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Wireless Measurement and Control - Opportunities for Diagnostics Process Metrics Inferential Measurements and Eliminating Oscillations

Wireless Measurement and Control - Opportunities for Diagnostics Process Metrics Inferential Measurements and Eliminating Oscillations

Presented by Greg McMillan on March 15, 2011.

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    Wireless Measurement and Control - AIChE New Orleans Wireless Measurement and Control - AIChE New Orleans Presentation Transcript

    • Wireless Measurement and Control - Opportunities for Diagnostics, Process Metrics, Inferential Measurements, and Eliminating Oscillations
      AIChE New Orleans Section Meeting March 15, 2011
    • Welcome
      Gregory K. McMillan
      Greg is a retired Senior Fellow from Solutia/Monsanto and an ISA Fellow. Greg was an adjunct professor in the Washington University Saint Louis Chemical Engineering Department 2001-2004. Presently, Greg contracts as a consultant in DeltaV R&D via CDI Process & Industrial. Greg received the ISA “Kermit Fischer Environmental” Award for pH control in 1991, the Control Magazine “Engineer of the Year” Award for the Process Industry in 1994, was inducted into the Control “Process Automation Hall of Fame” in 2001, was honored by InTech Magazine in 2003 as one of the most influential innovators in automation, and received the ISA Life Achievement Award in 2010. Greg is the author of numerous books on process control, his most recent being Advanced Temperature Measurement and Control. Greg has been the monthly “Control Talk” columnist for Control magazine since 2002. Greg’s expertise is available on the web site: http://www.modelingandcontrol.com/
    • Top Ten Things You Don’t Want to Hear on a Startup
      (10) You need the owner to be a little more patient (supplier expert).
      (9) Don’t bother with a checkout - just light it up! What is the worst that can happen?
      (8) We didn’t do any simulation or testing. We decided that would spoil the adventure.
      (7) I don’t understand. It fit fine on the drawing.
      (6) Cool - This is my first time in a real plant (supplier expert).
      (5) I tried to open the valve and nothing happened. Wait! The same valve on the other reactor just opened.
      (4) Should the Variable Frequency Drive smoke like that?
      (3) I don’t understand. I am sure I left all your tools and radios in a box right here.
      (2) The CEO is holding on a phone for you.
      (1) Boom!!! WHAT was that?!?!
      Source: “Final Word on Instrument Upgrade Projects”, Control Talk, Control, Dec 2010
      http://www.controlglobal.com/articles/2010/InstrumentProjects1012.html
    • ISA Automation Week - Oct 17-20
      Process Automation
      Hall of Fame Speakers
      Charlie Cutler
      Bela Liptak
      Russ Rhinehart
      Greg McMillan
      Terry Tolliver
    • Advances in Smart Measurements
      Technological advances in sensing element technology
      Integration of multiple measurements
      Compensation of application and installation effects
      Online device diagnostics
      Digital signals with embedded extensive user selected information
      Wireless communication
      The out of the box accuracy of modern industrial instrumentation has improved by an order
      of magnitude. Consider the most common measurement device, the differential pressure
      transmitter (DP). The 0.25% accuracy of an analog electronic DP has improved to 0.025%
      accuracy for a smart microprocessor based DP. Furthermore, the analog DP accuracy often
      deteriorated to 2% when it was moved from the nice bench top setting to service outdoors in
      a nasty process with all its non-ideal effects of installation, process, and ambient effects [1][16].
      A smart DP with its integrated compensation for non-ideal effects will stay close to its inherent
      0.025% accuracy. Additionally a smart DP takes 10 years to drift as much as the analog DP
      did in 1 year.
    • Smart Transmitter Auxiliary Variables
      The availability of auxiliary process variables in a smart wireless pH transmitter, provide early indicators of performance problems. The use of these variables by online data analytics tools could detect abnormal conditions and predict sensor life.
    • Smart Transmitter Diagnostic Messages
      “Fix Now” and “Fix Soon” alerts are provided along with common causes and recommended actions
    • Wireless Opportunities
      Wireless temperatures and differential pressures for packed absorber and distillation column hot spot and flow distribution analysis and control
      Wireless temperatures for finding the column control point with the largest and most symmetrical change in temperature with reflux/feed or steam/feed ratio
      Wireless temperatures for heat transfer coefficient metrics (fouling and frosting)
      Wireless temperatures and flows for measurement and control of reaction rate and crystallization rate from heat transfer (BTU/hr measurement and control)
      Wireless temperatures and differential pressures for fluidized bed reactor hot spot and flow distribution analysis and control
      Wireless temperatures and flows to debottleneck coolant systems
      Wireless pressures to debottleneck piping systems, monitor process filter operation, and track down the direction and source of pressure disturbances
      Wireless pressures to compute installed control valve characteristic (flow versus stroke) and variable speed drive installed characteristic (flow versus speed)
      Wireless instrumentation to increase the mobility, flexibility, and maintainability of lab and pilot plant experiments.
      Wireless pH and conductivity measurements for
      (1) Selecting the best sensor technology for a wide range of process conditions(2) Eliminating measurement noise(3) Predicting sensor demise(4) Developing process temperature compensation(5) Developing inferential measurements of process concentrations(6) Finding the optimum sensor location
      http://www.isa.org/InTechTemplate.cfm?template=/ContentManagement/ContentDisplay.cfm&ContentID=80886
    • WirelessHART Network Topology
      • Wireless Field Devices
      • Relatively simple - Obeys Network Manager
      • All devices are full-function (e.g., must route)
      • Adapters
      • Provide access to existing HART-enabled Field Devices
      • Fully Documented, well defined requirements
      • Gateway and Access Points
      • Allows access to WirelessHART Network from the Process Automation Network
      • Gateways can offer multiple Access Points for increased Bandwidth and Reliability
      • Caches measurement and control values
      • Directly Supports WirelessHART Adapters
      • Seamless access from existing HART Applications
      • Network Manager
      • Manages communication bandwidth and routing
      • Redundant Network Managers supported
      • Often embedded in Gateway
      • Critical to performance of the network
      • Handheld
      • Supports direct communication to field device
      • For security, one hop only communication
    • WirelessHART Features
      Wireless transmitters provide nonintrusive replacement and diagnostics
      Wireless transmitters automatically communicate alerts based on smart diagnostics without interrogation from an automated maintenance system
      Wireless transmitters eliminate the questions of wiring integrity and termination
      Wireless transmitters eliminate ground loops that are difficult to track down
      Network manager optimizes routing to maximize reliability and performance
      Network manager maximizes signal strength and battery life by minimizing the number of hops and preferably using routers and main (line) powered devices
      Network manager minimizes interference by channel hopping and blacklisting
      The standard WirelessHART capability of exception reporting via a resolution setting helps to increase battery life
      WirelessHART control solution, keeps control execution times fast but a new value is communicated as scheduled only if the change in the measurement exceeds the resolution or the elapsed time exceeds the refresh time
      PIDPLUS and new communication rules can reduce communications by 96%
    • Broadley-James Corporation Bioreactor Setup
      • Hyclone 100 liter Single Use Bioreactor (SUB)
      • Rosemount WirelessHART gateway and transmitters for measurement and control of pH and temperature. (pressure monitored)
      • BioNet lab optimized control system based on DeltaV
    • Elimination of Ground Noise by Wireless pH
      Incredibly tight pH control via 0.001 pH wireless resolution
      setting still reduced the number of communications by 60%
      Temperature compensated wireless pH controlling at 6.9 pH set point
      Wired pH ground noise spike
    • Wireless Bioreactor Adaptive pH Loop Test
    • University of Texas Pilot Plant for CO2 Research
      • The Separations Research Program was established at the J.J. Pickle Research Campus in 1984
      • This cooperative industry/university program performs fundamental research of interest to chemical, biotechnological, petroleum refining, gas processing, pharmaceutical, and food companies.
      • CO2 removal from stack gas is a focus project for which WirelessHART transmitters are being installed
    • Wireless Conductivity and pH Lab Setup
      In the UT lab that supports the pilot plant, solvent concentration and loading were varied and the conductivity and pH were wirelessly communicated to the DCS in the control room
    • Effect of Ions on Conductivity
      Conductivity measures the concentration and mobility of ions. Plots of conductivity versus ion concentration will increase from zero concentration to a maximum as the number of ions in solution increases. The conductivity then falls off to the right of the maximum as the ions get crowded and start to interact or associate (group) reducing the ion mobility.
    • 40 oC
      Conductivity (milliSiemens/cm)
      30 oC
      20 oC
      Effect of Solvent on Conductivity
      Conductivity in the operating range of 25% to 30% by weight solvent is relatively unaffected by solvent concentration
    • Conductivity (milliSiemens/cm)
      40 oC
      30 oC
      20 oC
      Effect of CO2 Load on Conductivity
      Conductivity shows good sensitivity to CO2 loading that can be fitted by a straight line whose slope depends upon temperature above 30 oC
    • Effect of Solvent on pH
      pH measures the activity of the hydrogen ion, which is the ion concentration multiplied by an activity coefficient. An increase in solvent concentration increases the pH by a decrease in the activity coefficient and a decrease in the ion concentration from a decrease per the water dissociation constant.
      pH is also affected by CO2 weight percent since pH changes with the concentration of carbonic acid.
      Density measurements by Micromotion meters provide an accurate inference of CO2 weight percent.
    • Effect of MEA Solvent on pH
    • Effect of PZ Solvent on pH
    • +
      +
      Elapsed
      Time
      +
      +
      Elapsed
      Time
      Enhanced PID Algorithm for Wireless (PIDPlus)
      • PID integral mode is restructured to provide integral action to match the process response in the elapsed time (reset time set equal to process time constant)
      • PID derivative mode is modified to compute a rate of change over the elapsed time from the last new measurement value
      • PID reset and rate action are only computed when there is a new value
      • If transmitter damping is set to make noise amplitude less than sensitivity limit, valve packing and battery life is dramatically improved
      • Enhancement compensates for measurement sample time suppressing oscillations and enabling a smooth recovery from a loss in communications further extending packing -battery life
      TD
      Kc
      TD
      Kc
      Link to PIDPlus White Paper
      http://www2.emersonprocess.com/siteadmincenter/PM%20DeltaV%20Documents/
      Whitepapers/WP_DeltaV%20PID%20Enhancements%20for%20Wireless.pdf
    • Flow Setpoint Response - PIDPlus vs. Traditional PID
      Enhanced PID
      Sensor PV
      Traditional PID
      Sensor PV
    • Flow Load Response - PIDPlus vs. Traditional PID
      Enhanced PID
      Sensor PV
      Traditional PID
      Sensor PV
    • Flow Failure Response - PIDPlus vs. Traditional PID
      Enhanced PID
      Sensor PV
      Traditional PID
      Sensor PV
    • pH Setpoint Response - PIDPlus vs. Traditional PID
      Enhanced PID
      Sensor PV
      Traditional PID
      Sensor PV
    • pH Load Response - PIDPlus vs. Traditional PID
      Enhanced PID
      Sensor PV
      Traditional PID
      Sensor PV
    • pH Failure Response - PIDPlus vs. Traditional PID
      Enhanced PID
      Sensor PV
      Traditional PID
      Sensor PV
    • PIDPlus Benefits Extend Far Beyond Wireless - 1
      The PID enhancement for wireless (PIDPlus) offers an improvement wherever there is an update time in the loop. In the broadest sense, an update time can range from seconds (wireless updates and valve or measurement sensitivity limits) to hours (failures in communication, valve, or measurement). Some of the sources of update time are:
      Wireless measurement default update rate for periodic reporting (default update rate)
      Wireless measurement trigger level for exception reporting (trigger level)
      Wireless communication failure
      Broken pH electrode glass or lead wires (failure point is about 7 pH)
      Large valve operating on upper part of installed characteristic (low sensitivity)
      Valve with backlash (deadband) and stick-slip (resolution and sensitivity limit)
      Operating at split range point (discontinuity of no response to abrupt response)
      Valve with solids, high temperature, or sticky fluid that causes plugging or seizing
      Plugged impulse lines
      Analyzer sample processing delay and analysis or multiplex cycle time
      Analyzer resolution and sensitivity limit
    • PIDPlus Benefits Extend Far Beyond Wireless - 2
      The PIDPlus executes when there a change in setpoint, feedforward, or remote output to provide an immediate reaction based on PID structure
      The improvement in control by the PIDPlus is most noticeable as the update time becomes much larger than the 63% process response time (defined in the white paper as the sum of the process deadtime and time constant). When the update time becomes 4 times larger than this 63% process response time that roughly corresponds to the 98% response time frequently cited in the literature, the feedforward and controller gains can be set to provide a complete correction for changes in the measurement and setpoint.
      Helps ignore inverse response and errors in feedforward timing
      Helps ignore discontinuity (e.g. steam shock) at split range point
      Helps extend packing life by reducing oscillations and hence valve travel
      Since the PIDPlus can be set to execute only upon a significant change in user valve position, the PIDPlus as a valve position controller offers less interaction and cycling for optimization of unit operations by increasing reactor feed, column feed or increasing refrigeration unit temperature, or decreasing compressor pressure till feed, vent, coolant, and/or steam, valves are at maximum good throttle position.
      Website entries on Enhanced PID Benefits
      http://www.modelingandcontrol.com/2010/08/wireless_pid_benefits_extend_t.html
      http://www.modelingandcontrol.com/2010/10/enhanced_pid_for_wireless_elim.html
      http://www.modelingandcontrol.com/2010/11/a_delay_of_any_sorts.html
    • Enhanced PID
      Traditional PID
      PID PV
      PID Output
      Limit Cycles from Valve Stick-Slip
      Enhanced PID Can Eliminate Valve Limit Cycles
    • Enhanced PID Can Maximize Production Rate
      ZC-3
      TC-3
      ZC-4
      <
      maximum
      production
      rate
      CTW
      vent
      CAS
      ZC-2
      PC-1
      condenser
      CAS
      FC-1
      <
      TT
      feed A
      FT
      PT
      CAS
      FC-2
      RC-1
      ratio
      CAS
      feed B
      TC-1
      TT
      FT
      ZC-1
      CAS
      coolant
      makeup
      TC-2
      Valve Position Controllers (VPC)
      ZC-1,2,3,4 are enhanced PID with
      directional output velocity limiting
      and position noise band set to reduce
      interactions and limit cycling
      TT
      reactor
      product
    • Self-Regulating Process Open Loop Response
      Response to change in controller output with controller in manual
      % Controlled Variable (CV)
      or
      % Controller Output (CO)
      CV
      Kp = DCV / DCO
      Self-regulating process gain (%/%)
      CO
      Maximum speed
      in 4 deadtimes
      is critical speed
      DCV
      0.63*DCV
      DCO
      Time (seconds)
      qo
      tp2
      to
      or
      observed
      total loop
      deadtime
      Self-regulating process
      open loop
      negative feedback time constant
    • Response to change in controller output with controller in manual
      % Controlled Variable (CV)
      or
      % Controller Output (CO)
      CV
      Ki = { [ CV2/ Dt2 ] - [ CV1/ Dt1 ] } / DCO
      Integrating process gain (%/sec/%)
      CO
      DCO
      ramp rate is
      DCV2/ Dt2
      ramp rate is
      DCV1 / Dt1
      Time (seconds)
      qo
      observed
      total loop
      deadtime
      Integrating Process Open Loop Response
      Maximum speed
      in 4 deadtimes
      is critical speed
      Wireless Trigger Level > noise
      Wireless
      Default
      Update
      Rate
    • t’
      t’
      o
      p2
      Runaway Process Open Loop Response
      Response to change in controller output with controller in manual
      % Controlled Variable (CV)
      or
      % Controller Output (CO)
      Kp = DCV / DCO
      Runaway process gain (%/%)
      Acceleration
      For safety reasons, tests are
      terminated after 4 deadtimes
      1.72*DCV
      Maximum speed
      in 4 deadtimes
      is critical speed
      DCV
      DCO
      Noise Band
      Time (seconds)
      q
      or
      observed
      total loop
      deadtime
      o
      runaway process
      open loop
      positive feedback time constant
    • Kc
      Ti
      Td
      Loop Block Diagram (First Order Approximation)
      Delay
      Gain
      Lag
      qL
      Delay <=> Dead Time
      Lag <=>Time Constant
      KL
      tL
      DV
      Load Upset
      Delay
      Delay
      Lag
      Lag
      Gain
      Lag
      Delay
      Gain
      qv
      tp1
      qp2
      tp2
      tv
      Kpv
      qp1
      Kmv
      MV
      Process
      Valve
      PV
      Hopefullytp2is the largest lag in the loop
      For integrating processes: Ki = Kmv * (Kpv / tp2 ) * Kcv
      100% / span
      CO
      %
      Local
      Set Point
      PID
      ½ of Wireless Default Update Rate
      %
      CV
      %
      Delay
      Lag
      Delay
      Lag
      Lag
      Gain
      tc1
      tm2
      qm2
      tm1
      qm1
      Kcv
      qc
      tc2
      Lag
      Delay
      Controller
      Measurement
      First Order Approximation: qo @ qv + qp1 + qp2 + qm1 + qm2 + qc + tv + tp1 + tm1 + tm2 + tc1 + tc2
      (set by automation system design for flow, pressure, level, speed, surge, and static mixer pH control)
    • Ultimate Limit to Loop Performance
      Peak error is proportional to the ratio of loop deadtime to 63% response time
      (Important to prevent SIS trips, relief device activation, surge prevention, and RCRA pH violations)
      Total loop deadtime
      that is often set by
      automation design
      ½ of Wireless Default Update Rate
      is additional deadtime
      Largest lag in loop
      that is ideally set by
      large process volume
      Integrated error is proportional to the ratio of loop deadtime squared to 63% response time
      (Important to minimize quantity of product off-spec and total energy and raw material use)
    • Practical Limit to Loop Performance
      Peak error decreases as the controller gain increases but is essentially the
      open loop error for systems when total deadtime >> process time constant
      Open loop error for
      fastest and largest
      load disturbance
      Integrated error decreases as the controller gain increases and reset time decreases
      but is essentially the open loop error multiplied by the reset time plus signal
      delays and lags for systems when total deadtime >> process time constant
      Rise time (time to reach a new setpoint) is inversely proportional to controller gain
    • Fastest Controller Tuning (reaction curve method*)
      * - Ziegler Nichols method closed loop modified
      to be more robust and less oscillatory
      For self-regulating processes:
      Near integrator (tp2 >> qo):
      Deadtime dominant (tp2 << qo):
      1.0 for Enhanced PID if Wireless Default
      Update Rate > Process Response Time !
      For integrating processes:
      For runaway processes:
      Near integrator (t’p2 >> qo):
      These tuning equations provide maximum
      disturbance rejection but will cause
      some overshoot of setpoint response
    • Nomenclature
      • DCV = change in controlled variable (%)
      • DCO = change in controller output (%)
      • Kc= controller gain (dimensionless)
      • Ki= integrating process gain (%/sec/% or 1/sec)
      • Kp= process gain (dimensionless) also known as open loop gain
      • DV = disturbance variable (engineering units)
      • MV = manipulated variable (engineering units)
      • PV = process variable (engineering units)
      • DSP = change in setpoint (engineering units)
      • SPff= setpoint feedforward (engineering units)
      • Dt = change in time (sec)
      • Dtx = execution or update time (sec)
      • qo = total loop dead time (sec)
      • tf = filter time constant or well mixed volume residence time (sec)
      • tm = measurement time constant (sec)
      • tp2 = primary (large) self-regulating process time constant (sec)
      • t’p2 = primary (large) runaway process time constant (sec)
      • tp1 = secondary (small) process time constant (sec)
      • Ti= integral (reset) time setting (sec/repeat)
      • Td= derivative (rate) time setting (sec)
      • Tr= rise time for setpoint change (sec)
      • to= oscillation period (sec)
      • l = Lambda (closed loop time constant or arrest time) (sec)
      • lf = Lambda factor (ratio of closed to open loop time constant or arrest time)