Training Courses

Training Courses

This section focuses on sensors related training courses for students, post graduate students and professionals (researchers and engineers). It showcases some of the more recent calls for EuroTraining courses as well as new university courses. The section is open for submission.

Sorry, your browser doesn't support Java(tm).

Smart Sensor Systems' 01

(May 28 -31, 2001)

A four-day advanced engineering course organized by the Electronic Instrumentation Laboratory and the Electronics Laboratory, Delft University of Technology, The Netherlands. Lectures are given by top experts from universities and industries. Course will be taught in English. Each attendee will receive a certificate of attendance at the course.

Short description: recent developments in the field of smart sensor systems are reviewed. After a general overview and introduction system details are discussed, concerning: sensor principles, tandem transducers, smart analog interfaces, A/D conversion, busses and digital interfaces, DSP and microcontrollers. Also a systematic approach towards the design of smart sensor systems is presented. The lectures include case studies and hands-on demonstrations.

Contents of the course:

1. Smart Sensor Systems, Where and How to Apply

2. Concepts and principles of Smart Sensor Systems

3. Silicon sensors: an introduction

4. Integrated fluid sensor systems

5. Optical sensors in silicon

6. Smart temperature sensors

7. Thermal Sensors

8. Integrated Hall magnetic sensors

9. Capacitive Sensors and contactless potentiometers

10./11. Interface electronics and busses

12. Data Acquisition for Frequency-Time Domain Smart Sensors

13. Universal asynchronous sensor interfaces

14. Dynamic offset-cancellation techniques

15. Smart Sensor Systems for high-temperature applications

16. Experiences of a young company in smart sensors

Location: The course will be held at the Faculty of Information Technology and Systems of Delft University of Technology, Delft, The Netherland.

Data Acquisition and Signal Processing for Digital and Quasi-Digital

Smart Sensors and Transducers

Summary: The lectures cover advanced frequency-to-code conversion methods and signal processing algorithms for different kind of smart sensors and transducers from state-of-the-art up to design and applications. Digital, frequency, period, duty-cycle, time interval and pulse number output smart sensors, direct interfacing to microcontrollers and PC are considered. The special attention will be paid to the novel self-adopted methods with high accuracy and non-redundant conversion time for frequency-to-code conversion. The lecture will be illustrated by practical examples and PC demonstrations. Course duration can be varied from 20 up to 180 hours. It is intended for students, post graduate students and professionals (researchers and engineers) and can be given in English at any university or company on request.

Content:

Introduction. Smart sensor and microsystem definitions, digital and quasi-digital sensors and transducers. Advantages of frequency as informative parameter. Frequency sensor classification; types of frequency transducers: x(t) -> F(t); x(t) -> U(t) -> F(t); x(t) -> P(t) -> F(t).
Smart sensors for electrical and non-electrical, physical and chemical quantities. The tendencies and perspectives of its development.
Classification of methods for frequency (period, duty-cycle)-to-code conversion. Discrete counting methods: classical methods of measurement (frequency-to-code conversion): standard (direct) counting method and indirect counting method. Specified measuring range of frequencies, error change coefficient; advantages and disadvantages for each of the methods. Examples.
Frequency-to-code conversion errors: quantization error, reference error (frequency base or time base accuracy); calculation error, trigger error, internal noise error, input signal noise error (main equations, distribution laws; methods for component error reducing).
Combined method of measurement; the ways of improvement for metrological performances.
Interpolation method of frequency-to-code conversion.
Advanced methods of measurement: reciprocal (ratiometric, coincidence) counting method; M/T method; constant elapsed time (CET) method. Examples and determination of main metrological performances; main equations and timing diagrams.
Single- double-buffered and DMA methods: metrological performances and limitations.
Methods for frequency-to-code conversion based on the Fourier transformation
Method of dependent count (method with non-redundant time of measurement: main metrological performances, its advantages and preference among all known methods; examples: hardware, hardware-software, software.
Direct microcontroller interfacing to sensors with frequency, period, duty-cycle, time interval, pulse number output: a program-oriented approach; one- and multi-channel sensor interfacing.
Program-oriented methods of measurement. Definition, classification; examples; analysis of electronic components, applicable for program-oriented method of measurement (Intel, Atmel, PIC, Texas Instruments microcontrollers); distinctive features of the usage of functional-logical architecture of modern microcontrollers; processors algorithms. Optimized microcontroller core for metering applications; VHDL model of the microcontroller; CAD-tools library elements (microcontroller cores and voltage-to-frequency converters);
Specific error components in the program-oriented method: error of reference time interval edges shaping, interrupt response shift error and interrupt response delay error.
Design methodology for reusable software components of smart sensors.
Adaptation possibilities, adaptive speed increasing methods.
The correction methods for systematic errors.
Reference frequency and reference time interval accuracy; limit metrological performances of program-oriented methods of measurement.
Method with non-redundant reference frequency, its main advantages for low power applications; MSP430 microcontroller (Texas Instruments) based example.
Methods for two frequencies ratio measurement.
Data acquisition methods for multichannel frequency sensor systems: sensor systems with cyclical polling for each sensor; accelerated sensor cyclical polling. Sensor systems with simultaneous sensor polling.
Signal processing for quasi-digital smart sensors: frequency multiplication, dividing, adding, subtraction and scaling; wave shape of sensor’s output signal. Error of period extraction (trigger error); weight function averaging as advanced digital signal processing in smart sensors; noise reduction.
Virtual sensor instrumentation, measuring channel in smart sensors: the definition, examples.
Practical usage of advanced methods in smart sensors and microsystems: rotation speed sensors; microsystems for ABS; multifunctional smart sensors.
PC based demonstration of virtual instruments with frequency sensors; virtual thermometer on the basis of smart temperature sensor. Closing Remarks.

For more details please contact:

Dr. Sergey Y. Yurish,

IFSA Vice President,

Head of R&D Department of INCOTECH.

Tel: +380 322 97 16 74

Fax:+380 322 97 16 41

E-mail: syurish@mail.icmp.lviv.ua

Statistical Process Control in Semiconductor Sensors Industry

Summary: This course is based on the EUROPRACTICE course EP-OTHER-359 and includes information how to estimate the modern technological microelectronics processes of semiconductor sensors with the aim to find latent reserves of production and increase the yield. Such measures for improvement of the technological process can be realized without large resources. It is especially important for estimation and control in the expensive novel technological processes (MCMs, MEMS, microsystems, etc.). Real industry examples will be given. The course is structured as a theoretical and practical intensive course including the lectures and practical sessions. The practical sessions are based on the original software - Statistical Process Estimation and Control (SPEC) - PC based CAD tool.

Objective: The aim of this course is to give advanced training, expertise and knowledge in the original statistical methods for adequate modeling of microelectronics technological processes on the basis of the multidimensional passive information.

Who should attend: Process/manufacturing engineers, technologists, managers, experts, instructors, production operators and supervisors from large companies as well as from SMEs, involved in microelectronics component and system production, requiring practical and fundamental knowledge how to estimate and optimize production processes with aim to increase the yield. This course will be also helpful for PhD students.