Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Kaimin Yu"'
Publikováno v:
Micromachines, Vol 15, Iss 9, p 1098 (2024)
This study addresses the limitation of traditional non-destructive testing methods in real-time corrosion monitoring of pipe elbows by proposing the utilization of fiber Bragg grating (FBG) strain sensors, renowned for their resilience in harsh envir
Externí odkaz:
https://doaj.org/article/78406a52b84d4fbf8ffc95295634033f
Publikováno v:
Photonics, Vol 11, Iss 7, p 645 (2024)
Real-time monitoring of heartbeat signals using multimode fiber optic microvibration sensing technology is crucial for diagnosing cardiovascular diseases, but the heartbeat signals are very weak and susceptible to noise interference, leading to inacc
Externí odkaz:
https://doaj.org/article/98945dc938474bc5a95af4f4b9a821f4
Publikováno v:
Sensors, Vol 24, Iss 7, p 2057 (2024)
Batteries play a crucial role as energy storage devices across various industries. However, achieving high performance often comes at the cost of safety. Continuous monitoring is essential to ensure the safety and reliability of batteries. This paper
Externí odkaz:
https://doaj.org/article/0b762d61692b4d848f26fa3fb3ffeafb
Autor:
Yunfei Chen, Kaimin Yu, Minfeng Wu, Lei Feng, Yuanfang Zhang, Peibin Zhu, Wen Chen, Jianzhong Hao
Publikováno v:
Photonics, Vol 11, Iss 2, p 137 (2024)
The choice of wavelet decomposition layer (DL) not only affects the denoising quality of wavelet denoising (WD), but also limits the denoising efficiency, especially when dealing with real phase-sensitive optical time-domain reflectometry (φ-OTDR) s
Externí odkaz:
https://doaj.org/article/17d7b54bdaa847758566d5037f927f61
Publikováno v:
Photonics, Vol 10, Iss 5, p 529 (2023)
Non-local mean (NLM) can significantly improve the signal-to-noise ratio (SNR), but it inevitably reduces the spatial resolution of distributed optical fiber sensors (DFOS), which hinders its practical application and the improvement of DFOS performa
Externí odkaz:
https://doaj.org/article/b001dee31b2b402880e0a97da1d1da36
Autor:
Weimin Feng, Zheng Wei, Jinlong Song, Qiao Qin, Kaimin Yu, Guochao Li, Jiayu Zhang, Wei Wu, Yanchun Yan
Publikováno v:
Scientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
Abstract A novel Penicillium oxalicum strain YC-WM1, isolated from activated sludge, was found to be capable of completely degrading 100 mg/L of nicosulfuron within six days when incubated in GSM at 33 °C. Nicosulfuron degradation rates were affecte
Externí odkaz:
https://doaj.org/article/9db0ba40ea204167a9a69e7164343510
Publikováno v:
Sensors, Vol 18, Iss 7, p 2012 (2018)
Networked multiple sensors are used to solve the problem of maneuvering target tracking. To avoid the linearization of nonlinear dynamic functions, and to obtain more accurate estimates for maneuvering targets, a novel adaptive information-weighted c
Externí odkaz:
https://doaj.org/article/5b81c81afe6a452eb4f6034ab9355d8e
Publikováno v:
Measurement. 214:112775
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::31d88ea87728fe079f1630d2e311b729
https://doi.org/10.1016/j.measurement.2023.112775
https://doi.org/10.1016/j.measurement.2023.112775
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6f216891fe364ea3e4722ef946227dda
https://doi.org/10.2139/ssrn.4305430
https://doi.org/10.2139/ssrn.4305430
Autor:
Kaimin Yu, Wei Wu, Zheng Wei, Qiao Qin, Jinlong Song, Yanchun Yan, Jiayu Zhang, Weimin Feng, Guochao Li
Publikováno v:
Scientific Reports, Vol 7, Iss 1, Pp 1-11 (2017)
Scientific Reports
Scientific Reports
A novel Penicillium oxalicum strain YC-WM1, isolated from activated sludge, was found to be capable of completely degrading 100 mg/L of nicosulfuron within six days when incubated in GSM at 33 °C. Nicosulfuron degradation rates were affected by GSM
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f4bfa03c9debb1c11526daea3768fff2
https://doaj.org/article/9db0ba40ea204167a9a69e7164343510
https://doaj.org/article/9db0ba40ea204167a9a69e7164343510