Vehicle Failure-Factor Specifier Using Frequency Distribution Analysis
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing vehicle failure-factor specifying apparatuses lack an efficient method to identify the failure-causing driving state, as they do not provide specific guidance on constructing failure models, leading to inefficiencies in determining the driving conditions that result in vehicle failures.
Innovation Solution
A vehicle failure-factor specifying apparatus that determines the presence of peculiarities in pre-failure driving states by comparing the frequency distribution of driving-state-related values with those of non-failure states, identifying deviations and categorizing them based on specific types of shift control operations, temperature, and other factors to pinpoint the failure-causing driving state.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a failure model is constructed using data mining methods with vehicle data from multiple disabled vehicles, then the failure prediction capability is improved, but the method of constructing the failure model is not specifically described, leading to inefficiency in specifying the failure-causing driving state
Solution Approach 1:
The patent segments the failure analysis process into distinct components: (1) obtaining pre-failure driving state data, (2) determining peculiarity presence through frequency distribution comparison, (3) comparing peculiarities across multiple vehicles, and (4) specifying the failure-causing driving state. This segmentation makes the construction method specific and efficient while maintaining high reliability.
Solution Approach 2:
The patent implements feedback by comparing the frequency distribution of pre-failure driving states with normal driving states, and by comparing peculiarities across multiple vehicles. This feedback mechanism identifies consistent abnormal patterns that reliably indicate failure-causing conditions while improving specification efficiency through systematic comparison.
2Measurement precision
If the frequency distribution of pre-failure driving state is compared with non-failure driving state to determine peculiarity, then the accuracy in identifying failure-causing conditions is improved, but the complexity of data analysis increases
Solution Approach 1:
The patent introduces frequency distribution as an intermediary tool to simplify the comparison between pre-failure and normal driving states. Instead of directly analyzing complex raw data, the system converts data into frequency distributions, making the analysis more manageable while maintaining high measurement precision in identifying peculiarities.
Solution Approach 2:
The patent changes the parameter representation from raw driving state data to frequency distribution parameters. This transformation simplifies the data structure while preserving the essential information needed for accurate peculiarity detection, thereby reducing analysis complexity without sacrificing measurement precision.
3Reliability
If pre-failure data from multiple vehicles is collected and compared to determine common peculiarities, then the reliability of failure-causing state specification is improved, but the time and computational resources required increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing and organizing driving state data into frequency distributions before failure occurrence. This preliminary organization of data from multiple vehicles enables faster comparison and identification of common peculiarities when failures occur, reducing the time and computational resources needed at the critical moment of failure analysis.
Data Source
AI summary
A vehicle failure-factor specifying apparatus includes (a) a peculiarity-presence determining portion configured to determine, based on a pre-failure driving state in a stage prior to occurrence of a certain failure in a vehicle, whether a peculiarity was present or absent in the pre-failure driving state, and (b) a failure-causing-driving state specifying portion configured, when the peculiarity was present in the pre-failure driving state, to determine whether the peculiarity present in the pre-failure driving state of the vehicle is substantially identical with a peculiarity in the pre-failure driving state of other vehicles. The peculiarity-presence determining portion determines whether the peculiarity was present or absent in the pre-failure driving state of the vehicle, depending on whether a frequency distribution of the pre-failure driving state of the vehicle is deviated from a frequency distribution of a non-failure driving state of a plurality of vehicles including the other vehicles in a non-failure case.