scholarly journals Whisker sensor and transmission of the multiple sensor signals.

1988 ◽  
Vol 6 (2) ◽  
pp. 101-108 ◽  
Author(s):  
Shigeo HIROSE ◽  
Souichi INOUE ◽  
Kan YONEDA
Keyword(s):  
Sensor Signals ◽  
Multiple Sensor

The whisker sensor and the transmission of multiple sensor signals

1989 ◽  
Vol 4 (2) ◽  
pp. 105-117 ◽  
Author(s):  
Shigeo Hirose ◽  
Souichi Inoue ◽  
Kan Yoneda
Keyword(s):  
Sensor Signals ◽  
Multiple Sensor

Sensor Synthesis for Control of Manufacturing Processes

1992 ◽  
Vol 114 (2) ◽  
pp. 158-174 ◽  
Author(s):  
G. Chryssolouris ◽  
M. Domroese ◽  
P. Beaulieu
Keyword(s):  
The State ◽  
Process Models ◽  
State Variables ◽  
Test Bed ◽  
Control Approach ◽  
State Variable ◽  
Sensor Signals ◽  
Multiple Sensor ◽  
Sensor Information ◽  
Basic Approaches

When a human controls a manufacturing process he or she uses multiple senses to monitor the process. Similarly, one can consider a control approach where measurements of process variables are performed by several sensing devices which in turn feed their signals into process models. Each of these models contains mathematical expressions based on the physics of the process which relate the sensor signals to process state variables. The information provided by the process models should be synthesized in order to determine the best estimates for the state variables. In this paper two basic approaches to the synthesis of multiple sensor information are considered and compared. The first approach is to synthesize the state variable estimates determined by the different sensors and corresponding process models through a mechanism based on training such as a neural network. The second approach utilizes statistical criteria to estimate the best synthesized state variable estimate from the state variable estimates provided by the process models. As a “test bed” for studying the effectiveness of the above sensor synthesis approaches turning has been considered. The approaches are evaluated and compared for providing estimates of the state variable tool wear based on multiple sensor information. The robustness of each scheme with respect to noisy and inaccurate sensor information is investigated.

scholarly journals Pocketable Labs for Everyone: Synchronized Multi-Sensor Data Streaming and Recording on Smartphones with the Lab Streaming Layer

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8135
Author(s):  
Sarah Blum ◽  
Daniel Hölle ◽  
Martin Georg Bleichner ◽  
Stefan Debener
Keyword(s):  
Data Streams ◽  
Time Series Data ◽  
Sensor Data ◽  
Series Data ◽  
Personal Health ◽  
Data Streaming ◽  
Sensor Signals ◽  
Multiple Sensor ◽  
Android Applications ◽  
Smartphone Sensor

The streaming and recording of smartphone sensor signals is desirable for mHealth, telemedicine, environmental monitoring and other applications. Time series data gathered in these fields typically benefit from the time-synchronized integration of different sensor signals. However, solutions required for this synchronization are mostly available for stationary setups. We hope to contribute to the important emerging field of portable data acquisition by presenting open-source Android applications both for the synchronized streaming (Send-a) and recording (Record-a) of multiple sensor data streams. We validate the applications in terms of functionality, flexibility and precision in fully mobile setups and in hybrid setups combining mobile and desktop hardware. Our results show that the fully mobile solution is equivalent to well-established desktop versions. With the streaming application Send-a and the recording application Record-a, purely smartphone-based setups for mobile research and personal health settings can be realized on off-the-shelf Android devices.

High-power disk laser welding statuses monitoring based on analyses of multiple-sensor signals

2019 ◽  
Vol 41 ◽  
pp. 221-230 ◽  
Author(s):  
Yanxi Zhang ◽  
Nanfeng Zhang ◽  
Deyong You ◽  
Xiangdong Gao ◽  
Seiji Katayama
Keyword(s):  
Laser Welding ◽  
High Power ◽  
Disk Laser ◽  
Sensor Signals ◽  
Multiple Sensor

scholarly journals A Frequency Modulation-Based Taxel Array: A Bio-Inspired Architecture for Large-Scale Artificial Skin

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5112
Author(s):  
Tareq Assaf
Keyword(s):  
Frequency Modulation ◽  
Large Scale ◽  
Artificial Skin ◽  
Spatial Awareness ◽  
Large Area ◽  
Single Wire ◽  
Current Consumption ◽  
Sensor Signals ◽  
Multiple Sensor ◽  
Robotic Platforms

This work introduces an array prototype based on a Frequency Modulation (FM) encoding architecture to transfer multiple sensor signals on a single wire. The use case presented adopts Hall-effect sensors as an example to represent a much larger range of sensor types (e.g., proximity and temperature). This work aims to contribute to large area artificial skin systems which are a key element to enhance robotic platforms. Artificial skin will allow robotic platforms to have spatial awareness which will make interaction with objects and users safe. The FM-based architecture has been developed to address limitations in large-scale artificial skin scalability. Scalability issues include power requirements; number of wires needed; as well as frequency, density, and sensitivity bottlenecks. In this work, eight sensor signals are simultaneously acquired, transferred on a single wire and decoded in real-time. The overall taxel array current consumption is 36 mA. The work experimentally validates and demonstrates that different input signals can be effectively transferred using this approach minimizing wiring and power consumption of the taxel array. Four different tests using single as well as multiple stimuli are presented. Observations on performances, noise, and taxel array behaviour are reported. The results show that the taxel array is reliable and effective in detecting the applied stimuli.

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