论文标题
基于FPGA的实时图像操纵和2D-XRAR检测器的高级数据采集
FPGA Based Real-Time Image Manipulation and Advanced Data Acquisition For 2D-XRAY Detectors
论文作者
论文摘要
科学实验依赖于某种类型的测量结果,这些测量提供了所需的数据来提取瞄准的信息或结论。因此,数据生产和分析是任何科学实验应用的核心。传统上,光子源检测器开发的努力集中在检测前端的性质和性能上。在许多情况下,数据采集链和数据处理被视为检测器系统的互补组成部分,并在项目的后期添加。在大多数情况下,数据处理任务委托给CPU。因此,达到最小带宽要求,并在功能方面保持硬件相对简单。这也可以最大程度地减少设计工作,复杂性和实施成本。在过去几年中,这种方法正在发生变化,因为它不符合新的高性能探测器。 FPGA和GPU现在用于执行复杂的图像操纵任务,例如图像重建,图像旋转,累积,过滤,数据分析等。这释放了CPU以完成更简单的任务。本文的目的是将基于FPGA的图像操纵技术的实施以及ESRF数据采集平台的性能(称为RashPA)的性能呈现为在ESRF开发的SmartPix光子计数检测器的后端板。
Scientific experiments rely on some type of measurements that provides the required data to extract aimed information or conclusions. Data production and analysis are therefore essential components at the heart of any scientific experimental application. Traditionally, efforts on detector development for photon sources have focused on the properties and performance of the detection front-ends. In many cases, the data acquisition chain as well as data processing, are treated as a complementary component of the detector system and added at a late stage of the project. In most of the cases, data processing tasks are entrusted to CPUs; achieving thus the minimum bandwidth requirements and kept hardware relatively simple in term of functionalities. This also minimizes design effort, complexity and implementation cost. This approach is changing in the last years as it does not fit new high-performance detectors; FPGA and GPUs are now used to perform complex image manipulation tasks such as image reconstruction, image rotation, accumulation, filtering, data analysis and many others. This frees up CPUs for simpler tasks. The objective of this paper is to present both the implementation of real time FPGA-based image manipulation techniques, as well as, the performance of the ESRF data acquisition platform called RASHPA, into the back-end board of the SMARTPIX photon-counting detector developed at the ESRF.