或磕碰。
在一示例中，可以通过传感器获取惯性数据，具体的，可以通过惯性测量传感器或其他可以采集惯性数据的其他设备获取惯性数据，惯性测量传感器或采集惯性数据的其他设备可以安装在车辆底盘或电池上靠近质心位置、电池上壳体或下壳体外部接近中心位置、电池内部接近中心位置，进而可以准确测量惯性数据，避免传输过程中，发生数据失真等情况，惯性测量传感器或采集惯性数据的其他设备和电池或车辆底盘的连接之间没有柔性连接，全部为刚性固定，可以有效避免信号衰减，进一步确保获取的惯性数据的真实性。惯性测量传感器和电池之间不能有橡胶减震装置之类的柔性环节；如果电池和底盘之间有橡胶减震装置，则惯性测量传感器可以安装在电池壳体上。
通过传感器采集的信号数据具有数据特征明显、稳定性高的特点，而且通过垂向加速度信息和俯仰角速度信息，可以准确识别车辆底盘是否存在剐蹭或磕碰。
步骤202，获取所述车辆的车速信息；
在获取惯性数据之后，还可以获取车速信号。
在一示例中，可以通过传感器(如：轮速传感器等传感器)或获取车速的其他设备(监控控制器可以根据电机转速计算车速)获取车速信号。
步骤203，根据所述车速信息，从所述惯性数据中，确定目标惯性数据；
惯性数据与车速信息之间存在关联，不同车速信息时，惯性数据在车辆底盘发生剐蹭事件或磕碰事件时的数据特征不同，例如，在车辆处于低速行驶时发生剐蹭事件或磕碰事件，惯性数据特征比较明显，而在车辆处于高速行驶时发生剐蹭事件或磕碰事件，惯性数据不是很明显，不容易判断异常值。
在获取车速信号后，可以根据车速信号确定预设算法(如：滤波算法)的参数(如：滤波器参数)，通过设置不同的参数，可以在惯性数据中，提取不同车速下的目标惯性数据。
在本发明一实施例中，在所述根据所述车速信息，从所述惯性数据中，确定目标惯性数据之前，还包括：
对所述惯性数据进行过滤处理。
在从惯性数据中确定目标惯性数据之前，可以对惯性数据进行过滤，以得到有效且无漂移的目标惯性数据，有利于准确判断车辆底盘是否发生剐蹭事件或磕碰事件，避免由于目标惯性数据不够准确而出现误判。
在一示例中，所述对所述惯性数据进行过滤处理，可以包括：
判断所述惯性数据是否为有效数据；当所述惯性数据为有效数据时，对所述惯性数据进行零漂处理。
在获取惯性数据之后，可以通过获取传感器或获取惯性数据的其他设备的运行数据，确定传感器或其他设备的运行是否正常，当运行正常时，可以确定获取的惯性数据为有效数据；当运行异常时，可以确定获取的惯性数据为无效数据。
在确定惯性数据为有效数据后，可以通过车辆在非运动状态下的漂移值，对惯性数据进行零漂处理，去除惯性数据的漂移值，得到目标惯性数据。
无效数据以及漂移值会使惯性数据的值实际上偏大或偏小，从而无法准确提取出异常数据做为目标惯性数据。因此，通过对惯性数据的过滤处理，可以提高所提取目标惯性数据的准确性。
步骤204，根据所述目标惯性数据，确定针对预设事件的触发概率信息。
在确定目标惯性数据后，可以根据目标惯性数据确定针对预设事件的触发概率信息。
在一示例中，可以通过专家经验模型，门限值判断方法，也可以是神经网络或深度学习等智能算法，根据目标惯性数据确定针对预设事件的触发概率信息。
步骤205，根据所述触发概率信息，生成针对所述预设事件的触发结果。
在一示例中，所述预设事件的触发结果可以是触发预设事件、未触发预设事件。
在确定预设事件的触发概率信息之后，可以根据触发概率信息生成所述预设事件的触发结果。
例如：当触发概率信息为零或小于预设值时，生成的触发结果为未触发预设事件，即车辆底盘未发生剐蹭或磕碰；当触发概率信息大于或等于预设值时，生成的触发结果为触发预设事件，即车辆底盘发生剐蹭或磕碰。
本发明实施例通过获取所述车辆的惯性数据，获取所述车辆的车速信息，根据所述车速信息，从所述惯性数据中，确定目标惯性数据，根据所述目标惯性数据，确定针对预设事件的触发概率信息。根据所述触发概率信息，生成针对所述预设事件的触发结果，实现了通过惯性数据确定预设事件的触发结果，由触发概率信息生成预设事件的触发结果，可以在车辆行驶过程中，准确判断车辆底盘是否发生了剐蹭或磕碰。
参照图3，示出了本发明一实施例提供的又一种数据处理的方法的步骤流程图，具体可以包括如下步骤：
步骤301，获取所述车辆的惯性数据；
步骤302，根据所述惯性数据，确定针对预设事件的触发概率信息；
步骤303，根据所述触发概率信息，生成针对所述预设事件的触发结果。
步骤304，在触发所述预设事件时，生成针对所述预设事件的事件数据；在一示例中，所述事件数据可以包括以下一项或多项：|
事件等级信息、目标视频数据和/或目标整车状态数据。
在得到触发结果之后，当确定可以触发预设事件时，可以生成针对预设事件的事件数据；
在本发明一实施例中，所述事件数据包括事件等级信息，所述在触发所述预设事件时，生成针对所述预设事件的事件数据，包括：
在触发所述预设事件时，根据所述触发概率信息，生成针对所述预设事件的事件等级信息。
在触发预设事件时，可以预先按照不同的触发概率信息分梯度设置对应的事件等级，从而可以根据事件触发概率信息生成针对预设事件的事件等级信息。
通过采用概率等级来评估车辆底盘的剐蹭事件或磕碰事件，可以确定剐蹭事件或磕碰事件的严重程度、剐蹭事件或磕碰事件的可能性等。
在本发明一实施例中，所述事件数据还包括目标视频数据和/或目标整车状态数据，所述在触发所述预设事件时，生成针对所述预设事件的事件数据，包括：
在触发所述预设事件时，生成针对所述预设事件的标志位信息；从采集的视频数据中，确定所述标志位信息对应的目标视频数据；和/或，从采集的整车状态数据中，确定所述标志位信息对应的目标整车状态数据。
在触发预设事件时，可以立即生成针对预设事件的标志位信息，标志位信息可以确定发生预设事件的具体时间，因此，可以从采集的视频数据中，确定所述标志位信息对应的目标视频数据，即发生预设事件前后一段时间的视频数据，也可以从采集的整车状态数据中，确定标志位信息对应的目标整车状态数据，即发生预设事件前后一段时间的整车状态数据。
步骤305，将所述事件数据发送至云平台。
将所述事件数据发送至云平台。
为了实现对车辆底盘发生剐蹭或磕碰时的及时监控，可以将在车辆底盘发生剐蹭或磕碰时所生成的事件数据发送至云平台进行分析处理。为了确保云平台可以接收到事件数据，可以设置在一定时间内，持续向云平台发送事件数据。
在一示例中，云平台可以在接收到事件数据后，根据事件数据生成提醒消息，并可以将提醒消息发送至车辆的大屏进行展示，以提示车主车辆底盘发生剐蹭或磕碰的情况，或者将提醒消息发送至用户终端。
通过准确的识别出车辆底盘是否发生了剐蹭或磕碰，作为电池安全的主动预警措施，能够大大降低电池在发生磕碰后继续使用带来的安全风险，为维修检查磕碰电池提供及时有效的预警。
本发明实施例通过获取所述车辆的惯性数据，根据所述惯性数据，确定针对预设事件的触发概率信息，根据所述触发概率信息，生成针对所述预设事件的触发结果，在触发所述预设事件时，生成针对所述预设事件的事件数据，实现了通过惯性数据确定预设事件的触发结果，由触发概率信息生成预设事件的触发结果，可以在车辆行驶过程中，准确判断车辆底盘是否发生了剐蹭或磕碰。
以下结合图4对本发明进行示例性说明：
在车辆中可以包括：惯性测量传感器、监控控制器；其中，监控控制器可以包括信号处理模块、磕底监控概率计算模块、输出信号处理模块。此外，该车辆还可以与云端连接。
在磕底监控过程中，可以包括以下步骤：
(1)在车辆行驶过程中，车辆底盘位置的惯性测量传感器可以实时获取垂向加速度信息和/或俯仰角速度信息(惯性数据)。
(2)在车辆行驶过程中，可以通过传感器(如：轮速传感器等传感器)或获取车速的其他设备(监控控制器可以根据电机转速计算车速)实时获取车速信号。
(3)将垂向加速度信息和/或俯仰角速度信息、以及车速信号一同发送至信号处理模块，进行相应数据处理；具体数据处理过程可以是对垂向加速度信息和/或俯仰角速度信息进行过滤处理(判断有效性、零漂处理等)，并根据车速信号调整滤波器参数，通过滤波算法得到目标惯性数据(车辆状态信号)。
(4)将目标惯性数据发送至磕底监控概率计算模块，计算磕底概率(触发概率信息)。
可以通过专家经验模型，门限值判断方法，也可以是神经网络或深度学习等智能算法，根据目标惯性数据确定针对预设事件的触发概率信息。
(5)将电池磕底概率发送至输出信号处理模块，得到磕底概率等级(事件等级信息)。
在确定预设事件的触发概率信息之后，可以根据触发概率信息生成所述预设事件的触发结果，在触发预设事件时，可以预先按照不同的触发概率信息分梯度设置对应的事件等级，从而可以根据事件触发概率信息生成针对预设事件的事件等级信息。
(6)将磕底概率等级发送至云端。
需要说明的是，对于方法实施例，为了简单描述，故将其都表述为一系列的动作组合，但是本领域技术人员应该知悉，本发明实施例并不受所描述的动作顺序的限制，因为依据本发明实施例，某些步骤可以采用其他顺序或者同时进行。其次，本领域技术人员也应该知悉，说明书中所描述的实施例均属于优选实施例，所涉及的动作并不一定是本发明实施例所必须的。
参照图5，示出了本发明一实施例提供的一种数据处理的装置的结构示意图，应用于车辆，具体可以包括如下模块：
惯性数据获取模块501，用于获取所述车辆的惯性数据；
触发概率信息确定模块502，用于根据所述惯性数据，确定针对预设事件的触发概率信息；
触发结果生成模块503，用于根据所述触发概率信息，生成针对所述预设事件的触发结果。
在本发明一实施例中，触发概率信息确定模块502可以包括：
车速获取子模块，用于获取所述车辆的车速信息；
目标惯性数据确定子模块，用于根据所述车速信息，从所述惯性数据中，确定目标惯性数据；
触发概率信息确定子模块，用于根据所述目标惯性数据，确定针对预设事件的触发概率信息。
在本发明一实施例中，触发概率信息确定模块502可以包括：
过滤处理子模块，用于对所述惯性数据进行过滤处理。
在本发明一实施例中，所述装置可以包括：
事件数据生成模块，用于在触发所述预设事件时，生成针对所述预设事件的事件数据；
发送模块，用于将所述事件数据发送至云平台。
在本发明一实施例中，所述事件数据可以包括事件等级信息，所述事件数据生成模块，包括：
事件等级信息生成子模块，用于在触发所述预设事件时，根据所述触发概率信息，生成针对所述预设事件的事件等级信息。
在本发明一实施例中，所述事件数据还包括目标视频数据和/或目标整车状态数据，述事件数据生成模块，包括：
标志位信息生成子模块，用于在触发所述预设事件时，生成针对所述预设事件的标志位信息；
目标视频数据确定子模块，用于从采集的视频数据中，确定所述标志位信息对应的目标视频数据；
目标整车状态数据确定子模块，用于从采集的整车状态数据中，确定所述标志位信息对应的目标整车状态数据。
本发明实施例通过获取所述车辆的惯性数据，根据所述惯性数据，确定针对预设事件的触发概率信息，根据所述触发概率信息，生成针对所述预设事件的触发结果，实现了通过惯性数据确定预设事件的触发结果，由触发概率信息生成预设事件的触发结果，可以在车辆行驶过程中，准确判断车辆底盘是否发生了剐蹭或磕碰。
本发明一实施例还提供了一种服务器，可以包括处理器、存储器及存储在存储器上并能够在处理器上运行的计算机程序，计算机程序被处理器执行时实现如上数据处理的方法。
本发明一实施例还提供了一种计算机可读存储介质，计算机可读存储介质上存储计算机程序，计算机程序被处理器执行时实现如上数据处理的方法。
对于装置实施例而言，由于其与方法实施例基本相似，所以描述的比较简单，相关之处参见方法实施例的部分说明即可。
本说明书中的各个实施例均采用递进的方式描述，每个实施例重点说明的都是与其他实施例的不同之处，各个实施例之间相同相似的部分互相参见即可。
本领域内的技术人员应明白，本发明实施例可提供为方法、装置、或计算机程序产品。因此，本发明实施例可采用完全硬件实施例、完全软件实施例、或结合软件和硬件方面的实施例的形式。而且，本发明实施例可采用在一个或多个其中包含有计算机可用程序代码的计算机可用存储介质(包括但不限于磁盘存储器、CD-ROM、光学存储器等)上实施的计算机程序产品的形式。
本发明实施例是参照根据本发明实施例的方法、终端设备(系统)、和计算机程序产品的流程图和/或方框图来描述的。应理解可由计算机程序指令实现流程图和/或方框图中的每一流程和/或方框、以及流程图和/或方框图中的流程和/或方框的结合。可提供这些计算机程序指令到通用计算机、专用计算机、嵌入式处理机或其他可编程数据处理终端设备的处理器以产生一个机器，使得通过计算机或其他可编程数据处理终端设备的处理器执行的指令产生用于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的装置。
这些计算机程序指令也可存储在能引导计算机或其他可编程数据处理终端设备以特定方式工作的计算机可读存储器中，使得存储在该计算机可读存储器中的指令产生包括指令装置的制造品，该指令装置实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能。
这些计算机程序指令也可装载到计算机或其他可编程数据处理终端设备上，使得在计算机或其他可编程终端设备上执行一系列操作步骤以产生计算机实现的处理，从而在计算机或其他可编程终端设备上执行的指令提供用 于实现在流程图一个流程或多个流程和/或方框图一个方框或多个方框中指定的功能的步骤。
尽管已描述了本发明实施例的优选实施例，但本领域内的技术人员一旦得知了基本创造性概念，则可对这些实施例做出另外的变更和修改。所以，所附权利要求意欲解释为包括优选实施例以及落入本发明实施例范围的所有变更和修改。
最后，还需要说明的是，在本文中，诸如第一和第二等之类的关系术语仅仅用来将一个实体或者操作与另一个实体或操作区分开来，而不一定要求或者暗示这些实体或操作之间存在任何这种实际的关系或者顺序。而且，术语“包括”、“包含”或者其任何其他变体意在涵盖非排他性的包含，从而使得包括一系列要素的过程、方法、物品或者终端设备不仅包括那些要素，而且还包括没有明确列出的其他要素，或者是还包括为这种过程、方法、物品或者终端设备所固有的要素。在没有更多限制的情况下，由语句“包括一个……”限定的要素，并不排除在包括所述要素的过程、方法、物品或者终端设备中还存在另外的相同要素。
以上对所提供的一种数据处理的方法和装置，进行了详细介绍，本文中应用了具体个例对本发明的原理及实施方式进行了阐述，以上实施例的说明只是用于帮助理解本发明的方法及其核心思想；同时，对于本领域的一般技术人员，依据本发明的思想，在具体实施方式及应用范围上均会有改变之处，综上所述，本说明书内容不应理解为对本发明的限制。
Claims (10)
- 一种数据处理的方法，其特征在于，应用于车辆，所述方法包括：获取所述车辆的惯性数据；根据所述惯性数据，确定针对预设事件的触发概率信息；根据所述触发概率信息，生成针对所述预设事件的触发结果。
- 根据权利要求1所述的方法，其特征在于，所述根据所述惯性数据，确定针对预设事件的触发概率信息，包括：获取所述车辆的车速信息；根据所述车速信息，从所述惯性数据中，确定目标惯性数据；根据所述目标惯性数据，确定针对预设事件的触发概率信息。
- 根据权利要求2所述的方法，其特征在于，在所述根据所述车速信息，从所述惯性数据中，确定目标惯性数据之前，还包括：对所述惯性数据进行过滤处理。
- 根据权利要求1或2或3所述的方法，其特征在于，还包括：在触发所述预设事件时，生成针对所述预设事件的事件数据；将所述事件数据发送至云平台。
- 根据权利要求4所述的方法，其特征在于，所述事件数据包括事件等级信息，所述在触发所述预设事件时，生成针对所述预设事件的事件数据，包括：在触发所述预设事件时，根据所述触发概率信息，生成针对所述预设事件的事件等级信息。
- 根据权利要求4所述的方法，其特征在于，所述事件数据还包括目标视频数据和/或目标整车状态数据，所述在触发所述预设事件时，生成针对所述预设事件的事件数据，包括：在触发所述预设事件时，生成针对所述预设事件的标志位信息；从采集的视频数据中，确定所述标志位信息对应的目标视频数据；和/或，从采集的整车状态数据中，确定所述标志位信息对应的目标整车状态数据。
- 一种数据处理装置，其特征在于，应用于车辆，所述装置包括：惯性数据获取模块，用于获取所述车辆的惯性数据；触发概率信息确定模块，用于根据所述惯性数据，确定针对预设事件的触发概率信息；触发结果生成模块，用于根据所述触发概率信息，生成针对所述预设事件的触发结果。
- 根据权利要求1所述的方法，其特征在于，所述触发概率信息确定模块包括：车速获取子模块，用于获取所述车辆的车速信息；目标惯性数据确定子模块，用于根据所述车速信息，从所述惯性数据中，确定目标惯性数据；触发概率信息确定子模块，用于根据所述目标惯性数据，确定针对预设事件的触发概率信息。
- 一种服务器，其特征在于，包括处理器、存储器及存储在所述存储器上并能够在所述处理器上运行的计算机程序，所述计算机程序被所述处理器执行时实现如权利要求1至6中任一项所述的数据处理的方法。
- 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质上存储计算机程序，所述计算机程序被处理器执行时实现如权利要求1至6中任一项所述的数据处理的方法。
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