Articles, Papers and
References |
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1. |
Ph.
A. Passeraub, P-A. Besse, A. Bayadroun,
E. Bernasconi, R.S. Popovic, First Integrated Inductive Proximity
Sensor with On-Chip CMOS Readout Circuit and Electrodeposited 1 mm Flat
Coil, In Proceedings of the 12th European Conference on Solid-State Transducers and the 9th
UK
Conference on Sensors and their Applications, Southampton, UK, 13-16
September 1998, EUROSENSORS XII, Ed. by N. M. White, Institute of Physics
Publishing Bristol and Philadelphia, Sensors Series, volume 1, pp.
575-578. |












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2. |
B.
Hok, M. Tallfors, G. Sandberg, A. Bluckert, A New Sensor for Indoor Air
Quality Control, In Proceedings of the 12th
European Conference on Solid-State Transducers and the 9th UK
Conference on Sensors and their Applications, Southampton, UK, 13-16
September 1998, EUROSENSORS XII, Ed. by N. M. White, Institute of Physics
Publishing Bristol and Philadelphia, Sensors Series, volume 2, pp.
1072-1075. |
3. |
R.
Hartinger, M. Irsiegler, H.-E. Endres, S. Drost, K. Rieblinger, G.
Ziegleder, Portable and Modular Electronic Nose for Olfactometric
Measurements, In Proceedings of the 12th
European Conference on Solid-State Transducers and the 9th UK
Conference on Sensors and their Applications, Southampton, UK, 13-16
September 1998, EUROSENSORS XII, Ed. by N. M. White, Institute of Physics
Publishing Bristol and Philadelphia, Sensors Series, volume 2, pp.
1111-1114. |
4. |
V.
Liberali, P. Malcovati, and F. Maloberti, Sigma-delta Modulation and
Bit-stream Processing for Sensor Interfaces, Proceedings
of Italian Conference on Sensors and Microsystems, Rome, Italy, pp.
369-373, 1996.
Abstract - The
sigma-delta technique is pretty convenient for realizing high performance
sensor interfaces. This technique, indeed, besides the conventional
benefits produced by oversampling, allows the straightforward
implementation of several simple linear and non linear processing
operations, useful in the correction of the non-idealities of low
frequency sensor signals. |
5. |
S.Jung,
C.Hierold, T.Scheiter, P.Werner von Basse, R.Thewes, K.Goser and W.Weber,
Intelligent CMOS Fingerprint Sensors, In Proceedings of the 10th
International Conference on Solid-State Sensors and Actuators (Transducers
'99), Sendai, Japan, 7-10 June, 1999, vol.2, pp.966-969. |
6. |
M.Hakozaki,
K.Nakamura and H.Shinoda, Telemetric Artificial Skin for Soft Robot,
In Proceedings of the 10th International Conference on Solid-State
Sensors and Actuators (Transducers '99), Sendai, Japan, 7-10 June, 1999,
vol.2, pp.1042-1045. |
7.
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Seung
S.Lee, Richard M.White, Piezoelectric Cantilever Voltage-to-frequency
Converter, Sensors and Actuators A71 (1998),153-157. |
8.
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G. Y.
Tian, Z. X. Zhao,
R. W. Baines, The Design of Frequency Output Sensors and their Flexible
Measuring System, XIV IMEKO WORLD CONGRESS, New measurements-challenges and vision,
Vol. VIII, Tampere, Finland, June 1997, pp. 94-100. |
9. |
A. Cichocki and R. Unbehauen: Switched-capacitor
Transducers with Digital or Duty-cycle Output Based on Pulse-width
Modulation Technique,
Int. Journal of Electronics, Vol. 71, no. 2, 1991, pp.
265-278.
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10. |
J.F. Creemer, F. Fruett, G.C.M. Meijer and P.J. French,
The Piezojunction Effect in Silicon Sensors and Circuits and its Relation to
Piezoresistance, IEEE Sensors J., Vol. 1, no.2, Aug. 2001, pp.98-108. |
11. |
Powner
E.T., Yalcinkaya F., From Basis Sensors to Intelligent Sensors:
Definitions and Examples, Sensor Review, Vol.15, No.4, 1995,
pp.19-22 |
12. |
Powner E.T., Yalcinkaya F., Intelligent
Sensors: Structure and System, Sensor Review, Vol.15, No.3, 1995,
pp.31-35. |
13. |
Prosser
S.J., Ernest D.D. Schmidt, Smart Sensors for Industrial Applications, Microelectronics
International, 16/2, 1999, pp.20-23
Abstract:
Gives a short history of "smart" in relation to the field of
instrumentation. Defines the boundaries and suggests that a smart
component should incorporate some combination of the elements of an
application system which includes some element of control, computation or decision
making. It should also enhance the functionality, performance or exit of
the end system. Presents a number of examples of smart functionality and
smart components and concludes that suppliers of sensors and actuators
will take a leading role in the smart revolution. |
14.
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Introduction to Sensor Terminology |
15.
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K. D. Wise, Sensor-Circuit Integration
and System Partitioning
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16.
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K.
Hejn, A. Krukowski, Insight into a Digital Sensor for Sigma - Delta
Modulator Investigation",
IEEE Instrumentation and Measurement Technology Conference (IMTC'94), Conference Record, Vol. 2, pp.660-663,
Hammamatsu, Shizuoka, Japan, 10-12 May
1994
Abstract
- Even an ideal SD modulator exhibits certain non-linear behavior. So, its comprehensive description has been both an absorbing and confusing task. Therefore simulation and measurement are key factors for a successful evaluation of the SD structure. This work is about high-quality decimation filters (digital sensors) for SD modulator investigations. They are based on the two-phase (two-branch) parallel structure incorporating recursive allpass filters which is particularly suitable for decimation by a factor of two. Moreover, the repeated use of a basic decimation stage
(BDS) makes this structure highly modular and well-fitted for silicon implementation. An important BDS with only three coefficients (1/8, 9/16 and -1/16) has been presented in detail. It was applied in the five stage decimator and can be implemented in CMOS technology. It achieves 20-bit processing accuracy for the passband of 20kHz with little design complexity and no cost penalties incurring in alternative approaches. The paper includes some design results with performance evaluation using fixed-point arithmetic. |
17.
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Fully Digital Signal Path Provides Unparalleled Accuracy for Capacitive Sensors
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18. 
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S.
Wolpin, Big Ideas for Small Devices
MicroElectroMechanical Systems (MEMS), 2002 |
19.
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J.
Vuori, Simple Method Measures Duty Cycle
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20.  |
E. Kolberg, A Microphone Frequency Sensor, Encoder,
The Newsletter of the Seattle Robotics Society
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21.
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Dave Harrold, Soft Sensors, Control
Engineering, Europe, June/July 2001, pp. 42-45. |
22.
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Choosing the Right Industrial Digital I/O Module for Your Digital Output
Sensor |
23.
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Sykulski, J. K. and Stoll, R. L. (1992) Finite element modelling of inductive sensors.
COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering 11(1):pp.
69-72 |
24.
|
Mike Botts, Sensor Web Enablement, An Open GIS Consortium
(OGC) White Paper |
25.
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Mayela Zamora,
Manus Henry and Christian Peter, Generation of Frequency Output for
Instrumentation Application Using Digital Hardware, Sensor Review,
Vol., 23, No.2, 2003, pp.143-149 |
26.
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Alan Melia,
Frequency and Time Measurement |
27.
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New Device Will Sense Through Concrete Walls |
28.
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Ed McConnell,
The Future of Virtual Instrumentation, Sensors Magazine, July 1997 |
29.
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Mark Clarkson,
Smart Sensors, Sensors Magazine,
May 1997 |
30.
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Muneeb Khalid,
Working at High Speed: Multimegahertz 16-Bit A/D Conversion, Sensors Magazine,
May 1998 |
31.
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Eric Jacobsen,
Creating a PWM Output Sensor Using a Field-Programmable Analog Array,
Sensors Magazine,
May 1998 |
32.
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David R. Crotzer,
Eric C. Cho, Multifunctional Sensors: A New Concept, Sensors Magazine,
May 1998 |
33.
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John R. Gilbert,
Stephen F. Bart, Enabling the Design and Use of MEMS Sensors, Sensors Magazine,
April 1998 |
34.
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Michael Cerna,
Mendy Ouzillou, Understanding Frequency Domain Measurements, Sensors Magazine,
July 1999 |
35.
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Ed Ramsden,
Embedded Microcontrollers, or Making Your Sensors Really Smart, Sensors Magazine,
June 1999 |
36.
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Wayne W. Manges, Glenn O.
Allgood, Stephen F. Smith, It's Time for Sensors to Go Wireless, Part 1: Technological Underpinnings,
Sensors Magazine, April 1999 |
37.
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Glenn O. Allgood, Wayne W.
Manges, Stephen F. Smith, It's Time for Sensors to Go Wireless, Part 2: Take a Good Technology
and Make It an Economic Success, Sensors Magazine, June 1999 |
38.
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Eric Jacobsen,
A Flexible Evaluation Tool for Sensor System ASICs, Sensors Magazine,
February 1999 |
39.
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Stephen Humpage,
A Short Guide to Measurement Uncertainty, Sensors Magazine,
October 1999 |
40.
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Bernard Dulmet, Design of
Frequency Output Resonant Piezoelectric Sensors, in Proceedings of 7th
International Conference on Laser and Fiber-Optical Networks Modeling (LFNM)
2005,15-17 September 2005, pp. 184- 188 |
41.
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Sandeep Kumar Vashist, A Review of Microcantilevers for Sensing
Applications, AZojono Journal of Nanotechnology Online, 2007
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42.
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Mustafa Ertunc Tat, Jon H. Van Gerpen ,
Biodiesel Blend Detection Using a Fuel Composition Sensor, Paper Number:
01-6052, ASAE Meeting Presentation |
43.
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Dentcho V. Ivanov, Advanced Sensors for
Multifunctional Applications, JOM-e, October 2000 |
44.
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Subhas C. Mukhopadhyay, Sensing and
Instrumentation for a low cost Intelligent Sensing System, in Proceedings
of SICE-ICASE International Joint Conference, Oct. 18-21, 2006 in Bexco,
Busan, Korea |
45.
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New Digital Sensor with Square Wave Output,
Diesel Progress, North American Edition, March 2007, p.94. |
46.
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Jack G. Ganssle, VCO Based Sensors, Embedded
Systems Programming, June 1991. |
47.
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Intelligent Sensing, Practicing Oil Analysis Magazine,
January 2008 |
48.
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S. Chatzandroulis, D. Tsoukalas, Capacitance to
Frequency Converter Suitable for Sensor Applications Using Telemetry,
Analog Integrated Circuits and Signal Processing, Vol. 27, No. 1-2,
April, 2001, pp.31-38 |
49.
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Pereira J. M.
D., Postolache O., Girao P. S., A
Self-Adaptable Method to Optimize the Performance of Frequency-To-Code
Conversion Based Measurement Systems, in Proceedings of IEEE
Conference on Intelligent Data Acquisition and Advanced Computing Systems:
Technology and Applications (IDAACS 2005), 5-7 September 2005, pp. 295-298.
Accuracy, error compensation and simplicity of
transducer's communication and interfacing are three important topics in the
design and development of any measurement system. Nowadays, there are a
substantial number of transducers and actuators that generate or receive,
respectively, frequency modulated signals. The main advantages associated with
frequency transducers include its high noise immunity, high output signal power,
wide dynamic range and simplicity of signal interfacing and coding [1-2]. The
frequency-to-digital conversion (FDC) is easily performed by any
microcontroller, or circuits based on commercial off-the- shelf (COTS)
components, without need of an analog-to-digital converter (ADC), and the same
easiness exists when frequency signals are required for actuators. Eliminating
the need of ADCs and DACs reduces the cost of instrumentation and measurement
systems and eliminates a large number of error sources associated with these
conversion devices. This paper is dedicated to FDC based measurement systems,
giving particular attention to calibration issues and self- adaptive measurement
capabilities that can be used to select a suitable conversion accuracy for a
given signal-to-noise ratio. Some simulation and experimental results for a
temperature and humidity measurement system will be included as application
examples. |
50.
 |
Dias Pereira J. M., Postolache O., Silva Girao P. A
Low-Cost Tide Measurement System for Water Quality Assessment, in
Proceedings of the IEEE Instrumentation and Measurement Technology Conference (IMTC 2006), 24-27
April 2006, pp.2226 - 2230.
Summary: This paper presents a low-cost tide
measurement system based on a set of two inclinometers. The inclination sensors
deliver a DC output voltage which varies linearly with the angle of its working
direction. Thus, with two inclinometers assembled in orthogonal directions, it
is possible to provide the tide direction and intensity. The tide measurement
system was developed for a stand alone operation and includes an RS-232
interface for communication purposes. However, in the present paper an
application for water quality assessment is considered and the presented system
also includes additional measuring channels, for temperature, electrical
conductivity, turbidity and pH measurements. All the measuring channels are
connected to a FieldPoint (FP-AI-100) analog input module that works under
FP-2000 control. The FP-2000 controller communicates through RS232 with the tide
measurement system whose conditioning circuit includes two voltage-to-frequency
converters and a universal frequency-to-digital converter (UFDC). Wi-Fi data
communication is also provided including an Ethernet-wireless to the FP-2000
Ethernet port. Realtime data processing is supported by a LabVIEW RT software
embedded in the FieldPoint controller. |
51.
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D. Ramírez Muñoz,
D. Moro Pérez, J.
Sánchez Moreno, S. Casans Berga, E. Castro Montero, Design
and Experimental Verification of a Smart Sensor to Measure the Energy and Power
Consumption in a One-phase AC Line, Measurement (in press)
Abstract: A mixed electronic system has
been designed to measure the active, apparent and reactive energies
delivered to a load in a single-phase AC voltage line. For this purpose a
smart sensor (ADE7753 from Analog Devices) was used. A magnetoresistance
sensor is used as a current transducer and it is constant current biased by
a generalized impedance converter. The magnetoresistance sensor technology
provides direct isolation from the mains voltage and ferrite cores are not
needed like Hall counterparts. All the measurements provided by the ADE7753
are read through the parallel port of the computer using a LabView
application, which will process and present the readings to the user. |
52.
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James Wiczer, Connectivity: Smart Sensors or Smart
Interfaces |
53.
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Lynn Linse, Sensor Trends: Sensor Data as a Distinct
Utility, Product Design & Development |
54.
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Creed Huddleston,
Designing intelligent sensors for use on the "Internet of Things" - Part 1,
EETimes Design, June 2010 |
55.
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Creed Huddleston,
Designing intelligent sensors for use on the "Internet of Things" - Part 2,
EETimes Design, June 2010
|
56.
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Charles J.
Murray, Smarter Sensors Could Add Intelligence to Everyday Products, Design
News, February 24, 2011
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57.
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Arsenia Chorti, Dimosthenis Karatzas, Neil M. White,
Chris J. Harris, Intelligent Sensors In Software: The Use Of Parametric Models
For Phase Noise Analysis, in Proceedings of the 4th International
Conference ICISIP' 2006, India, Bangalore, pp.191-196. |
58.
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Jay Esfandyari, Roberto De Nuccio, Gang Xu,
Solutions for MEMS Sensor Fusion, Electro IQ: the Portal for
Electronics Manufacturing |
59.
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Carolyn Mathas, Smart Sensors – Not Only
Intelligent, but Adaptable |