@article {aPuig-Sitjes21, title = {Real-time detection of overloads on the plasma-facing components of Wendelstein 7-X}, journal = {Applied sciences (Basel)}, volume = {11}, year = {2021}, month = {12/2021}, chapter = {1}, issn = {2076-3417}, doi = {10.3390/app112411969}, url = {http://hdl.handle.net/2117/361558}, author = {Puig-Sitjes, A. and Jakubowski, M. and Naujoks, D. and Gao, Y. and Drewelow, P. and Niemann, H. and Felinger, J. and Casas, J. and Salembier, P. and Clemente, R.} } @conference {cPuig-Sitjes21, title = {Spatio-temporal Detection and Tracking of Thermal Events on the Plasma Facing Components of Wendelstein 7-X}, booktitle = {4th IAEA Technical Meeting on Fusion Data Processing, Validation and Analysis}, year = {2021}, month = {11/2021}, publisher = {iaea.org}, organization = {iaea.org}, address = {Shanghai (online)}, abstract = {
In steady-state fusion devices like Wendelstein 7-X (W7-X), the active control of heat loads is mandatory to attain long-plasma operation. An intelligent feedback control system that mitigates the risk of overheating is required to avoid a premature plasma termination by the safety system. To keep the plasma within the safe operational limits of the plasma facing components, the feedback control system must be informed of the ongoing thermal events and their evolution in time. Then it can take effectives countermeasures to prevent the thermal events from reaching a critical point. These countermeasures may include reducing the heating power, changing the strike-line position or inducing detachment. With reaction times of the order of a hundred milliseconds, a fully automated real-time image analysis algorithm is required.
In this work, we present a spatio-temporal algorithm to detect, classify and track the thermal events observed by the thermography diagnostic on the plasma facing components of W7-X. The system detects and distinguishes between strike-lines and isolated hot spots as well as leading edges. The segmentation of the strike-line is specially challenging at W7-X. As a 3-dimensional helically-shaped stellarator equipped with 10 island divertors, the strike-lines have a complex heat load distribution with a high-dynamic range. The use of morphological tools and, in particular, the use of the Max-tree transform allow us to segment the thermal events in a hierarchical way preserving the inclusion relationship between different events, like hot spots and leading edges embedded in the strike-line structure. The thermal events are segmented for each frame and tracked over time in order to forecast their temporal evolution and to evaluate their risk. To this end, a spatio-temporal graph is built and spatio-temporal connected components are used to track the thermal events across the sequence frames. The spatio-temporal components in the graph are used to label the events in the sequence preserving temporal coherence and minimizing discontinuities, solving splits and merges. Spatio-temporal descriptors are then generated for each event to assess their risk.
The algorithm was tested offline on the infrared data acquired during the last operation phase OP1.2 and the results are presented here. Further work will follow to accelerate the code with GPUs to reach real-time processing and be ready to protect the water-cooled plasma facing components in the forthcoming operation phase OP2.
Wendelstein 7-X (W7-X), the most advanced fusion experiment in the stellarator line, aims at demonstrating the feasibility of the stellarator concept as a future fusion power plant. It is planned to restart operation by the end of 2021 with a high heat flux divertor and water-cooled plasma facing components (PFCs) to demonstrate steady-state operation. With plasma energy limits starting at 1 GJ and gradually increasing to 18 GJ over several experimental campaigns, the PFCs have to be protected from overheating. For that, a fully autonomous system is required in order to prevent damage to the plasma facing components due to thermal events.
During the last experimental campaign, when W7-X was equipped with inertially cooled test divertor units, extensive experience was gained with the preliminary design of the thermal event detection system. By then, the system was not yet real-time capable and it was not fully automated, requiring manual supervision between discharges. This experience, however, allowed to prove the validity of some design concepts and to define the new strategy towards the protection of the machine in steady-state operation, when the system will be connected to the Interlock System and the feedback control.
In this work, the design of the real-time thermal event detection system for W7-X for steady-state operation is presented. The system is based on the thermography and video diagnostics to monitor the divertor units, the baffles, and the wall heat-shields and panels. It will be implemented on a real-time system and integrated in CoDaC{\textquoteright}s safety infrastructure. The system relies on computer vision and machine learning techniques to perform a spatio-temporal analysis to detect and classify the thermal events and to perform a risk evaluation. The results and the main conclusions drawn from the analysis of the data from the past campaign are reported.