CN117649213B - Front-end management method and system for transportation safety - Google Patents
Front-end management method and system for transportation safety Download PDFInfo
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Abstract
The invention relates to the technical field of transportation management, in particular to a transportation safety front-end management method and a system, comprising the steps of establishing a front-end safety management platform of a freight vehicle; collecting vehicle safety hardware data, establishing a linear regression model, and predicting vehicle safety hardware performance loss; checking and repairing the safety hardware of the vehicle with serious performance loss; the driver evaluates the repaired vehicle safety hardware, checks the repaired vehicle safety hardware according to other vehicle detection catalogues, and transmits an evaluation result to the front safety management platform; the front safety management platform generates an approval report for the transport vehicle with normal evaluation results; after the terminal confirms the approval report, the driver drives the vehicle to enter a transportation flow and execute the transportation task. The invention optimizes the detection of the key safety hardware performance of the vehicle and the flow of the safety detection of the vehicle, and greatly improves the safety detection efficiency before the transportation of the vehicle.
Description
Technical Field
The invention relates to the technical field of transportation management, in particular to a transportation safety front-end management method and system.
Background
The safety inspection of the transport vehicle is a vital part in the process of transporting goods, and has great significance on transportation safety and driving safety.
The existing transportation safety inspection cannot inspect and predict the key safety performance of the vehicle, and an effective vehicle safety detection means and a concise and efficient vehicle safety detection flow are lacked.
In view of this, the invention provides a transportation safety front-end management method and system, which optimize the detection of key safety hardware performance of a vehicle and optimize the flow of vehicle safety detection.
Disclosure of Invention
This section is intended to outline some aspects of embodiments of the application and to briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section as well as in the description of the application and in the title of the application, which may not be used to limit the scope of the application.
The present invention has been made in view of the above-described problems.
The invention provides the following technical scheme: a front safety management platform of the freight vehicle is established, the front safety management platform comprises a driver terminal and a server, and a vehicle detection catalog is imported into the server; collecting vehicle safety hardware data, establishing a linear regression model, and predicting vehicle safety hardware performance loss; based on the predicted performance loss of the vehicle safety hardware, the front-end safety management platform arranges a vehicle maintenance center to inspect and repair the vehicle safety hardware with serious performance loss; after the inspection and repair of the vehicle are completed, the driver evaluates the repaired vehicle safety hardware, inspects the vehicle according to other vehicle detection catalogues, and transmits an evaluation result to a front safety management platform at a driver terminal; the front safety management platform checks the evaluation result transmitted by the driver, generates an approval report for the transportation vehicle with normal evaluation result, and transmits the approval report to the driver; after the terminal confirms the approval report, the driver drives the vehicle to enter a transportation flow and execute the transportation task.
Preferably, the vehicle detection list includes vehicle appearance detection, mechanical system detection, electrical system detection, and in-vehicle device consumption detection.
Preferably, the vehicle safety hardware is braking hardware of the vehicle, and the braking hardware comprises a brake, a brake pad, brake fluid and tires; acquiring brake wear data, brake pad wear data, brake fluid pressure loss data and tire wear data through a sensor; and detecting the change of the brake hardware data, and predicting the brake hardware loss.
Preferably, the step of establishing a linear regression model, wherein the step of predicting the performance loss of the safety hardware of the vehicle comprises the steps of predicting the performance loss parameter of the brake hardware by adopting the linear regression model to obtain the current performance loss degree of the brake;
；
wherein, For the data of the wear of the brake,In order to provide brake pad wear data,For the loss of data for the brake fluid pressure,Tire wear data; is a parameter of the regression model, which, ，，，For the weight factors of the respective input features, iteratively solving from historical data; Is an error term.
Preferably, the error termThe calculation formula of (2) is as follows:
；
Wherein i is a parameter; m is the number of weight factor samples; optimizing error terms And minimizing the calculation loss caused by error terms.
Preferably, the current vehicle safety hardware data is obtained, a linear regression model for predicting the brake performance loss value is substituted, and the loss value is calculatedSubstituting lossless brake hardware data to obtain parameter valueWill beAndFitting, if:
；
the brake hardware accords with the safety standard, the performance loss of the safety hardware is in the standard range, and if:
；
The brake hardware does not accord with the safety standard, the loss of the safety hardware is not in the range, and the maintenance is needed;
substituting the loss value obtained by the linear regression model into the current brake hardware data; substituting the lossless brake hardware data into a parameter value obtained by a linear regression model;
wherein, Is the standard braking distance of the vehicle, and the vehicle is provided with a brake system,For the minimum braking distance to be the same,Is the maximum braking distance.
Preferably, when the safety hardware performance is determined to be normal, a driver checks the vehicle according to the vehicle detection catalog, if a problem is detected, the driver contacts the vehicle detection center for maintenance, and then the vehicle is detected after the maintenance; when the vehicle does not detect the problem, filling in an evaluation result of normal operation of the vehicle through a driver terminal;
The front safety management platform checks whether the assessment result transmitted by the driver has a vehicle missing detection phenomenon or not, generates an approval report for the transport vehicle with normal assessment result, and transmits the approval report to the driver;
and the driver confirms the vehicle detection approval report at the terminal, and drives the vehicle to enter a transportation flow after the confirmation is completed.
It is another object of the present invention to provide a system for a transportation security pre-management method.
Preferably, the system comprises a front safety management module, a loss prediction module, a flow detection module, an approval module and a transportation execution module;
the front-end security management module: a front safety management platform of the freight vehicle is established, the front safety management platform comprises a driver terminal and a server, and a vehicle detection catalog is imported into the server;
The loss prediction module: collecting vehicle safety hardware data, establishing a linear regression model, and predicting vehicle safety hardware performance loss;
The flow detection module is used for: based on the predicted performance loss of the vehicle safety hardware, the front-end safety management platform arranges a vehicle maintenance center to inspect and repair the vehicle safety hardware with serious performance loss;
The approval module is used for: after the inspection and repair of the vehicle are completed, the driver evaluates the repaired vehicle safety hardware, inspects the repaired vehicle safety hardware according to other vehicle detection catalogues, transmits an evaluation result to a front safety management platform at a driver terminal, checks the evaluation result transmitted by the driver by the front safety management platform, generates an approval report for the transportation vehicle with a normal evaluation result, and transmits the approval report to the driver;
The transport execution module: after the terminal confirms the approval report, the driver drives the vehicle to enter a transportation flow and execute the transportation task.
The invention has the beneficial effects that: the method provided by the invention mainly optimizes the detection process of the safety performance of the vehicle and optimizes the detection flow of the safety of the vehicle;
The invention provides the prediction type detection of the braking performance in the vehicle safety hardware, establishes a regression model, predicts the braking performance loss of the vehicle by using a small amount of parameters in the vehicle, and saves a large amount of time compared with the traditional detection;
the invention also optimizes the safety detection flow of the vehicle, introduces a driver terminal, and saves the efficiency problem caused by vehicle detection approval.
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 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. Wherein:
FIG. 1 is a flow chart of a method for pre-management of transportation security according to the present invention;
FIG. 2 is a system architecture diagram of a transportation security pre-management system according to the present invention;
fig. 3 is a schematic structural diagram of an electronic device in embodiment 3 of the present invention;
Fig. 4 is a schematic diagram of a computer-readable storage medium according to embodiment 4 of the present invention.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. All other embodiments, which can be made by one of ordinary skill in the art based on the embodiments of the present invention without making any inventive effort, shall fall within the scope of the present invention.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Example 1
Referring to fig. 1, a transportation security pre-management method is provided for a first embodiment of the present invention.
S1, a front safety management platform of the freight vehicle is established, wherein the front safety management platform comprises a driver terminal and a server, and a vehicle detection catalog is imported into the server.
Specifically, the driver terminal is used for reporting transportation information and filling vehicle detection information, and the front safety management platform is used for collecting and storing the transportation management information.
The vehicle detection catalog includes vehicle appearance detection, mechanical system detection, electrical system detection, and in-vehicle device consumption detection.
The vehicle safety hardware is braking hardware of the vehicle, and the braking hardware comprises a brake, a brake pad, brake fluid and tires; acquiring brake wear data, brake pad wear data, brake fluid pressure loss data and tire wear data through a sensor; and detecting the change of the brake hardware data, and predicting the brake hardware loss.
And S2, collecting vehicle safety hardware data, establishing a linear regression model, and predicting the vehicle safety hardware performance loss.
Specifically, a linear regression model is adopted to predict the performance loss parameters of the brake hardware, and the current brake performance loss degree is obtained.
Establishing a linear regression model:；
wherein, For the data of the wear of the brake,In order to provide brake pad wear data,For the loss of data for the brake fluid pressure,Tire wear data; is a parameter of the regression model, which, ，，，For the weight factors of the respective input features, iteratively solving from historical data; As an error term, Is a performance loss parameter of brake hardware.
Error termThe calculation formula of (2) is as follows:
；
Wherein i is a parameter; m is the number of weight factor samples; optimizing error terms Minimizing the calculation loss caused by error term, so that the performance loss parameter of the brake hardwareMore accurate.
Further, the current vehicle safety hardware data is obtained and substituted into a linear regression model for predicting the brake performance loss value, and the loss value is calculatedSubstituting lossless brake hardware data to obtain parameter valueWill beAndFitting, if:
；
the brake hardware accords with the safety standard, the performance loss of the safety hardware is in the standard range, and if:
；
The brake hardware does not accord with the safety standard, the loss of the safety hardware is not in the range, and the maintenance is needed;
substituting the loss value obtained by the linear regression model into the current brake hardware data; substituting the lossless brake hardware data into a parameter value obtained by a linear regression model;
wherein, Is the standard braking distance of the vehicle, and the vehicle is provided with a brake system,For the minimum braking distance to be the same,Is the maximum braking distance.
And S3, based on the predicted performance loss of the vehicle safety hardware, the front safety management platform arranges a vehicle maintenance center to inspect and repair the vehicle safety hardware with serious performance loss.
S4, the driver carries out a detection flow and finishes the front safety inspection of the field vehicle.
When the safety hardware performance is determined to be normal, a driver checks the vehicle according to the vehicle detection catalog, if the problem is detected, the driver contacts the vehicle detection center for maintenance, and the vehicle is detected after the maintenance; and when the vehicle does not detect the problem, filling in an evaluation result of normal operation of the vehicle through the driver terminal.
The front safety management platform checks whether the assessment result transmitted by the driver has a vehicle missing detection phenomenon or not, generates an approval report for the transport vehicle with normal assessment result, and transmits the approval report to the driver.
And the driver confirms the vehicle detection approval report at the terminal, and drives the vehicle to enter a transportation flow after the confirmation is completed.
And S5, after the terminal confirms the approval report, the driver drives the vehicle to enter a transportation flow, and the transportation task is executed.
And the driver confirms the vehicle detection approval report at the terminal, and drives the vehicle to enter a transportation flow after the confirmation is completed.
Example 2
Referring to fig. 2, a system of a transportation security pre-management method is provided for a second embodiment of the present invention.
The system comprises a front-end safety management module, a loss prediction module, a flow detection module, an approval module and a transportation execution module.
The front-end security management module: and establishing a front safety management platform of the freight vehicle, wherein the front safety management platform comprises a driver terminal and a server, and importing a vehicle detection catalog into the server.
The loss prediction module: and collecting vehicle safety hardware data, establishing a linear regression model, and predicting the vehicle safety hardware performance loss.
The flow detection module is used for: based on the predicted performance loss of the vehicle safety hardware, the front-end safety management platform schedules a vehicle maintenance center to inspect and repair the vehicle safety hardware with serious performance loss.
The approval module is used for: after the inspection and repair of the vehicle are completed, the driver evaluates the repaired vehicle safety hardware, inspects the vehicle according to other vehicle detection catalogues, and transmits an evaluation result to the front safety management platform at the driver terminal: the front safety management platform checks the evaluation result transmitted by the driver, generates an approval report for the transportation vehicle with the normal evaluation result, and transmits the approval report to the driver.
The transport execution module: after the terminal confirms the approval report, the driver drives the vehicle to enter a transportation flow and execute the transportation task.
Example 3
Fig. 3 is a schematic structural diagram of an electronic device according to an embodiment of the present application. As shown in fig. 3, an electronic device 500 is also provided in accordance with yet another aspect of the present application. The electronic device 500 may include one or more processors and one or more memories. Wherein the memory has stored therein computer readable code which, when executed by the one or more processors, can perform the multi-source heterogeneous data driven intelligent manufacturing decision method as described above.
The method or system according to embodiments of the application may also be implemented by means of the architecture of the electronic device shown in fig. 3. As shown in fig. 3, the electronic device 500 may include a bus 501, one or more CPUs 502, a Read Only Memory (ROM) 503, a Random Access Memory (RAM) 504, a communication port 505 connected to a network, an input/output component 506, a hard disk 507, and the like. A storage device in electronic device 500, such as ROM503 or hard disk 507, may store the multi-source heterogeneous data driven intelligent manufacturing decision method provided by the present application. The intelligent manufacturing decision method driven by the multi-source heterogeneous data comprises the following steps: a front-end safety management platform of the freight vehicle is established, the front-end safety management platform comprises a driver terminal and a service end, and a vehicle detection catalog is imported into the front-end safety management platform service end; collecting vehicle safety hardware data, establishing a linear regression model, and predicting vehicle safety hardware performance loss; based on the predicted performance loss of the vehicle safety hardware, the front-end safety management platform arranges a vehicle maintenance center to inspect and repair the vehicle safety hardware with serious performance loss; after the inspection and repair of the vehicle are completed, the driver evaluates the repaired vehicle safety hardware, inspects the vehicle according to other vehicle detection catalogues, and transmits an evaluation result to a front safety management platform at a driver terminal; the front safety management platform checks the evaluation result transmitted by the driver, generates an approval report for the transportation vehicle with normal evaluation result, and transmits the approval report to the driver; after the terminal confirms the approval report, the driver drives the vehicle to enter a transportation flow and execute the transportation task.
Further, the electronic device 500 may also include a user interface 508. Of course, the architecture shown in fig. 3 is merely exemplary, and one or more components of the electronic device shown in fig. 3 may be omitted as may be practical in implementing different devices.
Example 4
FIG. 4 is a schematic diagram of a computer-readable storage medium according to one embodiment of the present application. As shown in fig. 4, is a computer-readable storage medium 600 according to one embodiment of the application. Computer readable storage medium 600 has stored thereon computer readable instructions. When the computer readable instructions are executed by the processor, the multi-source heterogeneous data driven intelligent manufacturing decision method according to the embodiments of the present application described with reference to the above figures may be performed. Storage medium 600 includes, but is not limited to, for example, volatile memory and/or nonvolatile memory. Volatile memory can include, for example, random Access Memory (RAM), cache memory (cache), and the like. The non-volatile memory may include, for example, read Only Memory (ROM), hard disk, flash memory, and the like.
In addition, according to embodiments of the present invention, the processes described above with reference to flowcharts may be implemented as computer software programs. For example, the present invention provides a non-transitory machine-readable storage medium storing machine-readable instructions executable by a processor to perform instructions corresponding to the method steps provided by the present invention, which when executed by a Central Processing Unit (CPU), perform the functions defined above in the method of the present invention.
The methods and apparatus, devices of the present invention may be implemented in numerous ways. For example, the methods and apparatus, devices of the present invention may be implemented by software, hardware, firmware, or any combination of software, hardware, firmware. The above-described sequence of steps for the method is for illustration only, and the steps of the method of the present invention are not limited to the sequence specifically described above unless specifically stated otherwise. Furthermore, in some embodiments, the present invention may also be embodied as programs recorded in a recording medium, the programs including machine-readable instructions for implementing the methods according to the present invention. Thus, the present invention also covers a recording medium storing a program for executing the method according to the present invention.
In addition, in the foregoing technical solutions provided in the embodiments of the present invention, parts consistent with implementation principles of corresponding technical solutions in the prior art are not described in detail, so that redundant descriptions are avoided.
The purpose, technical scheme and beneficial effects of the invention are further described in detail in the detailed description. It is to be understood that the above description is only of specific embodiments of the present invention and is not intended to limit the present invention. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
The above preset parameters or preset thresholds are set by those skilled in the art according to actual conditions or are obtained by mass data simulation.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (4)
1. A transportation safety prepositive management method is characterized in that: comprising the steps of (a) a step of,
A front safety management platform of the freight vehicle is established, the front safety management platform comprises a driver terminal and a server, and a vehicle detection catalog is imported into the server;
collecting vehicle safety hardware data, establishing a linear regression model, and predicting vehicle safety hardware performance loss;
Based on the predicted performance loss of the vehicle safety hardware, the front-end safety management platform arranges a vehicle maintenance center to inspect and repair the vehicle safety hardware with serious performance loss;
after the inspection and repair of the vehicle are completed, the driver evaluates the repaired vehicle safety hardware, inspects the vehicle according to other vehicle detection catalogues, and transmits an evaluation result to a front safety management platform at a driver terminal;
The front safety management platform checks the evaluation result transmitted by the driver, generates an approval report for the transportation vehicle with normal evaluation result, and transmits the approval report to the driver;
after the terminal confirms the approval report, the driver drives the vehicle to enter a transportation flow and executes a transportation task;
The vehicle safety hardware is braking hardware of the vehicle, and the braking hardware comprises a brake, a brake pad, brake fluid and tires; acquiring brake wear data, brake pad wear data, brake fluid pressure loss data and tire wear data through a sensor; detecting the data change of the brake hardware, and predicting the loss of the brake hardware;
The step of establishing a linear regression model, which is to predict the performance loss of the safety hardware of the vehicle, comprises the steps of establishing the linear regression model, substituting the performance loss parameters of the brake hardware of the current vehicle, and calculating to obtain the current brake performance loss value;
；
wherein, For brake wear data,/>For brake pad wear data,/>For brake fluid pressure loss data,/>Tire wear data; /(I)Is a regression model parameter,/>，/>，/>，/>For the weight factors of the respective input features, iteratively solving from historical data; /(I)Is an error term;
the error term The calculation formula of (2) is as follows:
；
Wherein i is a parameter; m is the number of weight factor samples; optimizing error terms The calculation of the error term is minimized;
Obtaining current vehicle safety hardware data, substituting the current vehicle safety hardware data into a linear regression model for predicting the brake performance loss value, and calculating to obtain the loss value And substituting the non-loss brake hardware data to obtain the parameter value/>Will/>And/>Fitting, if:
；
the brake hardware accords with the safety standard, the performance loss of the safety hardware is in the standard range, and if:
；
The brake hardware does not accord with the safety standard, the loss of the safety hardware is not in the range, and the maintenance is needed;
substituting the loss value obtained by the linear regression model into the current brake hardware data; /(I) Substituting the lossless brake hardware data into a parameter value obtained by a linear regression model;
wherein, For the standard braking distance,/>Is the minimum braking distance,/>Is the maximum braking distance.
2. A transportation security pre-management method as defined in claim 1, wherein: the vehicle detection catalog includes vehicle appearance detection, mechanical system detection, electrical system detection, and in-vehicle device consumption detection.
3. A transportation security pre-management method as defined in claim 2, wherein: when the safety hardware performance is determined to be normal, a driver checks the vehicle according to the vehicle detection catalog, if the problem is detected, the driver contacts the vehicle detection center for maintenance, and the vehicle is detected after the maintenance; when the vehicle does not detect the problem, filling in an evaluation result of normal operation of the vehicle through a driver terminal;
The front safety management platform checks whether the assessment result transmitted by the driver has a vehicle missing detection phenomenon or not, generates an approval report for the transport vehicle with normal assessment result, and transmits the approval report to the driver;
and the driver confirms the vehicle detection approval report at the terminal, and drives the vehicle to enter a transportation flow after the confirmation is completed.
4. A system employing a transportation security pre-management method according to any one of claims 1-3, characterized in that: the system comprises a front safety management module, a loss prediction module, a flow detection module, an approval module and a transportation execution module;
the front-end security management module: a front safety management platform of the freight vehicle is established, the front safety management platform comprises a driver terminal and a server, and a vehicle detection catalog is imported into the server;
The loss prediction module: collecting vehicle safety hardware data, establishing a linear regression model, and predicting vehicle safety hardware performance loss;
The flow detection module is used for: based on the predicted performance loss of the vehicle safety hardware, the front-end safety management platform arranges a vehicle maintenance center to inspect and repair the vehicle safety hardware with serious performance loss;
The approval module is used for: after the inspection and repair of the vehicle are completed, the driver evaluates the repaired vehicle safety hardware, inspects the repaired vehicle safety hardware according to other vehicle detection catalogues, transmits an evaluation result to a front safety management platform at a driver terminal, checks the evaluation result transmitted by the driver by the front safety management platform, generates an approval report for the transportation vehicle with a normal evaluation result, and transmits the approval report to the driver;
The transport execution module: after the terminal confirms the approval report, the driver drives the vehicle to enter a transportation flow and execute the transportation task.
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Citations (35)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101751033A (en) * | 2008-12-01 | 2010-06-23 | 北京经纬恒润科技有限公司 | Vehicular remote monitoring and diagnosing system and method |
| CN105372712A (en) * | 2014-09-02 | 2016-03-02 | 清华大学 | Vehicle inspection method and system |
| CN106131126A (en) * | 2016-06-23 | 2016-11-16 | 广州亿程交通信息有限公司 | Vehicle management system based on car networking cloud platform service |
| CN106249307A (en) * | 2016-07-22 | 2016-12-21 | 同方威视技术股份有限公司 | Safety detection method and system |
| CN106444716A (en) * | 2016-11-02 | 2017-02-22 | 深圳市元征软件开发有限公司 | Vehicle fault diagnosis and maintenance method, server and maintenance center |
| CN106779496A (en) * | 2017-01-24 | 2017-05-31 | 湖南晶威科技有限公司 | A kind of car for public affairs management method and management system based on internet |
| CN206938738U (en) * | 2017-07-03 | 2018-01-30 | 江苏金坛绿能新能源科技有限公司 | A kind of automobile brake sheet detection means |
| CN107908174A (en) * | 2017-11-08 | 2018-04-13 | 巨化集团公司汽车运输有限公司 | Vehicle maintenance Maintenance Scheduling management method and system |
| CN108549354A (en) * | 2018-03-14 | 2018-09-18 | 斑马网络技术有限公司 | Vehicle failure maintenance system and its breakdown maintenance method |
| CN207908959U (en) * | 2017-11-08 | 2018-09-25 | 巨化集团公司汽车运输有限公司 | Vehicle maintenance Maintenance Scheduling manages system |
| CN109801397A (en) * | 2018-12-28 | 2019-05-24 | 施帆 | A kind of car-mounted terminal and information interacting method based on information sharing |
| CN110149334A (en) * | 2019-05-23 | 2019-08-20 | 浙江吉利控股集团有限公司 | Vehicle management system |
| CN110254354A (en) * | 2019-07-16 | 2019-09-20 | 深圳市元征科技股份有限公司 | A kind of vehicle and its vehicle safety starting method and relevant device |
| CN111062089A (en) * | 2019-11-27 | 2020-04-24 | 厦门金龙联合汽车工业有限公司 | Brake effect evaluation method, terminal device and storage medium |
| CN111652388A (en) * | 2020-05-28 | 2020-09-11 | 三一汽车制造有限公司 | Method for prompting maintenance of work vehicle, terminal, work vehicle and maintenance system |
| CN112435465A (en) * | 2020-10-23 | 2021-03-02 | 贾雨欣 | Key vehicle management system and method |
| CN112668786A (en) * | 2020-12-30 | 2021-04-16 | 神华信息技术有限公司 | Mine car safety assessment prediction method, terminal equipment and storage medium |
| CN113222187A (en) * | 2021-04-15 | 2021-08-06 | 中通服咨询设计研究院有限公司 | Intelligent monitoring method for brake health degree of shared moped |
| CN113344490A (en) * | 2021-05-31 | 2021-09-03 | 杭州拼便宜网络科技有限公司 | Cargo midway management method and system, computer equipment and storage medium |
| CN113511213A (en) * | 2020-03-26 | 2021-10-19 | 英特尔公司 | Safety system for a vehicle |
| CN113752993A (en) * | 2021-11-09 | 2021-12-07 | 杭州智科精密机械有限公司 | Disc type braking device for kinetic energy conversion of new energy automobile |
| CN113886846A (en) * | 2021-09-10 | 2022-01-04 | 阿波罗智联(北京)科技有限公司 | Security check method and device |
| CN114104334A (en) * | 2021-12-09 | 2022-03-01 | 中国民航大学 | Airplane inspection method based on automatic image recognition mode of moving trolley |
| CN114120472A (en) * | 2021-11-23 | 2022-03-01 | 安雪斌 | Automatic driving vehicle safety management system |
| CN114435428A (en) * | 2022-02-25 | 2022-05-06 | 北京全路通信信号研究设计院集团有限公司 | Train braking curve determining method and device and train control method and system |
| CN114446076A (en) * | 2022-03-14 | 2022-05-06 | 广州公评科技有限公司 | Intelligent scheduling control system based on 5G communication technology |
| CN114527729A (en) * | 2022-02-21 | 2022-05-24 | 重庆长安汽车股份有限公司 | Vehicle health state remote monitoring system and method based on cloud platform |
| CN114684541A (en) * | 2020-12-31 | 2022-07-01 | 同方威视技术股份有限公司 | Vehicle transport system for safety check |
| CN115699050A (en) * | 2019-11-05 | 2023-02-03 | 强力价值链网络投资组合2019有限公司 | Value chain network control tower and enterprise management platform |
| CN115817471A (en) * | 2022-12-05 | 2023-03-21 | 吉林大学 | Safe distance calculation method of intelligent networked automobile self-adaptive cruise control system |
| CN116341897A (en) * | 2023-01-31 | 2023-06-27 | 浪潮通信技术有限公司 | Vehicle safety supervision method, device, equipment and storage medium |
| CN116872881A (en) * | 2023-08-09 | 2023-10-13 | 清华大学 | Active and passive safety cooperative control method and device for pedestrians and computer equipment |
| CN116911610A (en) * | 2023-07-20 | 2023-10-20 | 上海钢联物流股份有限公司 | Method and system for monitoring, evaluating and early warning of driving safety risk of transport vehicle |
| CN116956044A (en) * | 2023-08-01 | 2023-10-27 | 北京大示示粒科技有限公司 | Automatic driving vehicle and performance evaluation method and system thereof |
| CN117612387A (en) * | 2023-11-27 | 2024-02-27 | 浙江盛暄电力科技有限公司 | Intelligent tunnel and pipe gallery comprehensive monitoring system and monitoring method |
-
2024
- 2024-01-30 CN CN202410123927.8A patent/CN117649213B/en active Active
Patent Citations (35)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101751033A (en) * | 2008-12-01 | 2010-06-23 | 北京经纬恒润科技有限公司 | Vehicular remote monitoring and diagnosing system and method |
| CN105372712A (en) * | 2014-09-02 | 2016-03-02 | 清华大学 | Vehicle inspection method and system |
| CN106131126A (en) * | 2016-06-23 | 2016-11-16 | 广州亿程交通信息有限公司 | Vehicle management system based on car networking cloud platform service |
| CN106249307A (en) * | 2016-07-22 | 2016-12-21 | 同方威视技术股份有限公司 | Safety detection method and system |
| CN106444716A (en) * | 2016-11-02 | 2017-02-22 | 深圳市元征软件开发有限公司 | Vehicle fault diagnosis and maintenance method, server and maintenance center |
| CN106779496A (en) * | 2017-01-24 | 2017-05-31 | 湖南晶威科技有限公司 | A kind of car for public affairs management method and management system based on internet |
| CN206938738U (en) * | 2017-07-03 | 2018-01-30 | 江苏金坛绿能新能源科技有限公司 | A kind of automobile brake sheet detection means |
| CN207908959U (en) * | 2017-11-08 | 2018-09-25 | 巨化集团公司汽车运输有限公司 | Vehicle maintenance Maintenance Scheduling manages system |
| CN107908174A (en) * | 2017-11-08 | 2018-04-13 | 巨化集团公司汽车运输有限公司 | Vehicle maintenance Maintenance Scheduling management method and system |
| CN108549354A (en) * | 2018-03-14 | 2018-09-18 | 斑马网络技术有限公司 | Vehicle failure maintenance system and its breakdown maintenance method |
| CN109801397A (en) * | 2018-12-28 | 2019-05-24 | 施帆 | A kind of car-mounted terminal and information interacting method based on information sharing |
| CN110149334A (en) * | 2019-05-23 | 2019-08-20 | 浙江吉利控股集团有限公司 | Vehicle management system |
| CN110254354A (en) * | 2019-07-16 | 2019-09-20 | 深圳市元征科技股份有限公司 | A kind of vehicle and its vehicle safety starting method and relevant device |
| CN115699050A (en) * | 2019-11-05 | 2023-02-03 | 强力价值链网络投资组合2019有限公司 | Value chain network control tower and enterprise management platform |
| CN111062089A (en) * | 2019-11-27 | 2020-04-24 | 厦门金龙联合汽车工业有限公司 | Brake effect evaluation method, terminal device and storage medium |
| CN113511213A (en) * | 2020-03-26 | 2021-10-19 | 英特尔公司 | Safety system for a vehicle |
| CN111652388A (en) * | 2020-05-28 | 2020-09-11 | 三一汽车制造有限公司 | Method for prompting maintenance of work vehicle, terminal, work vehicle and maintenance system |
| CN112435465A (en) * | 2020-10-23 | 2021-03-02 | 贾雨欣 | Key vehicle management system and method |
| CN112668786A (en) * | 2020-12-30 | 2021-04-16 | 神华信息技术有限公司 | Mine car safety assessment prediction method, terminal equipment and storage medium |
| CN114684541A (en) * | 2020-12-31 | 2022-07-01 | 同方威视技术股份有限公司 | Vehicle transport system for safety check |
| CN113222187A (en) * | 2021-04-15 | 2021-08-06 | 中通服咨询设计研究院有限公司 | Intelligent monitoring method for brake health degree of shared moped |
| CN113344490A (en) * | 2021-05-31 | 2021-09-03 | 杭州拼便宜网络科技有限公司 | Cargo midway management method and system, computer equipment and storage medium |
| CN113886846A (en) * | 2021-09-10 | 2022-01-04 | 阿波罗智联(北京)科技有限公司 | Security check method and device |
| CN113752993A (en) * | 2021-11-09 | 2021-12-07 | 杭州智科精密机械有限公司 | Disc type braking device for kinetic energy conversion of new energy automobile |
| CN114120472A (en) * | 2021-11-23 | 2022-03-01 | 安雪斌 | Automatic driving vehicle safety management system |
| CN114104334A (en) * | 2021-12-09 | 2022-03-01 | 中国民航大学 | Airplane inspection method based on automatic image recognition mode of moving trolley |
| CN114527729A (en) * | 2022-02-21 | 2022-05-24 | 重庆长安汽车股份有限公司 | Vehicle health state remote monitoring system and method based on cloud platform |
| CN114435428A (en) * | 2022-02-25 | 2022-05-06 | 北京全路通信信号研究设计院集团有限公司 | Train braking curve determining method and device and train control method and system |
| CN114446076A (en) * | 2022-03-14 | 2022-05-06 | 广州公评科技有限公司 | Intelligent scheduling control system based on 5G communication technology |
| CN115817471A (en) * | 2022-12-05 | 2023-03-21 | 吉林大学 | Safe distance calculation method of intelligent networked automobile self-adaptive cruise control system |
| CN116341897A (en) * | 2023-01-31 | 2023-06-27 | 浪潮通信技术有限公司 | Vehicle safety supervision method, device, equipment and storage medium |
| CN116911610A (en) * | 2023-07-20 | 2023-10-20 | 上海钢联物流股份有限公司 | Method and system for monitoring, evaluating and early warning of driving safety risk of transport vehicle |
| CN116956044A (en) * | 2023-08-01 | 2023-10-27 | 北京大示示粒科技有限公司 | Automatic driving vehicle and performance evaluation method and system thereof |
| CN116872881A (en) * | 2023-08-09 | 2023-10-13 | 清华大学 | Active and passive safety cooperative control method and device for pedestrians and computer equipment |
| CN117612387A (en) * | 2023-11-27 | 2024-02-27 | 浙江盛暄电力科技有限公司 | Intelligent tunnel and pipe gallery comprehensive monitoring system and monitoring method |
Non-Patent Citations (1)
| Title |
|---|
| 适用于对多种车辆进行快速安全检查系统的实现;孙尚民;;电子测量与仪器学报;20180815(第08期);第129-136页 * |
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