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Wireless Sensor Networks Applications in UAV Helicopters and … talks/08 IDGA DC conf.pdf · 2017....

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Automation & Robotics Research Institute (ARRI) The University of Texas at Arlington F.L. Lewis Moncrief-O’Donnell Endowed Chair Head, Controls & Sensors Group Talk available online at http://ARRI.uta.edu/acs Wireless Sensor Networks Applications in UAV Helicopters and Intelligent Diagnosis
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  • Automation & Robotics Research Institute (ARRI)The University of Texas at Arlington

    F.L. LewisMoncrief-O’Donnell Endowed Chair

    Head, Controls & Sensors Group

    Talk available online at http://ARRI.uta.edu/acs

    Wireless Sensor Networks Applications in UAV Helicopters and Intelligent Diagnosis

  • John Wiley, New York, 2006 John Wiley, New York, 2003

  • Cooperative Networks for Trust, Decision, & ControlWarfighter Information Network-Tactical (WIN-T) Concept of OperationsUS Army Signal Center

    For warfighter:Extended sensory networkTrust verificationDecision fusion & assistanceControl over cooperating UAV & UGV

  • PDA

    BSC(Base Station

    Controller, Preprocessing)BST

    WirelessSensor

    Machine Monitoring

    Medical Monitoring

    Wireless SensorWireless

    Data Collection Networks

    Wireless(Wi-Fi 802.11 2.4GHz

    BlueToothCellular Network, -

    CDMA, GSM)

    Printer

    Wireland(Ethernet WLAN,

    Optical)

    Animal Monitoring

    Vehicle Monitoring

    Onlinemonitoring Server

    transmitter

    Any where, any time to access

    Notebook Cellular Phone PC

    Ship Monitoring

    Wireless Sensor Networks

    RovingHumanmonitor

    Data Distribution Network

    Management Center(Database large storage,

    analysis)Data Acquisition

    Network

  • ARRI Distributed Intelligence & Autonomy LabDIAL

    UnattendedGroundSensors

    SmallmobileSensor-Dan Popa

    Testbed containing MICA2 network (circle), Cricket network (triangle), Sentry robots, Garcia Robots & ARRI-bots

    Dr. Dan PopaMobile Robots

  • UGS-Xbow wireless sensor boards

    • Temperature, ambient light, acoustic sensors, accelerometer,and magnetometer, (can get GPS)

    • Each node has a microcontroller, programmable with a C-based operating system

    • Cricket motes have ultrasound rangefinders

    Environmental Monitoring & Secure Area Denial

  • Discrete Event Supervisory Control

    Objective:Develop new DE control algorithms for decision-

    making, supervision, & resource assignment

    Apply to manufacturing workcell control, battlefield C&C systems, & internetworkedsystems

    • Patent on Discrete Event Supervisory Controller • New DE Control Algorithms based on Matrices• Implemented on Intelligent Robotic Workcell• Implemented on Wireless Sensor Networks• Internet- Remote Site Control and Monitoring

    USA/Mexico Internetworked Control

    Man/Machine User Interface

    TexasTexas

    Intelligent Robot Workcell

    Fast programming of multiple missionsReal-time event responseDynamic assignment of shared resources

  • Programmable MissionsMission Programming and Execution

    Mission Programming for Distributed Networks`

    R1

    R2

    R3

    UGS1

    UGS2

    UGS3

    UGS4

    UGS5

  • Mission1-Task sequence

    Mission 1 completedy1output

    S2 takes measurementS2m1Task 11

    R1 takes measurementR1m1Task 10

    R1 deploys UGS2R1dS21Task 9

    R2 takes measurementR2m1Task 8

    R1 gores to UGS1R1gS11Task 7

    R1 listens for interruptsR1lis1Task 6

    R1 retrieves UGS2R1rS21Task 5

    R2 goes to location AR2gA1Task 4

    R1 goes to UGS2R1gS21Task 3

    UGS5 takes measurementS5m1Task 2

    UGS4 takes measurementS4m1Task 1

    UGS1 launches chemical alertu1Input 1

    Descriptionnotationmission1

    Mission 2-Task sequence

    Mission 2 completedy2output

    R1 docks the chargerR1dC2Task 5

    UGS3 takes measurementS3m2Task 4

    R1 charges UGS3R1cS32Task 3

    R1 goes to UGS3R1g S32Task 2

    UGS1 takes measurementS1m2Task 1

    UGS3 batteries are lowu2input

    DescriptionnotationMission2

    Fast Programming of Multiple Missions

  • DE Model State Equation:

    DDucrcv uFuFrFvFx +++=

    The Secret: multiply = AND & addition = OR

    Tasks complete

    Resources available

    Targets / parts in

    Command input

    Task sequencing matrix – by Mission Planner

    Resource assignment matrix – by Battlefield Leader

    Fire next tasks

    New Matrix Formulation for Supervisory Control

  • Discrete event controller

    T asksco m p le ted v c

    R u le-b ased rea l tim e con tro lle r

    Cu curv uFuFrFvFx ⊗⊕⊗⊕⊗⊕⊗=

    Job s ta rt lo g ic

    R esource re lease lo g ic

    W ireless Sensor

    N etw o rk

    . . .

    u c

    Se nsor ou tp ut u

    R esourcere leased rc

    S tart tasks v s

    S tart reso urcere lease rs

    O utp ut yM iss io n co m p le ted

    P la nt co m m a nds P la nt s ta tus

    D isp atch in g ru le s

    C o ntro ller state m o nito ring lo g ic

    xSv VS ⊗=

    xSr rS ⊗=

    xSy y ⊗= T ask co m p le te lo g ic

    User interface:Definition of missionPlanningResource allocationPriority rules

    U.S. Patent

    Sensor readings

    events

    commands

    Decision-making

  • Mission1-Task sequence

    Mission 1 completedy1output

    S2 takes measurementS2m1Task 11

    R1 takes measurementR1m1Task 10

    R1 deploys UGS2R1dS21Task 9

    R2 takes measurementR2m1Task 8

    R1 gores to UGS1R1gS11Task 7

    R1 listens for interruptsR1lis1Task 6

    R1 retrieves UGS2R1rS21Task 5

    R2 goes to location AR2gA1Task 4

    R1 goes to UGS2R1gS21Task 3

    UGS5 takes measurementS5m1Task 2

    UGS4 takes measurementS4m1Task 1

    UGS1 launches chemical alertu1Input 1

    Descriptionnotationmission1

    Mission 2-Task sequence

    Mission 2 completedy2output

    R1 docks the chargerR1dC2Task 5

    UGS3 takes measurementS3m2Task 4

    R1 charges UGS3R1cS32Task 3

    R1 goes to UGS3R1g S32Task 2

    UGS1 takes measurementS1m2Task 1

    UGS3 batteries are lowu2input

    DescriptionnotationMission2

    Fast Programming of Multiple Missions

  • Construct Task Sequencing Matrix Fv

    Part A job 1Part A job 2Part A job 3

    Part B job 1Part B job 2Part B job 3

    Par

    t A jo

    b 1

    Par

    t B jo

    b 1

    Par

    t A jo

    b 2

    Par

    t B jo

    b 2

    Par

    t A jo

    b 3

    Par

    t B jo

    b 3

    Nextjobs

    Prerequisitejobs

    Used by Steward in ManufacturingTask Sequencing

    Contains same informationas the Bill of Materials(BOM)

    Mission Planner

    Graphical User Interface

  • Construct Resource Requirements Matrix Fr

    Used by Kusiak in ManufacturingResource Assignment

    Contains informationabout available resources

    Nextjobs

    Prerequisiteresources

    Part A job 1Part A job 2Part A job 3

    Part B job 1Part B job 2Part B job 3

    Con

    veyo

    r 1C

    onve

    yor 3

    Fixt

    ure

    1

    Rob

    ot 1

    -IBM

    Rob

    ot 2

    -Pum

    aR

    obot

    3-A

    dept

    Battlefield Commander

    Graphical User Interface

  • ⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟

    ⎜⎜⎜⎜⎜⎜⎜⎜⎜⎜⎜⎜⎜

    =

    100000000000100000000000100000000000110000000000010000000000010000000000011000000000001100000000000

    19

    18

    17

    16

    15

    14

    13

    12

    11

    1

    xxxxxxxxx

    Fv

    ⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟⎟

    ⎜⎜⎜⎜⎜⎜⎜⎜⎜⎜⎜⎜⎜

    =

    000000000010000000000000000000000110000000000000000000111100000

    19

    18

    17

    16

    15

    14

    13

    12

    11

    1

    xxxxxxxxx

    Fr

    ⎟⎟⎟⎟⎟⎟⎟⎟

    ⎜⎜⎜⎜⎜⎜⎜⎜

    =

    100000100000100000100000100000

    26

    25

    24

    23

    22

    21

    2

    xxxxxx

    Fv

    ⎟⎟⎟⎟⎟⎟⎟⎟

    ⎜⎜⎜⎜⎜⎜⎜⎜

    =

    000000000000010010000000000000000010000100

    26

    25

    24

    23

    22

    21

    2

    xxxxxx

    Fr

    High Level Controller

    Dispatching rules

    To Generate uc

    RS232 RS232 RS232

    Wireless Network with Internet connection

    - -Rule Based Real Time Controller

    ucStart tasks/jobs

    Mission result

    Resource release

    Sensor output u

    Task completed v

    Resource released r

    Medium Level Tasks ControllersRobot 1

    Task 1 Task 1

    Robot 2

    Task 1

    Wireless sensors

    Task 1

    Robot 3

    RS232

    Pioneer arm

    Cybermotion robot

    Cybermotion robot

    Xbow sensors

    Environment

    Task1

    PC

    urv uFrFvFx ⊗⊕⊗⊕⊗=xSv VS ⊗=

    xSy y ⊗=xSr rS ⊗=

    Finite state machine for each agent

    UC-TDMA MAC protocol

    Supervisor control level A

    gent control levelN

    etwork control level

    Agents

    Mission 1 matrices

    Mission 2 matrices

    Events

  • Schematic Event Sequence for Mission Performance

  • LabVIEW Real-time Signaling & Processing

    CBM Database and real time Monitoring

    PDA access Failure Data from anytime and

    anywhere

    User Interface, Monitoring, & Decision AssistanceWireless Access over the Internet

  • Condition-Based MaintenanceMonitoring the System

    Wired SensorsWireless Sensors

    No long wiresRemote Monitoring

    Predicting Failures in the SystemUse of Features from Empirical Data

    Time Domain AnalysisSpectral Analysis

    Use of various techniques for Classification

    Fuzzy, Neural, etc.

    Prasanna Ballal

  • WSN for CBMFeatures:• Scalable and energy efficient wireless sensor

    network saves installation costs.

    • Continuous and real-time collection of sensor data

    • Low cost

    • Portable hardware processor with diagnostic and prognostic tools

  • The PHM/CBM Cycle

    MachineSensors

    Pre-Processing

    FeatureExtraction

    FaultClassification

    Predictionof Fault

    EvolutionData

    ScheduleRequired

    Maintenance

    Systems &Signal processing

    Diagnostics Prognostics MaintenanceScheduling

    Identify importantfeatures

    Fault Mode Analysis

    Machine legacy failure data

    Available resourcesRULMission due dates

    Required Background Studies

    CBMPHM

    SelectSensors!

    Systems Approach to Intelligent Diagnostics & Prognostics

    Dr. George Vachtsevanos http://icsl.gatech.edu/icsl

  • WSN and CBM

    Prognostic tools

    Turbine engine

    Enhanced prognostic results

    Base Station

    Base Station

    SN

    SN

    SNSN

    Feed Back

    Feed Back

    DataBase

    DataBase

    DisplayDisplay

    AnalysisAnalysis

    The network can be made very reliable and energy efficient using UCTDMA (Tiwari, Ballal, Lewis 2007)

  • Wireless Sensors

    Crossbow Mica2

    Microstrain SG-Link accelerometer

    McMiddleton Mote- built in-house at ARRI

  • Network Configuration Wizard

    Useful for making minor changes to node parameters

    Loads with Default Values for Parameters

    Install and Configure the WS Network in 1 hour

  • DSP- Data to Information

    Discrete Event - triggersAdvise, Decision Assistance, Alarm

    LabVIEW GUIs Developed

    Multiple Time Signal Display

    Analysis and FFT

    Decision-MakingDiagnosis & Prognosis Alarm Functions

  • Won U.S. Small Business Administration SBIR Tibbets Award

    ARRI SBIR Program

    Current SBIR DoE Small Business Innovation Research (SBIR) Contract, Phase I:

    PIs F.L. Lewis and Dr. Weijen Lee

    "Secure and Reliable Wireless Communication and Fault Diagnosis for Energy Control Systems,“

    From Dr. Chiman Kwan, SignalPro, Inc., 9 mo. contract.

    Prasanna Ballal

  • Electrical Faults Test-BedElectrical Fault Classification Test-Bed for Power Generators and

    Motors • Electrical partial discharge (PD) or corona discharge (CD) can result in dielectric breakdown of the

    electrical insulation and failure of switch-gear and motor windings.• Experience indicates that PD/CD occur years before failure, which leaves sufficient time to plan

    corrective maintenance to avoid equipment failure.

    Inductors to emulate winding fault Fault generator to emulate rotors

    Hall effect sensorWSN

    Dr. Weijen Lee

  • Mechanical Faults Test-BedMechanical Fault Monitoring for Power Generators and Motors Testbed

    Motor

    Fly Wheel

    WSN

    VibratingSensor

    Dr. Weijen Lee

  • Fault Features

    50 100 150 200 250 30010-4

    10-2

    100

    102

    Frequency(Hz)

    Am

    plitu

    de

    Wireless-Test data

    FaultlessSolid-10mHSolid-20mHSolid-30mHRes10-10mHRes10-20mHRes10-30mH

    30 40 50 60 70 80 90 100 110 120 130

    10-2

    10-1

    100

    PS

    D a

    mpl

    itude

    Freq no

    Electrical Test-Bed Mechanical Test-Bed

    Frequency Domain: Power Spectra

    Faults in Rotating Machinery Generally Appear in the FFT SIDEBANDS

  • Fault FeaturesTime Domain: Mean, Kurtosis, Skewness

  • Image from www.joker-usa.com (distributor of the Joker 2 helicopter platform)

    Communication Issues During Helo Aerobatic Flight

    •The orientation of the helicopters changes continuously

    •Antennas on the helicopters and on the ground station are not parallel

    •Fading

    Emanuel Stingu

  • Helicopter Control System Emanuel Stingu

  • Wireless communication systems: long-range & high-speed

    GPS

    Long Range14 mi

    WiFiHigh speed

  • Helicopter 1

    Helicopter 2

    Helicopter 3

    Ground Vehicle

    Ground station(laptop computer)

    Pilot 1(remote control)

    Pilot 2(remote control)

    Pilot 3(remote control) 900MHz long range, low speed

    2.4GHz high speed 802.11n network

    Radio links:

    Wireless Communication TopologyThe helicopters have two radio communication interfaces:• Backup- Long-range, low speed: Maxstream XTend radio transceiver

    900 MHz ISM band14 miles range with a 2.1dBi dipole antenna115,200 bps data ratepoint-to-point, point-to-multipoint, peer-to-peer and mesh topologies

    • Control- Short-range, high-speed, low latency: Intel Wireless WiFi Link 4965AGN

    2.4 GHz, 802.11n wireless network300 m rangeMIMO, diversity and three antennae support

  • GPSMagnetic compassAtm. pressure

    Long rangeRadio Transceiver

    Inertial unit

    Ultrasoundrange sensor

    Motor & rotor speedBatt. capacity

    Battery

    4 servomotors

    Motor speed controller

    Motor

    Rotor speed transducer

    Real Time & Computer

    Module

    802.11n antenna

    Placement of the system componentsThe electronic components added to the system must not affectthe center of gravity – aerobatic maneuver capability is desired

    GPS receiver and compass as far away as possible from the motor and the computer

    The long range radio transceiver has 1W transmit power – has to be far from the various sensors

    INU near the CG

    E. Stingu

  • 802.11n 2.4 GHz 5 dBi antennaTwo more to be installed

    Antennas on the helicopter body

  • 900 MHz 2.1 dBi dipole antenna(long-range comm.)

    GPS helical antennainside the box

    Antennas on the helicopter body

    The dipole and the helical antennas do not require a ground plane, which makes it easy to use them on the helicopter body

  • Elevation

    Azimuth

    During aerobatic flight, the antenna attached to the helicopter can become perpendicular to the antenna on the other end of the link (base station, remote control or another helicopter).

    Because the elevation pattern of the dipole is not uniform, depending of the orientation, it is possible for the received signal power to be as low as only 10% of the received power in normal conditions.

    For small distances, the received signal is usually strong enough and a configuration with one antenna will be able to handle all orientations.

    Issues regarding perpendicular TX and RX antennas

    Almost all the signal power is lost when the antennas are perpendicular

  • Using 3 antennas to overcome the change in helicopter orientation

    Extended Kalman Filter

    Helicopter system model

    Sensors on the helicopter: inertial unit, compass, GPS, pressure

    Measurementsky~

    )(tuInputs

    States)(ˆ tx Decide which antenna is the closest

    to the vertical

    Antenna switching module

    time

    Switch the antennas only when the communication protocol allows it

    (no RX / TX expected)

    As the helicopter rotates, it will switch antennas such that the active antenna is the closest to the vertical from all three.

  • RSSI

    RSSI

    RSSI

    Compare

    Antenna with thebest reception

    1

    x1

    xn-1

    xn

    1

    y1

    ym-1

    ym

    V W

    Neural net

    Extended Kalman Filter

    Helicopter system model

    Sensors on the helicopter: inertial unit, compass, GPS, pressure

    Measurementsky~

    )(tuInputs

    States)(ˆ tx Get the helicopter

    orientation

    ϕ

    θψ

    NN Training algorithm

    Using 3 receivers to determine how to choose the TX antennabased on the helicopter orientation

    Receive phase during communications

    Antenna selection signal

    A neural network learns which antenna is better to be used for each orientation of the helicopter by analyzing the RSSI signal for each transceiver.

  • The 802.11n wireless network

    • Intel 4965AGN mini PCI express wireless card• 802.11n standard – MIMO support already included• used for low-range, fast speed communication between helicoptersduring formation flight

  • Helix antenna for the GPS receiver

    • More uniform radiation pattern allows the helicopter to tilt and pitch

    • Problems appear for inverted flight

    The GPS receiver

  • Communication fault diagnosis

    Wireless card:

    Communication statistics from Linux

    Long-range transceiver:

    RSSI, ambient power, transmission retries

    Aerobatic flight

    Hover

    Automatic landing

    Fault analysis

    Communication errors Analyze Change behavior


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