ABSTRACT
Event-driven data acquisition is used to capture information from fast transient phenomena typically requiring a high sampling speed. This is an important requirement in the ITER Neutral Beam Test Facility for the development of one of the heating systems of the ITER nuclear fusion experiment. The Red Pitaya board has been chosen for this project because of its versatility and low cost. Versatility is provided by the hosted Zynq System on Chip (SoC), which allows full configuration of the module architecture and the OpenSource architecture of Red Pitaya. Price is an important factor, because the boards are installed in a hostile environment where devices can be damaged by EMI and radiation. A flexible solution for event-driven data acquisition has been developed in the Zynq SoC and interfaced to the Linux-based embedded ARM processor. It has been successfully adopted in a variety of data acquisition applications in the test facility.
ABSTRACT
Stable and uniform beams with low divergence are required in particle accelerators; therefore, beyond the accelerated current, measuring the beam current spatial uniformity and stability over time is necessary to assess the beam performance, since these parameters affect the perveance and thus the beam optics. For high-power beams operating with long pulses, it is convenient to directly measure these current parameters with a non-intercepting system due to the heat management requirement. Such a system needs to be capable of operating in a vacuum in the presence of strong electromagnetic fields and overvoltages, due to electrical breakdowns in the accelerator. Finally, the measure of the beam current needs to be efficiently integrated into a pulse file with the other relevant plant parameters to allow the data analyses required for beam optimization. This paper describes the development, design and commissioning of such a non-intercepting system, the so-called beamlet current monitor (BCM), aimed to directly measure the electric current of a particle beam. In particular, the layout of the system was adapted to the SPIDER experiment, the ion source (IS) prototype of the heating neutral beam injectors (HNB) for the ITER fusion reactor. The diagnostic is suitable to provide the electric current of five beamlets from DC up to 10 MHz.
Subject(s)
Data Analysis , Electricity , Electromagnetic Fields , Heart Rate , HeatingABSTRACT
One of the most important applications of sensors is feedback control, in which an algorithm is applied to data that are collected from sensors in order to drive system actuators and achieve the desired outputs of the target plant. One of the most challenging applications of this control is represented by magnetic confinement fusion, in which real-time systems are responsible for the confinement of plasma at a temperature of several million degrees within a toroidal container by means of strong electromagnetic fields. Due to the fast dynamics of the underlying physical phenomena, data that are collected from electromagnetic sensors must be processed in real time. In most applications, real-time systems are implemented in C++; however, Python applications are now becoming more and more widespread, which has raised potential interest in their applicability in real-time systems. In this study, a framework was set up to assess the applicability of Python in real-time systems. For this purpose, a reference operating system configuration was chosen, which was optimized for real time, together with a reference framework for real-time data management. Within this framework, the performance of modules that computed PID control and FFT transforms was compared for C++ and Python implementations, respectively. Despite the initial concerns about Python applicability in real-time systems, it was found that the worst-case execution time (WCET) could also be safely defined for modules that were implemented in Python, thereby confirming that they could be considered for real-time applications.
