A modular and flexible data acquisition system for a cosmic rays detector network. (1st April 2022)

• Record Type: Journal Article
• Authors: Saito, G.T.; Leite, M.A.L.; Menegasso, R.; Kuriyama, M.K.; Munhoz, M.G.; de Paula, R.E.
• Is Part Of: Journal of instrumentation. Volume 17:Number 4(2022)
• Publication Date: 2022-04-01
• Subjects: Photon detectors for UV, visible and IR photons (solid-state) (PIN diodes, APDs, Si-PMTs, G-APDs, CCDs, EBCCDs, EMCCDs, CMOS imagers, etc) -- Scintillators, scintillation and light emission processes (solid, gas and liquid scintillators); Scientific apparatus and instruments -- Periodicals; 502.84
• DOI: 10.1088/1748-0221/17/04/C04026
• Languages: English
• ISSNs: 1748-0221

Abstract

Abstract: In this paper, we describe a modular data acquisition system developed as the foundation of a cosmic ray detector network. Each detector setup (henceforth referred as a station) is composed of an independent hardware device that can be controlled and read-out through the Internet. This device is designed to acquire and process the signal of up to eight different detector planes. Each of these detector planes uses plastic scintillator slabs that are optically coupled to silicon photomultipliers (SiPM). Within a single station, different geometries and plane orientations are possible using the same baseline design. The main readout is based on a programmable system-on-a-chip (PSoC), a flexible and re-configurable commodity hardware that is used to implement the trigger and timing logic. A Time to Digital Converter (TDC) is used to determine the precise timing of the event relative to a GPS timing signal and to estimate the signal amplitude through the Time-over-Threshold (ToT) method. An auxiliary set of sensors provide environmental information and station detector planes orientation that, together with other operation data, are periodically sent to a server using the MQTT protocol. Data is cached using an in-memory database for online monitoring and further persisted into a SQL database for offline analysis. The server framework is based in software application containers allowing easy replication of the server infrastructure.