Fault prediction and health management method applied to automatic production line

An automated production line and health management technology, applied in neural learning methods, general control systems, biological neural network models, etc., to achieve the effects of reducing maintenance costs, protecting property, and reducing the probability of occurrence

Inactive Publication Date: 2018-03-13
SHANGHAI SECOND POLYTECHNIC UNIVERSITY
View PDF4 Cites 27 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

This method is currently mainly used to study the failure mechanism of the bearing equipment in the automated pro...

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
  • Fault prediction and health management method applied to automatic production line
  • Fault prediction and health management method applied to automatic production line
  • Fault prediction and health management method applied to automatic production line

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0037] The present invention is described in detail below in conjunction with accompanying drawing and embodiment

[0038] Such as figure 1 with 2 As shown, the present invention includes: design and trade-off study, FMECA analysis, CBM experiments, data collection, data analysis, algorithm development, execution check and validation. details as follows:

[0039] 1. The main role of design and trade-off research is to find the best or most balanced solution for the diagnosis and prediction of key component / subsystem failure modes in order to achieve the most ideal CBM / PHM.

[0040] 2. FMECA analysis collects previous machine failure data in order to predict failure evolution and plan existing human resources to perform maintenance operations.

[0041] 3. Perform data collection. The operating data of the equipment includes internal data and external parameters: internal data include: equipment operating frequency, error correction times, workload and other data that can be ...

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 belongs to the technical field of automatic production lines, and particularly relates to a fault prediction and health management method applied to an automatic production line. The method comprises the following steps of preparing a plurality of automatic production lines to be tested, carrying out heating aging and vibration testing on the bearing equipment in automatic productionlines to be tested to obtain training data and storing the training data in a database, carrying out FMECA analysis to obtain a training sample, training a neural network by using a particle filtering algorithm and placing into a test chip, monitoring the bearing equipment in the automatic production lines in the working state in real time by using a testing chip, and calculating residual servicelife and conducting health management. The running state of the bearing equipment in an automatic production line can be monitored in real time, and the fault time is predicted. The occurrence probability of sudden faults is reduced, and a plurality of potential safety hazards are avoided when the sudden faults occur, so that properties can be protected, and the maintenance cost is reduced.

Description

technical field [0001] The invention belongs to the technical field of automated production lines, and in particular relates to a fault prediction and health management method applied to automated production lines. Background technique [0002] With the development of science and technology, the integration and complexity of modern automated production line equipment are increasing day by day, and the maintenance cost and difficulty are also rising sharply; the traditional manual maintenance method with low efficiency and high cost is faced with a large number of complex The current automated production line equipment is no longer applicable. The failure prediction and health management system (PHM) aims to reduce the cost of manual maintenance, to analyze the failure model on the automated production line to determine its health status, so that self-assessment and failure warning can be performed in an unattended situation, and at the same time, health Management, repairin...

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
IPC IPC(8): G05B19/418G06N3/08
CPCG05B19/41875G05B2219/31356G06N3/08Y02P90/02
Inventor 何成刘长春武洋
Owner SHANGHAI SECOND POLYTECHNIC UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap