ece40275 - data acquisition systems victor kolesnichenko ucsd extension fall 2014

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ECE40275 - Data ECE40275 - Data Acquisition Systems Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

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Page 1: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

ECE40275 - Data Acquisition ECE40275 - Data Acquisition SystemsSystems

Victor KolesnichenkoUCSD Extension

Fall 2014

Page 2: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Course Objectives:• Provide students with the knowledge required to specify, design,

and implement a Data Acquisition System (DAS)• Learn common architecture of a Data Acquisition System and its

components• Apply basic principles of sampling and digitizing theory• Design a simple DAS based on a Cortex-type microcontroller. This

includes hardware and firmware design.• Collect and analyze data from the DAS• Evaluate “build versus buy” option

Grading and withdrawal policy – read Buy STM32F4-Discovery board from ST MicroelectronicBuy USB to USB To RS232 TTL UART PL2303HX Auto Converter from eBayThe main book: Data Conversion Handbook, Analog Devices, 2005, ISBN : 0750678410 http://hotfile.com/dl/19138498/ca230e6/0750678410.rar.html - does not work anymoreRoster Sheet – to [email protected], 858-500-6088

Page 3: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Prerequisites: Prerequisites: • Students must have a basic understanding of C programming,

circuit analysis, analog and digital electronics, and microprocessor-based design.

Audience:

• Instrumentation engineers / electronics engineers in manufacturing and process industries;

• Data Acquisition & Control (DA&C) system designers / integrators; • Control and Instrumentation Engineers;• Students taking Embedded Engineering courses; • Electrical, mechanical, software, and chemical engineers and

technicians wishing to understand the essentials of data acquisition.

Page 4: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Demo Board Selection• Criteria: price less than $50, easy

to add sensors and memory, several IDEs

• TI TMDX28027USB Piccolo ControlStick $39.00, now $40.5

• Microchip DM330011 - MPLAB Starter Kit for dsPIC DSC $59.98

• Futurlec dsPIC30F2010 Development Board $44.90

Page 5: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Demo Board Selection, 2

• FuturlecSTM32F103 Development Board

$39.90

Coridium Super-PRO board - $49.00 (LPC1756)

Page 6: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

STM32F4-Discovery

Page 7: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Features of STM32F4-Discovery

• STM32F407VGT6 microcontroller featuring 32-bit ARM Cortex-M4F core, 1 MB Flash, 192 KB RAM in an LQFP100 package

• On-board ST-LINK/V2 with selection mode switch to use the kit as a standalone ST-LINK/V2 (with SWD connector for programming and debugging)

• Board power supply: through USB bus or from an external 5 V supply voltage

• External application power supply: 3 V and 5 V• LIS302DL or LIS3DSH ST MEMS 3-axis accelerometer• MP45DT02, ST MEMS audio sensor, omni-directional

digital microphone• CS43L22, audio DAC with integrated class D speaker

driver

Page 8: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Features of STM32F4-Discovery, 2

• Eight LEDs:• LD1 (red/green) for USB communication• LD2 (red) for 3.3 V power on• Four user LEDs, LD3 (orange), LD4 (green), LD5 (red)

and LD6 (blue)• 2 USB OTG LEDs LD7 (green) VBus and LD8 (red)

over-current• Two push buttons (user and reset)• USB OTG FS with micro-AB connector• Extension header for all LQFP100 I/Os for quick

connection to prototyping board and easy probing• Price - $14.58 (Direct from STM)

Page 9: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Terminology• Accuracy - The extend to which a given

measurement agrees with the defined value.• Accuracy Class - The maximum allowable error of

measurement at reference conditions.• ADC - Analog-to-Digital Converter is a

device that converts a continuous quantity (usually – voltage) to discrete digital numbers.

• ANSI - American National Standards Institute is a nonprofit, privately funded membership organization that coordinates the development of U.S. voluntary national standards and represents the U.S. in international standards organizations. The institute promotes and facilitates the development and integrity of voluntary consensus standards and conformity assessment systems.

Page 10: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Terminology, 2

• ASCII - American Standard Code for Information Interchange

• ASIC - Application-Specific Integrated Circuit• b - Bit• B - Byte• bps - Bits per second• CMRR- Common-Mode Rejection Ratio• DAQ - Data Acquisition • DAS - Data Acquisition System• dB - decibel (?) (Graham Bell invented a

phone)• DIO - Digital Input/Output• DSP - Digital Signal Process(or/ing)

Page 11: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Terminology, 3

• EEPROM - Electrically Erasable Programmable ROM• ENOB - Effective Number Of Bits• Firmware - Software that is embedded in the

electronic device.• FRAM - Ferroelectric Random Access Memory• Giga - A prefix meaning 1,000,000,000. Example:

2.4GHz.• GPIB - General Purpose Interface Bus• GUI - Graphical User Interface• Hertz or Hz - Cycles per Second. The practical unit of

frequency measurement.• I/O - Input/Output

Page 12: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Terminology, 4

• I2C - Inter IC (Integrated Circuits) Communication

• IEC - International Electrotechnical Commission, a worldwide organization preparing and publishing international standards for electrical, electronic, and related technologies. The members of IEC have national committees in each country.

• kilo or k - the prefix meaning 1000. Use small letter k, for example, kV.

• LAN - Local Area Network. A network consisting of nodes that are confined within a localized area. For example, a floor of a building, or the building itself.

Page 13: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Terminology, 5

• LSB - least significant bit• Mega - A prefix (capital M) meaning

1,000,000. 10MW, for example.• Micro (u) - A prefix (small u) meaning

1/1,000,000. 100uA, for example.• Milli (m) - A prefix (small m) meaning 1/1000.

5 mA, for example.• N.E.C. - National Electric Code. A regulation

covering the electric wiring systems on the customer’s premises with regards to safety.

• PGA - Programmable Gain Amplifier• RMS - Root-Mean-Square• SCADA - Supervisory Control And Data Acquisition

Page 14: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Terminology, 6

• S/H - Sample-and-Hold• SNR - Signal-to-Noise Ratio• SPI - Serial Peripheral Interface.• USB - Universal Serial Bus – industry standard defining

physical connections, power supply, and protocol of communication between master and slave

• ZigBee - ZigBee™ is the standards-based wireless networking technology for reliable, secure, cost-effective, low-power monitoring and control solutions. ZigBee™ provides the network, security and application profile software layers for the IEEE 802.15.4 global wireless standard.

Page 15: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Google Search Results on Data Acquisition System

Page 16: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Google Search Results on Data Acquisition System, 2

Page 17: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Data Acquisition System – Definition from Wikipedia

• Data Acquisition is the process of sampling of real world physical conditions and conversion of the resulting samples into digital numeric values that can be manipulated by a computer.

The components of data acquisition systems include:- Sensors that convert physical parameters to electrical signals. - Signal conditioning circuitry to convert sensor signals into a form that can be converted to digital values. - Analog-to-digital converters, which convert conditioned sensor signals to digital values. - Communication channel for transmission data to a computer.

Page 18: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Data Logger (From Wikipedia)

• A data logger (also datalogger or data recorder) is an electronic device that records data over time or in relation to location either with a built in instrument or sensor or via external instruments and sensors. Increasingly, but not entirely, they are based on a digital processor (or computer). They generally are small, battery powered, portable, and equipped with a microprocessor, internal memory for data storage, and sensors. Some data loggers interface with a personal computer and utilize software to activate the data logger and view and analyze the collected data, while others have a local interface device (keypad, LCD) and can be used as a stand-alone device.

Page 19: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Applications of DAS:

– Automotive: Crash-, Drive-Tests (DAS or Logger?)– Aerospace: “black boxes” - Data ?– Industrial: AMI, SCADA, Monitoring…– Medical: Patient diagnostic, observation,

(including remote), etc…– Scientific Research– Semiconductors Testing– Transportation: traffic statistics, schedule

control, traffic violations…– Weather forecasting– Your examples:

Page 20: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Architecture of a Typical DAS/Data Logger

cers

Signal Conditioners

Communication Channel

Sensors/Transducers

Signal Conditioners

Analog to Digital Converters

Microcon

troller

Memory

Communication Channel

Other components – Firmware and Software

Page 21: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Sensors or Transducers• There is no agreement among scientists and engineers on this definition, for

example one well known states: Transducer: 1. A device that is intended to transform an electrical signal into acoustic, biological, chemical, electrical, magnetic, mechanical, optical, radiational, or thermal stimuli for the purpose of transmitting information. (Information in biological form??) 2. A device that is intended to transform energy in one form into energy in another form for the purpose of transmitting power. (Hydro-electro station??) Sensor: A device that is intended to transform acoustic, biological, chemical, electrical, magnetic, mechanical, optical, radiational, or thermal stimuli into an electrical signal for the purpose of transmitting information.

Rich Gorczyca:• “In a control system, sensors are on the input side and they sense specific

phenomena in the environment. Actuators are on the output side and they manipulate or adjust phenomena in the environment. Both sensors and actuators are transducers in that they convert one form of energy into another form. Sensors typically convert physical energy (??) into electrical energy (??). Actuators convert electrical energy into physical energy. A microphone is a sensor that converts sound waves into electrical signals. A speaker is an actuator that converts the electrical signals into sound waves. Both are transducers.”

Page 22: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Overview of Sensors/Transducers

• Sensors (give me your examples)• Transducers (piezoelectric mike or speaker,

electromechanical…- 2-way, photovoltiac, electrochemical…- 1-way)

• Gauges (pressure, vacuum, RPM…)• Detectors (photo, ion, alpha, beta, gamma, X-

Ray…)• Indicators: Test the pH of a substance by means

of the dye litmus (see also indicator )

Page 23: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Sensors from http://www.sensorsportal.com/HTML/Sensor.htm

• Optical sensors

• Chemical sensors

• Rotation speed sensors

• Temperature sensors

• Pressure sensors

• Gas sensors

• Nano-sensors

• Accelerometers

• Oxygen sensors

• Acoustic sensors

• pH sensors

• Torque sensors

• Level sensors

• Ultrasonic sensors

• Load Cells

• Vacuum sensors

• Magnetic sensors

• Viscosity sensors

• Mechanical sensors

• Wireless sensors

• Moisture sensors

• Yaw sensors

• Biosensors

• Position sensors

• Proximity sensors

• Displacement sensors

• Resonant sensors

• Flow sensors

• TEDS (Transducer Electronic Data Sheet) (IEEE 1451 plug-and-play) sensors

• Humidity sensors

• Tilt sensors

• Inclination sensors

Page 24: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Sensor(s) Selection

We will operate with the term “sensor” for our DAS.The sensor(s) selection is dictated by the requirements to

the DAS (MRD -> Functional Specs -> Hardware Requirements Specification):

• What physical phenomenon(s) to be measured? • What is the range of the parameter change? • What is the required accuracy of measurements?• Any requirements to (non)linearity (calibration)?• Speed of measurements (samples per second),• What type of interface does the sensor have to provide?• What is the price limit?

Page 25: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Sensors Deviations (from Wikipedia)• The sensitivity may in practice differ from the value specified. This is

called a sensitivity error, but the sensor is still linear. • Since the range of the output signal is always limited, the output signal

will eventually reach a minimum or maximum when the measured property exceeds the limits. The full scale range defines the maximum and minimum values of the measured property.

• If the output signal is not zero when the measured property is zero, the sensor has an offset or bias. This is defined as the output of the sensor at zero input.

• If the sensitivity is not constant over the range of the sensor, this is called nonlinearity. Usually this is defined by the amount the output differs from ideal behavior over the full range of the sensor, often noted as a percentage of the full range.

• If the deviation is caused by a rapid change of the measured property over time, there is a dynamic error. Often, this behavior is described with a bode plot showing sensitivity error and phase shift as function of the frequency of a periodic input signal.

• If the output signal slowly changes independent of the measured property, this is defined as drift (telecommunication).

Page 26: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Sensors Deviations (from Wikipedia), 2• Long term drift usually indicates a slow degradation of sensor properties

over a long period of time. • Noise is a random deviation of the signal that varies in time. • Hysteresis is an error caused by when the measured property reverses

direction, but there is some finite lag in time for the sensor to respond, creating a different offset error in one direction than in the other.

• If the sensor has a digital output, the output is essentially an approximation of the measured property. The approximation error is also called digitization error.

• If the signal is monitored digitally, limitation of the sampling frequency also can cause a dynamic error, or, if the variable or added noise changes periodically at a frequency near a multiple of the sampling rate, - it may induce aliasing errors.

• The sensor may to some extent be sensitive to properties other than the property being measured. For example, most sensors are influenced by the temperature of their environment.

• All these deviations can be classified as systematic errors or random errors. Systematic errors can sometimes be compensated for by means of some kind of calibration strategy. Noise is a random error that can be reduced by signal processing, such as filtering, usually at the expense of the dynamic behavior of the sensor.

Page 27: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Functional Requirements Specification for the Project Design• Data Acquisition System capable of logging and storing

data from two temperature sensors (inside and outside the building, for example)

• Samples are 8-bit long (what is the accuracy?)• Temperature range from 0 to 100F (what is the

resolution?)• Max number of records - >=10000 (how much memory?)• Each record must have a time stamp• Price of the DAS must not exceed $50.00• The DAS must be reprogrammable and reconfigurable

via RS-232• Data must be stored in non-volatile memory• The DAS must be able to work as a stand-alone unit

Page 28: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Temperature Sensors

• Semiconductor Diode (−2 mV/˚C at low constant current through the diode, needed additional circuitry)

• Integrated Circuit (analog or digital output)• RTD – Resistive Temperature Detector (carbon,

platinum layer on substrate): NTC, PTC (needed additional circuitry)

• Thermocouple - Junction of different metals or alloys (needed some methods of cold-junction compensation to adjust for varying temperature at the terminals and amplifiers)

Page 29: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Signal Conditioning• In most practical cases a proper interface

between a sensor and an ADC is required.• The goals of the interface is to provide the ADC

with:– Full-scale signal (voltage) corresponding to the

maximum of the measured parameter– Low-pass frequency filtering of the input signal equal

or lower than maximum sampling frequency of ADC– If necessary – differential and/or isolated from the

sensor signal– Phase correction – in case of simultaneous sampling

or S&H from different kinds of sensors (Wattmeter)– Linearization of sensor’s characteristic, if necessary

Page 30: ECE40275 - Data Acquisition Systems Victor Kolesnichenko UCSD Extension Fall 2014

Components of Signal Conditioners

• Operational Amplifiers (OpAmps)• Passive components:

– Resistors– Capacitors,– Inductors (warning),– Transformers,– Optoisolators.

• Example of R-C low-pass filter– Time Constant; error vs. time– Graphical Interpretation with an input step function