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FP-Tree sequential pattern mining-based fault diagnosis and valuation platform

A technology of sequential pattern mining and fault diagnosis, applied in the field of fault diagnosis and evaluation platform, can solve the problems of increasing processing difficulty, complicated and time-consuming vehicle fault diagnosis methods, and lack of unified standards.

Active Publication Date: 2016-11-09
DALIAN ROILAND SCI & TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, the current vehicle fault diagnosis method is tedious and time-consuming. Car maintenance workers basically rely on experience to judge equipment faults, and give the spare part number, spare part name and spare part price, which is highly subjective and lacks a unified standard.
Especially for multiple vehicle faults in parallel, the processing difficulty is increased, time-consuming and labor-intensive

Method used

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  • FP-Tree sequential pattern mining-based fault diagnosis and valuation platform
  • FP-Tree sequential pattern mining-based fault diagnosis and valuation platform
  • FP-Tree sequential pattern mining-based fault diagnosis and valuation platform

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0022] The corresponding relationship module includes a transaction database module and an application module. According to the transaction database, use FP-Tree, a compact data structure to store and search frequent item sets, mine association rules, and extract possible items of faults and spare parts according to confidence and support. set, namely:

[0023] Input: transaction database D (the connection relationship between fault codes and replacement parts) and the minimum support threshold minσ;

[0024] Output: FP-tree corresponding to transaction database D.

[0025] 1. Scan the DTC-spare parts transaction database D to obtain all frequent item sets F1 contained in the DTC-spare parts transaction database D and their respective support degrees. The frequent items in F1 are sorted in descending order of their support to get L.

[0026] The transaction database is as follows, each row represents a possible relationship between a fault code and replacement spare parts: ...

Embodiment 2

[0055] The topology search module includes a classification module and an identification module; the classification module classifies the spare parts according to the construction rules of the spare part code;

[0056] Classify spare parts according to the construction rules of the spare part code, as follows:

[0057] 1 (engine): engine assembly, cylinder block, cylinder head, piston, connecting rod, connecting parts, engine bracket, fast fasteners for bracket, fuel injection such as intake pipe, air flow meter, etc.;

[0058] 2 (fuel, exhaust, air conditioning cooling): fuel tanks, exhaust pipes, air conditioning refrigeration systems, etc.;

[0059] 3 (gearbox): gearbox assembly and internal components;

[0060] 4 (front axle, steering device): front wheel drive differential, steering system (steering gear), front shock absorber, etc.;

[0061] 5 (rear axle): rear axle, rear wheel drive differential, rear shock absorber, such as rear axle, rear wheel bearings, etc.;

[0...

Embodiment 3

[0079] The solution module includes the spare parts-maintenance item database module and the spare parts-maintenance item FP-Tree module;

[0080] Scan the database module of spare parts-maintenance work items to obtain the frequent item set F2 of spare parts and maintenance work items; arrange the frequent items in F2 in descending order of their support to obtain L'; the spare parts-maintenance work item FP-Tree module is created by The root node of the FP-Tree is marked with "null", and the database is re-arranged, and each record in the database is arranged in the order of L' to generate an FP-Tree; all frequent patterns are found from the FP-Tree, and spare parts and Corresponding relationship of maintenance work items.

[0081] By combining the above methods to find the corresponding relationship between faults and spare parts, a complete solution for fault codes corresponding to spare parts and work items is obtained.

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Abstract

The invention discloses an FP-Tree sequential pattern mining-based fault diagnosis and valuation platform. The platform comprises a corresponding relationship module, a topologic search module and a solution module, wherein the corresponding relationship module creates a frequent item set of a corresponding relationship between a fault code and a replacement spare part through an FP-Tree algorithm according to a transactional database; the topologic search module performs a topologic search by utilizing a topologic relationship between the position of the spare part and an ECU position where a fault is located, and selects the frequent item set; and the solution module obtains a complete solution of the spare part corresponding to the fault code and a repair item according to a corresponding relationship established by the spare part and the repair item. According to the diagnosis and valuation platform, the corresponding relationship is searched for through the frequent item set algorithm FP-Tree and the sequential pattern mining algorithm; the two algorithms are fused for use; the platform is suitable for the possibility of parallel solving of multiple faults in addition to a single fault; the spare part needed to be repaired and the item are judged by remotely estimating the fault code of the vehicle; the complete solution is provided; and a reference is provided for vehicle repair.

Description

technical field [0001] The present invention relates to the field of fault diagnosis, in particular to exploring the association relationship between fault codes, spare parts and work items through FP-Tree sequence pattern mining association algorithm, more specifically, a fault diagnosis and evaluation platform based on FP-Tree sequence pattern mining. Background technique [0002] In the prior art, automobile maintenance workers grasp the fault situation by reading the fault code in the diagnostic report generated by the vehicle diagnostic instrument, confirm the fault location that causes the fault situation through the service manual or combined with maintenance experience, and provide a maintenance plan, that is, the fault code The rough relationship with the replacement spare parts, and then the service consultant will give the work item bill. Therefore, the current vehicle fault diagnosis method is tedious and time-consuming. Car maintenance workers basically rely on ...

Claims

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Application Information

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IPC IPC(8): G06Q10/00G06F17/30
CPCG06F16/2465G06Q10/20
Inventor 田雨农宋安琪
Owner DALIAN ROILAND SCI & TECH CO LTD
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