Research on Ultra-precision Technology for Fault Law and Operation Trend Prediction of Machinery and Equipment

Jinghua Yu

2019

Abstract

Mechanical equipment is the key to ensure industrial production, which determines whether industrial production links can operate efficiently and continuously, but the occurrence of mechanical failure is an important factor hindering its stable operation. Therefore, accurate diagnosis and prediction of mechanical faults has become a hot research topic in the field of industrial production. In this paper, a fault diagnosis and operation trend prediction model of mechanical equipment will be established by combining vector regression and full vector technology. Compared with the traditional time domain model, the model built in this paper mainly uses spectrum structure to predict the model. Finally, this paper establishes the prediction model of fault operation trend based on gear trend development. The results show that the prediction model proposed in this paper can realize the prediction of gear fault trend development.

Paper Citation

in Harvard Style

Yu J. (2019). Research on Ultra-precision Technology for Fault Law and Operation Trend Prediction of Machinery and Equipment.In Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering - Volume 1: ICVMEE, ISBN 978-989-758-412-1, pages 139-143. DOI: 10.5220/0008386301390143

in Bibtex Style

@conference{icvmee19,
author={Jinghua Yu},
title={Research on Ultra-precision Technology for Fault Law and Operation Trend Prediction of Machinery and Equipment},
booktitle={Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering - Volume 1: ICVMEE,},
year={2019},
pages={139-143},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008386301390143},
isbn={978-989-758-412-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of 5th International Conference on Vehicle, Mechanical and Electrical Engineering - Volume 1: ICVMEE,
TI - Research on Ultra-precision Technology for Fault Law and Operation Trend Prediction of Machinery and Equipment
SN - 978-989-758-412-1
AU - Yu J.
PY - 2019
SP - 139
EP - 143
DO - 10.5220/0008386301390143