Automobile fault and early warning sorting processing method
By establishing a car fault warning and alarm model algorithm, massive data are extracted and sorted, and the car fault and early warning clues are identified, the problem of difficulty in identifying car fault warning and fault alarm is solved, accurate warning and alarm services are achieved, and fault data is improved Management efficiency.
Patent Information
- Application Number
- CN202411543387.5
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-31
- Publication Date
- 2025-02-14
AI Technical Summary
It is difficult to identify automobile fault warning and fault alarms, and it is difficult to provide accurate warning and alarm services in existing technologies, resulting in unclear responsibilities for fault data, difficult identification and analysis technology, and every additional large customer needs to be redeveloped, and resources are wasted.
Establish a car failure warning and alarm model algorithm, identify car failure and warning clues through massive data refining and sorting, store them in the sorting center, use business algorithms and data governance for analysis, and finally send them in real time and reach customers.
It realizes accurate identification and sorting of car failure and early warning information, improves the clarity of responsibilities of fault data and the efficiency of identification and analysis, reduces resource waste, and provides accurate early warning and alarm services.
Smart Images
Figure CN119445696A_ABST
Abstract
Description
Technical Field
[0001] The invention belongs to the field of automobile intelligent control, and in particular relates to an automobile fault and early warning sorting and processing method. Background Art
[0002] It is difficult to identify automobile fault warnings and fault alarms. The definition of warning and alarm algorithms is not clear, making it difficult to provide accurate warning and alarm services for automobile manufacturers and users. With the increase of Internet of Vehicles data and high-frequency data, there is no clear fault storage and management of fault source data, resulting in unclear responsibilities for fault data and high technical difficulty in fault identification and analysis. At the same time, each additional major customer requires redevelopment, which wastes resources. There is no sorting center, and the functional responsibilities are not clear, resulting in a lack of business focus, repeated processing of fault data, and repeated docking. Summary of the invention
[0003] In order to solve the above problems, the present invention provides a method for sorting and processing automobile faults and warnings. A set of automobile fault warning and alarm model algorithms, storage and sorting centers are established to extract, identify, and calculate from massive data, accurately find automobile faults and automobile warning clues, and store them in the sorting center. The sorting center uses business algorithms, analysis and data management to sort and process the faults, and finally sends them in real time and reaches customers. The specific technical solution is as follows: A method for sorting and processing automobile faults and early warnings, the method comprising the following steps: Step (1) accessing massive vehicle condition source data of the Internet of Vehicles; Step (2) Create an automobile fault data service for key customers, generate a TOPIC for each key customer, and use it to store fault data; decouple and asynchronously process the data to improve overall performance and form a usable fault service system; Step (3) Add vehicle groups, sort the primary algorithm based on Flink sorting, and select the vehicle fault alarm model algorithm and the vehicle fault early warning model algorithm; Step (4) Confirm the car fault alarm and warning clues, set up the https topic, Kafka topic and Datahub topic for each major customer; extract the massive data and sort it into the TOPIC of each major customer; Step (5) The sorting center stores and manages fault and warning clues; consumes TOPICs through the sorting center microservice, distributes clues in real time and reaches the client.
[0004] The present invention uses a fault and warning algorithm to salvage automobile fault and warning data from the massive data reported by the automobile, controls the warning threshold, establishes an automobile fault model, establishes a warning model, and then uses the model algorithm to sort out useful automobile fault alarms and automobile warning information, reports them for storage in a sorting center, and the sorting center redistributes them to multiple users according to the automobile business attributes. BRIEF DESCRIPTION OF THE DRAWINGS
[0005] Figure 1 Schematic diagram of the process of the present invention; Figure 2 Schematic diagram of the key customer request and feedback process of the present invention. DETAILED DESCRIPTION
[0006] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.
[0007] A method for sorting and processing automobile faults and early warnings, the method comprising the following steps: Step (1) accessing massive vehicle condition source data of the Internet of Vehicles; Step (2) Create an automobile fault data service for key customers, generate a TOPIC for each key customer, and use it to store fault data; decouple and asynchronously process the data to improve overall performance and form a usable fault service system; Step (3) Add vehicle groups, sort the primary algorithm based on Flink sorting, and select the vehicle fault alarm model algorithm and the vehicle fault early warning model algorithm; Step (4) Confirm the car fault alarm and warning clues, set up the https topic, Kafka topic and Datahub topic for each major customer; extract the massive data and sort it into the TOPIC of each major customer; Step (5) The sorting center stores and manages fault and warning clues; consumes TOPICs through the sorting center microservice, distributes clues in real time and reaches the client.
[0008] The specific process is shown as follows Figure 1 and 2 shown.
[0009] The above describes in detail the preferred implementation of this patent, but this patent is not limited to the above implementation. Various changes can be made within the knowledge scope of ordinary technicians in this field without departing from the purpose of this patent.
Claims
1. A method for sorting and processing automobile failures and early warnings, characterized in that: The method comprises the following steps: Step (1) accessing massive vehicle condition source data of the Internet of Vehicles; Step (2) Create an automobile fault data service for key customers, generate a TOPIC for each key customer, and use it to store fault data; decouple and asynchronously process the data to improve overall performance and form a usable fault service system; Step (3) Add vehicle groups, sort the primary algorithm based on Flink sorting, and select the vehicle fault alarm model algorithm and the vehicle fault early warning model algorithm; Step (4) Confirm the car fault alarm and warning clues, set up the httpstopic, Kafka topic and Datahub topic for each major customer; extract the massive data and sort it into the TOPIC of each major customer; Step (5) The sorting center stores and manages fault and warning clues; consumes TOPICs through the sorting center microservice, distributes clues in real time and reaches the client.