Early bearing fault diagnosis based on improved SFLA and ELM network
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Post-publication record
- Nature
- Retraction
- Reason
- Author Unresponsive;False/Forged Authorship;
- Date
- 3/11/2019 0:00
- Flagged by OpenAlex?
- Yes
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement — it reports them as false, which reads as “fine”.
Abstract
In this paper, an extreme learning machine (ELM) network based on an improved shuffled frog leaping algorithm (CCSFLA) is applied in early bearing fault diagnosis. ELM is a new type of single layer forward network. Although the generalization is stronger compared with traditional neural networks, a random setup of initial parameters increases instability of the network. An improved SFLA based on sinusoidal chaotic mapping with infinite collapses and constriction factors (CCSFLA) is proposed in this paper to optimize the ELM and obtain a CCSFLA–ELM model. Results show that the CCSFLA–ELM model can be used for optimization and that it improved the recognition of early bearing fault diagnosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
The record
- Venue
- Transactions of the Canadian Society for Mechanical Engineering
- Topic
- Machine Learning and ELM
- Field
- Computer Science
- Canadian institutions
- —
- Funders
- National Natural Science Foundation of China
- Keywords
- Extreme learning machineGeneralizationBearing (navigation)Fault (geology)Artificial neural networkComputer scienceChaoticArtificial intelligenceControl theory (sociology)AlgorithmPattern recognition (psychology)MathematicsGeology
- Has abstract in OpenAlex
- yes