Y
Yingchun Chen
Researcher at Beijing University of Technology
Publications - 25
Citations - 68
Yingchun Chen is an academic researcher from Beijing University of Technology. The author has contributed to research in topics: Pipeline (computing) & Signal. The author has an hindex of 3, co-authored 25 publications receiving 28 citations. Previous affiliations of Yingchun Chen include Peking University.
Papers
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Journal ArticleDOI
Non-contact harmonic magnetic field detection for parallel steel pipeline localization and defects recognition
TL;DR: In this article, an orthogonal vector differential focusing array detector was designed, which radiates high-frequency and ultra-low-frequency (ULF) electromagnetic waves to pipeline based on the principle of Frequency Modulated Continuous Wave (FMCW), and records the signals in parallel using high-sensitivity Tunnel Magneto Resistance (TMR) array sensors.
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Model-Based Design Approach to Improve Performance Characteristics of Hydrostatic Bearing Using Multivariable Optimization
Waheed Ur Rehman,Xinhua Wang,Yiqi Cheng,Yingchun Chen,Hasan Shahzad,Hui Chai,Kamil Abbas,Zia Ullah,Marya Kanwal +8 more
TL;DR: A mathematical model-based system for hydrostatic bearings is proposed that helps to improve its static/dynamic characteristics under varying conditions of performance-influencing variables such as temperature, spindle speed, external load, and clearance gap.
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Magnetic anomaly detection of adjacent parallel pipelines using deep learning neural networks
Mikayla Biggs,Tao Sun,Xinhua Wang,Robert De Saro,Junqiang Wang,Xuyun Yang,Tao Meng,Yi Shuai,Yingchun Chen +8 more
TL;DR: In this article, a magnetic anomaly detection method based on deep learning neural networks (DLNN) is proposed to decouple and denoise the integrated detection to accurately extract the magnetic anomaly of single pipeline.
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Non-Contact Geomagnetic Detection Using Improved Complete Ensemble Empirical Mode Decomposition with Adaptive Noise and Teager Energy Operator
TL;DR: In this article, a detection method based on improved CEEMDAN (ICEEDMAN) and the Teager energy operator (TEO) is proposed to solve the non-contact geomagnetic detection of pipeline defects.
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A new technology for steel pipeline damage detecting without removing cladding
TL;DR: Based on the electromagnetic theory and magnetic field detection principle integrated with magnetic focusing technology, an array consisting of focusing detection probe and harmonic magnetic field system was designed in this paper to detect the damage of an in-service coated steel pipeline.