Dimensionality reduce-based for remaining useful life prediction of machining tools with multisensor fusion

Yongmeng Zhu, Jiechang Wu, Jun Wu and Shuyong Liu

Reliability Engineering and System Safety, 2022, vol. 218, issue PB

Abstract: The remaining useful life (RUL) prediction has received increasing research attention in recent years due to its essential role in improving industrial manufacturing systems' productivity and reliability. High dimensionality time-series data is collected during the system's operating time with the implementation of various sensors. To monitor the machining tool's RUL, a novel multisensor fusion method based on t-SNE-DBSCAN dimensionality reduction is proposed in this paper to aggregate the multiple sensor measurements into a healthy indication that represents the RUL. The robust MCD-Estimator is used to denoise multidimensional sensor data, flag the outliers, and enhance the robustness of the denoising process. The high dimensional statistical features are extracted, and the dimensionality is reduced with t-distributed Stochastic Neighbor Embedding (t-SNE) according to the RUL labels, and optimum features selected by Density-Based Spatial Clustering of Application with Noise algorithm (DBSCAN). Ultimately, Long Short-Term Memory (LSTM) is adopted for RUL estimation with multisensor fusion. A case study with a practical application of the proposed approach, which can be demonstrated, is compared with state-of-the-art methods by evaluating its performance and migration capability in different working conditions.

Keywords: Machining tool; Multisensor fusion; Dimensionality reduction; Remaining useful life prediction; Long short-term memory network (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0951832021006633
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:218:y:2022:i:pb:s0951832021006633

DOI: 10.1016/j.ress.2021.108179

Access Statistics for this article

Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares

More articles in Reliability Engineering and System Safety from Elsevier
Bibliographic data for series maintained by Catherine Liu ().