Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Data-mining-based engineering vehicle fault prediction system and prediction method

A technology for fault prediction and engineering vehicles, which is applied in the direction of test/monitoring control system, general control system, control/regulation system, etc. It can solve problems such as vehicle failure and engineering impact, achieve efficient and fast fault prediction methods, and reduce execution the effect of time

Inactive Publication Date: 2018-12-07
TIANZE INFORMATION IND
View PDF8 Cites 11 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Due to long-time work and other reasons, these engineering vehicles are prone to breakdowns, and once a breakdown occurs, factors such as consignment, maintenance, and work delays will also have a greater impact on the entire project

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Data-mining-based engineering vehicle fault prediction system and prediction method
  • Data-mining-based engineering vehicle fault prediction system and prediction method
  • Data-mining-based engineering vehicle fault prediction system and prediction method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0046] The present invention will be further described below through embodiments in conjunction with the accompanying drawings.

[0047] refer to figure 1 , a fault prediction system for engineering vehicles based on data mining, including the module of mining fault-related frequent itemsets, establishing a decision forest module, and fault prediction module connected in sequence; the module of mining fault-related frequent itemsets includes a data preprocessing part and a frequent itemset acquisition part ; The decision forest building module includes the data reprocessing part and the decision tree building part; the fault prediction module includes the voting classifier part and the result output part.

[0048] The fault prediction method of this system includes the following steps:

[0049] 1) Preprocess the basic data of engineering vehicles by mining fault-related frequent itemset modules to obtain attributes of faulty vehicles; the basic data includes engineering vehic...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention, which belongs to the intersection field of data mining and engineering application, provides a data-mining-based engineering vehicle fault prediction system and prediction method. The fault prediction system comprises a mining fault-related frequent item set module, a decision-making forest establishment module, and a fault prediction module that are connected successively. The mining fault-related frequent item set module preprocesses basic data of an engineering vehicle to obtain a faulty vehicle attribute and acquires a frequent item set through the faulty vehicle attribute;the decision-making forest establishment module carries out data reprocessing, constructs a training set, and forms a decision-making tree and a corresponding decision-making forest and the fault prediction module carries out classification prediction on a fault risk of the engineering vehicle and outputs a result. Therefore, a rule relates to a fault is obtained from lots of irregular engineeringvehicle working condition information; a possible fault is predicted by using the existing engineering vehicle working condition information effectively; and the prediction method is one with fast operation and high efficiency.

Description

technical field [0001] The invention belongs to the intersecting field of data mining and engineering application, and relates to a data mining-based engineering vehicle failure prediction system and a prediction method thereof. Background technique [0002] In real life, a large number of engineering vehicles are needed in various mines and construction sites. Due to long-time work and other reasons, these engineering vehicles are prone to breakdowns, and once a breakdown occurs, factors such as consignment, maintenance, and work delays will also have a greater impact on the entire project. In order to reduce the failure rate of engineering vehicles and thereby reduce engineering losses, there is a great demand to dig out the hidden relationship between the working conditions and faults of engineering vehicles through data mining algorithms, so as to make correct predictions for the state of engineering vehicles. [0003] There are two main requirements for engineering veh...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Applications(China)
IPC IPC(8): G05B23/02
CPCG05B23/0243G05B2219/24065
Inventor 孙杰李鹏飞戴华陈智也
Owner TIANZE INFORMATION IND
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com