Yongzhi Qu

Orcid: 0000-0002-5314-023X

According to our database1, Yongzhi Qu authored at least 12 papers between 2014 and 2022.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2022
Development of Deep Residual Neural Networks for Gear Pitting Fault Diagnosis Using Bayesian Optimization.
IEEE Trans. Instrum. Meas., 2022

2020
Unsupervised rotating machinery fault diagnosis method based on integrated SAE-DBN and a binary processor.
J. Intell. Manuf., 2020

2019
The Detection of the Pipe Crack Utilizing the Operational Modal Strain Identified from Fiber Bragg Grating.
Sensors, 2019

A Novel Method for Early Gear Pitting Fault Diagnosis Using Stacked SAE and GBRBM.
Sensors, 2019

An FBG based smart clamp fabricated by 3D printing technology and its application to incipient clamp looseness detection.
Proceedings of the 2019 IEEE International Conference on Prognostics and Health Management, 2019

2018
Dynamic Modeling and Fault Feature Analysis of Pitted Gear System.
Proceedings of the 2018 IEEE International Conference on Prognostics and Health Management, 2018

On research of incipient gear pitting fault detection using optic fiber sensors.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2018

Gear pitting fault diagnosis using disentangled features from unsupervised deep learning.
Proceedings of the IEEE International Instrumentation and Measurement Technology Conference, 2018

2017
Collective Geographical Embedding for Geolocating Social Network Users.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2017

Deep and Broad Learning on Content-Aware POI Recommendation.
Proceedings of the 3rd IEEE International Conference on Collaboration and Internet Computing, 2017

2015
A Fiber Bragg Grating Sensing Based Triaxial Vibration Sensor.
Sensors, 2015

2014
Gearbox Tooth Cut Fault Diagnostics Using Acoustic Emission and Vibration Sensors - A Comparative Study.
Sensors, 2014


  Loading...