Wujun Xie

AviChina Industry & Technology (China)

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Trends

Author Order

Document Type

Co-Authors

David Li

University of Strathclyde

Haochang Chen

Shanghai Jiao Tong University

Zhenya Zang

University of Strathclyde

Y. Wang

University of Strathclyde

Dong Xiao

Hubei Water Resources Research Institute

Yu Chen

University of Strathclyde

Yu Wang

Tsinghua University

Hui Li

China University of Petroleum, East China

Quan Wang

University of Strathclyde

Jun Li

Xinjiang Industry Technical College

Cooperative Institutions

University of Strathclyde

AviChina Industry & Technology (China)

University of Chinese Academy of Sciences

Tsinghua University

Xi'an Institute of Optics and Precision Mechanics

Chinese Academy of Sciences

Guangxi University

Fraunhofer Centre for Applied Photonics

Southern University of Science and Technology

Shenzhen University

Author Statistics

Papers

Citation

H-Index

i-10 index

Research Field

Dynamic fluorescence lifetime sensing with CMOS single-photon avalanche diode arrays and deep learning processors

Biomedical Optics Express (2021)

Dong Xiao Zhenya Zang Natakorn Sapermsap Quan Wang Wujun Xie

Measuring fluorescence lifetimes of fast-moving cells or particles have broad applications in biomedical sciences. This paper presents a dynamic fluorescence lifetime sensing (DFLS) system based on the time-correlated single-photon counting (TCSPC) principle. It integrates a CMOS 192 × 128 single-photon avalanche diode (SPAD) array, offering an enormous photon-counting throughput without pile-up effects. We also proposed a quantized convolutional neural network (QCNN) algorithm and designed a field-programmable gate array embedded processor for fluorescence lifetime determinations. The processor uses a simple architecture, showing unparallel advantages in accuracy, analysis speed, and power consumption. It can resolve fluorescence lifetimes against disturbing noise. We evaluated the DFLS system using fluorescence dyes and fluorophore-tagged microspheres. The system can effectively measure fluorescence lifetimes within a single exposure period of the SPAD sensor, paving the way for portable time-resolved devices and shows potential in various applications.

Single-photon avalanche diode

Photon Counting

Avalanche diode

Fluorescence-lifetime imaging microscopy

Gate array

10.1364/boe.425663

Cite

Citations (19)

Multichannel Time-to-Digital Converters With Automatic Calibration in Xilinx Zynq-7000 FPGA Devices

IEEE Transactions on Industrial Electronics (2021)

Y. Wang Wujun Xie Haochang Chen David Li

This article proposes a weighted histogram calibration method and an automatic calibration architecture to implement high-linearity time-to-digital converters (TDCs) in low-cost Advanced RSIC Machine (ARM)-based system-on-chips (SoCs). The proposed method significantly reduces the nonlinearity introduced by nonuniform bins. It offers automatic calibration without manual interventions using ARM processors. Besides, our design is cost-effective in hardware consumption. We implemented and evaluated a 16-channel TDC system in a low-cost Zynq-7000 ARM-based SoC, in which the programable logic is equivalent to a 28 nm Artix-7 FPGA. The proposed TDC offers a resolution of 9.83 ps with good uniformity, achieving an averaged

${\rm{DN}}{{\rm{L}}_{{\rm{pk}} - {\rm{pk}}}}$

of 0.38 LSB, and an averaged

${\rm{IN}}{{\rm{L}}_{{\rm{pk}} - {\rm{pk}}}}$

of 0.63 LSB.

10.1109/tie.2021.3111563

Cite

Citations (14)

Time-Frequency Characteristics of Parachute Gun Shockwave Based on VMD-HT

2022 7th International Conference on Communication, Image and Signal Processing (CCISP) (2023)

Jun Li Wujun Xie Hui Li Liyi Fang

During the ejection process of the fighter pilot, the parachute is shot out by the life-saving seat gun, which generates a shockwave that endangers human safety. In order to accurately and stably extract the time-frequency distribution characteristics, the shockwave signal is obtained through parachute gun shooting experiments, and features of the shockwave signal is extracted by using Variational mode decomposition and Hilbert transform methods (VMD-HT). VMD is a high sampling rate shockwave signal decomposition technique, which is suitable for analysing unsteady airborne parachute gun shooting shockwave signals. The HT method is used to accurately extract the relationship between time, instantaneous frequency and energy for the decomposed signal, and to obtain the marginal spectra. The analytic results show that the shockwave signal lasting 3ms has a significant energy concentration in the low frequency band of 0∽1kHz, which is important for the better protection of pilots.

SIGNAL (programming language)

10.1109/ccisp59915.2023.10355811

Cite

Citations (0)

Efficient Time-to-Digital Converters in 20 nm FPGAs With Wave Union Methods

IEEE Transactions on Industrial Electronics (2021)

Wujun Xie Haochang Chen David Li

The wave union (WU) method is a well-known method in time-to-digital converters (TDCs) and can improve TDC performances without consuming extra logic resources. However, an earlier study concluded that the WU method is not suitable for UltraScale field-programmable gate array (FPGA) devices, due to more severe bubble errors. This article proves otherwise and presents new strategies to pursue high-resolution TDCs in Xilinx UltraScale 20 nm FPGAs. Combining our new subtapped delay line (sub-TDL) architecture (effective in removing bubbles and zero-width bins) and the WU method, we found that the wave union method is still powerful in UltraScale devices. We also compared the proposed TDC with the TDCs combining the dual sampling structure and the sub-TDL technique. A binning method is introduced to improve the linearity. Moreover, we derived a formula of the total measurement uncertainties for a single-stage TDL-TDC to obtain its root-mean-square resolution. Compared with the previously published FPGA-TDCs, we presented (for the first time) much more detailed precision analysis for single-TDL TDCs.

Linearity

10.1109/tie.2021.3053905

Cite

Citations (34)

High-Resolution Time-to-Digital Converters (Tdcs) with a Bidirectional Encoder

SSRN Electronic Journal (2022)

Yu Wang Wujun Xie Haochang Chen David Li

A high-resolution time-to-digital converter (TDC) based on wave union (four-edge WU A), dual-sampling, and sub-TDL methods is proposed and implemented in a 16-nm Xilinx UltraScale+ field-programmable gate array (FPGA). We combine WU and dual-sampling techniques to achieve a high resolution. Besides, we use the sub-TDL method and the proposed bidirectional encoder to suppress bubbles and encode four-transition pseudo thermometer codes efficiently. Experimental results indicate the proposed TDC achieves a 0.4 ps resolution with a 450MHz sampling clock and a 3.06 ps RMS precision in the best-case scenario. These characteristics make this design suitable for particle physics, biomedical imaging (such as positron emission tomography, PET), and general-purpose scientific instruments.

10.2139/ssrn.4206839

Cite

Citations (0)

128-Channel High-Linearity Resolution-Adjustable Time-to-Digital Converters for LiDAR Applications: Software Predictions and Hardware Implementations

IEEE Transactions on Industrial Electronics (2021)

Wujun Xie Y. Wang Haochang Chen David Li

This article proposes a new calibration method, called the mixed-binning (MB) method, to pursue high-linearity time-to-digital converters (TDCs) for light detection and ranging applications. The proposed TDCs were developed using tapped delay-line (TDL) cells in field-programmable gate arrays (FPGAs). With the MB method, we implemented a resolution-adjustable TDC showing excellent linearity in Xilinx UltraScale FPGAs. We demonstrate a 128-channel TDC to show that the proposed method is cost-effective in logic resources. We also developed a software tool to predict the performances of TDL-based TDCs robustly. Results from both software analysis and hardware implementations are in good agreement and show that the proposed design has great potential for multichannel applications; the averaged

${{\bf DN}}{{{\bf L}}_{{\boldsymbol{pk}} - {\boldsymbol{pk}}}}$

and

${{\bf IN}}{{{\bf L}}_{{\boldsymbol{pk}} - {\boldsymbol{pk}}}}$

are close to or even less than 0.05 LSB in multichannel designs.

Linearity

Software implementation

Implementation

10.1109/tie.2021.3076708

Cite

Citations (22)

Spatial resolution improved fluorescence lifetime imaging via deep learning

Optics Express (2022)

Dong Xiao Zhenya Zang Wujun Xie Natakorn Sapermsap Yu Chen

We present a deep learning approach to obtain high-resolution (HR) fluorescence lifetime images from low-resolution (LR) images acquired from fluorescence lifetime imaging (FLIM) systems. We first proposed a theoretical method for training neural networks to generate massive semi-synthetic FLIM data with various cellular morphologies, a sizeable dynamic lifetime range, and complex decay components. We then developed a degrading model to obtain LR-HR pairs and created a hybrid neural network, the spatial resolution improved FLIM net (SRI-FLIMnet) to simultaneously estimate fluorescence lifetimes and realize the nonlinear transformation from LR to HR images. The evaluative results demonstrate SRI-FLIMnet's superior performance in reconstructing spatial information from limited pixel resolution. We also verified SRI-FLIMnet using experimental images of bacterial infected mouse raw macrophage cells. Results show that the proposed data generation method and SRI-FLIMnet efficiently achieve superior spatial resolution for FLIM applications. Our study provides a solution for fast obtaining HR FLIM images.

Fluorescence-lifetime imaging microscopy

10.1364/oe.451215

Cite

Citations (10)

Performance of Hearing Protectors in Ejection Seat Parachute Gun Firing

Lecture notes in mechanical engineering (2023)

Wujun Xie Liwu Min Jun Li Hui Li

Overpressure

10.1007/978-981-99-8861-7_6

Cite

Citations (0)

Fast Analysis of Time-Domain Fluorescence Lifetime Imaging via Extreme Learning Machine

Sensors (2022)

Zhenya Zang Dong Xiao Quan Wang Zinuo Li Wujun Xie

We present a fast and accurate analytical method for fluorescence lifetime imaging microscopy (FLIM), using the extreme learning machine (ELM). We used extensive metrics to evaluate ELM and existing algorithms. First, we compared these algorithms using synthetic datasets. The results indicate that ELM can obtain higher fidelity, even in low-photon conditions. Afterwards, we used ELM to retrieve lifetime components from human prostate cancer cells loaded with gold nanosensors, showing that ELM also outperforms the iterative fitting and non-fitting algorithms. By comparing ELM with a computational efficient neural network, ELM achieves comparable accuracy with less training and inference time. As there is no back-propagation process for ELM during the training phase, the training speed is much higher than existing neural network approaches. The proposed strategy is promising for edge computing with online training.

Extreme Learning Machine

10.3390/s22103758

Cite

Citations (12)

High-resolution time-to-digital converters (TDCs) with a bidirectional encoder

Measurement (2022)

Yu Wang Wujun Xie Haochang Chen David Li

Time-to-Digital Converter

10.1016/j.measurement.2022.112258

Cite

Citations (16)