A pragmatic data processing system for large resistive sensor arrays

Large resistive sensor arrays (RSAs) show great potential in tactile perception. However, the large number of sensors can result in great hardware overhead and bring difficulties for acquiring and processing mass data timely in transient measurement applications. This paper implements a field programmable gate array (FPGA)-based data processing system for a large RSA of 96 × 96, which shows good power consumption and high-speed wireless data update. For crosstalk-free measure, the zero potential method is improved with bus switches, leading to fewer operational amplifiers required and less negative power consumption. A real-time embedded data processing system is realized by FPGA for excellent parallel processing ability. A high-speed wireless transfer scheme with automatic regulated transfer size is proposed and realized by a wireless fidelity module, which allows timely data analysis at the remote end. Moreover, fault identification of RSAs fabricated by micro-electromechanical system technology is achieved. Tests carried out on a 32 × 32 RSA show that the total power consumption is 2209 mW, including 1261 mW of processors and 948 mW of readout circuits, corresponding to 2.15 mW/pixel. The total negative power consumption of 549 mW has been reduced by 50% compared with the zero potential method. The scanning speed is 400 fps, and the wireless transfer speed is up to 120 fps when the transceiver and receiver are 5 m apart.

Authors

Institutions

Publication Details

Journal
Review of Scientific Instruments
Published
2024-08-01
DOI
https://doi.org/10.1063/5.0212979
Citations
1
Primary Topic
Advanced Sensor and Energy Harvesting Materials
Type
article
Field-Weighted Citation Impact
0.18

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A pragmatic data processing system for large resistive sensor arrays

X. Sun, Min Zhang
1 citations
Review of Scientific Instruments
Advanced Sensor and Energy Harvesting Materials
0.18
article

A pragmatic data processing system for large resistive sensor arrays

X. Sun, Min Zhang
article en
1 citations

Abstract

Large resistive sensor arrays (RSAs) show great potential in tactile perception. However, the large number of sensors can result in great hardware overhead and bring difficulties for acquiring and processing mass data timely in transient measurement applications. This paper implements a field programmable gate array (FPGA)-based data processing system for a large RSA of 96 × 96, which shows good power consumption and high-speed wireless data update. For crosstalk-free measure, the zero potential method is improved with bus switches, leading to fewer operational amplifiers required and less negative power consumption. A real-time embedded data processing system is realized by FPGA for excellent parallel processing ability. A high-speed wireless transfer scheme with automatic regulated transfer size is proposed and realized by a wireless fidelity module, which allows timely data analysis at the remote end. Moreover, fault identification of RSAs fabricated by micro-electromechanical system technology is achieved. Tests carried out on a 32 × 32 RSA show that the total power consumption is 2209 mW, including 1261 mW of processors and 948 mW of readout circuits, corresponding to 2.15 mW/pixel. The total negative power consumption of 549 mW has been reduced by 50% compared with the zero potential method. The scanning speed is 400 fps, and the wireless transfer speed is up to 120 fps when the transceiver and receiver are 5 m apart.

Review of Scientific InstrumentsVol. 95(8)
University Town of Shenzhen (CN), China Coal Technology and Engineering Group Corp (China) (CN), Tsinghua University (CN)
Natural Science Foundation of Shenzhen City
Affordable and clean energy
Openalex Percentile: Top 53%
Advanced Sensor and Energy Harvesting Materials
0.18
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A pragmatic data processing system for large resistive sensor arrays — X. Sun, Min Zhang · Review of Scientific Instruments (2024) | TGRS Research Map | TGRS