Method for vehicle remote diagnosis and spare parts retrieval

A technology of remote diagnosis and spare parts, applied in the field of information retrieval, can solve problems such as differences in group numbers, and achieve the effect of solving the problem of experience limitations

Active Publication Date: 2019-12-24
DALIAN ROILAND SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] In order to solve the failure of the owner's vehicle, it is necessary to rely on the manual judgment of the technician and the selection of spare parts by the technician; at the same time, because different spare parts have the same main group number, the group number is still different, in order to be able to solve the problem of accurately matching spare parts

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  • Method for vehicle remote diagnosis and spare parts retrieval
  • Method for vehicle remote diagnosis and spare parts retrieval
  • Method for vehicle remote diagnosis and spare parts retrieval

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0014] Embodiment 1: A method for vehicle remote diagnosis and spare parts retrieval: such as figure 1 shown, including the following steps:

[0015] Step 1. Collect vehicle information data;

[0016] Step 2. Analyze the vehicle VIN code to obtain variables, the variables include the engine displacement, body type, and engine gearbox type obtained by the VIN code analysis; through the vehicle chassis number (17-digit VIN code), translate each number to represent Relevant information (variables) to form a rich data knowledge base, such as the translation rules for each number of a vehicle with a chassis number of LFV5A14B8Y3000001 such as figure 2 shown.

[0017] Step 3. Perform a decision tree analysis on the spare part codes corresponding to the variables, complete the classification of variable data to form spare part information, and establish an index to form a diagnostic knowledge base;

[0018] Step 4. For the historical vehicle fault data, count and record the work ...

Embodiment 2

[0022] Embodiment 2: have the technical scheme identical with embodiment 1, more specifically:

[0023] In the step 3, the historical records of the maintenance spare parts table are used as the data basis, and the spare parts are classified through the decision tree model, and the maintenance spare parts table sample is shown in Table 1:

[0024] Table I

[0025] VIN123 VIN4 VIN6 VIN78 BJDM LFV 5 1 4B 06J115403J LFV 3 2 8K LN052167A21 LFV 4 2 4F LN052167A24

[0026] The basic principles of the decision tree model are as follows:

[0027] First: Determine the entropy of different categories of spare parts in each dimension. Taking VIN4 as an example, the entropy is defined as

[0028] E=sum(-p(I)*log(p(I)))

[0029] Wherein I=1:N (N category results, such as this example 1, that is, the spare part belongs to this model, so the probability P(I)=1)

[0030] Then E(5)=-(1 / 1) Log2(1 / 1)-(0 / 1) Log2(0 / 1)=0+0=0

[0031] E(3)=-(1...

Embodiment 3

[0050] Embodiment 3: have the technical scheme identical with embodiment 1 or 2, more specifically:

[0051] In the fourth step, using variance analysis to simulate the technician's diagnostic thinking, the steps to obtain the best solution under the fault code are:

[0052] (1) According to the personal experience and different ways of thinking of different technicians, check the solutions given by each fault description and the information of the work items and spare parts used;

[0053] (2) Quantify the diagnostic data given by all technicians;

[0054] (3) Then use analysis of variance to compare, and compare the difference between the answers between the two;

[0055] (4) According to the difference results, the solution with the smallest difference is selected as the final solution of the fault code.

[0056] Through the above methods, a relatively complete data knowledge base is formed from fault code → solution → spare parts information.

[0057] In this embodiment,...

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Abstract

Provided is a method for remote diagnoses of cars and retrieval of spare parts, pertaining to the field of information retrieval. Due to the fact that different spare parts are in the same main group number, group numbers differ. In order to precisely match spare parts, the technical key points comprise following steps: collecting car information data; analyzing car VIN codes for obtaining variables; analyzing spare part codes corresponding to variables by using decision-making trees; counting and recording historical car fault data to a same fault code and forming a diagnostic database in the way that different technicians solve tools and spare part information used by car fault; correlating the diagnostic database to a diagnostic knowledge base and establishing major keys; and retrieving fault codes generated by car fault through keywords and obtaining tools and spare part information. The method for remote diagnoses of cars and retrieval of spare parts has following beneficial effects: after fault codes are acquired, a solution scheme for common faults and corresponding spare parts and tools can be quickly found.

Description

technical field [0001] The invention belongs to the field of information retrieval and relates to a method for vehicle remote diagnosis and spare part retrieval. Background technique [0002] At present, my country's automobile maintenance industry has developed from the stage of diagnosis based entirely on the feeling and practical experience of inspectors to the stage of comprehensive detection and diagnosis using special equipment. However, there are many problems in the traditional automobile maintenance industry, such as the technical aging of maintenance workers. , It is often impossible to quickly and economically use various technical forces to solve the fault; with the increasing number of automobiles, various services in the automobile aftermarket have sprung up like mushrooms after rain. So from the perspective of the car owner, how can we better and more comprehensively understand the car condition, how to quickly obtain the car’s pending solution and the required...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/901G06F16/903G06N5/02G06Q10/00
CPCG06F16/901G06F16/903G06N5/022G06N5/027G06Q10/20
Inventor 田雨农初莹莹
Owner DALIAN ROILAND SCI & TECH CO LTD
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